Breast Cancer Outcomes Research Articles

Subcellular expression of MTA1, HIF1A and p53 in primary tumor predicts aggressive triple negative breast cancers: a meta-analysis based study.

The prevalence of TNBC in India is higher compared to western countries. There is a multitude of biomarkers associated with different clinical outcomes of TNBC with contradictory reports. Identification of a set of specific biomarkers from the very many number of proteins reported in the literature to predict prognosis of TNBC is an urgent clinical need. A systematic review of key molecular biomarkers in cohort studies that have been investigated for their role in breast cancer prognosis was conducted. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology was followed. A meta-analysis was used to evaluate their pooled hazard ratio (HR) and the corresponding 95% confidence interval (95% CI) statistically. Immunohistochemical characterization of the meta-analyzed markers were performed in a cohort of 200 retrospective TNBC and 100 non TNBC patient tissues. Kaplan-Meier plot were used to evaluate disease free survival (DFS), and overall survival (OS). Cox regression models were used to evaluate predictors of DFS and OS. Using a meta-analytical approach, we consolidated the biomarker signatures associated with survival outcomes in breast cancers. The promising markers that emerged for the prediction of DFS and OS included E-Cadherin, Survivin, p53, MTA1, HIF1A, CD133, Vimentin and CK5/6. Evaluation of these markers in tumor tissue revealed that subcellular localization of p53, MTA1 and HIF1A had a significant association in predicting TNBC prognosis. Kaplan Meier plot revealed that p53 (OS p = 0.007, DFS p = 0.004), HIF 1A (OS p = 0.054, DFS p = 0.009) and MTA1 (OS p = 0.043, DFS = p = 0.001) expression in the primary tumor tissue were found to be significantly correlated with poor OS and DFS, whereas expression of Survivin (DFS p = 0.024) and E Cadherin (DFS p = 0.027) correlated with DFS alone in TNBC. Univariate analysis revealed that p53, HIF1A and MTA1 could be independent prognostic markers. Our study suggests cytoplasmic over expression of HIF1A, nuclear over expression of MTA1 and mutated p53 in the primary tumor tissue of TNBC have significance as markers predicting survival of TNBC patients.

Implementation and Evaluation of a Breast Cancer Disease Model Using Real-World Claims Data in Germany from 2010 to 2020

Breast cancer is the leading cause of cancer-related mortality among women in Germany and worldwide. This retrospective claims data analysis utilizing data from AOK Baden-Wuerttemberg, a major statutory German health insurance provider, aimed to construct and assess a real-world data breast cancer disease model. The study included 27,869 female breast cancer patients and 55,738 age-matched controls, analyzing data from 2010 to 2020. Three distinct breast cancer stages were analyzed: Stage A (early breast cancer without lymph node involvement), Stage B (early breast cancer with lymph node involvement), and Stage C (primary distant metastatic breast cancer). Tumor subtypes were estimated based on the prescription of antihormonal or HER2-targeted therapy. The study established that 77.9% of patients had HR+ breast cancer and 9.8% HER2+; HR+/HER2− was the most common subtype (70.9%). Overall survival (OS) analysis demonstrated significantly lower survival rates for stages B and C than for controls, with 5-year OS rates ranging from 79.3% for stage B to 35.4% for stage C. OS rates were further stratified by tumor subtype and stage, revealing varying prognoses. Distant recurrence-free survival (DRFS) analysis showed higher recurrence rates in stage B than in stage A, with HR−/HER2− displaying the worst DRFS. This study, the first to model breast cancer subtypes, stages, and outcomes using German claims data, provides valuable insights into real-world breast cancer epidemiology and demonstrates that this breast cancer disease model has the potential to be representative of treatment outcomes.

Social capital in the management of breast cancer in Lagos, Nigeria.

Breast cancer is the most common cancer in women worldwide, necessitating substantial social support during diagnosis and treatment. This study examines the role of social capital in breast cancer management, focusing on the experiences of patients. The objective of the study was to explore the role of social capital in breast cancer management among women living with breast cancer in Lagos, Nigeria. Using a qualitative design, the study recruited 23 women with breast cancer receiving treatment at a teaching hospital in Lagos, Nigeria. Data were content analyzed to identify themes related to social capital. The study found that social capital, crucial for breast cancer patients' emotional and instrumental support, stems from various sources such as relatives, immediate family, spouses, places of worship, friends, and neighbors. Effective coping and management of the condition were facilitated through this support network. However, assistance from places of worship, friends, and neighbors was only accessible to those who openly acknowledged their health conditions and had established connections with these social groups. Relationships led to support only when there was a disclosure of the health condition. (1) This finding reinforces the importance of integrating social support mechanisms including family, friends, and community networks into breast cancer management programs. (2) The study identifies diverse sources of social capital, including relatives, family, spouses, places of worship, friends, and neighbors, stressing the need for tailored support networks. (3) Research reveals the link between health condition disclosure and support accessibility from groups like places of worship and friends, and it emphasizes creating stigma-free environments for patients to disclose health status comfortably. (4) The study highlights family involvement in breast cancer management as crucial for effective coping. Healthcare professionals should prioritize interventions strengthening family support systems. (5) Findings of stress community support for better breast cancer outcomes, advocating for initiatives like support groups and awareness campaigns to boost social capital and aid affected individuals. The study emphasizes the significance of involving family members in the breast cancer management process and highlights the need for support systems within families and communities to facilitate better outcomes for breast cancer patients.

Distinct ER and PR expression patterns significantly affect the clinical outcomes of early HER2-positive breast cancer: A real-world analysis of 871 patients treated with neoadjuvant therapy

IntroductionThe impact of distinct estrogen receptor (ER) and progesterone receptor (PR) expression patterns on tumor behavior and treatment outcomes within HER2-positive breast cancer is not fully explored. This study aimed to comprehensively examine the clinical differences among patients with HER2-positive breast cancer harboring distinct ER and PR expression patterns in the neoadjuvant setting. MethodsThis retrospective analysis included 871 HER2-positive breast patients treated with neoadjuvant therapy at our hospital between 2011 and 2022. Comparisons were performed across the three hormone receptor (HR)-specific subtypes, namely the ER-negative/PR-negative/HER2-positive (ER-/PR-/HER2+), the single HR-positive (HR+)/HER2+, and the triple-positive breast cancer (TPBC) subtypes. ResultsOf 871 patients, 21.0% had ER-/PR-/HER2+ tumors, 33.6% had single HR+/HER2+ disease, and 45.4% had TPBC. Individuals with single HR+/HER2+ tumors and TPBC cases demonstrated significantly lower pathological complete response (pCR) rates compared to those with ER-/PR-/HER2+ tumors (36.9% vs. 24.3% vs. 49.2%, p < 0.001). Multivariate analysis confirmed TPBC as significantly associated with decreased pCR likelihood (OR = 0.42, 95%CI 0.28–0.63, p < 0.001). Survival outcomes, including disease-free survival (DFS) and overall survival (OS), showed no significant differences across HR-specific subtypes in the overall patient population. However, within patients without anti-HER2 therapy, TPBC was linked to improved DFS and a trend towards better OS. ConclusionsHER2-positive breast cancer exhibited three distinct HR-specific subtypes with varying clinical manifestations and treatment responses. These findings suggest personalized treatment strategies considering ER and PR expression patterns, emphasizing the need for further investigations to unravel molecular traits underlying HER2-positive breast cancer with distinct HR expression patterns.

Pathway-based signatures predict patient outcome, chemotherapy benefit and synthetic lethal dependencies in invasive lobular breast cancer.

Invasive Lobular Carcinoma (ILC) is a morphologically distinct breast cancer subtype that represents up to 15% of all breast cancers. Compared to Invasive Breast Carcinoma of No Special Type (IBC-NST), ILCs exhibit poorer long-term outcome and a unique pattern of metastasis. Despite these differences, the systematic discovery of robust prognostic biomarkers and therapeutically actionable molecular pathways in ILC remains limited. Pathway-centric multivariable models using statistical machine learning were developed and tested in seven retrospective clinico-genomic cohorts (n = 996). Further external validation was performed using a new RNA-Seq clinical cohort of aggressive ILCs (n = 48). mRNA dysregulation scores of 25 pathways were strongly prognostic in ILC (FDR-adjusted P < 0.05). Of these, three pathways including Cell-cell communication, Innate immune system and Smooth muscle contraction were also independent predictors of chemotherapy response. To aggregate these findings, a multivariable machine learning predictor called PSILC was developed and successfully validated for predicting overall and metastasis-free survival in ILC. Integration of PSILC with CRISPR-Cas9 screening data from breast cancer cell lines revealed 16 candidate therapeutic targets that were synthetic lethal with high-risk ILCs. This study provides interpretable prognostic and predictive biomarkers of ILC which could serve as the starting points for targeted drug discovery for this disease.

Breast cancer (BC) and severe COVID-19 (C-19) outcomes: a matched analysis.

Patients with cancer receiving anticancer treatment have a higher risk of severe COVID-19 (C-19) outcomes. We examine the association between breast cancer (BC), recent treatment (systemic therapy, surgery, radiation), and C-19 outcomes. Retrospective matched cohort study using the Optum® de-identified C-19 Electronic Health Record dataset (2007-2022). Patients with C-19 were categorized into: no cancer, BC with recent treatment, and BC without recent treatment and matched based on age, C-19 diagnosis date, and comorbidity score. We evaluated 30-day mortality, mechanical ventilation, intensive care unit (ICU) stay, and hospitalization. A composite outcome including all outcomes was analyzed. Multivariable logistic regression models were used. 2200 matched triplets (1:1:10) of patients with BC recently treated, BC not recently treated, and no cancer were included. Rates of adverse outcomes improved in 2021 compared to 2020. Compared to patients without cancer, those with BC recently treated had a similar risk of adverse outcomes, while patients with BC not recently treated had a lower risk of ICU stay and hospitalization. Using the composite variable, BC recently treated had similar outcomes (OR = 1.02; 95%CI 0.93-1.11) to patients without cancer, while BC patients not recently treated had better outcomes (OR = 0.66; 95%CI 0.59-0.74). Among patients with BC, chemotherapy within 3months was associated with a higher risk of hospitalization (OR = 2.30; 95%CI 1.76-2.99) and composite outcome (OR = 2.11; 95%CI 1.64-2.72). Patients with BC have a similar risk of adverse C-19 outcomes compared to patients without cancer. Among patients with BC, recent chemotherapy was associated with a higher risk of hospitalization.

Exploring the effectiveness of molecular subtypes, biomarkers, and genetic variations as first-line treatment predictors in Asian breast cancer patients: a systematic review and meta-analysis

BackgroundBreast cancer incidence has been on the rise significantly in the Asian population, occurring at an earlier age and a later stage. The potential predictive value of molecular subtypes, biomarkers, and genetic variations has not been deeply explored in the Asian population. This study evaluated the effect of molecular subtype classification and the presence or absence of biomarkers and genetic variations on pathological complete response (pCR) after neoadjuvant treatment in Asian breast cancer patients.MethodsA systematic search was conducted in MEDLINE (PubMed), Science Direct, Scopus, and Cochrane Library databases. Studies were selected if they included Asian breast cancer patients treated with neoadjuvant chemotherapy and contained data for qualitative or quantitative analyses. The quality of the included studies was assessed using the Newcastle Ottawa Scale. Following the random effects model, pooled odds ratios or hazard ratios with 95% confidence intervals for pCR were analysed using Review Manager Software. Heterogeneity between studies was assessed using Cochran’s Q-test and I2 test statistics.ResultsIn total, 19,708 Asian breast cancer patients were pooled from 101 studies. In the neoadjuvant setting, taxane-anthracycline (TA) chemotherapy showed better pCR outcomes in triple-negative breast cancer (TNBC) (p<0.0001) and human epidermal growth factor receptor 2 enriched (HER2E) (p<0.0001) than luminal breast cancer patients. Similarly, taxane-platinum (TP) chemotherapy also showed better pCR outcomes in TNBC (p<0.0001) and HER2E (p<0.0001). Oestrogen receptor (ER)-negative, progesterone receptor (PR)-negative, HER2-positive and high Ki-67 were significantly associated with better pCR outcomes when treated with either TA or TP. Asian breast cancer patients harbouring wildtype PIK3CA were significantly associated with better pCR outcomes when treated with TA in the neoadjuvant setting (p=0.001).ConclusionsIn the neoadjuvant setting, molecular subtypes (HER2E and TNBC), biomarkers (ER, PR, HER2, HR, Ki-67, nm23-H1, CK5/6, and Tau), and gene (PIK3CA) are associated with increased pCR rates in Asian breast cancer patients. Hence, they could be further explored for their possible role in first-line treatment response, which can be utilised to treat breast cancer more efficiently in the Asian population. However, it needs to be further validated with additional powered studies.Systematic review registrationPROSPERO CRD42021246295.

Socioecologic Factors and Racial Differences in Breast Cancer Multigene Prognostic Scores in US Women

Disproportionately aggressive tumor biology among non-Hispanic Black women with early-stage, estrogen receptor (ER)-positive breast cancer contributes to racial disparities in breast cancer mortality. It is unclear whether socioecologic factors underlie racial differences in breast tumor biology. To examine individual-level (insurance status) and contextual (area-level socioeconomic position and rural or urban residence) factors as possible mediators of racial and ethnic differences in the prevalence of ER-positive breast tumors with aggressive biology, as indicated by a high-risk gene expression profile. This retrospective cohort study included women 18 years or older diagnosed with stage I to II, ER-positive breast cancer between January 1, 2007, and December 31, 2015. All data analyses were conducted between December 2022 and April 2023. The primary outcome was the likelihood of a high-risk recurrence score (RS) (≥26) on the Oncotype DX 21-gene breast tumor prognostic genomic biomarker. Among 69 139 women (mean [SD] age, 57.7 [10.5] years; 6310 Hispanic [9.1%], 274 non-Hispanic American Indian and Alaskan Native [0.4%], 6017 non-Hispanic Asian and Pacific Islander [8.7%], 5380 non-Hispanic Black [7.8%], and 51 158 non-Hispanic White [74.0%]) included in our analysis, non-Hispanic Black (odds ratio [OR], 1.33; 95% CI, 1.23-1.43) and non-Hispanic American Indian and Alaska Native women (OR, 1.38; 95% CI, 1.01-1.86) had greater likelihood of a high-risk RS compared with non-Hispanic White women. There were no significant differences among other racial and ethnic groups. Compared with non-Hispanic White patients, there were greater odds of a high-risk RS for non-Hispanic Black women residing in urban areas (OR, 1.35; 95% CI, 1.24-1.46), but not among rural residents (OR, 1.05; 95% CI, 0.77-1.41). Mediation analysis demonstrated that lack of insurance, county-level disadvantage, and urban vs rural residence partially explained the greater odds of a high-risk RS among non-Hispanic Black women (proportion mediated, 17%; P < .001). The findings of this cohort study suggest that the consequences of structural racism extend beyond inequities in health care to drive disparities in breast cancer outcome. Additional research is needed with more comprehensive social and environmental measures to better understand the influence of social determinants on aggressive ER-positive tumor biology among racial and ethnic minoritized women from disadvantaged and historically marginalized communities.

Tumor-infiltrating lymphocytes refine outcomes in triple-negative breast cancer treated with anthracycline-free neoadjuvant chemotherapy.

Stromal tumor-infiltrating lymphocytes (sTILs) are associated with pathologic complete response (pCR) and long-term outcomes for triple-negative breast cancer (TNBC) in setting of anthracycline-based chemotherapy. Impact of sTILs on refining outcomes beyond prognostic information provided by pCR in anthracycline-free neoadjuvant chemotherapy (NAC) is not known. This is pooled analysis of two studies where patients with stage I(T>1cm)-III TNBC received carboplatin(AUC 6) plus docetaxel(75mg/m2) (CbD) NAC. sTILs were evaluated centrally on pre-treatment H&E slides using standard criteria. Cox regression analysis was used to examine effect on event-free survival (EFS) and overall survival (OS). Among 474 patients, 44% had node-positive disease. Median sTILs were 5% (range 1%-95%), and 32% of patients had ≥30% sTILs. pCR rate was 51%. On multivariable analysis, T stage (OR=2.08,p=0.007), nodal status (OR=1.64,p=0.035), and sTILs (OR=1.10,p=0.011) were associated with pCR. On multivariate analysis, nodal status (HR=0.46,p=0.008), pCR(HR=0.20,p<0.001), and sTILs(HR=0.95,p=0.049) were associated with OS. At 30% cut-point, sTILs stratified outcomes in stage III disease, 5-year OS 86% vs 57% in ≥30% vs <30% sTILs (HR=0.29,p=0.014), and numeric trend in stage II, 5-year OS 93% vs 89% in ≥30% vs <30% sTILs (HR=0.55,p=0.179). Among stage II-III patients with pCR, EFS was better in those with ≥30% sTILs (HR=0.16,p=0.047). sTILs density was independent predictor of OS beyond clinicopathologic features and pathologic response in TNBC patients treated with anthracycline-free CbD chemotherapy. Notably, sTILs density stratified outcomes beyond TNM stage and pathologic response. These findings highlight role of sTILs in patient selection/stratification for neo/adjuvant escalation and de-escalation strategies.

The VEGF-Hypoxia Signature is Upregulated in Basal like Breast Tumors from Women of African Ancestry and Associated with Poor Outcomes in Breast Cancer.

Black women experience the highest breast cancer mortality rate compared to women of other racial/ethnic groups. To gain a deeper understanding of breast cancer heterogeneity across diverse populations, we examined a VEGF-hypoxia gene expression signature in breast tumors from women of diverse ancestry. We developed a NanoString nCounter gene expression panel and applied it to breast tumors from Nigeria (n=182) and the University of Chicago (n=161). We also analyzed RNA sequencing data from Nigeria (n=84) and TCGA datasets (n=863). Patient prognosis was analyzed using multiple datasets. The VEGF-hypoxia signature was highest in the basal-like subtype compared to other subtypes, with greater expression in Black women compared to White women. In the TCGA dataset, necrotic breast tumors had higher scores for the VEGF-hypoxia signature compared to non-necrosis tumors (p<0.001), with the highest proportion in the basal-like subtype. Furthermore, necrotic breast tumors have higher scores for the proliferation signature, suggesting an interaction between the VEGF-hypoxia signature, proliferation and necrosis. T cell gene expression signatures also correlated with the VEGF-hypoxia signature when testing all tumors in the TCGA dataset. Lastly, we found a significant association of the VEGF-hypoxia profile with poor outcomes when using all patients in the METABRIC (p<0.0001) and SCAN-B datasets (p=0.002). These data provide further evidence for breast cancer heterogeneity across diverse populations and molecular subtypes. Interventions selectively targeting VEGF-hypoxia and the immune microenvironment have the potential to improve overall survival in aggressive breast cancers that disproportionately impact Black women in the African Diaspora.

Ensemble Learning Approach Reveals Significant Clinical Attributes from Real-World Breast Cancer Cases

Breast cancer has become on of the leading causes of death in Indonesia. This study contributes to global efforts to combat breast cancer by improving patient outcome prediction accuracy. This study employed ensemble learning techniques such as Random Forest, XGBoost, and LightGBM. The results of the study demonstrates LightGBM's superior performance (accuracy=85%, ROC-AUC=81%, AUPR=85%). Notably, all three algorithms identify key clinical attributes: "Relapse Free Status (Months)", "Overall Survival (Months)", "Nottingham Prognostic Index", and "Lymph Nodes Examined Positive". LightGBM uniquely highlights "pam50_LumA" as significant, suggesting reduced fatality risk for Luminal A subtype patients, while others prioritize "Tumor Size". This research lays groundwork for intelligent systems to predict breast cancer outcomes, potentially transforming patient care and clinical practice.

Thermo-immune synergy: Camrelizumab plus microwave ablation in preoperative early-stage breast cancer

Immunotherapy has enhanced breast cancer outcomes, but optimizing combination therapies is crucial. Integrating additional treatment modalities, like physical therapies, holds promise for optimizing efficacy. Pan etal. recently reported that combining preoperative immunotherapy with microwave ablation is safe and feasible in early-stage breast cancer, effectively sensitizing peripheral CD8+ Tcells.1.

A novel long non-coding RNA LINC00524 facilitates invasion and metastasis through interaction with TDP43 in breast cancer.

Breast cancer (BC) remains a significant health concern worldwide, with metastasis being a primary contributor to patient mortality. While advances in understanding the disease's progression continue, the underlying mechanisms, particularly the roles of long non-coding RNAs (lncRNAs), are not fully deciphered. In this study, we examined the influence of the lncRNA LINC00524 on BC invasion and metastasis. Through meticulous analyses of TCGA and GEO data sets, we observed a conspicuous elevation of LINC00524 expression in BC tissues. This increased expression correlated strongly with a poorer prognosis for BC patients. A detailed Gene Ontology analysis suggested that LINC00524 likely exerts its effects through RNA-binding proteins (RBPs) mechanisms. Experimentally, LINC00524 was demonstrated to amplify BC cell migration, invasion and proliferation invitro. Additionally, invivo tests showed its potent role in promoting BC cell growth and metastasis. A pivotal discovery was LINC00524's interaction with TDP43, which leads to the stabilization of TDP43 protein expression, an element associated with unfavourable BC outcomes. In essence, our comprehensive study illuminates how LINC00524 accelerates BC invasion and metastasis by binding to TDP43, presenting potential avenues for therapeutic interventions.

FXR Agonism with Bile Acid Mimetic Reduces Pre-Clinical Triple-Negative Breast Cancer Burden.

Bariatric surgery is associated with improved outcomes for several cancers, including breast cancer (BC), although the mechanisms mediating this protection are unknown. We hypothesized that elevated bile acid pools detected after bariatric surgery may be factors that contribute to improved BC outcomes. Patients with greater expression of the bile acid receptor FXR displayed improved survival in specific aggressive BC subtypes. FXR is a nuclear hormone receptor activated by primary bile acids. Therefore, we posited that activating FXR using an established FDA-approved agonist would induce anticancer effects. Using in vivo and in vitro approaches, we determined the anti-tumor potential of bile acid receptor agonism. Indeed, FXR agonism by the bile acid mimetic known commercially as Ocaliva ("OCA"), or Obeticholic acid (INT-747), significantly reduced BC progression and overall tumor burden in a pre-clinical model. The transcriptomic analysis of tumors in mice subjected to OCA treatment revealed differential gene expression patterns compared to vehicle controls. Notably, there was a significant down-regulation of the oncogenic transcription factor MAX (MYC-associated factor X), which interacts with the oncogene MYC. Gene set enrichment analysis (GSEA) further demonstrated a statistically significant downregulation of the Hallmark MYC-related gene set (MYC Target V1) following OCA treatment. In human and murine BC analyses in vitro, agonism of FXR significantly and dose-dependently inhibited proliferation, migration, and viability. In contrast, the synthetic agonism of another common bile acid receptor, the G protein-coupled bile acid receptor TGR5 (GPBAR1) which is mainly activated by secondary bile acids, failed to significantly alter cancer cell dynamics. In conclusion, agonism of FXR by primary bile acid memetic OCA yields potent anti-tumor effects potentially through inhibition of proliferation and migration and reduced cell viability. These findings suggest that FXR is a tumor suppressor gene with a high potential for use in personalized therapeutic strategies for individuals with BC.

ZIP Code to Genomic Code: Neighborhood Disadvantage, Aggressive Breast Cancer Biology, and Breast Cancer Outcomes.

To determine the association between objective (geospatial) and subjective (perceived) measures of neighborhood disadvantage (ND) and aggressive breast cancer (BCa) tumor biology, defined using validated social adversity-associated transcription factor (TF) activity and clinical outcomes. ND is associated with shorter BCa recurrence-free survival (RFS), independent of individual, tumor, and treatment characteristics, suggesting potential unaccounted biological mechanisms by which ND influences RFS. We quantified TF-binding motif prevalence within promoters of differentially expressed genes for 147 tissue samples prospectively collected on protocol. Covariate-adjusted multivariable regression analyzed objective and subjective ND scores with 5 validated TFs of social adversity and aggressive biology-pro-inflammatory activity (NF-kB, AP-1), sympathetic nervous system (SNS) activity (CREB), and protective cellular responses (IRF, STAT). To clinically validate these TFs as prognostic biomarkers of aggressive biology, logistic regression and multivariable Cox proportional-hazards models analyzed their association with Oncotype DX scores and RFS, respectively. Increasing objective ND was associated with aggressive tumor biology (up-regulated NF-kB, AP-1, down-regulated IRF, STAT) and SNS activation (up-regulated CREB). Increasing subjective ND (e.g., threat to safety), was associated with up-regulated NF-kB and CREB and down-regulated IRF. These TF patterns were associated with high-risk Oncotype DX scores and shorter RFS. In the largest human social genomics study, objective and subjective ND were significantly associated with TFs of aggressive biology and SNS activation. These TFs also correlated with worse clinical outcomes, implicating SNS activation as one potential mechanism behind ND survival disparities. These findings remain to be validated in a national cohort.

A scoping review of web-based, interactive, personalized decision-making tools available to support breast cancer treatment and survivorship care.

We reviewed existing personalized, web-based, interactive decision-making tools available to guide breast cancer treatment and survivorship care decisions in clinical settings. The study was conducted using the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews(PRISMA-ScR). We searched PubMed and related databases for interactive web-based decision-making tools developed to support breast cancer treatment and survivorship care from 2013 to 2023. Information on each tool's purpose, target population, data sources, individual and contextual characteristics, outcomes, validation, and usability testing were extracted. We completed a quality assessment for each tool using the International Patient Decision Aid Standard (IPDAS)instrument. We found 54 tools providing personalized breast cancer outcomes (e.g., recurrence) and treatment recommendations (e.g., chemotherapy) based on individual clinical (e.g., stage), genomic (e.g., 21-gene-recurrence score), behavioral (e.g., smoking), and contextual (e.g., insurance) characteristics. Forty-five tools were validated, and nine had undergone usability testing. However, validation and usability testing included mostly White, educated, and/or insured individuals. The average quality assessment score of the tools was 16 (range: 6-46; potential maximum: 63). There was wide variation in the characteristics, quality, validity, and usability of the tools. Future studies should consider diverse populations for tool development and testing. There are tools available to support personalized breast cancer treatment and survivorship care decisions in clinical settings. It is important for both cancer survivors and physicians to carefully consider the quality, validity, and usability of these tools before using them to guide care decisions.

The HLA-I landscape confers prognosis and antitumor immunity in breast cancer.

Breast cancer is a highly heterogeneous disease with varied subtypes, prognoses and therapeutic responsiveness. Human leukocyte antigen class I (HLA-I) shapes the immunity and thereby influences the outcome of breast cancer. However, the implications of HLA-I variations in breast cancer remain poorly understood. In this study, we established a multiomics cohort of 1156 Chinese breast cancer patients for HLA-I investigation. We calculated four important HLA-I indicators in each individual, including HLA-I expression level, somatic HLA-I loss of heterozygosity (LOH), HLA-I evolutionary divergence (HED) and peptide-binding promiscuity (Pr). Then, we evaluated their distribution and prognostic significance in breast cancer subtypes. We found that the four breast cancer subtypes had distinct features of HLA-I indicators. Increased expression of HLA-I and LOH were enriched in triple-negative breast cancer (TNBC), while Pr was relatively higher in hot tumors within TNBCs. In particular, a higher Pr indicated a better prognosis in TNBCs by regulating the infiltration of immune cells and the expression of immune molecules. Using the matched genomic and transcriptomic data, we found that mismatch repair deficiency-related mutational signature and pathways were enriched in low-Pr TNBCs, suggesting that targeting mismatch repair deficiency for synthetic lethality might be promising therapy for these patients. In conclusion, we presented an overview of HLA-I indicators in breast cancer and provided hints for precision treatment for low-Pr TNBCs.

A Comprehensive Analysis of the Effect of A&gt;I(G) RNA-Editing Sites on Genotoxic Drug Response and Progression in Breast Cancer

Dysregulated A&gt;I(G) RNA editing, which is mainly catalyzed by ADAR1 and is a type of post-transcriptional modification, has been linked to cancer. A low response to therapy in breast cancer (BC) is a significant contributor to mortality. However, it remains unclear if there is an association between A&gt;I(G) RNA-edited sites and sensitivity to genotoxic drugs. To address this issue, we employed a stringent bioinformatics approach to identify differentially RNA-edited sites (DESs) associated with low or high sensitivity (FDR 0.1, log2 fold change 2.5) according to the IC50 of PARP inhibitors, anthracyclines, and alkylating agents using WGS/RNA-seq data in BC cell lines. We then validated these findings in patients with basal subtype BC. These DESs are mainly located in non-coding regions, but a lesser proportion in coding regions showed predicted deleterious consequences. Notably, some of these DESs are previously reported as oncogenic variants, and in genes related to DNA damage repair, drug metabolism, gene regulation, the cell cycle, and immune response. In patients with BC, we uncovered DESs predominantly in immune response genes, and a subset with a significant association (log-rank test p &lt; 0.05) between RNA editing level in LSR, SMPDL3B, HTRA4, and LL22NC03-80A10.6 genes, and progression-free survival. Our findings provide a landscape of RNA-edited sites that may be involved in drug response mechanisms, highlighting the value of A&gt;I(G) RNA editing in clinical outcomes for BC.

Abstract 5185: A multimodal, spatially defined, nanomechanical signature as predictive biomarker for breast cancer outcome: A 20 year survival study

Abstract Background: With the recent advancement in perioperative treatment protocols, the search for clinical biomarkers that can predict overall response and long-term cancer outcome independent from treatment acquires even more importance. Recently, it has become clear that mechanical properties of the tumor microenvironment in solid tumors play a key role in driving outcome, mediating immune infiltration and activation, and response to therapy. Moreover, a growing body of evidence supports the understanding that mechanical changes induced by a plethora of therapeutic regimens should be leveraged to elicit favorable outcome. Methods: In this work we propose a dual approach to reveal mechanical biomarkers predictive of long-term outcome in solid cancers. Our first approach is based on a newly developed, 60 channel, biomechanical imaging mass cytometry panel to elucidate biomechanical cues that drive tumor aggressiveness and immune infiltration. Our second approach utilizes the AFM-based Automated and Reliable Tissue Diagnostics (ARTIDIS) investigational device to measure mechanical properties of fresh clinical biopsy samples at a nanoscale resolution. Our analysis was performed on over 300 clinical samples, from routine baseline clinical biopsies collected from both the Breast Clinic, University Hospital Basel, and the University of Dundee, in the UK. Patients in these two cohorts were treated with either adjuvant or neoadjuvant approaches, including radiation, chemotherapy, hormonal, and surgical treatment regimens, with individual patient follow up as long as 20 years. Results: We demonstrated with two complimentary technologies that biomechanical spatial patterns drive outcome in breast cancer. Our results include a multi-platform elucidation of the biomechanical phenotypes of epithelial to mesenchymal transitions driven by hypoxic environments. Furthermore, we identified several biomechanical subpopulations of cancer associated fibroblasts, and their role in mediating cancer outcome, in relationship with survival time and several clinical variables (e.g. metastasis, nodes, grade). We mechanistically corroborated these results by evaluating the immune modulatory effect of the identified biomechanical microenvironments in breast cancer. Lastly, we correlated the identified biomechanical microenvironments with the ARTIDIS nanomechanical signature as a clinically integrated, rapid, single biomechanics signature at the nanoscale. Conclusion: Our results further validate the importance of biomechanics in driving tumor response and immune infiltration across a variety of clinical treatment setting. These result support the integration of ARTIDIS nanomechanical signature in clinical settings as a single predictive biomarker able to rapidly and accurately capture biomechanical alterations that drive cancer outcome. Citation Format: Sara Nizzero, Maria Pelaez Soni, Gregory Zaugg, Yitian Xu, Licheng Zhang, Junjun Zheng, Lee B. Jordan, Colin A. Purdie, Philip R. Quinlan, Chandandeep Nagi, Karla A. Sepulveda, Philipp Oertle, Tobias A. Appenzeller, Marko Loparic, Shu-Hsia Chen, Vittorio Cristini, Marija Plodinec, Alastair M. Thompson. A multimodal, spatially defined, nanomechanical signature as predictive biomarker for breast cancer outcome: A 20 year survival study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5185.

Abstract 5797: Next generation antibody drug conjugates: Multi-payload conjugates targeting multiple mechanisms of cell killing

Abstract Introduction: ADCs have had tremendous impact on patient outcomes in breast cancer and are now second line therapy for stage IV HER2 positive metastatic breast cancer. However, many patients fail to respond or relapse after treatment with ADC therapies due to tumor heterogeneity and resistance to ADC payloads. We are developing next generation ADCs that deliver targeted combination chemotherapies with a single molecule. Method: CatenaBio has developed a novel system capable of attaching distinct payloads at different sites to the same antibody, enabling the production of highly stable single-molecule targeted combination therapies, Multi-Payload-Conjugates (MPCs), with a well-defined drug-antibody ratio (DAR). Results: We screened combinations of different payloads targeting several different mechanisms of cell division attached to trastuzumab at different DARs to optimize tumor cell killing. These targeted combination ADCs demonstrated robust killing in both HER2 high and low tumor cell lines. Additionally, these novel MPCs show potent inhibition of tumor growth in a HER2+ xenograft model of cancer. Conclusion: Antibody Drug Conjugates have revolutionized the treatment of high HER2 positive breast cancer. More recently advances have been made in the design of ADCs to expand indications to include HER2 low as well as HER2 negative patients. Multi-payload Conjugates® offer the next step in ADC design and allow for the combination of multiple mechanisms of action in a single MPC that are highly effective across multiple breast cancer cell lines and HER2 expression levels. These molecules offer the potential to circumvent tumor resistance pathways and deliver deeper and more durable responses. Citation Format: Richard L. Kendall, Marco Lobba, Saurabh Johri, Chanez Symister, Devin Trinter, Maxwell Nguyen, Daniel Gutierrez, Samantha Brady, Andrew Lau, Matthew B. Francis. Next generation antibody drug conjugates: Multi-payload conjugates targeting multiple mechanisms of cell killing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5797.