Breast Cancer Survival Research Articles

Characterization of KIF20B as a novel prognostic biomarker and therapeutic target for breast cancer.

Despite advances in treatment and early detection, breast cancer remains one of the most common types of cancer and is the second leading cause of cancer death after lung cancer in women. Therefore, there is an urgent need to develop new biomarkers and therapeutic targets for the treatment of breast cancer. Based on gene expression profiles and subsequent screening performed in a preliminary study, kinesin family member 20B (KIF20B) was selected as a candidate target molecule, because it was highly and frequently expressed in all subtypes of breast cancer and barely detected in normal tissues. Reverse transcription‑quantitative PCR and western blotting revealed that KIF20B mRNA and protein expression levels were upregulated in most breast cancer cell lines but were scarcely expressed in normal mammary epithelial cells. Immunohistochemical staining of a tissue microarray showed that KIF20B was detected in 145 out of 251 (57.8%) breast cancer tissues. Strong KIF20B expression was significantly related to advanced pathological N stage. Moreover, patients with breast cancer and strong KIF20B expression exhibited a significantly worse prognosis than those with weak or negative KIF20B expression (P<0.0001, log‑rank test). In multivariate analysis, strong expression was an independent prognostic factor for patients with breast cancer. Furthermore, knockdown of KIF20B expression by small interfering RNA inhibited breast cancer cell proliferation and induced apoptosis. In addition, Matrigel cell invasion assays revealed that the invasiveness of breast cancer cells was significantly decreased by KIF20B silencing. Since KIF20B is an oncoprotein that is strongly expressed in highly malignant clinical breast cancer and serves a pivotal role in breast cancer cell proliferation, survival and invasion, KIF20B could be considered a candidate biomarker for prognostic prediction and a potential molecular target for developing new therapeutics, such as small molecule inhibitors, for a wide variety of breast cancers.

Triple-negative breast cancer survival prediction using artificial intelligence through integrated analysis of tertiary lymphoid structures and tumor budding.

Triple-negative breast cancer (TNBC) is a highly heterogeneous and clinically aggressive disease. Accumulating evidence indicates that tertiary lymphoid structures (TLSs) and tumor budding (TB) are significantly correlated with the outcomes of patients who have TNBC, but no integrated TLS-TB profile has been established to predict their survival. The objective of this study was to investigate the relationship between the TLS/TB ratio and clinical outcomes of patients with TNBC using artificial intelligence (AI)-based analysis. The infiltration levels of TLSs and TB were evaluated using hematoxylin and eosin staining, immunohistochemistry staining, and AI-based analysis. Various cellular subtypes within TLS were determined by multiplex immunofluorescence. Subsequently, the authors established a nomogram model, conducted calibration curve analyses, and performed decision curve analyses using R software. In both the training and validation cohorts, the antitumor/protumor model established by the authors demonstrated a positive correlation between the TLS/TB index and the overall survival (OS) and relapse-free survival (RFS) of patients with TNBC. Notably, patients who had a high percentage of CD8-positive T cells, CD45RO-positive T cells, or CD20-positive B cells within the TLSs experienced improved OS and RFS. Furthermore, the authors developed a comprehensive TLS-TB profile nomogram based on the TLS/TB index. This novel model outperformed the classical tumor-lymph node-metastasis staging system in predicting the OS and RFS of patients with TNBC. A novel strategy for predicting the prognosis of patients with TNBC was established through integrated AI-based analysis and a machine-learning workflow. The TLS/TB index was identified as an independent prognostic factor for TNBC. This nomogram-based TLS-TB profile would help improve the accuracy of predicting the prognosis of patients who have TNBC.

Evaluating the impact of pre-diagnostic use of statins and testosterone replacement therapy on mortality outcomes in older men with hormone-related cancers: Surveillance, Epidemiology, and End Results-Medicare 2007-2015.

The link between the pre-diagnostic use of statins and testosterone replacement therapy and their impact on hormone-related cancers, prostate cancer, colorectal cancer, and male breast cancer survival remains a topic of controversy. Further, there is a knowledge gap concerning the joint effects of statins and testosterone replacement therapy on hormone-related cancer survival outcomes. To examine the independent and joint effects of pre-diagnostic use of statins and testosterone replacement therapy on the risk of all-cause and cause-specific mortality among older men diagnosed with hormone-related cancers, including prostate cancer, colorectal cancer, and male breast cancer. In 41,707 men (≥65 years) of Surveillance, Epidemiology, and End Results-Medicare 2007-2015, we identified 31,097 prostate cancer, 10,315 colorectal cancer, and 295 male breast cancer cases. Pre-diagnostic prescription of statins and testosterone replacement therapy was ascertained and categorized into four groups (Neither users, statins alone, testosterone replacement therapy alone, and Dual users). Multivariable-adjusted Cox proportional hazards and competing-risks (Fine-Gray subdistribution hazard) models were conducted. No significant associations were found in Cox-proportional hazard models for hormone-related cancers. However, in the Fine-Gray competing risk models among high-grade hormone-related cancers, statins alone had an 11% reduced risk of hormone-related cancer-specific death (hazard ratio: 0.89; 95% confidence interval: 0.81-0.99; p 0.0451). In the prostate cancer cohort with both statistical models, the use of testosterone replacement therapy alone had a 24% lower risk of all-cause death (hazard ratio: 0.76; 95% confidence interval: 0.59-0.97; p 0.0325) and a 57% lower risk of prostate cancer-specific death (hazard ratio: 0.43; 95% confidence interval: 0.24-0.75; p 0.0029). Similar inverse associations were found among aggressive prostate cancer cases with testosterone replacement therapy alone and statins alone. No significant associations were found in the colorectal cancer and male breast cancer sub-groups. Pre-diagnostic use of statins and testosterone replacement therapy showed a survival benefit with reduced mortality in high-grade hormone-related cancer patients (only statins) and aggressive prostate cancer patients in both statistical models. Findings of testosterone replacement therapy use in aggressive prostate cancer settings could facilitate clinical trials. Further studies with extended follow-up periods are needed to substantiate these findings.

Prognostic factors and survival of breast cancer in patients over 40 years of age

Aims: Breast cancer is the cancer with the highest incidence and mortality in women. There are differences in prognosis and survival between women over and under the age of 40. In this article, we aimed to examine breast cancer prognostic factors and survival results in people over the age of 40. Methods: 1187 patients aged 40 and over who underwent surgery at the Ondokuz Mayıs University Department of General Surgery between August 2005 and April 2019 and whose data were accessible were retrospectively examined. Data were obtained from the hospital automation system, the Ministry of Health’s online database, hospital archives, patients, and/or their relatives. They were classified separately in terms of type of surgery, axillary metastasis status (according to radiological status if axilla surgery is not performed), type of axilla surgery performed, pathological tumor size, number of pathological lymph nodes, pathological stage, lymphovascular and perineural invasion status, hormone receptor positivity, C-erb B2 and Ki-67 status, neoadjuvant treatment status, and molecular subgroup. Variables were analyzed individually for recurrence, mortality, and survival. Results found to be significant were subjected to multivariate analysis testing. Statistical significance was accepted as p&lt;0.05. Results: As a result of multivariate analysis performed by excluding data that disrupted homogeneous distribution, perineural invasion, lymphovascular invasion, grade, and progesterone receptor status were determined to be independent prognostic factors in terms of recurrence. Lymphovascular invasion and progesterone receptor status were found to be independent prognostic factors for mortality. Conclusion: A lot of studies have been conducted, and criteria have been determined for breast cancer prognosis and survival. In our results, lymphovascular invasion and progesterone receptor status were found to be independent prognostic markers for both recurrence and mortality. More reliable results can be obtained with prospective study analyses.

Cyclin-dependent kinase 4/6 inhibitors in the treatment of advanced or metastatic breast cancer.

Despite the relatively high cure rates in early-stage breast cancer, advanced and metastatic breast cancer cases are associated with more inauspicious patient outcomes. Fortunately, with the advent of cyclin-dependent kinase (CDK)4/6 inhibitors (e.g. palbociclib, ribociclib, and abemaciclib) with endocrine therapy, survival in advanced and metastatic breast cancer has appreciably improved. In the current review, we discuss these distinctions and the concomitant implications associated with the individual CDK4/6 inhibitors. We conducted an extensive PubMed search comprising several review articles on the topic of advanced or metastatic breast cancer treatment, with specific terms that included CDK4/6 inhibitors, treatment, and breast cancer. Palbociclib, ribociclib, and abemaciclib have exhibited superior progression-free survival differences compared to endocrine therapy alone. However, there are differences among the various CDK4/6 inhibitors with regard to overall survival, tolerability and quality of life. Ribociclib may be indicated for pre/perimenopausal patients, whereas abemaciclib is potentially recommended to address endocrine-resistant or visceral disease. Alternatively, palbociclib is associated with lower discontinuation rates than abemaciclib and unlike ribociclib, QTc prolongation is not observed with palbociclib.

A prognostic nomogram for predicting breast cancer survival based on mammography and AJCC staging

Rationale and objectivesTo develop a prognostic nomogram using mammography data and AJCC staging to predict breast cancer survival. Materials and methodsA prognostic nomogram was created using data from 1000 women diagnosed with breast cancer at a medical cancer center in Taiwan between 2011 and 2015. The variables included age at diagnosis (≤60 or > 60 years), mammography purpose (screening or diagnostic), mammography modality (digital mammogram or digital breast tomosynthesis), and the 7th American Joint Committee on Cancer (AJCC) stage. The outcome predicted was breast cancer-related mortality. The nomogram utilized Kaplan-Meier analysis for all subsets and Cox proportional hazards regression analysis for prediction. The nomogram's accuracy was internally validated using the concordance index and receiver operating characteristic (ROC) curve analysis, focusing on 3-year and 5-year survival predictions. ResultsParticipants' mean age at breast cancer diagnosis was 54 years (SD = 11.2 years). The 1-year, 3-year, and 5-year overall survival (OS) rates were found to be 99.7%, 95.3%, and 91.4%, respectively. The bootstrap-corrected concordance indices indicated the following: nomogram, 0.807 and AJCC, 0.759. A significant difference was observed between the nomogram's area under the curve (AUC) and the AJCC stage in predicting the probability of 5-year survival (p = 0.005). A nomogram, constructed based on mammography and AJCC, demonstrated excellent calibration through internal validation using bootstrapping. ConclusionThe utilization of a nomogram that incorporates mammography data and the AJCC registry data has been demonstrated to be a reliable predictor of breast cancer survival.

Five-year survival of triple-negative breast cancer and the associated clinicopathological factors: a study in an Indonesian tertiary hospital

BACKGROUND Triple-negative breast cancer (TNBC) has a worse rate of recurrence, survival, and overall survival. This study aimed to find the survival of TNBC and its clinicopathological factors at Cipto Mangunkusumo Hospital.&#x0D; METHODS This study used survival analysis based on clinicopathology in 112 TNBC cases at Cipto Mangunkusumo Hospital, Jakarta, Indonesia, diagnosed from 2009 to 2019. Kaplan–Meier and log-rank tests were used for the analysis. Bivariate and multivariate analyses using Cox regression were performed to obtain the hazard ratios (HRs).&#x0D; RESULTS Most patients were diagnosed at the locally advanced stage (40.2%) compared to the early (33.0%) and metastatic stages (17.9%). The 5-year survival of TNBC was 81.2% with an HR value of 1.372 (p = 0.239) compared to luminal A. Bivariate analyses showed that the older age group with an HR of 6.845 (p = 0.013; CI 1.500–31.243), larger tumor size and extension (T) with an HR of 11.826 (p = 0.001; CI 2.707–51.653), broader regional lymph node involvement (N) with an HR of 8.929 (p = 0.019; CI 1.434–55.587), farther distant metastases (M) with an HR of 3.016 (p = 0.015; CI 1.242–7.322), more lymphovascular invasion with HR of 3.006 (p = 0.018; CI 1.209–7.477), and not operated-on cases with an HR of 9.165 (p&lt;0.001; CI 3.303–25.434) significantly shortened the survival of TNBC. Multivariate analysis found that the only factor worsening the survival was not having surgery, with an HR of 6.175 (p&lt;0.001; CI 1.518–34.288).&#x0D; CONCLUSIONS The 5-year survival rate of TNBC patients was 81.2%. Not having surgery was a clinicopathological factor that worsened survival outcomes in TNBC.

Digital PCR quantification of ultrahigh ERBB2 copy number identifies poor breast cancer survival after trastuzumab

HER2/ERBB2 evaluation is necessary for treatment decision-making in breast cancer (BC), however current methods have limitations and considerable variability exists. DNA copy number (CN) evaluation by droplet digital PCR (ddPCR) has complementary advantages for HER2/ERBB2 diagnostics. In this study, we developed a single-reaction multiplex ddPCR assay for determination of ERBB2 CN in reference to two control regions, CEP17 and a copy-number-stable region of chr. 2p13.1, validated CN estimations to clinical in situ hybridization (ISH) HER2 status, and investigated the association of ERBB2 CN with clinical outcomes. 909 primary BC tissues were evaluated and the area under the curve for concordance to HER2 status was 0.93 and 0.96 for ERBB2 CN using either CEP17 or 2p13.1 as reference, respectively. The accuracy of ddPCR ERBB2 CN was 93.7% and 94.1% in the training and validation groups, respectively. Positive and negative predictive value for the classic HER2 amplification and non-amplification groups was 97.2% and 94.8%, respectively. An identified biological “ultrahigh” ERBB2 ddPCR CN group had significantly worse survival within patients treated with adjuvant trastuzumab for both recurrence-free survival (hazard ratio, HR: 3.3; 95% CI 1.1–9.6; p = 0.031, multivariable Cox regression) and overall survival (HR: 3.6; 95% CI 1.1–12.6; p = 0.041). For validation using RNA-seq data as a surrogate, in a population-based SCAN-B cohort (NCT02306096) of 682 consecutive patients receiving adjuvant trastuzumab, the ultrahigh-ERBB2 mRNA group had significantly worse survival. Multiplex ddPCR is useful for ERBB2 CN estimation and ultrahigh ERBB2 may be a predictive factor for decreased long-term survival after trastuzumab treatment.

Unmet Social Needs and Breast Cancer Screening Utilization and Stage at Presentation

Unmet social needs in local populations may hinder the development of targeted cancer control interventions aimed at improving screening utilization and early-stage breast cancer diagnosis to ultimately improve breast cancer survival disparities. To evaluate if (1) city-funded screening mammography is associated with utilization of screening mammography, (2) unmet social needs are associated with utilization of screening mammography, and (3) unmet social needs are associated with later-stage disease at diagnosis. This cohort study included patients with stages I-IV invasive ductal or lobular carcinoma treated at an academic medical center (including both an underserved safety-net hospital [SNH] and a National Cancer Institute-designated academic cancer center [ACC]) from 2020 to 2023. Eligible patients were aged 18 years or older and able to consent. Data were analyzed between July 2023 and September 2023. The Health Leads Social Needs Screening Toolkit, a screening tool that gathers information on the most common social need domains affecting patient health. Univariable and multivariable logistic regression was utilized to evaluate the following primary outcomes: (1) routine screening mammography and (2) American Joint Committee on Cancer 8th edition clinical stage at presentation. Of the 322 women who completed the Health Leads Social Needs Screening Toolkit, 201 (62%) self-identified as Hispanic, 63 (19%) as non-Hispanic Black, and 63 (19%) as non-Hispanic White. Two hundred fifty-five (76%) patients with access to city-funded screening mammography completed a screening mammogram. Patients who presented to the SNH were more likely to present with late-stage disease compared with early-stage disease (15 of 48 [31%] vs 50 of 274 [18%]; P = .04). On multivariable logistic regression, not completing a screening mammography was associated with having an increasing number of unmet social needs (OR, 0.74; 95% CI, 0.55-0.99; P = .047) and an increasing age at diagnosis (OR, 0.92; 95% CI, 0.89-0.96; P < .001). Moreover, increasing unmet social needs was significantly associated with late-stage diagnosis above and beyond screening mammography (OR, 1.38; 95% CI, 1.01-1.89; P = .04). In this cohort study, access to screening mammography did not translate to utilization of screening mammography, increasing unmet social needs were significantly associated with lower rates of screening mammography, and those with increasing unmet social needs were more likely to present with late-stage disease. This association transcended recruitment site (SNH vs ACC), indicating that patients in either hospital setting may benefit from unmet social needs screening to overcome access to care barriers associated with late-stage disease at diagnosis.

Disparities in Breast Cancer Care-How Factors Related to Prevention, Diagnosis, and Treatment Drive Inequity.

Breast cancer survival has increased significantly over the last few decades due to more effective strategies for prevention and risk modification, advancements in imaging detection, screening, and multimodal treatment algorithms. However, many have observed disparities in benefits derived from such improvements across populations and demographic groups. This review summarizes published works that contextualize modern disparities in breast cancer prevention, diagnosis, and treatment and presents potential strategies for reducing disparities. We conducted searches for studies that directly investigated and/or reported disparities in breast cancer prevention, detection, or treatment. Demographic factors, social determinants of health, and inequitable healthcare delivery may impede the ability of individuals and communities to employ risk-mitigating behaviors and prevention strategies. The disparate access to quality screening and timely diagnosis experienced by various groups poses significant hurdles to optimal care and survival. Finally, barriers to access and inequitable healthcare delivery patterns reinforce inequitable application of standards of care. Cumulatively, these disparities underlie notable differences in the incidence, severity, and survival of breast cancers. Efforts toward mitigation will require collaborative approaches and partnerships between communities, governments, and healthcare organizations, which must be considered equal stakeholders in the fight for equity in breast cancer care and outcomes.

Effects of hormone receptor status on patient clinic and survival in HER2 positive breast cancer

Abstract Background In the current study, the effect of hormone receptor (HR) status on clinical and survival in early-stage human epidermal growth factor receptor 2 (HER2)-positive breast cancer was investigated. Methods Two hundred ninety-one patients with HER2- positive were examined in two categories as HR-positive and HR-negative. Results Of these, 197 (68%) were HR-positive and 94 (32%) were HR-negative with a mean follow-up period of 68 ± 2.7 months. The groups were found to be similar in terms of age, menopausal status, comorbidity, pathologic type, stage, T stage, N stage, lymphovascular invasion, presence and percentage of intraductal component, multicentricity/focality and extracapsular invasion. Family history (P = 0.038), stage 2 tumor rate (P &amp;lt; 0.001), and perineural invasion (P = 0.005) were significantly higher in the HR-positive group. In the HR-negative group, mean Ki-67 value (P = 0.014), stage 3 tumor rate (P &amp;lt; 0.001), tumor necrosis (P = 0.004) and strong (3+) HER2 staining on immunohistochemical staining (P = 0.003) were higher. The incidence of relapse and metastasis, and the localization of metastasis were similar in both patient groups. The rate of locoregional relapse during the first 2 years was higher in the HR-negative patients than in the HR-positive patients (P = 0.023). Overall survival (OS) and disease-free survival (DFS) did not differ between the groups in univariate analysis. However, HR status was determined as an independent prognostic factor (HR: 2.11, 95% CI: 1.17–3.79; P = 0.012) for OS was not found to be significant for DFS in multivariate analysis. Conclusion Both clinicopathologic features and OS outcomes of HR-negative patients were worse than those of HR-positive patients.

Anti-HER2 therapy response assessment for guiding treatment (de-)escalation in early HER2-positive breast cancer using a novel deep learning radiomics model.

Anti-HER2 targeted therapy significantly reduces risk of relapse in HER2 + breast cancer. New measures are needed for a precise risk stratification to guide (de-)escalation of anti-HER2 strategy. A total of 726 HER2 + cases who received no/single/dual anti-HER2 targeted therapies were split into three respective cohorts. A deep learning model (DeepTEPP) based on preoperative breast magnetic resonance (MR) was developed. Patients were scored and categorized into low-, moderate-, and high-risk groups. Recurrence-free survival (RFS) was compared in patients with different risk groups according to the anti-HER2 treatment they received, to validate the value of DeepTEPP in predicting treatment efficacy and guiding anti-HER2 strategy. DeepTEPP was capable of risk stratification and guiding anti-HER2 treatment strategy: DeepTEPP-Low patients (60.5%) did not derive significant RFS benefit from trastuzumab (p = 0.144), proposing an anti-HER2 de-escalation. DeepTEPP-Moderate patients (19.8%) significantly benefited from trastuzumab (p = 0.048), but did not obtain additional improvements from pertuzumab (p = 0.125). DeepTEPP-High patients (19.7%) significantly benefited from dual HER2 blockade (p = 0.045), suggesting an anti-HER2 escalation. DeepTEPP represents a pioneering MR-based deep learning model that enables the non-invasive prediction of adjuvant anti-HER2 effectiveness, thereby providing valuable guidance for anti-HER2 (de-)escalation strategies. DeepTEPP provides an important reference for choosing the appropriate individualized treatment in HER2 + breast cancer patients, warranting prospective validation. We built an MR-based deep learning model DeepTEPP, which enables the non-invasive prediction of adjuvant anti-HER2 effectiveness, thus guiding anti-HER2 (de-)escalation strategies in early HER2-positive breast cancer patients. • DeepTEPP is able to predict anti-HER2 effectiveness and to guide treatment (de-)escalation. • DeepTEPP demonstrated an impressive prognostic efficacy for recurrence-free survival and overall survival. • To our knowledge, this is one of the very few, also the largest study to test the efficacy of a deep learning model extracted from breast MR images on HER2-positive breast cancer survival and anti-HER2 therapy effectiveness prediction.

Downregulation of long noncoding RNA B4GALT1-AS1 is associated with breast cancer development

The misregulation of long non-coding RNAs (lncRNAs) is related to the progressive evolution of various human cancers, such as Breast cancer (BC). The role of lncRNA B4GALT1-AS1 has been investigated in some human cancers. Therefore, studying B4GALT1-AS1 expression was aimed for the first time in the tumor and marginal tissues of BC in this study. The cancer genome atlas (TCGA) database was utilized to evaluate the relative expression of B4GALT1-AS1 in BC and other cancers. RNA was extracted from twenty-eight paired BC and marginal tissues, and cDNA was synthesized. The quantitative expression level of B4GALT1-AS1 was evaluated using real-time PCR. The bioinformatics analyses were performed to identify co-expression genes and related pathways. B4GALT1-AS1 was significantly downregulated in BC specimens compared to tumor marginal samples. The TCGA data analysis confirmed the downregulation of B4GALT1-AS1 in BC. The bioinformatics analysis discovered the correlation between 700 genes and B4GALT1-AS1 and identified GNAI1 as the high degree gene which was positively correlated with B4GALT1-AS1 expression. It seems B4GALT1-AS1 provides its function, at least partly, in association with one of the hippo pathway components, YAP, in other cancers. This protein has the opposite role in BC and its loss of function can result in poor survival in BC. Further research is needed to investigate the interaction between B4GALT1‐AS1 and YAP in various subtypes of BC.

Bayesian mediation analysis for time-to-event outcome: Investigating racial disparity in breast cancer survival

Mediation analysis is conducted to make inferences on the effects of mediators that intervene in the relationship between an exposure variable and an outcome. Bayesian mediation analysis (BMA) naturally considers the hierarchical structure of the effects from the exposure variable to mediators and then to the outcome. We propose three BMA methods on survival outcomes, where mediation effects are measured in terms of hazard rate, survival time, or log of survival time respectively. In addition, we allow setting a limited survival time in the time-to-event analysis. The methods are validated by comparing the estimation precision at different scenarios through simulations. The three methods all give effective estimates. Finally, the methods are applied to the Surveillance, Epidemiology, and End Results Program (SEER) supported special studies to explore the racial disparity in breast cancer survival. The included variable completely explained the observed racial disparities. We provide visual aids to help with the result interpretations.

Development and Psychometric Validation of the Breast Cancer Stigma Assessment Scale for Women with Breast Cancer and Its Survivors.

The increase in breast cancer cases and breast cancer survival makes it advisable to quantify the impact of the health-related stigma of this disease. To develop and validate a breast cancer stigma scale in Spanish. Women diagnosed with, or survivors of, breast cancer were included. The development of the Breast Cancer Stigma Assessment Scale (BCSAS) involved both a literature review and personal interviews. Content validity was assessed using a Delphi study and a pilot test; construct validity was evaluated using an exploratory factor analysis; and convergent validity was assessed using six scales. Cronbach's α internal consistency and test-retest reliability were used to determine the reliability of the scales. 231 women responded to the 28-item scale. The BCSAS showed good reliability, with α = 0.897. Seven factors emerged: concealment (α = 0.765), disturbance (α = 0.772), internalized stigma (α = 0.750), aesthetics (α = 0.779), course (α = 0.599), danger (α = 0.502), and origin (α = 0.350). The test-retest reliability was 0.830 (p < 0.001). Significant correlation was observed with event centrality (r = 0.701), anxiety-depression (r = 0.668), shame (r = 0.645), guilt (r = 0.524), and quality of life (r = -0.545). The BCSAS is a reliable and valid measure of stigma in women with breast cancer and its survivors. It could be useful for detecting stigma risk and establishing psychotherapeutic and care priorities.

The androgen receptor interacts with GATA3 to transcriptionally regulate a luminal epithelial cell phenotype in breast cancer

BackgroundThe androgen receptor (AR) is a tumor suppressor in estrogen receptor (ER) positive breast cancer, a role sustained in some ER negative breast cancers. Key factors dictating AR genomic activity in a breast context are largely unknown. Herein, we employ an unbiased chromatin immunoprecipitation-based proteomic technique to identify endogenous AR interacting co-regulatory proteins in ER positive and negative models of breast cancer to gain new insight into mechanisms of AR signaling in this disease.ResultsThe DNA-binding factor GATA3 is identified and validated as a novel AR interacting protein in breast cancer cells irrespective of ER status. AR activation by the natural ligand 5α-dihydrotestosterone (DHT) increases nuclear AR-GATA3 interactions, resulting in AR-dependent enrichment of GATA3 chromatin binding at a sub-set of genomic loci. Silencing GATA3 reduces but does not prevent AR DNA binding and transactivation of genes associated with AR/GATA3 co-occupied loci, indicating a co-regulatory role for GATA3 in AR signaling. DHT-induced AR/GATA3 binding coincides with upregulation of luminal differentiation genes, including EHF and KDM4B, established master regulators of a breast epithelial cell lineage. These findings are validated in a patient-derived xenograft model of breast cancer. Interaction between AR and GATA3 is also associated with AR-mediated growth inhibition in ER positive and ER negative breast cancer.ConclusionsAR and GATA3 interact to transcriptionally regulate luminal epithelial cell differentiation in breast cancer regardless of ER status. This interaction facilitates the tumor suppressor function of AR and mechanistically explains why AR expression is associated with less proliferative, more differentiated breast tumors and better overall survival in breast cancer.

Breast (female), colorectal, and lung cancer survival in people with intellectual or developmental disabilities: A population-based retrospective cohort study.

Cancer is a leading cause of death among people living with intellectual or developmental disabilities (IDD). There is little empirical evidence documenting survival or comparing outcomes to those without IDD. This study investigated the association between IDD and cancer survival among adults with breast(female), colorectal, or lung cancer. A population-based retrospective cohort study was conducted in Ontario, Canada, with routinely collected data. Patients with breast, colorectal, or lung cancer were included (2007‒2019). IDD status before cancer was determined using an established administrative data algorithm. The outcomes of interest included death from any cause and death from cancer. Cox proportional hazards models and competing events analyses using multivariable cause-specific hazards regression were completed. Analyses were stratified by cancer type. Interactions with age, sex, and stage at diagnosis, as well as sensitivity analyses, were completed. The final cohorts included 123,695 breast, 98,809 colorectal, and 116,232 lung cancer patients. Individuals with IDD experienced significantly worse survival than those without IDD. The adjusted hazard ratios of all-cause death were 2.74 (95% CI 2.41‒3.12), 2.42 (95% CI 2.18‒2.68), and 1.49 (95% CI 1.34‒1.66) times higher for breast, colorectal, and lung cancer patients with IDD relative to those without. These findings were consistent for cancer-specific deaths. With few exceptions, worse survival for people with IDD persisted regardless of stage at diagnosis. People with IDD experienced worse cancer survival than those without IDD. Identifying and intervening on the factors and structures responsible for survival disparities is imperative.

YTHDF1's Regulatory Involvement in Breast Cancer Prognosis, Immunity, and the ceRNA Network.

YTH N6-methyladenosine RNA binding protein 1 (YTHDF1), an m6A reader, has a role in the development and progression of breast cancer as well as the immunological microenvironment. The networks of competing endogenous RNA in cancer have received much attention in research. In tumor gene therapy, the regulatory networks of m6A and competing endogenous RNA are increasingly emerging as a new route. We evaluated the relationship between the YTHDF1 expression, overall survival, and clinicopathology of breast cancer using TCGA, PrognoScan, and other datasets. We used Western blot to demonstrate that YTHDF1 is substantially expressed in breast cancer tissues. Furthermore, we explored YTHDF1's functions in the tumor mutational burden, microsatellite instability, and tumor microenvironment. Our findings indicate that YTHDF1 is a critical component of the m6A regulatory proteins in breast cancer and may have a particular function in the immunological microenvironment. Crucially, we investigated the relationship between YTHDF1 and the associated competitive endogenous RNA regulatory networks, innovatively creating three such networks (Dehydrogenase/Reductase 4-Antisense RNA 1-miR-378g-YTHDF1, HLA Complex Group 9-miR-378g-YTHDF1, Taurine Up-regulated 1-miR-378g-YTHDF1). Furthermore, we showed that miR-378g could inhibit the expression of YTHDF1, and that miR-378g/YTHDF1 could impact MDA-MB-231 proliferation. We speculate that YTHDF1 may serve as a biomarker for poor prognosis and differential diagnosis, impact the growth of breast cancer cells via the ceRNA network axis, and be a target for immunotherapy against breast cancer.

Expression and clinical significance of hypoxia-induced long non-coding RNA TCONS_I2_00001955 in breast cancer.

Long non-coding RNAs (lncRNAs) have been found to play important roles in occurrence, development, and metastasis of various tumors. We aimed to screen long non-coding RNAs (lncRNAs) that promote invasion and metastasis of breast cancer cells under hypoxia, and investigate the relationship between lncRNA expression and clinicopathological features and prognosis in invasive breast cancer. LncRNA microarray was used to screen the differentially expressed lncRNAs in MCF7, MDA-MB-231, and SKBR3 breast cancer cell lines cultured under normoxia and hypoxia, respectively. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was used to verify the microarray results. CCK8 and Transwell experiments were performed to identify the lncRNA that promote proliferation, migration, and invasion of breast cancer cells. Expression of the lncRNA and HIF-1α in invasive breast cancer was detected by RNAscope and immunohistochemistry, respectively. Correlation between the lncRNA expression and baseline characteristics was analyzed. Prognostic value of the lncRNA was evaluated using univariate and multivariate Cox regression. Expression of lncRNA TCONS_I2_00001955 in all the three breast cancer cells was increased under hypoxia. Overexpression of TCONS_I2_00001955 significantly enhanced proliferation, migration, and invasion of SKBR3 cells. Positive expression of TCONS_I2_00001955 was associated with recurrence, metastasis, and high expression of HIF-1α (P < 0.05), and it was an independent risk factor for poor disease-free survival of breast cancer. Hypoxia-induced lncRNA TCONS_I2_00001955 was associated with aggressive feature and poor prognosis of breast cancer.

Racial disparities in breast cancer survival after treatment initiation in Brazil: a nationwide cohort study

Breast cancer is a public health priority in Brazil and ensuring equity in health care is one of the cancer control plan goals. Our aim was to present the first assessment on the influence of race or skin colour on breast cancer survival at the national level. In this nationwide cohort study, data on women who initiated treatment for breast cancer in the public health-care system (Sistema Unico de Saúde), Brazil, were assembled through record linkage of administrative and mortality information systems. The administrative information systems were the Outpatient Information System (data from high complexity procedure authorisations) and the Hospital Information System (data from hospitalisation authorisations). We included women aged 19 years or older who started treatment between Jan 1, 2008, and Nov 30, 2010; self-identified as having White, Black, or Brown race or skin colour; had tumour stage I-IV; and were treated with chemotherapy or radiotherapy, or both. Patients were followed up until Dec 31, 2015. Patients with only hormone therapy records or who underwent only surgery were excluded. The Kaplan-Meier method was used to estimate crude overall survival for race or skin colour by time since treatment initiation, and Cox regression to estimate all-cause mortality hazard ratios (HRs) before and after adjustment for other covariates. We identified 59 811 women treated for stage I-IV breast cancer. 37 318 (62·4%) women identified themselves as White, 18 779 (31·4%) as Brown, and 3714 (6·2%) as Black. 5-year overall survival probability was higher for White women (74% [95% CI 73-74]) than Black women (64% [62-65]; p<0·0001). In adjusted regression models stratified by the absence of hormone therapy, Black women had a 24% (HR 1·24 [95% CI 1·16-1·34]; p<0·0001) higher risk of all-cause death than White women, and in the presence of hormone therapy Black women had a 25% (1·25 [1·14-1·38]; p<0·0001) higher risk of all-cause death than White women. Black skin colour was identified as a statistically significant risk marker for lower 5-year survival probability and higher risk of all-cause death among women treated for breast cancer by the Sistema Unico de Saúde. Actions to understand and mitigate this unfair difference in health results are urgently needed. Conselho Nacional de Desenvolvimento Científico e Tecnológico and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior and Pró-Reitoria de Pesquisa da Universidade Federal de Minas Gerais.