Immune status is prognostic for poor survival in colorectal cancer patients and is associated with tumour hypoxia.

BACKGROUND: Immunohistochemical quantification of the immune response is prognostic for colorectal cancer (CRC). Here, we evaluate the suitability of alternative immune classifiers on prognosis and assess whether they relate to biological features amenable to targeted therapy. METHODS: Overall survival by immune (CD3, CD4, CD8, CD20 and FOXP3) and immune-checkpoint (ICOS, IDO-1 and PD-L1) biomarkers in independent CRC cohorts was evaluated. Matched mutational and transcriptomic data were interrogated to identify associated biology. RESULTS: Determination of immune-cold tumours by combined low-density cell counts of CD3, CD4 and CD8 immunohistochemistry constituted the best prognosticator across stage II-IV CRC, particularly in patients with stage IV disease (HR 1.98 [95% CI: 1.47-2.67]). These immune-cold CRCs were associated with tumour hypoxia, confirmed using CAIX immunohistochemistry (P = 0.0009), which may mediate disease progression through common biology (KRAS mutations, CRIS-B subtype and SPP1 mRNA overexpression). CONCLUSIONS: Given the significantly poorer survival of immune-cold CRC patients, these data illustrate that assessment of CD4-expressing cells complements low CD3 and CD8 immunohistochemical quantification in the tumour bulk, potentially facilitating immunophenotyping of patient biopsies to predict prognosis. In addition, we found immune-cold CRCs to associate with a difficult-to-treat, poor prognosis hypoxia signature, indicating that these patients may benefit from hypoxia-targeting clinical trials.

Downregulation of PPARα during Experimental Left Ventricular Hypertrophy Is Critically Dependent on Nox2 NADPH Oxidase Signalling.

Pressure overload-induced left ventricular hypertrophy (LVH) is initially adaptive but ultimately promotes systolic dysfunction and chronic heart failure. Whilst underlying pathways are incompletely understood, increased reactive oxygen species generation from Nox2 NADPH oxidases, and metabolic remodelling, largely driven by PPARα downregulation, are separately implicated. Here, we investigated interaction between the two as a key regulator of LVH using in vitro, in vivo and transcriptomic approaches. Phenylephrine-induced H9c2 cardiomyoblast hypertrophy was associated with reduced PPARα expression and increased Nox2 expression and activity. Pressure overload-induced LVH and systolic dysfunction induced in wild-type mice by transverse aortic constriction (TAC) for 7 days, in association with Nox2 upregulation and PPARα downregulation, was enhanced in PPARα-/- mice and prevented in Nox2-/- mice. Detailed transcriptomic analysis revealed significantly altered expression of genes relating to PPARα, oxidative stress and hypertrophy pathways in wild-type hearts, which were unaltered in Nox2-/- hearts, whilst oxidative stress pathways remained dysregulated in PPARα-/- hearts following TAC. Network analysis indicated that Nox2 was essential for PPARα downregulation in this setting and identified preferential inflammatory pathway modulation and candidate cytokines as upstream Nox2-sensitive regulators of PPARα signalling. Together, these data suggest that Nox2 is a critical driver of PPARα downregulation leading to maladaptive LVH.

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. © 2018 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

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.

Evolutionary genetic algorithm identifies IL2RB as a potential predictive biomarker for immune-checkpoint therapy in colorectal cancer.

Identifying robust predictive biomarkers to stratify colorectal cancer (CRC) patients based on their response to immune-checkpoint therapy is an area of unmet clinical need. Our evolutionary algorithm Atlas Correlation Explorer (ACE) represents a novel approach for mining The Cancer Genome Atlas (TCGA) data for clinically relevant associations. We deployed ACE to identify candidate predictive biomarkers of response to immune-checkpoint therapy in CRC. We interrogated the colon adenocarcinoma (COAD) gene expression data across nine immune-checkpoints (PDL1, PDCD1, CTLA4, LAG3, TIM3, TIGIT, ICOS, IDO1 and BTLA). IL2RB was identified as the most common gene associated with immune-checkpoint genes in CRC. Using human/murine single-cell RNA-seq data, we demonstrated that IL2RB was expressed predominantly in a subset of T-cells associated with increased immune-checkpoint expression (P < 0.0001). Confirmatory IL2RB immunohistochemistry (IHC) analysis in a large MSI-H colon cancer tissue microarray (TMA; n = 115) revealed sensitive, specific staining of a subset of lymphocytes and a strong association with FOXP3+ lymphocytes (P < 0.0001). IL2RB mRNA positively correlated with three previously-published gene signatures of response to immune-checkpoint therapy (P < 0.0001). Our evolutionary algorithm has identified IL2RB to be extensively linked to immune-checkpoints in CRC; its expression should be investigated for clinical utility as a potential predictive biomarker for CRC patients receiving immune-checkpoint blockade.

ACE: A Workbench Using Evolutionary Genetic Algorithms for Analyzing Association in TCGA.

Modern methods of acquiring molecular data have improved rapidly in recent years, making it easier for researchers to collect large volumes of information. However, this has increased the challenge of recognizing interesting patterns within the data. Atlas Correlation Explorer (ACE) is a user-friendly workbench for seeking associations between attributes in The Cancer Genome Atlas (TCGA) database. It allows any combination of clinical and genomic data streams to be searched using an evolutionary algorithm approach. To showcase ACE, we assessed which RNA sequencing transcripts were associated with estrogen receptor (ESR1) in the TCGA breast cancer cohort. The analysis revealed already well-established associations with XBP1 and FOXA1, but also identified a strong association with CT62, a potential immunotherapeutic target with few previous associations with breast cancer. In conclusion, ACE can produce results for very large searches in a short time and will serve as an increasingly useful tool for biomarker discovery in the big data era. SIGNIFICANCE: ACE uses an evolutionary algorithm approach to perform large searches for associations between any combinations of data in the TCGA database.

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.

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.

Comprehensive molecular pathology analysis of small bowel adenocarcinoma reveals novel targets with potential for clinical utility.

Small bowel accounts for only 0.5% of cancer cases in the US but incidence rates have been rising at 2.4% per year over the past decade. One-third of these are adenocarcinomas but little is known about their molecular pathology and no molecular markers are available for clinical use. Using a retrospective 28 patient matched normal-tumor cohort, next-generation sequencing, gene expression arrays and CpG methylation arrays were used for molecular profiling. Next-generation sequencing identified novel mutations in IDH1, CDH1, KIT, FGFR2, FLT3, NPM1, PTEN, MET, AKT1, RET, NOTCH1 and ERBB4. Array data revealed 17% of CpGs and 5% of RNA transcripts assayed to be differentially methylated and expressed respectively (p < 0.01). Merging gene expression and DNA methylation data revealed CHN2 as consistently hypermethylated and downregulated in this disease (Spearman -0.71, p < 0.001). Mutations in TP53 which were found in more than half of the cohort (15/28) and Kazald1 hypomethylation were both were indicative of poor survival (p = 0.03, HR = 3.2 and p = 0.01, HR = 4.9 respectively). By integrating high-throughput mutational, gene expression and DNA methylation data, this study reveals for the first time the distinct molecular profile of small bowel adenocarcinoma and highlights potential clinically exploitable markers.