Exploring ten distinct types of cancer, scientists uncovered the common threads that weave through the intricate tapestry of tumourigenesis. By integrating multi-omic data, including genomic and proteomic information, they unveiled shared pathways that harbour oncogenic drivers across various cancer types. This revelation a panoramic view of the molecular landscapes that drive cancer, transcending the boundaries of individual tumour categories. Intriguingly, the researchers found that genetic alterations in cancer cells have a profound impact on protein-protein interactions within the cellular milieu. Like architects rearranging building blocks, genetic changes lead to the rewiring of protein networks, creating novel avenues for cellular communication. This insight opens the door to understanding how genetic mutations influence the complex interplay of proteins and potentially contribute to the development of cancer.

Not all oncogenic drivers are created equal. The study unveiled a heterogeneous landscape of driver effects, where different drivers display distinct influences on cellular processes. This heterogeneity goes beyond genetic alterations and extends to the functional effects of these drivers. Peering even deeper, the researchers discovered a fascinating convergence point. Despite the diversity of oncogenic drivers, many cancer genes seem to gravitate towards similar molecular states, characterized by specific kinase activity profiles. This convergence hints at underlying similarities in how these drivers manipulate cellular signalling pathways, offering potential targets for future therapeutic interventions. By correlating predicted neoantigen burden with the infiltration of T cells – key players in the immune response – potential vulnerabilities in cancer cells that could be exploited for immunotherapies were found.

Cancer is notorious for its hallmarks – distinct characteristics that define different types of tumours. This study adds a new layer of complexity to these hallmarks by revealing how polygenic protein abundance influences their patterns. From uniformity to heterogeneity, the protein landscape contributes to the diverse manifestations of cancer hallmarks across different tumours.

Pan-cancer proteogenomics connects oncogenic drivers to functional states

Yize Li, Eduard Porta-Pardo, Collin Tokheim, Matthew H Bailey, Tomer M Yaron, Vasileios Stathias, Yifat Geffen, Kathleen J Imbach, Song Cao, Shankara Anand, Yo Akiyama, Wenke Liu, Matthew A Wyczalkowski, Yizhe Song, Erik P Storrs, Michael C Wendl, Wubing Zhang, Mustafa Sibai, Victoria Ruiz-Serra, Wen-Wei Liang, Nadezhda V Terekhanova, Fernanda Martins Rodrigues, Karl R Clauser, David I Heiman, Qing Zhang, Francois Aguet, Anna P Calinawan, Saravana M Dhanasekaran, Chet Birger, Shankha Satpathy, Daniel Cui Zhou, Liang-Bo Wang, Jessika Baral, Jared L Johnson, Emily M Huntsman, Pietro Pugliese, Antonio Colaprico, Antonio Iavarone, Milan G Chheda, Christopher J Ricketts, David Fenyö, Samuel H Payne, Henry Rodriguez, Ana I Robles, Michael A Gillette, Chandan Kumar-Sinha, Alexander J Lazar, Lewis C Cantley, Gad Getz, Li Ding; Clinical Proteomic Tumor Analysis Consortium