Analysis of the Prognosis Related Genes in HER2+ Breast Cancer Based on Weighted Gene Co-expression Network Analysis

Abstract Background: Breast cancer is one of the malignant tumors that threaten women's health, with HER2+ breast cancer being more aggressive. In this study, bioinformatics methods were used to find potential key genes in HER2 + for diagnosis and treatment.Methods: Datasets of HER2+ breast cancer and normal tissue samples retrieved from TCGA databases were subjected to DEGs analysis using R software. Then WGCNA is constructed for DEGs. The key gene co-expression modules were then subjected to GO and KEGG pathway enrichment analyses, as well as construction of PPI networks using the STRING database for identifying key genes. Finally, key genes were further validated by survival analysis, protein expression, and COX regression models.Results: We identified 2063 DEGs and 4 gene co-expression modules. Functional enrichment analysis showed that these key co-expression modules were mainly associated with extracellular matrix organization, extracellular matrix structural constituent and neuroactive ligand−receptor interaction. PPI network visualization identified 100 key genes, 3 of which were not present in the other subtypes of breast cancer. UTS2 DRD4 and GLP1R are key genes specific to the HER2+ subtype. Survival analysis showed that UTS2 are prognosis-related key genes in HER2+ breast cancer. Finally, UTS2 combined with clinical data to construct Cox regression model.Conclusions: Combined with the two screening methods, 3 key genes closely related to HER2 + breast cancer were identified. UTS2 is a new potential key gene and may become a new therapeutic target for HER2 + breast cancer.

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Integrative analyses of biomarkers and pathways for heart failure

10.21203/rs.3.rs-1031511/v1 ◽

2021 ◽

Author(s):

Shaowei Fan ◽

Yuanhui Hu

Keyword(s):

Heart Failure ◽

Extracellular Matrix ◽

Microarray Data ◽

Enrichment Analysis ◽

Signal Pathway ◽

Gene Set Enrichment Analysis ◽

Functional Enrichment ◽

Pathway Enrichment Analysis ◽

Ppi Networks ◽

Key Genes

Abstract Background: Heart failure (HF) is the most common potential cause of death, causing a huge health and economic burden all over the world. So far, some impressive progress has been made in the study of pathogenesis. However, the underlying molecular mechanisms leading to this disease remain to be fully elucidated. Methods: The microarray data sets of GSE76701, GSE21610 and GSE8331 were retrieved from the gene expression comprehensive database (GEO). After merging all microarray data and adjusting batch effects, differentially expressed genes (DEG) were determined. Functional enrichment analysis was performed based on Gene Ontology (GO) resources, Kyoto Encyclopedia of Genes and Genomes (KEGG) resources, gene set enrichment analysis (GSEA), response pathway database and Disease Ontology (DO). Protein protein interaction (PPI) network was constructed using string database. Combined with the above important bioinformatics information, the potential key genes were selected. The comparative toxicological genomics database (CTD) is used to explore the interaction between potential key genes and HF. Results: We identified 38 patients with heart failure and 16 normal controls. There were 315 DEGs among HF samples, including 278 up-regulated genes and 37 down-regulated genes. Pathway enrichment analysis showed that most DEGs were significantly enriched in BMP signal pathway, transmembrane receptor protein serine / threonine kinase signal pathway, extracellular matrix, basement membrane, glycosaminoglycan binding, sulfur compound binding and so on. Similarly, GSEA enrichment analysis showed that DEGs were mainly enriched in extracellular matrix and extracellular matrix related proteins. BBS9, CHRD, BMP4, MYH6, NPPA and CCL5 are central genes in PPI networks and modules. Conclusions: the enrichment pathway of DEGs and go ontology may reveal the molecular mechanism of HF. Among them, target genes EIF1AY, RPS4Y1, USP9Y, KDM5D, DDX3Y, NPPA, HBB, TSIX, LOC28556 and XIST are expected to become new targets for heart failure. Our findings provide potential biomarkers or therapeutic targets for the further study of heart failure and contribute to the development of advanced prediction, diagnosis and treatment strategies.

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Highly heterogeneous-related genes of triple-negative breast cancer: potential diagnostic and prognostic biomarkers

BMC Cancer ◽

10.1186/s12885-021-08318-1 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Yiduo Liu ◽

Linxin Teng ◽

Shiyi Fu ◽

Guiyang Wang ◽

Zhengjun Li ◽

...

Keyword(s):

Breast Cancer ◽

Survival Analysis ◽

Triple Negative Breast Cancer ◽

Regression Models ◽

Triple Negative ◽

Cox Regression ◽

Enrichment Analysis ◽

Functional Enrichment ◽

Free Interval ◽

Potential Biomarkers

Abstract Background Triple-negative breast cancer (TNBC) is a highly heterogeneous subtype of breast cancer, showing aggressive clinical behaviors and poor outcomes. It urgently needs new therapeutic strategies to improve the prognosis of TNBC. Bioinformatics analyses have been widely used to identify potential biomarkers for facilitating TNBC diagnosis and management. Methods We identified potential biomarkers and analyzed their diagnostic and prognostic values using bioinformatics approaches. Including differential expression gene (DEG) analysis, Receiver Operating Characteristic (ROC) curve analysis, functional enrichment analysis, Protein-Protein Interaction (PPI) network construction, survival analysis, multivariate Cox regression analysis, and Non-negative Matrix Factorization (NMF). Results A total of 105 DEGs were identified between TNBC and other breast cancer subtypes, which were regarded as heterogeneous-related genes. Subsequently, the KEGG enrichment analysis showed that these genes were significantly enriched in ‘cell cycle’ and ‘oocyte meiosis’ related pathways. Four (FAM83B, KITLG, CFD and RBM24) of 105 genes were identified as prognostic signatures in the disease-free interval (DFI) of TNBC patients, as for progression-free interval (PFI), five genes (FAM83B, EXO1, S100B, TYMS and CFD) were obtained. Time-dependent ROC analysis indicated that the multivariate Cox regression models, which were constructed based on these genes, had great predictive performances. Finally, the survival analysis of TNBC subtypes (mesenchymal stem-like [MSL] and mesenchymal [MES]) suggested that FAM83B significantly affected the prognosis of patients. Conclusions The multivariate Cox regression models constructed from four heterogeneous-related genes (FAM83B, KITLG, RBM24 and S100B) showed great prediction performance for TNBC patients’ prognostic. Moreover, FAM83B was an important prognostic feature in several TNBC subtypes (MSL and MES). Our findings provided new biomarkers to facilitate the targeted therapies of TNBC and TNBC subtypes.

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Key Genes and Prognostic Analysis in HER2+ Breast Cancer

Technology in Cancer Research & Treatment ◽

10.1177/1533033820983298 ◽

2021 ◽

Vol 20 ◽

pp. 153303382098329

Author(s):

Yujie Weng ◽

Wei Liang ◽

Yucheng Ji ◽

Zhongxian Li ◽

Rong Jia ◽

...

Keyword(s):

Breast Cancer ◽

Gene Expression ◽

Differentially Expressed Genes ◽

Protein Interaction ◽

Differentially Expressed ◽

Protein Kinase Activity ◽

Protein Protein Interaction ◽

Risk Of Death ◽

Her2 Breast Cancer ◽

Key Genes

Human epidermal growth factor 2 (HER2)+ breast cancer is considered the most dangerous type of breast cancers. Herein, we used bioinformatics methods to identify potential key genes in HER2+ breast cancer to enable its diagnosis, treatment, and prognosis prediction. Datasets of HER2+ breast cancer and normal tissue samples retrieved from Gene Expression Omnibus and The Cancer Genome Atlas databases were subjected to analysis for differentially expressed genes using R software. The identified differentially expressed genes were subjected to gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses followed by construction of protein-protein interaction networks using the STRING database to identify key genes. The genes were further validated via survival and differential gene expression analyses. We identified 97 upregulated and 106 downregulated genes that were primarily associated with processes such as mitosis, protein kinase activity, cell cycle, and the p53 signaling pathway. Visualization of the protein-protein interaction network identified 10 key genes ( CCNA2, CDK1, CDC20, CCNB1, DLGAP5, AURKA, BUB1B, RRM2, TPX2, and MAD2L1), all of which were upregulated. Survival analysis using PROGgeneV2 showed that CDC20, CCNA2, DLGAP5, RRM2, and TPX2 are prognosis-related key genes in HER2+ breast cancer. A nomogram showed that high expression of RRM2, DLGAP5, and TPX2 was positively associated with the risk of death. TPX2, which has not previously been reported in HER2+ breast cancer, was associated with breast cancer development, progression, and prognosis and is therefore a potential key gene. It is hoped that this study can provide a new method for the diagnosis and treatment of HER2 + breast cancer.

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Prediction of Prognostic Biomarkers and Construction of an Autophagy Prognostic Model for Colorectal Cancer Using Bioinformatics

Technology in Cancer Research & Treatment ◽

10.1177/1533033820984177 ◽

2020 ◽

Vol 19 ◽

pp. 153303382098417

Author(s):

Ting-ting Liu ◽

Shu-min Liu

Keyword(s):

Colorectal Cancer ◽

Regression Analysis ◽

Prognostic Model ◽

Cox Regression ◽

Small Gtpase ◽

Functional Enrichment ◽

Clinical Correlation ◽

Cox Regression Analysis ◽

Prognostic Analysis ◽

Key Genes

Objective: The incidence of colorectal cancer is increasing every year, and autophagy may be related closely to the pathogenesis of colorectal cancer. Autophagy is a natural catabolic mechanism that allows the degradation of cellular components in eukaryotic cells. However, autophagy plays a dual role in tumorigenesis. It not only promotes normal cell survival and tumor growth but also induces cell death and suppresses tumors survival. In addition, the pathogenesis of various conditions, including inflammation, neurodegenerative diseases, or tumors, is associated with abnormal autophagy. The present work aimed to examine the significance of autophagy-related genes (ARGs) in prognosis prediction, to construct an autophagy prognostic model, and to identify independent prognostic factors for colorectal cancer (CRC). Methods: This study discovered a total of 36 ARGs in CRC cases using The Cancer Genome Atlas (TCGA) and Human Autophagy-dedicated (HADd) databases along with functional enrichment analysis. Then, an autophagy prognostic model was constructed using univariate Cox regression analysis, and the key prognostic genes were screened. Finally, independent prognostic markers were determined through independent prognostic analysis and clinical correlation analysis of key genes. Results: Of the 36 differentially expressed ARGs, 13 were related to prognosis, as determined by univariate Cox regression analysis. A total of 6 key genes were obtained by a multivariate Cox regression analysis. Independent prognostic values were shown by 3 genes, namely, microtubule-associated protein 1 light chain 3 (MAP1LC3C), small GTPase superfamily and Rab family (RAB7A), and WD-repeat domain phosphoinositide-interacting protein 2 (WIPI2) by independent prognostic analysis and clinical correlation. Conclusions: In this study, molecular bioinformatics technology was employed to determine and construct a prognostic model of autophagy for colon cancer patients, which revealed 3 autophagy-related features, namely, MAP1LC3C, WIPI2, and RAB7A.

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Identification of a prognostic long non-coding RNA signature in breast cancer

10.21203/rs.3.rs-27286/v1 ◽

2020 ◽

Author(s):

Gaochen Lan ◽

Xiaoling Yu ◽

Yanna Zhao ◽

Jinjian Lan ◽

Wan Li ◽

...

Keyword(s):

Breast Cancer ◽

Cox Regression ◽

Prognostic Biomarker ◽

Expression Profiles ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Differentially Expressed ◽

Cox Regression Analysis

Abstract Background: Breast cancer is the most common malignant disease among women. At present, more and more attention has been paid to long non-coding RNAs (lncRNAs) in the field of breast cancer research. We aimed to investigate the expression profiles of lncRNAs and construct a prognostic lncRNA for predicting the overall survival (OS) of breast cancer.Methods: The expression profiles of lncRNAs and clinical data with breast cancer were obtained from The Cancer Genome Atlas (TCGA). Differentially expressed lncRNAs were screened out by R package (limma). The survival probability was estimated by the Kaplan‑Meier Test. The Cox Regression Model was performed for univariate and multivariate analysis. The risk score (RS) was established on the basis of the lncRNAs’ expression level (exp) multiplied regression coefficient (β) from the multivariate cox regression analysis with the following formula: RS=exp a1 * β a1 + exp a2 * β a2 +……+ exp an * β an. Functional enrichment analysis was performed by Metascape.Results: A total of 3404 differentially expressed lncRNAs were identified. Among them, CYTOR, MIR4458HG and MAPT-AS1 were significantly associated with the survival of breast cancer. Finally, The RS could predict OS of breast cancer (RS=exp CYTOR * β CYTOR + exp MIR4458HG * β MIR4458HG + exp MAPT-AS1 * β MAPT-AS1). Moreover, it was confirmed that the three-lncRNA signature could be an independent prognostic biomarker for breast cancer (HR=3.040, P=0.000).Conclusions: This study established a three-lncRNA signature, which might be a novel prognostic biomarker for breast cancer.

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Identification of Hypoxia-Related Differentially Expressed Genes and Construction of the Clinical Prognostic Predictor in Hepatocellular Carcinoma by Bioinformatic Analysis

BioMed Research International ◽

10.1155/2021/7928051 ◽

2021 ◽

Vol 2021 ◽

pp. 1-15

Author(s):

Hao Guo ◽

Jing Zhou ◽

Yanjun Zhang ◽

Zhi Wang ◽

Likun Liu ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Regression Model ◽

Molecular Mechanisms ◽

Cox Regression ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Differentially Expressed ◽

Clinical Prognosis ◽

Prognostic Predictor ◽

Key Genes

Background. Hypoxia closely relates to malignant progression and appears to be prognostic for outcome in hepatocellular carcinoma (HCC). Our research is aimed at mining the hypoxic-related genes (HRGs) and constructing a prognostic predictor (PP) model on clinical prognosis in HCC patients. Methods. RNA-sequencing data about HRGs and clinical data of patients with HCC were obtained from The Cancer Genome Atlas (TCGA) database portal. Differentially expressed HRGs between HCC and para-carcinoma tissue samples were obtained by applying the Wilcox analysis in R statistical software. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were used for gene functional enrichment analyses. Then, the patients who were asked to follow up for at least one month were enrolled in the following study. Cox proportional risk regression model was applied to obtain key HRGs which related to overall survival (OS) in HCC. PP was constructed and defined, and the accuracy of PP was validated by constructing the signature in a training set and validation set. Connectivity map (CMap) was used to find potential drugs, and gene set cancer analysis (GSCA) was also performed to explore the underlying molecular mechanisms. Results. Thirty-seven differentially expressed HRGs were obtained. It contained 28 upregulated and 9 downregulated genes. After the univariate Cox regression model analysis, we obtained 27 prognosis-related HRGs. Of these, 25 genes were risk factors for cancer, and 2 genes were protective factors. The PP was composed by 12 key genes (HDLBP, SAP30, PFKP, DPYSL4, SLC2A1, HMOX1, PGK1, ERO1A, LDHA, ENO2, SLC6A6, and TPI1). GSCA results showed the overall activity of these 12 key genes in 10 cancer-related pathways. Besides, CMap identified deferoxamine, crotamiton, talampicillin, and lycorine might have effects with HCC. Conclusions. This study firstly reported 12 prognostic HRGs and constructed the model of the PP. This comprehensive research of multiple databases helps us gain insight into the biological properties of HCC and provides deferoxamine, crotamiton, talampicillin, and lycorine as potential drugs to fight against HCC.

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Clinical significance of crown-like structures to trastuzumab response in patients with primary invasive HER2+ breast cancer.

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.15_suppl.e12533 ◽

2021 ◽

Vol 39 (15_suppl) ◽

pp. e12533-e12533

Author(s):

Constantinos Savva ◽

Charles N Birts ◽

Stéphanie A Laversin ◽

Alicia Lefas ◽

Jamie Krishnan ◽

...

Keyword(s):

Breast Cancer ◽

Adipose Tissue ◽

Cancer Patients ◽

Metastatic Disease ◽

Cox Regression ◽

Prognostic Significance ◽

Metabolic Reprogramming ◽

Breast Cancer Patients ◽

Adjuvant Trastuzumab ◽

Her2 Breast Cancer

e12533 Background: Obesity is associated with breast cancer development and worse survival. Obesity can initiate, promote, and maintain systemic inflammation via metabolic reprogramming of macrophages that encircle adipocytes, termed crown-like structures (CLS). In breast cancer patients, CLS are present in 36-50% of patients and have been associated with anthropometric parameters. Here we focus on HER2+ breast cancer. The role of adiposity in HER2+ breast cancer is conflicting which may be attributed to the tumour heterogeneity. Adiposity has also been shown to affect the local immune environment of solid tumours. However, the prognostic significance of CLS in HER2+ breast cancer is still unknown. Methods: We investigated the prognostic significance of CLS in a cohort of 219 patients with primary HER2+ breast cancer who were diagnosed between 1982 to 2012 in Southampton General Hospital. This cohort includes 76 HER2+ trastuzumab naïve patients and 143 HER2+ patients treated with adjuvant trastuzumab. We stained FFPE tumour samples for the expression of CD68, CD16 and CD32B on CLS and correlated these to clinical outcomes. CLS were defined as CLS within distant adipose tissue, CLS within the adipose-tumour border (B-CLS) and intratumoural CLS. CLS were quantified manually in full face sections by two independent scorers and descriptive and Cox regression analysis was carried out. Results: A total of 201 tumours were suitable for CLS analyses. The median follow-up was 34.74 months (range, 0.43-299.08). In the trastuzumab naive cohort, B-CLS≤1 and B-CLS > 1 were present in 37 (52.11%) and 34 (47.89%), respectively. In the trastuzumab treated cohort, B-CLS≤1 were identified in 69 (53.08%) and B-CLS > 1 were found in 61 (46.92%) of the tumours. CLS were more commonly found in the adipose-tumour border (60.89%) rather than in the distant adipose tissue (36.14%) or intratumorally (14.36%). The presence of any CLS was significantly associated with BMI≥25 kg/m2 (p = 0.018). There was strong evidence of association between CD68+CD32B+ B-CLS and BMI≥25 kg/m2 (p = 0.007). Co-expression of CD16 and CD32B by B-CLS was more frequent in patients with BMI≥25 kg/m2 (p = 0.036). Survival analysis showed shorter time to metastatic disease in patients with CD68+ B-CLS > 1 (p = 0.011) in the trastuzumab treated cohort. Subgroup analysis revealed that in the BMI≥25 kg/m2 group, patients with CD68+ B-CLS > 1 had shorter time to metastatic disease compared to patients with B-CLS≤1 (p = 0.004). Multivariate cox regression showed that B-CLS > 1 is an independent prognostic factor for shorter time to metastatic disease in patients with primary HER2+ breast cancer that received adjuvant trastuzumab (HR 6.81, 95%CI (1.38-33.54), p = 0.018). Conclusions: B-CLS can be potentially used as a predictive biomarker to optimize the stratification and personalisation of treatment in HER2-overexpressed breast cancer patients.

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Commission on Cancer CP3R Compliance Rates for Treatment of Patients With Triple Negative and HER2+ Breast Cancer: A National Cancer Database Analysis

The American Surgeon ◽

10.1177/00031348211051674 ◽

2021 ◽

pp. 000313482110516

Author(s):

Srivarshini C. Mohan ◽

Joshua Tseng ◽

Marissa Srour ◽

Alice Chung ◽

Ashley Marumoto ◽

...

Keyword(s):

Breast Cancer ◽

Overall Survival ◽

Cox Regression ◽

Quality Care ◽

Private Insurance ◽

National Cancer Database ◽

Database Analysis ◽

Her2 Breast Cancer ◽

Academic Hospitals ◽

Multi Agent

Background Cancer Program Practice Profile Reports (CP3R) metrics were released by the Commission on Cancer to provide standards for high-quality care. One metric is the recommendation of combination chemotherapy or chemo-immunotherapy (CIT) within 120 days of diagnosis for women under 70 with AJCC T1cN0M0 or Stage IB-III HER2+ or hormone receptor negative breast cancer ([Multi-agent chemotherapy] MAC). Our study assesses national concordance rates for MAC and CIT. Methods The National Cancer Database was queried from 2004-2014. Results 122,045 patients met criteria, of whom treatment for 101,800 (83.4%) patients was concordant with MAC and CIT. Treatment concordance increased from 75.7% in 2004 to 89.5% in 2014. For HER2+ patients, use of CIT treatment downtrended with progression of pathological stage, from 70.1% (stage I) to 58.1% (stage III). Mean overall survival of patients whose treatment was concordant with MAC and CIT was longer than that of patients who were non-concordant (146.6 vs 143.8 months, P <.01). On Cox regression, there was a survival benefit for concordant patients who were treated at academic hospitals (HR .89, 95% CI 0.802-.976) and had private insurance (HR .76, 95% CI 0.65-.89). Conclusion Compliance with MAC and CIT has improved over the past decade and is associated with a significant improvement in overall survival.

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Real-world analysis of disease progression after CDK 4/6 inhibitor (CDKi) therapy in patients with hormone receptor positive (HR+)/HER2- metastatic breast cancer (MBC).

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.15_suppl.e13030 ◽

2021 ◽

Vol 39 (15_suppl) ◽

pp. e13030-e13030

Author(s):

Malinda West ◽

Andy Kaempf ◽

Shaun Goodyear ◽

Thomas Kartika ◽

Jessica Ribkoff ◽

...

Keyword(s):

Breast Cancer ◽

Cox Regression ◽

Metastatic Breast ◽

Molecular Characteristics ◽

Rapid Progression ◽

Hormone Receptor Positive ◽

Her2 Breast Cancer ◽

Metastatic Setting ◽

Increased Risk ◽

Visceral Disease

e13030 Background: CDKi with endocrine therapy (ET) is approved treatment of metastatic HR+/HER2- breast cancer based on PFS benefit vs ET alone. Outcomes data following CDKi discontinuation (dc) is limited, with trials ongoing in this setting. The reported phenomenon of rapid progression within 4 months of CDKi dc raises concern over CDKi impact on HR+/HER2- MBC biology. This study aims to define outcomes after CDKi dc and identify predictors of progression. Methods: This is a retrospective review of women ≥18 years with HR+/HER2- MBC who received CDKi between 4/1/14 and 12/1/19. Patient and tumor characteristics, pre and post CDKi tx, and reason for CDKi dc were collected. Time to event outcomes from date of CDKi dc (primary = PFS, secondary = Overall Survival, OS) were analyzed with Kaplan Meier estimators and Cox regression. Results: Analysis included 140 patients (median age 65 years), with most MBC (84%) arising from earlier stage disease. 51% of MBCs had visceral disease, and 66% received tx prior to CDKi. The most common CDKi was palbociclib (93%); and most common ET were letrozole (52%) and fulvestrant (40%). Median CDKi tx duration was 9 months (3.5 – 17.4) with 80% dc due to progression. Post CDKi txs included chemotherapy (44%), ET (24%), targeted tx (21%), no further tx (7%) and CDKi tx (4%). Median follow up was 12 months. mPFS post CDKi dc were 6.5 months (95% CI: 5.0 – 7.9) and 11.3 months (95% CI: 4.6 – 23.7) in patients who dc CDKi due to progression or other reasons, respectively (HR 1.77, 95%CI: 1.10-2.85). Among 112 patients who progressed on CDKi, estimated 4-month incidence of post CDKi progression or death was 31% (Table ). mOS post CDKi dc was 15.4 months (95%CI: 13.3-19.0) and mOS post CDKi initiation was 26.5 months (95% CI: 23.3 – 34.3). Visceral disease (HR 1.45, 95%CI: 1.01-2.08) and progression as reason for CDKi dc (HR 1.77, 95%CI: 1.1-2.85) were predictors of PFS (p < 0.05). Receiving fulvestrant with CDKi (HR 1.42, 95%CI: 0.96-1.0), prior chemotherapy in the metastatic setting (HR = 1.39, 95% CI: 0.90 – 2.14), and shorter CDKi duration were associated with non-significant increased risk of PFS. Conclusions: Rapid progression or death at 4 months occurred in 31% of MBCs following CDKi dc due to progression. Ongoing studies to define clinical and molecular characteristics of rapidly progressing tumors are underway to develop targeted tx approaches and improve outcomes.[Table: see text]

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Exploratory Analysis of Single-Gene Predictive Biomarkers in HERA DASL Cohort Reveals That C8A mRNA Expression Is Prognostic of Outcome and Predictive of Benefit of Trastuzumab

JCO Precision Oncology ◽

10.1200/po.18.00016 ◽

2018 ◽

pp. 1-12 ◽

Cited By ~ 1

Author(s):

Scooter Willis ◽

Varvara Polydoropoulou ◽

Yuliang Sun ◽

Brandon Young ◽

Zoi Tsourti ◽

...

Keyword(s):

Breast Cancer ◽

Mrna Expression ◽

Cox Regression ◽

Single Gene ◽

Disease Free Survival ◽

Predictive Biomarkers ◽

Exploratory Analysis ◽

Treatment Benefit ◽

Significant Treatment ◽

Her2 Breast Cancer

Purpose The Herceptin Adjuvant study is an international multicenter randomized trial that compared 1 or 2 years of trastuzumab given every 3 weeks with observation in women with human epidermal growth factor 2–positive (HER2+) breast cancer after chemotherapy. Identification of biomarkers predictive of a benefit from trastuzumab will minimize overtreatment and lower health care costs. Methods To identify possible single-gene biomarkers, an exploratory analysis of 3,669 gene probes not expected to be expressed in normal breast tissue was conducted. Disease-free survival (DFS) was used as the end point in a Cox regression model, with the interaction term between C8A mRNA and treatment as a categorical variable split on the cohort mean. Results A significant interaction between C8A mRNA and treatment was detected ( P < .001), indicating a predictive response to trastuzumab treatment. For the C8A-low subgroup (mRNA expression lower than the cohort mean), no significant treatment benefit was observed ( P = .73). In the C8A-high subgroup, patients receiving trastuzumab experienced a lower hazard of a DFS event by approximately 75% compared with those in the observation arm (hazard ratio [HR], 0.25; P < .001). A significant prognostic effect of C8A mRNA also was seen ( P < .001) in the observation arm, where the C8A-high group hazard of a DFS event was three times the respective hazard of the C8A-low group (HR, 3.27; P < .001). C8A mRNA is highly prognostic in the Hungarian Academy of Science HER2+ gastric cancer cohort (HR, 1.72; P < .001). Conclusion C8A as a single-gene biomarker prognostic of DFS and predictive of a benefit from trastuzumab has the potential to improve the standard of care in HER2+ breast cancer if validated by additional studies. Understanding the advantage of overexpression of C8A related to the innate immune response can give insight into the mechanisms that drive cancer.

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