Ruff, L. | bioRxiv Science

bioRxiv2024

Natural language processing charts transcriptome evolution to design combination cancer therapies

Combination treatment-the mainstay of cancer therapy-often fails because treatment interactions evoke complex resistance mechanisms that are hard to predict. Designing combination therapy to prevent treatment resistance is especially challenging for rare cancers. Here, we introduce REsistance through COntext DRift (RECODR): a computational pipeline that tracks how genes change their transcriptome context across cancer development and drug treatment conditions. By applying RECODR to a genetically modified mouse model of choroid plexus carcinoma-a rare brain tumour of young children-we identified patterns of transcriptome evolution, cellular heterogeneity and treatment targets that emerged as tumours were initiated and resisted combination treatment. This enabled the prediction of treatment resistance mechanisms and the design of highly effective therapeutic protocols that avoided treatment failure. RECODR can describe complex and dynamic changes in normal and diseased tissues that could be applied to multimodal data from a variety of settings, mitigating treatment resistance across cancers and other diseases.

cancer biology↗

bioRxiv2023

High-resolution molecular atlas of a lung tumor in 3D

Cells live and interact in three-dimensional (3D) cellular neighborhoods. However, histology and spatial omics methods mostly focus on 2D tissue sections. Here we present a 3D spatial atlas of a routine clinical sample, an aggressive human lung carcinoma, by combining in situ quantification of 960 cancer-related genes across [~]340,000 cells with measurements of tissue-mechanical components. 3D cellular neighborhoods subdivided the tumor microenvironment into tumor, stromal, and immune multicellular niches. Interestingly, pseudotime analysis suggested that pro-invasive epithelial-to-mesenchymal transition (EMT), detected in stroma-infiltrating tumor cells, already occurred in one region at the tumor surface. There, myofibroblasts and macrophages specifically co-localized with pre-invasive tumor cells and their multicellular molecular signature identified patients with shorter survival. Moreover, cytotoxic T-cells did not infiltrate this niche but colocalized with inhibitory dendritic and regulatory T cells. Importantly, systematic scoring of cell-cell interactions in 3D neighborhoods highlighted niche-specific signaling networks accompanying tumor invasion and immune escape. Compared to 2D, 3D neighborhoods improved the characterization of immune niches by identifying dendritic niches, capturing the 3D extension of T-cell niches and boosting the quantification of niche-specific cell-cell interactions, including druggable immune checkpoints. We believe that 3D communication analyses can improve the design of clinical studies investigating personalized, combination immuno-oncology therapies.

systems biology↗