WO2020193746A1 - Methods for predicting the survival of patients suffering from melanoma - Google Patents

Abstract

Melanoma displayed sphingolipid (SL) metabolism alterations, which likely contribute to melanoma progression. In non-cancer cells, de novo synthesized ceramide is mainly converted to sphingomyelin (SM) and, to a lesser extent, glucosylceramide (GlcCer). Herein, the inventors provide evidence that both SM synthases 1 (SMS1) and 2 (SMS2) were expressed at low levels in human melanoma and low SMS1 expression was associated with a worse prognosis. Accordingly, the present invention relates to a method for predicting the survival of a patient suffering from melanoma comprising determining the expression level of SGMS1 (e.g. at RNA level or by immunohi stochemi stry) in a tumor sample obtained from the patient.

Description

METHODS FOR PREDICTING THE SURVIVAL OF PATIENTS SUFFERING

FROM MELANOMA

FIELD OF THE INVENTION:

The present invention relates to methods for predicting the survival of patients suffering from melanoma.

BACKGROUND OF THE INVENTION:

Melanoma is a bad-prognosis skin cancer, the treatment of which has been recently revolutionized with the development of targeted therapies (B-Raf and MEK inhibitors) and immunotherapies (anti-CTLA-4 and anti-PD-1). Despite objective clinical responses, half of the patients do not respond to such new therapies and a large proportion of good-responders experience tumor relapse within 2 years following treatment induction. In melanoma, sphingosine 1 -phosphate (SIP) behaves as an oncometabolite, enhancing tumor angiogenesis, stromagenesis and modulating tumor-associated macrophages. Whereas glucosylceramide synthase (GCS), which converts ceramide to glucosylceramide (GlcCer), is also involved in melanoma growth, the contribution of sphingomyelin synthases (SMS) has been poorly documented.

SUMMARY OF THE INVENTION:

The present invention relates to methods for predicting the survival of patients suffering from melanoma. In particular, the present invention is defined by the claims.

DETAILED DESCRIPTION OF THE INVENTION:

Melanoma displayed sphingolipid (SL) metabolism alterations, which likely contribute to melanoma progression. In non-cancer cells, de novo synthesized ceramide is mainly converted to sphingomyelin (SM) and, to a lesser extent, glucosylceramide (GlcCer). Herein, the inventors provide evidence that both SM synthases 1 (SMS1) and 2 (SMS2) were expressed at low levels in human melanoma and low SMS1 expression was associated with a worse prognosis.

Accordingly, the first object of the present invention relates to a method for predicting the survival of a patient suffering from melanoma comprising i) determining the expression level of SGMS1 , which encodes SMS1, in a tumor sample obtained from the patient, ii) comparing the expression level determined at step i) with a predetermined reference value and iii) and concluding that the patient will have short survival time when the level determined at step i) is lower than the predetermined reference value or concluding that the patient will have long survival time when the expression level determined at step i) is higher than the predetermined reference value.

As used herein, "melanoma" refers to a condition characterized by the growth of a tumor arising from the melanocytic system of the skin and other organs. Most melanocytes occur in the skin, but are also found in the meninges, digestive tract, lymph nodes and eyes. When melanoma occurs in the skin, it is referred to as cutaneous melanoma. Melanoma can also occur in the eyes and is called ocular or intraocular melanoma. Melanoma occurs rarely in the meninges, the digestive tract, lymph nodes or other areas where melanocytes are found. 40- 60 % of melanomas carry an activating mutation in the gene encoding the serine-threonine protein kinase B-RAF (BRAF). Among the BRAF mutations observed in melanoma, over 90 % are at codon 600, and among these, over 90 % are a single nucleotide mutation resulting in substitution of glutamic acid for valine (BRAFV600E).

The method is particularly suitable for predicting the duration of the overall survival (OS), progression-free survival (PFS) and/or the disease-free survival (DFS) of the cancer patient. Those of skill in the art will recognize that OS survival time is generally based on and expressed as the percentage of people who survive a certain type of cancer for a specific amount of time. Cancer statistics often use an overall five-year survival rate. In general, OS rates do not specify whether cancer survivors are still undergoing treatment at five years or if they've become cancer-free (achieved remission). DSF gives more specific information and is the number of people with a particular cancer who achieve remission. Also, progression-free survival (PFS) rates (the number of people who still have cancer, but their disease does not progress) includes people who may have had some success with treatment, but the cancer has not disappeared completely. As used herein, the expression“short survival time” indicates that the patient will have a survival time that will be lower than the median (or mean) observed in the general population of patients suffering from said cancer. When the patient will have a short survival time, it is meant that the patient will have a“poor prognosis”. Inversely, the expression “long survival time” indicates that the patient will have a survival time that will be higher than the median (or mean) observed in the general population of patients suffering from said cancer. When the patient will have a long survival time, it is meant that the patient will have a“good prognosis”. As used herein, the term“tumor tissue sample” has its general meaning in the art and encompasses pieces or slices of tissue that have been removed including following a surgical tumor resection. The tumor tissue sample can be subjected to a variety of well-known post collection preparative and storage techniques (e.g., fixation, storage, freezing, etc.) prior to determining the cell densities. Typically the tumor tissue sample is fixed in formalin and embedded in a rigid fixative, such as paraffin (wax) or epoxy, which is placed in a mould and later hardened to produce a block which is readily cut. Thin slices of material can be then prepared using a microtome, placed on a glass slide and submitted e.g. to immunohistochemistry (using an IHC automate such as BenchMark® XT, for obtaining stained slides). The tumour tissue sample can be used in microarrays, called as tissue microarrays (TMAs). TMA consists of paraffin blocks in which up to 1000 separate tissue cores are assembled in array fashion to allow multiplex histological analysis. This technology allows rapid visualization of molecular targets in tissue specimens at a time, either at the DNA, RNA or protein level. TMA technology is described in W02004000992, US8068988, Olli et al 2001 Human Molecular Genetics, Tzankov et al 2005, Elsevier; Kononen et al 1198; Nature Medicine.

As used herein, the term“ SGMSF has its general meaning in the art and refers to the gene encoding the sphingomyelin synthase 1 (SMS1). NCBI gene ID for SGMS1 is Gene ID: 259230. An exemplary human nucleic acid sequence is represented by the NCBI reference sequence NM 147156.3. An exemplary human amino acid sequence for is represented by the NCBI reference sequence NP_671512.1.

In some embodiments, the expression level of SGMS1 in the tumor tissue sample is determined by immunohistochemistry. For example, the determination is performed by contacting the tumor tissue sample with a binding partner (e.g. an antibody) specific for SMS1. Immunohistochemistry typically includes the following steps i) fixing the tumor tissue sample with formalin, ii) embedding said tumor tissue sample in paraffin, iii) cutting said tumor tissue sample into sections for staining, iv) incubating said sections with the binding partner specific for SMS1, v) rinsing said sections, vi) incubating said section with a secondary antibody typically biotinylated and vii) revealing the antigen-antibody complex typically with avidin- biotin-peroxidase complex. Accordingly, the tumor tissue sample is firstly incubated with the binding partners having for SMS1. After washing, the labeled antibodies that are bound to SMAase2 are revealed by the appropriate technique, depending of the kind of label is borne by the labeled antibody, e.g. radioactive, fluorescent or enzyme label. . Exemplary labels include radioactive isotopes, fluorophores, ligands, chemiluminescent agents, enzymes, and combinations thereof. Non-limiting examples of labels that can be conjugated to primary and/or secondary affinity ligands include fluorescent dyes or metals (e.g. fluorescein, rhodamine, phycoerythrin, fluorescamine), chromophoric dyes (e.g. rhodopsin), chemiluminescent compounds (e.g. luminal, imidazole) and bioluminescent proteins (e.g. luciferin, luciferase), haptens (e.g. biotin). Multiple labelling can be performed simultaneously. Alternatively, the method of the present invention may use a secondary antibody coupled to an amplification system (to intensify staining signal) and enzymatic molecules. Such coupled secondary antibodies are commercially available, e.g. from Dako, EnVision system. Counterstaining may be used, e.g. Hematoxylin & Eosin, DAPI, Hoechst. Other staining methods may be accomplished using any suitable method or system as would be apparent to one of skill in the art, including automated, semi- automated or manual systems.

In some embodiments, the expression level of SGMS1 is determined by determining the quantity of mRNA encoding for SGMS1. Methods for determining the quantity of mRNA are well known in the art. For example the nucleic acid contained in the samples (e.g., cell or tissue prepared from the subject) is first extracted according to standard methods, for example using lytic enzymes or chemical solutions or extracted by nucleic-acid-binding resins following the manufacturer's instructions. The extracted mRNA is then detected by hybridization (e. g., Northern blot analysis, in situ hybridization) and/or amplification (e.g., RT-PCR). Other methods of Amplification include ligase chain reaction (LCR), transcription-mediated amplification (TMA), strand displacement amplification (SDA) and nucleic acid sequence based amplification (NASBA). Typically, the nucleic acid probes include one or more labels, for example to permit detection of a target nucleic acid molecule using the disclosed probes. In various applications, such as in situ hybridization procedures, a nucleic acid probe includes a label (e.g., a detectable label). A“detectable label” is a molecule or material that can be used to produce a detectable signal that indicates the presence or concentration of the probe (particularly the bound or hybridized probe) in a sample. Thus, a labeled nucleic acid molecule provides an indicator of the presence or concentration of a target nucleic acid sequence (e.g., genomic target nucleic acid sequence) (to which the labeled uniquely specific nucleic acid molecule is bound or hybridized) in a sample. A label associated with one or more nucleic acid molecules (such as a probe generated by the disclosed methods) can be detected either directly or indirectly. A label can be detected by any known or yet to be discovered mechanism including absorption, emission and/ or scattering of a photon (including radio frequency, microwave frequency, infrared frequency, visible frequency and ultra-violet frequency photons). Detectable labels include colored, fluorescent, phosphorescent and luminescent molecules and materials, catalysts (such as enzymes) that convert one substance into another substance to provide a detectable difference (such as by converting a colorless substance into a colored substance or vice versa, or by producing a precipitate or increasing sample turbidity), haptens that can be detected by antibody binding interactions, and paramagnetic and magnetic molecules or materials. Probes made using the disclosed methods can be used for nucleic acid detection, such as ISH procedures (for example, fluorescence in situ hybridization (FISH), chromogenic in situ hybridization (CISH) and silver in situ hybridization (SISH)) or comparative genomic hybridization (CGH). Numerous procedures for FISH, CISH, and SISH are known in the art. For example, procedures for performing FISH are described in U.S. Pat. Nos. 5,447,841; 5,472,842; and 5,427,932; and for example, in Pirlkel et ak, Proc. Natl. Acad. Sci. 83 :2934-2938, 1986; Pinkel et ak, Proc. Natl. Acad. Sci. 85:9138-9142, 1988; and Lichter et ak, Proc. Natl. Acad. Sci. 85:9664-9668, 1988. CISH is described in, e.g., Tanner et ak, Am. .1. Pathol. 157: 1467-1472, 2000 and U.S. Pat. No. 6,942,970. Additional detection methods are provided in U.S. Pat. No. 6,280,929. In some embodiments, the nCounter® Analysis system is used to detect intrinsic gene expression. The basis of the nCounter® Analysis system is the unique code assigned to each nucleic acid target to be assayed (International Patent Application Publication No. WO 08/124847, U.S. Patent No. 8,415,102 and Geiss et ak Nature Biotechnology. 2008. 26(3): 317-325; the contents of which are each incorporated herein by reference in their entireties).

Expression level of a gene may be expressed as absolute level or normalized level. Typically, levels are normalized by correcting the absolute level of a gene by comparing its expression to the expression of a gene that is not a relevant for determining the cancer stage of the subject, e.g., a housekeeping gene that is constitutively expressed. Suitable genes for normalization include housekeeping genes such as the actin gene ACTB, ribosomal 18S gene, GUSB, PGK1 and TFRC. This normalization allows the comparison of the level in one sample, e.g., a subject sample, to another sample, or between samples from different sources.

In some embodiments, the predetermined reference value is a threshold value or a cut off value. Typically, a "threshold value" or "cut-off value" can be determined experimentally, empirically, or theoretically. A threshold value can also be arbitrarily selected based upon the existing experimental and/or clinical conditions, as would be recognized by a person of ordinary skilled in the art. For example, retrospective measurement of expression level of the gene in properly banked historical subject samples may be used in establishing the predetermined reference value. The threshold value has to be determined 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). Typically, the optimal sensitivity and specificity (and so the threshold value) can be determined using a Receiver Operating Characteristic (ROC) curve based on experimental data. For example, after determining the expression level of the gene in a group of reference, one can use algorithmic analysis for the statistic treatment of the measured expression levels of the gene(s) in samples to be tested, and thus obtain a classification standard having significance for sample classification. The full name of ROC curve is receiver operator characteristic curve, which is also known as receiver operation characteristic curve. It is mainly used for clinical biochemical diagnostic tests. ROC curve is a comprehensive indicator that reflects the continuous variables of true positive rate (sensitivity) and false positive rate (1 -specificity). It reveals the relationship between sensitivity and specificity with the image composition method. A series of different cut-off values (thresholds or critical values, boundary values between normal and abnormal results of diagnostic test) are set as continuous variables to calculate a series of sensitivity and specificity values. Then sensitivity is used as the vertical coordinate and specificity is used as the horizontal coordinate to draw a curve. The higher the area under the curve (AUC), the higher the accuracy of diagnosis. On the ROC curve, the point closest to the far upper left of the coordinate diagram is a critical point having both high sensitivity and high specificity values. The AUC value of the ROC curve is between 1.0 and 0.5. When AUC>0.5, the diagnostic result gets better and better as AUC approaches 1. When AUC is between 0.5 and 0.7, the accuracy is low. When AUC is between 0.7 and 0.9, the accuracy is moderate. When AUC is higher than 0.9, the accuracy is quite high. This algorithmic method is preferably done with a computer. Existing software or systems in the art may be used for the drawing of the ROC curve, such as: MedCalc 9.2.0.1 medical statistical software, SPSS 9.0, ROCPOWER.SAS, DESIGNROC.FOR, MULTIREADER POWER.SAS, CREATE-ROC.SAS, GB STAT VIO.O (Dynamic Microsystems, Inc. Silver Spring, Md., USA), etc.

In some embodiments, the predetermined reference value is determined by carrying out a method comprising the steps of a) providing a collection of samples; b) providing, for each ample provided at step a), information relating to the actual clinical outcome for the corresponding subject (i.e. the duration of the survival); c) providing a serial of arbitrary quantification values; d) determining the expression level of the gene for each sample contained in the collection provided at step a); e) classifying said samples in two groups for one specific arbitrary quantification value provided at step c), respectively: (i) a first group comprising samples that exhibit a quantification value for level that is lower than the said arbitrary quantification value contained in the said serial of quantification values; (ii) a second group comprising samples that exhibit a quantification value for said level that is higher than the said arbitrary quantification value contained in the said serial of quantification values; whereby two groups of samples are obtained for the said specific quantification value, wherein the samples of each group are separately enumerated; f) calculating the statistical significance between (i) the quantification value obtained at step e) and (ii) the actual clinical outcome of the subjects from which samples contained in the first and second groups defined at step f) derive; g) reiterating steps f) and g) until every arbitrary quantification value provided at step d) is tested; h) setting the said predetermined reference value as consisting of the arbitrary quantification value for which the highest statistical significance (most significant) has been calculated at step g)·

For example the expression level of the gene has been assessed for 100 samples of 100 subjects. The 100 samples are ranked according to the expression level of the gene. Sample 1 has the highest level and sample 100 has the lowest level. A first grouping provides two subsets: on one side sample Nr 1 and on the other side the 99 other samples. The next grouping provides on one side samples 1 and 2 and on the other side the 98 remaining samples etc., until the last grouping: on one side samples 1 to 99 and on the other side sample Nr 100. According to the information relating to the actual clinical outcome for the corresponding subject, Kaplan Meier curves are prepared for each of the 99 groups of two subsets. Also for each of the 99 groups, the p value between both subsets was calculated. The predetermined reference value is then selected such as the discrimination based on the criterion of the minimum p value is the strongest. In other terms, the expression level of the gene corresponding to the boundary between both subsets for which the p value is minimum is considered as the predetermined reference value.

It should be noted that the predetermined reference value is not necessarily the median value of expression levels of the gene. Thus in some embodiments, the predetermined reference value thus allows discrimination between a poor and a good prognosis for a subject. Practically, high statistical significance values (e.g. low P values) are generally obtained for a range of successive arbitrary quantification values, and not only for a single arbitrary quantification value. Thus, in one alternative embodiment of the invention, instead of using a definite predetermined reference value, a range of values is provided. Therefore, a minimal statistical significance value (minimal threshold of significance, e.g. maximal threshold P value) is arbitrarily set and a range of a plurality of arbitrary quantification values for which the statistical significance value calculated at step g) is higher (more significant, e.g. lower P value) are retained, so that a range of quantification values is provided. This range of quantification values includes a "cut-off value as described above. For example, according to this specific embodiment of a "cut-off value, the outcome can be determined by comparing the expression level of the gene with the range of values which are identified. In some embodiments, a cut-off value thus consists of a range of quantification values, e.g. centered on the quantification value for which the highest statistical significance value is found (e.g. generally the minimum p value which is found). For example, on a hypothetical scale of 1 to 10, if the ideal cut-off value (the value with the highest statistical significance) is 5, a suitable (exemplary) range may be from 4-6. For example, a subject may be assessed by comparing values obtained by measuring the expression level of the gene, where values higher than 5 reveal a good prognosis and values less than 5 reveal a poor prognosis. In some embodiments, a subject may be assessed by comparing values obtained by measuring the expression level of the gene and comparing the values on a scale, where values above the range of 4-6 indicate a good prognosis and values below the range of 4-6 indicate a poor prognosis, with values falling within the range of 4-6 indicating an intermediate occurrence (or prognosis).

A further object of the present invention relates to a method of treating melanoma in a patient in need thereof comprising administering to the patient a therapeutically effective amount of an agent capable of restoring the intratumoral sphingomyelin/glucosylceramide homeostasis.

The therapeutic method of the present invention is particularly suitable for the treatment of patients characterized as having a poor prognosis by the diagnostic method as above described.

Accordingly, a further object of the present invention relates to a method of treating melanoma in a patient in need thereof comprising i) determining the expression level of SGMS1 in a tumor sample obtained from the patient ii) comparing the expression level determined at step i) with a predetermined reference value and iii) administering to the patient a therapeutically effective amount of an agent capable of restoring the intratumoral sphingomyelin/glucosylceramide homeostasis when the level determined at step i) is lower than the predetermined reference value.

In some embodiments, an agent capable of restoring the intratumoral sphingomyelin/glucosylceramide homeostasis consists in a SMS1 polypeptide or a polynucleotide encoding for a SMS1 polypeptide. Typically, the polynucleotide encoding for SMS1 is delivered with a vector. In its broadest sense, a "vector" is any vehicle capable of facilitating the transfer of the antisense oligonucleotide siRNA or ribozyme nucleic acid to the cells. Preferably, the vector transports the polynucleotide to cells with reduced degradation relative to the extent of degradation that would result in the absence of the vector. In general, the vectors useful in the invention include, but are not limited to, plasmids, phagemids, viruses, other vehicles derived from viral or bacterial sources that have been manipulated by the insertion or incorporation of the polynucleotide sequence of interest. Viral vectors are a preferred type of vector and include, but are not limited to polynucleotide sequences from the following viruses: retrovirus, such as moloney murine leukemia virus, harvey murine sarcoma virus, murine mammary tumor virus, and rouse sarcoma virus; adenovirus, adeno-associated virus; SV40-type viruses; polyoma viruses; Epstein-Barr viruses; papilloma viruses; herpes virus; vaccinia virus; polio virus; and RNA virus such as a retrovirus. One can readily employ other vectors not named but known to the art. Preferred viral vectors are based on non- cytopathic eukaryotic viruses in which non-essential genes have been replaced with the gene of interest. Non-cytopathic viruses include retroviruses (e.g., lentivirus), the life cycle of which involves reverse transcription of genomic viral RNA into DNA with subsequent proviral integration into host cellular DNA. Retroviruses have been approved for human gene therapy trials. Most useful are those retroviruses that are replication-deficient (i.e., capable of directing synthesis of the desired proteins, but incapable of manufacturing an infectious particle). Such genetically altered retroviral expression vectors have general utility for the high-efficiency transduction of genes in vivo. Standard protocols for producing replication-deficient retroviruses (including the steps of incorporation of exogenous genetic material into a plasmid, transfection of a packaging cell lined with plasmid, production of recombinant retroviruses by the packaging cell line, collection of viral particles from tissue culture media, and infection of the target cells with viral particles) are provided in KRIEGLER (A Laboratory Manual," W.H. Freeman C.O., New York, 1990) and in MURRY ("Methods in Molecular Biology," vol.7, Humana Press, Inc., Cliffton, N.J., 1991). Preferred viruses for certain applications are the adeno-viruses and adeno-associated viruses, which are double-stranded DNA viruses that have already been approved for human use in gene therapy. The adeno-associated virus can be engineered to be replication deficient and is capable of infecting a wide range of cell types and species. It further has advantages such as, heat and lipid solvent stability; high transduction frequencies in cells of diverse lineages, including hematopoietic cells; and lack of superinfection inhibition thus allowing multiple series of transductions. Reportedly, the adeno- associated virus can integrate into human cellular DNA in a site-specific manner, thereby minimizing the possibility of insertional mutagenesis and variability of inserted gene expression characteristic of retroviral infection. In addition, wild-type adeno-associated virus infections have been followed in tissue culture for greater than 100 passages in the absence of selective pressure, implying that the adeno-associated virus genomic integration is a relatively stable event. The adeno-associated virus can also function in an extrachromosomal fashion. Other vectors include plasmid vectors. Plasmid vectors have been extensively described in the art and are well known to those of skill in the art. See e.g., SANBROOK et ah, "Molecular Cloning: A Laboratory Manual," Second Edition, Cold Spring Harbor Laboratory Press, 1989. In the last few years, plasmid vectors have been used as DNA vaccines for delivering antigen-encoding genes to cells in vivo. They are particularly advantageous for this because they do not have the same safety concerns as with many of the viral vectors. These plasmids, however, having a promoter compatible with the host cell, can express a peptide from a gene operatively encoded within the plasmid. Some commonly used plasmids include pBR322, pUC18, pUC19, pRC/CMV, SV40, and pBlueScript. Other plasmids are well known to those of ordinary skill in the art. Additionally, plasmids may be custom designed using restriction enzymes and ligation reactions to remove and add specific fragments of DNA. Plasmids may be delivered by a variety of parenteral, mucosal and topical routes. For example, the DNA plasmid can be injected by intramuscular, intradermal, subcutaneous, or other routes. It may also be administered by intranasal sprays or drops, rectal suppository and orally. It may also be administered into the epidermis or a mucosal surface using a gene-gun. The plasmids may be given in an aqueous solution, dried onto gold particles or in association with another DNA delivery system including but not limited to liposomes, dendrimers, cochleate and mi croencapsul ati on .

In some embodiments, the agent capable of restoring the intratumoral sphingomyelin/glucosylceramide homeostasis is an inhibitor of glucosylceramide synthase.

As used herein, the term“glucosylceramide synthase” or“GCS” has its general meaning in the art and refers to a pivotal enzyme which catalyzes the conversion of ceramide to glucosylceramide. GCS is a transmembrane, type III integral protein localized in the cis/medial Golgi. Accordingly, the term“inhibitor of glucosylceramide synthase” refers to any compound capable of inhibiting the activity or expression of GCS. The term thus encompasses pharmacological inhibitors (e.g. small organic molecules) but also inhibitor of expression such as siRNA or antisense oligonucleotides.

A number of GCS inhibitors have been disclosed, for example, in U.S. Patent Nos. 5,302,609; 5,472,969; 5.525,616; 5,916,911; 5,945,442; 5,952,370; 6,030,995; 6,051,598; 6,255,336; 6,569,889; 6,610,703; 6,660,794; 6,855,830; 6,916,802; 7,253,185; 7,196,205; and 7,615,573. Additional GCS inhibitors and treatments are disclosed in WO 2008/150486; WO 2009/1 17150; WO 2013059119, WO 2010/014554; and WO 2012129084. For example said inhibitor of glucosylceramide synthase may be eliglustat tartrate (N-(( I R,2R)- 1 -(2,3 - dihydrobenzo[b] [ 1 ,4]dioxin-6-yl)- 1 -hydroxy-3 -(pyrrolidin- 1 -yl)propan-2- yl)octanamide, also known as Genz-1 12638) as described in Cox TM. Curr Opin Investing Drugs 2010 Oct; 11(10): 1 169-81 or peterschmitt MJ. Et al. Clin Pharmacol. 2010 Oct 25. Other examples also include D-threo-l-phenyl-2- decanoylamino-3-morpholino-l-propanol (PDMP) and derivatives thereof as described in Abe A. et al. Curr Drug Metab. 2001 Sep;2(3):331-8 such as D-threo- 3', 4'-ethylenedioxy-l- phenyl-2-palmitoylamino-3- pyrrolidino-l-propanol and D-threo-4'- hydroxy-l-phenyl-2- palmitoylamino-3- pyrrolidino-l-propanol. Other examples include piperidine derivatives as described in WO02/055498 and 3,4,5-piperidinetriol, 2- (hydroxymethyl)-l-[(4- (pentyloxy)phenyl)methyl]-, (2S,3S,4R,5S) such as decribed in US2007/0259918. In some embodiments, the inhibitor of GlcCer synthesis is selected from the group consisting of l-(3⁷ ,4⁷ -ethyl enedioxy)phenyl-2-nonanoylamino-3 -pyrrolidino-l- propanol; l-(3⁷ ,4⁷ -ethylenedioxy)phenyl-2-octanoylamino-3-pyrrolidino-l-propanol; D- threo-(lR,2R)-phenyl-2-decanoylamino-3-morpholino-l-propanol (PDMP) and analogs thereof including D-PDMP; PPMP (DL-threo-l-Phenyl-2-palmitoylamino-3-morpholino-l- propanol), D-threo-EtDO-P4; ((lR,2R)-nonanoic acid[2-(2^/ ,3⁷ -dihydro-benzo [1,4] dioxin- 6' -yl)-2-hydroxy-l -pyrrolidin- l-ylmethyl-ethyl]-amide-L-tartaric acid salt; CCG0203586 (1- hydroxy-3 -(pyrrolidin- l-yl)acetamide); Genz-529468; deoxynojiromycin-based GlcCer inhibitors; GZ-161; Genz-682452; EXEL-0346; OGT2378; and Genz-123346. In some embodiments, the deoxynojiromycin-based GlcCer inhibitor is N-(5⁷ -adamantane- 1 ' -yl- methoxy)-pentyl-l-deoxynojirimycin (AMP-DNM), or N-butyl-deoxynojirimycin (miglustat).

By a "therapeutically effective amount" is meant a sufficient amount of the agent capable of restoring the intratumoral sphingomyelin/glucosylceramide homeostasis for treating or reducing the symptoms at reasonable benefit/risk ratio applicable to any medical treatment. It will be understood that the total daily usage of the compounds and compositions of the present invention will be decided by the attending physician within the scope of sound medical judgment. The specific therapeutically effective dose level for any particular subject will depend upon a variety of factors including the disorder being treated and the severity of the disorder; activity of the specific compound employed; the specific composition employed, the age, body weight, general health, sex and diet of the subject; the time of administration, route of administration, and rate of excretion of the specific compound employed; the duration of the treatment; drugs used in combination with the active ingredients; and like factors well known in the medical arts. For example, it is well within the skill of the art to start doses of the compound at levels lower than those required to achieve the desired therapeutic effect and to gradually increase the dosage until the desired effect is achieved. However, the daily dosage of the products may be varied over a wide range from 0.01 to 1,000 mg per adult per day. Typically, the compositions contain 0.01, 0.05, 0.1, 0.5, 1.0, 2.5, 5.0, 10.0, 15.0, 25.0, 50.0, 100, 250 and 500 mg of the active ingredient for the symptomatic adjustment of the dosage to the subject to be treated. A medicament typically contains from about 0.01 mg to about 500 mg of the active ingredient, typically from 1 mg to about 100 mg of the active ingredient. An effective amount of the drug is ordinarily supplied at a dosage level from 0.0002 mg/kg to about 20 mg/kg of body weight per day, especially from about 0.001 mg/kg to 7 mg/kg of body weight per day.

Typically the agent capable of restoring the intratumoral sphingomyelin/glucosylceramide homeostasis is combined with pharmaceutically acceptable excipients, and optionally sustained-release matrices, such as biodegradable polymers, to form pharmaceutical compositions. The term "Pharmaceutically" or "pharmaceutically acceptable" refers to molecular entities and compositions that do not produce an adverse, allergic or other untoward reaction when administered to a mammal, especially a human, as appropriate. A pharmaceutically acceptable carrier or excipient refers to a non-toxic solid, semi-solid or liquid filler, diluent, encapsulating material or formulation auxiliary of any type. The carrier can also be a solvent or dispersion medium containing, for example, water, ethanol, polyol (for example, glycerol, propylene glycol, and liquid polyethylene glycol, and the like), suitable mixtures thereof, and vegetables oils. The proper fluidity can be maintained, for example, by the use of a coating, such as lecithin, by the maintenance of the required particle size in the case of dispersion and by the use of surfactants. The prevention of the action of microorganisms can be brought about by various antibacterial and antifungal agents, for example, parabens, chlorobutanol, phenol, sorbic acid, thimerosal, and the like. In many cases, it will be preferable to include isotonic agents, for example, sugars or sodium chloride. Prolonged absorption of the injectable compositions can be brought about by the use in the compositions of agents delaying absorption, for example, aluminium monostearate and gelatin. In the pharmaceutical compositions of the present invention, the active ingredients of the invention can be administered in a unit administration form, as a mixture with conventional pharmaceutical supports. Suitable unit administration forms comprise oral-route forms such as tablets, gel capsules, powders, granules and oral suspensions or solutions, sublingual and buccal administration forms, aerosols, implants, subcutaneous, transdermal, topical, intraperitoneal, intramuscular, intravenous, subdermal, transdermal, intrathecal and intranasal administration forms and rectal administration forms.

The invention will be further illustrated by the following figures and examples. However, these examples and figures should not be interpreted in any way as limiting the scope of the present invention.

FIGURES:

Figure 1: SMS1 is frequently downregulated in cancer tissues. A, cDNA samples isolated from normal (N) and tumor (T) tissues from the same patient were compared. Hybridization with a SGMS1 probe was carried out first (left panel); the same array was stripped and hybridized with a probe to ubiquitin (Ub) (right panel). B, The ratios T/N and N/T between standardized samples for each pair was calculated and the data expressed as a fold increase (T/N) (left panel) or fold decrease (N/T) (right panel) of SMS1 expression in tumor vs normal tissues are depicted.

Figure 2: SMS1 downregulation in melanoma is associated with a worse prognosis.

A-C, SMS1 expression was analysed in 3 different cohorts from Oncomine in normal Skin (n=4), primary (P; n=14) and metastatic (M; n=39) melanoma (Ricker et al, #35) (A); in nevus (n=18) and primary melanoma (P; n=45) (Talantov et al, #36) (B); in nevus (n=9), primary (P; n=6) and metastatic (M ; n=19) melanoma (Haqq et al, #37) (C). D, SMS1 expression was analysed in various cancer type cohorts from cbioportal. Missense and frameshift mutations are depicted. E, Analysis of overall survival in metastatic melanoma patients from the TCGA melanoma cohort (n=342), exhibiting high (80th percentile; n=68) and low (20th percentile; n=68) SGMS1 expression in melanoma samples.

EXAMPLE:

Material & Methods

Macroarray experiment: Cancer Profiling array II (#631777) including patient-derived cDNA tumor and non-tumor samples was purchased from BD Biosciences Clontech. Human samples were collected in accordance with all applicable laws and regulations in an ethical manner. Membrane was successively hybridized according to the manufacturer’s instructions with SMS1 and ubiquitin 32P-labeled probes generated using a random nonamer primer labeling procedure (# RPN1604, Amersham Biosciences). The membrane was exposed to an intensifying screen that was developed using Phosphorlmager and Image Quant software.

SGMS1, SGMS2 and UGCG expression and mutations in human melanoma: SGMS1, SGMS2 and UGCG expression was evaluated from Oncomine database (Riker et al, 2008, Talantov et al., 2005, Haqq et al., 2005) and the cancer genome atlas (TCGA) melanoma (Cancer Genome Atlas, 2015). TCGA genomic and clinical data were downloaded from the UCSC cancer genome browser project (https://genomecancer.ucsc.edu). The analysis population consisted of 342 patients with distant metastasis for whom RNAseq and clinical data overlap. All survival times were calculated from the date of specimen procurement and were estimated by the Kaplan Meier method with 95% confidence intervals (Cl). Univariates analyses were performed using Cox proportional hazards model. Alternatively, SGMS1, SGMS2 and UGCG mutation analyses in human melanoma were assessed on cBioportal (http://www.cbioportal.org/) (Gao et al., 2013, Cerami et al., 2012).

SGMS1 methylation analysis: The correlation between SGMS1 expression and methylation status of SGMS1 CpGs in metastatic patient samples was analysed using the TCGA melanoma RNA-seq and DNA methylation Illumina datasets. For each analysed CpG, the rho values, indicating the Spearman’s rank correlation coefficients between the CpG methylation and the SGMS1 expression, are reported. The organization of the SGMS1 locus is depicted in Figure 2A as previously described (Vladychenskaya et al., 2004).

Melanoma cell lines: Human melanoma cell lines (M249, SKMEL28, A375, WM9, WM35, WM115, WM266, WM793, WM1346, C0L0829, G361) were from ATCC or Wistar institute.

Determination of in situ SMS and GCS activities: 1x106 melanoma cells were incubated with 2.5 mM C6-NBD-ceramide (Sigma) solubilized in ethanol and SMS and GCS activities were measured as previously described (Lafont et al., 2010, Bilal et al., 2017a).

Analysis of sphingolipids: SLs were analysed from 1.106 melanoma cells by liquid chromatography/mass spectrometry (LC/MS) as previously described (Bilal et al, 2017b). qRT-PCR analysis : Total RNA was reverse-transcribed using 1 pg of input RNA and random primers (Superscript II, Invitrogen). qRT-PCR reactions were performed in duplicate on StepOne apparatus (Applied Biosystems) using SYBR Green (QuantiTect, Qiagen) as fluorescent detection dye. Results were quantified and mRNA expression for each target gene (UGCG, SGMS1 or SGMS2) was determined by normalization to reference genes (b-actin and GAPDH) using the ACt method. Primers for UGCG and reference genes were from Qiagen. Primers for SGMS1 and SGMS2 were from Sigma (Lafont et al., 2010).

Statistics and reproducibility: Statistical significance of differences between groups was evaluated using the Graph-Pad Prism 7 software. For multiple comparisons, an Anova test was used. Wilcoxon test was used in Figure IB. Differences were considered to be statistically significant when p<0.05 (*p<0.05; **p<0.01; ***p<0.001).

Results

SMS1 downregulation in melanoma is associated with SL metabolism reprogramming

We initially performed a macroarray to evaluate the expression of SMS1 in matched tumour and non-tumour samples from the same patients (Figure 1A). The data analysis with a threshold of 1.5 showed that, whereas SMS1 was up-regulated in 11% of tumor samples, it was down-regulated in 46% of tumor samples (table 1). As a matter of fact, SMS1 was most frequently down-regulated in vulva (5 out of 5), testis (9 out of 10) and skin (9 out of 10) cancers, including melanoma (6 out of 7) (Figure IB and table 1). Accordingly, our transcriptomic analysis in 3 different cohorts from published database indicates that SGMS1 was downregulated in primary and metastatic human melanoma as compared to normal skin and nevus (Figure 2A-2C) (Riker et al, 2008, Talantov et al., 2005, Haqq et al, 2005). In contrast, the expression of SGMS2 and UGCG, encoding SMS2 and GCS, respectively, remained unchanged (not shown). We next evaluated the expression of SGMS1 in various cancer types from the TCGA database. Strikingly, melanoma exhibited the lowest expression of SGMS1 (Figure 2D). Moreover, melanoma expressed SGMS2 at rather low levels, while expressing UGCG at high levels (not shown). In metastatic melanoma from the TCGA, the expression of UGCG was significantly higher than that of SGMS1 and SGMS2 (not shown). Accordingly, melanoma cells exhibited low SGMS1 and SGMS2 expression, while they expressed UGCG at higher levels (not shown). We next evaluated the SL metabolism signature in human melanoma cell lines. Whereas four melanoma cell lines exhibited a higher proportion of SM, six were enriched in GlcCer (not shown). Accordingly, in situ enzyme activity was significantly higher for GCS than for SMS in the cell lines with high GlcCer proportion only (not shown). Consequently, endogenous intracellular levels of GlcCer were greater than SM and other SL species as evaluated by mass spectrometry for those six melanoma cell lines (not shown). Of note, neither the mutation status (Bairoch, 2018) nor the origin of the melanoma cell lines (i.e., from radial or vertical growth phase or metastasis) were associated with a specific SL signature (not shown).

SMS1 downregulation in human melanoma is associated with a worse prognosis.

To get insight into the molecular mechanisms that may account for SMS1 downregulation and/or inhibition of enzyme activity, we evaluated SGMS1 mutation and methylation status in the public databases of melanoma. Whereas SGMS2 and UGCG were mutated with low frequency, SGMS1 exhibited a higher mutation rate in the coding sequence (not shown). Most of the mutations were missense mutations and some of them affected residues in the catalytic domain (not shown). In the TCGA melanoma cohort, 7.7% of the 287 sequenced samples were mutated (16 missense mutations, 2 nonsense mutations and 4 deep deletions). One of the nonsense mutations (W309*) was also found in one specimen from another melanoma cohort (not shown). The other nonsense mutation (R387*) was also found in colorectal carcinoma, sarcoma and uterus carcinoma (not shown).

To delineate the effect of DNA methylation on the regulation of SGMS1 expression, we analysed the TCGA metastatic melanomas. Among the 50 SGMS1 Illumina 450K probes with workable data, the DNA methylation level of 33 probes displayed a significant correlation with expression. Ten probes out of the 14 located in the CpG island 1 and its shores, as well as 3 out of the 3 in the CpG island 2 and its shores, both containing putative promoter sequences, were inversely correlated with the expression level. In contrast, 13 CpG out of the 16 located outside CpG islands and shores were positively correlated with the expression (not shown). Thus, hypermethylation of CpG islands and hypomethylation events in open sea were significantly associated with the decrease in SGMS1 expression, indicating the regulation of SMS1 expression in metastatic melanoma might rely, at least partly, on DNA methylation of the SGMS1 locus.

Finally, the clinical outcome in metastatic melanoma patients exhibiting low (20th percentile, medium (between the 20th and 80th percentile), high (80th percentile) SGMS1, SGMS2 and UGCG expression was analysed in the TCGA cohort. Whereas UGCG and SGMS2 expression did not impact on overall survival (not shown), low SGMS1 expression was statistically associated with shortened overall survival (Figure 2E).

Collectively, our data indicate that melanoma exhibit a SL metabolism reprogramming associated with SMS1 downregulation, which constitutes a worse-prognosis biomarker.

Since GCS was strongly active in melanoma, we sought to evaluate the consequence of

GCS inhibition on SL metabolism in melanoma. We pre-incubated melanoma cells for 72 hours with Eliglustat, a selective GCS inhibitor, which is used in the clinic for the treatment of Gaucher's disease. Whereas Eliglustat reduced GlcCer levels, it concomitantly enhanced SM and ceramide content (not shown). Miglustat, another GCS inhibitor used for Gaucher disease therapy, also modified SL content (not shown).

Collectively, our data indicate that melanoma exhibit a SL metabolism reprogramming associated with SMS1 downregulation, which constitutes a worse-prognosis biomarker and GCS inhibition restores SM/GlcCer homeostasis. Table 1 SGMS1 gene upregulation and downregulation in cancer tissues of the cancer profiling array.

REFERENCES:

Throughout this application, various references describe the state of the art to which this invention pertains. The disclosures of these references are hereby incorporated by reference into the present disclosure. ALBINET, V., BATS, M. L., HUWILER, A., ROCHAIX, P., CHEVREAU, C., SEGUI, B., LEVADE, T. & ANDRIEU-ABADIE, N. 2014. Dual role of sphingosine kinase-1 in promoting the differentiation of dermal fibroblasts and the dissemination of melanoma cells. Oncogene, 33, 3364-73.

BAIROCH, A. 2018. The Cellosaurus, a Cell-Line Knowledge Resource. J Biomol Tech, 29, 25-38.

BILAL, F., PERES, M., ANDRIEU-ABADIE, N., LEVADE, T., BADRAN, B., DAHER, A. & SEGUI, B. 2017a. Method to Measure Sphingomyelin Synthase Activity Changes in Response to CD95L. Methods Mol Biol, 1557, 207-212.

BILAL, F., PERES, M., LE FAOUDER, P., DUPUY, A., BERTRAND-MICHEL, T, ANDRIEU-ABADIE, N., LEVADE, T., BADRAN, B., DAHER, A. & SEGUI, B. 2017b. Liquid Chromatography-High Resolution Mass Spectrometry Method to Study Sphingolipid Metabolism Changes in Response to CD95L. Methods Mol Biol, 1557, 213-217.

CANCER GENOME ATLAS, N. 2015. Genomic Classification of Cutaneous Melanoma. Cell, 161, 1681-96.

CERAMI, E., GAO, T, DOGRUSOZ, U., GROSS, B. E., SUMER, S. O., AKSOY, B. A., JACOBSEN, A., BYRNE, C. J., HEUER, M. L., LARS SON, E., ANTIPIN, Y., REVA, B., GOLDBERG, A. P., SANDER, C. & SCHULTZ, N. 2012. The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data. Cancer Discov, 2, 401- 4.

COLIE, S., VAN VELDHOVEN, P. P., KEDJOUAR, B., BEDIA, C., ALBINET, V., SORLI, S. C., GARCIA, V., DJAVAHERI-MERGNY, M., BAUVY, C., CODOGNO, P., LEVADE, T. & ANDRIEU-ABADIE, N. 2009. Disruption of sphingosine 1-phosphate lyase confers resistance to chemotherapy and promotes oncogenesis through Bcl-2/Bcl-xL upregulation. Cancer Res, 69, 9346-53.

DENG, W., LI, R., GUERRERA, M., LIU, Y. & LADISCH, S. 2002. Transfection of glucosylceramide synthase antisense inhibits mouse melanoma formation. Glycobiology, 12, 145-52.

EROGLU, Z. & RIBAS, A. 2016. Combination therapy with BRAF and MEK inhibitors for melanoma: latest evidence and place in therapy. Ther Adv Med Oncol, 8, 48-56.

GAO, J., AKSOY, B. A., DOGRUSOZ, U., DRESDNER, G, GROSS, B., SUMER, S. O., SUN, Y., JACOBSEN, A., SINHA, R., LARSSON, E., CERAMI, E., SANDER, C. & SCHULTZ, N. 2013. Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. Sci Signal, 6, pi 1. HANNUN, Y. A. 1996. Functions of ceramide in coordinating cellular responses to stress. Science, 274, 1855-9.

HANNUN, Y. A. & OBEID, L. M. 2002. The Ceramide-centric universe of lipid- mediated cell regulation: stress encounters of the lipid kind. J Biol Chem, 277, 25847-50.

HAQQ, C., NOSRATI, M., SUDILOVSKY, D., CROTHERS, J., KHODABAKHSH, D., PULLIAM, B. L., FEDERMAN, S., MILLER, J. R., 3RD, ALLEN, R. E., SINGER, M. F, LEONG, S. P., LJUNG, B. M., SAGEBIEL, R. W. & KASHANI-SABET, M. 2005. The gene expression signatures of melanoma progression. Proc Natl Acad Sci USA, 102, 6092-7.

HAYASHI, Y., NEMOTO-SASAKI, Y., MATSUMOTO, N., HAMA, K., TANIKAWA, T., OKA, S., SAEKI, T., KUMASAKA, T., KOIZUMI, T., ARAI, S., WAD A, T, YOKOYAMA, K., SUGIURA, T. & YAMASHITA, A. 2018. Complex formation of sphingomyelin synthase 1 with glucosylceramide synthase increases sphingomyelin and decreases glucosylceramide levels. J Biol Chem, 293, 17505-17522.

HODIS, E., WATSON, I. R., KRYUKOV, G. V., AROLD, S. T., IMIELINSKI, M., THEURILLAT, J. P., NICKERSON, E., AUCLAIR, D., LI, L., PLACE, C., DICARA, D., RAMOS, A. H., LAWRENCE, M. S., CIBULSKIS, K., SIVACHENKO, A., VOET, D., SAKSENA, G, STRANSKY, N., ONOFRIO, R. C., WINCKLER, W., ARDLIE, K., WAGLE, N., WARGO, T, CHONG, K., MORTON, D. L., STEMKE-HALE, K., CHEN, G, NOBLE, M., MEYERSON, M., LADBURY, J. E., DAVIES, M. A., GERSHENWALD, J. E., WAGNER, S. N., HOON, D. S., SCHADENDORF, D., LANDER, E. S., GABRIEL, S. B., GETZ, G., GARRAWAY, L. A. & CHIN, L. 2012. A landscape of driver mutations in melanoma. Cell, 150, 251-63.

HUITEMA, K., VAN DEN DIKKENBERG, T, BROUWERS, J. F. & HOLTHUIS, J. C. 2004. Identification of a family of animal sphingomyelin synthases. Embo J, 23, 33-44.

LAFONT, E., MILHAS, D., CARPENTIER, S., GARCIA, V., JIN, Z. X., UMEHARA, H., OKAZAKI, T., SCHULZE-OSTHOFF, K., LEVADE, T., BENOIST, H. & SEGUI, B. 2010. Caspase-mediated inhibition of sphingomyelin synthesis is involved in FasL-triggered cell death. Cell Death Differ, 17, 642-54.

LAVIE, Y., CAO, H., VOLNER, A., LUCCI, A., HAN, T. Y., GEFFEN, V., GIULIANO, A. E. & CABOT, M. C. 1997. Agents that reverse multidrug resistance, tamoxifen, verapamil, and cyclosporin A, block glycosphingolipid metabolism by inhibiting ceramide glycosylation in human cancer cells. J Biol Chem, 272, 1682-7.

LECLERC, J., GARANDEAU, D., PANDIANI, C., GAUDEL, C., BILLE, K., NOTTET, N., GARCIA, V., COLOSETTI, P., PAGNOTTA, S., BAHADORAN, P., TONDEUR, G, MOGRABI, B., DALLE, S., CARAMEL, I, LEVADE, T., BALLOTTI, R, ANDRIEU-ABADIE, N. & BERTOLOTTO, C. 2018. Lysosomal acid ceramidase ASAH1 controls the transition between invasive and proliferative phenotype in melanoma cells. Oncogene, in press.

LIU, Y. Y., GUPTA, V., PATWARDHAN, G. A., BHINGE, K., ZHAO, Y., BAO, J., MEHENDALE, H., CABOT, M. C., LI, Y. T. & JAZWINSKI, S. M. 2010. Glucosylceramide synthase upregulates MDRl expression in the regulation of cancer drug resistance through cSrc and beta-catenin signaling. Mol Cancer, 9, 145.

LIU, Y. Y., HAN, T. Y., YU, J. Y., BITTERMAN, A., LE, A., GIULIANO, A. E. & CABOT, M. C. 2004. Oligonucleotides blocking glucosylceramide synthase expression selectively reverse drug resistance in cancer cells. J Lipid Res, 45, 933-40.

MOORTHI, S., BURNS, T. A., YU, G. Q. & LUBERTO, C. 2018. Bcr-Abl regulation of sphingomyelin synthase 1 reveals a novel oncogenic-driven mechanism of protein up- regulation. FASEB J, 32, 4270-4283.

MRAD, M., IMBERT, C., GARCIA, V., RAMBOW, F., THERVILLE, N., CARPENTIER, S., SEGUI, B., LEVADE, T., AZAR, R., MARINE, J. C., DIAB-ASSAF, M., COLACIOS, C. & ANDRIEU-ABADIE, N. 2016. Downregulation of sphingosine kinase- 1 induces protective tumor immunity by promoting Ml macrophage response in melanoma. Oncotarget, 7, 71873-71886.

OGRETMEN, B. & HANNUN, Y. A. 2004. Biologically active sphingolipids in cancer pathogenesis and treatment. Nat Rev Cancer, 4, 604-16.

RIKER, A. T, ENKEMANN, S. A., FODSTAD, O., LIU, S., REN, S., MORRIS, C., XI, Y., HOWELL, P., METGE, B., SAMANT, R. S., SHEVDE, L. A., LI, W., ESCHRICH,

S., DAUD, A., JU, J. & MATTA, J. 2008. The gene expression profiles of primary and metastatic melanoma yields a transition point of tumor progression and metastasis. BMC Med Genomics, 1, 13.

SEGUI, B., ANDRIEU-ABADIE, N., JAFFREZOU, J. P., BENOIST, H. & LEVADE,

T. 2006. Sphingolipids as modulators of cancer cell death: potential therapeutic targets. Biochim Biophys Acta, 1758, 2104-20.

SHARMA, P., HU-LIESKOVAN, S., WARGO, J. A. & RIBAS, A. 2017. Primary, Adaptive, and Acquired Resistance to Cancer Immunotherapy. Cell, 168, 707-723.

SORLI, S. C., COLIE, S., ALBINET, V., DUBRAC, A., TOURIOL, C., GUILBAUD, N., BEDIA, C., FABRIAS, G, CASAS, T, SEGUI, B., LEVADE, T. & ANDRIEU-ABADIE, N. 2013. The nonlysosomal beta-glucosidase GBA2 promotes endoplasmic reticulum stress and impairs tumorigenicity of human melanoma cells. FASEB J, 27, 489-98.

SUN, Y. L., ZHOU, G. Y., LI, K. N., GAO, P., ZHANG, Q. H., ZHEN, J. H., BAI, Y. H. & ZHANG, X. F. 2006. Suppression of glucosylceramide synthase by RNA interference reverses multidrug resistance in human breast cancer cells. Neoplasma, 53, 1-8.

TALANTOV, D., MAZUMDER, A., YU, J. X., BRIGGS, T., JIANG, Y., BACKUS, J., ATKINS, D. & WANG, Y. 2005. Novel genes associated with malignant melanoma but not benign melanocytic lesions. Clin Cancer Res, 11, 7234-42.

VELDMAN, R. J., MITA, A., CUVILLIER, O., GARCIA, V., KLAPPE, K., MEDIN, J. A., CAMPBELL, J. D., CARPENTER, S., KOK, J. W. & LEVADE, T. 2003. The absence of functional glucosylceramide synthase does not sensitize melanoma cells for anticancer drugs. FASEB J, 17, 1144-6.

VLADYCHENSKAYA, I. P., DERGUNOVA, L. V., DMITRIEVA, V. G. & LIMBORSKA, S. A. 2004. Human gene MOB: structure specification and aspects of transcriptional activity. Gene, 338, 257-65.

WEISS, M., HETTMER, S., SMITH, P. & LADISCH, S. 2003. Inhibition of melanoma tumor growth by a novel inhibitor of glucosylceramide synthase. Cancer Res, 63, 3654-8.

YAMAOKA, S., MIYAJI, M., KITANO, T., UMEHARA, H. & OKAZAKI, T. 2004. Expression cloning of a human cDNA restoring sphingomyelin synthesis and cell growth in sphingomyelin synthase-defective lymphoid cells. J Biol Chem, 279, 18688-93.

Claims

CLAIMS:

1. A method for predicting the survival of a patient suffering from melanoma comprising i) determining the expression level of SGMS1 in a tumor sample obtained from the patient, ii) comparing the expression level determined at step i) with a predetermined reference value and iii) and concluding that the patient will have short survival time when the level determined at step i) is lower than the predetermined reference value or concluding that the patient will have long survival time when the expression level determined at step i) is higher than the predetermined reference value.

2. The method of claim 1 wherein the expression level of SGMS1 is determined by immunohistochemistry or by determining the quantity of mRNA encoding for SMS1.

3. A method of treating melanoma in a patient in need thereof comprising administering to the patient a therapeutically effective amount of an agent capable of restoring the intratumoral sphingomyelin/glucosylceramide homeostasis.

4. The method of claim 3 comprising i) determining the expression level of SGMS1 in a tumor sample obtained from the patient ii) comparing the expression level determined at step i) with a predetermined reference value and iii) administering to the patient a therapeutically effective amount of an agent capable of restoring the intratumoral sphingomyelin/glucosylceramide homeostasis when the level determined at step i) is lower than the predetermined reference value.

5. The method of claim 3 wherein the agent capable of restoring the intratumoral sphingomyelin/glucosylceramide homeostasis consists in a SMS1 polypeptide or a polynucleotide encoding for a SMS1 polypeptide.

6. The method of claim 3 wherein the agent capable of restoring the intratumoral sphingomyelin/glucosylceramide homeostasis is an inhibitor of glucosylceramide synthase.

7. The method of claim 6 wherein the inhibitor of glucosylceramide synthase is eliglustat tartrate or miglustat.