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.

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.

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.

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.

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.

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.

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.

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.

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.

Epidemiology and a Predictive Model of Prognosis Index Based on Machine Learning in Primary Breast Lymphoma: Population-Based Study.

BACKGROUND: Primary breast lymphoma (PBL) is a rare disease whose epidemiological features, treatment principles, and factors used for the patients' prognosis remain controversial. OBJECTIVE: The aim of this study was to explore the epidemiology of PBL and to develop a better model based on machine learning to predict the prognosis for patients with primary breast lymphoma. METHODS: The annual incidence of PBL was extracted from the surveillance, epidemiology, and end results database between 1975 and 2019 to examine disease occurrence trends using Joinpoint software (version 4.9; National Cancer Institute). We enrolled data from 1251 female patients with primary breast lymphoma from the surveillance, epidemiology, and end results database for survival analysis. Univariable and multivariable analyses were performed to explore independent prognostic factors for overall survival and disease-specific survival of patients with primary breast lymphoma. Eight machine learning algorithms were developed to predict the 5-year survival of patients with primary breast lymphoma. RESULTS: The overall incidence of PBL increased drastically between 1975 and 2004, followed by a significant downward trend in incidence around 2004, with an average annual percent change (AAPC) of -0.8 (95% CI -1.1 to -0.6). Disparities in trends of PBL exist by age and race. The AAPC of the 65 years or older cohort was about 1.2 higher than that for the younger than 65 years cohort. The AAPC of White patients is 0.9 (95% CI 0.0-1.8), while that of Black patients was significantly higher at 2.1 (95% CI -2.5 to 6.9). We also identified that the risk of death from PBL is multifactorial and includes patient factors and treatment factors. Survival analysis revealed that the patients diagnosed between 2007 and 2015 had a significant risk reduction of mortality compared to those diagnosed between 1983 and 1990. The gradient booster model outperforms other models, with 0.752 for sensitivity and 0.817 for area under the curve. The important features established with the gradient booster model were the year of diagnosis, age, histologic type, and primary site, which were the 4 most relevant variables to explain 5-year survival status. CONCLUSIONS: The incidence of PBL started demonstrating a tendency to decrease after 2004, which varied by age and race. In recent years, the prognosis of patients with primary breast lymphoma has been remarkably improved. The gradient booster model had a promising performance. This model can help clinicians identify the early prognosis of patients with primary breast lymphoma and therefore improve the clinical outcome by changing management strategies and patient health care.

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.

Efficacy and safety of neoadjuvant therapy for triple-negative breast cancer: a Bayesian network meta-analysis.

BACKGROUND: Numerous studies have concentrated on neoadjuvant therapies for treating triple-negative breast cancer (TNBC) that improve the pathological complete response (pCR) rate but remain controversial. We conducted a network meta-analysis (NMA) to objectively explore the efficacy and safety of different neoadjuvant regimens. METHODS: Phase II/III randomized clinical trials that compared different neoadjuvant therapies for TNBC were included. NMA and pairwise meta-analysis were performed using WinBUGS (version 1.4.3) and Review Manager 5.3. RESULTS: Forty-four studies with 8459 patients met the eligibility criteria. The NMA of pCR showed that programmed cell death Protein-1 and programmed cell death Ligand-1 inhibitors (PD-1/PD-L1), bevacizumab (Bev), zoledronic acid (ZOL), and platinum salts plus poly polymerase inhibitors (Pt+PARPi) may be favorable for TNBC neoadjuvant therapy. Chemotherapy combined with platinum salts or nanoparticle albumin-bound paclitaxel (Nab-p) has additional beneficial effects. However, neo-type drugs may also have increased toxicity. CONCLUSION: PD-1/PD-L1, Bev, ZOL, and Pt+ PARPi-containing regimens improved the pCR rate compared to traditional chemotherapy, including anthracyclines and taxanes. Chemotherapy with platinum salts or Nab-p improved the pCR rate. Nevertheless, the balance between efficacy and toxicity should be evaluated rigorously. PD-1/PD-L1-containing regimens appear to be the most favorable for TNBC neoadjuvant therapy, with good efficacy and tolerance.

LINC00092 Modulates Oxidative Stress and Glycolysis of Breast Cancer Cells via Pyruvate Carboxylase-Mediated AKT/mTOR Pathway.

Background: The discovery of noncoding RNAs (ncRNAs) offers new options for cancer-targeted therapy. This study is aimed at exploring the regulatory function of LINC00092 on breast cancer (BC) oxidative stress and glycolysis, along with internal mechanism concerning pyruvate carboxylase (PC). Methods: Bioinformatics analysis was used to explore LINC00092 (or friend leukemia virus integration 1 (FLI1)) expression on BC progression, as well as oxidative stress and glycolysis in BC. After LINC00092 overexpression or silence, BC cell viability, proliferation, migration, invasion, oxidative stress, glycolysis, and AKT/mTOR pathway were detected. Following 2-DG, SC79, or MK2206 treatment, effects of LINC00092 on BC cells were measured. Moreover, regulatory activity of LINC00092 in PC expression was analyzed. Whether PC participated in the modulation of LINC00092 on BC cell functions was explored. Results: LINC00092 was lowly expressed in BC and negatively related to BC progression. FLI1 bound to LINC00092 promoter to positively modulate LINC00092. LINC00092 overexpression inhibited BC cell proliferation, migration, invasion, oxidative stress, glycolysis, and AKT/mTOR pathway and likewise suppressed BC growth in vivo. Silence of LINC00092 had opposite influences. 2-DG partially reversed the LINC00092 silence-resulted increase of BC cell proliferation. SC79 alleviated the function of LINC00092 overexpression on BC cell functions. MK2206 had the contrary influence of SC79. Besides, LINC00092 bound to PC to modulate ubiquitination degradation of PC protein. PC took part in the influences of LINC00092 on BC cell functions. Conclusions: LINC0092 modulates oxidative stress and glycolysis of BC cells via the PC-mediated AKT/mTOR pathway, which is possibly a target for BC diagnosis and therapy.

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.

Analysis of Stemness and Prognosis of Subtypes in Breast Cancer Using the Transcriptome Sequencing Data.

The stem characteristics of tumor cells have been proposed in theory very early, and we can use the signature of gene expression to speculate the stemness of tumor cells. However, systematic studies on the stemness of breast cancer as well as breast cancer subtypes, and the relationship between stemness and metastasis and prognosis, are still lacking. In the present research, using the transcriptome data of patients with breast cancer in the TCGA database, a stemness prediction model was utilized to derive the stemness of the patients' tumors. We compared the stemness values among different subtypes and the differences with metastasis. COX regression was employed to evaluate the correlation between stemness value as well as prognosis. Using the Lasso-penalized Cox regression machine learning model, we obtained the gene signature of the basal subtype that is related to stemness and can also predict the prognosis of the patient. Patients can be stratified into two groups of high and low stemness, corresponding to good and poor prognosis. Based on further prediction of tumor infiltration by CIBERSORT and prediction of drug response by a connectivity map, we found that the difference in stemness between these two groups is associated with the activation of tumor-killing immune cells and drug response. Our findings can promote the understanding and research of subtypes of basal breast cancer and provide corresponding molecular markers for clinical detection and therapy.