Introduction: Ki67 value and its variation before and after neoadjuvant chemotherapy are commonly tested in relation to breast cancer patient prognosis. This study aims to quantify the extent of changes in Ki67 proliferation pre- and post-neoadjuvant chemotherapy, confirm an optimal cut-off point, and evaluate its potential value for predicting survival outcomes in patients with different molecular subtypes of breast cancer.Methods: This retrospective real-world study recruited 828 patients at the Department of Breast Surgery of the First Affiliated Hospital of China Medical University and the Cancer Hospital of China Medical University from Jan 2014 to Nov 2020. Patient demographic features and disease pathology characteristics were recorded, and biomarkers were verified through immunohistochemistry. Various statistical methods were used to validate the relationships between different characteristics and survival outcomes irrespective of disease-free and overall survival.Results: Among 828 patients, statistically significant effects between pathological complete response and survival outcome were found in both HER2-enriched and triple-negative breast cancer (p < 0.05) but not in Luminal breast cancer (p > 0.05). Evident decrease of Ki67 was confirmed after neoadjuvant chemotherapy. To quantify the extent of Ki67 changes between pre- and post-NAC timepoints, we adopted a computational equation termed ΔKi67% for research. We found the optimal cut-off value to be “ΔKi67% = −63%” via the operating characteristic curve, defining ΔKi67% ≤ −63% as positive status and ΔKi67% > −63% as negative status. Patients with positive ΔKi67% status were 37.1% of the entire cohort. Additionally, 4.7, 39.9, 34.5 and 39.6% of patients with Luminal A, Luminal B, HER2-enriched and triple negative breast cancer were also validated with positive ΔKi67% status. The statistically significant differences between ΔKi67% status and prognostic outcomes were confirmed by univariate and multivariate analysis in Luminal B (univariate and multivariate analysis: p < 0.05) and triple negative breast cancer (univariate and multivariate analysis: p < 0.05). We proved ΔKi67% as a statistically significant independent prognostic factor irrespective of disease-free or overall survival among patients with Luminal B and triple-negative breast cancer.Conclusions:ΔKi67% can aid in predicting patient prognostic outcome, provide a measurement of NAC efficacy, and assist in further clinical decisions, especially for patients with Luminal B breast cancer.

The leading cause of death in humans has long been considered cancer. People have developed a variety of cancer treatments as science has advanced. However, the side effects and flaws of the therapies are still intolerable for patients. Cancer immunotherapy, which potentially can give a long-lasting treatment with minimal toxicities, finally appeared to address the inadequacies. Cancer immunotherapy keeps up with the advancements in contemporary health. In recent years, there have been many updates on the many subtypes of cancer immunotherapy. A brief history of cancer immunotherapy and the most current developments are summarized in this paper. The assessment also emphasizes the newest investment trend in cancer immunotherapy and prospective drug combinations.

Objective: To explore the expression pattern of long chain fatty acyl CoA synthetase 3 (ACSL3) in breast cancer, and evaluate the clinical significance of ACSL3 by analyzing potential function and prognostic value of ACSL3 in human breast carcinoma.Methods: The expression of ACSL3 in normal mammary tissues and breast tumor tissues was analyzed by GEPIA and Human Protein Atlas. The prognostic value of ACSL3 was evaluated by Kaplan–Meier plotter analysis. ACSL3 expression was analyzed by immunohistochemistry in 297 breast cancer patients from the First Hospital of China Medical University Furthermore, based on LinkedOmics database, analyses of GO and KEGG pathways were performed to identify the potential function of ACSL3. Tumor Immune Estimation Resource (TIMER) database was used to evaluate the association between ACSL3 and immune infiltration in breast cancer. Results: GEPIA and Human Protein Atlas indicated that ACSL3 was significantly upregulated in breast carcinomas. Kaplan-Meier plotter analysis showed that increased expression of ACSL3 mRNA was significantly associated with shorter overall survival (OS) and relapse-free survival (RFS) in breast cancer patients. Results from immunochemical staining showed that ACSL3 was obviously related to clinicopathological features of breast cancer, and ACSL3 was highly abundant in TNBC tumors. Moreover, survival analysis of breast cancer patients demonstrated that higher ACSL3 protein expression is unfavorable prognostic biomarker in breast cancer patients. Results from TIMER database indicated that ACSL3 expression was significantly correlated with infiltration level of multiple immune cells. Further studies are needed to explore underlying mechanism of the pro-tumor effects of ACSL3 expression.Conclusions: ACSL3 may not only serve as a reliable predictive biomarker of breast cancer but also have impact on the occurrence and progression of breast cancer. Thus, ACSL3 may be an emerging therapeutic target for the development of molecular-targeted therapeutic strategies for breast cancer.