Project description:We report the RNA sequencing data from the REPEAT study, in which patients with beyond first-line esophagogastric cancer were treated with regorafenib and paclitaxel. For the RNA sequencing, biopsies from metastatic lesions were obtained on baseline (n=21) and fifteen days following treatment initiation (n=13). PURPOSE: Regorafenib monotherapy, a multikinase-inhibitor of angiogenesis, tumor microenvironment, and oncogenesis, showed promising results in gastric cancer. We aimed to assess the tolerability of regorafenib and paclitaxel in advanced esophagogastric cancer (EGC) patients refractory to first-line treatment, and explore potential biomarkers. METHODS: Patients received paclitaxel (80 mg/m2) on days 1, 8, and 15 of a 28-day cycle and regorafenib (80/120/160 mg) on day 1-21 in the dose-escalation cohort, and the maximum-tolerated dose (MTD) in the dose-expansion cohort. Exploratory, overall- (OS) and progression-free survival (PFS) were compared to a propensity-score matched cohort receiving standard second/third line systemic treatment. Paclitaxel pharmacokinetics were assessed using D1 and D15 samples. We performed ELISA measurements of galectin-1, RNA sequencing and shallow whole-genome sequencing of metastatic tumor biopsies for biomarker analyses. RESULTS: In the dose-escalation cohort (n=14), the MTD of regorafenib was 120 mg. Thirty-four patients were enrolled in the dose-expansion cohort. Most common toxicities (all grades; grade ≥3) were fatigue (79%; 4%) and sensory neuropathy (63%; 4%). Best responses achieved were partial response (28%) and stable disease (54%). Median OS and PFS were 7.8 and 4.2 months, respectively (median follow-up 7.8 months). OS (p=0.08) and PFS (p=0.81) were not significantly improved compared to the matched cohort. Paclitaxel concentrations were significantly increased with regorafenib (D15) compared with paclitaxel only (D1; p<0.05); no associations were observed with toxicity or efficacy. An increase in circulating galectin-1 compared to baseline was associated with shorter OS (p<0.01). Enrichment of angiogenesis-related gene expression was observed in short-survivors measured by RNA sequencing. Chromosome 19q13.12-q13.2 amplification was associated with shorter OS (p=0.02) and PFS (p=0.02). CONCLUSION: Treatment with regorafenib and paclitaxel is tolerable and shows promising efficacy in advanced EGC refractory to first-line treatment. Galectin-1 and chromosome 19q13.12-q13.2 amplification could serve as negative predictive biomarkers for treatment response.

Project description:Purpose: Despite advances in radical surgery and chemotherapy delivery, ovarian cancer is the most lethal gynecologic malignancy. Most of these patients are treated with platinum-based chemotherapies, but there is no biomarker model to guide their responses to these therapeutic agents. We have developed and independently tested our novel multivariate molecular predictors for forecasting patients' responses to individual drugs on a cohort of 58 ovarian cancer patients. Experimental Design: We adapted and applied the previously-published COXEN algorithm to develop molecular predictors for therapeutic responses of patients' tumors based on expression signatures derived from the NCI-60 in vitro drug activities and genomic expression data. Genome-wide candidate biomarkers were first triaged by examining expression patterns of frozen and formalin-fixed paraffin embedded (FFPE) tissue samples. We then identify initial drug sensitivity biomarkers for carboplatin and paclitaxel, respectively. These biomarkers were further narrowed by examining concordant expression patterns between cell lines and a historical set of ovarian cancer patients. Multivariate predictors were obtained from the NCI-60 cell lines and refined using historical patient cohorts. To independent validate these molecular predictors, we performed genome-wide profiling on FFPE samples of 58 ovarian cancer patients obtained prior to adjuvant chemotherapy. Results: Carboplatin predictor significantly stratified platinum sensitive and resistant patients (p = 0.019) with sensitivity = 93%, specificity = 33%, PPV = 65%, and NPV = 78%. Paclitaxel predictor also significantly stratified patients' responses (p = 0.033) with sensitivity = 96%, specificity = 26%, PPV = 61%, and NPV = 86%. The combination predictor for platinum-taxane combination demonstrated a significant survival difference between the predicted responders and nonresponders with median survival of 12.9 months vs. 8.1 months (p = 0.045). Conclusions: COXEN predictors successfully stratified platinum resistance and taxane response in this retrospective cohort, especially based on their FFPE tumor samples. Accurate prediction of chemotherapeutic response, especially to platinum agents is highly clinically relevant and could alter primary management of ovarian cancer. Gene expression data from 58 stage III-IV ovarian cancer patients treated with Carboplatin and Taxol agents

Project description:This is a model built by COPASI4.24(Build 197) This a model from the article: Computational design of improved standardized chemotherapy protocols for grade II oligodendrogliomas Víctor M. Pérez-García, Luis E. Ayala-Hernández, Juan Belmonte-Beitia, Philippe Schucht, Michael Murek, Andreas Raabe, Juan Sepúlveda. PLoS Comput Biol. 2019 Jul; 15(7): e1006778. Abstract: Here we put forward a mathematical model describing the response of low-grade (WHO grade II) oligodendrogliomas (LGO) to temozolomide (TMZ). The model describes the longitudinal volumetric dynamics of tumor response to TMZ of a cohort of 11 LGO patients treated with TMZ. After finding patient-specific parameters, different therapeutic strategies were tried computationally on the ‘in-silico twins’ of those patients. Chemotherapy schedules with larger-than-standard rest periods between consecutive cycles had either the same or better long-term efficacy than the standard 28-day cycles. The results were confirmed in a large trial of 2000 virtual patients. These long-cycle schemes would also have reduced toxicity and defer the appearance of resistances. On the basis of those results, a combination scheme consisting of five induction TMZ cycles given monthly plus 12 maintenance cycles given every three months was found to provide substantial survival benefits for the in-silico twins of the 11 LGO patients (median 5.69 years, range: 0.67 to 68.45 years) and in a large virtual trial including 2000 patients. We used 220 sets of experiments in-silico to show that a clinical trial incorporating 100 patients per arm (standard intensive treatment versus 5 + 12 scheme) could demonstrate the superiority of the novel scheme after a follow-up period of 10 years. Thus, the proposed treatment plan could be the basis for a standardized TMZ treatment for LGO patients with survival benefits. This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team. For more information see the terms of use. To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92

Project description:Purpose: Despite advances in radical surgery and chemotherapy delivery, ovarian cancer is the most lethal gynecologic malignancy. Most of these patients are treated with platinum-based chemotherapies, but there is no biomarker model to guide their responses to these therapeutic agents. We have developed and independently tested our novel multivariate molecular predictors for forecasting patients' responses to individual drugs on a cohort of 58 ovarian cancer patients. Experimental Design: We adapted and applied the previously-published COXEN algorithm to develop molecular predictors for therapeutic responses of patients' tumors based on expression signatures derived from the NCI-60 in vitro drug activities and genomic expression data. Genome-wide candidate biomarkers were first triaged by examining expression patterns of frozen and formalin-fixed paraffin embedded (FFPE) tissue samples. We then identify initial drug sensitivity biomarkers for carboplatin and paclitaxel, respectively. These biomarkers were further narrowed by examining concordant expression patterns between cell lines and a historical set of ovarian cancer patients. Multivariate predictors were obtained from the NCI-60 cell lines and refined using historical patient cohorts. To independent validate these molecular predictors, we performed genome-wide profiling on FFPE samples of 58 ovarian cancer patients obtained prior to adjuvant chemotherapy. Results: Carboplatin predictor significantly stratified platinum sensitive and resistant patients (p = 0.019) with sensitivity = 93%, specificity = 33%, PPV = 65%, and NPV = 78%. Paclitaxel predictor also significantly stratified patients' responses (p = 0.033) with sensitivity = 96%, specificity = 26%, PPV = 61%, and NPV = 86%. The combination predictor for platinum-taxane combination demonstrated a significant survival difference between the predicted responders and nonresponders with median survival of 12.9 months vs. 8.1 months (p = 0.045). Conclusions: COXEN predictors successfully stratified platinum resistance and taxane response in this retrospective cohort, especially based on their FFPE tumor samples. Accurate prediction of chemotherapeutic response, especially to platinum agents is highly clinically relevant and could alter primary management of ovarian cancer.

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Gene expression profiles of ovarian tumor biopsies from Phase I dasatinib trial

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