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Extramural venous invasion (EMVI) is the spread of microscopic tumour cells into the veins around the tumour. Rectal cancer treatment has improved greatly over recent years. However, it is important for us to learn as much about the tumours as possible in order to develop newer therapies. Current treatments may benefit from new genetic information relating to the cancer. We hope to identify genetic differences in certain types of rectal cancer which will allow future treatments.
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Neoadjuvant chemoradiotherapy (CRT) is widely accepted as beneficial to selected patients in terms of decreased risk of local recurrence and overall survival. Current management of rectal cancer involves risk stratification through pre-operative staging leading to formulation of treatment strategy. Very little is known about the long-term outcomes and response to CRT on MRI detected extramural venous invasion (mrEMVI). Although mrEMVI is accepted as a marker of poor prognosis, whether it has a predictive value and should be specifically treated is not known.
Molecular and genetic profiling provides us with an opportunity to understand the underlying mechanisms which govern clinical behaviour in rectal cancer. Using high-throughput technology such as tissue microarray analysis allows large-scale analysis of specimens in a relatively short amount of time. It offers the ability to compare the molecular profiles of different subtypes of rectal cancer such as mrEMVI-positive and -negative tumours and whether any changes are observed following CRT. This can then be correlated with clinical behaviour over the medium and long-term with regards to local recurrence, distant metastases and overall survival.
This study will identify important differences between key rectal cancer tumour subtypes. Identification of reliable pathological markers of EMVI pathways (from both the primary tumour sample, but more importantly from the pre-operative biopsies) has real potential for taking us a step closer to more personalised management of rectal cancer by establishing prognostic biomarkers reflective of disease type, but also through the underlying biology that may be highlighted (with its promise of therapeutic translation).
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246 participants in 2 patient groups
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Data sourced from clinicaltrials.gov
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