Matthew Alderdice

Cancer-cell intrinsic gene expression signatures overcome intratumoural heterogeneity bias in colorectal cancer patient classification

Stromal-derived intratumoural heterogeneity (ITH) has been shown to undermine molecular stratification of patients into appropriate prognostic/predictive subgroups. Here, using several clinically relevant colorectal cancer (CRC) gene expression signatures, we assessed the susceptibility of these signatures to the confounding effects of ITH using gene expression microarray data obtained from multiple tumour regions of a cohort of 24 patients, including central tumour, the tumour invasive front and lymph node metastasis. Sample clustering alongside correlative assessment revealed variation in the ability of each signature to cluster samples according to patient-of-origin rather than region-of-origin within the multi-region dataset. Signatures focused on cancer-cell intrinsic gene expression were found to produce more clinically useful, patient-centred classifiers, as exemplified by the CRC intrinsic signature (CRIS), which robustly clustered samples by patient-of-origin rather than region-of-origin. These findings highlight the potential of cancer-cell intrinsic signatures to reliably stratify CRC patients by minimising the confounding effects of stromal-derived ITH.

Prospective patient stratification into robust cancer-cell intrinsic subtypes from colorectal cancer biopsies

Colorectal cancer (CRC) biopsies underpin accurate diagnosis, but are also relevant for patient stratification in molecularly‐guided clinical trials. The consensus molecular subtypes (CMSs) and colorectal cancer intrinsic subtypes (CRISs) transcriptional signatures have potential clinical utility for improving prognostic/predictive patient assignment. However, their ability to provide robust classification, particularly in pretreatment biopsies from multiple regions or at different time points, remains untested. In this study, we undertook a comprehensive assessment of the robustness of CRC transcriptional signatures, including CRIS and CMS, using a range of tumour sampling methodologies currently employed in clinical and translational research. These include analyses using (i) laser‐capture microdissected CRC tissue, (ii) eight publically available rectal cancer biopsy data sets (n = 543), (iii) serial biopsies (from AXEBeam trial, NCT00828672; n = 10), (iv) multi‐regional biopsies from colon tumours (n = 29 biopsies, n = 7 tumours), and (v) pretreatment biopsies from the phase II rectal cancer trial COPERNCIUS (NCT01263171; n = 44). Compared to previous results obtained using CRC resection material, we demonstrate that CMS classification in biopsy tissue is significantly less capable of reliably classifying patient subtype (43% unknown in biopsy versus 13% unknown in resections, p = 0.0001). In contrast, there was no significant difference in classification rate between biopsies and resections when using the CRIS classifier. Additionally, we demonstrated that CRIS provides significantly better spatially‐ and temporally‐ robust classification of molecular subtypes in CRC primary tumour tissue compared to CMS (p = 0.003 and p = 0.02, respectively). These findings have potential to inform ongoing biopsy‐based patient stratification in CRC, enabling robust and stable assignment of patients into clinically‐informative arms of prospective multi‐arm, multi‐stage clinical trials.

Natural killer-like signature observed post therapy in locally advanced rectal cancer is a determinant of pathological response and improved survival

Around 12–15% of patients with locally advanced rectal cancer undergo a pathologically complete response (tumor regression grade 4) to long-course preoperative chemoradiotherapy; the remainder exhibit a spectrum of tumor regression (tumor regression grade 1–3). Understanding therapy-related transcriptional alterations may enable better prediction of response as measured by progression-free and overall survival, in addition to aiding the development of improved strategies based on the underlying biology of the disease. To this end, we performed high-throughput gene expression profiling in 40 pairs of formalin-fixed paraffin-embedded rectal cancer biopsies and matched resections following long-course preoperative chemoradiotherapy (discovery cohort). Differential gene expression analysis was performed contrasting tumor regression grades in resections. Enumeration of the tumor microenvironment cell population was undertaken using in silico analysis of the transcriptional data, and real-time PCR validation of NCR1 undertaken. Immunohistochemistry and survival analysis was used to measure CD56+ cell populations in an independent cohort (n=150). Gene expression traits observed following long-course preoperative chemoradiotherapy in the discovery cohort suggested an increased abundance of natural killer cells in tumors that displayed a clinical response to CRT in a tumor regression grade-dependent manner. CD56+ natural killer-cell populations were measured by immunohistochemistry and found to be significantly higher in tumor regression grade 3 patients compared with tumor regression grade 1–2 in the validation cohort. Furthermore, it was observed that patients positive for CD56 cells after therapy had a better overall survival (HR=0.282, 95% CI=0.109–0.729, χ2=7.854, P=0.005). In conclusion, we have identified a novel post-therapeutic natural killer-like transcription signature in patients responding to long-course preoperative chemoradiotherapy. Furthermore, patients with a higher abundance of CD56-positive natural killer cells post long-course preoperative chemoradiotherapy had better overall survival. Therefore, harnessing a natural killer-like response after therapy may improve outcomes for locally advanced rectal cancer patients. Finally, we hypothesize that future assessment of this natural killer-like response in on-treatment biopsy material may inform clinical decision-making for treatment duration.

Bcl-xL as a poor prognostic biomarker and predictor of response to adjuvant chemotherapy specifically in BRAF-mutant stage II and III colon cancer

Purpose BRAF mutation occurs in 8–15% of colon cancers (CC), and is associated with poor prognosis in metastatic disease. Compared to wild-type BRAF (BRAFWT) disease, stage II/III CC patients with BRAF mutant (BRAFMT) tumors have shorter overall survival after relapse; however, time-to-relapse is not significantly different. The aim of this investigation was to identify, and validate, novel predictors of relapse of stage II/III BRAFMT CC. Experimental design We used gene expression data from a cohort of 460 patients (GSE39582) to perform a supervised classification analysis based on risk-of-relapse within BRAFMT stage II/III CC, to identify transcriptomic biomarkers associated with prognosis within this genotype. These findings were validated using immunohistochemistry in an independent population-based cohort of Stage II/III CC (n = 691), applying Cox proportional hazards analysis to determine associations with survival. Results High gene expression levels of Bcl-xL, a key regulator of apoptosis, were associated with increased risk of relapse, specifically in BRAFMT tumors (HR = 8.3, 95% CI 1.7–41.7), but not KRASMT/BRAFWT or KRASWT/BRAFWT tumors. High Bcl-xL protein expression in BRAFMT, untreated, stage II/III CC was confirmed to be associated with an increased risk of death in an independent cohort (HR = 12.13, 95% CI 2.49–59.13). Additionally, BRAFMT tumors with high levels of Bcl-xL protein expression appeared to benefit from adjuvant chemotherapy (P for interaction = 0.006), indicating the potential predictive value of Bcl-xL expression in this setting. Conclusions These findings provide evidence that Bcl-xL gene and/or protein expression identifies a poor prognostic subgroup of BRAFMT stage II/III CC patients, who may benefit from adjuvant chemotherapy.

Abstract 4792: Comprehensive molecular pathology analysis of small bowel adenocarcinoma reveals novel targets with clinical utility

Small bowel accounts for only 0.5% of cancer cases in the US; a third of which are adenocarcinomas. But incidence rates have been rising at a rate of 2.4% per year over the last decade. Because of the rarity of this cancer, little is known about its molecular pathology and there are no molecular markers for diagnosis, predicting prognosis or therapeutic intervention. The aim of this study was therefore to look into this disease at a molecular level to better understand its biology and identify biomarkers and potential points of therapeutic intervention. Using a retrospective 28 patient matched normal-tumor cohort next generation sequencing (NGS) was performed using a 50 gene cancer hotspot panel, gene expression arrays were used to profile ∼29,000 RNA transcripts and 450k CpG methylation arrays were used to carry out DNA methylation analysis. We also looked at microsatellite instability (MSI), HER2 and p53 expression. NGS identified novel mutations in IDH1, CDH1, KIT, NRAS, FGFR2, FLT3, NPM1, PTEN, MET, AKT1, RET, NOTCH1 and ERBB4. Previously known mutations such as high-frequency KRAS and TP53 and low-frequency HER2 were also confirmed in our cohort. The average patient had 2.6 mutations with eight patients having only a single mutation to one having seven. Array data revealed 17% of CpGs and 5% of RNA transcripts assayed to be differentially methylated and expressed respectively (p This study has for the first time highlighted the extent of molecular changes taking place in SBA. The clinical potential of TP53 mutations and Kazald1 hypomethylation as prognostic biomarkers and CHN2 as a diagnostic biomarker are focus areas for further research by our group. Citation Format: Muhammad A. Alvi, Darragh G. McArt, Paul Kelly, Marc-Aurel Fuchs, Matthew Alderdice, Clare M. McCabe, Victoria Bingham, Claire McGready, Stephen McQuaid, Perry Maxwell, Peter Hamilton, Jacqueline A. James, Richard Wilson, Manuel Salto-Tellez. Comprehensive molecular pathology analysis of small bowel adenocarcinoma reveals novel targets with clinical utility. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4792. doi:10.1158/1538-7445.AM2015-4792