Details

Autor(en) / Beteiligte

• Malla, Sudhir B.
• Byrne, Ryan M.
• Lafarge, Maxime W.
• Corry, Shania M.
• Fisher, Natalie C.
• Tsantoulis, Petros K.
• Mills, Megan L.
• Ridgway, Rachel A.
• Lannagan, Tamsin R. M.
• Najumudeen, Arafath K.
• Gilroy, Kathryn L.
• Amirkhah, Raheleh
• Maguire, Sarah L.
• Mulholland, Eoghan J.
• Belnoue-Davis, Hayley L.
• Grassi, Elena
• Viviani, Marco
• Rogan, Emily
• Redmond, Keara L.
• Sakhnevych, Svetlana
• McCooey, Aoife J.
• Bull, Courtney
• Hoey, Emily
• Sinevici, Nicoleta
• Hall, Holly
• Ahmaderaghi, Baharak
• Domingo, Enric
• Blake, Andrew
• Richman, Susan D.
• Isella, Claudio
• Miller, Crispin
• Bertotti, Andrea
• Trusolino, Livio
• Loughrey, Maurice B.
• Kerr, Emma M.
• Tejpar, Sabine
• Maughan, Timothy S.
• Lawler, Mark
• Campbell, Andrew D.
• Leedham, Simon J.
• Koelzer, Viktor H.
• Sansom, Owen J.
• Dunne, Philip D.

Titel

Pathway level subtyping identifies a slow-cycling biological phenotype associated with poor clinical outcomes in colorectal cancer

Ist Teil von

• Nature genetics, 2024-03, Vol.56 (3), p.458-472

Ort / Verlag

New York: Nature Publishing Group US

Erscheinungsjahr

2024

Beschreibungen/Notizen

• Molecular stratification using gene-level transcriptional data has identified subtypes with distinctive genotypic and phenotypic traits, as exemplified by the consensus molecular subtypes (CMS) in colorectal cancer (CRC). Here, rather than gene-level data, we make use of gene ontology and biological activation state information for initial molecular class discovery. In doing so, we defined three pathway-derived subtypes (PDS) in CRC: PDS1 tumors, which are canonical/LGR5 + stem-rich, highly proliferative and display good prognosis; PDS2 tumors, which are regenerative/ANXA1 + stem-rich, with elevated stromal and immune tumor microenvironmental lineages; and PDS3 tumors, which represent a previously overlooked slow-cycling subset of tumors within CMS2 with reduced stem populations and increased differentiated lineages, particularly enterocytes and enteroendocrine cells, yet display the worst prognosis in locally advanced disease. These PDS3 phenotypic traits are evident across numerous bulk and single-cell datasets, and demark a series of subtle biological states that are currently under-represented in pre-clinical models and are not identified using existing subtyping classifiers. Analysis of colorectal cancer bulk gene expression data at the pathway level identifies a poor-prognosis subtype associated with cell differentiation. The subtypes are reproducible in single-cell data and offer biological insights beyond existing stratification strategies.