HER2-negative Breast Cancer Research Articles

Comparison of clinicopathological characteristics, efficacy of neoadjuvant therapy, and prognosis in HER2-low and HER2-ultralow breast cancer

BackgroundThis study aims to analyze potential differences in clinicopathology, efficacy of neoadjuvant therapy (NAT), and clinical outcome among HER2-null, HER2-ultralow and HER2-low breast cancers.MethodsConsecutive cases of HER2-negative breast cancer that received NAT were included. They were classified as HER2-null (no staining), HER2-ultralow (incomplete faint staining in ≤ 10% of tumour cells) and HER2-low (HER2-1 + or HER2-2+, in situ hybridisation negative). Subgroup analysis was performed based on the HER2 expression level.ResultsOut of 302 patients, 215 (71.19%) were HER2-low, 59 (19.54%) were HER2-ultralow, and 28 (9.27%) were HER2-null. In comparison to the HER2-ultralow group, the HER2-low group exhibited higher expression frequencies of ER (p < 0.001), PR (p < 0.001), and AR (p = 0.004), along with a greater prevalence of the luminal subtype (p < 0.001). The HER2-ultralow group also demonstrated a higher prevalence of lymph node metastasis compared to the HER2-null group (p = 0.026). Varied rates of pathologic complete response (pCR) were observed among the three subgroups: HER2-null, HER2-ultralow, and HER2-low, with rates of 35.71%, 22.03%, and 12.56%, respectively. Only the HER2-low subgroup exhibited a significant difference compared to HER2-null (p = 0.001). Despite variations in pCR rates, the three subgroups exhibited comparable disease-free survival (DFS) (p = 0.571). Importantly, we found HER2-low patients with better treatment response (RCB-0/I) exhibited significantly better DFS than those with significant residual disease (RCB-II/III) (P = 0.036). The overall rate of HER2 immunohistochemical score discordance was 45.24%, mostly driven by the conversion between HER2-0 and HER2-low phenotype. Notably, 32.19% of cases initially classified as HER2-0 phenotype on baseline biopsy were later reclassified as HER2-low after neoadjuvant therapy, and it is noteworthy that 22 out of these cases (78.57%) originally had an HER2-ultralow status in the pretreatment biopsy sample.ConclusionsOur results demonstrate the distinct clinicopathological features of HER2-low and HER2-ultralow breast tumors and confirm that RCB is an effective predictor of prognosis in HER2-low populations for the first time. Notably, our findings demonstrate high instability in both HER2-low and HER2-ultralow expression from the primary baseline biopsy to residual disease after NAT. Furthermore, this study is the first to investigate the clinicopathological feature and the effectiveness of NAT for HER2-ultralow breast cancer.

Eligibility for Adjuvant Cyclin-Dependent Kinase 4/6 Inhibitors in Endocrine Receptor-Positive and HER2-Negative Early Breast Cancer by Age and Type of Surgery

Background: Despite early diagnosis, approximately 20% of patients with ER-positive and HER2-negative breast cancer (BC) will experience disease recurrence. Improved survival has been reported with adjuvant treatment combining cyclin-dependent kinase 4/6 inhibitors with endocrine therapy, in high-risk patients with ER-positive and HER2-negative BC, regardless of age. Older patients have higher rates of ER-positive/HER2-negative BC than younger patients. Methods: In this real-world data analysis, MonarchE and NataLEE high-risk patients accounted for 9.5% and 33% of patients undergoing upfront surgery, respectively. Significantly higher eligibility rates were observed in patients who underwent a mastectomy, &gt;70 years and ≤40 years for adjuvant abemaciclib and ribociclib, and in patients &gt;80 years for ribociclib. Results: Eligibility rates in patients ≤40 years and &gt;80 years who underwent mastectomy were 27.8% and 24.7% for abemaciclib, respectively, and 56.6% and 65.2% for ribociclib, respectively. A higher discontinuation rate for abemaciclib was reported in patients aged ≥65 years and it can be assumed that discontinuation rates may increase in even older patients. Conclusions: If the results of the NataLEE trial translate into clinical practice, the number of patients potentially eligible for adjuvant CDK4/6 inhibitors may increase, especially in the elderly population.

Feature-based detection of breast cancer using convolutional neural network and feature engineering.

Breast cancer (BC) is a prominent cause of female mortality on a global scale. Recently, there has been growing interest in utilizing blood and tissue-based biomarkers to detect and diagnose BC, as this method offers a non-invasive approach. To improve the classification and prediction of BC using large biomarker datasets, several machine-learning techniques have been proposed. In this paper, we present a multi-stage approach that consists of computing new features and then sorting them into an input image for the ResNet50 neural network. The method involves transforming the original values into normalized values based on their membership in the Gaussian distribution of healthy and BC samples of each feature. To test the effectiveness of our proposed approach, we employed the Coimbra and Wisconsin datasets. The results demonstrate efficient performance improvement, with an accuracy of 100% and 100% using the Coimbra and Wisconsin datasets, respectively. Furthermore, the comparison with existing literature validates the reliability and effectiveness of our methodology, where the normalized value can reduce the misclassified samples of ML techniques because of its generality.

Efficacy and prognosis of neoadjuvant chemotherapy in HER2 low-expressing breast cancer: a retrospective single-center study.

Human epidermal growth factor receptor 2 (HER2) is vital for breast cancer prognosis. The aim of this study was to analyze the clinicopathological data of HER2-negative breast cancer patients receiving neoadjuvant chemotherapy and the associated factors affecting the pathological complete response rate (pCR) and prognosis. Clinical data of 173 patients with primary HER2-negative breast cancer, who initially received neoadjuvant chemotherapy followed by surgical treatment at the Breast Surgery Department of Bethune Hospital in Shanxi Province from January 2012 to December 2022, were collected. Compared to HER2-0 patients, HER2-low patients had higher T staging (p = 0.008), higher Ki67 proliferation index (p < 0.001), lower N staging (p = 0.001), and lower pCR rate (p < 0.001). Univariate analysis revealed that T stage, TNM stage, HR status, HER2 status, and Ki67 are risk factors that affect the pCR rate in HER-2 negative. Multivariate analysis identified HR status as an independent predictor of pCR rate. Kaplan-Meier survival curves showed that menstrual status, N staging, T staging, TNM staging, and pCR status affected the prognosis of HER2-low breast cancer patients (p < 0.05). HER2-low breast cancer exhibits distinct biological behaviors, suggesting personalized treatment approaches.

Monitoring the Response of Cyclin-Dependent Kinase 4/6 Inhibitors with Mean Corpuscular Volume.

Currently, the combination of cyclin-dependent kinase 4/6 (CDK4/6) inhibitors and endocrine therapy is a first-line treatment for hormone-receptor-positive and HER2-negative metastatic breast cancer. This study aimed to assess the impact of changes in Mean Corpuscular Volume (MCV) on predicting responses to treatment and survival in patients with hormone-receptor-positive, HER2-negative metastatic breast cancer receiving CDK4/6 inhibitors and endocrine therapy. Retrospectively, data on hemoglobin levels, MCV, B12, folate levels, and survival times were collected from 275 patients. Patients were categorized into two groups based on the degree of MCV change (delta MCV ≤ 10 vs. >10). Kaplan-Meier survival analysis was performed, with significance set at p < 0.05. The average age of the patients was 56.1 ± 12.1 years. In total, 72.7% received CDK4/6 inhibitors as first-line treatment, while 27.3% received them as second-line treatment. Before CDK4/6 inhibitor use, the median MCV level was 87.7 fL (IQR: 83-91), which increased to 98 fL (IQR: 92-103) after treatment (p < 0.001). ECOG performance score, CDK4/6 inhibitor treatment line, type of endocrine therapy, and MCV change were identified as independent predictors of progression-free survival in the Cox regression model. The median progression-free survival for the entire group was 28 months. Patients with MCV delta > 10 had a median progression-free survival of 33 months, compared to 23 months for those with MCV delta ≤ 10 (p = 0.029). There was no significant difference in median overall survival times between the two groups (p = 0.158). This study highlights that patients with MCV delta > 10 had longer median progression-free survival compared to those with MCV delta ≤ 10.

Clinical use of Abemaciclib a cyclin-dependent kinase (CDK) 4/6 inhibitor in patients with breast cancer — literature review

Breast cancer is the most common neoplasma affecting women. Over, the past few years, the incidence of breast cancer has significantly increased, including among young women. Hormone receptor-positive (HR+) Her2 negative (HER2-) early stage breast cancer can be successfully treated using the currently available treatment methods based on endocrine theraphy (ET). However, if we consider early stage breast cancer with high risk of recurrence or metastatic disease, endocrine therapy alone may be insufficient. Unfortunately, resistance to drugs is observed in both adjuvant and palliative endocrine therapy, therefore there is a need for new treatments that are both effective and less toxic than conventional chemotherapy. One of the most successful applications of this strategy has been the use of cyclin-dependent kinase (CDK) 4 and 6 inhibitors alongside endocrine therapy significantly enhance its effectiveness. This combination has been shown to substantially increase progression-free survival while maintaining relatively low levels of toxicity. One of them is abemaciclib, whose efficacy will be shown in this research work.

Hybrid ensemble deep learning model for advancing breast cancer detection and classification in clinical applications

Being the most common type of cancer worldwide, and affecting over 2.3 million women, breast cancer poses a significant health threat. Although survival rates have improved around the world due to advances in screening, diagnosis, and treatment, early detection remains crucial for effective management. This study seeks to introduce a novel hybrid model that makes use of image-preprocessing techniques and deep-learning algorithms on mammograms to enhance the detection and classification accuracy of breast cancer lesions. The model was tested on a dataset comprising 20,000 mammograms. First, image-processing techniques, such as Contrast-Limited Adaptive Histogram Equalization, Gaussian Blur, and sharpening methods were used to optimize the images for enhanced feature extraction. In addition, the Ensemble Deep Random Vector-Functional Link Neural Network algorithm, YOLOv5, and MedSAM segmentation models were utilized for robust deep learning-based extraction, classification, and visualization of lesions. Finally, the model was clinically validated on 800 patients. The study found a notable enhancement in both accuracy and processing time for benign and malignant diagnoses using the hybrid model. The model achieves an impressive accuracy of 99.7 % and demonstrates a remarkable processing time of 0.75 s. In clinical applications, the hybrid model exhibits high proficiency, reporting 97.2 % accuracy for benign cases and 98.6 % for malignant scenarios. These results highlight the effectiveness of the hybrid model in improving diagnostic accuracy, offering a promising tool for early breast cancer detection.

Fulvestrant en la práctica clínica: análisis de efectividad en pacientes uruguayas con cáncer de mama HR+/HER2.

Fulvestrant demonstrated benefits in overall survival and progression-free survival in patients with advanced breast cancer, who are hormone receptor-positive and human epidermal growth factor receptor 2 negative. The characteristics, evolution, and survival of patients with hormone receptor-positive, HER2-negative breast cancer treated with fulvestrant were evaluated according to the national treatment coverage protocols of the National Resources Fund, with the aim of understanding the efficacy of fulvestrant in patients treated in usual clinical practice and comparing our results with those from pivotal studies. A database from the National Resources Fund covering the period from 2009 to 2022 was used. Survival curves were assessed using the Kaplan-Meier method, and differences were analyzed using the Log-Rank test. A total of 1085 patients with an average age of 63,66 years were included. Following a follow-up of 14 months, the median overall survival was 16 months, and the median progression-free survival was 6 months. The presence of liver and bone metastases was associated with a shorter overall survival. Patients from the public sector and those with a better performance status experienced longer overall survival. Our findings provide a valuable perspective for treatment management in a context of limited resources. Overall survival and progression-free survival were somewhat lower than those reported in pivotal clinical trials. The presence of liver and bone metastases was associated with worse prognosis and survival; additionally, patients with worse performance status had shorter overall survival. These findings underscore the need for personalized therapies, opening new lines of future research.

Comparison of Risk Stratification by CanAssist Breast Test Performed on Core Needle Biopsies Versus Surgical Specimens in Hormone Receptor-Positive, Her2-Negative Early Breast Cancer.

Introduction Core needle biopsies (CNB) are being increasingly utilized for biomarker, prognostic, and predictive testing in breast cancer (BC).CanAssist Breast (CAB) is a prognostic test performed to assess the 'risk of breast cancer recurrence' in early-stage hormone receptor-positive, Her2-negative BC patients. CAB segregates tumors as 'low risk' or 'high risk' for distant recurrence.Risk assessment done by CAB aids in planning and making adjuvant chemotherapy or hormone therapy decisions.CAB is typically performed on surgical specimens (SS).However, performing it on CNB does offer additional insights into tumor biology leading to different strategies for treatment planning; hence, we aimed to compare the risk stratification performance of CAB using CNB versus SS. Method We analyzed 103 paired formalin-fixed paraffin-embedded CNB and SS samples from hormone receptor-positive, Her2-negative early BC tissue samples submitted for performing CAB at OncoStem Diagnostics between November 2021 and September 2023. Concordance on 'risk categories' of CAB performed on CNB versus SS was reported using overall percentage agreement and Pearson correlation coefficient. Results We found excellent overall concordance of 92.2% for CAB risk stratification between paired CNB and SS tumor samples with a strong Pearson correlation coefficient of r= 0.8351 (p< 0.0001) when either SS or CNB was used as the gold standard.In prognostic testing patients with a 'low risk' of recurrence may avoid chemotherapy and hence it is crucial to assess the accuracy of CAB in the low-risk category. Additionally, in a real-world scenario, it is more likely that CAB will be performed on CNB first. Conclusion CAB when performed on CNB samples showed high concordance with SS thus demonstrating that CNB was a suitable sample for the CanAssist Breast test.The accuracy in the low-risk category is 97.5%, which ensures that physicians can reliably use prognostic information by testing CNB to guide adjuvant therapy decisions.

Abstract B006: Reduced survival outcomes in lower income quintile groups for women with breast cancer treated with chemotherapy in Ontario, Canada

Abstract Background: Despite the comparably comprehensive healthcare system in Canada, health inequities are widespread, and this holds true for breast cancer patients in Ontario. It is thus essential to learn if socio-demographic disparities continue after diagnosis of breast cancer, and if these contribute to higher mortality rates in the lower income quintile groups. Methods: We conducted a real-word population-based study using a provincial health administrative dataset from Ontario, Canada. We included patients diagnosed with HER2-negative breast cancer, treated with surgery and adjuvant chemotherapy, between 2009 to 2017. We used log-rank test and Kaplan Meier curves to compare overall survival (OS) between breast cancer populations among income quintile groups, and Cox regression to evaluate risk factors, using hazard ratio (HR) and 95% confidence intervals (CI). Results: We analysed 10,634 women diagnosed with stage I-III breast cancer. At diagnosis, in the Q1 group, there were 248 (15.8%) women with stage I, 997 (63.7%) with stage II, and 320 (20.45%) with stage III. In the Q5 group, there were 568 (22.15%), with stage I, 1,532 (59.75%) with stage II and 464 (18%) with stage III. Comparison between those in the lowest versus highest income quintile groups, and lymph node (LN) status at diagnosis, showed that in Q1, 534 (34%) women had LN 0 and 897 (57.3%) had LN+. In Q5, there were 954 (37.2%) women with LN 0 and 1,379 (53.8%) with LN+. Similarly, comparing tumor size (TS) at diagnosis, we found that in Q1, there were 463 (32.2%) women with TS≤ 2 cm and 974 (67.8%) with TS &amp;gt; 2 cm. In Q5, 915 (39%) women had TS≤ 2 cm and 1,426 (61%) had TS &amp;gt; 2 cm. In the Q1 group, there were 325 (20.7%) patients who received non- anthracycline and 1,240 (79.3%) treated with anthracycline-taxane chemotherapy. In Q5, there were 673 (26.2%) women treated with non-anthracycline and 1,891 (73.8%) who received anthracycline-taxane chemotherapy. The OS analysis based on the household income group compared to Q5 showed a substantial difference in the Q1 (HR 1.52, 1.2–1.9, p = 0.0002) and Q2 (HR 1.34, 1.1–1.7, p = 0.006) groups. In Cox regression models, Q5 group and endocrine receptor (ER) positive were significantly associated with reduced mortality risk. There was a significant correlation between increased risk of death and the following: receipt of non- anthracycline chemotherapy, TS &amp;gt; 2 cm, LN+ and grade 3 histology. Conclusion: Our study found an uneven distribution of breast cancer patients between the lowest and highest income quintile groups. Women with HER2-negative breast cancer who were part of the lower income quintile groups, thereby likely with a socioeconomic disadvantage, had the lowest OS. At diagnosis, these women were more likely to have more advanced breast cancer staging, including larger tumors, LN+, and receive anthracycline-based chemotherapy as compared to those with higher household income. Further research is warranted to identify the key social determinants that are systematically associated with disparities in equitable access to care. Citation Format: Danilo Giffoni M. M. Mata, Rossanna C. Pezo, Kelvin K.W. Chan, Ines Menjak, Andrea Eisen, Maureen Trudeau. Reduced survival outcomes in lower income quintile groups for women with breast cancer treated with chemotherapy in Ontario, Canada [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr B006.

Regional lymph node changes on breast MRI in patients with early-stage breast cancer receiving neoadjuvant chemo-immunotherapy

Abstract Purpose Establishing breast MRI imaging patterns associated with neoadjuvant immunotherapy is needed to monitor response. We analyzed serial breast MRIs in patients receiving neoadjuvant chemo-immunotherapy on the I-SPY2 clinical trial. Methods Patients with stage 2–3 HER2-negative breast cancer were randomized to weekly paclitaxel (control), weekly paclitaxel and pembrolizumab, or weekly paclitaxel, pembrolizumab and intra-tumoral injection of SD-101, a TLR9 agonist. All patients received AC. Regional lymph nodes were retrospectively evaluated on breast MRI at baseline, 3, 12 and 20 weeks by a single blinded radiologist. MRIs were assessed for development of new regional lymphadenopathy, or increase in the longest diameter or cortical thickness of the largest abnormal regional lymph node. Results Between 12/2015 and 4/2021, a total of 43 patients enrolled in the control (n = 16) and paclitaxel + pembrolizumab ± SD-101 (n = 27) arms. 12 of 27 patients (44.4%) receiving chemo-immunotherapy experienced increased lymphadenopathy within the first 12 weeks compared to 1 of 16 patients (6.3%) in the control group (p = 0.014). Most patients with increased lymphadenopathy were in the SD101/pembro arm (n = 10, p = 0.002). Increased lymphadenopathy was observed despite concomitant decrease in breast tumor size at all time points. 11 of 12 patients with increased lymphadenopathy had pathologically negative nodes at surgery. There was no association between lymphadenopathy and lower residual cancer burden or immune-related toxicity. Conclusions The combination of neoadjuvant paclitaxel and pembrolizumab ± SD101 intratumoral injection was associated with early increases in regional lymphadenopathy on MRI despite decreased breast tumor size. Increased lymphadenopathy was not associated with node positive disease at surgery.

Canadian Expert Recommendations on Safety Overview and Toxicity Management Strategies for Sacituzumab Govitecan Based on Use in Metastatic Triple-Negative Breast Cancer.

Sacituzumab Govitecan (SG) is an antibody-drug conjugate (ADC) comprised of an anti-Trop-2 IgG1 molecule conjugated to SN-38, the active metabolite of irinotecan, via a pH-sensitive hydrolysable linker. As a result of recent Canadian funding for SG in advanced hormone receptor (HR)-positive breast cancer and triple-negative breast cancer (TNBC), experience with using SG and managing adverse events (AEs) has grown. This review presents a summary of evidence and adverse event recommendations derived from Canadian experience, with SG use in metastatic TNBC for extrapolation and guidance in all indicated settings. SG is dosed at 10 mg/kg on day 1 and day 8 of a 21-day cycle. Compared to treatment of physicians' choice (TPC) the phase III ASCENT and TROPiCS-02 studies demonstrated favorable survival data in unresectable locally advanced or metastatic TNBC and HR-positive HER2 negative metastatic breast cancer, respectively. The most common AEs were neutropenia, diarrhea, nausea, fatigue, alopecia, and anemia. This review outlines AE management recommendations for SG based on clinical trial protocols and Canadian guidelines, incorporating treatment delay, dose reductions, and the use of prophylactic and supportive medications.

Abstract C152: Improving Access to Genetic Services for Women with Breast Cancer from Underserved Communities in California: Design and Implementation of a Community- Engaged Program

Abstract This study aims to understand the barriers to genetic services uptake at the patient, provider, and healthcare system levels, and to develop a multi-level intervention to increase access and suitability to genetic services for women from minority and medically underserved populations in California who have been recently diagnosed with breast cancer. Germline-informed cancer screening has been found to improve breast cancer survival and help identify close relatives who may have an inherited mutation that increases their susceptibility to cancer. However, only 26% of women diagnosed with breast cancer reported having germline genetic testing; marginalized populations are less likely to receive these services (Kurian et al., 2023). Using Levesque’s Conceptual Framework (Lévesque et al., 2013) and Implementation Mapping (Fernández et al., 2019), we are iteratively developing a multi-level program to explore the role that Community Health Workers (CHWs)/Promotoras can play in reducing access disparities to genetic services. Eleven CHWs/Promotoras have completed 80 hours of CHW training, 7 hours of mental health, insurance and group facilitation training, and 14 hours of cancer health training. CHWs/Promotoras have established local community breast cancer groups in their local communities across California’s Central Valley and are participating in and organizing breast cancer health fairs in their communities in partnership with Community Based Organizations (CBOs). Identifying and addressing the barriers to genetic services is critical to reducing access disparities to genetic services for underserved populations. CHWs/Promotoras are a promising resource to help reduce existing disparities in genetic services for women diagnosed with breast cancer. Citation Format: Iñigo Verduzco Gallo, Nanci Chavarria Villa, Angelica Rolon, Guadalupe Carvajal, Ana P. Estrada-Florez, Luis G Carvajal-Carmona. Improving Access to Genetic Services for Women with Breast Cancer from Underserved Communities in California: Design and Implementation of a Community- Engaged Program [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr C152.

Abstract C062: Racial and ethnic disparities in risk of second primary non-breast cancer in breast cancer survivors

Abstract Purpose: Disparities in cancer outcomes are multifactorial and are attributed to differences in access to care, socioeconomic status, tumor characteristics, treatment, family history, and comorbidity burden. Studies evaluating disparities in breast cancer outcomes have mostly been restricted to Black and White patients. Additionally, whether racial and ethnic disparities affect the risk of second primary cancer in breast cancer survivors, remains under-studied. We evaluated disparities in risk of second primary non-breast cancer in a racially and ethnically diverse cohort of breast cancer survivors treated at an integrated healthcare system. Methods: This retrospective cohort study included 37,222 breast cancer patients (aged ≥18 years) diagnosed between 2008-2020 at Kaiser Permanente Southern California (KPSC). Data on tumor characteristics, cancer treatments and sociodemographic variables were extracted from KPSC’s cancer registry and electronic health records. Patients were followed electronically from breast cancer diagnosis until they developed second primary non-breast cancer, died, disenrolled from the health plan, or reached study’s end (12/31/2021), whichever occurred first. Cox proportional hazards regression was used to report the association [Hazard Ratio (95% Confidence Interval)] between race and ethnicity and second primary non-breast cancer. Results: More than half of the study cohort consisted of non-Hispanic White survivors (51.2%), followed by 20.9% Hispanic survivors, 13.9% Asian/Pacific Islander (API) survivors, 12.7% non-Hispanic Black survivors, and 1.3% survivors of other/mixed races. Overall, 55.7% and 23.9% were diagnosed with local and regional breast cancer, respectively. During a median follow-up of 5.2 years, 4.6% survivors developed second primary non-breast cancers. In the multivariable model adjusted for sociodemographic characteristics, breast tumor characteristics, and breast cancer treatments, Hispanic and API survivors were 25% and 28% less likely to develop second primary cancer compared to White survivors [adjusted HR (95%CI): 0.75 (0.65-0.86)] and 0.72 (0.61-0.86), respectively]. We did not find an increased risk in Black survivors compared to White survivors [adjusted HR (95%CI): 0.91 (0.78-1.04)]. However, factors related to higher risk of second primary non-breast cancers were older age at breast cancer diagnosis, smoking, and higher comorbidity burden. Conclusion: Interestingly, risk of second primary non-breast cancer was lower in Hispanic and API survivors compared to White survivors in this insured cohort. Next steps will include examining which lifestyle factors (e.g. less smoking), or if pharmacological management of modifiable comorbidities might have played a role in the decreased risks seen in these two racial and ethnic groups. Citation Format: Amrita Mukherjee, Zheng Gu, Lie H. Chen, Reina Haque. Racial and ethnic disparities in risk of second primary non-breast cancer in breast cancer survivors [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr C062.

Abstract C101: Shared gene expression pattern among breast cancer subtypes and its association with prognostic variables in Colombian patients

Abstract Introduction: The current molecular classification of breast cancer has significantly improved treatment targeting and disease prognosis. However, the heterogeneity among subtypes also poses a limitation when proposing new targets that integrate common biological processes, hindering their applicability across the entire spectrum of the disease. In that sense, it is essential to gain a deeper understanding of the similarities and common mechanisms involved in the molecular subtypes of breast cancer. Therefore, in this study, we aimed to identify shared differentially expressed genes (DEGs) and biological processes among the different breast cancer subtypes that could potentially impact the presentation of clinically significant variables in Colombian patients diagnosed at the National Cancer Institute (NCI). Methods: We included 97 women diagnosed with breast cancer at the NCI in Colombia. From each patient, we collected tumor biopsy and adjacent non-tumoral tissue for RNA extraction and sequencing (RNA-seq). A comparative analysis of DEGs and gene set enrichment (GSE) was performed between tumor tissue and its corresponding adjacent non-tumor tissue for each subtype independently to identify common DEGs and enriched biological processes. Shared over- and under-expressed genes in at least two subtypes were tested for their association with clinically significant prognostic variables. Results: Among breast cancer subtypes, ER-/HER2+ and ER-/HER2- tumors showed the highest number of shared DEGs (22 genes), of which 19 were over-expressed and 3 under-expressed. In contrast, GSE analysis revealed a high proportion of shared biological processes (5), molecular functions (3), and cellular component classification (11) between ER+/HER2+ and ER-/HER2+ tumors, corresponding to mechanisms involved in tissue homeostasis and extracellular matrix structural constituents. Furthermore, the association with clinically significant prognostic variables was assessed for 22 over-expressed genes and 9 under-expressed genes shared in at least two subtypes. Of this set of 31 genes, 9 were significantly associated with the degree of tumor differentiation measured by the Bloom-Richardson (BR) score. Interestingly, tumor suppressor genes like ADAMTS18 showed a decline in expression as the BR score increased (fold-change (FC) in BR I: 14 vs BR II: 11; BR III: 5, p-value: 0.028). Conversely, oncogenes like EFNA4 showed the opposite trend, with an increase in expression as the BR score also increased (FC in BR I: 9 vs. BR II: 11 vs. BR III: 17, p-value: 0.019). Another identified shared over-expressed gene, JPT1, which is involved in β-catenin signaling, was found to be associated not only with higher BR scores but also with a higher proliferation index Ki67 (FC in &amp;lt;20%: 16.5 vs. ≥20%: 23; p-value: 0.05). Conclusions: Despite the high degree of molecular heterogeneity among subtypes, it is still possible to identify shared over and under-expressed genes in at least 2 subtypes with significant prognostic implications in breast cancer subtypes. Citation Format: Laura Rey-Vargas, Lina Maria Bejarano, Diego Felipe Ballen-Lozano, Silvia J. Serrano-Gomez. Shared gene expression pattern among breast cancer subtypes and its association with prognostic variables in Colombian patients [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr C101.

Review of In Situ Hybridization (ISH) Stain Images Using Computational Techniques.

Recent advancements in medical imaging have greatly enhanced the application of computational techniques in digital pathology, particularly for the classification of breast cancer using in situ hybridization (ISH) imaging. HER2 amplification, a key prognostic marker in 20-25% of breast cancers, can be assessed through alterations in gene copy number or protein expression. However, challenges persist due to the heterogeneity of nuclear regions and complexities in cancer biomarker detection. This review examines semi-automated and fully automated computational methods for analyzing ISH images with a focus on HER2 gene amplification. Literature from 1997 to 2023 is analyzed, emphasizing silver-enhanced in situ hybridization (SISH) and its integration with image processing and machine learning techniques. Both conventional machine learning approaches and recent advances in deep learning are compared. The review reveals that automated ISH analysis in combination with bright-field microscopy provides a cost-effective and scalable solution for routine pathology. The integration of deep learning techniques shows promise in improving accuracy over conventional methods, although there are limitations related to data variability and computational demands. Automated ISH analysis can reduce manual labor and increase diagnostic accuracy. Future research should focus on refining these computational methods, particularly in handling the complex nature of HER2 status evaluation, and integrate best practices to further enhance clinical adoption of these techniques.

Effectiveness of combined targeted and hormonal therapies for post-menopausal women with hormone receptor-positive and HER2-negative advanced breast cancer: A systematic review and meta-analysis of RCTs.

we aim to synthesize available evidence on the effectiveness of hormonal plus targeted therapies for post-menopausal women with hormone receptor-positive and HER2-negative advanced breast cancer. We searched the following databases: Medline, PubMed, Cochrane Library, CINAHL, Web of Science, Scopus, and African Journal. Only studies that investigated the effectiveness of hormonal therapy combined with targeted therapy for HR+/HER2- advanced breast cancer treatment were included. The outcomes were progression-free survival (PFS), overall survival (OS) and objective response rate (ORR). A random-effect meta-analysis model was employed. Statistical analysis was performed using Comprehensive Meta-analysis version 3. 24 studies were included in the meta-analysis with an overall sample size of 7635. Median PFS, OS and ORR were found to be significantly increased in the combination group compared to hormonal monotherapy [SMD = 6.072 (95% CI = 3.785-8.360), p < 0.001], [SMD = 1.614 (95% CI = 0.139-3.089), p = 0.032] and [OR = 1.584 (CI 1.134-2.213), p = 0.007] respectively. Subgroup analysis showed a significant difference in PFS and ORR between patients who received "hormonal therapy + CDK4/6 inhibitors" vs hormonal therapy only [SMD = 6.015 (CI 3.069-8.960), p < 0.001], (OR = 1.828 (CI 1.030-3.243), p = 0.039] respectively. Compared with hormonal monotherapy, targeted plus hormonal therapy significantly improves PFS, OS and ORR in postmenopausal women with HR+/HER2- advanced breast cancer.

Alginate-functionalized and 4T1 cell membrane-coated multi-tasking nanoparticulate system for near-infrared-triggered photodynamic therapy on breast cancer: In vitro cellular and in vivo mice models

Recently, combination treatment of chemo-dynamic therapy (CDT) and photodynamic therapies (PDT) is well-known and prominent therapeutic strategy for breast tumor. Importantly, tailored nanomedicines with unique personalized properties including nanocarrier suitability and effective targeting ability that requires the exhaustive understanding of tumor microenvironment. Recently, researchers have designed a smart upconversion nanoparticles (UCNPs) that have unique characteristics to achieve targeting for respond tumor microenvironment. In the present study, we first time fabricated a novel combination of oxidized sodium alginate-enveloped and 4T1 cancer cell membrane-coated up-conversion nanoparticles (4TUCNP@SMZ) were engineered for breast cancer-targeted therapy. The nanoparticles could be formed via electrostatic interaction, which showed excellent biocompatibility, increased cellular uptake with normal and cancer cells. The fabricated Alginate and 4T1-membrane functionalized up-conversion nanoparticles significantly benefitted to targeted delivery system for local breast cancer and prominently inhibit tumor development via chemo-dynamic therapy (CDT) and PDT. The greater susceptibility of tumor cells to oxidative stress may also result from the depletion of intracellular GSH by the 4TUCNP@SMZ nanoparticles. The in vitro cell models (4T1 and MCF-7), in vivo tumor model and histological observation demonstrated that 4TUCNP@SMZ nanoparticles effectively targeted to breast tumor microenvironment and inhibit breast cancer cells. This report suggested that multifunctional Alginate-functionalized nanoparticles are a versatile agent for phototherapy for breast cancer treatment.

Computer-aided diagnosis of breast cancer from mammogram images using deep learning algorithms

Even though accurate detection of dangerous malignancies from mammogram images is mostly dependent on radiologists' experience, specialists occasionally differ in their assessments. Computer-aided diagnosis provides a better solution for image diagnosis that can help experts make more reliable decisions. In medical applications for diagnosing cancerous growths from mammogram images, computerized and accurate classification of breast cancer mammogram images is critical. The deep learning approach has been widely applied in medical image processing and has had considerable success in biological image classification. The Convolutional Neural Network (CNN), Inception, and EfficientNet are proposed in this paper. The proposed models attain better performance compared to the conventional CNN. The models are used to automatically classify breast cancer mammogram images from Kaggle into benign and malignant. Simulation results demonstrated that EfficientNet, with an accuracy between 97.13 and 99.27%, and overall accuracy of 98.29%, perform better than the other models in this paper.

Absolute lymphocyte count predicts efficacy of palbociclib in patients with metastatic luminal breast cancer

BackgroundAbsolute lymphocyte count (ALC) is a predictive and prognostic factor for various tumor types, including breast cancer. Palbociclib is a CDK4/6 inhibitor widely used for the treatment of metastatic estrogen receptor (ER)-positive, HER2-negative breast cancer. However, predictive biomarkers of the efficacy of palbociclib remain unelucidated. We conducted a retrospective study to examine the predictive value of the baseline ALC in patients treated with palbociclib.MethodsThe medical records of patients with ER-positive, HER2-negative breast cancer treated with palbociclib plus hormonal therapy between December 2017 and December 2021 were analyzed retrospectively. The cutoff value of ALC was set at 1800 cells/μL at the initiation of palbociclib treatment. The clinical benefit rate (CBR) was defined as the rate of complete or partial response or stable disease for at least 6 months. Progression-free survival (PFS) rates were estimated using the Kaplan–Meier method and compared using the log-rank test. Univariate and multivariate analyses were performed using Cox proportional hazards regression.ResultsAll of the 202 patients were women, with a median age of 59 years and a performance status (PS) of ≤ 2. The median numbers of lines of chemotherapy and endocrine therapy before palbociclib treatment were 0 (range, 0–9) and 1 (range, 0–7), respectively. Fifty-one patients had liver metastases. Forty-six patients tested negative for progesterone receptor (PgR) expression. The median follow-up time was 9.1 months. The CBR was significantly higher in the ALC-high group than in the ALC-low group (79% vs. 60%; P = 0.018). The median PFS was significantly longer in the ALC-high group than in the ALC-low group (26.8 months vs. 8.4 moths, respectively; P = 0.000013). ALC, age, PS, PgR status, prior chemotherapy, prior endocrine therapy, and liver metastasis were entered into the multivariate analysis. ALC was identified as an independent factor for PFS (P = 0.00085), along with liver metastasis (P = 0.0020), PS (P = 0.026), and prior endocrine therapy (P = 0.019).ConclusionALC can serve as a predictor of palbociclib efficacy in patients with metastatic ER-positive, HER2-negative breast cancer.