Back

Proteomic landscape of multi-layered breast cancer internal tumor heterogeneity

Mardamshina, M.; Shenoy, A.; Necula, D.; Krol, K.; Pirak, D.; Itzhacky, N.; Marin, I.; Shalmon, B.; Sharan, R.; Gal-Yam, E. N.; Barshack, I.; Geiger, T.

2021-08-06 cancer biology
10.1101/2021.08.05.455361 bioRxiv
Show abstract

Despite extensive research, internal tumor heterogeneity presents enormous challenges to achieve complete therapeutic responses. Changes in protein expression are central determinants of cancer phenotypes that reflect potential therapeutic targets. However, previous proteomic studies did not address internal heterogeneity, therefore, masked the necessary spatial resolution to achieve a comprehensive understanding of cancer complexity. Here we present the first large-scale multi-focal breast cancer proteomic study of 330 tumor regions which associated cancer cell function, pathological parameters, and spatial localization of each tumor region. We found marked internal proteomic heterogeneity even within tumors presenting homogeneous receptor expression. Additionally, analysis of the internal heterogeneity, based on coexisting receptor expression or histological patterns in single tumors, showed significant functional differences between homogeneous and heterogeneous tumors related to cancer metabolism, immunogenicity, and proliferation. We anticipate that this study will serve as a starting point towards the development of improved cancer therapy and diagnostics.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.