Discovery of a proliferation essential gene signature and actin-like 6A as potential biomarkers for predicting prognosis and neoadjuvant chemotherapy response in triple-positive breast cancer.

BACKGROUND: Patients with triple-positive breast cancer (TPBC) have a higher risk of recurrence and lower survival rates than patients with other luminal breast cancers. However, there are few studies on the predictive biomarkers of prognosis and treatment responses in TPBC. METHODS: Proliferation essential genes (PEGs) were acquired from clustered regularly interspaced short palindromic repeats-associated protein 9 (CRISPR-Cas9) technology, and cohorts of patients with TPBC were obtained from public databases and our cohort. To develop a TPBC-PEG signature, Cox regression and least absolute shrinkage and selection operator regression analyses were applied. Functional analyses were performed with gene set enrichment analysis. The relationship between candidate genes and neoadjuvant chemotherapy (NACT) sensitivity was explored via real-time quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC) on the basis of clinical samples. RESULTS: Among 900 TPBC-PEGs, 437 showed significant differential expression between TPBC and normal tissues. Three prognostic PEGs (actin-like 6A [ACTL6A], chaperonin containing TCP1 subunit 2 [CCT2], and threonyl-TRNA synthetase [TARS]) were identified and used to construct the PEG signature. Patients with high PEG signature scores exhibited a worse overall survival and lower sensitivity to NACT than patients with low PEG signature scores. RT-qPCR results indicated that ACTL6A and CCT2 expression were significantly upregulated in patients who lacked sensitivity to NACT. IHC results showed that the ACTL6A protein was highly expressed in patients with NACT resistance and nonpathological complete responses. CONCLUSIONS: This efficient PEG signature prognostic model can predict the outcomes of TPBC. Furthermore, ACTL6A expression level was associated with the response to NACT, and could serve as an important factor in predicting prognosis and drug sensitivity of patients with TPBC.

Unraveling the causal links and novel molecular classification of Crohn's disease in breast Cancer: a two-sample mendelian randomization and transcriptome analysis with prognostic modeling.

BACKGROUND: Crohn's disease (CD), a prominent manifestation of chronic gastrointestinal inflammation, and breast cancer (BC), seemingly disparate in the medical domain, exhibit a shared characteristic. This convergence arises from their involvement in chronic inflammation and immune responses, an aspect that has progressively captivated the attention of investigators but remain controversial. METHODS: We used two-sample Mendelian Randomization (MR) and transcriptomics to explore the relationship between CD and BC. MR assessed causality of CD on different BC subtypes and reverse causality of BC on CD. We identified CD-related differentially expressed genes and their prognostic impact on BC, and developed a new molecular BC classification based on these key genes. RESULTS: MR revealed a causal link between CD and increased BC risk, especially in estrogen receptor-positive (ER+) patients, but not in ER-negative (ER-) cases. BC showed no causal effect on CD. Transcriptomics pinpointed genes like B4GALNT2 and FGF19 that affected BC prognosis in CD patients. A nomogram based on these genes predicted BC outcomes with high accuracy. Using these genes, a new molecular classification of BC patients was proposed. CONCLUSIONS: CD is a risk factor for ER + BC but not for ER- BC. BC does not causally affect CD. Our prognostic model and new BC molecular classifications offer insights for personalized treatment strategies.

The value of oral selective estrogen receptor degraders in patients with HR-positive, HER2-negative advanced breast cancer after progression on ≥ 1 line of endocrine therapy: systematic review and meta-analysis.

BACKGROUND: Currently, the value of oral selective estrogen receptor degraders (SERDs) for hormone receptor-positive (HR+) and human epidermal growth factor receptor 2-negative (HER2-) advanced breast cancer (aBC) after progression on ≥ 1 line of endocrine therapy (ET) remains controversial. We conducted a meta-analysis to evaluate progression-free survival (PFS) and safety benefits in several clinical trials. MATERIALS AND METHODS: Cochrane Library, Embase, PubMed, and conference proceedings (SABCS, ASCO, ESMO, and ESMO Breast) were searched systematically and comprehensively. Random effects models or fixed effects models were used to assess pooled hazard ratios (HRs) and 95% confidence intervals (CIs) for treatment with oral SERDs versus standard of care. RESULTS: A total of four studies involving 1,290 patients were included in our analysis. The hazard ratio (HR) of PFS showed that the oral SERD regimen was better than standard of care in patients with HR+/HER2- aBC after progression on ≥ 1 line of ET (HR: 0.75, 95% CI: 0.62-0.91, p = 0.004). In patients with ESR1 mutations, the oral SERD regimen provided better PFS than standard of care (HR: 0.58, 95% CI: 0.47-0.71, p < 0.00001). Regarding patients with disease progression following previous use of CDK4/6 inhibitors, PFS benefit was observed in oral SERD-treatment arms compared to standard of care (HR: 0.75, 95% CI: 0.64-0.87, p = 0.0002). CONCLUSIONS: The oral SERD regimen provides a significant PFS benefit compared to standard-of-care ET in patients with HR+/HER2- aBC after progression on ≥ 1 line of ET. In particular, we recommend oral SERDs as a preferred choice for those patients with ESR1m, and it could be a potential replacement for fulvestrant. The oral SERD regimen is also beneficial after progression on CDK4/6 inhibitors combined with endocrine therapy.

The immune checkpoint TIGIT/CD155 promotes the exhaustion of CD8 + T cells in TNBC through glucose metabolic reprogramming mediated by PI3K/AKT/mTOR signaling.

OBJECTIVE: The CD155/TIGIT axis has attracted considerable interest as an emerging immune checkpoint with potential applications in cancer immunotherapy. Our research focused on investigating the role of CD155/TIGIT checkpoints in the progression of triple-negative breast cancer (TNBC). METHODS: We evaluated CD155 and TIGIT expression in TNBC tissues using both immunohistochemistry (IHC) and gene expression profiling. Our experiments, both in vivo and in vitro, provided evidence that inhibiting the CD155/TIGIT pathway reinstates the ability of CD8 + T cells to generate cytokines. To assess the impact of CD155/TIGIT signaling blockade, we utilized Glucose Assay Kits and Lactate Assay Kits to measure alterations in glucose and lactate levels within CD8 + T cells. We employed western blotting (WB) to investigate alterations in glycolytic-related proteins within the PI3K/AKT/mTOR pathways following the inhibition of CD155/TIGIT signaling. RESULTS: CD155 exhibits heightened expression within TNBC tissues and exhibits a negative correlation with the extent of infiltrating CD8 + T cells. Furthermore, patients with TNBC demonstrate elevated levels of TIGIT expression. Our findings indicate that the interaction between CD155 and TIGIT disrupts the glucose metabolism of CD8 + T cells by suppressing the activation of the PI3K/AKT/mTOR signaling pathway, ultimately leading to the reduced production of cytokines by CD8 + T cells. Both in vivo and in vitro experiments have conclusively demonstrated that the inhibition of CD155/TIGIT interaction reinstates the capacity of CD8 + T cells to generate cytokines. Moreover, in vivo administration of the blocking antibody against TIGIT not only inhibits tumor growth but also augments the functionality of CD8 + T lymphocytes. CONCLUSIONS: Our research findings strongly suggest that CD155/TIGIT represents a promising therapeutic target for treating TNBC.

Adjuvant chemotherapy and survival in males aged 70 years or older with breast cancer: a population-based retrospective study.

BACKGROUND: Male breast cancer constitutes a minority of breast cancer diagnoses, yet its incidence has been on the rise in recent decades. However, elderly male breast cancer patients have been inadequately represented in clinical trials, posing challenges in treatment decisions. This study seeks to clarify the efficacy of chemotherapy in this demographic and identify the population most likely to benefit from such intervention. METHODS: We conducted a retrospective analysis using the Surveillance, Epidemiology, and End Results (SEER) database, encompassing a total of 1900 male breast cancer patients aged 70 years or older. Among them, 1652 were categorized in the no-chemotherapy group, while 248 were in the chemotherapy group. A multifactorial logistic regression model was employed to investigate the determinants influencing the administration of chemotherapy in elderly male breast cancer patients. Additionally, the multivariate Cox proportional hazards regression model was applied to identify factors associated with outcomes, with overall survival (OS) as the primary endpoint. RESULTS: Multivariate logistic regression analysis revealed that grade, tumor size, and nodal status were robust predictors for elderly male breast cancer patients receiving chemotherapy. Furthermore, the multivariate analysis demonstrated that chemotherapy conferred benefits compared to the no-chemotherapy group (HR = 0.822, 95% CI: 0.682-0.991, p = 0.040). Stratified analyses indicated that individuals with N+, poorly/undifferentiated grade, and stage II/III disease could derive benefits from chemotherapy. Upon further investigation of progesterone receptor (PR) positive patients, it was found that only stage III patients experienced significant benefits from chemotherapy (HR = 0.571, 95% CI: 0.372-0.875, p = 0.010). Conversely, in PR negative patients, both stage II (HR = 0.201, 95% CI: 0.051-0.792, p = 0.022) and stage III patients (HR = 0.242, 95% CI: 0.060-0.972, p = 0.046) derived benefits from chemotherapy. CONCLUSION: Adjuvant chemotherapy may benefit certain elderly male breast cancer patients, specifically those with positive lymph node status, poorly/undifferentiated grade, and PR-positive in stage III, as well as PR-negative expression in stage II/III. Given favorable physical tolerance, it is advisable not to hastily dismiss chemotherapy for these elderly male breast cancer patients.

Predictive model of prognosis index for invasive micropapillary carcinoma of the breast based on machine learning: a SEER population-based study.

BACKGROUND: Invasive micropapillary carcinoma (IMPC) is a rare subtype of breast cancer. Its epidemiological features, treatment principles, and prognostic factors remain controversial. OBJECTIVE: This study aimed to develop an improved machine learning-based model to predict the prognosis of patients with invasive micropapillary carcinoma. METHODS: A total of 1123 patients diagnosed with IMPC after surgery between 1998 and 2019 were identified from the Surveillance, Epidemiology, and End Results (SEER) database for survival analysis. Univariate and multivariate analyses were performed to explore independent prognostic factors for the overall and disease-specific survival of patients with IMPC. Five machine learning algorithms were developed to predict the 5-year survival of these patients. RESULTS: Cox regression analysis indicated that patients aged > 65 years had a significantly worse prognosis than those younger in age, while unmarried patients had a better prognosis than married patients. Patients diagnosed between 2001 and 2005 had a significant risk reduction of mortality compared with other periods. The XGBoost model outperformed the other models with a precision of 0.818 and an area under the curve of 0.863. CONCLUSIONS: A machine learning model for IMPC in patients with breast cancer was developed to estimate the 5-year OS. The XGBoost model had a promising performance and can help clinicians determine the early prognosis of patients with IMPC; therefore, the model can improve clinical outcomes by influencing management strategies and patient health care decisions.

The trade-off of post-mastectomy radiotherapy usage for the breast cancer patients aged 70 years or older: a study based on SEER database.

BACKGROUND: This study aimed to investigate the role of post-mastectomy radiotherapy (PMRT) in the female aged 70 years or older diagnosed with breast cancer, which is still controversial. METHODS: This retrospective study enrolled female breast cancer women aged 70 + years following mastectomy from the Surveillance, Epidemiology, and End Results (SEER) database. Propensity score matching (PSM) was performed to reduce covariable imbalance. A nomogram was created to predict the 1,3,5-years overall survival (OS) and divide patients into three risk groups. RESULTS: After matching, PMRT were associated with significant improvement in breast cancer-specific survival (BCSS) and OS (p < 0.001). By contrast, the BCSS and OS benefit from PMRT were not significant in patients with T1N1 tumor (BCSS: HR = 0.716, p = 0.249;OS:HR = 0.908, p = 0.572), and T2N1 tumor (BCSS:HR = 0.866, p = 0.289;OS:HR = 0.879, p = 0.166). Stratified by subtype, the HR+/HER-2- subtype and the HR-/HER-2- subtype (all p < 0.001) have a significant prolonged survival, yet not significant BCSS difference are shown in the HER-2 + tumor. In the low-risk group as determined by the nomogram, the use of PMRT did not significantly improve OS (p = 0.203). CONCLUSIONS: This study demonstrated that PMRT improves the survival of females with elderly breast cancer, while for T1-2N1 breast cancer patients, the omission of PMRT could be considered. Furthermore, the nomogram we constructed could be used as a decision tool for the omission of PMRT in low-risk elderly patients.

Prognosis and local treatment strategies of breast cancer patients with different numbers of micrometastatic lymph nodes.

BACKGROUND: Lymph node micrometastasis is an important prognostic factor in breast cancer, but patients with different numbers of involved lymph nodes are all divided into the same N1mi stage without distinction. We designed this study to compare the prognosis and local treatment recommendations of N1mi breast cancer patients with different numbers of micrometastatic lymph nodes. PATIENTS AND METHODS: A total of 27,032 breast cancer patients with T1-2N1miM0 stage from the Surveillance, Epidemiology, and End Results (SEER) database (2004-2019) who underwent breast surgery were included in this retrospective study. Patients were divided into three groups for prognosis comparison according to the number of micrometastatic lymph nodes: N1mi with 1 (Nmi = 1), 2 (Nmi = 2), or more (Nmi ≥ 3) involved lymph nodes. We explored the characteristics and survival outcomes of the population receiving different local treatments, including different axillary surgery types and whether receiving radiotherapy or not. Univariate and multivariate Cox proportional hazards regression analysis were used to compare the overall survival (OS) and breast cancer-specific survival (BCSS) in different groups. Stratified analyses and interaction analyses were also applied to explore the predictive significance of different involved lymph nodes numbers. Propensity score matching (PSM) method was utilized to balance the differences between groups. RESULTS: Univariate and multivariate Cox regression analysis indicated that nodal status was an independent prognostic factor. After adjustment for other prognostic factors, there was a significant difference in prognosis between Nmi = 1 group and Nmi = 2 group [adjusted hazard ratio (HR) 1.145, 95% confidence interval (CI): 1.047-1.251, P = 0.003], and patients with Nmi ≥ 3 group had a significantly poorer prognosis (adjusted HR 1.679, 95% CI 1.589-2.407; P < 0.001). The proportion of N1mi patients only underwent sentinel lymph nodes biopsy (SLNB) gradually increased from 2010 (Ptrend < 0.001). After adjusting for other factors, N1mi patients who underwent axillary lymph nodes dissection (ALND) was associated with significant survival benefit than SLNB (adjusted HR 0.932, 95%CI 0.874-0.994; P = 0.033), the same goes for receiving radiotherapy (adjusted HR 1.107, 95%CI 1.030-1.190; P = 0.006). Further stratified analysis showed that in the SLNB subgroup, radiotherapy was associated with a significant survival benefit (HR 1.695, 95%CI 1.534-1.874; P < 0.001), whereas in the ALND subgroup, there was no significant prognostic difference with or without radiotherapy (HR 1.029, 95%CI 0.933-1.136; P = 0.564). CONCLUSION: Our study indicates that the increasing number of lymph node micrometastases was associated a worse prognosis of N1mi breast cancer patients. In addition, ALND does provide a significant survival benefit for these patients, while the benefit from local radiotherapy may be of even greater importance.

CTPS1 promotes malignant progression of triple-negative breast cancer with transcriptional activation by YBX1.

BACKGROUND: Cytidine nucleotide triphosphate synthase 1 (CTPS1) is a CTP synthase which play critical roles in DNA synthesis. However, its biological regulation and mechanism in triple-negative breast cancer (TNBC) has not been reported yet. METHODS: The expression of CTPS1 in TNBC tissues was determined by GEO, TCGA databases and immunohistochemistry (IHC). The effect of CTPS1 on TNBC cell proliferation, migration, invasion, apoptosis and tumorigenesis were explored in vivo and in vitro. In addition, the transcription factor Y-box binding protein 1 (YBX1) was identified by bioinformatics methods, dual luciferase reporter and chromatin immunoprecipitation (CHIP) assays. Pearson correlation analysis was utilized to assess the association between YBX1 and CTPS1 expression. RESULTS: CTPS1 expression was significantly upregulated in TNBC tissues and cell lines. Higher CTPS1 expression was correlated with a poorer disease-free survival (DFS) and overall survival (OS) in TNBC patients. Silencing of CTPS1 dramatically inhibited the proliferation, migration, invasion ability and induced apoptosis of MDA-MB-231 and HCC1937 cells. Xenograft tumor model also indicated that CTPS1 knockdown remarkably reduced tumor growth in mice. Mechanically, YBX1 could bind to the promoter of CTPS1 to promote its transcription. Furthermore, the expression of YBX1 was positively correlated with CTPS1 in TNBC tissues. Rescue experiments confirmed that the enhanced cell proliferation and invasion ability induced by YBX1 overexpression could be reversed by CTPS1 knockdown. CONCLUSION: Our data demonstrate that YBX1/CTPS1 axis plays an important role in the progression of TNBC. CTPS1 might be a promising prognosis biomarker and potential therapeutic target for patients with triple-negative breast cancer.

An iron metabolism and immune related gene signature for the prediction of clinical outcome and molecular characteristics of triple-negative breast cancer.

BACKGROUND: An imbalance of intracellular iron metabolism can lead to the occurrence of ferroptosis. Ferroptosis can be a factor in the remodeling of the immune microenvironment and can affect the efficacy of cancer immunotherapy. How to combine ferroptosis-promoting modalities with immunotherapy to suppress triple-negative breast cancer (TNBC) has become an issue of great interest in cancer therapy. However, potential biomarkers related to iron metabolism and immune regulation in TNBC remain poorly understand. METHODS: We constructed an optimal prognostic TNBC-IMRGs (iron metabolism and immune-related genes) signature using least absolute shrinkage and selection operator (LASSO) cox regression. Survival analysis and ROC curves were analyzed to identify the predictive value in a training cohort and external validation cohorts. The correlations of gene signature with ferroptosis regulators and immune infiltration are also discussed. Finally, we combined the gene signature with the clinical model to construct a combined model, which was further evaluated using a calibration curve and decision curve analysis (DCA). RESULTS: Compared with the high-risk group, TNBC patients with low-risk scores had a remarkably better prognosis in both the training set and external validation sets. Both the IMRGs signature and combined model had a high predictive capacity, 1/3/5- year AUC: 0.866, 0.869, 0.754, and 1/3/5-yaer AUC: 0.942, 0.934, 0.846, respectively. The calibration curve and DCA also indicate a good predictive performance of the combined model. Gene set enrichment analysis (GSEA) suggests that the high-risk group is mainly enriched in metabolic processes, while the low-risk group is mostly clustered in immune related pathways. Multiple algorithms and single sample GSEA further show that the low-risk score is associated with a high tumor immune infiltration level. Differences in expression of ferroptosis regulators are also observed among different risk groups. CONCLUSIONS: The IMRGs signature based on a combination of iron metabolism and immune factors may contribute to evaluating prognosis, understanding molecular characteristics and selecting treatment options in TNBC.

The impact of chemotherapy and survival prediction by machine learning in early Elderly Triple Negative Breast Cancer (eTNBC): a population based study from the SEER database.

PURPOSE: We aimed to analysis the impact of chemotherapy and establish prediction models of prognosis in early elderly triple negative breast cancer (eTNBC) by using machine learning. METHODS: We enrolled 4,696 patients in SEER Database who were 70 years or older, diagnosed with primary early TNBC(larger than 5 mm), from 2010 to 2016. The propensity-score matched method was utilized to reduce covariable imbalance. Univariable and multivariable analyses were used to compare breast cancer-specific survival(BCSS) and overall survival(OS). Nine models were developed by machine learning to predict the 5-year OS and BCSS for patients received chemotherapy. RESULTS: Compared to matched patients in no-chemotherapy group, multivariate analysis showed a better survival in chemotherapy group. Stratified analyses by stage demonstrated that patients with stage II and stage III other than stage I could benefit from chemotherapy. Further investigation in stage II found that chemotherapy was a better prognostic indicator for patients with T2N0M0 and stage IIb, but not in T1N1M0. Patients with grade III could achieve a better survival by receiving chemotherapy, but those with grade I and II couldn't. With 0.75 in 5-year BCSS and 0.81 in 5-year OS for AUC, the LightGBM outperformed other algorithms. CONCLUSION: For early eTNBC patients with stage I, T1N1M0 and grade I-II, chemotherapy couldn't improve survival. Therefore, de-escalation therapy might be appropriate for selected patients. The LightGBM is a trustful model to predict the survival and provide precious systemic treatment for patients received chemotherapy.

Validation of the Prognostic Significance of the Prognostic Stage Group According to the Eighth Edition of American Cancer Joint Committee on Cancer Staging System in Triple-Negative Breast Cancer: An Analysis From Surveillance, Epidemiology, and End Results 18 Database.

BACKGROUND: The eighth edition of the American Cancer Joint Committee on Cancer (AJCC) staging system for breast cancer put forward the prognostic stage groups for the first time based on the traditional anatomic tumor-node-metastasis staging system. Our study intends to validate the predictive significance of the eighth edition staging system in triple-negative breast cancer (TNBC) patients. MATERIALS AND METHODS: We collected and accessed 26,589 eligible cases of TNBC from the Surveillance, Epidemiology, and End Results database (2010-2015) and reclassified the patient cohort according to the eighth edition of the AJCC staging system into anatomic and prognostic stages. RESULTS: The results showed that more than half of the patients upstaged in the prognostic stage when compared with the anatomic stage. By comparing with the anatomic stage, the prognostic stage had a higher likelihood ratio and linear trend χ2 values. The prognostic stage group also had higher Akaike information criterion and Bayesian information criterion values than the anatomic stage group. CONCLUSIONS: The prognostic staging system in TNBC patients performs more optimistic prognostic stratification and predictability than the anatomic staging system. Moreover, the latest AJCC staging system has a milestone importance to the history of breast cancer staging system.

The spectrum of BRCA mutations and characteristics of BRCA-associated breast cancers in China: Screening of 2,991 patients and 1,043 controls by next-generation sequencing.

To characterize the prevalence of BRCA mutations and characteristics of BRCA carriers in China and to update the clinical recommendations for BRCA testing, we conducted a wide screen for BRCA mutations using next-generation sequencing (NGS). A total of 4,034 Chinese subjects were screened for germline BRCA1/2 mutations, including 2,991 breast cancer patients and 1,043 healthy individuals from the community enrolled as controls. We developed an NGS-based approach to perform BRCA1/2 screening. BRCA mutations were identified in 9.1% (232/2,560) of cases with at least one risk factor, in 3.5% (15/431) of sporadic patients and in 0.38% (4/1,043) of healthy controls. The mutation frequency ranged from 8.9 to 15.2% in cohorts with a single risk factor to 16.6-100% in groups with multiple risk factors. We identified 70 novel BRCA mutations. A high frequency of BRCA1 c.5470_5477del was detected, accounting for 13.9% (16/115) of the BRCA1 mutations detected in our study. Clinical characteristics such as family history, invasive carcinoma, negative human epidermal growth factor receptor 2 (HER2), high Ki67 index, lymph node status, and high tumour grade were closely related to BRCA mutations. BRCA2 carriers had poorer disease-free survival among HER2- or hormone receptor-positive patients (hazard ratio = 1.892; 95% confidence interval: 1.132-3.161; p = 0.013). This study shows that BRCA mutation carriers could be frequently identified among breast cancer patients with multiple risk factors. Importantly, we established an NGS-based pipeline for BRCA1/2 testing in clinical practice and strongly suggest that breast cancer patients of premier- and moderate-grade risks receive BRCA1/2 mutations testing in China.

Efficacy and safety of neoadjuvant therapy for HR-positive/HER2-negative early breast cancer: a Bayesian network meta-analysis.

BACKGROUND: Neoadjuvant treatment for hormone receptor-positive/human epidermal growth factor receptor 2-negative (HR+/HER2-) breast cancer is controversial and requires a comprehensive analysis for optimal therapy assessment. Therefore, a two-step Bayesian network meta-analysis (NMA) was performed to compare the efficacy and safety of different neoadjuvant regimens. RESEARCH DESIGN AND METHODS: Phase II/III randomized clinical trials comparing various neoadjuvant therapies for HR+/HER2- breast cancer were included. NMA and pairwise meta-analyses were conducted using Stata (version 14), R (version 4.2.3), and Review Manager 5.4. RESULTS: Twenty-eight studies (5,625 patients) were eligible. NMA of objective response rate (ORR) indicated the highest SUCRA for chemotherapy (CT) and chemotherapy with anthracycline (CT(A)). Pathologic complete response (PCR) NMA demonstrated significant PCR improvement with chemotherapy regimens containing programmed cell death protein-1 and programmed cell death ligand-1 inhibitors (PD-1i/PD-L1i) and poly ADP-ribose polymerase inhibitors (PARPi). Combined analysis considering both the ORR and safety highlighted CT(A)'s efficacy and toxicity balance. CONCLUSIONS: CT(A) and CT showed improved ORR compared with alternative regimens. CT(A) combined with PD-1/PD-L1 or PARP inhibitors significantly increased PCR rates. Comprehensive assessment of both ORR and safety indicated that CT(A) represents an optimal neoadjuvant therapy for HR+/HER2- breast cancer, whereas AI + CDK4/6 inhibitors rank solely behind chemotherapy. REGISTRATION: PROSPERO Registration: CRD42024538948. International Platform of Registered Systematic Review and Meta-Analysis Protocols (INPLASY) registration number INPLASY202440092.

Efficacy and safety of first-line therapy in patients with HER2-positive advanced breast cancer: a network meta-analysis of randomized controlled trials.

PURPOSE: The numerous first-line treatment regimens for human epidermal growth factor receptor 2 (HER2)-positive advanced breast cancer (ABC) necessitate a comprehensive evaluation to inform clinical decision-making. We conducted a Bayesian network meta-analysis (NMA) to compare the efficacy and safety of different interventions. METHODS: We systematically searched for relevant randomized controlled trials (RCTs) in Pubmed, Embase, Cochrane Library and online abstracts from inception to June 1, 2023. NMA was performed to calculate and analyze progression-free survival (PFS), overall survival (OS), objective response rate (ORR), and adverse events of grade 3 or higher (≥ 3 AEs). RESULTS: Out of the 10,313 manuscripts retrieved, we included 28 RCTs involving 11,680 patients. Regarding PFS and ORR, the combination of trastuzumab with tyrosine kinase inhibitors (TKIs) was more favorable than dual-targeted therapy. If only using trastuzumab, combination chemotherapy is superior to monochemotherapy in terms of PFS. It is important to note that the addition of anthracycline did not result in improved PFS. For patients with hormone receptor-positive HER2-positive diseases, dual-targeted combined with endocrine therapy showed better benefit in terms of PFS compared to dual-targeted alone, but it did not reach statistical significance. The comprehensive analysis of PFS and ≥ 3 AEs indicates that monochemotherapy combined with dual-targeted therapy still has the optimal balance between efficacy and safety. CONCLUSION: Monochemotherapy (Docetaxel) plus dual-target (Trastuzumab and Pertuzumab) therapy remains the optimal choice among all first-line treatment options for ABC. The combination of trastuzumab with TKIs (Pyrotinib) demonstrated a significant improvement in PFS and ORR, but further data are warranted to confirm the survival benefit.

Non-invasive prediction of axillary lymph node dissection exemption in breast cancer patients post-neoadjuvant therapy: A radiomics and deep learning analysis on longitudinal DCE-MRI data.

PURPOSE: In breast cancer (BC) patients with clinical axillary lymph node metastasis (cN+) undergoing neoadjuvant therapy (NAT), precise axillary lymph node (ALN) assessment dictates therapeutic strategy. There is a critical demand for a precise method to assess the axillary lymph node (ALN) status in these patients. MATERIALS AND METHODS: A retrospective analysis was conducted on 160 BC patients undergoing NAT at Fujian Medical University Union Hospital. We analyzed baseline and two-cycle reassessment dynamic contrast-enhanced MRI (DCE-MRI) images, extracting 3668 radiomic and 4096 deep learning features, and computing 1834 delta-radiomic and 2048 delta-deep learning features. Light Gradient Boosting Machine (LightGBM), Support Vector Machine (SVM), RandomForest, and Multilayer Perceptron (MLP) algorithms were employed to develop risk models and were evaluated using 10-fold cross-validation. RESULTS: Of the patients, 61 (38.13 %) achieved ypN0 status post-NAT. Univariate and multivariable logistic regression analyses revealed molecular subtypes and Ki67 as pivotal predictors of achieving ypN0 post-NAT. The SVM-based "Data Amalgamation" model that integrates radiomic, deep learning features, and clinical data, exhibited an outstanding AUC of 0.986 (95 % CI: 0.954-1.000), surpassing other models. CONCLUSION: Our study illuminates the challenges and opportunities inherent in breast cancer management post-NAT. By introducing a sophisticated, SVM-based "Data Amalgamation" model, we propose a way towards accurate, dynamic ALN assessments, offering potential for personalized therapeutic strategies in BC.

Patient-Reported Outcomes in OlympiA: A Phase III, Randomized, Placebo-Controlled Trial of Adjuvant Olaparib in gBRCA1/2 Mutations and High-Risk Human Epidermal Growth Factor Receptor 2-Negative Early Breast Cancer.

PURPOSE: The OlympiA randomized phase III trial compared 1 year of olaparib (OL) or placebo (PL) as adjuvant therapy in patients with germline BRCA1/2, high-risk human epidermal growth factor receptor 2-negative early breast cancer after completing (neo)adjuvant chemotherapy ([N]ACT), surgery, and radiotherapy. The patient-reported outcome primary hypothesis was that OL-treated patients may experience greater fatigue during treatment. METHODS: Data were collected before random assignment, and at 6, 12, 18, and 24 months. The primary end point was fatigue, measured with the Functional Assessment of Chronic Illness Therapy-Fatigue scale. Secondary end points, assessed with the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire, Core 30 item, included nausea and vomiting (NV), diarrhea, and multiple functional domains. Scores were compared between treatment groups using mixed model for repeated measures. Two-sided P values <.05 were statistically significant for the primary end point. All secondary end points were descriptive. RESULTS: One thousand five hundred and thirty-eight patients (NACT: 746, ACT: 792) contributed to the analysis. Fatigue severity was statistically significantly greater for OL versus PL, but not clinically meaningfully different by prespecified criteria (≥3 points) at 6 months (diff OL v PL: NACT: -1.3 [95% CI, -2.4 to -0.2]; P = .022; ACT: -1.3 [95% CI, -2.3 to -0.2]; P = .017) and 12 months (NACT: -1.6 [95% CI, -2.8 to -0.3]; P = .017; ACT: -1.3 [95% CI, -2.4 to -0.2]; P = .025). There were no significant differences in fatigue severity between treatment groups at 18 and 24 months. NV severity was worse in patients treated with OL compared with PL at 6 months (NACT: 6.0 [95% CI, 4.1 to 8.0]; ACT: 5.3 [95% CI, 3.4 to 7.2]) and 12 months (NACT: 6.4 [95% CI, 4.4 to 8.3]; ACT: 4.5 [95% CI, 2.8 to 6.1]). During treatment, there were some clinically meaningful differences between groups for other symptoms but not for function subscales or global health status. CONCLUSION: Treatment-emergent symptoms from OL were limited, generally resolving after treatment ended. OL- and PL-treated patients had similar functional scores, slowly improving during the 24 months after (N)ACT and there was no clinically meaningful persistence of fatigue severity in OL-treated patients.

Tyrosine kinase inhibitors in HER2-positive breast cancer brain metastases: A systematic review and meta-analysis.

BACKGROUND: Small tyrosine kinase inhibitors (TKIs) show activity against breast cancer brain metastases (BCBM) of the human epidermal growth factor receptor 2 (HER2)-positive subtype. This meta-analysis aimed to objectively explore the efficacy and safety of TKIs. METHODS: Electronic databases were searched for relevant clinical trials. We conducted a pairwise meta-analysis, pooled analysis, and estimated summary survival curves to compare survival outcomes following TKIs therapy for BCBM patients using Stata version 16.0 or R x64 4.0.5. RESULTS: Thirteen clinical trials involving 987 HER2-positive BCBM patients were analyzed. A trend of longer progression-free survival (PFS) was observed in the TKI-containing arm compared to the non-TKI-containing arm (hazard ratio = 0.64, 95% confidence interval [CI]: 0.35-1.15, p = 0.132), although the difference is not statistically significant. Summary survival curves reported the summary median PFS and overall survival were 7.9 months and 12.3 months. Subgroup analysis revealed that TKIs combined with capecitabine (TKI + Cap) regimens resulted in improved survival outcomes. Tucatinib may be more effective in BCBM patients. The main grade 3-5 adverse events (AEs) were diarrhea (22%, 95% CI: 14%-32%), neutropenia (11%, 95% CI: 5%-18%), hepatic toxicity (7%, 95% CI: 1%-16%), and sensory neuropathy (6%, 95% CI: 2%-12%). CONCLUSION: TKIs therapy improved the survival outcomes of HER2-positive BCBM patients, especially when combined with capecitabine and tolerable AEs. We also identified the clinical value of tucatinib, which appears to be the most favorable TKI drug for BCBM patients.