Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA252731 | ENA |
REPOSITORIES: ENA
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Project description:Immune checkpoint inhibitors combined with chemotherapy represent a promising treatment option in triple-negative breast cancer (TNBC). However, response rates are still relatively low necessitating the design of novel therapeutic strategies to improve clinical outcomes. Here, we describe a triple combination of anti-PDL-1 immune checkpoint blockade, epigenetic modulation thorough BET bromodomain inhibition, and chemotherapy with paclitaxel that effectively inhibits both primary and metastatic tumor growth in two different syngeneic murine breast cancer models. Detailed cellular and molecular profiling of tumors from single and combination treatment arms revealed increased T and B cell infiltration and macrophage reprogramming from M1 to a M2 phenotype in mice treated with triple combination.
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Project description:Immune checkpoint inhibitors combined with chemotherapy represent a promising treatment option in triple-negative breast cancer (TNBC). However, response rates are still relatively low necessitating the design of novel therapeutic strategies to improve clinical outcomes. Here, we describe a triple combination of anti-PDL-1 immune checkpoint blockade, epigenetic modulation thorough BET bromodomain inhibition, and chemotherapy with paclitaxel that effectively inhibits both primary and metastatic tumor growth in two different syngeneic murine breast cancer models. Detailed cellular and molecular profiling of tumors from single and combination treatment arms revealed increased T and B cell infiltration and macrophage reprogramming from M1 to a M2 phenotype in mice treated with triple combination.
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Project description:Therapeutic strategies that improve survival outcomes for advanced-stage breast cancers have proven a major clinical challenge. Here, we define an androgen receptor signalling network that governs the maintenance and de novo formation of cancer stem cells in triple-negative breast cancer. In response to chemotherapy, androgen receptor activation switches cells into a cancer stem cell state, while androgen receptor antagonism suppresses cancer stem cell formation and function. In vivo, we validate that the androgen receptor antagonist, seviteronel, significantly improves chemotherapy-mediated inhibition of primary and metastatic tumour growth.
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Project description:Therapeutic strategies that improve survival outcomes for advanced-stage breast cancers have proven a major clinical challenge. Here, we define an androgen receptor signalling network that governs the maintenance and de novo formation of cancer stem cells in triple-negative breast cancer. In response to chemotherapy, androgen receptor activation switches cells into a cancer stem cell state, while androgen receptor antagonism suppresses cancer stem cell formation and function. In vivo, we validate that the androgen receptor antagonist, seviteronel, significantly improves chemotherapy-mediated inhibition of primary and metastatic tumour growth.
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Project description:In the study presented here, a consecutively operated, well-defined cohort of 30 triple-negative breast cancer cases with neoadjuvant chemotherapy, followed up more than five years, was used to acquire TP53 signature composed of a total of 33 genes. Combining the response to NAC and the TP53signature score in triple-negative breast cancer was able to predict an unfavorable prognosis.
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Project description:Triple-Negative Breast Cancer (TNBC) is a heterogeneous collection of cancers where personalized treatment is difficult and chemotherapy and immunotherapy combinations are the main treatment options. Many attempts to tackle patient heterogeneity have focused on defining cancer-intrinsic subtypes based on differential tumor mRNA-expression across patient cohorts. While these multi-gene diagnostics have shown success in hormone receptor- positive cancers (e.g. OncotypeDX), no TNBC classifiers have shown clinical utility in predicting patient survival or treatment response. We hypothesize that TNBC-infiltrating immune-cells both affect mRNA-based classification and contribute to treatment response variability. To evaluate this hypothesis, we benchmarked the performance of common TNBC-classification (TNBC-type) and infiltrating immune (CIBERSORT) algorithms on the same underlying datasets. Encouragingly, we found that – as with OncotypeDx– highly proliferative TNBC-subtypes (BL1) show the strongest evidence of response to cytotoxic chemotherapies. Interestingly, this cancer-proliferative signature (BL1) is strongly correlated with enrichment in tumor-infiltrating lymphocyte signatures (TIL) which show superior prognostic and predictive power. In addition, Tumor Associated Macrophage (TAM) signatures show independent predictive and prognostic power for both patient survival and response to anthracycline- and taxane-based chemotherapies. These gene signature-based correlations were validated in a new independent cohort of 67 TNBC-patients treated with neoadjuvant chemotherapy. Overall, these results argue for the independent contributions of both cancer-intrinsic and -extrinsic factors in predicting treatment response in the neoadjuvant setting.
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