Integrating histopathology and transcriptomics for spatial tumor microenvironment profiling in a melanoma case study.

Local structures formed by cells in the tumor microenvironment (TME) play an important role in tumor development and treatment response. This study introduces SPoTLIghT, a computational framework providing a quantitative description of the tumor architecture from hematoxylin and eosin (H&E) slides. We trained a weakly supervised machine learning model on melanoma patients linking tile-level imaging features extracted from H&E slides to sample-level cell type quantifications derived from RNA-sequencing data.

Multimodal analysis unveils tumor microenvironment heterogeneity linked to immune activity and evasion.

The cellular and molecular heterogeneity of tumors is a major obstacle to cancer immunotherapy. Here, we use a systems biology approach to derive a signature of the main sources of heterogeneity in the tumor microenvironment (TME) from lung cancer transcriptomics. We demonstrate that this signature, which we called , is conserved in different cancers and associated with antitumor immunity.

Radiogenomics Analysis Linking Multiparametric MRI and Transcriptomics in Prostate Cancer.

Prostate cancer (PCa) is a highly prevalent cancer type with a heterogeneous prognosis. An accurate assessment of tumor aggressiveness can pave the way for tailored treatment strategies, potentially leading to better outcomes. While tumor aggressiveness is typically assessed based on invasive methods (e.