Breast Cancer Network Research Articles

Integrating molecular pathway with genome-wide association data for causality identification in breast cancer

ObjectiveThe study purpose was to explore the causal association between pyruvate metabolism and breast cancer (BC), as well as the molecular role of key metabolic genes, by using bioinformatics and Mendelian randomization (MR) analysis.MethodsWe retrieved and examined diverse datasets from the GEO database to ascertain differentially acting genes (DAGs) in BC via differential expression analysis. Following this, we performed functional and pathway enrichment analyses to ascertain noteworthy molecular functions and metabolic pathways in BC. Employing MR analysis, we established a causal association between pyruvate metabolism and the susceptibility to BC. Additionally, utilizing the DGIdb database, we identified potential targeted medications that act on genes implicated in the pyruvate metabolic pathway and formulated a competing endogenous RNA (ceRNA) regulatory network in BC.ResultsWe collected the datasets GSE54002, GSE70947, and GSE22820, and identified a total of 1127 DEGs between the BC and NC groups. GO and KEGG enrichment analysis showed that the molecular functions of these DEGs mainly included mitotic nuclear division, extracellular matrix, signaling receptor activator activity, etc. Metabolic pathways were mainly concentrated in PI3K−Akt signaling pathway, Cytokine−cytokine receptor binding and Pyruvate, Tyrosine, Propanoate and Phenylalanine metabolism, etc. In addition, MR analysis demonstrated a causal relationship between pyruvate metabolism and BC risk. Finally, we constructed a regulatory network between pathway genes (ADH1B, ACSS2, ACACB, ADH1A, ALDH2, and ADH1C) and targeted drugs, as well as a ceRNA (lncRNA-miRNA-mRNA) regulatory network for BC, further revealing their interactions.ConclusionsOur research revealed a causal association between pyruvate metabolism and BC risk, found that ADH1B, ACSS2, ACACB, ADH1A, ALDH2, and ADH1C takes place an important part in the development of BC in the molecular mechanisms related to pyruvate metabolism, and identified some potential targeted small molecule drugs.

Using an AI trial screening tool to assess language as a barrier for enrollment of underrepresented minorities in cancer clinical trials.

e13586 Background: A major limitation of clinical trials is limited generalizability due to low enrollment of underrepresented minorities (URM). The percentage of patients who are non-English speaking (NES) is higher in URM and language barriers may discourage providers to offer participation in clinical trials. We have developed an artificial intelligence-based system to identify patients eligible for clinical trials, Clinical Trials Patient Matching (CTPM). This platform offers an ideal opportunity to explore bias in enrolling patients on clinical trials (CT). Among patients identified by CTPM as eligible for CT we assessed the impact of NES on trial enrollment. Methods: Individual algorithms were constructed within CTPM to identify patients potentially eligible for two trials open at Yale Cancer Center, DARE (NCT04567420) and EMBER-4 (NCT05514054). Eligibility was confirmed by Clinical Trials Office staff and notification of eligibility was communicated to the treating provider. Retrospectively, we evaluated the impact of NES status on clinical trial enrollment. This analysis occurred between 9/1/2022 and 11/30/2023 and all study-related activities were approved by the Yale IRB. Results: Out of the 13,466 unique patients presenting to the Yale Cancer Center and Smilow Cancer Network breast program within the period of study, 5.1% were NES and 94.9% were English speaking (ES). Of the patients identified by CTPM as eligible for the 2 clinical trials 7.9% were NES and 92.14% were ES. However, out of patients enrolled, only 1.59% were NES and 98.41% were ES. For the DARE trial, enrollment rate was 38.3% for ES vs 0% for NES (p=0.0081). For the EMBER4 trial, enrollment was 13.4% for ES vs 14.3% for NES (p=1.0). The aggregate data for both trials revealed an enrollment rate of 29.4% for ES vs 5.6% for NES (p=0.0285). Conclusions: We found that patients who identify as NES were less likely to be enrolled in cancer clinical trials. CTPM appears to be an effective tool to prospectively identify underrepresented populations in clinical trials and serve as a platform for developing interventions to address disparities in trial participation, including language. [Table: see text]

Unraveling the cross-talk between N6-methyladenosine modification and non-coding RNAs in breast cancer: Mechanisms and clinical implications.

In recent years, breast cancer (BC) has surpassed lung cancer as the most common malignant tumor worldwide and remains the leading cause of cancer death in women. The etiology of BC usually involves dysregulation of epigenetic mechanisms and aberrant expression of certain non-coding RNAs (ncRNAs). N6-methyladenosine (m6A), the most prevalent RNA modification in eukaryotes, widely exists in ncRNAs to affect its biosynthesis and function, and is an important regulator of tumor-related signaling pathways. Interestingly, ncRNAs can also regulate or target m6A modification, playing a key role in cancer progression. However, the m6A-ncRNAs regulatory network in BC has not been fully elucidated, especially the regulation of m6A modification by ncRNAs. Therefore, in this review, we comprehensively summarize the interaction mechanisms and biological significance of m6A modifications and ncRNAs in BC. Meanwhile, we also focused on the clinical application value of m6A modification in BC diagnosis and prognosis, intending to explore new biomarkers and potential therapeutic targets.

Abstract 3688: Survival benefit of adjuvant radiotherapy among women with high comorbidity burden and low-risk breast cancer: SEER-MHOS analysis

Abstract Background: The National Comprehensive Cancer Network Breast Cancer Guidelines Committee has suggested that adjuvant radiotherapy (RT) after breast-conserving surgery (BCS) could be omitted among older women with low-risk breast cancer (early-stage, node-negative, and ER-positive) if they were treated with endocrine therapy. However, the effect of RT among older women with multimorbidity is not clearly understood. Objective: We examined the effect of adjuvant RT on survival outcomes among older women. We also assessed whether the association between RT and survival is modified by comorbidity burden. Methods: A total of 1105 older women (65+) diagnosed with low-risk breast cancer in 1998-2012 and who received BCS were identified from the population-based Surveillance, Epidemiology, and End-Results-Medicare Health Outcomes Survey (SEER-MHOS) data resource. A propensity score-based inverse probability of treatment weight (IPTW) was calculated with weighting applied to Cox regression models to obtain hazard ratios for the association of RT with survival outcomes. Stratified analysis was conducted to examine differential effects according to the comorbidity burden class, which was identified using the latent class analysis. Results: Over a 5-year follow-up period, a total of 117 deaths occurred (25 cancer-related and 92 noncancer-related). The IPTW-adjusted Cox proportional hazard analysis showed that RT omission did not significantly increase the risk for 5-year cancer-specific deaths (P=0.202). However, RT omission increased the risk for 5-year noncancer death by 1.84-fold (95% CI=1.35, 2.51) and all-cause death by 1.49-fold (95% CI=1.41, 1.95). The stratified analysis showed that the effect of RT omission on the risk of breast cancer-specific deaths was similar across the different comorbidity groups. For noncancer and all-cause deaths, the effect of RT omission varied by comorbidity burden. In Class 1, RT omission was not associated with an increased risk of noncancer and all-cause deaths. However, in Classes 2 and 3, RT omission is significantly associated with an increased risk of 5-year all-cause deaths in a dose-response manner: by 1.66-fold (95% CI=1.07, 2.56) in Class 2 and 1.96-fold in Class 3 (95% CI=1.13, 3.41). Similar results were observed for 10-year survival. Conclusions: RT omission does not increase the risk of cancer-specific death and appears to be a valid clinical decision for older women with low-risk breast cancer and multimorbidity. Citation Format: Eunkyung Lee, Robert B. Hines, Jianbin Zhu, Kayla Montan, Michael J. Rovito. Survival benefit of adjuvant radiotherapy among women with high comorbidity burden and low-risk breast cancer: SEER-MHOS analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3688.

The Expression and Prognostic Significance of Major MicroRNA Genes in Breast Cancer Based on Bioinformatics Analysis

Objective: Breast Cancer (BC) is characterized by high complexity and heterogeneity, and microRNA (miRNA) is bound up with the occurrence and development of BC. In this study, we evaluated the prognostic value of miRNA in BC. Background: Breast ductal and lobular cancers are the most common types of Breast Carcinomas (BC) and indicate the high complexity heterogeneity in this disease. Each BC patient has unique morphological and molecular features. MicroRNAs (miRNAs) play a critical role in human oncogenesis, progression, and prognosis. Our study aimed to identify potential prognostic biomarkers of breast ductal and lobular cancers to predict the overall survival outcome. Methods: All analyzed miRNA sequencing and clinical data were obtained from the Genomic Data Commons Data Porta. edgeR package in R software was used to analyze the differential miRNA expression profiles. Complete survival information and differentially expressed miRNA expression were obtained and the Caret package was used for random division of the samples along with their profiles into two groups (training group and test group). We performed univariate Cox regression analyses for miRNAs in the training group. We utilized three different web-based tools to identify the target genes of miRNAs and used the Perl language to evaluate the target genes for miRNA signature. STRING database was used to assess PPIs. Results: A total of 304 differentially expressed miRNAs were identified (213 were upregulated and 91 were downregulated). Among these, nine (hsa-miR-204-5p, hsa-miR-7706, hsa-miR-1247-3p, hsa-miR-20b-3p, hsa-miR-605-5p, hsa-miR-615-3p, hsa-miR-4652-5p, hsa-miR-9-5p, hsa-miR-2115-5p) miRNAs which remarkably correlated with overall survival rate of BC were performed by Cox regression analysis and miRNA signature risk score built. And then we performed the model of BC patients for three years survival risk, the AUCs of ROC were 0.804, 0.667, and 0.739 in the training, test, and entire groups, respectively. miRNAs were differentially expressed in tumor-related biological processes and pathways by functional enrichment and bioinformatic analysis. Conclusion: The current study provided novel insights into the miRNA-based mRNA network in BC. The nine miRNA and ten hub genes may be independent prognostic signatures for survival prediction in BC patients.

Integrated Analysis of Circular RNA-Associated ceRNA Network Reveals Potential circRNA Biomarkers in Human Breast Cancer.

Circular RNA (circRNA) is closely related to tumorigenesis and cancer progression. Yet, the roles of cancer-specific circRNAs in the circRNA-related ceRNA network of breast cancer (BRCA) remain unclear. The aim of this study was to construct a ceRNA network associated with circRNA and to explore new therapeutic and prognostic targets and biomarkers for breast cancer. We downloaded the circRNA expression profile of BRCA from Gene Expression Omnibus (GEO) microarray datasets and downloaded the miRNA and mRNA expression profiles of BRCA from The Cancer Genome Atlas (TCGA) database. Differentially expressed mRNAs (DEmRNAs), differentially expressed miRNAs (DEmiRNAs), and differentially expressed circRNAs (DEcircRNAs) were identified, and a competitive endogenous RNA (ceRNA) regulatory network was constructed based on circRNA–miRNA pairs and miRNA–mRNA pairs. Gene ontology and pathway enrichment analyses were performed on mRNAs regulated by circRNAs in ceRNA networks. Survival analysis and correlation analysis of all mRNAs and miRNAs in the ceRNA network were performed. A total of 72 DEcircRNAs, 158 DEmiRNAs, and 2762 DE mRNAs were identified. The constructed ceRNA network contains 60 circRNA–miRNA pairs and 140 miRNA–mRNA pairs, including 40 circRNAs, 30 miRNAs, and 100 mRNAs. Functional enrichment indicated that DEmRNAs regulated by DEcircRNAs in ceRNA networks were significantly enriched in the PI3K-Akt signaling pathway, microRNAs in cancer, and proteoglycans in cancer. Survival analysis and correlation analysis of all mRNAs and miRNAs in the ceRNA network showed that 13 mRNAs and 6 miRNAs were significantly associated with overall survival, and 48 miRNA–mRNA interaction pairs had a significant negative correlation. A PPI network was established, and 21 hub genes were determined from the network. This study provides an effective bioinformatics basis for further understanding of the molecular mechanisms and predictions of breast cancer. A better understanding of the circRNA-related ceRNA network in BRCA will help identify potential biomarkers for diagnosis and prognosis.

Identification of LIG1 and LIG3 as prognostic biomarkers in breast cancer.

DNA ligase (LIG) plays a key role in connecting the 3′-OH end of a DNA strand to the 5′-P end of another DNA strand, resulting in the formation of a phosphodiester bond. It has been reported that LIGs (including LIG1, LIG3 and LIG4) play important roles in the occurrence and progression of many cancers. However, the role of LIGs in breast cancer (BC) is still unclear. In this study, we aim to reveal the expression level, function, and prognostic value of LIGs in BC. Bioinformatic tools were used to study the expression level, potential function and prognostic value of LIG1 and LIG3 in BC patients. ENCORI was used to predict microRNAs (miRNAs) that regulate LIG1 and LIG3 and established a valuable miRNA–mRNA regulation network for BC. We found that the expression of LIG1 and LIG3 was upregulated in BC and predicted high relapse-free survival (RFS) in BC patients. Functional annotation analysis was performed to reveal the role of LIG1 and LIG3 in BC. In addition, hsa-miR-22-3p was identified to be potentially involved in the regulation of LIG3. We suggest that LIG1 and LIG3 are novel valuable prognostic biomarkers for BC and has-miRNA-22-3p may be a potential therapeutic target for BC.

How to Perform Repeat Sentinel Node Biopsy Safely After a Previous Mastectomy: Technical Features and Oncologic Outcomes.

The latest National Comprehensive Cancer Network Breast Cancer Guidelines still discourage repeat sentinel node biopsy (SNB) after mastectomy, and the largest multicentric study available reports only 35 cases in the absence of previous axillary dissection (AD). From January 2003 to November 2018, 89 patients of the European Institute of Oncology with local recurrence of breast cancer after mastectomy, free of distant metastases, with a clinically negative axilla and a negative axillary ultrasound, in absence of AD, underwent lymphatic mapping before wide local excision. During surgery, SNB was successful for 99% of the patients, with 14% being metastatic. Additional metastatic nodes removed by AD after a positive sentinel node occurred in 82% of cases. After a medium follow-up period of 3.7years, the overall survival rate was 96.7%, and the disease-free survival rate was 84.4%. No axillary relapse after AD was recorded. One patient who refused human epidermal growth factor receptor 2 (HER2)-targeted treatment experienced ipsilateral axillary recurrence after a negative repeat SNB. The first axillary level was never directly irradiated because all the patients with positive repeat SNB underwent AD. For invasive luminal-like HER2-negative recurrences, the metastatic sentinel node was significantly associated with the choice to prescribe adjuvant chemotherapy (p=0.003). In specialized centers, repeat axillary SNB for patients with local recurrence after mastectomy in the absence of previous AD can represent a safe option for detection and removal of occult axillary disease that would otherwise not be excised/irradiated to achieve better local control and could possibly influence the choice of adjuvant treatments.

Factors Associated with Breast Cancer Screening Adherence among Church-Going African American Women.

Relative to White women, African American/Black women are at an increased risk of breast cancer mortality. Early detection of breast cancer through mammography screening can mitigate mortality risks; however, screening rates are not ideal. Consequently, there is a need to better understand factors associated with adherence to breast cancer screening guidelines to inform interventions to increase mammography use, particularly for groups at elevated mortality risk. This study used the Andersen Behavioral Model of Health Services Use to examine factors associated with adherence to National Comprehensive Cancer Network breast cancer screening guidelines amongst 919 African American, church-going women from Houston, Texas. Logistic regression analyses measured associations between breast cancer screening adherence over the preceding 12 months (adherent or non-adherent) and predisposing (i.e., age, education, and partner status), enabling (i.e., health insurance status, annual household income, employment status, patient-provider communication, and social support), and need (i.e., personal diagnosis of cancer, family history of cancer, and risk perception) factors, separately and conjointly. Older age (predisposing: OR = 1.015 (1.007–1.023)), having health insurance and ideal patient–provider communication (enabling: OR = 2.388 (1.597–3.570) and OR = 1.485 (1.080–2.041)), and having a personal diagnosis of cancer (need: OR = 2.244 (1.058–4.758)) were each associated with greater odds of screening adherence. Only having health insurance and ideal patient-provider communication remained significantly associated with screening adherence in a conjoint model; cancer survivorship did not moderate associations between predisposing/enabling factors and screening adherence. Overall, results suggest that interventions which are designed to improve mammography screening rates amongst African American women might focus on broadening health insurance coverage and working to improve patient–provider communication. Implications for multi-level intervention approaches, including the role of churches in their dissemination, are proposed.

Construction and Analysis of the Dysregulated ceRNA Network and Identification of Risk Long Noncoding RNAs in Breast Cancer.

Breast cancer (BRCA) is the second leading cause of cancer-related mortality in women worldwide. However, the molecular mechanism involved in the development of BRCA is not fully understood. In this study, based on the miRNA-mediated long non-coding RNA (lncRNA)–protein coding gene (PCG) relationship and lncRNA–PCG co-expression information, we constructed and analyzed a specific dysregulated lncRNA–PCG co-expression network in BRCA. Then, we performed the random walk with restart (RWR) method to prioritize BRCA-related lncRNAs through comparing their RWR score and significance. As a result, we identified 30 risk lncRNAs for BRCA, which can distinguish normal and tumor samples. Moreover, through gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, we found that these risk lncRNAs mainly synergistically exerted functions related to cell cycle and DNA separation and replication. At last, we developed a four-lncRNA prognostic signature (including AP000851.1, LINC01977, MAFG-DT, SIAH2-AS1) and assessed the survival accuracy of the signature by performing time-dependent receiver operating characteristic (ROC) analysis. The areas under the ROC curve for 1, 3, 5, and 10 years of survival prediction were 0.68, 0.61, 0.62, and 0.63, respectively. The multivariable Cox regression results verified that the four-lncRNA signature could be used as an independent prognostic biomarker in BRCA. In summary, these results have important reference value for the study of diagnosis, treatment, and prognosis evaluation of BRCA.

Effects of Radiation Therapy and Comorbidity on Health-Related Quality of Life and Mortality Among Older Women With Low-Risk Breast Cancer: Protocol for a Retrospective Cohort Study.

BackgroundThe National Comprehensive Cancer Network Breast Cancer Guidelines Committee suggests that the omission of adjuvant radiation therapy (RT) after breast-conserving surgery can be a reasonable option among older women with low-risk breast cancer (early-stage, estrogen receptor-positive, and node-negative) if they are treated with endocrine therapy. However, RT usage in this group of women still exceeds 50%. Conversely, older women tend to forego RT (even when necessary) due to cost, inconvenience, and potential adverse responses associated with RT. Understanding health-related quality of life (HRQOL) change with receipt of RT among older women in the modern era is limited due to the under-representation of this population in clinical trials.ObjectiveThe proposed study aims to examine the associations of RT with HRQOL trajectories as well as survival outcomes among older women with 5-10 years of follow-up. We will also assess whether prediagnosis comorbidity burden influences receipt of RT and whether the associations between RT and HRQOL trajectory and survival outcomes are modified by the comorbidity burden.MethodsWe will use a retrospective cohort study design with the population-based Surveillance, Epidemiology, and End-Results database linked to the Medicare Health Outcomes Survey (SEER-MHOS). Older women (≥65 years) who were diagnosed with low-risk breast cancer in 1998-2014, received breast-conserving surgery, and participated in MHOS 1998-2016 are eligible for this analysis. The latent class analysis clustering method will be used to identify each patient’s prediagnosis comorbidity burden, and HRQOL will be evaluated using the Short Form 36/Veterans RAND 12-Item Health Survey scales. The inverse-weighted estimates of the probability of treatment will be included to control for treatment selection bias and confounding effects in subsequent analysis. The association of RT with HRQOL trajectory will be evaluated using inverse-weighted multilevel growth mixture models. The inverse-weighted Cox regression model will be used to obtain hazard ratios with 95% CIs for the association of RT with survival outcomes. Differential effects of RT on both outcomes according to comorbidity burden class will also be evaluated.ResultsAs of October 2020, the study was approved by the institutional review board, and SEER-MHOS data were obtained from the National Cancer Institute. Women with low-risk breast cancer who met inclusion and exclusion criteria have been identified, and prediagnosis comorbidity burden class has been characterized using latent class analysis. Further data analysis will begin in November 2020, and the first manuscript will be submitted in a peer-reviewed journal in February 2021.ConclusionsThis research can potentially improve clinical outcomes of older women with low-risk breast cancer by providing them additional information on the HRQOL trajectories when they make RT treatment decisions. It will facilitate informed, shared treatment decision making and cancer care planning to ultimately improve the HRQOL of older women with breast cancer.International Registered Report Identifier (IRRID)DERR1-10.2196/18056

Construction and Analysis of Competing Endogenous RNA Networks for Breast Cancer Based on TCGA Dataset.

Background Long noncoding RNAs (lncRNAs) act as competing endogenous RNAs for microRNAs in cancer metastasis. However, the roles of lncRNA-mediated competing endogenous RNA (ceRNA) networks for breast cancer (BC) are still unclear. Material and Methods. The expression profiles of mRNAs, lncRNAs, and miRNAs with BC were extracted from The Cancer Genome Atlas database. Weighted gene coexpression network analysis was conducted to extract differentially expressed mRNAs (DEmRNAs) that might be core genes. Through miRWalk, TargetScan, and miRDB to predict the target genes, an abnormal lncRNA-miRNA-mRNA ceRNA network with BC was constructed. The survival possibilities of mRNAs, miRNAs, and lncRNAs for patients with BC were determined by Kaplan-Meier survival curves and Oncomine. Results We identified 2134 DEmRNAs, 1059 differentially expressed lncRNAs (DElncRNAs), and 86 differentially expressed miRNAs (DEmiRNAs). We then compose a ceRNA network for BC, including 72 DElncRNAs, 8 DEmiRNAs, and 12 DEmRNAs. After verification, 2 lncRNAs (LINC00466, LINC00460), 1 miRNA (Hsa-mir-204), and 5 mRNAs (TGFBR2, CDH2, CHRDL1, FGF2, and CHL1) were meaningful as prognostic biomarkers for BC patients. In the ceRNA network, we found that three axes were present in 10 RNAs related to the prognosis of BC, namely, LINC00466-Hsa-mir-204-TGFBR2, LINC00466-Hsa-mir-204-CDH2, and LINC00466-Hsa-mir-204-CHRDL1. Conclusion This study highlighted lncRNA-miRNA-mRNA ceRNA related to the pathogenesis of BC, which might be used for latent diagnostic biomarkers and therapeutic targets for BC.

High SET Domain Bifurcated 1 (SETDB1) Expression Predicts Poor Prognosis in Breast Carcinoma.

BackgroundSETDB1, an H3K9-specific histone methyltransferase, plays important roles in the progression of various human cancers. However, the expression patterns and its clinical roles of SETDB1 remain elusive in breast cancer (BC).Material/MethodsThe transcriptional level of SETDB1 and survival data in BC were analyzed through UALCAN, ONCOMINE, and Pan Cancer Prognostics Database. SETDB1 protein expression was assessed by immunohistochemistry (IHC) in 159 BC tissue samples. The associations between SETDB1 expression and clinical pathological characteristics of patients were analyzed. The GEO dataset GSE108656 was downloaded and analyzed to identify the differentially expressed genes (DEGs) between control and BC cells targeting interference with SETDB. The DEGs were further integrated by bioinformatics analysis to decipher the key signaling pathways and hub genes that are regulated by SETDB.ResultsThe public databases showed the level of SETDB1 mRNA was significantly upregulated in BC. Our IHC results demonstrated the level of SETDB1 protein was associated with tumor size (P=0.028), histopathological grading (P=0.012), lymph node metastasis (P<0.001), and TNM stage (P<0.001). High expression of SETDB1 indicated worse overall survival (P=0.015) and shorter relapse-free survival (P=0.027). The bioinformatic analysis of GSE108656 suggested that the SETDB1-related DEGs was mainly enriched in antigen processing and presentation, as well as immune networks in BC. The cytoHubba analysis suggested the top 10 hub genes were IL6, BMP4, CD74, PECAM1, HLA-DPA1, HLA-DRA, LAMC1, CTSB, SERPINA1, and CTSD.ConclusionsThe results suggest that SETDB1 is an oncogene and can serve as a prognostic biomarker for BC. However, the mechanisms of SETDB1 in BC remain to be explored.

Abstract P3-08-46: Correlation of prognostic indicators based on clinical and pathological features in hormone receptor positive and HER2 receptor negative early breast cancer with the 21 gene assay recurrence score

Abstract Background: With the advent of genomic testing in routine practice to predict the benefit of adjuvant chemotherapy, in a resource limited health service, many multi-disciplinary breast cancer teams are relying on known clinical and pathological factors to determine which patients undergo testing or to avoid/receive chemotherapy in hormone receptor positive, HER2 negative (HR+, HER2 -ve) breast cancer. These factors are manipulated in formulae or in online prognostic calculators to determine "risk". Oncotype DX Recurrence Score® is routinely used in the UK to determine benefit of adjuvant chemotherapy in early breast cancer according to National guidelines (NICE) which determines risk using the Nottingham Prognostic Index (NPI) and Predict. Methods: With the kind permission of surgical and oncology colleagues within the Wales Cancer Network Breast Clinical Site Group, all patients with HR+, HER2-ve invasive breast cancer who had undergone Oncotype DX Recurrence Score® testing between 31/10/15 and 1/11/18 were matched to the prospectively held national cancer database. Post- operative tumour size, grade, nodal status, age of patient and route of diagnosis were then utilized to calculate the NPI for each case and the PREDICT! on line calculator for chemotherapy benefit in addition to endocrine therapy. A correlation co-efficient was then calculated for NPI, PREDICT 5 and PREDICT 10 to the recurrence score®. Ki 67 is not routinely calculated. Results: There were 734 cases with a RS® available matched to the cancer registry database, 96 of which had missing data items preventing calculation of NPI or PREDICT! values. Demographics of patients tested – n= 734MeanMedianRangeAge (years)585927-97Referral RouteBreast Cancer Screening296GP Referral/ Symptomatic438RS®Low - &amp;lt;18381Intermediate: 18-25202Intermediate: 26-3051High - ≥31100 GradeG143G2457G3225Grade unknown4Tumour Size T1244T2402T346T45Size unknown36Nodal StatusN0528N1mic58N1 (1_3)110Nodal status unknown38 all RS® (n= 638)r co-efficient of correlationNPI0.07Predict 5 year0.09Predict 10 year0.08LN0 (n= 481)NPI0.12Predict 5 year0.11Predict 10 year0.10LN mic (n= 52)NPI0.29Predict 5 year0.40Predict 10 year0.35LN1 (1_3) (n=105)NPI0.02Predict 5 year0.05Predict 10 year0.05 Conclusions: This is the largest cohort analysis in the UK of recurrence score testing published to date and covers a wider range of node negative, micro metastatic and node positive patients. We have demonstrated a weak correlation between the RS® and the NPI or PREDICT outcome in predicting benefit of chemotherapy and we do not believe these clinic-pathological surrogates should be relied upon to determine indications for adjuvant chemotherapy in HR+, HER2-ve early breast cancer patients or in determining if Oncotype DX Recurrence Score® testing should be performed in order to reduce over treatment with chemotherapy. Citation Format: Marianne Dillon, Adam Yarwood, Daniel Thomas, Wales Cancer Network Breast Clinical Steering Group. Correlation of prognostic indicators based on clinical and pathological features in hormone receptor positive and HER2 receptor negative early breast cancer with the 21 gene assay recurrence score [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P3-08-46.

A Competing Endogenous RNA Network Reveals Novel lncRNA, miRNA and mRNA Biomarkers With Diagnostic and Prognostic Value for Early Breast Cancer.

Background:This study aims to reveal early breast cancer (BC) specific competing endogenous RNA (ceRNA) network through the expression profiles of microRNAs (miRNAs), long non-coding RNAs (lncRNAs) and mRNAs.Methods:Based on The Cancer Genome Atlas (TCGA), we obtained the differentially expressed mRNAs, miRNAs, and lncRNAs (DEmRNAs, DEmiRNAs and DElncRNAs) between early BC and normal samples. The lncRNA–miRNA–mRNA interaction network was constructed using Cytoscape. Functional enrichment were performed using GeneCoDis3. The expression of selected genes were validated by qRT-PCR. Based on the published dataset, we validated the result of TCGA integration analysis. The diagnostic and prognostic value of candidate genes was evaluated by ROC curve analysis and survival analysis, respectively.Results:Totally, 1207 DEmRNAs, 194 DElncRNAs and 37 DEmiRNAs were obtained. Functional enrichment analysis results showed that all of DEmRNAs were enriched in pathway of cytokine-cytokine receptor interaction, PPAR signaling pathway and pathways in cancer. The DEmRNA-DEmiRNA-DElncRNA interaction network in early BC was consisted of 23 DEmiRNAs, 95 DElncRNAs and 309 DEmRNAs. Among ceRNA network, IL-6-hsa-miR-182-5p-ADAMTS9-AS1 interactions, LIFR-hsa-miR-21-5p-ADAMTS9-AS1 interactions and MMP1/MMP11-hsa-miR-145-5p-CDKN2B-AS1 interactions were speculated to involve in the development of early BC. The qRT-PCR results were consistent with our integrated analysis. Except for ADAMTS9-AS1 and CDKN2B-AS1, expression of the others results in the Gene Expression Omnibus (GEO) dataset were generally consistent with TCGA integrated analysis. The area under curve (AUC) of the ADAMTS9-AS1, CDKN2B-AS1, IL-6, MMP11, hsa-miR-145-5p and hsa-miR-182-5p were 0.947, 0.862, 0.842, 0.993, 0.960 and 0.944, and the specificity and sensitivity of the 6 biomarkers were 83.4% and 95.6%, 72.2% and 90.3%, 80.1% and 74.3%, 96.2% and 96.5%, 90.1% and 92.3%, and 88.7% and 90.4%, respectively. In addition, IL-6 had potential prognostic value for early BC.Conclusion:These findings may provide novel insights into the lncRNA-miRNA-mRNA network and uncover potential therapeutic targets in early BC.

Attrition in metastatic breast cancer: a metric to be reported in randomised clinical trials?

Breast cancer remains an incurable disease, causing about 630 000 deaths in 2018 worldwide. 1 Bray F Ferlay J Soerjomataram I Siegel RL Torre LA Jemal A Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018; 68: 394-424 Crossref PubMed Scopus (50356) Google Scholar A better understanding of the underlying biology and the availability of more active drugs have substantially extended life expectancy in some subsets of patients with metastatic breast cancer. 2 Caswell-Jin JL Plevritis SK Tian L et al. Change in survival in metastatic breast cancer with treatment advances: meta-analysis and systematic review. JNCI Cancer Spectr. 2018; 2pky062 Crossref PubMed Google Scholar New drug approvals are dependent on randomised clinical trials that test new treatments head-to-head against standards of care. Although this methodology is pivotal in clinical research, in practice, patients with metastatic breast cancer receive different treatments sequentially across multiple progressions of their disease. 3 Seah DS Luis IV Macrae E et al. Use and duration of chemotherapy in patients with metastatic breast cancer according to tumor subtype and line of therapy. J Natl Compr Canc Netw. 2014; 12: 71-80 Crossref PubMed Scopus (30) Google Scholar Due to a paucity of studies that specifically address treatment sequencing, guidelines recommend first and further lines of treatment on the basis of the results of separate randomised trials specifically conducted in each line of therapy. 4 National Comprehensive Cancer NetworkBreast cancer (version 1.2019). https://www.nccn.org/professionals/physician_gls/pdf/breast_blocks.pdfDate: 2019 Date accessed: April 22, 2019 Google Scholar With the growing number of therapeutic options with overlapping indications, treatment sequencing is becoming a critical issue both in research and clinical practice. 5 Caffo O Treatment sequencing in oncology: balancing clinical trial and real-world evidence. Future Oncol. 2019; 15: 2887-2889 Crossref PubMed Scopus (4) Google Scholar

Artificial Intelligence Treatment Decision Support For Complex Breast Cancer Among Oncologists With Varying Expertise.

The aim of the current study was to assess treatment concordance and adherence to National Comprehensive Cancer Network breast cancer treatment guidelines between oncologists and an artificial intelligence advisory tool. Study cases of patients (N = 1,977) who were at high risk for recurrence or who had metastatic disease and cell types for which the advisory tool was trained were obtained from the Chinese Society for Clinical Oncology cancer database (2012 to 2017). A cross-sectional observational study was performed to examine treatment concordance and guideline adherence among an artificial intelligence advisory tool and 10 oncologists with varying expertise-three fellows, four attending physicians, and three chief physicians. In a blinded fashion, each oncologist provided treatment advice on an average of 198 cases and the advisory tool on all cases (N = 1,977). Results are reported as rates and logistic regression odds ratios. Concordance for the recommended treatment was 0.56 for all physicians and higher for fellows compared with chief and attending physicians (0.68 v 0.54; 0.49; P = .001). Concordance differed by hormone receptor subtype-TNM stage, with the lowest for hormone receptor-positive human epidermal growth factor receptor 2/neu-positive cancers (0.48) and highest for triple-negative breast cancers (0.71) across most TNM stages. Adherence to National Comprehensive Cancer Network guidelines was higher for oncologists compared with the advisory tool (0.96 v 0.82; P < .003) and lower for fellows compared with attending physicians (0.93 v 0.98; 0.96; P = .04). Study findings reflect a complex breast cancer case mix, the limits of medical knowledge regarding optimum treatment, clinician practice patterns, and use of a tool that reflects expertise from one cancer center. Additional research in different practice settings is needed to understand the tool's scalability and its impact on treatment decisions and clinical and health services outcomes.

Integrated Transcriptome and Pathway Analyses Revealed Multiple Activated Pathways in Breast Cancer.

Breast cancer (BC) is the leading cause of cancer-related death in women. Therefore, a better understanding of BC biology and signaling pathways might lead to the development of novel biomarkers and targeted therapies. Although a number of transcriptomic studies have been performed on breast cancer patients from various geographic regions, there are almost no such comprehensive studies performed on breast cancer from patients in the gulf region. This study aimed to provide a better understanding of the altered molecular networks in BC from the gulf region. Herein, we compared the transcriptome of BC to adjacent normal tissue from six BC patients and identified 1,108 upregulated and 518 downregulated transcripts. A selected number of genes from the RNA-Seq analysis were subsequently validated using qRT-PCR. Differentially expressed (2.0-fold change, adj. p < 0.05) transcripts were subjected to ingenuity pathway analysis, which revealed a myriad of affected signaling pathways and functional categories. Activation of ERBB2, FOXM1, ESR1, and IGFBP2 mechanistic networks was most prominent in BC tissue. Additionally, BC tissue exhibited marked enrichment in genes promoting cellular proliferation, migration, survival, and DNA replication and repair. The presence of genes indicative of immune cell infiltration and activation was also observed in BC tissue. We observed high concordance [43.5% (upregulated) and 62.1% (downregulated)] between differentially expressed genes in our study group and those reported for the TCGA BC cohort. Our data provide novel insight on BC biology and suggest common altered molecular networks in BC in this geographic region. Our data suggest future development of therapeutic interventions targeting those common signaling pathways.

Systematic analysis of lncRNA\u2013miRNA\u2013mRNA competing endogenous RNA network identifies four-lncRNA signature as a prognostic biomarker for breast cancer

BackgroundIncreasing evidence has underscored the role of long non-coding RNAs (lncRNAs) acting as competing endogenous RNAs (ceRNAs) in the development and progression of tumors. Nevertheless, lncRNA biomarkers in lncRNA-related ceRNA network that can predict the prognosis of breast cancer (BC) are still lacking. The aim of our study was to identify potential lncRNA signatures capable of predicting overall survival (OS) of BC patients.MethodsThe RNA sequencing data and clinical characteristics of BC patients were obtained from the Cancer Genome Atlas database, and differentially expressed lncRNA (DElncRNAs), DEmRNAs, and DEmiRNAs were then identified between BC and normal breast tissue samples. Subsequently, the lncRNA–miRNA–mRNA ceRNA network of BC was established, and the gene oncology enrichment analyses for the DEmRNAs interacting with lncRNAs in the ceRNA network was implemented. Using univariate and multivariate Cox regression analyses, a four-lncRNA signature was developed and used for predicting the survival in BC patients. We applied receiver operating characteristic analysis to assess the performance of our model.ResultsA total of 1061 DElncRNAs, 2150 DEmRNAs, and 82 DEmiRNAs were identified between BC and normal breast tissue samples. A lncRNA–miRNA–mRNA ceRNA network of BC was established, which comprised of 8 DEmiRNAs, 48 DElncRNAs, and 10 DEmRNAs. Further gene oncology enrichment analyses revealed that the DEmRNAs interacting with lncRNAs in the ceRNA network participated in cell leading edge, protease binding, alpha-catenin binding, gamma-catenin binding, and adenylate cyclase binding. A univariate regression analysis of the DElncRNAs revealed 7 lncRNAs (ADAMTS9-AS1, AC061992.1, LINC00536, HOTAIR, AL391421.1, TLR8-AS1 and LINC00491) that were associated with OS of BC patients. A multivariate Cox regression analysis demonstrated that 4 of those lncRNAs (ADAMTS9-AS1, LINC00536, AL391421.1 and LINC00491) had significant prognostic value, and their cumulative risk score indicated that this 4-lncRNA signature independently predicted OS in BC patients. Furthermore, the area under the curve of the 4-lncRNA signature associated with 3-year survival was 0.696.ConclusionsThe current study provides novel insights into the lncRNA-related ceRNA network in BC and the 4 lncRNA biomarkers may be independent prognostic signatures in predicting the survival of BC patients.

Use of axillary lymph node dissection (ALND) in patients with micrometastatic breast cancer

BackgroundSentinel lymph node (SLN) biopsy is the current prognostic tool for clinically node-negative breast cancer patients. If the SLN reveals macrometastasis, axillary lymph node dissection (ALND) is recommended. However, the use of ALND in patients with micrometastasis is debated. The objective of this study was to assess the utilization of ALND in the treatment of micrometastatic breast cancer. MethodsAn IRB approved, retrospective study of a pooled dataset of breast cancer patients with micrometastatic disease on SLN biopsy was performed. Patients diagnosed from 1999-2016 were identified via query of a single-institution National Comprehensive Cancer Network (NCCN) breast cancer database as well as a prospective tumor board. ResultsA total of 91 patients were diagnosed with micrometastatic nodal disease. The median age at diagnosis was 56 y (range: 31-85); median follow-up time was 47 mo (range: 0-203 mo). 42/91(46.2%) patients had ALND of which 37/42 (88.1%) were a second operation; 3/42(7.1%) patients had additional positive nodes found at ALND. 44/91 (48.4%) patients received radiation. 7/91 (7.7%) patients had a recurrence, 5/7 local, including one axillary (2.1%; patient declined ALND). ConclusionsGiven that the risk of lymphedema after ALND ranges between 20%-53%, the morbidity of ALND may far exceed the likelihood of detecting further nodal involvement in women with micrometastatic disease: 7.1% in this series.