WO2021004610A1 - Biomarqueurs et procédés pour le traitement personnalisé d'un cancer du poumon à petites cellules au moyen d'inhibiteurs de kdm1a - Google Patents

Biomarqueurs et procédés pour le traitement personnalisé d'un cancer du poumon à petites cellules au moyen d'inhibiteurs de kdm1a Download PDF

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WO2021004610A1
WO2021004610A1 PCT/EP2019/068150 EP2019068150W WO2021004610A1 WO 2021004610 A1 WO2021004610 A1 WO 2021004610A1 EP 2019068150 W EP2019068150 W EP 2019068150W WO 2021004610 A1 WO2021004610 A1 WO 2021004610A1
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treatment
patient
ascl1
sox2
sample
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PCT/EP2019/068150
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English (en)
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Filippo CICERI
Natalia SACILOTTO
Serena LUNARDI
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Oryzon Genomics, S.A.
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Priority to CN201980100040.4A priority Critical patent/CN114341366A/zh
Priority to PCT/EP2019/068150 priority patent/WO2021004610A1/fr
Priority to JP2022500505A priority patent/JP2022546908A/ja
Priority to EP19735339.4A priority patent/EP3994280A1/fr
Publication of WO2021004610A1 publication Critical patent/WO2021004610A1/fr

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    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/106—Pharmacogenomics, i.e. genetic variability in individual responses to drugs and drug metabolism
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/158—Expression markers

Definitions

  • the present invention relates to biomarkers and methods for the personalized treatment of small cell lung cancer (SCLC) using KDM1A inhibitors.
  • SCLC small cell lung cancer
  • the invention provides methods to identify patients having SCLC that may benefit from treatment with KDM1 A inhibitors and methods for the treatment of such patients with KDM1A inhibitors.
  • Lysine Specific Demethylase 1 (LSD1 , also known as KDM1A) is a histone-modifying enzyme responsible for demethylation of the di-methyl histone 3 lysine 4 (H3K4me2) (Shi et al dislike Cell 2004).
  • KDM1A histone-modifying enzyme responsible for demethylation of the di-methyl histone 3 lysine 4 (H3K4me2) (Shi et al dislike Cell 2004).
  • KDM1A has been recognized as a target of interest for the development of new drugs to treat cancer, and several KDM1A inhibitors are currently in clinical trials in oncology.
  • KDM1 A inhibitors have been reported to be effective for the treatment of small cell lung cancer (SCLC). It has been shown that KDM1A inhibition reduces proliferation of SCLC cell lines in vitro and delays tumor growth in vivo in SCLC xenograft-bearing mice (Mohammad et al., 2015, Cancer Cell 28, 57-69).
  • SCLC small cell lung cancer
  • sensitivity to KDM1A inhibition is not a widespread feature of SCLC cells. This raises the need to develop methods of individualizing SCLC treatment with KDM1A inhibitors, and in particular to develop methods of patient selection that allow to identify those patients having SCLC that would benefit, or that would benefit the most, from receiving treatment with a KDM1A inhibitor.
  • the technical problem underlying the present invention is the provision of means and methods for identifying and treating patients having SCLC that are best suited for treatment with a KDM1A inhibitor.
  • the present invention provides means and methods for the personalized treatment of small cell lung cancer (SCLC) using KDM1A inhibitors.
  • SCLC small cell lung cancer
  • the present invention provides a method of identifying a patient having SCLC who is more likely to respond to a treatment comprising a KDM1A inhibitor, the method comprising measuring the level of ASCL1 and SOX2 in a sample from the patient prior to initiating the treatment comprising a KDM1A inhibitor.
  • the patient is identified as more likely to respond to a treatment comprising a KDM1A inhibitor when the level of each of ASCL1 and SOX2 in the sample surpasses a threshold.
  • the patient is identified as more likely to respond to a treatment comprising a KDM1A inhibitor compared to a patient having SCLC and having the level of ASCL1 and SOX2 measured in a sample from the patient prior to initiating the treatment comprising a KDM1A inhibitor when the level of each of ASCL1 and SOX2 in the sample does not surpassa threshold.
  • the latter patient (with the level of each of ASCL1 and SOX2 in the sample not surpassing a threshold) would vice versa be less likely to respond to a treatment comprising a KDM1A inhibitor.
  • This exemplary explanation applies to all aspects and uses provided herein that concern, encompass or comprise identifying a patient having SCLC who is more likely to respond/to be responsive to a treatment comprising a KDM1 A inhibitor or the like.
  • the method further comprises using the level of ASCL1 and SOX2 in the sample to generate a score for the sample, wherein the patient is identified as more likely to respond to a treatment comprising a KDM1A inhibitor when the score in the sample surpasses a threshold.
  • the invention provides a method of identifying a patient having SCLC who may benefit from a treatment comprising a KDM1A inhibitor, the method comprising measuring the level of ASCL1 and SOX2 in a sample from the patient prior to initiating the treatment comprising a KDM1A inhibitor.
  • the patient is identified as one who may benefit from a treatment comprising a KDM1 A inhibitor when the level of each of ASCL1 and SOX2 in the sample surpasses a threshold.
  • the method further comprises using the level of ASCL1 and SOX2 in the sample to generate a score for the sample, wherein the patient is identified as one who may benefit from a treatment comprising a KDM1A inhibitor when the score in the sample surpasses a threshold.
  • the present invention provides a method of predicting responsiveness of a patient having SCLC to a treatment comprising a KDM1A inhibitor, the method comprising measuring the level of ASCL1 and SOX2 in a sample from the patient prior to initiating the treatment comprising a KDM1A inhibitor.
  • the patient is identified as more likely to be responsive to a treatment comprising a KDM1A inhibitor when the level of each of ASCL1 and SOX2 in the sample surpasses a threshold.
  • the method further comprises using the level of ASCL1 and SOX2 in the sample to generate a score for the sample, wherein the patient is identified as more likely to be responsive to a treatment comprising a KDM1A inhibitor when the score in the sample surpasses a threshold.
  • the present invention provides a method of assessing the likelihood of a patient having SCLC to respond to a treatment comprising a KDM1A inhibitor, the method comprising measuring the level of ASCL1 and SOX2 in a sample from the patient prior to initiating the treatment comprising a KDM1A inhibitor.
  • the patient is identified as more likely to respond to a treatment comprising a KDM1A inhibitor when the level of each of ASCL1 and SOX2 in the sample surpasses a threshold.
  • the method further comprises using the level of ASCL1 and SOX2 in the sample to generate a score for the sample, wherein the patient is identified as more likely to respond to a treatment comprising a KDM1A inhibitor when the score in the sample surpasses a threshold.
  • the present invention provides a method of assessing the likelihood of a SCLC in a patient to respond to a treatment comprising a KDM1A inhibitor, the method comprising measuring the level of ASCL1 and SOX2 in a sample from a patient having SCLC prior to initiating the treatment comprising a KDM1A inhibitor.
  • the SCLC is identified as more likely to respond to a treatment comprising a KDM1 A inhibitor when the level of each of ASCL1 and SOX2 in the sample surpasses a threshold.
  • the method further comprises using the level of ASCL1 and SOX2 in the sample to generate a score for the sample, wherein the SCLC is identified as more likely to respond to a treatment comprising a KDM1A inhibitor when the score in the sample surpasses a threshold.
  • the invention provides a method of selecting a treatment for a patient having SCLC, the method comprising measuring the level of ASCL1 and SOX2 in a sample from the patient prior to initiating the treatment.
  • the method comprises providing a recommendation that the treatment selected for the patient comprises a KDM1A inhibitor when the level of each of ASCL1 and SOX2 in the sample surpasses a threshold.
  • the method further comprises using the level of ASCL1 and SOX2 in the sample to generate a score for the sample, and providing a recommendation that the treatment selected for the patient comprises a KDM1A inhibitor when the score in the sample surpasses a threshold.
  • the treatment to be selected for a patient having SCLC is a treatment comprising a KDM1A inhibitor, for example, when the level of each of ASCL1 and SOX2 in the sample surpasses a threshold or when the score in the sample surpasses a threshold.
  • a KDM1A inhibitor for example, when the level of each of ASCL1 and SOX2 in the sample surpasses a threshold or when the score in the sample surpasses a threshold.
  • other treatment options than treatment comprising a KDM1A inhibitor may be contemplated for the patients, e.g. treatment with drugs/therapeutic agents other than a KDM1 A inhibitor.
  • the invention provides a method of treating a patient having SCLC, the method comprising administering to the patient a therapeutically effective amount of a treatment comprising a KDM1A inhibitor, if the patient has been identified as more likely to respond to a treatment comprising a KDM1A inhibitor using a method according to any of the preceding aspects prior to initiating the treatment comprising a KDM1 A inhibitor.
  • the invention features a method of treating a patient having SCLC, the method comprising measuring the level of ASCL1 and SOX2 in a sample from the patient prior to initiating the treatment, identifying the patient as more likely to respond to a treatment comprising a KDM1 A inhibitor when the level of each of ASCL1 and SOX2 in the sample surpasses a threshold, and administering a therapeutically effective amount of a treatment comprising a KDM1A inhibitor to the patient if identified as more likely to respond.
  • the invention features a method of treating a patient having SCLC, the method comprising measuring the level of ASCL1 and SOX2 in a sample from the patient prior to initiating the treatment, using these levels to generate a score for the sample, identifying the patient as more likely to respond to a treatment comprising a KDM1A inhibitor when the score in the sample surpasses a threshold, and administering a therapeutically effective amount of a treatment comprising a KDM1 A inhibitor to the patient if identified as more likely to respond.
  • the invention provides a KDM1A inhibitor for use in treating a patient having SCLC, wherein the patient has been identified as more likely to respond to a treatment comprising a KDM1A inhibitor using a method according to any of the preceding aspects prior to initiating the treatment comprising a KDM1A inhibitor.
  • the invention provides a use of ASCL1 and SOX2 in a method of identifying a patient having SCLC who is more likely to respond to a treatment comprising a KDM1A inhibitor. ln a further aspect, the invention provides a use of ASCL1 and SOX2 in a method of assessing the likelihood of response of a patient having SCLC to a treatment comprising a KDM1A inhibitor.
  • the invention provides the use of one or more agents for measuring the level of ASCL1 and SOX2 in a method of identifying a patient having SCLC who is more likely to respond to a treatment comprising a KDM1A inhibitor.
  • the invention provides the use of one or more agents for measuring the level of ASCL1 and SOX2 in a method of assessing the likelihood of response of a patient having SCLC to a treatment comprising a KDM1A inhibitor.
  • the invention provides a use of ASCL1 and SOX2 for the manufacture of a diagnostic for identifying a patient having SCLC who is more likely to respond to a treatment comprising a KDM1A inhibitor.
  • the invention provides a use of ASCL1 and SOX2 for the manufacture of a diagnostic for assessing the likelihood of response of a patient having SCLC to a treatment comprising a KDM1A inhibitor.
  • the invention provides a kit for identifying a patient having SCLC who is more likely to respond to a treatment comprising a KDM1 A inhibitor, the kit comprising one or more agents for measuring the level of ASCL1 and SOX2 in a sample, and optionally, instructions for use.
  • the invention provides a kit for assessing the likelihood of response of a patient having SCLC to a treatment comprising a KDM1A inhibitor, the kit comprising one or more agents for measuring the level of ASCL1 and SOX2 in a sample, and optionally, instructions for use.
  • Fiqure 1 Dot plot representing expression of ASCL1 (Y-axis) and SOX2 (X-axis) measured by RNA-seq
  • Figure 2 Dot plot representing gene expression measured by qRT-PCR (absolute Cp values) of ASCL1 and
  • SOX2 for SCLC cell lines sensitive (grey dot), sensitive in part (empty square) or resistant (black diamond) to KDM1A inhibition as described in Example 3. Plotted values are means of independent experiments. The value in brackets has a Cp value above 40 for the expression of SOX2.
  • FIG. 1 Dot plot representing gene expression measured by microarray Affymetrix analysis (RMA values) of
  • ASCL1 and SOX2 in an extended panel of SCLC cell lines sensitive (grey dot), sensitive in part (empty square), or resistant (black triangle) to KDM1A inhibition, as described in Example 4.
  • Figure 4 ROC curves based on gene expression of ASCL1 (Figure 4A) and SOX2 ( Figure 4B) to discriminate
  • FIG. 5 Western Blot (WB) (Fig 5A) and quantification (Fig 5B) of ASCL1 and SOX2 protein levels in NCI-H146,
  • Fiqure 6 Correlation between protein and mRNA (CCLE Affymetrix) levels for SOX2 (Fig 6A) and ASCL1 (Fig 6A).
  • FIG. 7 Fluorescent immunohistochemistry stainings for SOX2 (Fig. 7A), ASCL1 (Fig. 7B) and negative control
  • DAPI DAPI (4',6- diamidino-2-phenylindole) is a fluorescent dye that strongly binds to A-T rich regions in DNA and stains the nuclei. Signal is not detected in negative control with secondary antibody only (AF546: Alexa Fluor 546).
  • Figure 8 Correlation between protein and mRNA (CCLE Affymetrix) levels for SOX2 (Fig 8A) and ASCL1 (Fig 8A).
  • Figure 9 Representative ASCL1 , SOX2 and their corresponding DAPI fluorescent immunohistochemistry images from SCLC PDX TMA are shown for each staining classification level 0, 1 , 2 and 3, as described in Example 5.3
  • Figure 10 Two-tailed Spearman correlation tests between RNASeq (Log2FPKM) and IF (visual score) datasets for SOX2 ( Figure 10A and 10B) and ASCL1 ( Figure 10C and 10D) with a 95% confidence interval are shown for two independent experiments (coefficients are specified at the bottom of each graph), as described in Example 5.3.
  • Figure 11 WB and Ponceau staining for ASCL1 and SOX2 in exosomal fraction according to Example 6.
  • ASCL1 was not detected in exosomes derived from NCI-H446 and NCI-H526 and SOX2 was not present in exosomes derived from NCI-H526.
  • Figure 12 WB (left) and Ponceau staining (right) for ASCL1 , SOX2 and CD151 (lung cancer-specific exosome marker) in both exosomes and the corresponding parental cells, according to Example 6.
  • ASCL1 , SOX2 and CD151 signals are significantly reduced or ablated in the exosomal fraction after treatment of NCI-H510A cells with 5mM GW4869 (exosome production inhibitor) for 48 hours, while expression of these proteins in cells is not affected, indicating detection of ASCL1 ,SOX2 and CD151 is exosome- specific.
  • pharmaceutically acceptable salts denotes salts which are not biologically or otherwise undesirable.
  • Pharmaceutically acceptable salts include both acid and base addition salts.
  • Pharmaceutically acceptable salts are well known in the art.
  • pharmaceutically acceptable acid addition salt denotes those pharmaceutically acceptable salts formed with inorganic acids such as hydrochloric acid, hydrobromic acid, sulfuric acid, nitric acid, carbonic acid, phosphoric acid, and organic acids selected from aliphatic, cycloaliphatic, aromatic, araliphatic, heterocyclic, carboxylic, and sulfonic classes of organic acids such as formic acid, acetic acid, propionic acid, glycolic acid, gluconic acid, lactic acid, pyruvic acid, oxalic acid, malic acid, maleic acid, maloneic acid, succinic acid, fumaric acid, tartaric acid, citric acid, aspartic acid, ascorbic acid, glutamic acid, anthranilic acid, benzoic acid, cinnamic acid, mandelic acid, embonic acid, phenylacetic acid, methanesulfonic acid, ethanesulfonic acid, p-toluene
  • pharmaceutically acceptable base addition salt denotes those pharmaceutically acceptable salts formed with an organic or inorganic base.
  • acceptable inorganic bases include sodium, potassium, ammonium, calcium, magnesium, iron, zinc, copper, manganese, and aluminum salts.
  • Salts derived from pharmaceutically acceptable organic nontoxic bases includes salts of primary, secondary, and tertiary amines, substituted amines including naturally occurring substituted amines, cyclic amines and basic ion exchange resins, such as isopropylamine, trimethylamine, diethylamine, triethylamine, tripropylamine, ethanolamine, 2- diethylaminoethanol, trimethamine, dicyclohexylamine, lysine, arginine, histidine, caffeine, procaine, hydrabamine, choline, betaine, ethylenediamine, glucosamine, methylglucamine, theobromine, purines, piperizine, piperidine, N- ethylpiperidine, and polyamine resins.
  • substituted amines including naturally occurring substituted amines, cyclic amines and basic ion exchange resins, such as isopropylamine, trimethylamine, diethylamine, trie
  • KDM1A inhibitor or“KDM1 Ai” are used interchangeably and as used herein means any compound that is capable of inhibiting KDM1A activity. Methods to determine KDM1A inhibitory activity are well known in the art. In preferred embodiments, the KDM1A inhibitor is a small molecule. Examples of KDM1A inhibitors are described in more detail elsewhere herein.
  • a“small molecule” refers to an organic compound with a molecular weight below 900 daltons, preferably below 500 daltons.
  • the molecular weight is the mass of a molecule and is calculated as the sum of the atomic weights of each constituent element multiplied by the number of atoms of that element in the molecular formula.
  • A“treatment comprising a KDM1A inhibitor” means any therapy or treatment regimen incorporating a KDM1A inhibitor, whether as a sole active pharmaceutical ingredient (API) or in combination with one or more additional APIs, like other anticancer agents.
  • Said treatment comprising a KDM1A inhibitor will typically be in the form of a pharmaceutical composition.
  • the treatment comprising a KDM1A inhibitor comprises one or more APIs in addition to the KDM1A inhibitor, they may be administered in the form of a single pharmaceutical composition incorporating all APIs, or else may be administered in the form of individual pharmaceutical compositions for each API (i.e. the KDM1A inhibitor and the one or more additional APIs), which may be administered by the same or different routes (e.g. one may be administered orally and the other one parenterally), and which may be administered simultaneously or sequentially.
  • composition e.g. a mixture or solution
  • pharmaceutically acceptable excipients e.g. a pharmaceutically acceptable excipient to be administered to a mammal, e.g. a human in need thereof.
  • pharmaceutically acceptable denotes an attribute of a material which is useful in preparing a pharmaceutical composition that is generally safe, non-toxic, and neither biologically nor otherwise undesirable and is acceptable for veterinary as well as human pharmaceutical use.
  • pharmaceutically acceptable excipient can be used interchangeably and denote any pharmaceutically acceptable ingredient in a pharmaceutical composition having no therapeutic activity and being non-toxic to the subject administered, such as disintegrators, binders, fillers, solvents, buffers, tonicity agents, stabilizers, antioxidants, surfactants, carriers, diluents or lubricants used in formulating pharmaceutical products.
  • therapeutically effective amount denotes an amount of a compound of the present invention that, when administered to a patient, (i) treats or prevents the particular disease, (ii) attenuates, ameliorates or eliminates one or more symptoms of the disease, or (iii) prevents or delays the onset of one or more symptoms of the disease.
  • the therapeutically effective amount will vary depending on the compound, the disease state being treated, the severity of the disease treated, the age and relative health of the patient, the route and form of administration, the judgment of the attending medical or veterinary practitioner, and other factors.
  • treating or“treatment” of a disease (e.g. SCLC) includes reversing, alleviating, or inhibiting the progress of the disease or one or more symptoms thereof.
  • A“patient” or“subject” may be used interchangeably, and means a mammal in need of treatment. Mammals include, but are not limited to primates (e.g., humans and non-human primates such as monkeys), domesticated animals (e.g., cows, sheep, cats, dogs, and horses) and laboratory animals (mice, rats, guinea pigs and the like).
  • the patient is a human. Intended to be included as a patient are any subjects involved in clinical research trials.
  • the patient may have been previously treated for example with other drugs and/or with any KDM1A inhibitor. In one aspect, the patient has not been previously treated with any KDM1A inhibitor.
  • the patient may be being treated with other drugs, particularly at the time of obtaining the sample, but shall not be being treated with any KDM1A inhibitor at the time of obtaining the sample for use in the methods according to the invention (i.e. the patient should not be treated concurrently with a KDM1A inhibitor at the time of obtaining the sample).
  • the patient shall not be being treated with any KDM1A inhibitor within a period of time prior to obtaining the sample, if biomarker levels could be still modulated by the (remaining) KDM1A inhibitor within said period of time (for example if the biomarker levels have not returned to the level before a previous treatment with (or administration of) a KDM1A inhibitor).
  • the patient shall not be being treated with any KDM1A inhibitor within two weeks, or more preferably within one month, prior to obtaining the sample.
  • the latter is to avoid that biomarker levels could be still modulated by the (remaining) KDM1A inhibitor.
  • biomarker or“marker” as used herein refers to a protein or polynucleotide, the expression or presence of which in or on a mammalian tissue or cell can be detected by standard methods (or methods disclosed herein) and which is associated with a mammalian cell’s or tissue’s sensitivity to treatment comprising a KDM1A inhibitor.
  • the biomarkers according to the invention are ASCL1 and SOX2,
  • measuring refers to experimentally determining the amount of biomarker in the sample, employing appropriate methods of detection as described elsewhere herein.
  • threshold refers to a predetermined value, line or a more complex n dimensional function that defines the frontier between two categories/subsets of a population, e.g. patients with SCLC more likely to respond to KDM1A inhibitor treatment vs. patients with SCLC less likely to respond to KDM1A inhibitor treatment.
  • different thresholds can apply to individual biomarker levels (i.e. each biomarker, ASCL1 and SOX2, has its respective threshold) or to a score derived from the levels of the biomarkers by application of a classification algorithm as described elsewhere herein. As the skilled person will appreciate, thresholds are established to optimally distinguish between samples of different categories.
  • Thresholds can be established according to methods known in the art. Typically, a threshold can be determined experimentally or theoretically using a training set of samples with known sensitivity or resistance to treatment with KDM1A inhibitors. Training samples can be e.g. SCLC cell lines, patient-derived xenografts (PDX) or human clinical samples with known sensitivity or resistance to treatment with a KDM1A inhibitor. A threshold can also be arbitrarily selected based upon existing experimental and/or clinical and/or regulatory requirements, as would be recognized by a person of ordinary skill in the art. Preferentially the threshold is established in order to obtain the optimal sensitivity and specificity according to the function of the test and the benefit/risk balance (clinical consequences of false positive and false negative).
  • the optimal sensitivity and specificity can be determined using a Receiver Operating Characteristic (ROC) curve based on experimental data, as shown in the appended Examples.
  • the threshold is a threshold value.
  • threshold values for the biomarkers are derived from the ASCL1 and SOX2 levels measured in one or more samples of patient-derived SCLC cells that are sensitive or resistant to treatment comprising a KDM1A inhibitor.
  • threshold values are derived from the ASCL1 and SOX2 levels measured in one or more samples of (human) patients that have responded or not responded to treatment comprising a KDM1A inhibitor.
  • the threshold values are derived from the ASCL1 and SOX2 levels measured in one or more samples obtained from patient derived xenograft models that have responded or not responded to treatment comprising a KDM1A inhibitor. In some embodiments, the threshold values are obtained from the mRNA levels of the biomarkers. In some embodiments, the threshold values are obtained from the protein levels of the biomarkers.
  • the term“score’’ as used herein refers to the output calculated from the biomarker levels measured in a sample by a classification algorithm.
  • the score will be/is compared to a threshold and used to decide whether a patient from which a sample is derived is more likely or less likely to respond to a treatment comprising a KDM1A inhibitor. For example, when the score surpasses a threshold, the patient is identified as more likely to respond to a treatment comprising a KDM1A inhibitor / the patient is identified that he/she may benefit from treatment comprising a KDM1A inhibitor.
  • A“classification algorithm” as used herein is a mathematical function that is used to calculate a score for a sample and evaluate (“classify”) which category the sample belongs to, i.e. if it surpasses a threshold.
  • Classification algorithms are well known in the art. Examples of classification algorithms include: linear classifiers, fisher's linear discriminant, linear Boolean classification, logistic regression, naive bayes classifier, perceptron, support vector machines, least squares support vector machines, quadratic classifiers, kernel estimation, k-nearest neighbor, decision trees, random forests, neural networks, learning vector quantization.
  • classification algorithm is a Boolean function (truth function).
  • Samples can be classified using the Boolean conjunction function A AND B, wherein A and B evaluate whether the level of each of the biomarkers (ASCL1 and S0X2) in the sample are above that biomarker’s respective threshold.
  • the Boolean conjunction function yields a score, typically represented by 1 (truth) when all criteria are complied with (for example if the level of each of the biomarkers (ASCL1 and S0X2) in the sample is above/surpasses that biomarker’s respective threshold(s)), or 0 (falsehood) when one (or both) of the criteria is not (for example if only one level or none level of each of the biomarkers (ASCL1 and S0X2) in the sample is above/surpasses that biomarker’s respective threshold(s)).
  • the threshold applied to the score generated by the Boolean algorithm to classify the sample is 0, i.e. samples surpassing this threshold (i.e. with score > 0 ) are classified as likely to respond to treatment comprising a KDM1A inhibitor / to benefit from treatment comprising a KDM1A inhibitor.
  • the classification algorithm is a Support Vector Machine (SVM).
  • SVM is used to perform a classification by mapping a training data set in space and constructing an N-dimensional hyperplane that optimally separates the sample data into two categories (e.g. sensitive and resistant to KDMIAi) and thus acts as a threshold function.
  • SVMs can perform a non-linear classification using the kernel trick, mapping the sample data into high-dimensional feature spaces. Using the scoring function of the trained SVM, new data are then mapped into that same space and predicted to belong to a category based on which side of the hyperplane they fall.
  • the performance of a classification algorithm can be further evaluated by comparing the classification predicted by the algorithm with experimental values and calculating true positives, false positives, true negatives, and false negatives as well as the sensitivity, specificity, etc and may optionally be subjected to multiple rounds of training using training samples of known responsiveness/resistance to KDMIAi in order to tune model parameters and/or optimise performance.
  • a biomarker level or score of a test sample (with unknown sensitivity to KDMIAi), e.g. a sample from a SCLC patient that is being considered for receiving a treatment comprising a KDMIAi, will surpass or cross a threshold when the comparison of the levels or score (as the case may be) of that test sample with the respective threshold classifies that sample in the category of samples known to be sensitive to KDMIAi.
  • the threshold is a threshold value
  • the biomarker level or score will surpass the threshold (threshold value) when the biomarker level or score is above its respective threshold value.
  • the comparison of the level of the biomarker or score in the sample with the respective threshold for the biomarker or score may be carried out mentally, manually or can be automatically carried out by a computer program.
  • sample as used herein in relation to a patient sample to be used in the methods according to the invention can be a tumor sample (e.g. a biopsy sample, such as a biopsy sample either from primary or metastatic SCLC lesions), a body fluid or a patient derived cell line, a PDX sample (“PDX” means a“patient-derived xenograft", i.e. a human tumor grown in mice) or (an)exosome(s).
  • PDX means a“patient-derived xenograft", i.e. a human tumor grown in mice) or (an)exosome(s).
  • the sample is rich in/enriched for tumor cells.
  • the sample from the patient to be used to practice the methods according to the present invention is to be obtained prior to initiating treatment with a KDM1A inhibitor (i.e.
  • the sample from the patient to be used in accordance with the methods according to the present invention is to not be obtained within two weeks, preferably one month, following previous treatment with (or administration of) a KDM1A inhibitor).
  • Biopsy samples can be obtained by well-known techniques and may be fresh or may be subjected to post- collection preparative and storage techniques (e.g.
  • Samples of body fluids can be obtained by well-known techniques and include samples of blood, sputum, bronchoalveolar lavage fluid or any other bodily secretion or derivative thereof that may contain SCLC cells. Separated cells may be obtained from the body fluids or the tissues or organs by separating techniques such as centrifugation or cell sorting.
  • the cell sample can, of course, be subjected to a variety of well-known post-collection preparative and storage techniques (e.g., nucleic acid and/or protein extraction, fixation, storage, freezing, ultrafiltration, concentration, evaporation, centrifugation, etc.) prior to assessing the level of the markers in the sample.
  • the sample in which the biomarker levels are measured is rich in / enriched for the presence of SCLC cells or for SCLC cell-derived vesicles (e.g. exosomes, etc).
  • SCLC cells can be isolated from sputum using methods described in the literature (Chest. 1992 Aug;102(2);372-4).
  • SCLC circulating tumor cells can be purified from blood by methods described in the literature (Peeters et al., Br J Cancer 2013 Apr 2; 108(6) : 1358-67 ; Hodgkinson et al., Nat Med. 2014 Aug;20(8):897- 903; Carter et al, Nat Med, 2017 Jan;23(1):114-119) and SCLC derived exosomes can be purified from blood by various methods described in the literature (Li et al.Jheranostics. 2017; 7(3): 789-804; Sandfeld-Paulsen et al.,J Thorac Oncol. 2016 Oct; 11(10): 1701 -10).
  • the biomarker levels can also be analyzed in a spatially defined area from the sample rich in SCLC cells, as may be determined e.g. by anatomopathologists using standard methods used in the field.
  • responsiveness to”, “responsive to”, “respond to”, “sensitivity to”, “sensitive to” and the like expressions in the context of a treatment comprising a KDM1A inhibitor mean that a patient having SCLC (or a sample, SCLC cell line, etc) shows a positive response to KDM1A inhibition, i.e. to a treatment comprising a KDM1A inhibitor.
  • the terms“responsive to a treatment comprising a KDM1A inhibitor” and the like can be phrased as“responsive to a KDM1A inhibitor”,“responsive to KDM1A inhibition” and the like.
  • “a positive response to a treatment comprising a KDM1A inhibitor” or“a benefit from a treatment comprising a KDM1A inhibitor” can be or can include reversing, alleviating, or inhibiting the progress of the disease SCLC or one or more symptoms thereof.
  • the terms“more likely to respond” as used herein can mean“more responsive to” or, simply, “responsive to”.
  • identifying a patient” or“selecting a patient” may be used interchangeably and as used herein refers to using the information or data generated relating to the biomaker levels in a sample of a patient to identify or selecting the patient as more likely to respond to (or to benefit from) or less likely to respond to (or to benefit from) a treatment comprising a KDM1A inhibitor.
  • the information or data used or generated may be in any form, written, oral or electronic.
  • the herein provided methods and uses can include communicating the result, information or data to the patient and/or any person(s) involved in or in charge of the treatment of the patient, the treatment comprising a KDM1 A inhibitor.
  • using the information or data generated includes communicating, presenting, reporting, storing, sending, transferring, supplying, transmitting, dispensing, or combinations thereof.
  • communicating, presenting, reporting, storing, sending, transferring, supplying, transmitting, dispensing, or combinations thereof are performed by a computing device, analyzer unit or combination thereof.
  • communicating, presenting, reporting, storing, sending, transferring, supplying, transmitting, dispensing, or combinations thereof are performed by a laboratory or medical professional.
  • the information or data includes a comparison of the biomarker levels to a threshold.
  • the information or data includes an indication that the patient is more likely or less likely to respond to (or to benefit from) a treatment comprising a KDM1 A inhibitor.
  • the phrase“predicting responsiveness of a patient” as used herein refers to using the information or data generated relating to the biomaker levels in a sample of a patient to evaluate the likelihood that the patient will respond to a treatment comprising a KDM1 A inhibitor.
  • the information or data used or generated may be in any form, written, oral or electronic.
  • using the information or data generated includes communicating, presenting, reporting, storing, sending, transferring, supplying, transmitting, dispensing, or combinations thereof.
  • communicating, presenting, reporting, storing, sending, transferring, supplying, transmitting, dispensing, or combinations thereof are performed by a computing device, analyzer unit or combination thereof.
  • communicating, presenting, reporting, storing, sending, transferring, supplying, transmitting, dispensing, or combinations thereof are performed by a laboratory or medical professional.
  • the information or data includes a comparison of the biomarker levels to a threshold.
  • the information or data includes an indication that the patient is more likely or less likely to respond to a treatment comprising a KDM1A inhibitor.
  • the phrase“selecting a treatment’’ as used herein refers to using the information or data generated relating to the biomarker levels in a sample of a patient to identify or selecting a treatment (therapy) for a patient.
  • the treatment may comprise a KDM1A inhibitor.
  • the information or data used or generated may be in any form, written, oral or electronic.
  • using the information or data generated includes communicating, presenting, reporting, storing, sending, transferring, supplying, transmitting, dispensing, or combinations thereof.
  • communicating, presenting, reporting, storing, sending, transferring, supplying, transmitting, dispensing, or combinations thereof are performed by a computing device, analyzer unit or combination thereof.
  • communicating, presenting, reporting, storing, sending, transferring, supplying, transmitting, dispensing, or combinations thereof are performed by a laboratory or medical professional.
  • the information or data includes a comparison of biomarker levels to a threshold.
  • the information or data includes an indication that a treatment comprising a KDM1A inhibitor is suitable for the patient (i.e. the patient is likely to respond to said treatment).
  • recommending a treatment refers to using the information or data generated relating to the biomarker levels for proposing or selecting a treatment comprising a KDM1A inhibitor for a patient identified or selected as more or less likely to respond to the treatment comprising a KDM1A inhibitor.
  • the information or data used or generated may be in any form, written, oral or electronic.
  • using the information or data generated includes communicating, presenting, reporting, storing, sending, transferring, supplying, transmitting, dispensing, or combinations thereof.
  • communicating, presenting, reporting, storing, sending, transferring, supplying, transmitting, dispensing, or combinations thereof are performed by a computing device, analyzer unit or combination thereof.
  • communicating, presenting, reporting, storing, sending, transferring, supplying, transmitting, dispensing, or combinations thereof are performed by a laboratory or medical professional.
  • the information or data includes a comparison of the biomarker levels to a threshold.
  • the information or data includes an indication that a treatment comprising a KDM1 A inhibitor is suitable for the patient.
  • a“kit” is any manufacture (e.g. a package or container) comprising one or more agents for measuring the level of ASCL1 and SOX2, as described herein, the manufacture being promoted, distributed or sold as a unit for performing the methods of the present invention.
  • the present invention provides means and methods for identifying patients having SCLC with increased likelihood to respond to treatment with KDM1A inhibitors and thus that are best suited for treatment comprising a KDM1 A inhibitor, and therapeutic methods for treating those patients with KDM1A inhibitors.
  • the invention is based, at least in part, on the discovery that levels of ASCL1 and SOX2 can be used as biomarkers (e.g. predictive biomarkers) in methods of predicting likelihood to respond to treatment with KDM1A inhibitors. As documented herein and in the appended Examples, the inventors have found that high levels of both ASCL1 and SOX2 in SCLC cell lines correlate with responsiveness (sensitivity) of SCLC to KDM1A inhibitor therapy.
  • SCLC cell lines that express high levels of both ASCL1 and SOX2 are usually responsive (sensitive) to KDM1A inhibitors, whereas SCLC cell lines that exhibit low levels of either one or both of ASCL1 and SOX2 are usually resistant to KD 1A inhibition treatment.
  • ASCL1 and SOX2 levels can thus be used to stratify SCLC patients for treatment with KDM1A inhibitors, identifying those patients that are more likely to be responsive to treatment with a KDM1A inhibitor from those that are less likely to respond to KDM1A inhibition.
  • the methods according to the invention using ASLC1 and SOX2 are able to predict responsiveness of SCLC to KDM1A inhibition with high sensitivity and specificity, as shown in more detail in the appended Examples, which is remarkable in view of the reduced number of biomarkers used.
  • the methods according to the invention are amenable to measuring the biomarkers as either mRNA levels or protein levels, since a good correlation has been shown between their mRNA and protein expression levels, as shown in Example 5 using either SCLC cell lines or patient-derived samples like SCLC PDX samples.
  • the methods of the invention comprise measuring the level of ASCL1 and SOX2. These markers per se are known in the art and also described herein below.
  • nucleotide sequences and amino acid sequences of human ASCL1 and SOX2 are shown in SEQ ID NO: 1 to 4 herein.
  • the following table allocates the markers and the respective sequences:
  • the present invention provides a method of identifying a patient having SCLC who is more likely to respond to a treatment comprising a KDM1A inhibitor, the method comprising measuring the level of ASCL1 and SOX2 in a sample from the patient prior to initiating the treatment comprising a KDM1A inhibitor.
  • the patient is identified as more likely to respond to a treatment comprising a KDM1A inhibitor when the level of each of ASCL1 and SOX2 in the sample surpasses a threshold.
  • the method further comprises using the level of ASCL1 and SOX2 in the sample to generate a score for the sample, wherein the patient is identified as more likely to respond to a treatment comprising a KDM1A inhibitor when the score in the sample surpasses a threshold.
  • the invention provides a method of identifying a patient having SCLC who is more likely to respond to a treatment comprising a KDM1A inhibitor, the method comprising measuring the level of ASCL1 and SOX2 in a sample from the patient prior to initiating the treatment comprising a KDM1A inhibitor, wherein the patient is identified as more likely to respond to a treatment comprising a KD 1A inhibitor when the level of each of ASCL1 and SOX2 in the sample surpasses a threshold.
  • the invention provides a method of identifying a patient having SCLC who is more likely to respond to a treatment comprising a KDM1A inhibitor, the method comprising measuring the level of ASCL1 and SOX2 in a sample from the patient prior to initiating the treatment comprising a KDM1A inhibitor, and using the level of ASCL1 and SOX2 in the sample to generate a score for the sample, wherein the patient is identified as more likely to respond to a treatment comprising a KDM1 A inhibitor when the score in the sample surpasses a threshold.
  • the invention provides a method of identifying a patient having SCLC who may benefit from a treatment comprising a KDM1A inhibitor, the method comprising measuring the level of ASCL1 and SOX2 in a sample from the patient prior to initiating the treatment comprising a KDM1A inhibitor.
  • the patient is identified as one who may benefit from a treatment comprising a KDM1A inhibitor when the level of each of ASCL1 and SOX2 in the sample surpasses a threshold.
  • the method further comprises using the level of ASCL1 and SOX2 in the sample to generate a score for the sample, wherein the patient is identified as one who may benefit from a treatment comprising a KDM1A inhibitor when the score in the sample surpasses a threshold.
  • the invention features a method of identifying a patient having SCLC who may benefit from a treatment comprising a KDM1A inhibitor, the method comprising measuring the level of ASCL1 and SOX2 in a sample from the patient prior to initiating the treatment comprising a KDM1A inhibitor, wherein the patient is identified as one who may benefit from a treatment comprising a KDM1A inhibitor when the level of each of ASCL1 and SOX2 in the sample surpasses a threshold.
  • the invention features a method of identifying a patient having SCLC who may benefit from a treatment comprising a KDM1A inhibitor, the method comprising measuring the level of ASCL1 and SOX2 in a sample from the patient prior to initiating the treatment comprising a KDM1A inhibitor, and using the level of ASCL1 and SOX2 in the sample to generate a score for the sample, wherein the patient is identified as one who may benefit from a treatment comprising a KDM1A inhibitor when the score in the sample surpasses a threshold.
  • the present invention provides a method of predicting responsiveness of a patient having SCLC to a treatment comprising a KDM1A inhibitor, the method comprising measuring the level of ASCL1 and SOX2 in a sample from the patient prior to initiating the treatment comprising a KDM1A inhibitor.
  • the patient is identified as more likely to be responsive to a treatment comprising a KDM1A inhibitor when the level of each of ASCL1 and SOX2 in the sample surpasses a threshold.
  • the method further comprises using the level of ASCL1 and SOX2 in the sample to generate a score for the sample, wherein the patient is identified as more likely to be responsive to a treatment comprising a KDM1A inhibitor when the score in the sample surpasses a threshold.
  • the present invention provides a method of predicting responsiveness of a patient having SCLC to a treatment comprising a KDM1A inhibitor, the method comprising measuring the level of ASCL1 and SOX2 in a sample from the patient prior to initiating the treatment comprising a KDM1A inhibitor, wherein the patient is identified as more likely to be responsive to a treatment comprising a KDM1A inhibitor when the level of each of ASCL1 and SOX2 in the sample surpasses a threshold.
  • the present invention provides a method of predicting responsiveness of a patient having SCLC to a treatment comprising a KDM1 A inhibitor, the method comprising measuring the level of ASCL1 and SOX2 in a sample from the patient prior to initiating the treatment comprising a KDM1A inhibitor, and using the level of ASCL1 and SOX2 in the sample to generate a score for the sample, wherein the patient is identified as more likely to be responsive to a treatment comprising a KDM1 A inhibitor when the score in the sample surpasses a threshold.
  • the present invention provides a method of assessing the likelihood of a patient having SCLC to respond to a treatment comprising a KDM1A inhibitor, the method comprising measuring the level of ASCL1 and SOX2 in a sample from the patient prior to initiating the treatment comprising a KDM1A inhibitor.
  • the patient is identified as more likely to respond to a treatment comprising a KDM1A inhibitor when the level of each of ASCL1 and SOX2 in the sample surpasses a threshold.
  • the method further comprises using the level of ASCL1 and SOX2 in the sample to generate a score for the sample, wherein the patient is identified as more likely to respond to a treatment comprising a KDM1A inhibitor when the score in the sample surpasses a threshold.
  • the present invention provides a method of assessing the likelihood of a patient having SCLC to respond to a treatment comprising a KDM1A inhibitor, the method comprising measuring the level of ASCL1 and SOX2 in a sample from the patient prior to initiating the treatment comprising a KDM1A inhibitor, wherein the patient is identified as more likely to respond to a treatment comprising a KDM1A inhibitor when the level of each of ASCL1 and SOX2 in the sample surpasses a threshold.
  • the present invention provides a method of assessing the likelihood of a patient having SCLC to respond to a treatment comprising a KDM1A inhibitor, the method comprising measuring the level of ASCL1 and SOX2 in a sample from the patient prior to initiating the treatment comprising a KDM1A inhibitor, and using the level of ASCL1 and SOX2 in the sample to generate a score for the sample, wherein the patient is identified as more likely to respond to a treatment comprising a KDM1A inhibitor when the score in the sample surpasses a threshold.
  • the present invention provides a method of assessing the likelihood of a SCLC in a patient to respond to a treatment comprising a KDM1A inhibitor, the method comprising measuring the level of ASCL1 and SOX2 in a sample from a patient having SCLC prior to initiating the treatment comprising a KDM1 A inhibitor.
  • the SCLC is identified as more likely to respond to a treatment comprising a KDM1A inhibitor when the level of each of ASCL1 and SOX2 in the sample surpasses a threshold.
  • the method further comprises using the level of ASCL1 and SOX2 in the sample to generate a score for the sample, wherein the SCLC is identified as more likely to respond to a treatment comprising a KDM1A inhibitor when the score in the sample surpasses a threshold.
  • the present invention provides a method of assessing the likelihood of a SCLC to respond to a treatment comprising a KDM1A inhibitor, the method comprising measuring the level of ASCL1 and SOX2 in a sample from a patient having SCLC prior to initiating the treatment comprising a KDM1A inhibitor, wherein the SCLC is identified as more likely to respond to a treatment comprising a KDM1A inhibitor when the level of each of ASCL1 and SOX2 in the sample surpasses a threshold.
  • the present invention provides a method of assessing the likelihood of a SCLC to respond to a treatment comprising a KDM1A inhibitor, the method comprising measuring the levels of ASCL1 and SOX2 in a sample from a patient having SCLC prior to initiating the treatment comprising a KDM1A inhibitor, and using the level of ASCL1 and SOX2 in the sample to generate a score for the sample, wherein the SCLC is identified as more likely to respond to a treatment comprising a KDM1 A inhibitor when the score in the sample surpasses a threshold.
  • the invention provides a method of selecting a treatment for a patient having SCLC, the method comprising measuring the level of ASCL1 and SOX2 in a sample from the patient prior to initiating the treatment.
  • the method comprises providing a recommendation that the treatment selected for the patient comprises a KDM1A inhibitor when the level of each of ASCL1 and SOX2 in the sample surpasses a threshold.
  • the method further comprises using the level of ASCL1 and SOX2 in the sample to generate a score for the sample, and providing a recommendation that the treatment selected for the patient comprises a KDM1A inhibitor when the score in the sample surpasses a threshold.
  • the invention further provides a method of selecting a treatment for a patient having SCLC, the method comprising measuring the level of ASCL1 and SOX2 in a sample from the patient prior to initiating the treatment, and providing a recommendation that the treatment selected for the patient comprises a KDM1A inhibitor when the level of each of ASCL1 and SOX2 in the sample surpasses a threshold.
  • the invention further provides a method of selecting a treatment for a patient having SCLC, the method comprising measuring the level of ASCL1 and SOX2 in a sample from the patient prior to initiating the treatment, using the level of ASCL1 and SOX2 in the sample to generate a score for the sample, and providing a recommendation that the treatment selected for the patient comprises a KDM1A inhibitor when the score in the sample surpasses a threshold.
  • All the above methods according to the invention comprise measuring the level of the biomarkers of the invention (ASCL1 and SOX2) in a sample and assessing said biomarker levels or a derived score (based on said levels) versus a threshold.
  • each biomarker i.e. ASCL1 and SOX2
  • the threshold which can be established as described elsewhere herein
  • the (measured) levels of ASCL1 and SOX2 are each assessed versus its respective threshold, wherein the patient is identified as more likely to respond to a treatment comprising a KDM1A inhibitor (or, as applicable, the patient is identified as one who may benefit from a treatment comprising a KDM1A inhibitor, etc) when the level of each of ASCL1 and SOX2 in the sample surpasses its threshold.
  • the (measured) levels of ASCL1 and SOX2 in the sample can be used to generate a score for the sample, using a classification algorithm; in such a case a threshold for the score will apply (which can be established as described elsewhere herein) and the patient is identified as more likely to respond to a treatment comprising a KDM1A inhibitor (or, as applicable, the patient is identified as one who may benefit from a treatment comprising a KDM1 A inhibitor, etc) when the score in the sample surpasses the threshold.
  • a threshold for the score will apply (which can be established as described elsewhere herein) and the patient is identified as more likely to respond to a treatment comprising a KDM1A inhibitor (or, as applicable, the patient is identified as one who may benefit from a treatment comprising a KDM1 A inhibitor, etc) when the score in the sample surpasses the threshold.
  • the method further comprises a step of obtaining or providing a sample from the patient.
  • the obtaining/providing step is prior to the measuring of the level of the biomarkers (and prior to the administration of any treatment comprising a KD 1 A inhibitor to the patient from which the sample is to be obtained/provided).
  • the method further comprises recommending, prescribing or administering a therapeutically effective amount of a treatment comprising a KDM1A inhibitor to the patient if the patient is identified as more likely to respond to a treatment comprising a KDM1A inhibitor.
  • the method can optionally further comprise recommending that the patient is not treated with a KDM1A inhibitor if the patient is identified as less likely to respond to a treatment comprising a KDM1A inhibitor.
  • the levels of ASCL1 and SOX2 can be determined either as mRNA levels or as protein levels, using any methods known in the art for measuring mRNA or protein levels, including the methods as described herein.
  • mRNA from a sample can be directly used for determining the level of the biomarker.
  • the level can be determined by hybridization.
  • the RNA can be transformed into cDNA (complementary DNA) copy using methods known in the art.
  • Methods for detecting can include but are not limited to quantitative reverse transcriptase polymerase chain reaction (qRT-PCR), gene expression analyses, RNA sequencing, nanopore sequencing, microarray analyses, gene expression chip analyses, (in situ) hybridization techniques, RNAscope, and chromatography as well as any other techniques known in the art, e.g.
  • Methods for detecting RNA can include but are not limited to PCR, real-time PCR, digital PCR, hybridization, microarray analyses, as well as any other techniques known in the art, e.g. those described in Leland et al,“Handbook of Molecular and cellular Methods in Biology and Medicine", published 2011, ISBN 9781420069389.
  • the method can comprise detecting the protein expression level of a biomarker.
  • Any suitable methods of protein detection, quantization and comparison can be used, such as those described in John M. Walker,“The Protein Protocols Handbook”, published 2009, ISBN 978-1-59745-198-7.
  • the protein expression level of a biomarker can be determined by immune assays which include the recognition of the protein or protein complex by an antibody or antibody fragment, comprising but not limited to enzyme linked immunosorbent assays (ELISA), "sandwich” immunoassays, immunoradiometric assays, in situ immunoassays, alphaLISA immunoassays, protein proximity assays, proximity ligation assay technology (e.g.
  • Immunoassays may be homogeneous assays or heterogeneous assays.
  • the immunological reaction usually involves the specific antibody, a labeled analyte, and the sample of interest.
  • the signal arising from the label is modified, directly or indirectly, upon the binding of the antibody to the labeled analyte. Both the immunological reaction and detection of the extent thereof can be carried out in a homogeneous solution.
  • Immunochemical labels which may be employed include free radicals, radioisotopes, fluorescent dyes, enzymes, bacteriophages, or coenzymes.
  • the reagents are usually the sample, the antibody, and means for producing a detectable signal.
  • the antibody can be immobilized on a support, such as a bead, plate or slide, and contacted with the specimen suspected of containing the antigen in a liquid phase.
  • the support is then separated from the liquid phase and either the support phase or the liquid phase is examined for a detectable signal employing means for producing such signal.
  • the signal is related to the presence of the analyte in the sample.
  • Means for producing a detectable signal include the use of radioactive labels, fluorescent labels, or enzyme labels.
  • an antibody to the biomarker of interest can be used.
  • a kit for detection can be used.
  • Such antibodies and kits are available from commercial sources such as EMD Millipore, R&D Systems for biochemical assays, Thermo Scientific Pierce Antibodies, Novus Biologicals, Aviva Systems Biology, Abnova Corporation, AbD Serotec or others.
  • antibodies can also be synthesized by any known method.
  • the term "antibody” as used herein is intended to include monoclonal antibodies, polyclonal antibodies, single chain antibodies and chimeric antibodies.
  • Antibodies can be conjugated to a suitable solid support (e.g., beads such as protein A or protein G agarose, microspheres, plates, slides or wells formed from materials such as latex or polystyrene) in accordance with known techniques, such as passive binding.
  • a suitable solid support e.g., beads such as protein A or protein G agarose, microspheres, plates, slides or wells formed from materials such as latex or polystyrene
  • Antibodies as described herein may likewise be conjugated to detectable labels or groups able to create signals such as radiolabels (e.g., 35 S), enzyme labels (e.g., horseradish peroxidase, alkaline phosphatase), fluorescent labels (e.g., fluorescein, Alexa, green fluorescent protein, rhodamine), phthalocyanine containing beads that can release singlet oxygen after irradiation at 680 nM and provoke emission of light after its subsequent absorption by acceptor beads containing Europium or Therbium, and oligonucleotide labels. Labels can generate signal directly or indirectly. Signal generated can include e.g. fluorescence, radioactivity, or luminescence, in accordance with known techniques.
  • radiolabels e.g. 35 S
  • enzyme labels e.g., horseradish peroxidase, alkaline phosphatase
  • fluorescent labels e.g., fluorescein, Alexa, green fluorescent protein,
  • Antibodies can be substituted by alternative protein capture agents with high affinity and selectivity for the protein biomarkers to be analyzed, including aptamers, affimers, or chemoprobes.
  • the level of the biomarker when measuring biomarker protein levels, can be assessed in parts of the SCLC tumor cells, e.g. in the nuclei of tumor cells for example in immunofluorescence analysis of biopsies.
  • the level of the biomarker can be expressed in any form of mRNA expression or protein expression measurement used in the field, and can be raw data or processed data, i.e. raw data subjected to background substraction, normalizations or other corrections or other mathematical operations or transformations typically used in the field.
  • biomarker levels can be represented by the hybridization signal intensity values of the sample, the Log2(hybridization intensity value of the sample), or the Log2(hybridization signal intensity value of the sample / hybridization signal intensity values of a reference sample).
  • a suitable reference sample is a patient derived tumor sample with high expression level of ASCL1 and SOX2, obtained from a xenograft or PDX model, or a SCLC cell pellet.
  • Hybridization signal values can be obtained using single color or 2 color hybridizations.
  • Cp crossing point-PCR-cycle
  • biomarker levels when measured by RNA sequencing, can be represented by the Reads Per Million (RPM), Reads Per Kilobase Million (RPKM), Fragments Per Kilobase Million (FPKM),or Transcripts Per Million (TPM) values.
  • RPM Reads Per Million
  • RPKM Reads Per Kilobase Million
  • FPKM Fragments Per Kilobase Million
  • TPM Transcripts Per Million
  • biomarker levels when measured by Western blot, biomarker levels can be represented as integrated density (A.U) of the corresponding bands after image analysis, either as raw integrated density or normalized by protein content and/or as a ratio relative to a reference sample.
  • A.U integrated density
  • biomarker levels when measured by immunostaining, can be represented as integrated density (A.U) of nuclear signals after image analysis, either as raw integrated density (A.U)/area unit (pixel 2 or pm 2 ), or as integrated density/nucleus, or as a ratio relative to a reference sample.
  • biomarker levels when measured by ELISA, can be represented as R.L.U (relative light units) or Absorbance units, either raw or background-corrected or normalized by total protein content and/or as a ratio relative to a reference sample.
  • the biomarker level (i.e. the ASCL1 level and the SOX2 level) is an mRNA expression level.
  • the mRNA expression level is measured by qRT- PCR .
  • the biomarker level is a protein expression level.
  • the protein expression level is measured by fluorescence immunohistochemistry.
  • biomarker expression levels in immunofluorescent stainings are visually classified, based on staining intensity levels, as high, medium, low or undetectable, with values 3, 2, 1 and 0, respectively.
  • Samples with medium and high levels are considered“positive” (i.e. surpassing the threshold for the respective biomarker), whereas samples with undetectable or low levels (values 0 and 1) are considered“negative” (i.e. not surpassing the threshold for the respective biomarker).
  • a sample is considered “positive” for both biomarkers (i.e.
  • the patient is identified as more likely to respond to a treatment comprising a KDM1A inhibitor/ the patient is identified that he/she may benefit from a treatment comprising a KD 1 A inhibitor.
  • biomarker expression levels in immunofluorescent staining images can be quantified.
  • a DNA dye e.g.. DAPI staining can be used to localize the nuclei using fluorescence quantification.
  • Expression of SOX2 and ASCL1 in the nuclei can be analyzed using immunofluorescence quantification.
  • Individual images from biomarker and DAPI stainings can be analyzed using imaging software, e.g. using ImageJ. Signal may be obtained by background subtraction and normalized to a reference (calibrator) sample.
  • a suitable calibrator sample is a sample that has high and homogeneous nuclear expression of both biomarkers, e.g. an NCI-H1417- derived xenograft sample.
  • Normalized quantification values may be expressed in % or as ratios relative to the calibrator sample.
  • the threshold for each biomarker may be established as a fraction of the signal of the calibrator sample and shall be chosen to be higher than the (mean) signal of the negative control sample(s) used (which can be e.g. normal lung biopsy or xenograft samples that have low or undetectable expression of both biomarkers).
  • the thresholds are at least the mean signal of the negative control samples plus 1 SD, 2 SD or 3 SD, wherein SD means standard deviation.
  • the term“when the level of each of ASCL1 and SOX2 in the sample surpasses a threshold” or the like can mean“when the level of each of ASCL1 and SOX2 in the sample is increased in comparison to a control”.
  • the patient when the level of each of ASCL1 and SOX2 in the sample is increased in comparison to a control, the patient is identified as more likely to respond to a treatment comprising a KDM1A inhibitor / the patient is identified that he/she may benefit from a treatment comprising a KDM1A inhibitor.
  • control or“reference” are used interchangeably herein.
  • a non-limiting example of a“control” e.g.
  • a“control value”) or“reference” may be the level of ASCL1 and SOX2, respectively, in a sample or pool of samples from one or more healthy individual(s)/subject(s).
  • a healthy individual/subject may, for example, be an individual/subject that is not suffering from SCLC as defined herein, particularly one that is not suffering from SCLC at the time of obtaining the sample from the individual/subject.
  • a healthy individual/subject may, for example, be an individual/subject that is not suffering from a disease or disorder associated with increased levels of each of ASCL1 and SOX2.
  • the healthy individual/subject is a human.
  • a“control” e.g.
  • a“control value”) or“reference” may be the level of ASCL1 and SOX2, respectively, in a sample or pool of samples from a“non-responder”, e.g. one or more patients that suffer from SCLC and are known to be not responsive to a KDM1A inhibitor.
  • a“non-responder” control is(are) (a) cell line(s)/cell(s)/tissue(s) that show(s) no response to a KDM1A inhibitor in an in vitro, ex-vivo or (patient derived) xenograft test.
  • a“control” is an“internal standard”, for example purified or synthetically produced proteins and/or peptides or a mixture thereof, or corresponding nucleic acids, where the amount of each protein/peptide (or corresponding nucleic acid) is gauged by using the“non-responder” control described above.
  • this“internal standard” can contain the protein(s) (or a corresponding nucleic acid) ASCL1 and SOX2 as described and defined herein.
  • a non-limiting example of a “control” e.g. a“control value”
  • “reference” e.g.
  • a“reference value) may be the level of ASCL1 and SOX2, respectively, in a sample from the patient to be identified herein, if, for example, the sample was obtained before the patient suffered SCLC, before the patient was prone to (or at risk of) suffering from SCLC cancer, or if the sample was obtained when the patient had (fully) recovered from a previous SCLC.
  • the sample is a SCLC biopsy, preferably a SCLC biopsy rich in SCLC cells.
  • the patient is a human patient.
  • the above (diagnostic) methods are in vitro methods.“In vitro”, as used herein, means that the methods of the invention as described above, such as methods of identifying patients having SCLC that are more likely to respond to treatment comprising a KDM1A inhibitor and the like, are not performed in vivo, i.e. directly on a patient, but outside of a living human (or other mammal), on a sample obtained from and separated/isolated from the patient (i.e. removed from its in vivo location).
  • the invention provides a use of ASCL1 and SOX2 in a method of identifying a patient having SCLC who is more likely to respond to a treatment comprising a KDM1A inhibitor.
  • the invention provides a use of ASCL1 and SOX2 in a method of assessing the likelihood of response of a patient having SCLC to a treatment comprising a KDM1 A inhibitor.
  • the invention provides the use of one or more agents for measuring the level of ASCL1 and SOX2 in a method of identifying a patient having SCLC who is more likely to respond to a treatment comprising a KDM1A inhibitor.
  • the invention provides the use of one or more agents for measuring the level of ASCL1 and SOX2 in a method of assessing the likelihood of response of a patient having SCLC to a treatment comprising a KDM1A inhibitor.
  • the invention provides a use of ASCL1 and SOX2 for the manufacture of a diagnostic for identifying a patient having SCLC who is more likely to respond to a treatment comprising a KDM1A inhibitor.
  • the invention provides a use of ASCL1 and SOX2 for the manufacture of a diagnostic for assessing the likelihood of response of a patient having SCLC to a treatment comprising a KDM1A inhibitor.
  • the invention provides a kit for identifying a patient having SCLC who is more likely to respond to a treatment comprising a KDM1A inhibitor, the kit comprising one or more agents for measuring the level of ASCL1 and SOX2 in a sample, and optionally, instructions for use.
  • the invention provides a kit for assessing the likelihood of response of a patient having SCLC to a treatment comprising a KDM1A inhibitor, the kit comprising one or more agents for measuring the level of ASCL1 and SOX2 in a sample, and optionally, instructions for use.
  • the present invention also relates to therapeutic methods for treating those SCLC patients so identified.
  • the invention provides a method of treating a patient having SCLC, the method comprising administering to the patient a therapeutically effective amount of a treatment comprising a KDM1A inhibitor, if the patient has been identified as more likely to respond to a treatment comprising a KDM1A inhibitor using a method according to any of the preceding aspects prior to initiating the treatment comprising a KDM1A inhibitor.
  • the invention features a method of treating a patient having SCLC, the method comprising measuring the level of ASCL1 and SOX2 in a sample from the patient prior to initiating the treatment, identifying the patient as more likely to respond to a treatment comprising a KDM1A inhibitor when the level of each of ASCL1 and SOX2 in the sample surpasses a threshold, and administering a therapeutically effective amount of a treatment comprising a KDM1 A inhibitor to the patient if identified as more likely to respond.
  • the invention features a method of treating a patient having SCLC, the method comprising measuring the level of ASCL1 and SOX2 in a sample from the patient prior to initiating the treatment, using these levels to generate a score for the sample, identifying the patient as more likely to respond to a treatment comprising a KDM1A inhibitor when the score in the sample surpasses a threshold, and administering a therapeutically effective amount of a treatment comprising a KDM1 A inhibitor to the patient if identified as more likely to respond.
  • the invention provides a KDM1A inhibitor for use in treating a patient having SCLC, wherein the patient has been identified as more likely to respond to a treatment comprising a KDM1A inhibitor using a method according to any of the preceding aspects prior to initiating the treatment comprising a KDM1A inhibitor.
  • the method further comprises a step of obtaining or providing a sample from the patient.
  • the patient is a human patient.
  • KDM1A inhibitors which can be used in accordance with the present invention include any KDM1A inhibitor currently known in the art or that may be reported in the future.
  • the KDM1A inhibitor is a small molecule. Both irreversible and reversible KDM1A inhibitors have been reported. Irreversible KDM1A inhibitors exert their inhibitory activity by becoming covalently bound to the FAD cofactor within the KDM1A active site and are typically based on a 2-cyclyl-cyclopropylamino moiety such as a 2-(hetero)arylcyclopropylamino moiety. Reversible inhibitors of KDM1A have also been disclosed. Preferably, the KDM1A inhibitor should be active in cells.
  • KDM1 A inhibitors can be determined for example using well-established in vitro cellular assays for KDM1 A inhibitors, like for example an SCLC cell viability assay (such as e.g. the assays as described in Example 1 herein or in Mohammad et al, 2015, supra) or an acute myeloid leukemia cell line differentiation assay (such as e.g. the assay as described in Lynch et al, Anal Biochem. 2013 Nov 1 ;442(1):104-6. doi: 10.1016/j.ab.2013.07.032).
  • SCLC cell viability assay such as e.g. the assays as described in Example 1 herein or in Mohammad et al, 2015, supra
  • an acute myeloid leukemia cell line differentiation assay such as e.g. the assay as described in Lynch et al, Anal Biochem. 2013 Nov 1 ;442(1):104-6. doi: 10.1016/j.ab.2013.07.032
  • KDM1A inhibitors which can be used in accordance with the present invention include, but are not limited, to those disclosed in: WO2010/043721 , WO2010/084160, WO2011/035941 , WO2011/042217, WO2011/131697, WO2012/013727, WO2012/013728, WO2012/045883, WO2013/057320, WO2013/057322, WO2010/143582, WO2011/022489, WO2011/131576, WO2012/034116, WO2012/135113, WO2013/022047, WO2013/025805, WO2014/058071 , WO2014/084298, W02014/086790, WO2014/164867, WO2014/205213, WO2015/021128, WO2015/031564, W02007/021839, W02008/127734, WO2014/164867 WO2015/089192, WO2015/123408, WO2015
  • a particularly preferred KDM1A inhibitor is (trans)-N1-((1 R,2S)-2-phenylcyclopropyl)cyclohexane-1 ,4-diamine [CAS Reg, No. 1431304-21-0] or a pharmaceutically acceptable salt thereof, more preferably, (trans)-N1-((1 R,2S)-2- phenylcyclopropyl)cyclohexane-1 , 4-diamine bis-hydrochloride [CAS Reg. No.
  • ORY-1001 has been disclosed for example in WO2013/057322, see example 5 therein.
  • Pharmaceutical formulations comprising ORY-1001 for administration to patients can be prepared following methods known to those skilled in the art, for example as described in WO2013/057322.
  • KDM1A inhibitors may be administered as the sole API, i.e. as monotherapy, or may be administered in combination of one or more additional APIs, such as other anticancer agents used for the treatment of SCLC. While it is possible that a KDM1A inhibitor (or a treatment comprising a KDM1A inhibitor) may be administered for use in therapy directly as such, it is typically administered in the form of a pharmaceutical composition, which comprises the compound as active pharmaceutical ingredient together with one or more pharmaceutically acceptable excipients or carriers. Any reference to the KDM1A inhibitor herein includes a reference to the compound as such, i.e.
  • the KDM1A inhibitor may be administered by any means that accomplish the intended purpose. Examples include administration by the oral or parenteral (including e.g. intravenous or subcutaneous) routes.
  • the compound can be incorporated into a formulation that includes pharmaceutically acceptable carriers such as binders (e.g., gelatin, cellulose, gum tragacanth), excipients (e.g., starch, lactose), lubricants (e.g., magnesium stearate, silicon dioxide), disintegrating agents (e.g., alginate, Primogel, and corn starch), and sweetening or flavoring agents (e.g., glucose, sucrose, saccharin, methyl salicylate, and peppermint).
  • binders e.g., gelatin, cellulose, gum tragacanth
  • excipients e.g., starch, lactose
  • lubricants e.g., magnesium stearate, silicon dioxide
  • disintegrating agents e.g., alginate, Primogel, and corn starch
  • sweetening or flavoring agents e.g., glucose, sucrose, saccharin, methyl salicylate, and peppermint
  • Suitable oral formulations can also be in the form of suspension, syrup, chewing gum, wafer, elixir, and the like. If desired, conventional agents for modifying flavors, tastes, colors, and shapes of the special forms can also be included.
  • the active compounds can be dissolved in an acceptable lipophilic vegetable oil vehicle such as olive oil, corn oil and safflower oil.
  • the compound can also be administered parenterally in the form of solution or suspension, or in lyophilized form capable of conversion into a solution or suspension form before use.
  • diluents or pharmaceutically acceptable carriers such as sterile water and physiological saline buffer can be used.
  • Other conventional solvents, pH buffers, stabilizers, anti-bacteria agents, surfactants, and antioxidants can all be included.
  • useful components include sodium chloride, acetates, citrates or phosphates buffers, glycerin, dextrose, fixed oils, methyl parabens, polyethylene glycol, propylene glycol, sodium bisulfate, benzyl alcohol, ascorbic acid, and the like.
  • the parenteral formulations can be stored in any conventional containers such as vials and ampoules.
  • compositions can be formulated in unit dosage forms for ease of administration and uniformity of dosage.
  • unit dosage forms refers to physically discrete units suitable as unitary dosages for administration to subjects, each unit containing a predetermined quantity of active ingredient calculated to produce the desired therapeutic effect, in association with one or more suitable pharmaceutical carriers.
  • pharmaceutical compositions are to be administered in a manner appropriate to the disease to be treated, as determined by a person skilled in the medical arts. An appropriate dose and suitable duration and frequency of administration will be determined by such factors as the condition of the patient, the severity of the disease, the specific KDM1 A inhibitor administered, the method of administration, and the judgement of the attending physician, among others.
  • an appropriate dose and administration regimen provides the pharmaceutical composition in an amount sufficient to provide therapeutic benefit, for example an improved clinical outcome, such as more frequent complete or partial remissions, or longer disease-free and/or overall survival, or lessening of symptoms severity, or any other objectively identifiable improvement as noted by the clinician.
  • Effective doses may generally be assessed or extrapolated using experimental models like dose-response curves derived from in vitro or animal model test systems. The skilled person shall be able to determine suitable dosages and treatment regimens based on the above factors.
  • compositions of the invention can be included in a container, pack or dispenser together with instructions for administration.
  • Example 1 Classification of sensitive and resistant cell lines to KDM1 A inhibitors
  • SCLC cell lines were classified for their response to KDM1A inhibitor treatment based on the results of viability assays performed after either 4 or 10 days of treatment with the KDM1A inhibitor, ORY-1001 (as described herein elsewhere).
  • viability assays SCLC cell lines were seeded in 384-well plates in a final volume of 40m ⁇ of the optimized medium recommended by the provider of the each cell line, supplemented with ORY-1001 (maximum concentration: 50mM; 18 serial 1 :2 dilutions tested). After 4 days incubation at 37°C in a 5% C02-controlled atmosphere, cell viability was evaluated using the CellTiterGlo® assay according to manufacturer protocol (Promega).
  • EC50 values were calculated using the the Microsoft Excel software to normalize against untreated cells (100% growth) and no CellTiterGlo® reagent (100% growth inhibition). Quantification of viability after 10 days exposure to ORY-1001 was performed in a 96-well plate format (maximum concentration 1 mM, 100nM for the NCI-H187 cell line).
  • Cells were initially seeded in 100m ⁇ of medium (RPMI-1640 10% FBS 2mM glutamine, with the exception of the NCI-H1876 cell line that was cultured in HITES medium, prepared adding 4.5mM glutamine, 0.005mg/mL Insulin, 0.01 mg/mL Transferrin, 30nM Sodium Selenite, 10nM Hydrocortisone, 10nM beta- estradiol to DMEM:F12 5%FBS) and incubated at 37°C in a 5% C02-controlled atmosphere. On day 6, additional 100m ⁇ of ORY-1001 -containing medium were added. After 4 additional days, residual viability was measured using the Alamar Blue® assay (Thermo Fisher Scientific). After background subtraction, normalization was performed against vehicle treated cells. EC50 values were calculated after fitting non-linear model using the GraphPad Prism software.
  • Cells were grown in flasks for 6 consecutive days. On the final day of the assay, cells were collected in a Falcon tube, counted and then centrifuged for 4 min at 1200 rpm. The supernatant was discarded and cells were suspended in 1 mL of PBS and transferred to an eppendorf samples to be centrifuged for 5 min at 3000 rpm in an eppendorf centrifuge at 4°C. Finally, the supernatant was discarded and the pellets frozen at -80°C.
  • the RNeasy Mini Kit combines selective binding properties of a silica-gel-based membrane with the speed of microspin technology. Briefly, tissue was homogenized and lysed in RLT buffer (with beta-mercaptoethanol) using Lysing Matrix D tubes (MP Biomedicals LLC) or vortexing. Ethanol was added to the homogenate to provide appropriate binding conditions for all RNA molecules longer than 200 nucleotides (nt). The sample was applied to an RNeasy Mini column where the total RNA binds to the membrane and contaminants were efficiently washed away. High-quality RNA was then eluted with nuclease-free water. The resulting RNA was quantitated and integrity assessed using an Agilent Bioanalyzer.
  • RNA samples were converted into cDNA libraries using the TruSeq Stranded mRNA Sample Prep Kit (lllumina). Starting with 100 ng of total RNA, polyadenylated RNA (primarily mRNA) was selected and purified using oligo-dT conjugated magnetic beads. This mRNA was chemically fragmented and converted into single-stranded cDNA using reverse transcriptase and random hexamer primers, with the addition of Actinomycin D to suppress DNA-dependent synthesis of the second strand.
  • TruSeq Stranded mRNA Sample Prep Kit lllumina
  • Double-stranded cDNA was created by removing the RNA template and synthesizing the second strand in the presence of dUTP in place of dTTP. A single A base was added to the 3’ end to facilitate ligation of sequencing adapters, which contain a single T base overhang.
  • Adapter-ligated cDNA was amplified by polymerase chain reaction to increase the amount of sequence-ready library. During this amplification the polymerase stalls when it encounters a U base, rendering the second strand a poor template. Accordingly, amplified material used the first strand as a template, thereby preserving the strand information.
  • samples had 100ng of input RNA and had a RIN value 3 7.0 to move forward with library preparation.
  • a minimum total of 30 Million 50 bp paired-end reads were generated per individual sample.
  • a minimum of 28.5 million reads were delivered after subtracting out various off-target sequences such as ribosomal RNA, phiX, homopolymer repeats, and globin RNA.
  • the lllumina HiSeq software reports the total number of clusters (DNA fragments) loaded in each lane, percent passing sequencing quality filters (which identifies errors due to overloading and sequencing chemistry), a phred quality score for each base of each sequence read, overall average phred scores for each sequencing cycle, and overall percent error (based on alignment to the reference genome). For each RNA-seq sample, the percentage of reads that contain mitochondrial and ribosomal RNA is calculated.
  • the FASTQC package is used to provide additional QC metrics (base distribution, sequence duplication, over represented sequences, and enriched kmers) and a graphical summary. Raw reads were aligned against the human genome (hg19) using GSNAP and recommended options for RNASeq data.
  • GSNAP is given a database of human splice junctions and transcripts based on Ensembl v73. Resulting SAM files are then converted to sorted BAM files using Samtools. Gene expression values were calculated both as RPKM values following Mortazavi et al. (Nat Methods (2008) 5(7):621-8) and as read counts. Normalized read counts were obtained using the R package DESeq2. The data are reported as mean of Log2(RPKM) of three independent experiments. RPKM stands for reads per kilobase per million.
  • Figure 1 is a dot plot representing expression of ASCL1 (Y-axis) and SOX2 (X-axis) measured by RNA-seq as described above for SCLC cell lines sensitive, sensitive in part or resistant to KDM1A inhibition. Based on the RNASeq data generated for these cell lines, it was identified that all ORY-1001 sensitive and partially sensitive cell lines express high level of ASCL1 and medium-to-high levels of SOX2, while in SCLC cell lines resistant to ORY-1001 treatment, either ASCL1 or SOX2 were detected at very low levels (Log2(RPKM ) £ 0), as shown in Table 2 and Figure 1.
  • ASCL1 and SOX2 may be used as biomarkers to identify SCLC cells, or subjects having SCLC, that are sensitive (i.e. responsive), or more likely to be sensitive (responsive), to treatment with KDM1 A inhibitors, such as ORY-1001.
  • biomarkers of responsiveness to KDM1A inhibitors identified in Example 2, ASCL1 and SOX2 were then validated by Taqman qRT-PCR analysis on the same panel of SCLC cell lines described in Example 1 and 2, including two additional SCLC cell lines, one identified as sensitive (DMS53) and one as sensitive in part (NCIH526) to KDMIAi treatment.
  • qRT-PCR was performed with LightCycler 480 Probes Master (PNT-L-034; Roche #04887301001 ) and using pre-designed and pre-optimized TaqMan Gene Expression Assays from ThermoFisher Scientific.
  • qRT-PCR was performed in triplicate using the Lightcycler 480 Instrument II (Roche; PNT-L-035).
  • ASCL1 and S0X2 gene expression in this panel of SCLC cell lines as measured by qRT-PCR is shown in Table 3.
  • the table reports Cp values.
  • Exp.R Experimental replicate; A v.: Average; n.d.: not detected.
  • Each experimental replicate value is the average of three technical replicates
  • the same RNA quantity per sample was analyzed by qRT-PCR.
  • the average Cp expression of GAPDH reference gene are reported and they ranged from 23 to 26 Cp among all samples (see Table 3).
  • Table 4 shows the average Cp values of all experimental replicates for ASCL1 and SOX2 in SCLC cell lines measured by qRT-PCR. Color code shown is based on the gene expression levels; the darker the color, the higher the expression of the biomarker.
  • Figure 2 is a dot plot representing gene expression of ASCL1 (Y-axis) and SOX2 (X-axis) measured by qRT-PCR (absolute Cp values) for the above-identified SCLC cell lines sensitive, sensitive in part or resistant to KDM1A inhibition. Plotted values are means of independent experiments as indicated in Table 3. One of the cell lines exhibits a Cp value above 40 for the expression of SOX2; this is indicated by showing the dot in brackets in Fig 2.
  • ASCL1 and SOX2 were then evaluated in these KDMIAi sensitive and resistant cells, using the cell lines transcriptomic dataset curated by the Broad Institute (Cancer Cell Line Encyclopedia; https://portals.broadinstitute.org/ccle; CCLE_Expression_Entrez_2012-09-29.gct.txt).
  • Gene expression of ASCL1 , SOX2, and GAPDH in said SCLC cell lines as in CCLE database is shown in Table 6, below p value for two-tailed Student’s t-test was calculated using Microsoft Office Excel.
  • ASCL1 and SOX2 were differentially expressed between cell lines sensitive and resistant to treatment with KDMIAi (Table 6).
  • Example 4 therefore further support the use of these two biomarkers in combination to identify/select subjects that are more likely to be responsive to treatment with a KDM1A inhibitor, like ORY-1001.
  • KDM1A sensitive and resistant cell lines can be discriminated with a sensitivity of 68.42% and a specificity of 100%.
  • SOX2 biomarker alone with a threshold level for the given expression dataset 3 8.030 KDM1A sensitive and resistant cell line can be discriminated with a sensitivity of 84.21% and a specificity of 87.50%.
  • a Boolean Conjunction model classification algorithm was built based on the simultaneous compliance of the biomarkers surpassing the individual thresholds for ASCL1 and SOX2 indicated above ( Figure 4A and B); in case the algorithm met the conditions indicated in the first raw of Table 7, below, a score of ⁇ ” was obtained, otherwise a score of“0” was obtained. Cell lines were then classified as more likely to respond to a KDMIAi when the score surpassed the threshold i.e. was > 0 (in this case, equal to 1) and less likely to respond when the score was equal to 0 (see Table 7 below). Finally, we evaluated the performance of the Boolean Conjunction classification algorithm.
  • Sensitivity also called True Positive Rate; TPR
  • specificity also called True Negative Rate; TNR
  • Positive Predictive Value PPV, also called Precision
  • Negative Predictive Value NPV
  • NPV TN / (TN + FN)
  • TP stands for number of true positives
  • TN number of true negatives
  • FP number of false positives
  • FN number of false negatives
  • the ASCL1/SOX2 signature exhibits high sensitivity (88%), specificity (100%), precision (100%) and Negative predictive value (95%).
  • Supportive Vector Machine (SVM) modeling of the DTREG Predictive Modeling Software was used to develop algorithms that can be used to classify samples using the biomarkers.
  • SVM Supportive Vector Machine
  • two different algorithms with different Kernel function, polynomial and radial basis function (RBF) and the respective parameters (C: Cost parameter; Gamma: Kernell Coefficient) reflected in Table 8, Top were used to evaluate the combination of ASCL1 and SOX2 as predictive biomarkers of responsiveness to KDM1A inhibitors.
  • the SVM algorithm employing the ASCL1/SOX2 combination has high sensitivity (88%) and high speficity (395%) using both the polynomial and the RBF fitting.
  • Linear Regression of the DTREG Predictive Modeling Software was used to develop an algorithm to classify samples as more likely to respond or less likely to respond to KDMIAi in function of the combination of the selected biomarkers on the dataset in Table 6 (Table 9).
  • the algorithm calculates the score for each sample and classifies the cell lines as sensitive or resistant to KDMIAi by comparing the score for each sample with the threshold.
  • the performance of the linear regression model generated based on the combination of ASCL1/SOX2 biomarkers has a sensitivity of 87.5% and specificity of 94.74% to predict sensitivity to KDMIAi (Table 9).
  • Table 9 shows the Parameters, Specificity, Sensitivity and Confusion Matrix for the Linear Regression model generated to predict sensitivity and resistance using the combination of ASCL1 and SOX2 expression.
  • C Cost parameter
  • Gamma Kernell Coefficient for the respective functions.
  • ASCL1 and SOX2 were analyzed by WB in SCLC cell lines with either high, medium or low/undetectable expression of these biomarkers, as well as by fluorescent immunohistochemistry of the same sectioned SCLC cell pellets and SCLC patient-derived xenografts (PDXs) with known mRNA levels.
  • SCLC Human small cell lung cancer
  • Proteins were transferred using the iBIot System (Life Technologies) and after secondary antibody incubation and washing, blots were developed with ECL Prime (Amersham) and photographed with G:BOX Chemi XRQ (Syngene). Ponceau S staining of transferred blots was used a loading control. Quantification of WB signals was carried out with Image J. Integrated densities for each WB band were normalised by the corresponding total protein integrated densities from Ponceau stainings and made relative to NCI-H146 signal.
  • ASCL1 and SOX2 protein levels were analyzed by WB in SCLC cell lines with either high, medium or low/undetectable expression of these biomarkers, as determined by qRT-PCR (Example 3) and confirmed with publicly available Affymetrix mRNA expression data from the Cancer Cell Line Encyclopedia (CCLE) (see Example 4).
  • WB as obtained is shown in Figure 5A, and the corresponding quantification of ASCL1 and SOX2 protein levels in NCI-H146, NCI-H510A, NCI-H446 and NCI-H526 cell lines is shown in Figure 5B.
  • Protein expression levels of ASCL1 and SOX2 by WB correlate with their respective mRNA levels, as ASCL1 was not detected in NCI-H446 and neither ASCL1 nor SOX2 were detected in NCI-H526 cells, while their expression was the highest in NCI-H146, confirming both mRNA expression levels and specificity of the antibodies used.
  • the correlation between protein and mRNA (CCLE Affymetrix) levels for SOX2 and ASCL1 is plotted in Figures 6A and 6B, respectively; a good correlation is observed, with R values of 0.8957 for SOX2 and 0.9910 for ASCL1.
  • 5.2 SOX2 and ASCL1 analysis bv fluorescent immunohistochemistry on SCLC cell pellets
  • NCI-H146 10 million exponentially growing cells (NCI-H146, NCI-H510A, NCI-H446 and NCI-H526) were fixed in 10% formalin (Sigma) for 1 hour at room temperature, washed in 1X PBS (Sigma), pelleted, included in 1.3% agarose (Sigma) and subsequently dehydrated and included in paraffin for microtome sectioning, 5mhi sections were placed on Superfrost slides, deparaffinised in HistoChoice clearing agent (Sigma) for 5 min twice and hydrated through a decreading ethanol series (2x 100% 5 min, 90% 1 min, 70% 1 min, 30% 1 min, 2x running water).
  • Sections were then subjected to heat-induced antigen retrieval in boiling pH 6 citrate buffer 1X (Sigma) for 20 min. After 20 min left at room temperature, slides were washed in PBS-Triton X100 0.1% (0.1 % PBS-Tx) and blocked in 5% goat serum in 0,1% PBS-Tx for 1 h at room temperature. After blocking, excess liquid was removed with paper tissue by capillarity and sections incubated with primary antibodies diluted in 1% goat serum in 0,1% PBS-Tx overnight at 4°C (1 :500 dilution for SOX2, Abeam ab97959; 1 :100 for ASCL1 Abeam ab213151) and the corresponding negative control (1% goat serum in 0,1% PBS-Tx only).
  • DAPI is 4',6-diamidino-2-phenylindole, a fluorescent dye that strongly binds to A-T rich regions in DNA and is used to stain the nuclei.
  • IF images were processed and quantified with imageJ software.
  • imageJ software For SOX2 and ASCL1 nuclear-specific signal quantification, a mask enclosing the area covered by nuclei was created from the DAPI staining image and then transferred to the corresponding IF image, such that the integrated density was determined in the selected area defined by nuclei only.
  • SOX2 levels were high in NCI-H146, medium in NCI-H510A and low in NCI-H446 cell lines, while no nuclear-specific expression was detected in NCI-H526 cells.
  • ASCL1 levels were high in NCI-H146, medium in NCI-H510A and absent/undetectable in NCI-H446 and NCI-H526 cells. No expression was observed in the negative control with secondary antibody only (AF546: Alexa Fluor 546).
  • staining intensity levels were established and are employed from now onwards in the examples below: high levels will be defined as“Level 3”, medium levels as“Level 2’’, low levels as“Level 1” and absence of signal as“Level 0”.
  • Table 10 shows the quantification of the nuclear biomarker signal in the immunofluorescence images shown in Figure 7 along with the corresponding intensity levels and RMA values from CCLE Affymetrix in NCI-H146, NCI-H510A, NCI-H446 and NCI-H526 cells. Signals were background-corrected and represented relative to the NCI- H146 signal (equivalent to 100%).
  • ASCL1 and SOX2 can be used as predictive biomarkers of responsiveness to KDM1 A inhibition measuring either their mRNA or protein levels.
  • SOX2 and ASCL1 IF were performed on patient-derived SCLC xenograft tissue microarrays with available SOX2 and ASCL1 RNASeq data. Sections of tissue microarrays containing 44 cases of patient-derived SCLC xenografts were purchased from Molecular Response (now Crown Bioscienses) and their corresponding available RNASeq data downloaded from https://oncoexpress.crownbio.com/OncoExpress/index.aspx.
  • TMAs were deparaffinised in HistoChoice clearing agent (Sigma) for 5 min twice and hydrated through a decreading ethanol series (2x 100% 5 min, 90% 1 min, 70% 1min, 30% 1 min, 2x running water. Sections were then subjected to heat-induced antigen retrieval in boiling pH 6 citrate buffer 1X (Sigma) for 20 min. After 20 min left at room temperature, slides were washed in PBS-Triton X100 0.1% (0.1 % PBS-Tx) and blocked in 5% goat serum in 0,1% PBS-Tx for 1 h at room temperature.
  • samples with expression levels surpassing the individual biomarker thresholds of 1 i.e. medium to high expression Levels 2 and 3
  • samples with a ASCL1/SOX2 Boolean conjunction score surpassing the threshold > 0
  • samples with score surpassing the threshold are indicated as“Positive” and samples with score not surpassing the threshold are indicated as“Negative”.
  • SOX2 and ASCL1 IF were performed on patient-derived SCLC xenograft tissue microarrays, with available SOX2 and ASCL1 RNASeq data. All samples were visually analyzed in a fluorescence microscope, tumor areas defined by nuclear morphology and given intensity levels according to the nuclear signals observed within tumor areas, as explained above. Representative ASCL1 and SOX2 stainings from SCLC PDX TMA are shown for each staining intensitity classification level in Figure 9.
  • Exosomes are microvesicles present in bodily fluids reflecting in their contents the proteasome, genome and transcriptome of parental cells. Thus, exosomes constitute an excellent minimally invasive tool for quantitative biomarker detection. We therefore tested if the detection of our predictive biomarkers of responsiveness to KDM1A inhibitors, ASCL1 and SOX2, was suitable in methods employing exosome-containing samples.
  • Exosomes were isolated by precipitation from SCLC cell lines and SOX2 and ASCL1 protein levels determined by WB.
  • NCI-H146, NCI-H510A, NCI-H446 and NCI-H526 SCLC cells were seeded in 20ml RPMI medium (Sigma) supplemented with 2mM glutamine (Sigma) and 10% exosome-free FBS (System Biosciences), and incubated in T75 flasks at 37°C and 5% CO2 in a humid atmosphere. After 48h, 15ml of well-resuspended cells were spun at 2.000xg for 30 min at room temperature, the supernatant transferred to a clean tube and cell pellet kept at - 20°C.
  • Exosome isolation method was validated by growing NCI-H510A cells, either in the presence of 5mM of the exosome-releasing inhibitor GW4869 (SelleckChem) or vehicle in the conditions specified above, and exosomes isolated with the Total Exosome Isolation reagent (from cell culture media) (Life Technologies) exactly following manufacturer ' s instructions.
  • Example 6 confirm that measurement of protein levels of the predictive biomarkers of the invention, ASCL1 and SOX2, can be performed to determine responsiveness to KDM1A inhibitors using exosomes as starting material/sample.
  • the present invention refers to the following nucleotide and amino acid sequences:
  • the present invention also provides techniques and methods wherein homologous sequences, and variants of the concise sequences provided herein are used.
  • such“variants” are genetic variants, e.g. splice variants.
  • Exemplary amino acid sequences and nucleotide sequences of human ASCL1 and SOX2 are shown in SEQ ID NO: 1 to 4 herein below.
  • Exemplary nucleotide and amino acid sequences of human GAPDH (glyceraldehyde-3- phosphate dehydrogenase), used as control gene in some of the Examples, are shown in SEQ ID NO: 5 and 6.
  • SEQ ID No, 1 Nucleotide sequence encoding Homo sapiens Achaete-Scute Family bHLH Transcription Factor 1 (ASCL1), mRNA
  • NCBI Reference Sequence NM_004316.3.
  • the coding region ranges from nucleotide 572 to nucleotide 1282 (highlighted in bold). It is understood that the mRNA corresponds to the sequence below (i.e. is identical to that sequence) with the exception that the“t” (thymidine) residue is replaced by a“uracil” (u) residue.
  • SEQ ID No. 2 Amino acid sequence of Homo sapiens Achaete-Scute Family bHLH Transcription Factor 1 (ASCL1), protein
  • SAAFQAGVLSPTISPNYSNDLNSMAGSPVSSYSSDEGSYDPLSPEEQELLDFTNWF SEQ ID No. 3 Nucleotide sequence encoding Homo sapiens SRY-box 2 (SOX2), mRNA NCBI Reference Sequence: NM_003106.3.The coding region ranges from nucleotide 438 to nucleotide 1391 (highlighted in bold). It is understood that the mRNA corresponds to the sequence below (i.e. is identical to that sequence) with the exception that the“t” (thymidine) residue is replaced by a“uracil” (u) residue.
  • SEQ ID No. 4 Amino acid sequence of Homo sapiens Homo sapiens SRY-box 2 (S0X2), protein UniProtKB/Swiss-Prot: S0X2_HUMAN, P48431
  • SEQ ID No. 5 Homo sapiens glyceraldehyde-3-phosphate dehydrogenase (GAPDH), mRNA
  • NCBI Reference Sequence NM_002046.6.
  • the coding region ranges from nucleotide 77 to nucleotide 1084 (highlighted in bold). It is understood that the mRNA corresponds to the sequence below (i.e. is identical to that sequence) with the exception that the T (thymidine) residue is replaced by a“uracil” (u) residue.
  • SEQ ID No. 6 Amino acid sequence of Homo sapiens glyceraldehyde-3-phosphate dehydrogenase (GAPDH), protein UniProtKB/Swiss-Prot: G3P_HUMAN, P04406

Abstract

La présente invention concerne des biomarqueurs et des procédés pour prédire la réactivité d'un patient ayant un cancer du poumon à petites cellules (SCLC) à un traitement avec des inhibiteurs de KDM1A, et des procédés de traitement de sous-groupes de patients SCLC identifiés à l'aide desdits procédés.
PCT/EP2019/068150 2019-07-05 2019-07-05 Biomarqueurs et procédés pour le traitement personnalisé d'un cancer du poumon à petites cellules au moyen d'inhibiteurs de kdm1a WO2021004610A1 (fr)

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CN201980100040.4A CN114341366A (zh) 2019-07-05 2019-07-05 用于使用kdm1a抑制剂个体化治疗小细胞肺癌的生物标志物和方法
PCT/EP2019/068150 WO2021004610A1 (fr) 2019-07-05 2019-07-05 Biomarqueurs et procédés pour le traitement personnalisé d'un cancer du poumon à petites cellules au moyen d'inhibiteurs de kdm1a
JP2022500505A JP2022546908A (ja) 2019-07-05 2019-07-05 Ｋｄｍ１ａ阻害剤を使用した小細胞肺がんの個別化された処置のためのバイオマーカーおよび方法
EP19735339.4A EP3994280A1 (fr) 2019-07-05 2019-07-05 Biomarqueurs et procédés pour le traitement personnalisé d'un cancer du poumon à petites cellules au moyen d'inhibiteurs de kdm1a

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