Dataset Information

Accelerated glycolysis in tumor microenvironment is associated with worse survival in triple-negative but not consistently with ER+/HER2- breast cancer.

ABSTRACT: Metabolic reprogramming to sustain immortality is a hallmark of cancer and glycolysis is an important way to attain this. Thus, we investigate the association of glycolysis and associated pathways in the survival of breast cancer. A total of 5,176 breast cancer patients from multiple independent cohorts were analyzed. We determined the glycolytic signaling score by the degree of enrichment by Gene Set Variant Analysis and the median was used to divide each cohort into high vs low score groups. Glycolysis high breast cancer significantly enriched the hallmark cell proliferation-related gene sets (E2F targets, G2M checkpoint, and MYC targets v1 and v2) and was associated with high MKI67 expression. In all cohorts, triple-negative breast cancer (TNBC) was associated with the highest glycolysis score. It was found that in TNBC, glycolysis high breast cancer was associated with worse survival but in ER-positive/HER2-negative breast cancer this was not observed consistently. The glycolysis high TNBC enriched multiple pro-cancerous gene sets and was infiltrated with a low level of B-cells and anti-cancerous immune cells, and significantly associated with a decreased level of cytolytic activity. It was also observed that the glycolysis was higher in the metastatic sites than in the primary breast cancer and the survival was not affected by the metastatic sites. In conclusion, accelerated glycolysis is associated with cancer cell proliferation and worse survival in TNBC.

SUBMITTER: Oshi M

PROVIDER: S-EPMC10408485 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Accelerated glycolysis in tumor microenvironment is associated with worse survival in triple-negative but not consistently with ER+/HER2- breast cancer.

Oshi Masanori M Roy Arya Mariam AM Yan Li L Sasamoto Mahato M Tokumaru Yoshihisa Y Wu Rongrong R Yamada Akimitsu A Yamamoto Shinya S Chishima Takashi T Narui Kazutaka K Endo Itaru I Takabe Kazuaki K

American journal of cancer research 20230715 7

Metabolic reprogramming to sustain immortality is a hallmark of cancer and glycolysis is an important way to attain this. Thus, we investigate the association of glycolysis and associated pathways in the survival of breast cancer. A total of 5,176 breast cancer patients from multiple independent cohorts were analyzed. We determined the glycolytic signaling score by the degree of enrichment by Gene Set Variant Analysis and the median was used to divide each cohort into high vs low score groups. G ...[more]

PMID: 37559984

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Project description:IntroductionBreast cancer (BC) presents diverse malignancies with varying biological and clinical behaviors, driven by an interplay between cancer cells and tumor microenvironment. Deciphering these interactions is crucial for personalized diagnostics and treatment. This study explores the prognostic impact of tumor proliferation and immune response patterns, assessed by computational pathology indicators, on breast cancer-specific survival (BCSS) models in estrogen receptor-positive HER2-negative (ER+HER2-) and triple-negative BC (TNBC) patients.Materials and methodsWhole-slide images of tumor surgical excision samples from 252 ER+HER2- patients and 63 TNBC patients stained for estrogen and progesterone receptors, Ki67, HER2, and CD8 were analyzed. Digital image analysis (DIA) was performed for tumor tissue segmentation and quantification of immunohistochemistry (IHC) markers; the DIA outputs were subsampled by hexagonal grids to assess the spatial distributions of Ki67-positive tumor cells and CD8-positive (CD8+) cell infiltrates, expressed as Ki67-entropy and CD8-immunogradient indicators, respectively. Prognostic models for BCSS were generated using multivariable Cox regression analysis, integrating clinicopathological and computational IHC indicators.ResultsIn the ER+HER2- BC, multivariable Cox regression revealed that high CD8+ density within the tumor interface zone (IZ) (HR: 0.26, p = 0.0056), low immunodrop indicator of CD8+ density (HR: 2.93, p = 0.0051), and low Ki67-entropy (HR: 5.95, p = 0.0.0061) were independent predictors of better BCSS, while lymph node involvement predicted worse BCSS (HR: 3.30, p = 0.0013). In TNBC, increased CD8+ density in the IZ stroma (HR: 0.19, p = 0.0119) and Ki67-entropy (HR: 3.31, p = 0.0250) were independent predictors of worse BCSS. Combining these independent indicators enhanced prognostic stratification in both BC subtypes.ConclusionsComputational biomarkers, representing spatial properties of the tumor proliferation and immune cell infiltrates, provided independent prognostic information beyond conventional IHC markers in BC. Integrating Ki67-entropy and CD8-immunogradient indicators into prognostic models can improve patient stratification with regard to BCSS.

Project description:BackgroundTreatment strategies for various subtypes of breast cancer (BC) are different based on their distinct molecular characteristics. Therefore, it is very important to identify key differentially expressed genes (DEGs) between ER-positive/HER2-negative BC and ER-negative/HER2-negative BC.MethodsGene expression profiles of GSE22093 and GSE23988 were obtained from the Gene Expression Omnibus database. There were 74 ER-positive/HER2-negative BC tissues and 85 ER-negative/HER2-negative BC tissues in the two profile datasets. DEGs between ER-positive/HER2-negative tissues and ER-negative/HER2-negative BC tissues were identified by the GEO2R tool. The common DEGs among the two datasets were detected with Venn software online. Next, we made use of the Database for Annotation, Visualization and Integrated Discovery to analyze enriched Kyoto Encyclopedia of Gene and Genome (KEGG) pathways and gene ontology terms. Then, the protein-protein interactions (PPIs) of these DEGs were visualized by Cytoscape with the Search Tool for the Retrieval of Interacting Genes. Of the proteins in the PPI network, Molecular Complex Detection plug-in analysis identified nine core upregulated genes and one core downregulated gene. UALCAN and Gene Expression Profiling Interactive Analysis were applied to determine the expression of these 10 genes in BC. Furthermore, for the analysis of overall survival among those genes, the Kaplan-Meier method was implemented.ResultsNinety-three common DEGs (63 upregulated and 30 downregulated) were identified. KEGG pathway enrichment analysis showed that upregulated DEGs were particularly enriched in the progesterone-mediated oocyte maturation pathway. In addition, PGR might be a prognostic biomarker for ER-positive/HER2-negative BC. CCND1 is a poor prognostic biomarker for ER-positive/HER2-negative BC and ER-negative/HER2-negative BC. Moreover, TFF1, AGR2 and EGFR might be predictive biomarkers of node metastasis in ER-positive/HER2-negative BC and ER-negative/HER2-negative BC.ConclusionsCCND1, AGR2, PGR, TFF1 and EGFR are the key DEGs between ER-positive/HER2-negative BC and ER-negative/HER2-negative BC. Further studies are required to confirm the functions of the identified genes.

Project description:PurposeTriple-negative breast cancer (TNBC) is an aggressive type of breast cancer. Currently, no effective treatment options for this condition exist. Nuclear factor erythroid 2-related factor 2 (NRF2), encoded by nuclear factor erythroid-derived 2-like 2 (NFE2L2) gene and its endogenous inhibitor, Kelch-like ECH-associated protein 1 (KEAP1), both participate in cellular defense mechanisms against oxidative stress and contribute to chemoresistance and tumor progression in numerous types of cancers. This study aimed to evaluate the expression patterns of NRF2 and KEAP1 and their prognostic value in operable TNBC.MethodsTissue microarrays were prepared using tumor tissues collected from 203 patients with TNBC who underwent surgery. Immunohistochemical staining analyses of NRF2 and KEAP1 were performed. The expression of each immunomarker was categorized into two groups (low or high) based on the median H-score. We analyzed the association between the expression of each immunomarker and clinicopathological information to predict survival. A total of 225 TNBC samples from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset were used to validate our results.ResultsNRF2 immunoreactivity was detected in the nucleus and was associated with histologic grade and Ki-67 index, whereas KEAP1 immunoreactivity was detected in the cytoplasm and was associated with the Ki-67 index. Survival analyses showed that NRF2 and KEAP1 expressions were independent prognostic factors for overall survival (OS) (hazard ratio [HR], 2.45 and 0.30; p = 0.015 and 0.016, respectively) and disease-free survival (HR, 2.27 and 0.42; p = 0.019 and 0.022, respectively). NFE2L2 mRNA expression was an independent prognostic factor for OS (HR, 0.59; p = 0.009) in the METABRIC dataset.ConclusionHigh NRF2 and low KEAP1 expressions independently predicted poor survival in patients with operable TNBC. Further investigations are warranted to examine the possible therapeutic benefits of targeting the KEAP1-NRF2 pathway for TNBC treatment.

Dataset Information

Accelerated glycolysis in tumor microenvironment is associated with worse survival in triple-negative but not consistently with ER+/HER2- breast cancer.

Publications

Accelerated glycolysis in tumor microenvironment is associated with worse survival in triple-negative but not consistently with ER+/HER2- breast cancer.

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