Abstract PD6-05: Distinct tumor microenvironments stratify triple negative breast cancer into immune subtypes

Background:

Triple negative breast cancer (TNBC) are especially difficult to treat effectively. While only 20-30% of TNBC patients respond to chemotherapy in the neoadjuvant setting, overall outcome remains poor for non-responding patients. Engaging the immune system promises optimal personalized cancer therapy as mounting evidence suggests that immune-checkpoint inhibitor immunotherapies may become a therapeutic option for TNBC patients. The presence of CD8+ T cells, a crucial component of the cytotoxic arm of the adaptive immune response, is associated with good clinical outcome in TNBC patients. Specifically, it is the efficient CD8+ T cell invasion and infiltration in the tumor that is associated with good outcome. On the other hand, some tumors accumulate CD8+ T cells in the tumor-associated stroma with poor infiltration in the tumor epithelium. These patients show poor outcome. As CD8+ T cell infiltration in the tumor is a crucial step to mount an efficient anti-tumor response, we thus wondered how the tumor microenvironment affects CD8+ T cell invasion into the tumor epithelial compartment of the TNBC tumors.

Methods:

To identify potential stroma-dependent mechanisms that potentiate or inhibit CD8+ T cells invasion into the tumor epithelium, we coupled analysis of spatial patterns of CD8+ T cell localization by Immunohistochemistry (IHC) andperformed gene expression profiling of laser-capture microdissected tumor-associated stroma (as well as matched epithelium and bulk tumor) from 38 TNBC chemotherapy-naive primary cases. GSEA-based Metasignatures were derived from bulk tumor gene expression data from our cohort. To investigate the compartment of origin of the pathways identified via the Metasignatures, the (LCM)-derived tumor stromal and epithelial gene expression were analyzed.

Results:

CD8+ T cell quantification in different compartments of the tumor identify 3 main subgroups of TNBC based on CD8+ T cell localization. Importantly we developed a 2-step classification scheme based on CD8+ T cell localization. We developed metasignatures following our 2 steps classification and identified key bulk tumor metasignatures that showed prognostic value in an independent cohort. In addition the matched LCM gene expression from the tumor epithelium and stromal compartments allowed us to identify the compartment of origin.

Importantly, while 1 group of TNBC tumor was showing a significant anti-tumor response, the 2 other groups showed absence of such environment. The 2 non inflamed immune subtypes showed distinct phenotypes and biologies associated with poor anti-tumor response that we validated by immunohistochemistry and fluorescence. These results highlight different potential mecanisms that lead to immune evasion and allow us to stratify TNBC into immune subgroups.

Citation Format: Gruosso T, Gigoux M, Bertos N, Manem VS, Zuo D, Saleg SM, Souleimanova M, Zhao H, Johnson RM, Monette A, Muñoz Ramos V, Hallett MT, Stagg J, Lapointe R, Omeroglu A, Meterissian S, Buisseret L, Van den Eyden G, Salgado R, Guiot M-C, Haibe-Kains B, Park M. Distinct tumor microenvironments stratify triple negative breast cancer into immune subtypes [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr PD6-05.

Urinary Markers of Fibrosis and Risk of Cardiovascular Events and Death in Kidney Transplant Recipients: The FAVORIT Trial

Cardiovascular risk remains high in kidney transplant recipients (KTRs) despite improved kidney function after transplant. Urinary markers of kidney fibrosis and injury may help to reveal mechanisms of this risk. In a case-cohort study among stable KTRs who participated in the FAVORIT trial, we measured four urinary proteins known to correlate with kidney tubulointerstitial fibrosis on biopsy (urine alpha 1 microglobulin [α1m], monocyte chemoattractant protein-1 [MCP-1], procollagen type I [PINP] and type III [PIIINP] N-terminal amino peptide) and evaluated associations with cardiovascular disease (CVD) events (n = 300) and death (n = 371). In adjusted models, higher urine α1m (hazard ratio [HR] per doubling of biomarker 1.40 [95% confidence interval [CI] 1.21, 1.62]), MCP-1 (HR 1.18 [1.03, 1.36]), and PINP (HR 1.13 [95% CI 1.03, 1.23]) were associated with CVD events. These three markers were also associated with death (HR per doubling α1m 1.51 [95% CI 1.32, 1.72]; MCP-1 1.31 [95% CI 1.13, 1.51]; PINP 1.11 [95% CI 1.03, 1.20]). Higher concentrations of urine α1m, MCP-1, and PINP may identify KTRs at higher risk for CVD events and death. These markers may identify a systemic process of fibrosis involving both the kidney and cardiovascular system, and give new insights into mechanisms linking the kidney with CVD.