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Computational Deconvolution Identifies a Th2-enriched Immune-Inflammatory Signature in Invasive Breast Carcinoma

A Champions SITC 2023 Poster


Breast cancer (BC) is the most common cancer in women and current treatments for invasive BC are not decisive and do not prevent breast cancer recurrence.

Cancer progression, response, and resistance to therapy are multifaceted phenomena mediated by tumor intrinsic factors, and by the complex milieu of cellular interactions occurring between tumor cells and their microenvironment. Understanding the molecular dynamics in the tumor microenvironment (TME) at different stages of cancer progression may unlock optimal treatment efficacy, by enabling therapeutical control over the behavior of the cellular component within the TME.

Novel high throughput molecular profiling technologies and new computational methods revolutionized our ability to characterize the tumor immune microenvironment providing the missing piece to achieve control over the TME.

Within tumor tissues, the inflammatory status of the TME is orchestrated by CD4+ T helper (Th) cells which play a central role in coordinating the adaptive immune responses at epithelial sites by releasing a wide array of cytokines that recruit and regulate the activity of other immune cells.
Within BC tissues the development of inflammatory Th2 cells is driven by molecular signaling involving IL-4, IL-5, IL-9, and IL-13 expressed by both tumor cells and stroma. Th2 cells have been described as anti-tumorigenic in pancreatic and gastric cancer while being pro-tumoral in other cancer types.4 The pro or anti-tumorigenic role of Th2 cells in BC is still controversial and a better understanding of the factors influencing inflammatory states throughout different stages of tumor progression will be able to guide anti-metastatic treatments.

To identify the differential inflammatory state of primary inflammatory BC and the paired metastasis, cellular deconvolution analysis on TCGA transcriptomics data was performed. Cell abundances were compared between matched primary and metastatic samples.

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