Background: The molecular features of fibroblasts and the role of fibrosis in neoadjuvant chemotherapy (NAC) response and breast cancer (BRCA) prognosis remain unclear. Therefore, this study aimed to investigate the impact of interstitial fibrosis on the response and prognosis of patients with BRCA undergoing NAC treatment. Materials and Methods: The molecular characteristics of pathologic complete response (pCR) and non-pCR (npCR) in patients with BRCA were analyzed using multi-omics analysis. A clinical cohort was collected to investigate the predictive value of fibrosis in patients with BRCA. Results: Fibrosis-related signaling pathways were significantly upregulated in patients with npCR. npCR may be associated with distinct and highly active fibroblast subtypes. Patients with high fibrosis had lower pCR rates. The fibrosis-dependent nomogram for pCR showed efficient predictive ability (training set: area under the curve [AUC]=0.871, validation set: AUC=0.792). Patients with low fibrosis had a significantly better prognosis than those with high fibrosis, and those with a high fibrotic focus index had significantly shorter overall and recurrence-free survival. Therefore, fibrosis can be used to predict pCR. Our findings provide a basis for decision-making in the treatment of BRCA. Conclusions: npCR is associated with a distinct and highly active fibroblast subtype. Furthermore, patients with high fibrosis have lower pCR rates and shorter long-term survival. Therefore, fibrosis can predict pCR. A nomogram that includes fibrosis can provide a basis for decision-making in the treatment of BRCA. Export

Background: Triple-negative breast cancer (TNBC) is characterized by aggressive behavior and limited treatment options, with chemotherapy resistance posing a significant clinical challenge. UBR5, an E3 ubiquitin ligase, has been consistently reported to be amplified and overexpressed in breast cancers. Materials and methods: This study analyzed 185 TNBC patients to investigate the association between UBR5 expression levels and clinical outcomes. Experimental approaches included in vitro assays using UBR5 knockout or knockdown TNBC cell models treated with doxorubicin and cisplatin, alongside in vivo xenograft models to assess therapeutic responses. Results: High UBR5 expression correlated significantly with poor 5-year disease-free survival (44.0% vs. 82.0% in low UBR5 group) and reduced pathological complete response rates to anthracycline-based neoadjuvant chemotherapy (8.8% vs. 33.3%). In vitro , UBR5 knockout or knockdown sensitized TNBC cells to doxorubicin and cisplatin, enhancing apoptosis and DNA damage accumulation, as evidenced by elevated γ-H2AX levels and impaired DNA damage repair (DDR) pathways, including ATM/CHK2 signaling and key repair proteins (53BP1, RAD51, BRCA1). Mechanistically, UBR5 loss suppressed p38/NF-κB signaling, further compromising DDR and exacerbating chemosensitivity. In vivo , UBR5-deficient xenografts exhibited enhanced doxorubicin responsiveness, an effect mimicked by p38 inhibition. Conclusions: UBR5 serves as a critical mediator of chemoresistance in TNBC by regulating the DNA damage response through the p38 signaling pathway. Targeting UBR5 or p38 signaling presents a promising therapeutic approach to overcome treatment resistance.

Vacuolar H+‑ATPase (V‑ATPase) serves a key role in adjusting and maintaining the intracellular pH, as well as in regulating the drug resistance of tumor cells. In recent years, the expression level of V‑ATPase has been considered to be able to predict the sensitivity of breast cancer cells to chemotherapy drugs. Cluster of differentiation 147 (CD147) is known to serve a key role in the development and progression of breast cancer. The present study aimed to identify the role CD147 and V‑ATPase in chemoresistance in breast cancer, and to characterize the regulation of CD147 on V‑ATPase. Firstly, the expression levels of CD147 and V‑ATPase were detected in chemotherapy‑resistance breast cancer samples. It was demonstrated that V‑ATPase was highly expressed in chemotherapy‑resistance breast cancer samples, and that its expression was correlated with CD147 expression. Subsequently, MCF‑7 and MDA‑MB‑231 cells were used to study the regulatory effect of CD147 on the expression and function of V‑ATPase. Gene transfection or small interfering RNA transfection were used to control the expression of CD147 in the two cell lines. The results revealed that the overexpression of CD147 increased the expression of V‑ATPase in MCF‑7 cells, whereas CD147 knockdown decreased V‑ATPase expression in MDA‑MB‑231 cells. It was also observed that CD147 affected the V‑ATPase activity, regulating the transmembrane pH gradient of cancer cells. These results demonstrated that CD147 was associated with the sensitivity of chemotherapeutic drugs of epirubicin and docetaxel, while pantoprazole was able to partially reverse the CD147‑mediated chemoresistance in breast cancer. Therefore, the current study provided a possible mechanism for further examination of drug resistance in breast cancer.

Models for predicting axillary lymph node metastasis (ALNM) in breast cancer patients are lacking. We aimed to develop an efficient model to accurately predict ALNM. Three hundred fifty-five breast cancer patients were recruited and randomly divided into the training and validation sets. Univariate and multivariate logistic regressions were applied to identify predictors of ALNM. We developed nomograms based on these variables to predict ALNM. The performance of the nomograms was tested using the receiver operating characteristic curve and calibration curve, and a decision curve analysis was performed to assess the clinical utility of the prediction models. The nomograms that included clinical N stage (cN), pathological grade (pathGrade), and hemoglobin accurately predicted ALNM in the training and validation sets (area under the curve [AUC] 0.80 and 0.80, respectively). We then explored the importance of the cN and pathGradesignatures used in the integrated model and developed new nomograms by removing the two variables. The results suggested that the combine-pathGrade nomogram also accurately predicted ALNM in the training and validation sets (AUC 0.78 and 0.78, respectively), but the combine-cN nomogram did not (AUC 0.64 and 0.60, in training and validation sets, respectively). We described a cN-based ALNM prediction model in breast cancer patients, presenting a novel efficient clinical decision nomogram for predicting ALNM.

To describe the hospitalization spending for cancers in Hunan Province, China, and to investigate the hospitalization cost across diverse cancer classifications. We conducted a retrospective study based on the hospitalization admission data from 2017 to 2019 in Hunan Province. We retrieved information on age, sex, diagnosis, number of comorbidities, level of hospitalization, hospital location, hospital costs, length of stay, and type of payer for eligible participants. Factors for cost (log-transformed) were investigated through multiple linear regression. A total of 872,309 records of cancer were hospitalized in Hunan Province during 2017–2019, with a total cost of US$2490.36 million, and 64.10% of the cost was covered by medical insurance. The top five cancers in terms of cost were lung (300.32 million), colorectum ($234.56 million), liver ($126.46 million), lip, oral cavity & pharynx ($102.29 million), and stomach ($98.98 million) cancers in men, were breast ($176.03 million), colorectum ($156.15 million), cervix ($112.68 million), lung ($112.21 million), and thyroid ($56.75 million) cancers in women, respectively. Site of cancer, sex, age, year of hospitalization, number of comorbidities, length of stay, hospital level, and hospital location were significantly associated with the per-capita log-transformed cost. The economic burden of cancer was heavy in Hunan, and lung, colorectal, breast, liver, and stomach cancers accounted for half of the total cost. Site of cancer, sex, age, comorbidity, level, and location of hospital were factors for the per-capita cost.