Therapy In Breast Cancer Patients Research Articles

The use of longitudinal CT-based radiomics and clinicopathological features predicts the pathological complete response of metastasized axillary lymph nodes in breast cancer

BackgroundAccurate assessment of axillary status after neoadjuvant therapy for breast cancer patients with axillary lymph node metastasis is important for the selection of appropriate subsequent axillary treatment decisions. Our objectives were to accurately predict whether the breast cancer patients with axillary lymph node metastases could achieve axillary pathological complete response (pCR).MethodsWe collected imaging data to extract longitudinal CT image features before and after neoadjuvant chemotherapy (NAC), analyzed the correlation between radiomics and clinicopathological features, and developed models to predict whether patients with axillary lymph node metastasis can achieve axillary pCR after NAC. The clinical utility of the models was determined via decision curve analysis (DCA). Subgroup analyses were also performed. Then, a nomogram was developed based on the model with the best predictive efficiency and clinical utility and was validated using the calibration plots.ResultsA total of 549 breast cancer patients with metastasized axillary lymph nodes were enrolled in this study. 42 independent radiomics features were selected from LASSO regression to construct a logistic regression model with clinicopathological features (LR radiomics-clinical combined model). The AUC of the LR radiomics-clinical combined model prediction performance was 0.861 in the training set and 0.891 in the testing set. For the HR + /HER2 − , HER2 + , and Triple negative subtype, the LR radiomics-clinical combined model yields the best prediction AUCs of 0.756, 0.812, and 0.928 in training sets, and AUCs of 0.757, 0.777 and 0.838 in testing sets, respectively.ConclusionsThe combination of radiomics features and clinicopathological characteristics can effectively predict axillary pCR status in NAC breast cancer patients.

Assessment of Chemotherapy-Induced Cardiac Dysfunction in Breast Cancer Patients: A Prospective Study.

Background Advances in cancer treatment have markedly improved survival rates but have also heightened morbidity due to treatment-related side effects. Despite this, the literature remains scarce on predicting the incidence of acute cardiac toxicity resulting from chemotherapy. We conducted a prospective evaluation to assess the incidence, timing, clinical correlates, global longitudinal strain (GLS), and response to heart failure (HF) therapy in patients experiencing cardiotoxicity. Aims and objectives Our study aimed to assess the cardiovascular complications of cancer therapy in breast cancer patients, with particular emphasis on therapy-related cardiac dysfunction. Materials and methods We conducted a prospective observational study to detect chemotherapy-related cardiac dysfunction (CTRCD) in breast cancer patients attending the outpatient department (OPD) or admitted to Dayanand Medical College and Hospital (DMCH), Ludhiana, Punjab, between March 1, 2020, and October 31, 2021. We assessed left ventricular ejection fraction (LVEF) at baseline, mid-chemotherapy, and post-chemotherapy. Patients who developed left ventricular dysfunction (LVD) had their chemotherapy regimen modified and were initiated on HF therapy. Results Ninety-seven patients (mean age: 50.74±10.30 years) were enrolled and categorized into the LVD group (n=13) and non-LVD group (n=84). CTRCD developed in 13 patients (13.4%). Patients with estrogen receptor (ER) positive, progesterone receptor (PR) positive, and human epidermal growth factor receptor 2 (HER2) positive status, as well as those in cancer stages III and IV, are at higher risk of developing LV dysfunction. Among the 13 patients, 10 (77%) experienced complete recovery, while three (23%) had partial recovery. Markers for partial recovery included cancer stages III-IV, younger age, lower body mass index (BMI), lower radiotherapy dosage, lower mean chemotherapy dosage, and left breast involvement. Conclusion Our findings suggest that acute cardiotoxicity is not linked to the cumulative dose of anthracyclines. Early detection, modification of chemotherapy regimens, and prompt initiation of CTRCD therapy can lead to substantial recovery of cardiac dysfunction.

Predictive Factors of Neoadjuvant Chemotherapy Response in Breast Cancer Validated by Three Anatomopathological Scores: Residual Cancer Burden, Chevallier System, and Tumor-Infiltrating Lymphocytes.

The aim of this retrospective, observational, descriptive study was to identify predictors of response to neoadjuvant therapy in breast cancer patients and to validate them using three anatomopathological scores, such as residual cancer burden (RCB) score, Chevallier system, and tumor-infiltrating lymphocytes (TIL) score. We conducted a study on 88 female patientsaged 37 to 78 years with confirmed breast cancerwho were indicated for neoadjuvant chemotherapy. We analyzed different individual variables (such as age, menarche, and menopause), clinical/imaging characteristics of the breast tumor and axillary nodes, immunohistochemical biomarkers (such as ER/PR/HER2 and Ki67), and histopathological features (such as subtype and grading) in relation to three anatomopathological scores calculated based on the surgical resection specimen. The percentage of patients who could have benefited from conservative surgery increased from 6% at the time of diagnosis to 20% post-primary systemic therapy (PST). Age under 49 (p = 0.01), premenopausal status (p < 0.01), no special type (NST) (p = 0.04), high Ki67 (p < 0.01), triple-negative breast cancer (TNBC) (p = 0.02) are positive predictive factors of neoadjuvant therapy, whilelobular/mixt carcinoma-type (p = 0.04), luminal A (p = 0.01), positive lymph node (p < 0.01), and low differentiation grade (p = 0.01) are negative predictive factors for the response to PST. There is a strong correlation between the RCB score and the Chevallier system for quantifying the response to PST, with most predictive factors being confirmed through appropriate statistical analysis for both.TIL score values correlated with only some of the predictors, most likely due to the importance of calculating this score on both biopsy specimens at diagnosis and resection specimens after chemotherapy.

Determining individual suitability for neoadjuvant systemic therapy in breast cancer patients through deep learning.

The survival advantage of neoadjuvant systemic therapy (NST) for breast cancer patients remains controversial, especially when considering the heterogeneous characteristics of individual patients. To discern the variability in responses to breast cancer treatment at the individual level and propose personalized treatment recommendations utilizing deep learning (DL). Six models were developed to offer individualized treatment suggestions. Outcomes for patients whose actual treatments aligned with model recommendations were compared to those whose did not. The influence of certain baseline features of patients on NST selection was visualized and quantified by multivariate logistic regression and Poisson regression analyses. Our study included 94,487 female breast cancer patients. The Balanced Individual Treatment Effect for Survival data (BITES) model outperformed other models in performance, showing a statistically significant protective effect with inverse probability treatment weighting (IPTW)-adjusted baseline features [IPTW-adjusted hazard ratio: 0.51, 95% confidence interval (CI), 0.41-0.64; IPTW-adjusted risk difference: 21.46, 95% CI 18.90-24.01; IPTW-adjusted difference in restricted mean survival time: 21.51, 95% CI 19.37-23.80]. Adherence to BITES recommendations is associated with reduced breast cancer mortality and fewer adverse effects. BITES suggests that patients with TNM stage IIB, IIIB, triple-negative subtype, a higher number of positive axillary lymph nodes, and larger tumors are most likely to benefit from NST. Our results demonstrated the potential of BITES to aid in clinical treatment decisions and offer quantitative treatment insights. In our further research, these models should be validated in clinical settings and additional patient features as well as outcome measures should be studied in depth.

Detecting Metastatic Patterns of Oligometastatic Breast Cancer: A Comparative Analysis of 18F-FDG PET/CT and Conventional CT Imaging.

Metastasis-directed therapy has the potential to improve progression-free and overall survival in oligometastatic disease (OMD). For breast cancer, however, randomized trials have failed so far to confirm this finding. Because the concept of metastasis-directed therapy in OMD is highly dependent on the accuracy of the imaging modality, we aimed to assess the impact of 18F-FDG PET/CT on the definition of OMD in breast cancer patients. Methods: Eighty patients with a total of 150 18F-FDG PET/CT images (between October 2006 and January 2022) were enrolled in this retrospective study at the Technical University of Munich. The inclusion criteria were OMD, defined as 1-5 distant metastases, at the time of 18F-FDG PET/CT. For the current study, we systemically compared the metastatic pattern on 18F-FDG PET/CT with conventional CT. Results: At the time of 18F-FDG PET/CT, 21.3% of patients (n = 32) had a first-time diagnosis of metastatic disease, 40.7% (n = 61) had a previous history of OMD, and 38% (n = 57) had a previous history of polymetastatic disease. In 45.3% of cases, the imaging modality (18F-FDG PET/CT vs. conventional CT) had an impact on the assessment of whether OMD was present. An identical metastatic pattern was observed in only 32% of cases.18F-FDG PET/CT detected additional metastases in 33.3% of cases, mostly in the nonregional lymph node system. Conclusion: The use of 18F-FDG PET/CT had a substantial impact on the definition of OMD and detection of metastatic pattern in breast cancer. Our results emphasize the importance of establishing a standardized definition for imaging modalities in future trials and clinical practices related to metastasis-directed therapy in breast cancer patients.

Efficacy of an aloe vera, chamomile, and thyme cosmetic cream for the prophylaxis and treatment of mild dermatitis induced by radiation therapy in breast cancer patients (the Alantel study)

ObjectivesRadiation-induced dermatitis (RD) is one of the most common toxicities in radiation therapy (RT) patients. Corticosteroids, immunosuppressants, and natural products (NPs) have been used as treatment. The objective was to evaluate the efficacy of a NPs-based cream (Alantel®) to reduce the incidence of RD in women with breast cancer undergoing RT treatment. DesignWe conducted a controlled, randomized, double-blind clinical trial. SettingRadiation Oncology Unit of the Reina Sofía Hospital and 5 Primary Care centers of the Cordoba and Guadalquivir Health District (Spain). InterventionsPatients assigned to the experimental group (GTA) were treated with Alantel, while those in the control group (GTE) were treated with a moisturizer and emollient cream. Main outcome measuresThe primary outcome variable was the incidence of RD. RD-free time, duration of RD, quality of life, and product safety were also assessed. ResultsSeventy patients were included in the study, 35 in the GTA and 35 in the GTE. The incidence of RD was lower in the GTA (71.4%) than in the GTE (91.4%) after 4 weeks of follow-up (RR = 0.78; NNT = 5; p < 0.031). The Skindex-29 questionnaire showed differences in the statement: “My skin condition makes it hard to work or do hobbies” (17.1% in the GTE vs. 2.9% in GTA; p = 0.024). ConclusionsThe higher efficacy of Alantel® compared to the control cream in reducing the incidence of RD in women with breast cancer has been demonstrated.

Assessing Agreement to the Use of Hormone Replacement Therapy for Breast Cancer Patients Experiencing Menopausal Symptoms

Assessing Agreement to the Use of Hormone Replacement Therapy for Breast Cancer Patients Experiencing Menopausal Symptoms

Hubungan Pengetahuan Mengenai Kanker Payudara Dalam Mengelola Kecemasan Dan Pengobatan Komplementer

Objective: The large number of breast cancer sufferers and the lack of knowledge have resulted in many sufferers experiencing excessive anxiety; this is one of the factors for the government to focus more on providing education to the public. Methods: This research design uses a systematic review of data sources obtained from several articles collected by conducting computer searches via Google Scholar of the articles that have been searched. Population and sample from research article entitled Relationship between knowledge about breast cancer and awareness behavior (breast self-examination), description of anxiety and depression in women with breast cancer, Indonesian Journal of Community Empowerment (IJCE) The importance of breast self-examination (SADARI) as an early detection effort Breast cancer, experience of using complementary therapy in breast cancer patients, comparative analysis of the CART algorithm classification with C 4.5 in cases of breast cancer sufferers. Results: The article discusses primarily breast cancer and knowledge about breast cancer so that you can manage anxiety. Early detection of breast cancer can be done using a BSE examination. This examination can easily detect signs of breast cancer. Conclusion: Breast cancer is a deadly cancer and affects many women in Indonesia and even around the world. The BSE examination is an early detection that is easy to carry out, and anxiety in breast cancer sufferers is normal. Patients who are afraid of undergoing surgery prefer complementary therapy, but this therapy takes longer to heal.

Establishment of patient-derived organoids for guiding personalized therapies in breast cancer patients.

Breast cancer has become the most commonly diagnosed cancer. The intra- and interpatient heterogeneity induced a considerable variation in treatment efficacy. There is an urgent requirement for preclinical models to anticipate the effectiveness of individualized drug responses. Patient-derived organoids (PDOs) can accurately recapitulate the architecture and biological characteristics of the origin tumor, making them a promising model that can overtake many limitations of cell lines and PDXs. However, it is still unclear whether PDOs-based drug testing can benefit breast cancer patients, particularly those with tumor recurrence or treatment resistance. Fresh tumor samples were surgically resected for organoid culture. Primary tumor samples and PDOs were subsequently subjected to H&E staining, immunohistochemical (IHC) analysis, and whole-exome sequencing (WES) to make comparisons. Drug sensitivity tests were performed to evaluate the feasibility of this model for predicting patient drug response in clinical practice. We established 75 patient-derived breast cancer organoid models. The results of H&E staining, IHC, and WES revealed that PDOs inherited the histologic and genetic characteristics of their parental tumor tissues. The PDOs successfully predicted the patient's drug response, and most cases exhibited consistency between PDOs' drug susceptibility test results and the clinical response of the matched patient. We conclude that the breast cancer organoids platform can be a potential preclinical tool used for the selection of effective drugs and guided personalized therapies for patients with advanced breast cancer.

Postmastectomy radiation therapy in breast cancer patients with micrometastatic disease in sentinel node dissection: A cohort study and meta-analysis

AimThe potential role of postmastectomy radiation therapy (PMRT) on prognosis in patients with T1-2 breast cancer and micrometastatic disease in sentinel lymph node dissection (SLND) has not yet been established. The aim of this study was to investigate the impact of PMRT on prognosis in patients with T1-2 breast cancer and micrometastatic in SLND. MethodA register- and population-based cohort was utilized by identifying eligible patients on the research database BcBase 3.0. Multivariate Cox regression models were applied for survival outcomes. In addition, a systematic literature review and meta-analysis including all relevant studies on this topic was performed. ResultsIn total, 956 patients fulfilling the inclusion criteria were found through the BcBaSe 3.0 with 237 (25.0 %) receiving PMRT and 719 (75.0 %) not receiving PMRT. No statistically significant differences between the two patient groups in terms of neither breast cancer-specific (adjusted Hazard Ratio (HR): 0.49; 95 % Confidence Interval (CI): 0.14 – 1.73) nor overall survival (adjusted HR: 0.63; 95 % CI: 0.29 – 1.35) was found. In the pooled analyses after literature review, PMRT did not result in better breast cancer-specific (5 studies; pooled HR: 1.06; 95 % CI: 0.88–1.27; I2 = 1 %; low certainty of evidence) or overall survival (6 studies; pooled HR: 1.01; 95 % CI: 0.91–1.13; I2 = 10 %; low certainty of evidence). ConclusionPMRT does not seem to impact survival in patients with T1 or T2 breast cancer with micrometastatic disease in SLND. Considering the low level of evidence and the relatively short follow-up of included studies, caution in interpreting the results into clinical practice is suggested.

Abstract 22: Development and characterization of human tumor specific cytotoxic lymphocytes for preclinical drug development

Abstract Heterogeneity within a tumor allows it to better adapt to changing conditions and can have therefore a negative impact on a patient’s prognosis, response to treatment and overall health. Breast cancer is a highly heterogeneous disease caused by distinct genetic mutations in mammary epithelial cells, resulting in significantly different forms of the disease and a need for highly personalized treatment schemes for patients. Hence, it is important to develop and improve (immuno)therapies for breast cancer patients. Adoptive T-cell therapy with autologous CD8+ cytotoxic T cell lymphocytes (CTL) is a promising method that has already shown promising effects in melanoma patients. Unfortunately, there is almost no information about the use in breast cancer patients. We developed an in vitro protocol to generate tumor-specific CTLs by priming on HER2+ breast cancer cell lines JIMT-1 and SKBR-3. Subsequently, these primed CTLs were tested in 2D and 3D immune cell killing assays in a life cell imaging device in combination with an endpoint viability assay. The activity was compared with unspecific CD8+T cells activated by phytohemagglutinin (PHA) or αCD2/αCD3/αCD28, HER2-peptide specific T cells and HER2-CAR T cells serving as a positive control. We investigated the feasibility to freeze CTLs for use in subsequent studies and validated the relevance of HER2 as the main druggable target in the tumor lines using an siRNA approach. The CTLs were most effective on JIMT-1 in a 3D setting, whereas the SKBR-3 CTLs displayed similar activity in 2D and in 3D. The respective CTLs were tumor line specific, as SKBR-3 CTLs did not kill efficiently the JIMT-1 cells and vice versa. The same CTLs displayed the same efficacy pattern after thawing but less pronounced. Thus, within one experimental set-up it is recommended to use either one. The Her2 knockdown in the target cells reduced the killing activity of the CTLs slightly. However, this effect was not statistically significant proving the importance of CTLs as treatment option as well as neoantigens as targets in drug development. In summary, the CTLs proved to capture the respective tumor heterogeneity showing high killing rates in both SK-BR3 and JIMT-1 being more active than HER2-peptide specific T cells. The availability of CTLs in a preclinical setting facilitates screening approaches for combinational studies. Beyond that they can serve as starting material to develop cancer vaccines and identify highly immunogenic neoantigens. Citation Format: Ina Rohleff, Lea Gröne, Kanstantsin Lashuk, Julia B. Schueler. Development and characterization of human tumor specific cytotoxic lymphocytes for preclinical drug development [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 22.

Abstract 3972: Personalized immune-organoid co-culture system for modeling the anti-tumor immune response in breast cancer patients

Abstract Recent studies have reported the effectiveness of immune checkpoint blockade (ICB) therapy in breast cancer patients. However, only a subset of patients benefits from ICB therapy due to various immunosuppressive mechanisms. The development of personalized predictive models for the anti-tumor immune response is essential to broaden the indication of ICB therapy. Here, we suggest a novel model platform using a co-culture system with patient tumor-derived organoids and matched immune cells to predict the immune response of individual patients. We successfully established fifty-nine cases of patient-derived breast cancer organoids with matched peripheral blood mononuclear cells (PBMCs) (subtype: Luminal A, 18.6%; Luminal B, 28.8%; Triple-negative breast cancer, 35.6%; HER2-positive, 17.0%). Three rapidly proliferating organoids (one Luminal B and two TNBC organoids) were selected to develop an immune-organoid co-culture (IOC) system. To mimic the anti-tumor immune response, cytotoxic immune cells were expanded from PBMCs by modified cytokine-induced killer (CIK) cell expansion protocol utilizing IL-2/IL-15. The CIK cells were co-cultured with patient-derived tumor organoids for killing assay to enable the prediction of ICB responsiveness in vitro. The CIK cells were expanded in the IOC system by stimulation of PBMC with IL-2/IL-15 in the presence of matched tumor organoids for 11 to 14 days. The CIK cells exhibited tumor organoid-specific killing (measured by Caspase-3, 15.22% ± 8.58, mean ± SEM) on organoid co-culture and showed induction of CD107a and CD137 expression in CD8+ T cells and NK cells with the PD-1 blocking antibody. The CIK-mediated tumor organoid deaths and immune cell activation were reduced by HLA class I blocking antibody (W6/32) treatment, confirming HLA-TCR mediated immune response and killing of tumor organoids in the IOC system (-14.85% in organoid-specific lysis and -7.46% in CD107a expression). In the live cell imaging of the IOC system, the interaction between T cells and tumor organoid cells and subsequent induction of Caspase 3 was noted. Our IOC system could directly measure the immunogenic tumor organoid killing by immune cells on ICB treatment in individual breast cancer patients. Moreover, the analysis of immune receptor profiles may reveal immune modulating mechanisms in each patient. We expect the IOC system to serve as a useful platform for personalized immunotherapy and exploration of combinatory therapy to enhance the anti-tumor efficacy of ICB in breast cancer patients. Citation Format: Cheol-Hwa Hong, Won-Ji Ryu, Shinyoung Park, Tae Yeong Kim, Yumi Hwang, Hyunju Han, Seongyeon Jo, Taeyong Kweon, Gun Min Kim, Min Hwan Kim, Hyung Seok Park, Joo Hyuk Sohn. Personalized immune-organoid co-culture system for modeling the anti-tumor immune response in breast cancer patients [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 3972.

Abstract 2014: Tumor glycosylation impacts the efficacy of HER2 targeting therapies

Abstract Cancer progression remains a major obstacle to the successful treatment of cancer. In HER2+ breast cancer, targeting therapies against HER2 have revolutionized the treatment landscape. However, predictive factors for response are largely unknown and a significant number of patients develop resistance. An extensive body of work has revealed a plethora of mechanisms of resistance. However, a key aspect of cancer cells has been largely overlooked: their aberrant glycosylation profile. Aberrant glycosylation of proteins is a hallmark in cancer and has been linked to multiple processes such as invasion, angiogenesis and modulation of the immune response. Yet the influence of altered glycosylation on the efficacy of HER2-targeted therapies remains unknown. Therefore, here, we address this question using clinical data, 3D co-culture systems and advanced live microscopy. Bioinformatics analysis of SPY-2 clinical trial data reveals an association of specific glycogenes with response to HER2-targeting therapies in breast cancer patients. We validated these findings in resistance cell models generated in-vitro and in-vivo using gain and loss of function assays. Furthermore, to provide a more relevant cell model system, we implement the use of 3D co-cultures of cancer spheroids and immune cells. Thus, our research addresses a largely unexplored area in cancer biology combining clinical data from tumor biopsies, trastuzumab-resistant cancer cell models and, live imaging of 3D heterotypic cultures. This work holds the potential to identify new markers of response to therapies and highlights the importance of the interplay of cancer cells and their microenvironment on the efficacy of current treatments. Citation Format: Ana Ruiz-Saenz, Roos Vincken, Denise Wolf, Veronica Steri, Laura van't Veer, John Martens, Danny Huylebroeck, Mark M. Moasser. Tumor glycosylation impacts the efficacy of HER2 targeting therapies [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 2014.

Modeling of Mouse Experiments Suggests that Optimal Anti-Hormonal Treatment for Breast Cancer is Diet-Dependent

Estrogen receptor positive breast cancer is frequently treated with anti-hormonal treatment such as aromatase inhibitors (AI). Interestingly, a high body mass index has been shown to have a negative impact on AI efficacy, most likely due to disturbances in steroid metabolism and adipokine production. Here, we propose a mathematical model based on a system of ordinary differential equations to investigate the effect of high-fat diet on tumor growth. We inform the model with data from mouse experiments, where the animals are fed with high-fat or control (normal) diet. By incorporating AI treatment with drug resistance into the model and by solving optimal control problems we found differential responses for control and high-fat diet. To the best of our knowledge, this is the first attempt to model optimal anti-hormonal treatment for breast cancer in the presence of drug resistance. Our results underline the importance of considering high-fat diet and obesity as factors influencing clinical outcomes during anti-hormonal therapies in breast cancer patients.

Skin perfusion and oxygen saturation after mastectomy and radiation therapy in breast cancer patients

The pathophysiological mechanism behind complications associated with postmastectomy radiotherapy (PMRT) and subsequent implant-based breast reconstruction are not completely understood. The aim of this study was to examine if there is a relationship between PMRT and microvascular perfusion and saturation in the skin after mastectomy and assess if there is impaired responsiveness to a topically applied vasodilator (Methyl nicotinate – MN).Skin microvascular perfusion and oxygenation >2 years after PMRT were measured using white light diffuse reflectance spectroscopy (DRS) and laser Doppler flowmetry (LDF) in the irradiated chest wall of 31 women with the contralateral breast as a control. In the non-irradiated breast, the perfusion after application of MN (median 0.84, 25th–75th centile 0.59–1.02 % RBC × mm/s) was higher compared to the irradiated chest wall (median 0.51, 25th–75th centile 0.21–0.68 % RBC × mm/s, p < 0.001). The same phenomenon was noted for saturation (median 91 %, 25th–75th centile 89–94 % compared to 89 % 25th–75th centile 77–93 %, p = 0.001). Eight of the women (26%) had a ≥10 % difference in skin oxygenation between the non-irradiated breast and the irradiated chest wall.These results indicate that late microvascular changes caused by radiotherapy of the chest wall significantly affect skin perfusion and oxygenation.

273 (PB-089) Poster - Effect of pharmacogenomic polymorphism on hormone therapy for breast cancer patients: systematic review and meta-analysis

273 (PB-089) Poster - Effect of pharmacogenomic polymorphism on hormone therapy for breast cancer patients: systematic review and meta-analysis

Oncovox: A randomised controlled trial of a web-based acceptance and commitment therapy for breast cancer patients

BackgroundiACT interventions can be cost-effective and convenient for providing evidence-based care to breast cancer patients (BCPs). ObjectivesDetermining the feasibility, acceptability, and efficacy of Oncovox, a guided iACT intervention designed to improve psychosocial outcomes in BCP undergoing treatment. MethodsA parallel, two-arm, open-label, randomized controlled trial (RCT) evaluating an 8-module intervention. Participants were randomized to the iACT group (N = 75) or a waitlist group (N = 75). Primary outcomes: Quality of Life (QoL), Behavioral Activation (BA), Symptom Interference (SI) and Reward Noticing (RN). Secondary outcomes: anxiety and depression symptoms and psychological flexibility (PF). Measurements were made pre- and post-intervention, twice during the intervention, and at 1- and 2-month follow-up. ResultsSI, anxiety and depression, and PF improved significantly, with further improvement at follow-up. QoL, BA and RN improved moderately, but only when imputed data were analyzed. ConclusionsOncovox has good dissemination potential and could be appropriately implemented in stepped care.

Discrimination between HER2-overexpressing, -low-expressing, and -zero-expressing statuses in breast cancer using multiparametric MRI-based radiomics.

To explore the performance of multiparametric MRI-based radiomics in discriminating different human epidermal growth factor receptor 2 (HER2) expressing statuses (i.e., HER2-overexpressing, HER2-low-expressing, and HER2-zero-expressing) in breast cancer. A total of 771 breast cancer patients from two institutions were retrospectively studied. Five-hundred-eighty-one patients from Institution I were divided into a training dataset (n1 = 407) and an independent validation dataset (n1 = 174); 190 patients from Institution II formed the external validation dataset. All patients were categorized into HER2-overexpressing, HER2-low-expressing, and HER2-zero-expressing groups based on pathologic examination. Multiparametric (including T2-weighted imaging with fat suppression [T2WI-FS], diffusion-weighted imaging [DWI], apparent diffusion coefficient [ADC], and dynamic contrast-enhanced [DCE]) MRI-based radiomics features were extracted and then selected from the training dataset using the least absolute shrinkage and selection operator (LASSO) regression. Three predictive models to discriminate HER2-overexpressing vs. others, HER2-low expressing vs. others, and HER2-zero-expressing vs. others were developed based on the selected features. The model performance was evaluated using the area under the receiver operating characteristic curve (AUC). Eleven radiomics features from DWI, ADC, and DCE; one radiomics feature from DWI; and 17 radiomics features from DWI, ADC, and DCE were selected to build three predictive models, respectively. In training, independent validation, and external validation datasets, radiomics models achieved AUCs of 0.809, 0.737, and 0.725 in differentiating HER2-overexpressing from others; 0.779, 0.778, and 0.782 in differentiating HER2-low-expressing from others; and 0.889, 0.867, and 0.813 in differentiating HER2-zero-expressing from others, respectively. Multiparametric MRI-based radiomics model may preoperatively predict HER2 statuses in breast cancer patients. The MRI-based radiomics models could be used to noninvasively identify the new three-classification of HER2 expressing status in breast cancer, which is helpful to the decision-making for HER2-target therapies. • Detecting HER2-overexpressing, HER2-low-expressing, and HER2-zero-expressing status in breast cancer patients is crucial for determining candidates for anti-HER2 therapy. • Radiomics features from multiparametric MRI significantly differed among HER2-overexpressing, HER2-low expressing, and HER2-zero-expressing breast cancers. • Multiparametric MRI-based radiomics could preoperatively evaluate three different HER2-expressing statuses and help to determine potential candidates for anti-HER2 therapy in breast cancer patients.

Coronary Flow Velocity Reserve Declines After Anthracycline Therapy in Breast Cancer Patients

Anthracycline therapy (ANT) is associated with cancer therapy-related cardiac dysfunction. Coronary flow velocity reserve (CFVR) has shown prognostic utility in non-cancer cohorts, but no data have been obtained in a cardio-oncology setting. We investigated the acute effect of ANT on CFVR in breast cancer patients. A total of 12 female breast cancer patients undergoing ANT had pre- and post-ANT CFVR assessment. A significant decline in CFVR occurred (baseline: 2.66 ± 0.41 vs post-ANT: 2.47 ± 0.37, P = 0.016). This prospective study is the first to identify ANT-related coronary physiology changes in humans. Further studies are required to determine their clinical significance.

Genomic Features of Homologous Recombination Deficiency in Breast Cancer: Impact on Testing and Immunotherapy.

Genomic instability is one of the well-established hallmarks of cancer. The homologous recombination repair (HRR) pathway plays a critical role in correcting the double-stranded breaks (DSB) due to DNA damage in human cells. Traditionally, the BRCA1/2 genes in the HRR pathway have been tested for their association with breast cancer. However, defects in the HRR pathway (HRD, also termed 'BRCAness'), which has up to 50 genes, have been shown to be involved in tumorigenesis and treatment susceptibility to poly-ADP ribose polymerase inhibitors (PARPis), platinum-based chemotherapy, and immune checkpoint inhibitors (ICIs). A reliable consensus on HRD scores is yet to be established. Emerging evidence suggests that only a subset of breast cancer patients benefit from ICI-based immunotherapy. Currently, albeit with limitations, the expression of programmed death-ligand 1 (PDL1) and tumor mutational burden (TMB) are utilized as biomarkers to predict the favorable outcomes of ICI therapy in breast cancer patients. Preclinical studies demonstrate an interplay between the HRR pathway and PDL1 expression. In this review, we outline the current understanding of the role of HRD in genomic instability leading to breast tumorigenesis and delineate outcomes from various clinical trials. Furthermore, we discuss potential strategies for combining HRD-targeted therapy with immunotherapy to achieve the best healthcare outcomes in breast cancer patients.