Biology subjects

Cunningham, D.

Publications and source records attributed to Cunningham, D..

3 recordsLinked to original sources

bioRxiv2018

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↗

bioRxiv2017

Ultra-sensitive mutation detection and genome-wide DNA copy number reconstruction by error corrected circulating tumour DNA sequencing

Minimally invasive circulating free DNA (cfDNA) analysis can portray cancer genome landscapes but highly sensitive and specific genetic approaches are necessary to accurately detect mutations with often low variant frequencies. We developed a targeted cfDNA sequencing technology using novel off-the-shelf molecular barcodes for error correction, in combination with custom solution hybrid capture enrichment. Modelling based on cfDNA yields from 58 patients shows that our assay, which requires 25ng of cfDNA input, should be applicable to >95% of patients with metastatic colorectal cancer. Sequencing of a 163.3 kb target region including 32 genes detected 100% of single nucleotide variants with 0.15% variant frequency in cfDNA spike-in experiments. Molecular barcode error correction reduced false positive mutation calls by 98.6%. In a series of 28 patients with metastatic colorectal cancers, 80 out of 91 (88%) mutations previously detected by tumour tissue sequencing were called in the cfDNA. Call rates were similar for single nucleotide variants and small insertions/deletions. Mutations only called in cfDNA but not detectable in matched tumour tissue included, among others, a subclonal resistance driver mutation to anti-EGFR antibodies in the KRAS gene, multiple activating PIK3CA mutations in each of two patients (indicative of parallel evolution), and TP53 mutations originating from clonal haematopoiesis. Furthermore, we demonstrate that cfDNA off-target read analysis allows the reconstruction of genome wide copy number aberration profiles from 71% of these 28 cases. This error-corrected ultra-deep cfDNA sequencing assay with a target region that can be readily customized enables broad insights into cancer genomes and evolution.

genomics↗

bioRxiv2017

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↗