Prognostic and treatment response predictive method
Inventors
Smyth, Elizabeth • Sadanandam, Anguraj • Nyamundanda, Gift • Cunningham, David • TAN, Boon Ooi Patrick
Assignees
Institute of Cancer Research Royal Cancer Hospital • Royal Marsden NHS Foundation Trust • National University of Singapore
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Publication Number
US-11788148-B2
Publication Date
2023-10-17
Expiration Date
Abstract
The present invention provides a method for predicting the treatment response of a human gastroesophageal cancer patient, the method comprising: a) measuring the gene expression of at least 3 of the following genes: CDH1, CDK6, COX2, ELOVL5, GATA4, EGFR, TBCEL, FGF7, CDH17, FNBP1, PIP5K1B, TWIST, CD44, MET, CEACAM1, TOX3, GLIPR2, GSTP1, RON, TMEM136, MYB, BRCA2, FGF1, POU5F1, EPR, DPYD, ABL2 and SH3RF1 in a sample obtained from the gastroesophageal tumour of the patient to obtain a sample gene expression profile of at least said genes; and b) making a prediction of the treatment response and/or prognosis of the patient based on the sample gene expression profile. Also provided are related computer-implemented methods and methods of treatment of gastroesophageal cancer.
Core Innovation
The invention relates to a method of treatment of gastroesophageal cancer in a human patient based on measuring gene expression in a sample obtained from the gastroesophageal tumour after perioperative treatment and surgical resection. The method comprises measuring the gene expression of at least the genes CDH1, ELOVL5, EGFR, PIP5K1B, FGF1, CD44 and TBCEL to obtain a sample gene expression profile of at least said genes.
A risk score is derived by weighting the measured, and optionally normalised, expression level of each gene and summing the weighted expression levels of the genes. The contribution to the total risk score made by CD44 and EGFR has the opposite sign to that of the contribution made by CDH1, ELOVL5, PIP5K1B, FGF1 and TBCEL. The patient is then determined from said score to be at high or moderate risk of poor prognosis.
After determining high or moderate risk of poor prognosis, the method follows by administering therapy to the patient a therapeutically effective amount of at least one chemotherapeutic agent selected from the group consisting of epirubicin, cisplatin, 5-fluorouracil, capecitabine, oxaliplatin, and docetaxel.
The problem being solved is establishing a gastroesophageal cancer prognostic and treatment-response model for patients who have had perioperative chemotherapy and surgical resection, using gene expression profiling to stratify risk independently of lymph node status and to guide the selection of additional anti-cancer therapy.
Claims Coverage
The provided partial content contains one independent claim (clm-00001). It recites a complete treatment method that links post-perioperative resection gene expression measurement to risk-score derivation, high or moderate poor-prognosis determination, and subsequent administration of a selected chemotherapeutic agent.
Gene expression measurement of a defined gastroesophageal cancer marker set
Measuring the gene expression of at least the genes CDH1, ELOVL5, EGFR, PIP5K1B, FGF1, CD44 and TBCEL in a sample obtained from the gastroesophageal tumour of the patient to obtain a sample gene expression profile.
Weighted opposite-sign risk scoring with optional normalization
Deriving a risk score by weighting the measured, and optionally normalised, expression level of each gene and summing the weighted expression level of each gene, wherein the contribution to the total risk score made by CD44 and EGFR has the opposite sign to that of the contribution made by CDH1, ELOVL5, PIP5K1B, FGF1 and TBCEL.
Risk determination for poor prognosis and treatment selection
Determining from said score that the patient is at high or moderate risk of poor prognosis and, following said determining, administering therapy by providing a therapeutically effective amount of at least one chemotherapeutic agent selected from epirubicin, cisplatin, 5-fluorouracil, capecitabine, oxaliplatin, and docetaxel.
The claim coverage centers on a treatment method that uses expression profiling of a specific gene set (CDH1, ELOVL5, EGFR, PIP5K1B, FGF1, CD44 and TBCEL), computes a weighted risk score with opposite-sign contributions (CD44/EGFR versus CDH1/ELOVL5/PIP5K1B/FGF1/TBCEL), determines high or moderate risk of poor prognosis, and administers a therapeutically effective amount of a selected chemotherapeutic agent from a specified group.
Stated Advantages
Prognostic discrimination independent of lymph node status.
Links risk classification to treatment selection for high/moderate risk patients and reduced/no additional therapy for low risk patients.
Documented Applications
Gastroesophageal cancer prognosis and treatment-response assessment after perioperative chemotherapy and surgical resection using gene expression profiling of a defined gene set (GC-RiskAssigner including CDH1, ELOVL5, EGFR, PIP5K1B, FGF1, CD44v8-10, and TBCEL).
Clinical validation in the MAGIC and PROGRESS cohorts for overall survival (OS) and risk stratification independent of lymph node status.
A computer-implemented method for classifying patients using risk scores derived from measured, optionally normalized gene expression and corresponding reference classification.
Treatment method for gastroesophageal cancer in which patients determined to be at high or moderate risk of poor prognosis receive additional/aggressive anti-cancer therapy with selected chemotherapeutic agents.
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