scholarly journals NEFM DNA methylation correlates with immune infiltration and survival in breast cancer

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Dandan Li ◽  
Wenhao Zhao ◽  
Xinyu Zhang ◽  
Hanning Lv ◽  
Chunhong Li ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Dna Methylation ◽  
Gene Signature ◽  
Normal Breast ◽  
Macrophage Infiltration ◽  
Immune Gene ◽  
Transcriptional Expression ◽  
Immune Infiltration ◽  
Kaplan Meier ◽  
Kaplan Meier Plotter

Abstract Background This study aims to determine whether NEFM (neurofilament medium) DNA methylation correlates with immune infiltration and prognosis in breast cancer (BRCA) and to explore NEFM-connected immune gene signature. Methods NEFM transcriptional expression was analyzed in BRCA and normal breast tissues using Oncomine and Tumor Immune Estimation Resource (TIMER) databases. The relationship between NEFM DNA methylation and NEFM transcriptional expression was investigated in TCGA. Potential influence of NEFM DNA methylation/expression on clinical outcome was evaluated using TCGA BRCA, The Human Protein Atlas and Kaplan–Meier plotter databases. Association of NEFM transcriptional expression/DNA methylation with cancer immune infiltration was investigated using TIMER and TISIDB databases. Results High expression of NEFM correlated with better overall survival (OS) and recurrence-free survival (RFS) in TCGA BRCA and Kaplan–Meier plotter, whereas NEFM DNA methylation with worse OS in TCGA BRCA. NEFM transcriptional expression negatively correlated with DNA methylation. NEFM DNA methylation significantly negatively correlated with infiltrating levels of B, CD8+ T/CD4+ T cells, macrophages, neutrophils and dendritic cells in TIMER and TISIDB. NEFM expression positively correlated with macrophage infiltration in TIMER and TISIDB. After adjusted with tumor purity, NEFM expression weekly negatively correlated with infiltration level of B cells, whereas positively correlated with CD8+ T cell infiltration in TIMER gene modules. NEFM expression/DNA methylation correlated with diverse immune markers in TCGA and TISIDB. Conclusions NEFM low-expression/DNA methylation correlates with poor prognosis. NEFM expression positively correlates with macrophage infiltration. NEFM DNA methylation strongly negatively correlates with immune infiltration in BRCA. Our study highlights novel potential functions of NEFM expression/DNA methylation in regulation of tumor immune microenvironment.

scholarly journals Nomogram Models Based on Gene Expression in Prediction of Breast Cancer Bone Metastasis

2021 ◽  
Author(s):  
Teng-di Fan ◽  
Di-kai Bei ◽  
Song-wei Li
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Bone Metastasis ◽  
Gene Signature ◽  
Functional Enrichment ◽  
Training Set ◽  
Hub Genes ◽  
Kaplan Meier ◽  
Patient Prognosis ◽  
Kaplan Meier Plotter

Abstract Objective: To design a weighted co-expression network and build gene expression signature-based nomogram (GESBN) models for predicting the likelihood of bone metastasis in breast cancer (BC) patients. Methods: Dataset GSE124647 was used as a training set, and GSE14020 was taken as a validation set. In the training cohort, limma package in R was adopted to obtain differentially expressed genes (DEGs) between BC non-bone metastasis and bone metastasis patients, which were used for functional enrichment analysis. After weighted co-expression network analysis (WGCNA), univariate Cox regression and Kaplan-Meier plotter analyses were performed to screen potential prognosis-related genes. Then, GESBN models were constructed and evaluated. Further, the expression levels of genes in the models were explored in the training set, which was validated in GSE14020. Finally, the prognostic value of hub genes in BC was explored. Results: A total of 1858 DEGs were obtained. WGCNA result showed that the blue module was most significantly related to bone metastasis and prognosis. After survival analyses, GAJ1, SLC24A3, ITGBL1, and SLC44A1 were subjected to construct a GESBN model for overall survival. While GJA1, IGFBP6, MDFI, ITGFBI, ANXA2, and SLC24A3 were subjected to build a GESBN model for progression-free survival. Kaplan-Meier plotter and receiver operating characteristic analyses presented the reliable prediction ability of the models. Besides, GJA1, IGFBP6, ITGBL1, SLC44A1, and TGFBI expressions were significantly different between the two groups in GSE124647 and GSE14020. The hub genes had a significant impact on patient prognosis. Conclusion: Both the four-gene signature and six-gene signature could accurately predict patient prognosis, which may provide novel treatment insights for BC bone metastasis.

scholarly journals Upregulated CCNE1 Correlates with Poor Prognosis, Tumor Immune Infiltration and Escape in Breast Cancer

2021 ◽  
Author(s):  
Jiaxi Feng ◽  
Yanan Hu ◽  
Dan Liu ◽  
Shanshan Wang ◽  
Mengci Zhang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Immune Cells ◽  
Poor Prognosis ◽  
Immune Cell ◽  
High Expression ◽  
Expression Level ◽  
Immune Cell Infiltration ◽  
Immune Infiltration ◽  
Kaplan Meier ◽  
Kaplan Meier Plotter

Abstract Background Breast cancer (BC) is the most common malignant tumor in women and widely known for its poor prognosis. More and more research has discovered that cyclin E1 (CCNE1) plays an important role in progression of various types of cancer. But its specific mechanism in BC progression still needs further research to explore.Methods At first, we determined the expression and prognostic value of CCNE1 through The Cancer Genome Atlas (TCGA) database and The Genotype-Tissue Expression (GTEx) data. Then, we predicted the upstream non-coding RNAs of CCNE1 through StarBase, GEPIA, and Kaplan-Meier plotter database. We further studied the correlation of CCNE1 expression with BC immune cell infiltration, biomarkers of immune cells and immune checkpoints expression through TIMER and GEPIA databases.Results The results suggested that CCNE1 was significantly upregulated in BC and its high expression was correlated with poor prognosis in BC patients. Next, we identified long noncoding RNA (lncRNA) LINC00511 / microRNA-195-5p (miR-195-5p) / CCNE1 axis as the most potential pathway that could regulate CCNE1 expression in BC through StarBase, GEPIA, and Kaplan-Meier plotter database. Furthermore, our in-depth research discovered that CCNE1 expression level was significantly correlated with tumor immune cell infiltration, biomarkers of immune cells, and immune checkpoint expression in BC. conclusions In summary, high expression level of CCNE1 was significantly correlated with poor prognosis, tumor immune infiltration and escape in BC.

scholarly journals CXCL2 as a Prognostic Marker in Breast Cancer is Associated with Immune Infiltration and Regulated by miR-215

2020 ◽  
Author(s):  
Jia-Xiang An ◽  
Ying-Ying Chen ◽  
Zhao-Sheng Ma ◽  
Wen-Jie Yu ◽  
Jin-Xi Hu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Survival Time ◽  
Cancer Patients ◽  
Breast Cancer Patients ◽  
Clinical Prognosis ◽  
Immune Infiltration ◽  
Kaplan Meier ◽  
The Impact ◽  
Kaplan Meier Plotter ◽  
Low Expression

Abstract Background: CXCL2 is a part of chemokine superfamily, which encodes secretory proteins involved in immune regulation and inflammation. The correlation between CXCL2 and prognosis of different cancers, tumor infiltrating lymphocytes are not clear. Methods: We analyzed the expression of CXCL2 and its effect on clinical prognosis through Oncomine database, Tumor Immune Estimation Resource (TIMER) website, Kaplan-Meier plotter, PrognoScan database and Gene Expression Profiling Interactive Analysis (GEPIA). TIMER and GEPIA were used to analyze the correlation between CXCL2 and the gene marker of immune infiltration. StarBase was used to predict the miRNA that may regulate CXCL2. The relationship between miR-532-5p and CXCL2 was detected by qRT-PCR. Kaplan-Meier plotter was used to evaluate the impact of miR-532-5p on clinical prognosis. Results: PrognoScan, Kaplan-Meier plotter and GEPIA database analysis showed that low expression of CXCL2 was associated with poor disease-specific survival time (DSS), relapse-free survival time (RFS) and overall disease survival (OS) in breast cancer patients. In addition, low expression of CXCL2 was associated with poor OS and RFS in patients with lymph node positive breast cancer. CXCL2 expression was positively correlated with the infiltration of B cells, CD4+T and CD8+T cells, neutrophils and dendritic cells (DCs) in BRCA, mainly in Luminal breast cancer. MiR-532-5p can directly regulate CXCL2 expression. High miR-532-5p expression is significantly correlated with HER2 negative, grade 2 and 3 and poor OS in patients with HER+ER- breast cancer. Conclusion: CXCL2 is closely related to the prognosis and immune infiltration level of breast cancer patients, it can be regulated by miR-532-5p.

scholarly journals Upregulated CCNE1 Correlates with Poor Prognosis, Tumor Immune Infiltration and Escape in Breast Cancer

2021 ◽  
Author(s):  
Jiaxi Feng ◽  
Yanan Hu ◽  
Dan Liu ◽  
Shanshan Wang ◽  
Mengci Zhang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Immune Cells ◽  
Poor Prognosis ◽  
Immune Cell ◽  
High Expression ◽  
Expression Level ◽  
Immune Cell Infiltration ◽  
Immune Infiltration ◽  
Kaplan Meier ◽  
Kaplan Meier Plotter

Abstract BackgroundBreast cancer (BC) is the most common malignant tumor in women and widely known for its poor prognosis. More and more research has discovered that cyclin E1 (CCNE1) plays an important role in progression of various types of cancer. But its specific mechanism in BC progression still needs further research to explore.MethodsAt first, we determined the expression and prognostic value of CCNE1 through The Cancer Genome Atlas (TCGA) database and The Genotype-Tissue Expression (GTEx) data. Then, we predicted the upstream non-coding RNAs of CCNE1 through StarBase, GEPIA, and Kaplan-Meier plotter database. We further studied the correlation of CCNE1 expression with BC immune cell infiltration, biomarkers of immune cells and immune checkpoints expression through TIMER and GEPIA databases.ResultsThe results suggested that CCNE1 was significantly upregulated in BC and its high expression was correlated with poor prognosis in BC patients. Next, we identified long noncoding RNA (lncRNA) LINC00511 / microRNA-195-5p (miR-195-5p) / CCNE1 axis as the most potential pathway that could regulate CCNE1 expression in BC through StarBase, GEPIA, and Kaplan-Meier plotter database. Furthermore, our in-depth research discovered that CCNE1 expression level was significantly correlated with tumor immune cell infiltration, biomarkers of immune cells, and immune checkpoint expression in BC.ConclusionIn summary, high expression level of CCNE1 was significantly correlated with poor prognosis, tumor immune infiltration and escape in BC.

scholarly journals Bioinformatic analysis of the expression and prognostic value of chromobox family proteins in human breast cancer

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Xiaomin Li ◽  
Junhe Gou ◽  
Hongjiang Li ◽  
Xiaoqin Yang
Keyword(s):  
Breast Cancer ◽  
Cancer Progression ◽  
Prognostic Index ◽  
Bioinformatic Analysis ◽  
Tumor Stage ◽  
Normal Breast ◽  
Nottingham Prognostic Index ◽  
Breast Cancer Patients ◽  
Kaplan Meier ◽  
Kaplan Meier Plotter

Abstract Chromobox (CBX) family proteins control chromatin structure and gene expression. However, the functions of CBXs in cancer progression, especially breast cancer, are inadequately studied. We assessed the significance of eight CBX proteins in breast cancer. We performed immunohistochemistry and bioinformatic analysis of data from Oncomine, GEPIA Dataset, bcGenExMiner, Kaplan–Meier Plotter, and cBioPortal. We compared mRNA and protein expression levels of eight CBX proteins between breast tumor and normal tissue. The expression difference of CBX7 was the greatest, and CBX7 was downregulated in breast cancer tissues compared with normal breast tissues. The expression of CBX2 was strongly associated with tumor stage. We further analyzed the association between the eight CBX proteins and the following clinicopathological features: menopause age, estrogen receptor (ER), progesterone receptor (PR) and HER-2 receptor status, nodal status, P53 status, triple-negative status, and the Scarff–Bloom–Richardson grade (SBR) and Nottingham prognostic index (NPI). Survival analysis in the Kaplan–Meier Plotter database showed that the eight CBX proteins were significantly associated with prognosis. Moreover, CBX genes in breast cancer patients had a high net alteration frequency of 57%. There were significant co-expression correlations between the following CBX protein pairs: CBX4 positively with CBX8, CBX6 positively with CBX7, and CBX2 negatively with CBX7. We also analyzed the Gene Ontology enrichment of the CBX proteins, including biological processes, cellular components, and molecular functions. CBX 1/2/3/5/8 may be oncogenes for breast cancer, whereas CBX 6 and 7 may be tumor suppressors for breast cancer. All eight CBX proteins may be predictive for prognosis. Clinical trials are needed to confirm the significance of the eight CBX proteins in breast cancer.

scholarly journals Accelerated aging in normal breast tissue of women with breast cancer

2021 ◽  
Vol 23 (1) ◽  
Author(s):  
Shoghag Panjarian ◽  
Jozef Madzo ◽  
Kelsey Keith ◽  
Carolyn M. Slater ◽  
Carmen Sapienza ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Dna Methylation ◽  
Anomaly Detection ◽  
Breast Tissue ◽  
Preventive Intervention ◽  
Normal Breast Tissue ◽  
Accelerated Aging ◽  
Normal Breast ◽  
Age Related ◽  
Unsupervised Anomaly Detection

Abstract Background DNA methylation alterations have similar patterns in normal aging tissue and in cancer. In this study, we investigated breast tissue-specific age-related DNA methylation alterations and used those methylation sites to identify individuals with outlier phenotypes. Outlier phenotype is identified by unsupervised anomaly detection algorithms and is defined by individuals who have normal tissue age-dependent DNA methylation levels that vary dramatically from the population mean. Methods We generated whole-genome DNA methylation profiles (GSE160233) on purified epithelial cells and used publicly available Infinium HumanMethylation 450K array datasets (TCGA, GSE88883, GSE69914, GSE101961, and GSE74214) for discovery and validation. Results We found that hypermethylation in normal breast tissue is the best predictor of hypermethylation in cancer. Using unsupervised anomaly detection approaches, we found that about 10% of the individuals (39/427) were outliers for DNA methylation from 6 DNA methylation datasets. We also found that there were significantly more outlier samples in normal-adjacent to cancer (24/139, 17.3%) than in normal samples (15/228, 5.2%). Additionally, we found significant differences between the predicted ages based on DNA methylation and the chronological ages among outliers and not-outliers. Additionally, we found that accelerated outliers (older predicted age) were more frequent in normal-adjacent to cancer (14/17, 82%) compared to normal samples from individuals without cancer (3/17, 18%). Furthermore, in matched samples, we found that the epigenome of the outliers in the pre-malignant tissue was as severely altered as in cancer. Conclusions A subset of patients with breast cancer has severely altered epigenomes which are characterized by accelerated aging in their normal-appearing tissue. In the future, these DNA methylation sites should be studied further such as in cell-free DNA to determine their potential use as biomarkers for early detection of malignant transformation and preventive intervention in breast cancer.

scholarly journals Identification of Flap Endonuclease 1 With Diagnostic and Prognostic Value in Breast Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Min Wu ◽  
Pan Zhang ◽  
Penghui Wang ◽  
Zhen Fang ◽  
Yaqin Zhu
Keyword(s):  
Breast Cancer ◽  
Prognostic Marker ◽  
Prognostic Value ◽  
Diagnostic Value ◽  
Roc Curve Analysis ◽  
Free Survival ◽  
Flap Endonuclease 1 ◽  
Normal Tissues ◽  
Kaplan Meier ◽  
Kaplan Meier Plotter

ObjectiveThis study aims to identify the potential value of flap endonuclease 1 (FEN1) as a diagnostic and prognostic marker for breast cancer (BC).MethodsELISA was used to measure serum FEN1 levels and ECLIA for CA153 and CEA levels. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic value. Oncomine and UALCAN databases were used to analyze the differences in FEN1 mRNA and protein expressions. Kaplan-Meier Plotter database was then used to assess the prognostic value.ResultsBioinformatics analysis showed that the FEN1 mRNA and protein levels were significantly higher in BC tissues than in normal tissues. FEN1 was detected in culture medium of BC cell lines and serum FEN1 concentrations were significantly increased in BC patients than in cancer-free individuals. Besides, FEN1 exhibited higher diagnostic accuracy (AUC values>0.800) than CA153 and CEA for distinguishing BC patients, especially early BC, from the healthy and benign groups, or individually. Additionally, serum FEN1 levels were significantly associated with the stage (P=0.001) and lymph invasion (P=0.016), and serum FEN1 levels were increased with the development of BC. Furthermore, serum FEN1 levels were significantly decreased in post-operative patients than in pre-operative patients (P=0.016). Based on the Kaplan-Meier Plotter database, the survival analysis indicated that FEN1 overexpression was associated with poor prognoses for overall survival (OS), relapse-free survival (RFS), and distant metastasis-free survival (DMFS) in BC patients.ConclusionFEN1 might be a novel diagnostic and prognostic marker for BC.

scholarly journals The Alterations and Potential Roles of MCMs in Breast Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Xinyu Liu ◽  
Ying Liu ◽  
Qiangshan Wang ◽  
Siqi Song ◽  
Lingjun Feng ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Network ◽  
Relapse Free Survival ◽  
Minichromosome Maintenance ◽  
Free Survival ◽  
Oncomine Database ◽  
Kaplan Meier ◽  
Eukaryotic Dna ◽  
Coexpressed Genes ◽  
Kaplan Meier Plotter

The minichromosome maintenance (MCM) protein family plays a key role in eukaryotic DNA replication and has been confirmed to be associated with the occurrence and progression of many tumors. However, the expression levels, functions, and prognostic values of MCMs in breast cancer (BC) have not been clearly and systematically explained. In this article, we studied the transcriptional levels of MCMs in BC based on the Oncomine database. Kaplan-Meier plotter was used to analyze prognostic value of MCMs in human BC patients. Furthermore, we constructed a MCM coexpression gene network and performed functional annotation analysis through DAVID to reveal the functions of MCMs and coexpressed genes. The data showed that the expression of MCM2–8 and MCM10 but not MCM1 and MCM9 was upregulated in BC. Kaplan-Meier plotter analysis revealed that high transcriptional levels of MCM2, MCM4–7, and MCM10 were significantly related to low relapse-free survival (RFS) in BC patients. In contrast, high levels of MCM1 and MCM9 predicted high RFS for BC patients. This study suggests that MCM2, MCM4–7, and MCM10 possess great potential to be valuable prognostic biomarkers for BC and that MCM1 and MCM9 may serve as potential treatment targets for BC patients.

scholarly journals APOC1 is a Potential Prognostic Biomarker and Correlated With Immune Infiltration in ESCC

2020 ◽  
Author(s):  
Jia-yi XIE ◽  
Ming Liu ◽  
Yaxin Luo ◽  
Zhen Wang ◽  
Zhenghong Lu ◽  
...  
Keyword(s):  
T Cells ◽  
Transcription Factors ◽  
Cd8 T Cells ◽  
Immune Cells ◽  
Poor Prognosis ◽  
Killer Cell ◽  
Gene Set Enrichment Analysis ◽  
Immune Infiltration ◽  
Kaplan Meier ◽  
Kaplan Meier Plotter

Abstract PurposeEsophageal cancer (EC) is the sixth leading cause of cancer death worldwide. Esophageal squamous cell carcinoma (ESCC) is a predominant subtype of EC. Identifying diagnostic biomarkers for ESCC is necessary for cancer practice. Increasing evidence illustrates that apolipoprotein C-1 (APOC1) participates in the carcinogenesis. However, the biological function of APOC1 in ESCC remains unclear. Patients and methodsWe investigated the expression level of APOC1 using TIMER2.0 and GEO databases, the prognostic value of APOC1 in ESCC using Kaplan-Meier plotter and TCGA databases. We used LinkedOmics to identify co-expressed genes with APOC1 and perform GO and KEGG pathway analysis. The target networks of kinases, miRNAs and transcription factors were predicted by gene set enrichment analysis (GSEA). The correlations between APOC1 and immune infiltration were calculated using TIMER2.0 and CIBERSORT databases. We further performed the prognostic analysis based on APOC1 expression levels in related immune cells subgroups via Kaplan-Meier plotter database. ResultsAPOC1 was found overexpressed in tumor tissues in multiple ESCC cohorts and high APOC1 expression was related to a dismal prognosis. Multivariate analysis confirmed that APOC1 overexpression was an independent indicator of poor OS. Functional network analysis indicated that APOC1 might regulate the natural killer cell mediated cytotoxicity, phagosome, AMPK and hippo signaling through pathways involving some cancer-related kinases, miRNA and transcription factors. Immune infiltration analysis showed that APOC1 was significantly positively correlated with M0 macrophages cells, M1 macrophages cells and activated NK cells, negatively correlated with regulatory T cells, CD8 T cells, neutrophils and monocytes. High APOC1 expression had a poor prognosis in server immune cells subgroups in ESCC, including decreased CD8+ T cells subgroups. ConclusionThese findings suggest that increased expression of APOC1 is related to poor prognosis and immune infiltration in ESCC. APOC1 holds promise for serving as a valuable diagnostic and prognostic marker in ESCC.

Gasdermin D as a potential prognosis and treatment response prediction biomarker for invasive breast cancer.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e12548-e12548
Author(s):  
Xianghou Xia ◽  
Wenjuan Yin ◽  
Jiefei Mao ◽  
Jiejie Hu ◽  
Dehong Zou ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Invasive Breast Cancer ◽  
Response Prediction ◽  
Chemotherapy Response ◽  
Breast Cancer Patients ◽  
Free Survival ◽  
Kaplan Meier ◽  
Kaplan Meier Plotter ◽  
Treatment Response Prediction

e12548 Background: Pyroptosis is a type of inflammatory cell death mediated by gasdermins. Pyroptosis is critical for macrophage against pathogen infection. Recently growing evidences show that pyroptosis may affect development and progression of many cancers. We aim to explore the expression and related function of pyroptosis executioner Gasdermin D (GSDMD) in breast cancer. Methods: We investigated the expression level of GSDMD using TNM plotter and Breast Cancer landscape proteome with TCGA, GTEx and TARGET databases, and the prognostic value of GSDMD in invasive breast cancer using Kaplan-Meier plotter with TCGA, GEO and EGA databases. The treatment response prediction values of GSDMD in invasive breast were calculated using ROC-plotter with GEO database. Further validation of the prognostic value and chemotherapy response prediction value of GSDMD were carried out with immunohistochemical staining on tissues from 165 cases of breast cancer patients receiving neoadjuvant chemotherapy in our cancer center. Results: TNM plotter and breast cancer landscape proteome portal analysis shows that overall expression level of GSDMD in invasive breast cancer tissue is 1.67 folds higher than it is in breast normal tissues ( p=1.05*e-06). Expression of GSDMD in LuminalB subtype (p=0.019) and Her2 subtype(p=0.04) is significantly higher than it is in TNBC subtype. Calculations with Kaplan-Meier plotter show expression of GSDMD is negatively correlated with overall survival(OS), HR=0.61(0.4−0.95) p=0.027 and relapse free survival (RFS), HR =0.65(0.58−0.63), p=8.7*e-14 and distant metastasis free survival (DMFS) HR =0.75(0.61−0.91), p=0.0038 in breast cancer patients. ROC-plotter calculations show high GSDMD expression is a powerful endocrine therapy (AUC=0.731 p=6*e-09 ) and chemotherapy response (AUC=0.64 p=8*e-05 ) predictor based on 5-year RFS in overall breast cancer patients. Our IHC staining analysis shows consistent prognostic and chemotherapy prediction value of GSDMD expression in TNBC patients. Conclusions: In conclusion, our findings suggest that high expression of GSDMD is positively correlated with prognosis and therapeutic response in breast cancer. GSDMD is a promising prognostic marker and therapeutic response predictor in invasive breast cancer.

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