Identification and validation of a combined hypoxia and immune index for triple‐negative breast cancer

Zheng, Shaoquan; Zou, Yutian; Liang, Jie; Xiao, Weikai; Yang, Anli; Meng, Tiebao; Lu, Shilin; Luo, Zhongbing; Xie, Xiaoming

doi:10.1002/1878-0261.12747

Cited by 69 publications

(69 citation statements)

References 65 publications

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“…The key markers of hypoxia (ALDOA, ENO1, LDHA, etc.) are highly expressed in the hypoxia high / immune low group, while a higher percentage of CD8+ T cells was observed in the hypoxia low /immune high group (40). In this case, both their and our results confirmed that there is a strong positive correlation between the hypoxia status of tumor and immunosuppression.…”

Section: Discussionsupporting

confidence: 83%

Hypoxia-Associated Prognostic Markers and Competing Endogenous RNA Co-Expression Networks in Breast Cancer

et al. 2020

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ObjectiveMany primary tumors have insufficient supply of molecular oxygen, called hypoxia. Hypoxia is one of the leading characteristics of solid tumors resulting in a higher risk of local failure and distant metastasis. It is quite necessary to investigate the hypoxia associated molecular hallmarks in breast cancer.Materials and MethodsAccording to the published studies, we selected 13 hypoxia related gene expression signature to define the hypoxia status of breast cancer using ConsensusClusterPlus package based on the data from The Cancer Genome Atlas (TCGA). Subsequently, we characterized the infiltration of 24 immune cell types under different hypoxic conditions. Furthermore, the differentially expressed hypoxia associated microRNAs, mRNAs and related signaling pathways were analyzed and depicted. On this basis, a series of prognostic markers related to hypoxia were identified and ceRNA co-expression networks were constructed.ResultsTwo subgroups (cluster1 and cluster2) were identified and the 13 hypoxia related gene signature were all up-regulated in cluster1. Thus, we defined the cluster1 as “hypoxic subgroup” compared with cluster2. The infiltration of CD8+ T cell and CD4+ T cell were lower in cluster1 while the nTreg cell and iTreg cell were higher, indicating that there was immunosuppressive status in cluster1. We observed widespread hypoxia-associated dysregulation of microRNAs and mRNAs. Next, a risk signature for predicting prognosis of breast cancer patients was established based on 12 dysregulated hypoxia associated prognostic genes. Two microRNAs, hsa-miR-210-3p and hsa-miR-190b, with the most significant absolute logFC value were related to unfavorable and better prognosis, respectively. Several long non-coding RNAs were predicted to be microRNA targets and positively correlated with two selected mRNAs, CPEB2 and BCL11A. Predictions based on the SNHG16-hsa-miR-210-3p-CPEB2 and LINC00899/PSMG3-AS1/PAXIP-AS1-hsa-miR-190b-BCL11A ceRNA regulation networks indicated that the two genes might act as tumor suppressor and oncogene, respectively.ConclusionHypoxia plays an important role in the initiation and progression of breast cancer. Our research provides potential mechanisms into molecular-level understanding of tumor hypoxia.

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Section: Discussionsupporting

confidence: 83%

Hypoxia-Associated Prognostic Markers and Competing Endogenous RNA Co-Expression Networks in Breast Cancer

et al. 2020

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“…Biological processes including apoptosis, hypoxia, mTORC1 signaling and myogenesis, and oncogenic features of EGFR and RAF were in proactivity to attribute to an inferior response. In fact, the potential triggers of distinct response to NCT remain undetermined, considering these findings to some extent enlighten the quest for improvement of efficacy, which were in accordance with the previous studies [34][35][36][37]. Current trials have exerted efforts and assess the efficacy of this kind of targeted therapies in TNBC [38,39], while these results were controversial and remained to be updated through randomized controlled trials with a large sample cohort.…”

Section: Discussionsupporting

confidence: 77%

Novel biomarkers and prediction model for the pathological complete response to neoadjuvant treatment of triple-negative breast cancer

Wang¹,

Xu²

2021

J. Cancer

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“…Biological processes including apoptosis, hypoxia, mTORC1 signaling and myogenesis, and oncogenic features of EGFR and RAF were in proactivity to attribute to an inferior response. In fact, the potential triggers of distinct response to NCT remain undetermined, considering, these ndings to some extent enlighten the quest for improvement of e cacy, which were in accordance with the previous studies [24][25][26][27]. Current trials have exerted efforts and assess the e cacy of this kind of targeted therapies in TNBC [28,29], however, these results were controversial and remained to be updated through randomized controlled trials with a large sample cohort.…”

Section: Discussionsupporting

confidence: 77%

Novel biomarkers and prediction model for the pathological complete response to neoadjuvant treatment of triple-negative breast cancer

Wang

2020

Preprint

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Background: To develop and validate a prediction model for the pathological complete response (pCR) to neoadjuvant chemotherapy (NCT) of triple-negative breast cancer (TNBC).Methods: We systematically searched Gene Expression Omnibus, ArrayExpress, and PubMed for the gene expression profiles of operable TNBC accessible to NCT. The molecular heterogeneity was detected with hierarchical clustering method, and the biological profiles of differentially expressed genes were investigated by Gene Ontology, Kyoto Encyclopedia of Genes and Genomes analyses, and Gene Set Enrichment Analysis (GSEA). Next, the machine-learning algorithms including random-forest analysis and least absolute shrinkage and selection operator (LASSO) analysis were synchronously performed and, then, the intersected proportion of genes were undergone binary logistic regression to fulfill variables selection. The predictive response score (pRS) system was built as the product of the gene expression and coefficient obtained from logistic analysis. Last, the cohorts were randomly divided in a 7:3 ratio into training cohort and validation cohort for the introduction of robust model, and a nomogram was constructed with the independent predictors for pCR rate.Results: A total of 217 individuals from four cohort datasets (GSE32646, GSE25065, GSE25055, GSE21974) with complete clinicopathological information were included. Based on the microarray data, a six-gene panel (ATP4B, FBXO22, FCN2, RRP8, SMERK2, TET3) was identified. A robust nomogram, adopting pRS and clinical tumor size stage, was established and the performance was successively validated by calibration curves and receiver operating characteristic curves with the area under curve 0.704 and 0.756, respectively. Results of GSEA revealed that the biological processes including apoptosis, hypoxia, mTORC1 signaling and myogenesis, and oncogenic features of EGFR and RAF were in proactivity to attribute to an inferior response.Conclusions: This study provided a robust prediction model for pCR rate and revealed potential mechanisms of distinct response to NCT in TNBC, which were promising and warranted to further validate in the perspective.

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Identification and validation of a combined hypoxia and immune index for triple‐negative breast cancer

Cited by 69 publications

References 65 publications

Hypoxia-Associated Prognostic Markers and Competing Endogenous RNA Co-Expression Networks in Breast Cancer

Hypoxia-Associated Prognostic Markers and Competing Endogenous RNA Co-Expression Networks in Breast Cancer

Novel biomarkers and prediction model for the pathological complete response to neoadjuvant treatment of triple-negative breast cancer

Novel biomarkers and prediction model for the pathological complete response to neoadjuvant treatment of triple-negative breast cancer

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