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1285 Computational deconvolution identifies a Th2-enriched immune-inflammatory signature in invasive breast carcinoma

August, 08, 2024 | Select Oncology Journal Articles

Background

Breast cancer (BC) is the most common cancer in women and current treatments for invasive BC are not effective or do not prevent recurrence.1

Cancer progression, response to treatment and the development of resistance to therapy are complex phenomena mediated by intrinsic tumor biology, and by their interaction with the tumor microenvironment (TME). Deconvoluting the molecular dynamics at play in the TME at different stages of cancer progression may unlock optimal treatment efficacy and improve patients’ outcomes.

Recent advances in high throughput molecular profiling technologies combined with novel computational methods have revolutionized our ability to decipher the role of immune cells in tumorigenesis and tumor suppression, therefore providing actionable insights on how to modulate the TME for therapeutic purposes.

Amongst infiltrated immune populations in the TME, CD4+ T helper (Th) cells play a central role in coordinating the adaptive immune responses at epithelial sites by releasing a wide array of cytokines. 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 associated with an anti-tumorigenic role in pancreatic and gastric cancer while being pro-tumoral in other cancer types. The pro or anti tumorigenic role of Th2 cells in BC is still disputed. Gaining better understanding of those factors influencing inflammatory states throughout different stages of tumor progression is therefore critical to guide future treatments.

Methods

To identify the differential inflammatory state of primary inflammatory BC and the matched metastatic tissues, cellular deconvolution analysis on TCGA transcriptomics data was performed.2 Abundance of different cell types were compared between matched primary and metastatic samples.

Results

The results revealed that BC primary tumors are characterized by a significantly more prominent Th2 inflammatory state when compared to matched metastasis. The bioinformatic analysis also uncovered a new role of Th2 cells in inflammatory BC, when associated with tumor-infiltrating myeloid cells.

Conclusions

The newly identified inflammation signature was featured exclusively in primary tumors and could be a novel therapeutic target to prevent progression in breast cancer patients. Leveraging similar computational approaches will allow us to perform biomarker identification studies and guide drug discovery targeting new pathways and cellular subpopulations.

References

  • Zahl PH, Mæhlen J, Welch HG. The Natural History of Invasive Breast Cancers Detected by Screening Mammography. Arch Intern Med 2008;168:2311–2316.

  • Aran D, Hu Z, Butte AJ. xCell: Digitally portraying the tissue cellular heterogeneity landscape. Genome Biol 2017;18:1–14.

  • Ethics Approval

    All human biological samples utilized for the research described in this abstract have been procured or collected after an Informed Consent form has been issued according to the current local legislation. All animals studies described in this abstract have been conducted under Champions’ approved IACUC.

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