Using several clinically relevant colorectal cancer (CRC) gene expression signatures, we assessed the susceptibility of these signatures to the confounding effects of intratumoural heterogeneity (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. The findings highlight the potential of cancer-cell intrinsic signatures to reliably stratify CRC patients by minimising the confounding effects of stromal-derived ITH.
In order to maximise the value of data from genomic and clinical data from patients and healthy individuals, it is important to embed a culture within the scientific, medical and patient communities that supports the appropriate sharing of genomic and clinical information. This article identifies the challenges that a data sharing culture poses and highlights a series of practical solutions that will benefit patients, researchers and society.
This editorial discusses and interrelates the articles of the issue under four headings: the promise and the hype of personalised medicine; the human person and the communication of risk; data sharing and participation; value, equity and power. A key intention throughout is to provoke discourse and debate, to identify aspirations which are more grounded in myth or hype than reality and to challenge them; and to identify focussed, practical questions which need further examination.
Intra-tumor heterogeneity (ITH) is a major underlying cause of therapy resistance and disease recurrence, and is a read-out of tumor growth. Current genetic ITH analysis methods do not preserve spatial context and may not detect rare subclones. Here, we address these shortfalls by developing and validating BaseScope-a novel mutation-specific RNA in situ hybridization assay.
In this review of a large number of colorectal cancer (CRC) transcriptional studies, we identify recurrent sources of technical variability that encompass collection, preservation and storage of malignant tissue, nucleic acid extraction, methods to quantitate RNAtranscripts and data analysis pipelines. We propose a series of defined steps for removal of these confounding issues, to ultimately aid in the development of more robust clinical biomarkers.
Evidence strongly indicates that extended RAS testing should be undertaken in mCRC patients, prior to prescribing anti-EGFR therapies. Data was analysed from 15 United Kingdom National External Quality Assessment Service (UK NEQAS) for Molecular Genetics Colorectal cancer external quality assurance (EQA) schemes, delivered between 2009 and 2016. Within this EQA scheme, we have observed that the quality of molecular analysis for colorectal cancer has continued to improve, despite changes in the required targets, the volume of testing and the technologies employed.
In this study, we undertook a comprehensive assessment of the robustness of colorectal cancer (CRC) transcriptional signatures, including colorectal cancer intrinsic subtypes (CRISs) and consensus molecular subtypes (CMSs), using a range of tumour sampling methodologies currently employed in clinical and translational research. 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.
The biomedical paradigm of personalised precision medicine - identification of specific molecular targets for treatment of an individual patient - offers great potential for treatment of many diseases including cancer. This article provides a critical analysis of the promise, the hype, and the pitfalls attending this approach. In particular, we focus on “molecularly unstratified” patients - those who, for various reasons, are not eligible for a targeted therapy. We outline future research to consider the societal, psycho-social and moral issues relating to “molecularly unstratified” patients, and the impact of the drive towards personalisation on the research, funding, and regulatory ecosystem.
We used gene expression data from a cohort of 460 patients (GSE39582) to perform a supervised classification analysis based on risk-of-relapse within BRAF mutant (BRAFMT)stage II/III colon cancers (CC), to identify transcriptomic biomarkers associated with prognosis within this genotype. 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.
Colorectal cancer (CRC) leads to significant morbidity/mortality worldwide. Defining critical research gaps (RG), their prioritisation and resolution, could improve patient outcomes. RG analysis was conducted by a multidisciplinary panel of patients, clinicians and researchers (n=71). Eight working groups (WG) were constituted: discovery science; risk; prevention; early diagnosis and screening; pathology; curative treatment; stage IV disease; and living with and beyond CRC. The study concluded that prioritising research activity and funding could have a significant impact on reducing CRC disease burden over the next 5 years.
Molecular indicators of colorectal cancer prognosis have been assessed in several studies, but most analyses have been restricted to a handful of markers. We aimed to identify prognostic biomarkers for colorectal cancer by sequencing panels of multiple driver genes. Multigene panels identified two previously unreported prognostic associations in colorectal cancer involving TP53 mutation and total mutation burden, and confirmed associations with KRAS and BRAF. Even a modest-sized gene panel can provide important information for use in clinical practice and outperform MSI-based prognostic models.