Cancers · 2018 · 57 citations · 46 references
MedicineGeneticsOncologyCancer GeneticsMolecular OncologySignal TransductionCancer Cell SignalingCancer GenomicsColorectal CancerMolecular Tumor ProfilingOncogenic Signaling PathwaysSignal Transduction In CancerCopy Number LossesJak-stat Signaling PathwayKinase Domain MutationsOncogenic Receptor Tyrosine Kinase MutationsPredictive Tumor MarkersRelative Risk EstimationSingle-gene MutationsTherapeutic Resistance Mechanisms
Background: Bevacizumab-based regimens are used as standard treatments for colorectal cancer. Unfortunately, there are no established predictive markers for bevacizumab response. Methods: Tumor samples from 36 metastatic colorectal cancer patients treated with bevacizumab plus chemotherapy were analyzed by next-generation sequencing of all coding exons of more than 400 genes. Single gene and signaling pathway analyses were performed to correlate genomic data with response. Results: Among the genes most frequently mutated in our cohort, only mutations in PTPRT, a phosphatase involved in JAK/STAT signaling, were associated with response status, with deleterious mutations being enriched in non-responders. Pathway analysis revealed that deleterious mutations in genes of the JAK/STAT pathway, namely in PTPRT and the related gene PTPRD, correlated with resistance. Mutations in RTK/PI3K/RAS, Wnt and TGFβ pathways did not associate with response. Lack of response was observed in all patients with deleterious mutations or copy number loss of PTPRT/PTPRD (n = 10), compared to only 30.8% (n = 8) of patients without such alterations (relative risk, 3.25; 95% CI, 1.83–5.79, p = 0.0003). Similarly, PTPRT/PTPRD deleterious alterations were associated with shorter progression-free survival, an association that was retained in multivariate analysis (HR, 3.33; 95% CI, 1.47–7.54; p = 0.0038). Conclusion: Deleterious alterations in PTPRT/PTPRD are potential biomarkers for bevacizumab resistance.
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New response evaluation criteria in solid tumours: Revised RECIST guideline (version 1.1)
E. Eisenhauer, P. Therasse, Jan Bogaerts et al. · European Journal of Cancer · 2008 · 29.5K citations
Ethan Cerami, Jianjiong Gao, Uğur Doğrusöz et al. · Cancer Discovery · 2012 · 18.4K citations · Full text
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Medicine, Bioinformatics, Oncology +17
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