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Patil, Y.

Publications and source records attributed to Patil, Y..

2 recordsLinked to original sources

Genomic and transcriptomic determinants of therapy resistance and immune landscape evolution during anti-EGFR treatment in colorectal cancer

Anti-epidermal growth factor receptor (EGFR) antibodies (anti-EGFR-Ab) are effective in a subgroup of patients with metastatic colorectal cancer (CRC). We applied genomic and transcriptomic analyses to biopsies from 35 RAS wild-type CRCs treated with the anti-EGFR-Ab cetuximab in a prospective trial to interrogate the molecular resistance landscape. This validated transcriptomic CRC-subtypes as predictors of cetuximab benefit; identified novel associations of NF1-inactivation and non-canonical RAS/RAF-aberrations with primary progression; and of FGF10- and non-canonical BRAF-aberrations with AR. No genetic resistance drivers were detected in 64% of AR biopsies. The majority of these had switched from the cetuximab-sensitive CMS2-subtype pretreatment to the fibroblast- and growth factor-rich CMS4-subtype at progression. Fibroblast supernatant conferred cetuximab resistance in vitro, together supporting subtype-switching as a novel mechanism of AR. Cytotoxic immune infiltrates and immune-checkpoint expression increased following cetuximab responses, potentially providing opportunities to treat CRCs with molecularly heterogeneous AR with immunotherapy.

cancer biology

A Low-Cost Multiplex Biomarker Assay Stratifies Colorectal Cancer Patient Samples into Clinically-Relevant Subtypes

Previously, we classified colorectal cancers (CRCs) into five CRCA subtypes with different prognoses and potential treatment responses, using a 786-gene signature. We merged our subtypes and those described by five other groups into four consensus molecular subtypes (CMS) that are similar to CRCA subtypes. Here we demonstrate the analytical development and application of a custom NanoString platform-based biomarker assay to stratify CRC into subtypes. To reduce costs, we switched from the standard protocol to a custom modified protocol (NanoCRCA) with a high Pearson correlation coefficient (>0.88) between protocols. Technical replicates were highly correlated (>0.96). The assay included a reduced robust 38-gene panel from the 786-gene signature that was selected using an in-laboratory developed computational pipeline of class prediction methods. We applied our NanoCRCA assay to untreated CRCs including fresh-frozen and formalin-fixed paraffin-embedded (FFPE) samples (n=81) with matched microarray or RNA-Seq profiles. We further compared the assay results with CMS classification, different platforms (microarrays/RNA-Seq) and gene-set classifiers (38 and 786 genes). NanoCRCA classified fresh-frozen samples (n=39; not including those showing a mixture of subtypes) into all five CRCA subtypes with overall high concordance across platforms (89.7%) and with CMS subtypes (84.6%), independent of tumour cellularity. This analytical validation of the assay shows the association of subtypes with their known molecular, mutational and clinical characteristics. Overall, our modified NanoCRCA assay with further clinical assessment may facilitate prospective validation of CRC subtypes in clinical trials and beyond.\n\nNovelty and ImpactWe previously identified five gene expression-based CRC subtypes with prognostic and potential predictive differences using a 786-gene signature and microarray platform. Subtype-driven clinical trials require a validated assay suitable for routine clinical use. This study demonstrates, for the first time, how molecular CRCA subtype can be detected using NanoString Technology-based biomarker assay (NanoCRCA) suitable for clinical validation. NanoCRCA is suitable for analysing FFPE samples, and this assay may facilitate patient stratification within clinical trials.

cancer biology