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Sanders, M. E.

Publications and source records attributed to Sanders, M. E..

2 recordsLinked to original sources

Tumor cell-adipocyte gap junctions activate lipolysis and are essential for breast tumorigenesis

A pro-tumorigenic role for adipocytes has been identified in breast cancer, and reliance on fatty acid catabolism found in aggressive tumors. The molecular mechanisms by which tumor cells coopt neighboring adipocytes, however, remain elusive. Here, we describe a direct interaction linking tumorigenesis to adjacent adipocytes. We examine breast tumors and their normal adjacent tissue from several patient cohorts, patient-derived xenografts and mouse models, and find that lipolysis and lipolytic signaling are activated in neighboring adipose tissue. We find that functional gap junctions form between breast cancer cells and adipocytes. As a result, cAMP is transferred from breast cancer cells to adipocytes and activates lipolysis in a gap junction-dependent manner. We identify connexin 31 (GJB3), which promotes receptor triple negative breast cancer growth and activation of lipolysis in vivo. Thus, direct tumor cell-adipocyte interaction contributes to tumorigenesis and may serve as a new therapeutic target in breast cancer. One sentence summaryGap junctions between breast cancer cells and adipocytes transfer cAMP and activate lipolysis in the breast tumor microenvironment to support growth.

cancer biology

quanTIseq: quantifying immune contexture of human tumors

The immune contexture has a prognostic value in several cancers and the study of its pharmacological modulation could identify drugs acting synergistically with immune checkpoint blockers. However, the quantification of the immune contexture is hampered by the lack of simple and efficient methods. We developed quanTIseq, a deconvolution method that quantifies the densities of ten immune cell types from bulk RNA sequencing data and tissue imaging data. We performed extensive validation using simulated data, flow cytometry data, and immunohistochemistry data from three cancer cohorts.\n\nAnalysis of 8,000 samples showed that the activation of the CXCR3/CXCL9 axis, rather than the mutational load is associated with cytotoxic T cell infiltration. We also show the prognostic value of deconvolution-based immunoscore and T cell/B cell score in several solid cancers. Finally, we used quanTIseq to show how kinase inhibitors modulate the immune contexture, and we suggest that it might have predictive value for immunotherapy.

bioinformatics