Breast Cancer Treatment Outcome Research Articles

DYRK2 controls GSTPI expression through ubiquitination and degradation of Twist1 to reduce chemotherapy resistance caused by EMT in breast cancer.

Breast cancer (BC) poses a significant global health challenge, with chemotherapy resistance, especially to docetaxel, remaining a major obstacle in effective treatment. The molecular mechanisms underlying this resistance are critical for developing targeted therapeutic strategies. This study aims to explore the role of dual-specificity tyrosine phosphorylation-regulated kinase 2 (DYRK2), a member of the DYRK family, in docetaxel resistance in breast cancer cells and investigate its impact on cellular responses, including drug sensitivity and migration. Additionally, potential interactions between DYRK2 and Twist1, associated with epithelial-mesenchymal transition (EMT) and drug resistance, are explored. Docetaxel-resistant breast cancer cells were induced, and the expression levels of DYRK2, Twist1, and related genes were evaluated using real-time PCR and Western blotting. Lentivirus-mediated DYRK2 overexpression was employed to assess its effect on drug sensitivity, migratory ability, and Twist1 expression. The relationship between DYRK2 and Twist1 was examined, focusing on Twist1 ubiquitination. The impact of Twist1 on chemotherapy resistance and its binding to the Glutathione S-transferase Pi 1 (GSTP1) promoter were also investigated. Docetaxel-resistant cells exhibited down-regulated DYRK2 and up-regulated Twist1 expression. DYRK2 overexpression reversed drug resistance, decreased migration, and attenuated Twist1 and GST-π expression. DYRK2 was found to suppress Twist1 expression through ubiquitination, supported by decreased Twist1 phosphorylation and increased ubiquitination after DYRK2 overexpression. Twist1 overexpression counteracted DYRK2-induced drug sensitivity enhancement, promoting GST-π expression, EMT, migration, and proliferation. Twist1 was shown to bind to the GSTP1 promoter, enhancing its transcription. In vivo experiments confirmed DYRK2's ability to suppress chemoresistance in breast cancer cells. DYRK2 plays a pivotal role in overcoming docetaxel resistance in breast cancer cells by suppressing Twist1 expression through ubiquitination, impacting downstream signaling and cellular responses. This study provides valuable insights for developing targeted therapies to improve breast cancer treatment outcomes.

Interpretable Machine Learning Algorithms Identify Inetetamab-Mediated Metabolic Signatures and Biomarkers in Treating Breast Cancer.

HER2-positive breast cancer (BC), a highly aggressive malignancy, has been treated with the targeted therapy inetetamab for metastatic cases. Inetetamab (Cipterbin) is a recently approved targeted therapy for HER2-positive metastatic BC, significantly prolonging patients' survival. Currently, there is no established biomarker to reliably predict or assess the therapeutic efficacy of inetetamab in BC patients. This study harnesses the power of metabolomics and machine learning to uncover biomarkers for inetetamab in BC therapy. A total of 23 plasma samples from inetetamab-treated BC patients were collected and stratified into responders and nonresponders. Ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry was utilized to analyze the metabolites in blood samples. A combination of univariate and multivariate statistical analyses was employed to identify these metabolites, and their biological functions were then ascertained by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Finally, machine learning algorithms were employed to screen responsive biomarkers from all differentially expressed metabolites. Our finding revealed 6889 unique metabolites that were detected. Pathways like retinol metabolism, fatty acid biosynthesis, and steroid hormone biosynthesis were enriched for differentially expressed metabolites. Notably, two key metabolites associated with inetetamab response in BC were identified: FAPy-adenine and 2-Pyrocatechuic acid. There was some negative correlation between progress-free survival (PFS) and their kurtosis content. In summary, the identification of these two significant differential metabolites holds promise as potential biomarkers for evaluating and predicting inetetamab treatment outcomes in BC, ultimately contributing to the diagnosis of the disease and the discovery of prognostic markers.

Harnessing natural compounds to modulate miRNAs in breast cancer therapy.

Breast cancer's complexity and heterogeneity continue to present significant challenges in its treatment and management. Emerging research has underscored the pivotal role of microRNAs (miRNAs) in breast cancer pathogenesis, acting as crucial regulators of gene expression. This review delivers an in-depth analysis of miRNAs, highlighting their dual functions as both oncogenes and tumor suppressors, and detailing their impact on key biological processes, including cell proliferation, apoptosis, and metastasis. The mechanisms underlying miRNA action, particularly their interactions with target mRNAs and the factors influencing these dynamics, are thoroughly explored. Additionally, the review discusses the therapeutic prospects of miRNAs, with a focus on innovative delivery systems like nanoparticles that improve the stability and effectiveness of miRNA-based therapies. It also addresses the anticancer effects of natural compounds, such as genistein, hesperidin, quercetin, curcumin, resveratrol, epigallocatechin-3-gallate (EGCG), and glyceollins, which modulate miRNA expression and contribute to tumor growth inhibition. These advances seek to address the limitations of conventional therapies, paving the way for targeted interventions in breast cancer. By integrating current insights on miRNA biology, therapeutic strategies, and the potential of natural products to regulate miRNA expression, this review aims to shed light on miRNA- and natural product-based approaches as promising avenues for enhancing breast cancer treatment outcomes.

Artificial Intelligence in Breast Cancer Diagnosis and Treatment: Advances in Imaging, Pathology, and Personalized Care.

Breast cancer is the most prevalent cancer worldwide, affecting both low- and middle-income countries, with a growing number of cases. In 2024, about 310,720 women in the U.S. are projected to receive an invasive breast cancer diagnosis, alongside 56,500 cases of ductal carcinoma in situ (DCIS). Breast cancer occurs in every country of the world in women at any age after puberty but with increasing rates in later life. About 65% of women with the BRCA1 and 45% with the BRCA2 gene variants develop breast cancer by age 70. While these genes account for 5% of breast cancers, their prevalence is higher in certain populations. Advances in early detection, personalised medicine, and AI-driven diagnostics are improving outcomes by enabling a more precise analysis, reducing recurrence, and minimising treatment side effects. Our paper aims to explore the vast applications of artificial intelligence within the diagnosis and treatment of breast cancer and how these advancements can contribute to elevating patient care as well as discussing the potential drawbacks of such integrations into modern medicine. We structured our paper as a non-systematic review and utilised Google Scholar and PubMed databases to review literature regarding the incorporation of AI in the diagnosis and treatment of non-palpable breast masses. AI is revolutionising breast cancer management by enhancing imaging, pathology, and personalised treatment. In imaging, AI can improve the detection of cancer in mammography, MRIs, and ultrasounds, rivalling expert radiologists in accuracy. In pathology, AI enhances biomarker detection, improving HER2 and Ki67 assessments. Personalised medicine benefits from AI's predictive power, aiding risk stratification and treatment response. AI also shows promise in triple-negative breast cancer management, offering better prognosis and subtype classification. However, challenges include data variability, ethical concerns, and real-world validation. Despite limitations, AI integration offers significant potential in improving breast cancer diagnosis, prognosis, and treatment outcomes.

Quality-of-Life Outcomes from NRG/NSABP B-39/RTOG 0413: Whole-breast Irradiation vs Accelerated Partial-breast Irradiation after Breast Conserving Surgery.

NRG Oncology (NRG)/NSABP B-39/RTOG 0413 compared whole-breast irradiation (WBI) to accelerated partial-breast irradiation (APBI). APBI was not equivalent to WBI in local tumor control. Secondary outcome was Quality-of-life (QOL). The QOL sub-study used validated self-report questionnaires including the Breast Cancer Treatment Outcome Scale (BCTOS) and SF-36 vitality scale. Assessments occurred: before randomization, at treatment completion (chemotherapy or radiotherapy), 4-weeks later, at 6-, 12-, 24-, and 36-months. Primary aims: cosmesis change equivalency (baseline to 3 years; a priori margin of equivalence 0.4 standard deviations) and fatigue change superiority (baseline to end-of-treatment (EOT)) for APBI vs WBI, by patient groups treated with or without chemotherapy when appropriate. From 3/21/05-5/25/09, 975 patients enrolled in this sub-study; 950 had follow-up data. APBI had 3-year cosmesis equivalent to WBI (95%CI,-0.0001-0.16; equivalence margin -0.22-0.22) in all patients. The APBI group without chemotherapy had less EOT fatigue (p = .011; mean score APBI 63 vs WBI 59); APBI group receiving chemotherapy had worse EOT fatigue (p = .011; APBI 43 vs WBI 49). The APBI group reported less pain (BCTOS) at EOT (WBI 2.29 vs APBI 1.97), but worse pain at 3-years (WBI 1.62 vs APBI 1.71). APBI patients reported greater convenience of care than with WBI and reported less symptom severity at EOT and 4-weeks later. Cosmetic outcomes were similar for APBI and WBI groups, with small statistically significant differences in other outcomes that varied over time. Differences in fatigue and other symptoms appeared to resolve by ≥ 6 months. APBI may be preferred by some patients, for whom extended treatment is burdensome.

PLGA Nanoplatform for the Hypoxic Tumor Delivery: Folate Targeting, Therapy, and Ultrasound/Photoacoustic Imaging.

Effective targeting of breast tumors is critical for improving therapeutic outcomes in breast cancer treatment. Additionally, hypoxic breast cancers are difficult to treat due to resistance toward chemotherapeutics, poor vascularity, and enhanced angiogenesis, which complicate effective drug delivery and therapeutic response. Addressing this formidable challenge requires designing a drug delivery system capable of targeted delivery of the anticancer agent, inhibition of efflux pump, and suppression of the tumor angiogenesis. Here, we have introduced Palbociclib (PCB)-loaded PLGA nanoparticles (NPs) consisting of chitosan-folate (CS-FOL) for folate receptor-targeted breast cancer therapy. The developed NPs were below 219 nm with a smooth, spherical surface shape. The entrapment efficiencies of NPs were achieved up to 85.78 ± 1.8%. Targeted NPs demonstrated faster drug release at pH 5.5, which potentiated the therapeutic efficacy of NPs due to the acidic microenvironment of breast cancer. In vitro cellular uptake study in MCF-7 cells confirmed the receptor-mediated endocytosis of targeted NPs. In vivo ultrasound and photoacoustic imaging studies on rats with hypoxic breast cancer showed that targeted NPs significantly reduced tumor growth and hypoxic tumor volume, and suppressed angiogenesis.

Association of residual ductal carcinoma in situ with breast cancer treatment outcomes after neoadjuvant chemotherapy according to hormone receptor status

PurposeThis research aimed to clarify the impact of residual ductal carcinoma in situ(DCIS) in surgical specimens obtained after neoadjuvant chemotherapy(NAC) for breast cancer on the associated prognosis outcomes.MethodsThis retrospective study was performed on a cohort of 1,009 patients who achieved pCR following NAC for breast cancer and underwent subsequent breast surgery at a single institution between January 2008 and December 2019. Overall survival, local recurrence-free survival, distant metastasis-free survival, and disease-free survival of the residual and non-residual DCIS groups were the outcomes compared, with further subgroup analysis performed according to hormone receptor status. Results260 individuals (25.8%) presented with residual DCIS. Based on a median follow-up of 54.0 months, no significant differences in outcomes were observed between the two groups. Patients with residual DCIS and hormone receptor-negative (HR-) breast cancer demonstrated a significant decrease in distant metastasis-free survival (p = 0.030) compared to those without residual DCIS. In the HR + cohort, no significant difference was observed between the two groups. Multivariate analysis of the HR- cohort demonstrated a significant association between residual DCIS and an elevated risk for distant recurrence (hazard ratio = 2.3, 95% confidence interval = 1.01–5.20, p = 0.047).ConclusionsResidual DCIS following NAC may impact breast cancer outcomes, particularly with respect to the occurrence of distant metastasis in HR- patients. Therefore, clinicians must vigilantly monitor patients with residual DCIS after NAC, and further research is needed to expand our understanding of the clinical implications of residual DCIS.

Summary and Roadmap of Breast Cancer Research in the Veterans Affairs.

Women are the largest growing population of Veterans within the U.S. Department of Veterans Affairs (VA) Health Care System. Among women Veterans, breast cancer is the most common malignancy (30% of all cancers), yet little is known about the unique needs of women Veterans with cancer and how to provide them with high quality care. The VA health care system has initiated multiple system-wide systemic efforts, including launching the Breast and Gynecologic Cancer System of Excellence (BGSOE) to address this knowledge gap. This report summarizes the outcomes of the inaugural 2023 VA Women's Cancer Research Conference, which assembled 37 multidisciplinary clinicians, scientists, the VA and civilian partners with a shared goal of advancing VA breast cancer research. Conference objectives were to build a collective vision for improving: (1) referral patterns for breast cancer treatment and patient-level outcomes and (2) molecular and genetic testing patterns across the breast cancer continuum among women Veterans. The meeting hosted 15 speakers at the Houston VA Medical Center. Future research priorities for women Veterans with cancer were identified from discussions and a post-conference survey. We then administered a 13-question post-conference survey to conference attendees. Respondents ranked the research priorities. The survey results show that the cross-cutting cancer research priorities designed to transform cancer care for women Veterans at the VA fit into 5 broad areas of study, including (1) care quality for treatment, (2) improving treatment, (3) care quality of molecular and genetic testing, (4) risk reduction through risk assessment and germline genetic testing, and (5) establishing strategic partnerships. Our data elucidate areas for further investigation to improve the delivery of cancer care.

Advancing equity in breast cancer care: natural language processing for analysing treatment outcomes in under-represented populations

ObjectiveThe study aimed to develop natural language processing (NLP) algorithms to automate extracting patient-centred breast cancer treatment outcomes from clinical notes in electronic health records (EHRs), particularly for women from...

Enhancing Chemotherapy Efficacy: Investigating the Synergistic Impact of Paclitaxel and cd73 Gene Suppression on Breast Cancer Cell Proliferation and Migration.

Background Enhancing chemotherapy efficacy is crucial in breast cancer treatment. This study examines the synergistic effects of paclitaxel, a common chemotherapeutic drug, andCluster of differentiation 73(cd73) gene suppression via siRNA on MDA-MB-231 breast cancer cells. Methods MDA-MB-231 cells were transfected with CD73 siRNA and treated with paclitaxel.Cell viability, apoptosis, and migration wereassessed by using MTT assays, Annexin V-FITC/PI staining, and wound healing assays, respectively, with flow cytometry analyzing cell cycle distribution. Results The combination of CD73 siRNA and paclitaxel significantly reduced cell viability, lowering paclitaxel's IC50 from 14.73 μg/mL to 8.471 μg/mL, indicating enhanced drug sensitivity. Apoptosis rates increased with the combination treatment, while cell migration was significantly inhibited. Flow cytometry revealed cell cycle arrest in the Sub-G1 and G2-M phases. Conclusion These findings suggest that cd73 gene suppression enhances paclitaxel's cytotoxic effects, promoting apoptosis and inhibiting cell migration in MDA-MB-231 breast cancer cell line. This combined strategy shows promise for improving breast cancer treatment outcomes by increasing the efficacy of existing chemotherapeutic regimens, warranting further research to explore its potential clinical applications and effectiveness in other breast cancer cell lines and models.

Endoscopic excision of breast fibroadenoma through inframammary fold: Feasibility, safety and medium-term outcomes.

Endoscopic-assisted surgery for breast tumors has the advantage of inconspicuous scars, less breast volume loss, and nipple areolar distortion. A novel endoscopic-assisted technique through inframammary fold for excision of fibroadenomas is presented. Endoscopic-assisted excision of fibroadenoma(s) through inframammary fold was performed in four patients after informed written consent via three ports (12, 5, and 5 mm). Breast Cancer Treatment Outcome Score-12 (BCTOS-12) was used to evaluate patient satisfaction after surgery. No intraoperative and wound complication was noted. On median follow-up of 26.5 months, patients reported satisfactory responses to aesthetic and functional outcomes. No scar related complications were noted. Endoscopic-assisted excision of fibroadenoma through inframammary fold can be a safe and feasible option with good aesthetic outcomes.

Explainable Precision Medicine in Breast MRI: A Combined Radiomics and Deep Learning Approach for the Classification of Contrast Agent Uptake.

In DCE-MRI, the degree of contrast uptake in normal fibroglandular tissue, i.e., background parenchymal enhancement (BPE), is a crucial biomarker linked to breast cancer risk and treatment outcome. In accordance with the Breast Imaging Reporting & Data System (BI-RADS), it should be visually classified into four classes. The susceptibility of such an assessment to inter-reader variability highlights the urgent need for a standardized classification algorithm. In this retrospective study, the first post-contrast subtraction images for 27 healthy female subjects were included. The BPE was classified slice-wise by two expert radiologists. The extraction of radiomic features from segmented BPE was followed by dataset splitting and dimensionality reduction. The latent representations were then utilized as inputs to a deep neural network classifying BPE into BI-RADS classes. The network's predictions were elucidated at the radiomic feature level with Shapley values. The deep neural network achieved a BPE classification accuracy of 84 ± 2% (p-value < 0.00001). Most of the misclassifications involved adjacent classes. Different radiomic features were decisive for the prediction of each BPE class underlying the complexity of the decision boundaries. A highly precise and explainable pipeline for BPE classification was achieved without user- or algorithm-dependent radiomic feature selection.

Abstract PO3-09-08: Using Social Determinants of Health to Improve Surgical Delays for Breast Cancer Patients at Rush University Cancer Center

Abstract Introduction Delays to surgery in the treatment of breast cancer can lead to worse disease specific mortality and overall survival. Previous work has shown a woman’s time to surgical treatment is influenced by income, which may be secondary to social determinants of health (SDOH) including health literacy, safety, stress, access to health care and transportation, housing, and ability to pay utilities. This study sought to evaluate a screening process for SDOH to assess and address barriers to care for women newly diagnosed with breast cancer. Methods A SDOH screening tool consisting of 7 yes/no questions was developed and used by trained breast oncology nurses via phone call made to all new patients prior to their first visit. Based on patient response, patients are provided with community resources or referred to the hospital social work team. Primary outcome included the SDOH screening results, and secondary outcome included time to surgery. Results 118 patients were screened, of which 60 patients had surgery as their first treatment and were included in this analysis. Twenty-seven patients screened positive for SDOH need. Ten patients reported &amp;gt;3 SDOH concerns and were referred to social work. The most common concerns were food insecurity and trouble paying utilities. Of the 27 patients who screened positively, 18 identified as Black or African American, 3 were Hispanic, 1 Asian and 5 White. The mean household income for these patients based on their reported zip codes was $55,615.78. Average time to surgery for patients with a positive SDOH screen was 37.7 days and negative SDOH screen was 42 days. For patients with a positive SDOH screen, those with 2 or fewer SDOH needs had an average time to surgery of 41.9 days and those with 3 or more SDOH needs had an average 30.6 days until surgery. Discussion Patients who screened positive for SDOH need and were provided resources had a faster time to surgery than patients who initially screened negative for SDOH. Patients referred to social work had the fastest time to surgery. Early identification of SDOH is necessary for all patients to improve equity and outcomes in breast cancer treatment. Citation Format: Hilary Tingley, Madeline McIntosh, McKenzie Klee, Margaret Gladman, Alison Coogan, Andrea Madrigrano. Using Social Determinants of Health to Improve Surgical Delays for Breast Cancer Patients at Rush University Cancer Center [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-09-08.

Abstract PO2-02-10: Predicting the feasibility of breast conserving surgery using pre-treatment standard of care DCE-MRI: a novel clinical decision support tool for breast cancer surgical planning

Abstract Background: The decision-making process regarding breast cancer treatment options, specifically breast conserving surgery (BCS) versus mastectomy, is a complex and sensitive matter that takes into account the patient's preferences and their eligibility for BCS. A range of anatomical factors, such as tumor size, breast size, and proximity of the tumor to the skin, can influence the surgeon's recommendation regarding BCS or mastectomy. While mastectomy may be the only viable option for patients with large tumors, those with smaller tumors often have the opportunity to collaboratively decide with their surgeon on the most appropriate approach to ensure oncologic success and minimize potential cosmetic deformity. To facilitate this decision-making process, we developed a tool capable of providing informed recommendations on BCS or mastectomy based on standard of care imaging patient data. By integrating these recommendation capabilities, we aim to enhance the decision-making process and improve patient outcomes in breast cancer treatment. Methods: To assist surgeons and patients in determining a patient’s eligibility for breast conserving surgery (BCS), we developed the BCS Feasibility Score. The BCS Feasibility Score is generated from a binary classifier machine learning model and is representative of the probability that a given patient could receive BCS. The score is based solely on the output from TumorSight Viz, a software platform that uses only pre-treatment T1-weighted DCE MRI and applies a suite of deep learning algorithms to segment the patient’s disease and the surrounding breast tissues. From the multi-tissue segmentation generated using TumorSight Viz, we extracted 25 spatial morphology features to use in the model development process. The training and testing sets were a subsample of a publicly available dataset (Saha, et al, 2018). We selected patients that received either BCS or mastectomy and had a viable T1-weighted DCE MRI. Bi-lateral cases were excluded. The total training/testing set consisted of n = 749 cases, 363 of which received mastectomy and 386 who received BCS. Before model training occurred, we split 20% of the sample to use as the test set. We then trained a random forest classifier across a range of pre-set hyper-parameters, using a total of 25 features as inputs, and using 5x cross-validation in the training set. We then assessed model performance in the testing set only. Results: In the test set, 76 cases received BCS versus 74 that received mastectomy. We successfully predicted BCS in 56 out of 76 cases (74%), and mastectomy in 46 out of 74 cases (62%). Overall, we observed an AUC = 0.76 and an F1 score = 0.66, indicating moderate to strong model performance. The most important features in the model, as measured by SHAP values, included the axis aligned tumor longest dimension (mm), the closest distance between the tumor and the nipple (mm), the volume of the tumor convex hull (mL; dilated uni-centrically), and the ratio of tumor convex hull volume to breast volume. We tested the model’s performance in a fully independent holdout validation set of 579 cases. Within this validation set, 335 patients received BCS versus 244 received mastectomy. We successfully predicted BCS in 254 out of 335 cases (76%), and mastectomy in 149 out of 244 cases (61%). Overall, we observed an AUC = 0.75 and an F1 score = 0.63. Validation set performance mirrored results observed in the test set, indicating strong generalizability. In the validation set, comparing patients who underwent BCS to those who underwent mastectomy, we observed significant differences across all four of the most predictive features. Conclusion: TumorSight Viz and the BCS Feasibility Score help empower both patients and clinicians with information and tools to facilitate surgical planning decisions. Citation Format: John Pfeiffer, Bradley Feiger, Anuja Antony, Joseph Peterson. Predicting the feasibility of breast conserving surgery using pre-treatment standard of care DCE-MRI: a novel clinical decision support tool for breast cancer surgical planning [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-02-10.

Abstract PS16-06: Tumor-infiltrating lymphocytes and pathologic response to neoadjuvant chemotherapy with the addition of platinum and pembrolizumab in TNBC: A single-center real-world study

Abstract Background Previous studies have presented compelling evidence suggesting that the inclusion of platinum agents alongside anthracyclines and taxanes could potentially enhance treatment outcomes in high-risk triple-negative breast cancer (TNBC). Moreover, pembrolizumab has been integrated into clinical practice as a part of standard-of-care for non-metastatic TNBC with high risk. In light of these findings, we undertook a real-world study to investigate the impact of incorporating platinum agents and pembrolizumab on achieving pathologic complete response (pCR) in TNBC patients undergoing neoadjuvant chemotherapy (NAC). Furthermore, we specifically examined the influence of tumor-infiltrating lymphocytes (TILs) on the treatment outcomes. Patients and Methods In this real-world study conducted at Gangnam Severance Hospital, Seoul, Republic of Korea, we analyzed a cohort of 398 patients with TNBC who underwent surgery following NAC between March 2007 and November 2022. Among them, 247 patients received an anthracycline-taxanes (A-T), 120 received a carboplatin regimen including A-T, and 31 received a pembrolizumab regimen including A-T-carboplatin as part of their neoadjuvant chemotherapy treatment. TIL was evaluated in biopsied samples prior to NAC according to the guideline of TIL international working group. The high TIL was defined with a cutoff of 50%. Results Among the 398 patients analyzed, 87 (21.9%) had high TIL tumors. The pCR rates were 32% in the anthracycline-taxane (A-T) regimen group, 57% in the A-T-carboplatin regimen group, and 68% in the pembrolizumab with A-T-carboplatin regimen group. Within the high TIL group, the pCR rate did not increase with the addition of carboplatin (51.8% in the A-T group and 41.7% in the A-T-carboplatin group), but reached 85.7% with the addition of pembrolizumab and carboplatin. Among the low TIL group, the pCR rate increased from 26.7% to 61.1% with the addition of carboplatin, but there was no difference in the pCR rate between the carboplatin and pembrolizumab groups (61.1% and 60.9%, respectively). In clinically node-positive patients, the pCR rate significantly increased with pembrolizumab in the high TIL group (40.9% versus 100%, p=0.035). However, in low TIL patients, the addition of carboplatin alone significantly increased the pCR rate to 62.3%, whereas the addition of pembrolizumab did not show the same effect. Conclusions Our real-world data consistently demonstrates an increased pCR rate with the addition of carboplatin and pembrolizumab. Among patients with high TIL, the addition of carboplatin did not result in an elevated pCR rate. However, the addition of pembrolizumab tended to maximize the pCR rate, surpassing 80%. On the other hand, among patients with low TIL, the addition of carboplatin significantly increased the pCR rate, while the addition of pembrolizumab did not have the same effect. Efforts should be made to improve the response to pembrolizumab-containing regimens for patients with low baseline TIL levels. Citation Format: Min Ji Kim, Yoonwon Kook, Seung Ho Baek, Junghyun Kim, Sohyun Moon, Seung Eun Lee, Jee Hung Kim, Soong June Bae, Sung Gwe Ahn, Joon Jeong. Tumor-infiltrating lymphocytes and pathologic response to neoadjuvant chemotherapy with the addition of platinum and pembrolizumab in TNBC: A single-center real-world study [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PS16-06.

Abstract PO1-17-12: The impact of treatment sequence of CDK4/6 inhibitor therapy on Metastatic Breast Cancer treatment outcomes in Real-World practice in U.S

Abstract Background A retrospective study to describe the actual benefit of treatment sequence with Endocrine Therapy (ET) plus cyclin D/cyclin-dependent kinases 4 and 6 (CDK4/6) therapy including as 1st-line and 2nd -line treatment for Metastatic breast cancer (MBC) patients with hormone receptor positive (HR+) and HER2 negative. We examined the extent that treatment sequence of CDK4/6 inhibitor therapy is associated with progression-free survival, and overall survival under real-world conditions. Methods This study used the nationwide electronic health record-derived-Flatiron Health de-identified database to estimate the real-world progression-free survival (rwPFS) and overall survival (rwOS) of MBC patients under different treatment sequence of CDK4/6 inhibitors. A total of 2,771 patients with ≥ 3 months of follow-up received either CDK4/6 inhibitor plus ET in the first-line setting (n=2,170) or ET alone in the first-line and CDK4/6 inhibitor plus ET in the second-line setting (n=601) between February 3, 2015, and November 02, 2021. We performed inverse probability weighting (IPW) to balance the baseline demographic and clinical characteristics between patients in the two groups. Kaplan-Meier method and Cox proportional hazards were used to test for an association of CDK4/6 treatment line sequence on PFS as the primary outcome and OS as the secondary outcome, adjusting for patient characteristics (e.g., age, race, comorbidities, ECOG value, Tumor site, and health insurance). Results Median follow-up was 25.6 months (interquartile range [IQR], 12.7–41.3) for the group with CDK4/6 inhibitor plus ET in first-line treatment and 33.1 months (IQR, 18.1–50.4) in those taking ET alone in first-line and CDK4/6 inhibitor plus ET in the second-line treatment. CDK4/6 inhibitor combination with ET as the first-line treatment was associated with significantly longer median rwPFS compared to receiving ET alone on first line and CDK4/6 inhibitor plus ET in the second line (28.0 vs 13.1 months; hazard ratio [HR], 0.40; 95% CI, 0.35–0.44; P &amp;lt; 0.0001). Median rwOS was 52 months for the group with first line CDK4/6 inhibitor plus ET and 48 months for the other group who received CDK4/6 inhibitor in the second line of treatment. However, the difference was not statistically significant (HR=0.91, 95% CI, 0.78–1.09, P-value=0.33). A propensity scores matching analysis showed similar results. Conclusions In this “real-world” population of patients with HR+/HER2− MBC, receiving CDK4/6 inhibitor plus ET as first line of treatment was associated with improved progression free survival compared with patients treated with ET alone in the first-line and CDK4/6 inhibitor plus ET on the second line of treatment. Citation Format: Gretchen Kimmick, Asal PIlehvari, Wen You, Gloribel Bonilla, Roger Anderson. The impact of treatment sequence of CDK4/6 inhibitor therapy on Metastatic Breast Cancer treatment outcomes in Real-World practice in U.S [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-17-12.

Abstract PS02-03: Is de-escalation of treatment by omission of radiotherapy associated with fear of cancer recurrence and health-related quality of life in women with early breast cancer? An exploratory study

Abstract Background: There is growing interest in treatment optimization in early breast cancer (EBC). PROSPECT (ANZ-1002) provided compelling evidence that a combination of pre-operative MRI and pathological features could identify a substantial group of patients with localised EBC in whom radiotherapy (RT) could be safely omitted. The patient experience of de-escalation or its association with health-related quality of life (HRQoL) and fear of cancer recurrence (FCR), was not examined in PROSPECT but is a key consideration of treatment decision-making. We conducted a retrospective, mixed methods, cross-sectional study to explore this association. Methods: Psychometrically validated measures including the Fear of Cancer Recurrence Inventory Short-Form, Depression Anxiety Stress Scale, Breast Cancer Treatment Outcomes Scale, EORTC QLQ-C30 and its breast-specific module, the BR23, and the Decision Regret Scale were completed by three groups of women with early EBC: Women in the PROSPECT clinical trial who underwent pre-surgical MRI and omitted RT (A), women who underwent pre-surgical MRI and received RT (B); and women who received usual care (no MRI, received RT; C). Between group differences were analysed with ANOVA or equivalent non-parametric tests. A subset from each group participated in a semi-structured interview. These data (n=44) were analysed with directed content analysis. Results: Data from 400 women were analysed. Median age was 65 years, and median time since diagnosis was 4.4 years. There were no group differences in neuroticism, mental health, age, medical comorbidities, parity, or time since diagnosis. Significantly lower FCR was observed in Group A (n=125) than in Group B (n=102; p=.002) or Group C (n=173; p=.001), and when participants were categorized by RT status (omitted RT vs received RT; p&amp;lt; .001). The proportion of women with normal FCR was significantly (p &amp;lt; .05) larger in Group A (62%) than in Group B (35%) or Group C (40%). There were no differences between groups on depression and anxiety. Women in Group A had fewer breast symptoms than in Group B (p=.003) and Group C (p= &amp;lt; .001), fewer arm symptoms than in Group B (p=.004) and Group C (p=.011), and better body image than Group C (p=.041). Compared to Groups B and C, Group A performed better on cosmetic (both p&amp;lt; .001), functional (A vs C: p=.011) and breast-specific pain measures (both p&amp;lt; .001). Pre-operative MRI and omission of RT were highly acceptable and decision regret was low. A secondary analysis was conducted to eliminate any potential impact of disease severity on the analysis. All cases (n=126) with any positive nodes, a Grade 3 tumour and tumour size &amp;gt;20mm were removed. The remaining sample comprised 274 women. The results were similar to the primary analysis. Qualitative analysis showed that women who omitted RT viewed this as appropriate treatment, not undertreatment. Women considered RT toxic but endured it as a necessity, if prescribed. Few women experienced ongoing negative effects from RT but there was a tendency to minimize RT treatment burden. Women managed their FCR by having trust in their treatment and faith in the medical advice they received. Conclusions: In the setting of the PROSPECT trial, treatment de-escalation via omitting RT was associated with less FCR, better HRQoL and functional and cosmetic outcomes and was highly acceptable. Clinicians should consider the potential for preserved HRQoL associated with omission of RT in treatment decision-making. Positive perceptions about tailored care, lower treatment burden, and trust in clinicians appear to be protective against FCR. Future studies should include prospective collection of FCR and HRQoL measures. Citation Format: Bruce Mann, Michelle Sinclair, Phyllis Butow, Janemary Hughes, Allan Park, Leslie Gilham, Allison Rose, Lesley Stafford. Is de-escalation of treatment by omission of radiotherapy associated with fear of cancer recurrence and health-related quality of life in women with early breast cancer? An exploratory study [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PS02-03.

Enhancing breast cancer segmentation and classification: An Ensemble Deep Convolutional Neural Network and U-net approach on ultrasound images

Breast cancer is a condition where the irregular growth of breast cells occurs uncontrollably, leading to the formation of tumors. It poses a significant threat to women’s lives globally, emphasizing the need for enhanced methods of detecting and categorizing the disease. In this work, we propose an Ensemble Deep Convolutional Neural Network (EDCNN) model that exhibits superior accuracy compared to several transfer learning models and the Vision Transformer model. Our EDCNN model integrates the strengths of the MobileNet and Xception models to improve its performance in breast cancer detection and classification. We employ various preprocessing techniques, including image resizing, data normalization, and data augmentation, to prepare the data for analysis. By following these measures, the formatting is optimized, and the model’s capacity to make generalizations is improved. We trained and evaluated our proposed EDCNN model using ultrasound images, a widely available modality for breast cancer imaging. The outcomes of our experiments illustrate that the EDCNN model attains an exceptional accuracy of 87.82% on Dataset 1 and 85.69% on Dataset 2, surpassing the performance of several well-known transfer learning models and the Vision Transformer model. Furthermore, an AUC value of 0.91 on Dataset 1 highlights the robustness and effectiveness of our proposed model. Moreover, we highlight the incorporation of the Grad-CAM Explainable Artificial Intelligence (XAI) technique to improve the interpretability and transparency of our proposed model. Additionally, we performed image segmentation using the U-Net segmentation technique on the input ultrasound images. This segmentation process allowed for the identification and isolation of specific regions of interest, facilitating a more comprehensive analysis of breast cancer characteristics. In conclusion, the study presents a creative approach to detecting and categorizing breast cancer, demonstrating the superior performance of the EDCNN model compared to well-established transfer learning models. Through advanced deep learning techniques and image segmentation, this study contributes to improving diagnosis and treatment outcomes in breast cancer.

PD-1/PD-L1 pathway: Current research in breast cancer.

Immunotherapy has shown encouraging outcomes in breast cancer (BC) treatment in recent years. The programmed cell death ligand 1 (PD-L1) transmembrane protein is suggested to function as a co-inhibitory factor in the immune response, where it collaborates with programmed cell death protein 1 (PD-1) to stimulate apoptosis, suppress cytokine release from PD-1 positive cells, and limit the growth of PD-1 positive cells. Furthermore, in many malignancies, PD-L1 reduces the immune system's response to neoplastic cells. These observations suggest that the PD-1/PD-L1 axis plays a vital role in cancer therapy and the regulation of cancer immune escape mechanisms. This review aimed to provide an overview of the functions of PD-1 and PD-L1 in BC cancer therapy. This research design is a literature review. The style is a traditional review on topics or variables relating to the PD-1/PD-L1 pathway. A literature search was carried out using three online databases. The search using the keywords yielded a total of 248 studies. Each result was filtered again according to the inclusion and exclusion criteria, resulting in a final total of 4 studies to be included in the literature review. The combination of PD-1/PD-L1 is essential for many malignancies. According to the evidence presented, this combination presents both an opportunity and a challenge in cancer treatment. Since many solid cancers, especially BC, express high levels of PD-1/PD-L1, cancer treatment mainly involves targeted therapies.

Impact of Low BMI and Nutritional Status on Quality of Life and Disease Outcome in Breast Cancer Patients: Insights From a Tertiary Cancer Center in India

This study investigates the impact of Body Mass Index (BMI) on Quality of Life (QoL) and treatment outcomes in breast cancer (BC) patients, particularly focusing on underweight individuals with compromised nutritional status. A nonrandomized prospective study comprising 121 newly diagnosed patients across various BMI categories utilized FACT-B & FACIT-Sp-12 questionnaires. Follow-ups occurred at baseline, during (3rd and 6th), and after (12th month) anthracycline-taxane chemotherapy, either sequentially or concomitantly. Patients with low BMI (<18.5 kg/m2; 53.7%) exhibited significantly poorer QoL, marked by compromised nutritional indicators (low MUAC and SFT). Repeated measures ANOVA identified significant correlations between BMI groups in functional, social, and emotional QoL aspects (p < 0.05), with no notable differences in other domains. A Chi-square (ꭓ2) test underscored a significant link between BMI and treatment response (p < 0.0001), showing higher rates of non-responders among underweight patients (p = 4.259e−14). The study advocates pretreatment consultation with a dietitian as standard care for Indian BC patients, offering complimentary nutritional support for improved QoL outcomes and treatment responses.