QuPath is new bioimage analysis software designed to meet the growing need for a user-friendly, extensible, open-source solution for digital pathology and whole slide image analysis. In addition to offering a comprehensive panel of tumor identification and high-throughput biomarker evaluation tools, QuPath provides researchers with powerful batch-processing and scripting functionality, and an extensible platform with which to develop and share new algorithms to analyze complex tissue images. Furthermore, QuPath’s flexible design makes it suitable for a wide range of additional image analysis applications across biomedical research.

Purpose: A number of independent gene expression profiling studies have identified transcriptional subtypes in colorectal cancer with potential diagnostic utility, culminating in publication of a colorectal cancer Consensus Molecular Subtype classification. The worst prognostic subtype has been defined by genes associated with stem-like biology. Recently, it has been shown that the majority of genes associated with this poor prognostic group are stromal derived. We investigated the potential for tumor misclassification into multiple diagnostic subgroups based on tumoral region sampled. Experimental Design: We performed multiregion tissue RNA extraction/transcriptomic analysis using colorectal-specific arrays on invasive front, central tumor, and lymph node regions selected from tissue samples from 25 colorectal cancer patients. Results: We identified a consensus 30-gene list, which represents the intratumoral heterogeneity within a cohort of primary colorectal cancer tumors. Using a series of online datasets, we showed that this gene list displays prognostic potential HR = 2.914 (confidence interval 0.9286–9.162) in stage II/III colorectal cancer patients, but in addition, we demonstrated that these genes are stromal derived, challenging the assumption that poor prognosis tumors with stem-like biology have undergone a widespread epithelial–mesenchymal transition. Most importantly, we showed that patients can be simultaneously classified into multiple diagnostically relevant subgroups based purely on the tumoral region analyzed. Conclusions: Gene expression profiles derived from the nonmalignant stromal region can influence assignment of colorectal cancer transcriptional subtypes, questioning the current molecular classification dogma and highlighting the need to consider pathology sampling region and degree of stromal infiltration when employing transcription-based classifiers to underpin clinical decision making in colorectal cancer. Clin Cancer Res; 22(16); 4095–104. ©2016 AACR. See related commentary by Morris and Kopetz, p. 3989

Hypoxia is associated with a poor prognosis in prostate cancer. This work aimed to derive and validate a hypoxia-related mRNA signature for localized prostate cancer. Hypoxia genes were identified in vitro via RNA-sequencing and combined with in vivo gene co-expression analysis to generate a signature. The signature was independently validated in eleven prostate cancer cohorts and a bladder cancer phase III randomized trial of radiotherapy alone or with carbogen and nicotinamide (CON). A 28-gene signature was derived. Patients with high signature scores had poorer biochemical recurrence free survivals in six of eight independent cohorts of prostatectomy-treated patients (Log rank test P < .05), with borderline significances achieved in the other two (P < .1). The signature also predicted biochemical recurrence in patients receiving post-prostatectomy radiotherapy (n = 130, P = .007) or definitive radiotherapy alone (n = 248, P = .035). Lastly, the signature predicted metastasis events in a pooled cohort (n = 631, P = .002). Prognostic significance remained after adjusting for clinic-pathological factors and commercially available prognostic signatures. The signature predicted benefit from hypoxia-modifying therapy in bladder cancer patients (intervention-by-signature interaction test P = .0026), where carbogen and nicotinamide was associated with improved survival only in hypoxic tumours. A 28-gene hypoxia signature has strong and independent prognostic value for prostate cancer patients.

Purpose: EphA2, a member of the Eph receptor tyrosine kinases family, is an important regulator of tumor initiation, neovascularization, and metastasis in a wide range of epithelial and mesenchymal cancers; however, its role in colorectal cancer recurrence and progression is unclear. Experimental Design: EphA2 expression was determined by immunohistochemistry in stage II/III colorectal tumors (N = 338), and findings correlated with clinical outcome. The correlation between EphA2 expression and stem cell markers CD44 and Lgr5 was examined. The role of EphA2 in migration/invasion was assessed using a panel of KRAS wild-type (WT) and mutant (MT) parental and invasive colorectal cancer cell line models. Results: Colorectal tumors displayed significantly higher expression levels of EphA2 compared with matched normal tissue, which positively correlated with high CD44 and Lgr5 expression levels. Moreover, high EphA2 mRNA and protein expression were found to be associated with poor overall survival in stage II/III colorectal cancer tissues, in both univariate and multivariate analyses. Preclinically, we found that EphA2 was highly expressed in KRASMT colorectal cancer cells and that EphA2 levels are regulated by the KRAS-driven MAPK and RalGDS-RalA pathways. Moreover, EphA2 levels were elevated in several invasive daughter cell lines, and downregulation of EphA2 using RNAi or recombinant EFNA1 suppressed migration and invasion of KRASMT colorectal cancer cells. Conclusions: These data show that EpHA2 is a poor prognostic marker in stage II/III colorectal cancer, which may be due to its ability to promote cell migration and invasion, providing support for the further investigation of EphA2 as a novel prognostic biomarker and therapeutic target. Clin Cancer Res; 22(1); 230–42. ©2015 AACR.

Next Generation Sequencing (NGS) has the potential of becoming an important tool in clinical diagnosis and therapeutic decision-making in oncology owing to its enhanced sensitivity in DNA mutation detection, fast-turnaround of samples in comparison to current gold standard methods and the potential to sequence a large number of cancer-driving genes at the one time. We aim to test the diagnostic accuracy of current NGS technology in the analysis of mutations that represent current standard-of-care, and its reliability to generate concomitant information on other key genes in human oncogenesis. Thirteen clinical samples (8 lung adenocarcinomas, 3 colon carcinomas and 2 malignant melanomas) already genotyped for EGFR, KRAS and BRAF mutations by current standard-of-care methods (Sanger Sequencing and q-PCR), were analysed for detection of mutations in the same three genes using two NGS platforms and an additional 43 genes with one of these platforms. The results were analysed using closed platform-specific proprietary bioinformatics software as well as open third party applications. Our results indicate that the existing format of the NGS technology performed well in detecting the clinically relevant mutations stated above but may not be reliable for a broader unsupervised analysis of the wider genome in its current design. Our study represents a diagnostically lead validation of the major strengths and weaknesses of this technology before consideration for diagnostic use.