Spatially distinct tumor immune microenvironments stratify triple-negative breast cancers

Gruosso, Tina; Gigoux, Mathieu; Manem, Venkata S. K.; Bertos, Nicholas; Zuo, Dongmei; Perlitch, Irina; Saleh, Sadiq M.I.; Zhao, Hong; Souleimanova, Margarita; Johnson, Radia Marie; Monette, Anne; Ramos, Valentina Muñoz; Hallett, Michael; Stagg, John; Lapointe, Réjean; Ömeroğlu, Atilla; Meterissian, Sarkis; Buisseret, Laurence; Eynden, Gert Van den; Salgado, Roberto; Guiot, Marie Christine; Haibe‐Kains, Benjamin; Park, Morag

doi:10.1172/jci96313

Cited by 296 publications

(343 citation statements)

References 56 publications

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“…These discrepancies suggest that when considered alone, molecular subtypes or immune infiltration does not fully capture the varied clinical course of pGBMs. Our work established that both factors have independent prognostic value and combining them significantly improved our ability to predict survival, as also reported by others (Gruosso et al , 2019; Zeng et al , 2019), including recently in GBM (Klopfenstein et al , 2019).…”

Section: Discussionsupporting

confidence: 88%

Improved prognostication of glioblastoma beyond molecular subtyping by transcriptional profiling of the tumor microenvironment

et al. 2020

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Glioblastoma (GBM), the most aggressive form of brain cancer, is characterized by a high level of molecular heterogeneity, and infiltration by various immune and stromal cell populations. Important advances have been made in deciphering the microenvironment of GBMs, but its association with existing molecular subtypes and its potential prognostic role remain elusive. We have investigated the abundance of infiltrating immune and stromal cells in silico, from gene expression profiles. Two cohorts, including in-house normal brain and glioma samples (n = 70) and a large sample set from TCGA (n = 393), were combined into a single exploratory dataset. A third independent cohort (n = 124) was used for validation. Tumors were clustered based on their microenvironment infiltration profiles, and associations with known GBM molecular subtypes and patient outcome were tested a posteriori in a multivariable setting. We identified a subset of GBM samples with significantly higher abundances of most immune and stromal cell populations. This subset showed increased expression of both immune suppressor and immune effector genes compared to other GBMs and was enriched for the mesenchymal molecular subtype. Survival analyses suggested that tumor microenvironment infiltration pattern was an independent prognostic factor for GBM patients. Among all, patients with the mesenchymal subtype with low immune and stromal infiltration had the poorest survival. By combining molecular subtyping with gene expression measures of tumor infiltration, the present work contributes with improving prognostic models in GBM.

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Section: Discussionsupporting

confidence: 88%

Improved prognostication of glioblastoma beyond molecular subtyping by transcriptional profiling of the tumor microenvironment

et al. 2020

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“…In addition, accumulating evidence suggests that the density of stroma‐infiltrating immune cells reflects the focal immune response of patients to chemotherapy regimens and may serve as a promising predictor 11‐13 . Although some studies have investigated the prognostic relevance of some immune cells in TNBC, there are few systematic studies on the association between the overall stromal immune cell signature and clinical outcomes 12,14,15 …”

Section: Introductionmentioning

confidence: 99%

Development and validation of a stromal immune phenotype classifier for predicting immune activity and prognosis in triple‐negative breast cancer

Zheng

Zou

Xie

et al. 2020

Intl Journal of Cancer

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Our study aims to construct a prognosis-related immune phenotype classifier for predicting clinical prognosis and immune activity in triple-negative breast cancer (TNBC). A total of 237 patients with TNBC from Sun Yat-sen University Cancer Center (SYSUCC) and 533 patients with TNBC from public datasets were included in our study. A stromal immune quantified index was generated with a LASSO Cox regression model based on five prognosis-related immune cells evaluated by CIBERSORT or IHC and was used to determine immune phenotypes. Immune features were evaluated in the samples before chemotherapy. A total of 119 patients in the SYSUCC training cohort were classified into immune Phenotypes A and B according to the density of stromal CD4+ T cells, γδ T cells, monocytes, M1 macrophages and M2 macrophages. Phenotype A predicted better survival than Phenotype B, and the classification was further validated in the testing cohort of 118 patients and the validation cohort of 533 patients. In the combined cohort, significant differences were found in Phenotype A compared to Phenotype B for the 5-year overall survival (83.5% vs 65.8%, respectively, P < .01) and the 5-year disease-free survival (87.3% vs 76.0%, respectively, P < .01). In Phenotype A, immune-related pathways were significantly enriched, and a higher level of immune checkpoint molecules, including PD-L1, PD-1 and CTLA-4, could be observed. The immune phenotype classification was an independent prognostic indicator for TNBC and might serve as a potential predictor for immune activity within the tumor microenvironment. K E Y W O R D Sclassifier, immune phenotype, prognosis, stromal immune score, triple-negative breast cancer

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“…2c ). To gain insight into the cellular sources of LOX and LH2 in human tumors, we used laser capture microdissection to isolate regions of tumor epithelium and stroma to identify the origins of LOX and LH2 in invasive human breast cancers (38, 39). Gene expression analysis of stromal and epithelial compartments revealed that the stromal cells in the tumor tissue expressed significantly more LOX and PLOD2 than the associated tumor epithelium.…”

Section: Resultsmentioning

confidence: 99%

Inflammation promotes tumor aggression by stimulating stromal cell-dependent collagen crosslinking and stromal stiffening

Maller¹,

Drain²,

Barrett

et al. 2020

Preprint

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1Collagen deposition and stromal stiffening accompany malignancy, compromise treatment, and 2 promote tumor aggression. Clarifying the molecular nature of and the factors that regulate 3 extracellular matrix stiffening in tumors should identify biomarkers to stratify patients for therapy 4 and therapeutic interventions to improve outcome. We profiled lysyl hydroxylase-and lysyl 5 oxidase-mediated collagen crosslinks and quantified the greatest abundance of total and complex 6 collagen crosslinks in more aggressive human breast cancer subtypes with the stiffest stroma. 7These tissues also harbored the highest number of tumor-associated macrophages (TAM), whose 8 therapeutic ablation not only reduced metastasis, but also concomitantly decreased accumulation 9 of collagen crosslinks and stromal stiffening. Epithelial-targeted expression of the crosslinking 10 enzyme lysyl oxidase had no impact on collagen crosslinking in PyMT mammary tumors, whereas 11 stromal cell targeting did. Consistently, stromal cells in microdissected human tumors expressed 12 the highest level of collagen crosslinking enzymes. Immunohistochemical analysis of a cohort of 13 breast cancer patient biopsies revealed that stromal expression of lysyl hydroxylase two, an 14 enzyme that induces hydroxylysine aldehyde-derived collagen crosslinks and stromal stiffening 15 correlated significantly disease specific mortality. The findings link tissue inflammation, stromal 16 cell-mediated collagen crosslinking and stiffening to tumor aggression and identify lysyl 17 hydroxylase two as a novel stromal biomarker. 18 19Significance 20We show infiltrating macrophages induce stromal fibroblast, and not epithelial, expression of 21 collagen crosslinking enzymes that drive tumor stiffening. Stromal enzyme LH2 is significantly 22 upregulated in breast cancer patients with the stiffest stroma, the most trivalent HLCCs and the 23 worst prognosis, underscoring its potential as a biomarker and therapeutic target. 24 25 Her2/Neu mice or genetic reduction of PLOD2 in subcutaneously-injected lung tumor epithelial 52 cells reduce tissue fibrosis, stromal stiffening and collagen crosslinking and concomitantly 53 decrease tumor incidence and aggression(12,23). Moreover, elevating LOX or LH2-mediated 54 collagen crosslinking enhances fibrosis and stromal stiffness and promotes malignant 55 transformation and tumor aggression in lung and mammary xenografted tumors(12,23). These 56 observations suggest that the direct targeting of specific collagen crosslinking enzymes has 57 clinical merit for the treatment of cancer. However, given caveats with recent clinical trials 58 targeting ECM modifiers including suboptimal activity of inhibitory treatments and the risk of off-59 target effects, strategies designed to interfere with the induction and activation of these 60 crosslinking enzymes offer an attractive alternative(26). Towards this goal, the identification and 61 causal implication of additional factors that regulate the levels and/or activity of collagen 62 crosslinking...

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Spatially distinct tumor immune microenvironments stratify triple-negative breast cancers

Cited by 296 publications

References 56 publications

Improved prognostication of glioblastoma beyond molecular subtyping by transcriptional profiling of the tumor microenvironment

Improved prognostication of glioblastoma beyond molecular subtyping by transcriptional profiling of the tumor microenvironment

Development and validation of a stromal immune phenotype classifier for predicting immune activity and prognosis in triple‐negative breast cancer

Inflammation promotes tumor aggression by stimulating stromal cell-dependent collagen crosslinking and stromal stiffening

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