Publications by authors named "Amy M B McCorry"

The pro-tumourigenic role of epithelial TGFβ signalling in colorectal cancer (CRC) is controversial. Here, we identify a cohort of born to be bad early-stage (T1) colorectal tumours, with aggressive features and a propensity to disseminate early, that are characterised by high epithelial cell-intrinsic TGFβ signalling. In the presence of concurrent Apc and Kras mutations, activation of epithelial TGFβ signalling rampantly accelerates tumourigenesis and share transcriptional signatures with those of the born to be bad T1 human tumours and predicts recurrence in stage II CRC.

View Article and Find Full Text PDF

Intestinal homeostasis is underpinned by LGR5+ve crypt-base columnar stem cells (CBCs), but following injury, dedifferentiation results in the emergence of LGR5-ve regenerative stem cell populations (RSCs), characterized by fetal transcriptional profiles. Neoplasia hijacks regenerative signaling, so we assessed the distribution of CBCs and RSCs in mouse and human intestinal tumors. Using combined molecular-morphological analysis, we demonstrate variable expression of stem cell markers across a range of lesions.

View Article and Find Full Text PDF

Gremlin1 (GREM1) is a secreted glycoprotein member of the differential screening-selected gene in aberrant neuroblastoma (DAN) family of bone morphogenetic protein (BMP) antagonists, which binds to BMPs preventing their receptor engagement. Previous studies have identified that stage II colorectal cancer (CRC) patients with high levels of gene expression in their tumour tissue have a poorer prognosis. Using a series of and methodologies, we demonstrate that gene expression is significantly higher ( < 0.

View Article and Find Full Text PDF

Background: 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.

Method: Hypoxia genes were identified in vitro via RNA-sequencing and combined with in vivo gene co-expression analysis to generate a signature.

View Article and Find Full Text PDF

Aims: Output from biomarker studies involving immunohistochemistry applied to tissue microarrays (TMA) is limited by the lack of an efficient and reproducible scoring methodology. In this study, we examine the functionality and reproducibility of biomarker scoring using the new, open-source, digital image analysis software, QuPath.

Methods And Results: Three different reviewers, with varying experience of digital pathology and image analysis, applied an agreed QuPath scoring methodology to CD3 and p53 immunohistochemically stained TMAs from a colon cancer cohort (n = 661).

View Article and Find Full Text PDF
Article Synopsis
  • BRAF mutations are found in 8-15% of colon cancers and are linked to poor survival outcomes, particularly in stage II/III patients, emphasizing the importance of identifying predictive markers for relapse.
  • The study utilized gene expression data from a cohort of 460 patients to find biomarkers linked to relapse risk in BRAF mutant colon cancer, with validation in a larger cohort of 691 patients using immunohistochemistry.
  • High levels of Bcl-xL, an apoptosis regulator, were identified as a strong predictor of relapse and poor survival in BRAF mutant tumors, suggesting that patients with high Bcl-xL expression may benefit from adjuvant chemotherapy.
View Article and Find Full Text PDF

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.

View Article and Find Full Text PDF