WO2021211057A1 - Procédé de prédiction de la réactivité à une thérapie du cancer - Google Patents

Procédé de prédiction de la réactivité à une thérapie du cancer Download PDF

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WO2021211057A1
WO2021211057A1 PCT/SG2021/050203 SG2021050203W WO2021211057A1 WO 2021211057 A1 WO2021211057 A1 WO 2021211057A1 SG 2021050203 W SG2021050203 W SG 2021050203W WO 2021211057 A1 WO2021211057 A1 WO 2021211057A1
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cancer
rna
editing
level
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Ömer AN
Leilei Chen
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National University Of Singapore
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61K—PREPARATIONS FOR MEDICAL, DENTAL OR TOILETRY PURPOSES
    • A61K31/00—Medicinal preparations containing organic active ingredients
    • A61K31/28—Compounds containing heavy metals
    • A61K31/282—Platinum compounds
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61K—PREPARATIONS FOR MEDICAL, DENTAL OR TOILETRY PURPOSES
    • A61K33/00—Medicinal preparations containing inorganic active ingredients
    • A61K33/24—Heavy metals; Compounds thereof
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61P—SPECIFIC THERAPEUTIC ACTIVITY OF CHEMICAL COMPOUNDS OR MEDICINAL PREPARATIONS
    • A61P35/00—Antineoplastic agents
    • 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
    • C12Q2600/112—Disease subtyping, staging or classification
    • 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
    • C12Q2600/156—Polymorphic or mutational markers

Definitions

  • the invention relates generally to the field of oncology.
  • the invention relates to a method of predicting the responsiveness of a cancer subject to a cancer therapy.
  • Platinum-based chemotherapeutic compounds such as cisplatin, carboplatin and oxaliplatin, are commonly used in the treatment of cancers that include testicular, ovarian, cervical, lung, liver, colorectal, gastric and head and neck cancer. These compounds bind to DNA and induce DNA adducts, which can lead to apoptosis in cancer cells, thus eliminating cancer cells in the patient. There is, however, a problem with poor responsiveness towards these compounds in some patients. This may be due to intrinsic or acquired resistance to such compounds in some tumours, the mechanism of which is not clearly understood. It is therefore preferable to be able to screen for patients who are likely to be responsive to treatment with these compounds. Alternative treatment strategies may have to be adopted for patients who are unlikely to respond well to such therapies.
  • a method of predicting the responsiveness of a cancer subject to a cancer therapy comprising determining the level of RNA-editing events in a sample obtained from the subject, wherein an increased level of RNA-editing events as compared to a reference indicates that the subject is likely to be responsive towards the cancer therapy.
  • a method of treating a cancer subject found likely to be responsive to a cancer therapy comprising: a) determining the level of RNA-editing events in a sample obtained from the subject, wherein an increased level of RNA editing events as compared to a reference indicates that the subject is likely to be responsive towards the cancer therapy; and b) treating the subject found likely to be responsive to the cancer therapy.
  • a method of stratifying a subject into a likely responder or non responder of a cancer therapy comprising determining the level of RNA- editing events in a sample obtained from the subject, wherein an increased level of RNA editing events as compared to a reference indicates that the subject is a likely responder of the cancer therapy and wherein an unchanged or decrease level of RNA-editing events indicates that the subject is a likely non-responder of the cancer therapy.
  • a method for managing treatment of a cancer subject with a cancer therapy comprising a) selecting a cancer subject for treating with the therapy on the basis that the subject is a likely responder to the therapy, or selecting a subject for not treating with the therapy on the basis that the subject is a likely non responder to the therapy; and b) treating or not treating the subject with the therapy based on the selection, wherein the selection is based on the stratification method as defined herein.
  • a method for predicting treatment outcome of a cancer subject with a cancer therapy comprising determining the level of RNA-editing events in a sample obtained from the subject, wherein an increased level of RNA editing events as compared to a reference indicates that the subject is likely to have a positive treatment outcome with the cancer therapy.
  • Disclosed herein is a method of identifying a subject who is suitable for treatment with a cancer therapy, the method comprising determining the level of RNA-editing events in a sample obtained from the subject, wherein an increased level of RNA editing events as compared to a reference indicates that the subject is likely to have a positive treatment outcome with the cancer therapy and therefore suitable for treatment with the cancer therapy.
  • a kit for predicting the responsiveness of a cancer subject to a cancer therapy the kit comprising one or more pairs of primers as described in Table 2 for determining the level of RNA-editing events in a sample obtained from the subject.
  • an array for predicting the responsiveness of a cancer subject to a cancer therapy comprising one or more nucleic acid probes for determining the level of RNA-editing events in a sample obtained from the subject.
  • Figure 1 RNA editing as a prognostic factor in advanced gastric cancer.
  • A) Number of high confidence RNA editing sites detected in the indicated across the patient samples.
  • B) Unbiased clustering of patient samples based on RNA editing levels of 780 editing sites detected in all patient samples (k-means, n 2).
  • Figure 2 Response to chemotherapy predicts overall survival in advanced GC patients. Overall survival plot for 3 response groups (PD, SD and PR) (log rank test).
  • Figure 3 Selection of a panel of 50 RNA editing sites as a 29-gene RNA editing (RE) signature for predicting overall response in advanced GC.
  • PD, SD and PR 3 response groups (PD, SD and PR) are defined as 0, 1, and 2 respectively, positive correlation denotes the higher the editing level the higher the response value (i.e. better response).
  • B) k-means clustering of patients (n 55 with available overall response information) based on RNA editing levels of 50 sites.
  • FIG. 4 Derivation of an RNA Editing (RE) score to accurately predict chemotherapy response in advanced GC.
  • Figure 5 Validation of RE signature in GC cell lines.
  • C) Editing levels of 26 sites from the panel of RE signature quantified by Sanger sequencing. Numbers in cells denote the percentage of editing levels and coloring shows the relative gradient across the row (scale). Black cells denote undetectable editing level. The Pearson correlation coefficient between the average IC50 values in A) and average RNA editing levels in C) is r -0.58.
  • Figure 6 Validation of RE signature in TCGA STAD cohort. Distribution (violin plots) and performance (ROC curves) of RE scores in TCGA STAD cohort stratified by response type in Stage IV patients. For score calculation, 50 sites in RE signature and their editing levels in TCGA patients are used wherever available and at least 8 sites were required to be edited to calculate the score.
  • Primary response A) refers to the “primary_therapy_outcome” and follow-up response B) denotes the “follow- up_treatment_success” as reported by TCGA.
  • Non-responder stable/progressive disease
  • Responder partial/complete remission
  • STAD stomach adenocarcinoma
  • TPR true positive rate
  • FPR false positive rate
  • AUC area under the curve p- values are shown for Wilcoxon rank-sum test.
  • a method of predicting the responsiveness of a cancer subject to a cancer therapy comprising determining the level of RNA-editing events in a sample obtained from the subject, wherein an increased level of RNA-editing events as compared to a reference indicates that the subject is likely to be responsive towards the cancer therapy.
  • RNA editing which is an epigenetic mechanism, introduces changes in the RNA sequences encoded by the genome, contributing to “RNA mutations”.
  • A-to-I Adenosine deaminases acting on RNA (ADAR) are enzymes responsible for binding to double stranded RNA (dsRNA) and converting A to I by deamination.
  • dsRNA double stranded RNA
  • RNA editing score (RE score) was derived.
  • PR partial response
  • SD stable disease
  • PD progressive disease
  • This 29-gene RNA editing signature can therefore be used to stratify patients with advanced gastric and predict benefit from chemotherapy. In particular, it can be used to predict clinical benefit of platinum-based chemotherapy in patients with advanced gastric cancer with up to 84% accuracy.
  • the cancer therapy may refer to chemotherapy, radiotherapy and immunotherapy.
  • cancer therapy is chemotherapy.
  • useful classes of anti-cancer agents include chemotherapeutic agents, representative examples of which include anti tubulin agents, auristatins, DNA minor groove binders, DNA replication inhibitors, alkylating agents (e.g., platinum complexes such as cis-platin, mono(platinum), bis(platinum) and tri-nuclear platinum complexes and carboplatin), anthracyclines, antibiotics, antifolates, antimetabolites, calmodulin inhibitors, chemotherapy sensitizers, duocarmycins, etoposides, fluorinated pyrimidines, ionophores, lexitropsins, maytansinoids, nitrosoureas, platinols, pore-forming compounds, purine antimetabolites, puromycins, radiation sensitizers, rapamycins, steroids, taxanes, topoisomerase inhibitors,
  • the cancer therapy is a platinum-based chemotherapy.
  • the cancer therapy may, for example, involve treatment with cisplatin, oxaliplatin, and carboplatin.
  • the platinum-based chemotherapy is a (platinum-fluoropyrimidine doublet chemotherapy.
  • responsiveness to therapy may refer to any one or more of: extending survival (including overall survival and progression free survival); resulting in an objective response (including a complete response or a partial response); or improving signs or symptoms of cancer.
  • responsiveness may refer to improvement of one or more factors according to the published set of RECIST guidelines for determining the status of a tumor in a cancer patient, i.e., responding, stabilizing, or progressing.
  • a responsive subject may refer to a subject whose cancer(s) show improvement, e.g., according to one or more factors based on RECIST criteria.
  • a non-responsive subject may refer to a subject whose cancer(s) do not show improvement, e.g., according to one or more factors based on RECIST criteria.
  • a responsive subject refers to a subject who shows a complete response (CR) or a partial response (PR), while a non-responsive subject is one who does not show improvement and has a stable disease (SD) or progressive disease (PD).
  • CR complete response
  • PR partial response
  • SD stable disease
  • PD progressive disease
  • predicting the responsiveness may also refer to determining the likelihood of a subject who is responsive to a cancer therapy.
  • a method of determining the likelihood of a cancer subject who is responsive to a cancer therapy comprising determining the level of RNA-editing events in a sample obtained from the subject, wherein an increased level of RNA-editing events as compared to a reference indicates that the subject is likely to be responsive towards the cancer therapy.
  • cancer refers to or describe the physiological condition in mammals that is typically characterized in part by unregulated cell growth.
  • cancer refers to non-metastatic and metastatic cancers, including early stage and late stage cancers.
  • precancerous refers to a condition or a growth that typically precedes or develops into a cancer.
  • non-metastatic is meant a cancer that is benign or that remains at the primary site and has not penetrated into the lymphatic or blood vessel system or to tissues other than the primary site.
  • a non-metastatic cancer is any cancer that is a Stage 0, 1, or II cancer, and occasionally a Stage III cancer.
  • early stage cancer is meant a cancer that is not invasive or metastatic or is classified as a Stage 0, I, or II cancer.
  • late stage cancer generally refers to a Stage III or Stage IV cancer but can also refer to a Stage II cancer or a sub-stage of a Stage II cancer.
  • Stage II cancer is classified as either an early stage cancer or a late stage cancer depends on the particular type of cancer.
  • cancer includes but is not limited to, breast cancer, large intestinal cancer, lung cancer, small cell lung cancer, gastric (stomach) cancer, liver cancer, blood cancer, bone cancer, pancreatic cancer, skin cancer, head or neck cancer, cutaneous or intraocular melanoma, uterine sarcoma, ovarian cancer, rectal or colorectal cancer, anal cancer, colon cancer, fallopian tube carcinoma, endometrial carcinoma, cervical cancer, vulval cancer, squamous cell carcinoma, vaginal carcinoma, Hodgkin's disease, non- Hodgkin's lymphoma, esophageal cancer, small intestine cancer, endocrine cancer, thyroid cancer, parathyroid cancer, adrenal cancer, soft tissue tumor, urethral cancer, penile cancer, prostate cancer, chronic or acute leukemia, lymphocytic lymphoma, bladder cancer, kidney cancer, ureter cancer, renal cell carcinoma, renal pelvic carcinoma, CNS tumor, glioma, astrocytom
  • the cancer is selected from the group consisting of gastric cancer, liver cancer, esophageal cancer and lung cancer.
  • the cancer is an advanced cancer (such as a stage IV cancer).
  • the cancer may, for example, be an advanced gastric cancer, an advanced liver cancer, an advanced esophageal cancer or an advanced lung cancer.
  • the RNA-editing events are adenosine to inosine (A-to-I) RNA- editing events.
  • the level of RNA-editing events is determined by RNA sequencing.
  • the level of RNA-editing events may be determined by PCR amplification followed by Sanger sequencing analysis of the purified PCR products or by other techniques that are well known in the art.
  • sample may refer to any sample derived from or containing cells, organisms (bacteria, viruses), lysed cells or organisms, cellular extracts, nuclear extracts, components of cells or organisms, extracellular fluid, media in which cells or organisms are cultured in vitro, blood, plasma, serum, gastrointestinal secretions, urine, ascites, homogenates of tissues or tumors, synovial fluid, feces, saliva, sputum, cyst fluid, amniotic fluid, cerebrospinal fluid, peritoneal fluid, lung lavage fluid, semen, lymphatic fluid, tears, pleural fluid, nipple aspirates, breast milk, external sections of the skin, respiratory, intestinal, and genitourinary tracts, and prostatic fluid.
  • the sample is a cancer sample.
  • the method as defined herein may comprise analyzing RNA editing frequencies of editing sites in endoscopic biopsies of the primary tumor prior to chemotherapy initiation, in order to evaluate the RNA editing profile for each patient.
  • the method comprises determining the level of RNA-editing events in one or more genes as described in Table 1.
  • the method may comprise determining the level of RNA-editing events in 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28 or 29 genes listed in Table 1.
  • the method comprises determining the level of RNA-editing events in all genes as described in Table 1.
  • the method comprises determining the level of RNA-editing events in one or more genes selected from the group consisting of CCNYL1, PHACTR4, LIMD1, RRP36, MRPL30, CPT1A, RBM39, ORC2, AHR, METTL7A, PAICS, NOP14, SLC35F5, SRFBP1, PGAM5, MAVS, FONP2, EIF2AK2, GATC, ZNF587, CTSS, ARSD, FGD5-AS1, SNRPD3, MED 18, NEAT1, NUP43, NDUFS1 and TMPO.
  • genes selected from the group consisting of CCNYL1, PHACTR4, LIMD1, RRP36, MRPL30, CPT1A, RBM39, ORC2, AHR, METTL7A, PAICS, NOP14, SLC35F5, SRFBP1, PGAM5, MAVS, FONP2, EIF2AK2, GATC, ZNF587, CTSS, ARSD, FGD5-AS1, SNRPD3, MED 18,
  • the method comprises determining the level of RNA-editing events in CCNYL1, PHACTR4, LIMD1, RRP36, MRPL30, CPT1A, RBM39, ORC2, AHR, METTL7A, PAICS, NOP14, SLC35F5, SRFBP1, PGAM5, MAVS, FONP2, EIF2AK2, GATC, ZNF587, CTSS, ARSD, FGD5-AS1, SNRPD3, MED18, NEAT1, NUP43, NDUFS1 and TMPO.
  • the method comprises determining the level of RNA-editing events in one or more RNA-editing sites as described in Table 1.
  • the method may comprise determining the level of RNA-editing events in 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49 or 50 RNA-editing sites listed in Table 1.
  • the method comprises determining the level of RNA-editing events in all 50 RNA-editing sites described in Table 1.
  • the method comprises determining a score (e.g. a Z score) based on the level of RNA-editing events in the one or more RNA-editing sites.
  • a score e.g. a Z score
  • the score (e.g. Z score or z-transformation) may be calculated based on the formula: x m where x is the RNA-editing level of each RNA-editing site, m is the mean RNA-editing level of all the RNA-editing sites and s is the standard deviation of the editing level of all RNA-editing sites.
  • the individual z-scores for the RNA-editing sites may be averaged to obtain an overall Z score for each patient.
  • the patient with a score that is above or below a cut-off value may be regarded as high or low editing patient, respectively.
  • the cut-off value may be adjusted in each cohort.
  • the score may be compared to a reference with a cut-off value.
  • the cut-off value may be cancer or cohort specific.
  • the cut-off value may be between -1 to 1.
  • the cut-off value may, for example, be -1, -0.95, -0.9, -0.85, -0.8, -0.75, -0.7, -0.65, -0.6, -0.55, -0.5, - 0.45, -0.4, 0.35, -0.3, -0.25, -0.2, -0.15, -0.1, -0.05, 0, 0.05, 0.1, 0.15, 0.2, 0.25, 0.3, 0.35, 0.4, 0.45, 0.5, 0.55, 0.6, 0.65, 0.7, 0.75, 0.8, 0.85, 0.9, 0.95 or 1.0.
  • a score that is above the cut-off value indicates that the subject is likely to have a complete response (CR) or partial response (PR), while a score of less or equal than the cut-off value indicates that the subject is likely to have a stable disease (SD) or progressive disease (PD).
  • CR complete response
  • PR partial response
  • SD stable disease
  • PD progressive disease
  • the score has a cut-off of 0.4, wherein a score of >0.4. indicates that the subject is likely to have a complete response (CR) or partial response (PR), while a score of ⁇ 0.4 indicates that the subject us likely to have a stable disease (SD) or progressive disease (PD).
  • CR complete response
  • PR partial response
  • SD stable disease
  • PD progressive disease
  • the score has a cut-off of 0.4, wherein a score of >0.4. indicates that the subject is likely to have a partial response (PR), while a score of ⁇ 0.4 indicates that the subject us likely to have a stable disease (SD) or progressive disease (PD).
  • PR partial response
  • SD stable disease
  • PD progressive disease
  • the method comprises determining the level of RNA-editing events with one or more pairs of primers as described in Table 2.
  • the method comprises treating the cancer subject with the cancer therapy.
  • the method as defined herein also predict the likelihood of resistance to a cancer therapy.
  • the method may comprise determining the level of RNA- editing events in a sample obtained from the subject, wherein an increased level of RNA-editing events as compared to a reference indicates that the subject is less likely to be resistant to the cancer therapy.
  • a method of treating a cancer subject found likely to be responsive to a cancer therapy comprising: a) determining the level of RNA-editing events in a sample obtained from the subject, wherein an increased level of RNA editing events as compared to a reference indicates that the subject is likely to be responsive towards the cancer therapy; an b) treating the subject found likely to be responsive to the cancer therapy.
  • treating may refer to (1) preventing or delaying the appearance of one or more symptoms of the disorder; (2) inhibiting the development of the disorder or one or more symptoms of the disorder; (3) relieving the disorder, i.e., causing regression of the disorder or at least one or more symptoms of the disorder; and/or (4) causing a decrease in the severity of one or more symptoms of the disorder.
  • Treatment of a subject may comprise administering to the subject a cancer therapy such as a platinum-based cancer therapy.
  • a cancer therapy such as a platinum-based cancer therapy.
  • administering may refer to contacting, applying, injecting, transfusing or providing an effective amount of a cancer therapy to a subject.
  • an effective amount as defined herein is meant the administration of an amount of agent to an individual in need thereof, either in a single dose or as part of a series, that is effective for that elicitation, treatment or prevention.
  • the effective amount will vary depending upon the health and physical condition of the individual to be treated, the taxonomic group of individual to be treated, the formulation of the composition, the assessment of the medical situation, and other relevant factors. It is expected that the amount will fall in a relatively broad range that can be determined through routine trials.
  • subject as used throughout the specification is to be understood to mean a human or may be a domestic or companion animal. While it is particularly contemplated that the methods of the invention are for treatment of humans, they are also applicable to veterinary treatments, including treatment of companion animals such as dogs and cats, and domestic animals such as horses, cattle and sheep, or zoo animals such as primates, felids, canids, bovids, and ungulates.
  • the “subject” may include a person, a patient or individual, and may be of any age or gender.
  • a method of stratifying a subject into a likely responder or non responder of a cancer therapy comprising determining the level of RNA- editing events in a sample obtained from the subject, wherein an increased level of RNA editing events as compared to a reference indicates that the subject is a likely responder of the cancer therapy and wherein an unchanged or decrease level of RNA-editing events indicates that the subject is a likely non-responder of the cancer therapy.
  • a method for managing treatment of a cancer subject with a cancer therapy comprising a) selecting a cancer subject for treating with the therapy on the basis that the subject is a likely responder to the therapy, or selecting a subject for not treating with the therapy on the basis that the subject is a likely non responder to the therapy; and b) treating or not treating the subject with the therapy based on the selection, wherein the selection is based on the stratification method as defined herein.
  • a method for predicting treatment outcome of a cancer subject with a cancer therapy comprising determining the level of RNA-editing events in a sample obtained from the subject, wherein an increased level of RNA editing events as compared to a reference indicates that the subject is likely to have a positive treatment outcome with the cancer therapy.
  • a method of identifying a subject who is suitable for treatment with a cancer therapy comprising determining the level of RNA-editing events in a sample obtained from the subject, wherein an increased level of RNA editing events as compared to a reference indicates that the subject is likely to have a positive treatment outcome with the cancer therapy and therefore suitable for treatment with the cancer therapy.
  • kits for predicting the responsiveness of a cancer subject to a cancer therapy comprising one or more pairs of primers as described in Table 2 for determining the level of RNA-editing events in a sample obtained from the subject.
  • an array for predicting the responsiveness of a cancer subject to a cancer therapy comprising one or more nucleic acid probes for determining the level of RNA-editing events in a sample obtained from the subject.
  • the one or more nucleic acid probes may be one that is selected from Table 2.
  • the one or more nucleic acid probes may be optionally conjugated to a detectable label.
  • composition comprising one or more nucleic acid probes for determining the level of RNA-editing events in a sample obtained from a subject.
  • the one or more nucleic acid probes may be one that is selected from Table 2.
  • the one or more nucleic acid probes may be optionally conjugated to a detectable label.
  • the composition may comprise a cancer sample that is obtained from a subject.
  • an agent includes a plurality of agents, including mixtures thereof.
  • RNA was used to create libraries with Illumina TruSeq Stranded Total RNA Library Prep Kit (Illumina) according to manufacturer’s instructions.
  • Library fragment size was determined using the DNA 1000 Kit on the Agilent Bioanalyzer (Agilent Technologies). Libraries were quantified by qPCR using the KAPA Library Quantification Kit (KAPA Biosystems). Libraries were pooled in equimolar and cluster generation was performed on the Illumina cBOT system (Illumina). Sequencing (150bp pair-end) was performed on the Illumina HiSeq 3000 system at the Duke-NUS Genome Biology Lacility, according to manufacturer’s protocol (Illumina).
  • Clean reads were mapped to the reference human genome ( hg!9 ) with a splicing junction database generated from transcript annotations derived from UCSC, RefSeq, Ensembl and GENCODE (vl9) by using Burrows-Wheeler Aligner with default parameters (bwa mem, v0.7.17-rl 188).
  • PCR duplicates were removed ( samtools markdup -r, vl.9) and the reads with mapping quality score ⁇ 20 were discarded.
  • Junction-mapped reads were then converted back to the genomic-based coordinates.
  • An in-house perl script was utilized to call the variants from samtools pileup data and the sites with at least two supporting reads were initially retained.
  • the candidate events were filtered by removing the single nucleotide polymorphisms reported in different cohorts (1000 Genomes Project), NHLBI GO Exome Sequencing Project (https://cvs.gs. washington.edn/EVS/), dbSNP (vl50) and excluding the sites within the first six bases of the reads caused by imperfect priming of random hexamer during cDNA synthesis.
  • the sites not located in Alu elements, i.e. short repetitive DNA sequences abundant in the human genome the candidates within the four bases of a splice junction on the intronic side, and those residing in the homopolymeric regions and in the simple repeats were all removed.
  • Candidate variants located in the reads that map to the non-unique regions of the genome by using BLAST-like alignment tool were also excluded. At last, only A-to-G editing sites based on the strand information from the strand-specific RNA-Seq data were considered for all the downstream analyses.
  • the genomic regions of the editing variants and the associated genes were annotated by using ANNOVAR (v2018) with the UCSC ref Gene table annotation. The same pipeline was applied on the TCGA ST AD (The Cancer Genome Atlas - stomach adenocarcinoma) cohort.
  • each editing site was required to have a coverage of at least 20 reads and editing frequency higher than 0.1 (10%) in all the samples. This resulted in 780 high confidence editing sites shared by 104 samples of our GC cohort.
  • these thresholds were not applied for the validation of RE signature in order to include more sites, as the number of high-confidence editing sites were relatively fewer in TCGA due to the lower sequencing depth.
  • the inventors included only those samples with at least 8 out of 50 sites in the RE signature were found to be edited. Then for each sample all these edited sites were used to calculate the RE score.
  • a RE score was developed based on the “z-score” using 50 sites that showed significant positive correlation with the overall response.
  • z-transformation was performed for each site based on the RNA editing levels.
  • the samples were ranked by using the average z-score across the sites.
  • the samples above and below a cut-off value (0.4) were regarded as the high and low editing groups, respectively.
  • the statistical measures were calculated based on the prediction of the responders in the cohort.
  • Disease enrichment analysis of RE signature genes were performed by using Enrichr web server with “PheWeb 2019” database.
  • a total of 10 cell lines were used for the validation of the RE signature.
  • AGS, SNU5, SNU16 and NCI-N87 were purchased from the American Type Culture Collection (Manassas, VA) between 2019-2020.
  • MKN1, MKN7, MKN28, MKN45 and MKN74 were obtained from Japanese Collection of Research Bioresources Cell Bank between 2019-2020.
  • YCC11 cell line was provided by Singapore Gastric Cancer Consortium (SGCC) in 2014. All the cell lines were tested negative for mycoplasma.
  • SNU5 cells were cultured with IMDM (Gibco BRL, Grand Island, NY, USA) supplemented with 20% FBS (Gibco BRL), and all the other cell lines were cultured in Roswell Park Memorial Institute (RPMI) medium (Gibco BRL) supplemented with 10% fetal bovine serum (FBS) (Gibco BRL). Cells were grown in a humidified incubator with 5% CO2 at 37°C.
  • RPMI Roswell Park Memorial Institute
  • FBS fetal bovine serum
  • the editing levels of 26 out of 50 editing sites in these 10 cell lines were quantified by Sanger sequencing. The sites were selected as the top 10 sites which showed the highest change in editing level between high and low editing group as defined in the RNA-Seq data, and additional 16 sites that are randomly picked from the remaining sites in the panel of RE signature.
  • Drug response of the cell lines to oxaliplatin were assessed by IC50 values using MTT (3-(4,5-Dimethylthiazol-2-yl)-2,5- diphenyltetrazolium bromide) assay. Briefly, GC cell lines were seeded in 96-well plates with 2.5 x 10 3 to 10 x 10 3 cells/well according to their growth rate.
  • MTT substrate Sigma-Aldrich
  • cell viability assay 6 suitable cell lines were used, where the cells were seeded in 6-well plate with 3 x 10 4 to 15 x 10 4 cells/well and cultured with indicated concentration of oxaliplatin for 48 hours. Cells were stained with crystal violet (Sigma- Aldrich) for colony visualization.
  • RNA-Editing pipeline is available online at the CSI NGS Portal
  • RNA-Seq data of 104 gastric cancer (GC) patients who have advanced, metastatic or recurrent GC and enrolled onto first-line palliative chemotherapy (platinum- fluoropyrimidine doublet chemotherapy regime).
  • GC gastric cancer
  • first-line palliative chemotherapy platinum- fluoropyrimidine doublet chemotherapy regime.
  • platinum-based chemotherapy was assessed by blinded radiologists and outcomes were locally reviewed.
  • OS overall survival
  • tumor response data had been obtained for 54 and 55 patients, respectively.
  • a total of 50 patients have both OS and tumor response data.
  • RNA editing analysis Based on the RNA editing analysis, patients could be stratified into two groups based on the global RNA editing level (calculated based on 780 editing sites detected in all patient samples, Fig. 1A), and patients demonstrating the higher editing level had better survival (Fig. IB, C).
  • RNA editing frequency in tumors can predict patient’ s overall response to chemotherapy. It was found that higher editing frequencies of a panel of 50 editing sites (across 29 gene transcripts) were significantly correlated with better response (Fig. 3A). This 29-gene RNA editing signature was next used to predict the likelihood of response to chemotherapy. Strikingly, 60% of patients in “high-editing” group had achieved partial response (PR) (“responders”), while only 22.5% of patients in “low-editing” group were responders (Fig. 3B).
  • PR partial response
  • RNA editing score (RE score) was derived.
  • RNA editing signature was next validated in 10 commercially available GC cell lines.
  • IC50 the half maximal inhibitory concentration
  • Figure 5B the cell viability assay
  • Figure 5C the RNA editing levels of 26 randomly selected sites from 50 sites of the signature was quantified in the same 6 cell lines by Sanger sequencing
  • the RE score was applied in a subset of patients with stage IV gastric cancer in the TCGA STAD (stomach adenocarcinoma) cohort. These patients were treated with multiple combinations of drugs, along with multiple data points reporting for primary and follow-up treatment outcome. When the RE score was applied on these patients, it was observed that responders had significantly higher levels of editing in the panel of 50 sites compared to non-responders ( Figure 6A-B), confirming the observation in the earlier advanced GC cohort, despite the diverse drug regimens between the two cohorts. These results suggest that the RE signature is coherent as a predictive marker which is independent of different chemotherapy regimens.

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Abstract

L'invention concerne un procédé de prédiction de la réactivité d'un sujet atteint d'un cancer gastrique à un régime de chimiothérapie à doublet platine-fluoropyrimidine, le procédé comprenant la détermination du niveau d'événements d'édition de l'ARN Adénosine-to-lnosine (A-to-l) dans un échantillon de cancer obtenu à partir du sujet, dans lequel un niveau accru d'événements d'édition de l'ARN A-to-l par rapport à une référence indique que le sujet est susceptible de réagir à la chimiothérapie.
PCT/SG2021/050203 2020-04-14 2021-04-13 Procédé de prédiction de la réactivité à une thérapie du cancer WO2021211057A1 (fr)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113981081A (zh) * 2021-10-22 2022-01-28 中山大学 一种基于rna编辑水平的乳腺癌分子标志物及诊断模型

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20130165337A1 (en) * 2011-12-22 2013-06-27 Aveo Pharmaceuticals, Inc. Identification of multigene biomarkers

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20130165337A1 (en) * 2011-12-22 2013-06-27 Aveo Pharmaceuticals, Inc. Identification of multigene biomarkers

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
AN OMER, SONG YANGYANG, KE XINYU, SO JIMMY BOK-YAN, SUNDAR RAGHAV, YANG HENRY, RHA SUN YOUNG, LEE MING HUI, TAY SU TING, ONG XUEWE: ""3G" Trial: An RNA Editing Signature to Guide Gastric Cancer Chemotherapy", CANCER RESEARCH, AMERICAN ASSOCIATION FOR CANCER RESEARCH, US, vol. 81, no. 10, 15 May 2021 (2021-05-15), US , pages 2788 - 2798, XP055864755, ISSN: 0008-5472, DOI: 10.1158/0008-5472.CAN-20-2872 *
CHAN TIM HON MAN; QAMRA ADITI; TAN KAR TONG; GUO JING; YANG HENRY; QI LIHUA; LIN JAYMIE SIQI; NG VANESSA HUI EN; SONG YANGYANG; HO: "ADAR-Mediated RNA Editing Predicts Progression and Prognosis of Gastric Cancer", GASTROENTEROLOGY, ELSEVIER INC., US, vol. 151, no. 4, 1 January 1900 (1900-01-01), US , pages 637, XP029748250, ISSN: 0016-5085, DOI: 10.1053/j.gastro.2016.06.043 *
HAN LENG; DIAO LIXIA; YU SHUANGXING; XU XIAOYAN; LI JIE; ZHANG RUI; YANG YANG; WERNER HENRICA M.J.; ETEROVIC A. KARINA; : "The Genomic Landscape and Clinical Relevance of A-to-I RNA Editing in Human Cancers", CANCER CELL, CELL PRESS, US, vol. 28, no. 4, 1 October 2015 (2015-10-01), US , pages 515 - 528, XP029298490, ISSN: 1535-6108, DOI: 10.1016/j.ccell.2015.08.013 *
SIDDIQUI JALAL, MILES WAYNE O.: "RNA editing signatures identify melanoma patients who respond to Pembrolizumab or Nivolumab treatment", TRANSLATIONAL ONCOLOGY, NEOPLASIA PRESS, UNITED STATES, vol. 14, no. 11, 1 November 2021 (2021-11-01), United States , pages 101197 - 5233, XP055864757, ISSN: 1936-5233, DOI: 10.1016/j.tranon.2021.101197 *

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113981081A (zh) * 2021-10-22 2022-01-28 中山大学 一种基于rna编辑水平的乳腺癌分子标志物及诊断模型

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