Molecular subtypes of pancreatic cancer

By E. Collisson, Peter Bailey, D. Chang, A. Biankin. Nature reviews: Gastroenterology & hepatology, 2019

736 citations recorded by the source corpus.

Cancers that appear morphologically similar often have dramatically different clinical features, respond variably to therapy and have a range of outcomes. Compelling evidence now demonstrates that differences in the molecular pathology of otherwise indistinguishable cancers substantially impact the clinical characteristics of the disease. Molecular subtypes now guide preclinical and clinical therapeutic development and treatment in many cancer types. The ability to predict optimal therapeutic strategies ahead of treatment improves overall patient outcomes, minimizing treatment-related morbidity and cost. Although clinical decision making based on histopathological criteria underpinned by robust data is well established in many cancer types, subtypes of pancreatic cancer do not currently inform treatment decisions. However, accumulating molecular data are defining subgroups in pancreatic cancer with distinct biology and potential subtype-specific therapeutic vulnerabilities, providing the opportunity to define a de novo clinically applicable molecular taxonomy. This Review summarizes current knowledge concerning the molecular subtyping of pancreatic cancer and explores future strategies for using a molecular taxonomy to guide therapeutic development and ultimately routine therapy with the overall goal of improving outcomes for this disease.This Review summarizes current knowledge concerning the molecular subtyping of pancreatic cancer and explores future strategies using molecular taxonomy to guide therapeutic development and therapy with the overall goal of improving outcomes for this disease.Key pointsPancreatic cancer is soon to become the second leading cause of cancer-related death.Histopathological criteria do not adequately inform treatment decisions for pancreatic cancer.A molecular taxonomy could improve outcomes with current treatments and accelerate therapeutic development through better patient selection.Emerging molecular taxonomies define biological differences between subtypes that are associated with prognosis.Genomic and transcriptomic subtypes potentially enrich for therapeutic vulnerabilities and require preclinical and clinical assessment.

Subfields: Cancer Research, Oncology

View Paper: https://www.semanticscholar.org/paper/6584940bfb94dc12aaabbf933fe8598c4c3f405e

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Citations in the corpus

An Introduction to Machine Learning (2020, background): “17 A cluster is a subset of the data which are “similar” to each other, whereas points belonging to different clusters are more “different.””