HER-2-positive locally advanced breast cancer (LABC) remains challenging to treat due to its aggressive biology and propensity for drug resistance. Currently, dual-targeted therapy (trastuzumab plus pertuzumab) combined with chemotherapy has increased pCR rates to 40%-60%; however, the risk of recurrence persists. Recently, significant advances have been made in preoperative treatment strategies, antibody-drug conjugates with high drug-to-antibody ratios and pronounced bystander effects, such as trastuzumab deruxtecan, have markedly enhanced therapeutic efficacy; tyrosine kinase inhibitors and bispecific antibodies have improved overall anti-tumor activity through multi-pathway synergistic inhibition. Additionally, chemotherapy de-escalation approaches, such as chemo-free regimens selected by imaging and metabolic assessment, the incorporation of immunotherapy, and fully oral regimens for triple-positive breast cancer, have significantly broadened personalized treatment options. Future efforts should focus on the identification of multi-omics biomarkers, optimization of targeted therapies and comprehensive management strategies to further overcome resistance, balance efficacy and quality of life, and ultimately achieve breakthroughs in precision oncology.

Locally advanced breast cancer (LABC) is a subtype characterized by high heterogeneity and significant therapeutic challenges. There are some unresolved issues in its local and systemic treatment. Based on traditional staging criteria, precise assessment of surgical feasibility is fundamental to formulating refined treatment plans. For patients with operable LABC, radical surgery is recommended as the primary strategy, rather than routinely opting for neoadjuvant therapy. This approach mitigates risks of increased drug resistance or disease progression that may compromise surgical opportunities. In cases of initially inoperable LABC, neoadjuvant therapy aims to achieve tumor downstaging to enable surgery which remains central to LABC management. Even neoadjuvant therapy serves as a critical treatment modality, it is not an obligatory screening step. Recent advances in systemic therapeutics have expanded options for adjuvant and intensive treatment, and sparked debates regarding optimal timing of interventions. This article synthesizes clinical research progress in LABC to explore current controversies in its diagnosis and therapeutic decision-making.

To investigate the effect of CD83 on the proliferation, apoptosis, cell cycle progression, migration, and invasion of triple negative breast cancer cells, and to explore the mechanisms underlying its regulation of the biological behaviors of these malignant cells.

To evaluate CD83 expression in breast cancer, we retrieved 822 breast cancer and 572 normal tissue samples from TCGA. This dataset enabled analysis of CD83 expression differences in breast cancer. We also used Western blot to measure CD83 protein levels in MCF-10A (normal breast epithelial cells) and breast cancer cells (MCF-7, BT-549, MDA-MB-231) . This method facilitated direct CD83 protein level comparison between normal and cancerous breast cells, enhancing insights into CD83’s role in breast cancer. Using the CRISPR/Cas9, we established stable CD83 knockout MDA-MB-231 cell lines (sg-CD83-#1, sg-CD83-#2, sg-CD83-#3) and selected sg-CD83 for further study based on protein extraction and CD83 disruption efficiency. Functional assays including CCK-8, scratch wound healing, and Transwell were conducted on sg-CD83 versus sg-ctrl, sg-ctrl as the negative control for CD83 knockout. Co-IP was used to examine CD83-ITGB1 interactions. Establishment of MDA-MB-231 cell line overexpressing CD83 through plasmid transfection, and created an ov-CD83 group to study CD83 overexpression effects, assessing proliferation, migration, and invasion via scratch and Transwell assays against vector, which as a control for CD83 overexpression. The impact of ITGB1 on CD83 function was assessed by silencing ITGB1 in CD83-overexpressing cells, using the si-NC as a control for ITGB1 knockdown. Statistical analysis involved independent t-tests for intergroup comparisons and one-way ANOVA with LSD post hoc tests for multiple groups, ensuring robustness of findings.

TCGA database analysis revealed significant CD83 mRNA expression differences among breast cancer subtypes and normal tissue. CD83 levels were 4.63±0.79 in lunimal A subtype, 4.57±0.77 in luminal B subtype, 4.62±0.75 in HER-2 overexpression subtype and 5.40±1.13 in TNBC subtype and 3.30±1.17 in normal tissue. Statistical analysis showed highly significant differences (F=196.802, P<0.001) , with TNBC showing notably higher CD83 expression than other subtypes (P<0.001) . This suggests CD83’s potential as a TNBC biomarker and therapeutic target, highlighting the need for further functional studies in this breast cancer subtype. The protein expression levels of CD83 in MCF-10A, MCF-7, BT-549, and MDA-MB-231 cells were 1.00±0.01, 1.44±0.02, 1.71±0.02, and 1.89±0.07, respectively, showing statistical significance (F=353.070, P<0.001) . The sg-CD83-#3 group showed the best CD83 knockout efficiency. Thus, it was selected as the CD83 knockout model (sg-CD83) for further experiments. The protein expression of CD83 in MDA-MB-231 cells in the four groups of sg-ctrl, sg-CD83-#1, sg-CD83-#2, and sg-CD83-#3 were 1.00±0.02, 0.79±0.18, 0.32±0.03, and 0.23±0.05, respectively, with statistical significance (F=48.758, P<0.001) . The absorbance at 450 nm for the sg-ctrl group and the sg-CD83 group at 24, 48, 72, and 96 hours was as follows: 0.63±0.05 vs 0.51±0.03, 0.92±0.03 vs 0.70±0.06, 1.27±0.02 vs 0.90±0.09, and 1.54±0.14 vs 1.06±0.09. These differences were statistically significant (all P<0.050) . The apoptosis rates in the sg-ctrl group and sg-CD83 group were [ (5.96±0.06) % vs (12.82±0.07) %, (t=-128.877, P<0.001) ], the G₀/G₁ phase cell ratio was [ (31.87±0.76) % vs (44.75±1.50) %, (t=-13.229, P<0.001) ]; There were statistically significant differences in cell scratch healing rate [ (34.47±0.87) % vs (16.63±0.70) %, (t=27.554, P<0.001) ], the number of migrating cells (143.67±4.16 vs 62.67±1.53, t=31.636, P<0.001) , and the number of invasive cells (123.67±3.06 vs 26.33±2.52, t=42.593, P<0.001) . The expression levels of ITGB1 were 1.00±0.02 in the sg-ctrl group and 0.34±0.02 in the sg-CD83 group, showing statistical significance (t=40.417, P<0.001) . Similarly, FAK expression was 1.00±0.01 in the sg-ctrl group and 0.79±0.07 in the sg-CD83 group (t=5.144, P=0.033) . The p-FAK levels were 0.99±0.03 and 0.35±0.05, respectively, with a statistically significant difference (t=19.395, P<0.001) . In the co-immunoprecipitation (Co-IP) assay, CD83 and ITGB1 were co-precipitated. There were statistically significant differences in scratch wound healing rates [ (8.40±2.73) % vs (45.08±1.51) %, t=-20.340, P<0.001], migratory cell counts (151.00±2.65 vs 337.67±3.51, t=-73.532, P<0.001) , and invasive cell counts (120.33±4.16 vs 288.67±4.51, t=-47.506, P<0.001] between the vector group and ov-CD83 group. There were statistically significant differences in scratch wound healing rates [ (44.63±2.11) % vs (13.93±2.90) %, t=14.839, P<0.001], migratory cell counts (339.67±3.06 vs 181.67±2.31, t=71.458, P<0.001) , and invasive cell counts (289.00±5.29 vs 170.33±5.03, t=28.144, P<0.001) between the si-NC group and si-ITGB1 group.

CD83 regulates the migration and invasion of triple negative breast cancer cells through the ITGB1/FAK signaling pathway and may serve as a potential target for breast cancer.

To investigate the microbial composition of breast papillary tumors, analyze the correlation between Fusobacterium abundance and tumor malignancy as well as clinical parameters, and identify independent risk factors for malignancy.

A total of 72 patients with pathologically confirmed breast papillary tumors who underwent surgery in the Department of Breast and Thyroid Surgery, Renmin Hospital of Wuhan University between January 2020 and December 2023 were retrospectively enrolled, including 25 benign and 47 malignant cases. Formalin-fixed paraffin-embedded tissue samples were collected for 16S rRNA gene sequencing to assess microbial diversity and composition. Alpha diversity indexes (Chao1、Faith_pd, Observed_species, Shannon) were compared between benign and malignant groups, and Kruskal-Wallis test was used to identify significantly different taxa. The association between Fusobacterium and malignancy risk was evaluated using univariate and multivariate logistic regression.

The malignant group showed significantly higher alpha diversity compared with the benign group [Chao1: 215.282 (100.823, 342.457) vs 616.534 (356.234, 752.416) , Z=-2.374, P=0.018; Faith_Pd: 48.888 (23.390, 60.698) vs 105.198 (58.700, 136.172) , Z=-2.387, P=0.017; Observed_species: 191.900 (95.600, 339.800) vs 612.800 (343.700, 749.700) , Z=-2.374, P=0.018; Shannon: 2.729 (2.426, 3.967) vs 7.016 (3.781, 8.932) , Z=-3.089, P=0.002] Dominant genera in the benign group included Lactobacillus (0.962%) and Acinetobacter (2.250%) , while Prevotella (0.668%) Staphylococcus (0.160%) , and Rhodococcus (0.016%) were enriched in the malignant group. The abundance of Fusobacterium was significantly higher in the malignant group than in the benign group [0.000 079 (0.000 026, 0.000 245) vs 0.000 512 (0.000 168, 0.001 560) , H=4.464, P=0.035]. Logistic regression analysis revealed that age >50 years (OR=12.520, 95%CI: 3.150~49.739, P=0.001) , tumor volume >1 cm³ (OR=6.598, 95%CI: 1.681~25.901, P=0.007) , and presence of Fusobacterium (OR=5.943, 95%CI: 1.154~30.600, P=0.033) were independent risk factors for malignancy.

The microbial composition of papillary breast tumors is closely associated with tumor malignancy. Fusobacterium may serve as a potential microbial biomarker for malignancy, providing a theoretical basis for microbiota-targeted intervention.

To compare the BRCA1/2 mutation rates between breast cancer and non-breast cancer populations and analyze the clinicopathological factors related to BRCA1/2 mutations in breast cancer patients.

The clinical study of 463 breast cancer patients and 321 non-breast cancer individuals in the Department of Thyroid, Breast and Vascular Surgery, the First Affiliated Hospital of Air Force Medical University between January 2021 and August 2023 were collected for a retrospective analysis. Germline BRCA mutations were screening out using the human BRCA1/2 mutation detection kit. Intergroup comparisons of BRCA1/2 mutation rates (breast cancer vs non-breast cancer) and clinicopathological characteristics (BRCA1/2-mutated vs non-mutated patients) were performed using chi-square test or Fisher’s exact test. For ordinal data (T/N/M stage, histological grade) , Wilcoxon rank-sum test was applied.

Among 463 breast cancer patients, BRCA1 pathogenic mutations were identified in 15 cases (3.2%) . The most frequent mutation sites were c.3288_3289del and c.5470_5477del (3/15 each) , followed by c.5155del and c.5074+1G>T. BRCA2 pathogenic mutations were detected in 16 cases (3.5%) , with c.9097del and c.7681C>T being the most common (2/16 each) . In the non-breast cancer cohort (321 cases) , BRCA1 and BRCA2 pathogenic mutations were observed in 1 (0.3%) and 2 cases (0.6%) , respectively. Variants of uncertain significance (VUS) in BRCA1 were identified in 13 breast cancer patients (2.8%) and 8 non-breast cancer individuals (2.5%) , while BRCA2 variants of uncertain significance (VUS) occurred in 28 breast cancer patients (6.0%) and 21 non-breast cancer individuals (6.5%) . The overall BRCA1/2 mutation rate was significantly higher in breast cancer patients than in non-breast cancer individuals (15.6% vs 10.0%, P=0.039) . BRCA1/2-mutated breast cancer patients had a higher proportion of diagnosis under the age of 45 (48.4% vs 31.5%, P=0.001) , family cancer history (32.3% vs 6.2%, P<0.001) , and bilateral breast cancer (9.7% vs 1.9%, P=0.014) compared with non-mutated patients. Tumor histological grade and Ki-67 expression also differed significantly between mutation carriers and non-carriers (P=0.016, 0.040) . BRCA1 mutation carriers had a higher proportion of early-onset diagnoses (<45 years) than BRCA2 mutation carriers (66.7% vs 31.2%, χ²=4.841, P=0.028) . Significant differences were observed between BRCA1 and BRCA2 mutation carriers in histologic grade, ER/PR status, Ki-67 expression, and molecular subtypes (P=0.023, 0.010, 0.020, 0.035, 0.004) .

BRCA1/2 pathogenic mutations in breast cancer patients are linked to early-onset breast cancer, family cancer history and bilateral breast cancer. Breast cancer patients with BRCA1 and BRCA2 mutations exhibit considerable differences in their clinicopathological characteristics, highlighting the need for further research into their distinct pathogenesis.

To analyze the efficacy of pyrotinib in the patients with HER-2-positive breast cancer and identify risk factors associated with poor prognosis.

A retrospective cohort study was conducted, involving 250 HER-2-positive breast cancer patients in the People’s Hospital of Yuechi County, Sichuan Province from May 2020 to May 2023. Among them, 125 patients receiving pyrotinib combined with conventional chemotherapy served as the observation group, and 125 patients undergoing conventional chemotherapy served as the control group. The chemotherapy efficacy and adverse reaction rates between the two groups were compared using χ² test. Progression-free survival (PFS) was analyzed using the Kaplan-Meier method, with log-rank tests used for intergroup PFS comparisons. Cox proportional hazards models were used for multivariate analysis of potential risk factors of poor prognosis. Patients were randomly divided into a modeling group and a validation group (7∶3 ratio) using simple random sampling. The R 4.1.0 software with the rms package was utilized to establish a prognostic prediction model for HER-2-positive breast cancer. Bootstrap validation was performed to calculate the concordance index (C-index) . Receiver operating characteristic (ROC) curves were plotted, and the area under the curve (AUC) was computed to evaluate the predictive value of the nomogram model.

The overall response rate was significantly higher in the observation group than in the control group (86.4% vs 69.6%, χ²=10.280, P=0.001) . No significant difference was found in the incidence of adverse reactions between two groups (all P>0.050). After a median follow-up of 24 months, the PFS was significantly longer in the observation group than in the control group [20.0 (18.0, 21.0) months vs 17.0 (16.0, 19.0) months, Z=16.673, P<0.001]. Among the 175 patients in the modeling group, 39 (22.3%) had poor prognosis, while 16 out of 75 patients (21.3%) in the validation group experienced poor prognosis, with no significant intergroup difference (χ²=0.028, P=0.868) . Multivariate analyses identified visceral metastasis (HR=2.684, 95%CI: 1.056-6.821, P=0.038) , Ki-67 positivity (HR=8.209, 95%CI: 3.048-22.106, P<0.001) , clinical stage Ⅲ (HR=4.038, 95%CI: 1.865-8.744, P<0.001) , and elevated expression of TNF-α (HR=7.433, 95%CI: 3.370-16.396, P<0.001) , IL-6 (HR=1.066, 95%CI: 1.004-1.131, P=0.036) and IL-8 (HR=1.735, 95%CI: 1.251-2.406, P=0.001) as independent risk factors for poor prognosis. The C-index values were 0.938 and 0.946 in the modeling and validation group, respectively, with calibration curves closely aligned to the ideal curve. The modeling group achieved an AUC of 0.936 (95%CI: 0.879-0.993, P<0.001) , while the validation group showed an AUC of 0.944 (95%CI: 0.872-0.988, P<0.001) .

Pyrotinib significantly improves therapeutic efficacy in patients with HER-2-positive breast cancer. The prognostic prediction model developed in this study can identify patients requiring intensified adjuvant therapy.