Chemotherapy-induced peripheral neuropathy (CIPN) is a severe paclitaxel-associated adverse effect in cancer treatment. This study explored celecoxib's therapeutic efficacy against paclitaxel-induced neuropathy in rats via the COX-2/PGE2 pathway. Behavioral assays revealed celecoxib attenuated paclitaxel-induced thermal/mechanical hypersensitivity; histological analyses demonstrated it ameliorated neuronal damage in the DRG, sciatic nerve, and plantar skin. Celecoxib also downregulated paclitaxel-induced upregulation of COX-2, PGE2, and MHC in these tissues. In vitro, it suppressed DRG neuronal apoptosis and promoted survival by regulating COX-2/PGE2 signaling. Its effects were comparable to COX-2 gene silencing, with a favorable preclinical safety profile supporting long-term clinical use. These findings elucidate the neuroprotective mechanism of celecoxib, propose COX-2/PGE2 as a therapeutic target for CIPN, and lay a foundation for relevant combination therapy research, highlighting celecoxib's potential in CIPN management.

Breast cancer exhibits profound biological and spatial heterogeneity, which contributes to variable responses to neoadjuvant chemotherapy (NAC) and challenges precision treatment planning. Radiomics, an emerging discipline that converts standard medical images into high-dimensional quantitative data, offers a non-invasive and reproducible means to capture tumor phenotype, heterogeneity, and treatment-induced changes. This review provides a comprehensive overview of recent advances in radiomics for breast cancer NAC, emphasizing the roles in predicting a pathologic complete response (pCR), monitoring early therapeutic efficacy, and quantifying intratumoral heterogeneity. Among imaging modalities, magnetic resonance imaging (MRI)-based radiomics, particularly utilizing dynamic contrast-enhanced and diffusion-weighted sequences, demonstrates robust predictive performance for the pCR, with multi-center studies reporting area under the curve (AUC) values >0.80. Longitudinal and delta-radiomics approaches further enhance early response evaluation by tracking temporal alterations in imaging features that precede measurable morphologic regression. Radiomic assessment of tumor heterogeneity, especially in triple-negative breast cancer (TNBC), reveals strong associations with immune infiltration, metabolic reprogramming, and therapeutic resistance, providing mechanistic insight into radiomic biomarkers. Integrative multi-omics frameworks, combining radiomics with genomics, transcriptomics and pathomics, are increasingly elucidating the biological underpinnings of imaging phenotypes, improving both model interpretability and clinical relevance. Despite these advances, widespread clinical adoption of radiomics is limited by methodologic variability, lack of standardization, and insufficient external validation. Future efforts should focus on harmonized imaging protocols, explainable artificial intelligence, and prospective multi-center trials to translate radiomics into a clinically actionable tool. Collectively, radiomics represents a transformative approach for individualized response prediction and dynamic treatment optimization in precision breast cancer management (Figure 1).

BACKGROUND:Pegfilgrastim-induced bone pain (PIBP) is common and lacks effective treatment. OBJECTIVE:To determine whether there is an association between the timing of pegfilgrastim administration and PIBP. DESIGN:Three-arm randomized controlled trial. (ClinicalTrials.gov: NCT05841186). SETTING:A tertiary A-level hospital. PATIENTS:Patients with I to III stage breast cancer who were naive to chemotherapy. INTERVENTION:Patients were randomly allocated in a 1:1:1 ratio to the 24-hour, 48-hour, or 72-hour group based on the timing of pegfilgrastim administration postchemotherapy. MEASUREMENTS:The primary end point was the area under the curve (AUC) of the daily worst bone pain score (assessed using the "worst pain" question from the Brief Pain Inventory, a 0 to 10 numerical rating scale [NRS]) for 5 consecutive days in the first chemotherapy cycle. Secondary end points included the incidence of severe bone pain (>5 on the NRS), neutropenia, and febrile neutropenia (FN). RESULTS:The intention-to-treat analyses included 159 patients, with 53 in each group. For the first cycle, in the 72-hour group, the mean AUC exhibited a statistically significant reduction from 12.74 in the 24-hour group and 14.20 in the 48-hour group to 6.05 (all P < 0.001). Furthermore, the incidence of severe bone pain also declined significantly from 58.5% in the 24-hour group and 66.0% in the 48-hour group to 22.6% in the 72-hour group (all P < 0.001). There was no substantial difference in the incidence of neutropenia among groups, and no patients developed FN. LIMITATION:Open label, single center, and relatively small sample size. CONCLUSION:Administration of pegfilgrastim 72 hours postchemotherapy reduced PIBP compared with 24- and 48-hour administration and did not seem to be associated with higher rates of neutropenia or FN. PRIMARY FUNDING SOURCE:National Natural Science Foundation of China.

Objectives:This study aims to create a model that combines ultrasonography (US), magnetic resonance imaging (MRI) examination, and clinicopathological features to predict the axillary pathological complete response (pCR) of patients with breast cancer (BC) who receive neoadjuvant therapy (NAT). Methods:This retrospective study included 600 patients with node-positive breast cancer who were eligible for enrollment (clinical stage cT1-4 and cN1-3) and received neoadjuvant therapy from January 2011 to January 2024. Before biopsy and neoadjuvant therapy, these patients underwent ultrasound (US) and MRI imaging of breast lesions and axillary lymph nodes (ALNs), and clinicopathological features were recorded before and after NAT. All imaging evaluations were independently performed by two experienced breast radiologists (with >10 years of experience), and discrepancies were resolved by consensus. Independent risk factors for predicting ALN status after NAT were identified by univariate and multivariate analyses. These independent risk factors were used for nomogram construction. Results:Univariate logistic regression analysis revealed that the maximum diameter of the breast lesions on MRI after NAT (p < 0.001), MRI ADC-value after NAT (p < 0.001), maximum and minimum diameter of the ALN on US after NAT (p < 0.001), the Ki67 level (p < 0.001), tumor grade 3 (p = 0.017), primary ALN stage cN 2 (p = 0.022), efficacy evaluation of the neoadjuvant therapy, pT stage, MP classification, HR, HER2, and the presence of the Hilum of the lymph gland were significantly associated with ALN pCR after NAT (p < 0.05). In the multivariate logistic regression analysis, ypT2 (p < 0.001), ypT3 (p = 0.007), HER2 (p < 0.001), response PR (p = 0.007), efficacy evaluation (SD/PD) (p = 0.010), and the presence of the Hilum of the lymph gland on US after NAT(p < 0.001) were considered independent predictors of ALN pCR after NAT. The area under the curve (AUC) of the nomogram was 0.934(95% CI: 0.913-0.960) in the training set and 0.908 (95% CI: 0.867-0.950) in the validation set, with a sensitivity of 82.0% and a specificity of 89.1% in the training set. Conclusion:Our noninvasive model based on US, MRI, and clinicopathological features can help accurately identify patients with ALN pCR after NAT and prevent unnecessary axillary lymph node dissection (ALND).

PURPOSE:The neoCARHP aimed to investigate the efficacy and safety of investigator-selected taxane (docetaxel, paclitaxel, or nab-paclitaxel) plus trastuzumab and pertuzumab, with carboplatin (TCbHP) or without carboplatin (THP), in stage II and III human epidermal growth factor receptor 2 (HER2)-positive breast cancer. METHODS:The neoCARHP was a multicenter, randomized, phase III, noninferiority study. Eligible patients were women age 18 years or older with previously untreated, stage II and III, HER2-positive invasive breast cancer. Patients were randomly assigned (1:1) to receive six 3-week cycles of TCbHP or THP. The primary end point was pathologic complete response (pCR) rate in the breast and axilla (ypT0/is ypN0) in the modified intention-to-treat (mITT) population (all randomly assigned patients receiving at least one dose of study treatment). Safety was evaluated in all patients who received any study treatment. RESULTS:Between April 30, 2021, and August 27, 2024, 774 patients were randomly assigned and 766 were included in the mITT population (382 in THP and 384 in TCbHP). pCR was achieved in 245 (64.1% [95% CI, 59.1 to 69.0]) patients in the THP group and 253 (65.9% [60.9-70.6]) in the TCbHP group (absolute difference, -1.8% [95% CI, -8.5 to 5.0]; odds ratio, 0.93 [95% CI, 0.69 to 1.25]; Pnoninferiority = .0089). The THP group had fewer grade 3 and 4 adverse events (20.7% v 34.6%) and serious adverse events (1.3% v 4.7%) than the TCbHP group. The most common grade 3 and 4 adverse events with THP were neutropenia (6.8% v 16.4% with TCbHP), leukopenia (5.5% v 14.8%), and diarrhea (2.6% v 4.2%). No treatment-associated deaths occurred. CONCLUSION:THP provided noninferior pCR rates and improved tolerability compared with TCbHP. Omitting carboplatin may be applicable in HER2-positive breast cancer.

BACKGROUND:Ischemic complications are common and severe postoperative complications in nipple-sparing mastectomy (NSM). This study aimed to evaluate the impact of preoperative three-dimensional (3D) vascular reconstruction assessment on the incidence of ischemic complications following laparoscopic-assisted NSM. MATERIALS AND METHODS:In this prospective randomized trial (October 2023-November 2024), 126 women scheduled for laparoscopic-assisted NSM were allocated 1:1. The experimental group underwent preoperative breast MRI (1mm slices) segmented in Mimics Software to create a 360° vascular heat-map that was projected onto the skin after induction. Under endoscopy, electrocautery dissected along the superficial fascia in perforator-rich zones, preserving a 2mm adipose cuff and clipping side branches; avascular zones were dissected with a scalpel after tumescence (500mL saline + 1mg adrenaline), avoiding thermal injury. Control group received electrocautery alone without mapping. Primary endpoint was nipple-areola complex ischemia at 1 and 2 weeks. RESULTS:A total of 126 patients were enrolled, with 39 cases (31.0%) experiencing ischemic events 1 week postoperatively. Two additional cases of ischemic events occurred 2 weeks postoperatively, while three patients recovered from mild ischemia. The use of 3D vascular reconstruction was associated with a significant reduction in the incidence of ischemic complications ( P = 0.012). Among those with ischemic events 1 week postoperatively, 23 had perfusion injury or ischemic damage, 12 had partial-thickness necrosis, and 4 had full-thickness necrosis. The severity of ischemic complications in the second week was similar to the first week. Regarding secondary endpoints, patients who underwent preoperative assessment with 3D vascular reconstruction had shorter operation time; however, no statistically significant differences were observed in body mass index, resected breast weight, blood loss, or BREAST-Q scores. CONCLUSION:Preoperative 3D vascular reconstruction assessment and the use of a combination of sharp dissection and electrocautery during dissection of skin flaps in laparoscopic-assisted NSM can significantly reduce the risk of ischemic complications.

PURPOSE:Up to 60% of breast cancer (BC) patients with positive sentinel lymph nodes (SLNs) after neoadjuvant chemotherapy (NAC) had no metastatic non-sentinel lymph node (non-SLN). We aimed to establish a model incorporating sentinel chain involvement pattern to predict the non-SLN status. METHODS:SLNs were ranked in the order of fluorescent intensity, black staining degree, and lymphatic drainage to form a sentinel chain, which included three involvement patterns: sequential pattern (metastases are found in SLNs ranking ahead), skip pattern (metastases do not relate to the order of SLNs), and all involved pattern. The relationship between sentinel chain involvement pattern and non-SLN metastasis was explored. RESULTS:Of the 316 patients analyzed, 98.6% (71/72) of patients with all involved pattern, 58.9% (66/112) with skip pattern, and 13.6% (18/132) with sequential pattern had non-SLN metastases. The non-SLN metastasis rate in sequential pattern was significantly lower than that in the other two patterns (OR Skip pattern = 15.83, 95% CI: 5.14-48.80, p < 0.001; OR All involved pattern = 2.273, 95% CI: 0.15-35.56, p = 0.559). Multivariate logistic regression indicated that factors including sentinel chain involvement pattern, number of positive and negative SLNs, and primary tumor size were independent predictors of non-SLN. The model showed adequate discrimination, with AUC of 0.942 and 0.930 in training and validation cohort, respectively. CONCLUSION:The model demonstrated satisfactory performance in predicting non-SLN metastasis in BC patients with positive SLNs after NAC and had potential to select patients with low risk of non-SLNs metastasis who could avoid ALND.

Neoadjuvant chemoimmunotherapy (NACI) has emerged as the standard treatment for early-stage triple-negative breast cancer (TNBC). However, reliable biomarkers for identifying patients who are likely to benefit from NACI are lacking. This study aims to develop an intratumoral microbiota-aided radiomics model for predicting pathological complete response (pCR) in patients with TNBC. Intratumoral microbiota are characterized by 16S rDNA sequencing and quantified through experimental assays. Single-cell RNA sequencing is performed to analyze the tumor microenvironment of tumors with various responses to NACI. Radiomics features are extracted from tumor regions on longitudinal magnetic resonance images (MRIs) scanned before and after NACI in the training set. On the basis of treatment response (pCR or non-pCR) and intratumoral microbiota scoring, we select key radiomics features and construct a fusion model integrating multi-timepoint (pre-NACI and post-NACI) MRI to predict the efficacy of immunotherapy, followed by independent external validation. A total of 124 patients are enrolled, with 88 in the training set and 36 in the validation set. Tumors from patients who achieves pCR present a significantly greater intratumoral microbiota load than tumors from patients who achieve non-pCR (p < 0.05). Additionally, tumors in non-pCR group exhibit greater infiltration of tumor-associated SPP1+ macrophages, which is negatively correlated with the microbiota load. On the basis of intratumoral microbiota scoring, we select 17 radiomics features and use them to construct the fusion radiomics model. The fusion model achieves the highest AUC of 0.945 in the training set, outperforming pre-NACI (AUC = 0.875) and post-NACI (AUC = 0.917) models. In the validation set, this model maintains a superior AUC of 0.873, surpassing those of pre-NACI (AUC = 0.769) and post-NACI (AUC = 0.802) models. Clinically, the fusion model distinguishes patients who achieve pCR from those who do not with an accuracy of 77.8

Neoadjuvant therapies are essential for managing high-risk early-stage breast cancer, but their effectiveness is limited, necessitating the exploration of the optimal neoadjuvant treatment strategy based on innovative subtypes. Given the heterogeneity inherent in breast cancer, there is growing need for identifying novel molecular subtypes predictive of treatment response through multi-omic analyses. A comprehensive analysis was performed using data from 142 high-risk early breast cancer patients, including genomic, transcriptomic, proteomic, and phosphoproteomic profiles. The molecular subtypes were explored based on the biological characteristics and responses to neoadjuvant treatments. The results were also validated in the TCGA-breast cancer cohort and external dataset. Three molecular subtypes were identified, each associated with different optimal treatment strategies. The immune-activated (IA) subtype displayed a significantly higher pathologic complete response (pCR) rate when treated with platinum-based neoadjuvant regimens, and exhibited heightened immune cell infiltration. The vesicular transport pathway-activated (VT) subtype, characterized by vesicular transport pathway activation, showed a favorable pCR rate to anthracycline-based neoadjuvant chemotherapy. In contrast, the kinase activation (KA) subtype demonstrated limited responsiveness to both platinum and anthracycline-based treatments and featured enrichment in non-canonical TGF-β signaling, MAPK/ATM kinase activation, and angiogenic signatures. A seven-gene classifier linked to non-canonical TGF-β signaling was created to identify the KA subtype, achieving an area under the curve value of 90

Background:Axillary surgical staging is required for patients with upgraded ductal carcinoma in situ (DCIS) (DCIS is diagnosed on core biopsy with invasive cancer found on pathology after complete surgical excision), which may lead to complications in axillary surgery. At present, there is no reliable and accurate method for predicting axillary lymph node metastasis (ALNM) in patients with upgraded DCIS; however, such a method could prevent unnecessary axillary surgical interventions from being performed. In this study, we aimed to construct a non-invasive model for predicting ALNM in DCIS patients based on clinicopathological characteristics, mammography (MG) features, and magnetic resonance imaging (MRI) features. Methods:Between February 2018 and June 2020, 326 patients with upgraded DCIS were enrolled in this retrospective analysis. These patients were randomly divided into the training cohort (80%) and validation cohort (20%). Univariate and multivariable regression analyses were conducted to identify the candidate pathological features, which then used to develop a clinicopathological model. The features of the 2-mm, 4-mm, and 6-mm intratumoral and peritumoral regions (T-PTR) were extracted to develop the MRI radiomics model, and two deep learning classification models were developed based on the medial-lateral oblique (MLO) and craniocaudal (CC) views of the MG. A fusion model was then established that combined these sub-models. The receiver operating characteristic (ROC) curve, area under the curve (AUC), and other indicators were used to evaluate the performance of these models. Results:The clinicopathological characteristics of the two cohorts were basically balanced. The AUC values of the clinicopathological model were 0.675 and 0.690 in the training and validation cohorts, respectively. The model based on the T-PTR of MRI showed promising predictive ability. Among the three MRI models, the T-PTR (4 mm) model showed the best predictivity both in the training (AUC =0.885) and validation cohorts (AUC =0.843). The AUC values for the deep learning models of the MG CC and MLO positions all exceeded 0.7, indicating reliable predictive performance. The fusion model that combined the three methods significantly improved the accuracy and robustness of ALNM prediction. In both the training (AUC =0.975) and validation (AUC =0.877) cohorts, the fusion model showed excellent performance. Conclusions:We developed a fusion model that combined clinicopathological characteristics, MRI T-PTR (4 mm) radiomics, and MG-based deep learning. Our combined model showed promising performance in predicting ALNM in patients with upgraded DCIS.

BACKGROUND:Neoadjuvant immunotherapy combined with chemotherapy (Chemo-IM) is associated with significantly improved pathological complete response (pCR) rates and long-term survival outcomes in patient with early-stage triple-negative breast cancer (TNBC). However, only a small proportion of patients benefit from the addition of immunotherapy. Here, we explored and confirmed the role of intratumoral microbiota in screening patients with TNBC who are likely to benefit from neoadjuvant Chemo-IM. METHODS:Patients with previously untreated, non-metastatic TNBC receiving neoadjuvant Chemo-IM were enrolled. Differences in the intratumoral microbiota between the pCR and non-pCR groups were explored via 16S rDNA sequencing (16S-seq). Single-cell transcriptome sequencing (scRNA-seq) was employed to profile the tumor microenvironment (TME). Moreover, correlations between the intratumor microbiota and the TME were explored. Finally, machine-learning models based on the intratumoral microbiota were constructed to predict pCR. RESULTS:A total of 89 female patients with early-stage TNBC treated by neoadjuvant Chemo-IM were enrolled. We found that the pCR group had greater diversity and a higher load of intratumoral microbiota than the non-pCR group. Intriguingly, scRNA-seq revealed significantly increased T cell infiltration and decreased tumor-associated macrophage infiltration into tumors in the pCR group. Moreover, intratumoral microbiota load was positively associated with CD4+CXCL13+ T cell infiltration and negatively associated with CD68+SPP1+ macrophage infiltration. Combined analysis of 16S-seq and scRNA-seq data revealed that intratumoral microbiota were present in both cancer and immune cells. Finally, we developed a model incorporating intratumoral microbiota and clinicopathological characteristics, and it showed strong power for predicting pCR to neoadjuvant Chemo-IM. CONCLUSIONS:Intratumoral microbiota may serve as a strong and specific predictor of the response of patients with early-stage TNBC to neoadjuvant Chemo-IM. Our findings could contribute to the development of individualized Chemo-IM strategies for treating TNBC.

Breast magnetic resonance imaging (MRI) is the most sensitive imaging method for diagnosing breast cancer and assessing treatment response. Artificial intelligence (AI) and radiomics offer new opportunities to identify patterns in imaging data, supporting personalized post-neoadjuvant surgical decisions. This paper reviewed breast MRI-based AI models for predicting outcomes after neoadjuvant therapy, with a focus on evidence from the Western Pacific region, to evaluate the quality of existing models, discuss their inherent limitations, and outline potential future directions. A literature search in MEDLINE, EMBASE, and Web of Science identified 51 relevant studies in the region, with the majority conducted in China, followed by South Korea and Japan. Most studies focused on predicting pathologic complete response (pCR), with a median sample size of 152 and largely retrospective single-center designs. Model performance was commonly assessed using validation sets, with pooled sensitivity and specificity for pCR prediction showing promising results. Models incorporating multitemporal MRI features were associated with improved accuracy. While MRI-based AI models show potential for guiding surgical planning, improved methodological quality and algorithmic explainability are needed to facilitate clinical translation.

Patient-derived organoids (PDOs) may facilitate treatment selection. This retrospective cohort study evaluated the feasibility and clinical benefit of using PDOs to guide personalized treatment in metastatic breast cancer (MBC). Patients diagnosed with MBC were recruited between January 2019 and August 2022. PDOs were established and the efficacy of customized drug panels was determined by measuring cell mortality after drug exposure. Patients receiving organoid-guided treatment (OGT) were matched 1:2 by nearest neighbor propensity scores with patients receiving treatment of physician's choice (TPC). The primary outcome was progression-free survival. Secondary outcomes included objective response rate and disease control rate. Targeted gene sequencing and pathway enrichment analysis were performed. Forty-six PDOs (46 of 51, 90.2%) were generated from 45 MBC patients. PDO drug screening showed an accuracy of 78.4% (95% CI 64.9%-91.9%) in predicting clinical responses. Thirty-six OGT patients were matched to 69 TPC patients. OGT was associated with prolonged median progression-free survival (11.0 months vs. 5.0 months; hazard ratio 0.53 [95% CI 0.33-0.85]; p = .01) and improved disease control (88.9% vs. 63.8%; odd ratio 4.26 [1.44-18.62]) compared with TPC. The objective response rate of both groups was similar. Pathway enrichment analysis in hormone receptor-positive, human epidermal growth factor receptor 2-negative patients demonstrated differentially modulated pathways implicated in DNA repair and transcriptional regulation in those with reduced response to capecitabine/gemcitabine, and pathways associated with cell cycle regulation in those with reduced response to palbociclib. Our study shows that PDO-based functional precision medicine is a feasible and effective strategy for MBC treatment optimization and customization.

Purpose: This study aims to explore whether neoadjuvant chemotherapy with immunotherapy (NACI) leads to different tumor shrinkage patterns, based on magnetic resonance imaging (MRI), compared to neoadjuvant chemotherapy (NAC) alone in patients with triple-negative breast cancer (TNBC). Additionally, the study investigates the relationship between tumor shrinkage patterns and treatment efficacy was investigated. Methods: This retrospective study included patients with TNBC patients receiving NAC or NACI from January 2019 until July 2021 at our center. Pre- and post-treatment MRI results were obtained for each patient, and tumor shrinkage patterns were classified into three categories as follows: 1) concentric shrinkage (CS); 2) diffuse decrease; and 3) no change. Tumor shrinkage patterns were compared between the NAC and NACI groups, and the relevance of the patterns to treatment efficacy was assessed. Results: Of the 99 patients, 65 received NAC and 34 received NACI. The CS pattern was observed in 53% and 20% of patients in the NAC and NACI groups, respectively. Diffuse decrease pattern was observed in 36% and 68% of patients in the NAC and NACI groups. The association between the treatment regimens (NAC and NACI) and tumor shrinkage patterns was statistically significant (p p = 0.004). The postoperative pathological complete response (pCR) rate was 45% and 82% in the NAC and NACI groups (p p < 0.001), respectively. In the NACI group, 17% of patients with the CS pattern and 56% of those with the diffuse decrease pattern achieved pCR (p p = 0.903). All tumor shrinkage patterns were associated with achieved a high pCR rate in the NACI group. Conclusion: Our study demonstrates that the diffuse decrease pattern of tumor shrinkage is more common following NACI than that following NAC. Furthermore, our findings suggest that all tumor shrinkage patterns are associated with a high pCR rate in patients with TNBC treated with NACI.

The number of breast cancer (BC) patients is increasing year by year, which is severely endangering to human life and health. c-Myc is a transcription factor, studies have shown that it is a very significant factor in tumor progression, but how it is regulated in BC is still not well understood. Here, we used the RIP microarray sequencing to confirm circXPO6, which had a high affinity with c-Myc and highly expressed in triple-negative breast cancer (TNBC) tissues and cells. CircXPO6 overexpression promoted tumor growth in vivo and in vitro. Furthermore, circXPO6 largely promoted the expression of genes related to glucose metabolism, such as GLUT1, HK2, and MCT4 in TNBC cells. Finally, high levels of circXPO6 expression were found to be closely associated with malignant pathological factors, such as tumor size, lymph node metastasis, TNM staging, and histopathological grading of TNBC. Mechanistically, circXPO6 interacted with c-Myc to prevent speckle-type POZ-mediated c-Myc ubiquitination and degradation, thus promoting TNBC progression. Through the regulation of c-Myc-mediated signal transduction, circXPO6 plays a key role in TNBC progresses. This discovery can provide new ideas for TNBC molecular targeted therapy.

Background: The high false negative rate (FNR) associated with sentinel lymph node biopsy often leads to unnecessary axillary lymph node dissection following neoadjuvant chemotherapy (NAC) in breast cancer. The authors aimed to develop a multifactor artificial intelligence (AI) model to aid in axillary lymph node surgery. Materials and Methods: A total of 1038 patients were enrolled, comprising 234 patients in the primary cohort, 723 patients in three external validation cohorts, and 81 patients in the prospective cohort. For predicting axillary lymph node response to NAC, robust longitudinal radiomics features were extracted from pre-NAC and post-NAC magnetic resonance images. The U test, the least absolute shrinkage and selection operator, and the spearman analysis were used to select the most significant features. A machine learning stacking model was constructed to detect ALN metastasis after NAC. By integrating the significant predictors, we developed a multifactor AI-assisted surgery pipeline and compared its performance and false negative rate with that of sentinel lymph node biopsy alone. Results: The machine learning stacking model achieved excellent performance in detecting ALN metastasis, with an area under the curve (AUC) of 0.958 in the primary cohort, 0.881 in the external validation cohorts, and 0.882 in the prospective cohort. Furthermore, the introduction of AI-assisted surgery reduced the FNRs from 14.88 (18/121) to 4.13% (5/121) in the primary cohort, from 16.55 (49/296) to 4.05% (12/296) in the external validation cohorts, and from 13.64 (3/22) to 4.55% (1/22) in the prospective cohort. Notably, when more than two SLNs were removed, the FNRs further decreased to 2.78% (2/72) in the primary cohort, 2.38% (4/168) in the external validation cohorts, and 0% (0/15) in the prospective cohort. Conclusion: Our study highlights the potential of AI-assisted surgery as a valuable tool for evaluating ALN response to NAC, leading to a reduction in unnecessary axillary lymph node dissection procedures.

e12600 Background: Neoadjuvant chemotherapy is the backbone treatment modalities for BC patients for locally advanced breast cancer (BC) improves R0 resection rate. Determinants of differentially therapeutic response to anthracycline or platinum-based neoadjuvant therapy were largely unknown but were urgently needed to maximize patients’ benefit. Methods: A total of 149 local advanced (cT2-3, cN0-2, cM0-1) BC patients (HER2 positive BC, n = 54 and TNBC, n = 95) were retrospectively enrolled in the study, whole-exon sequencing (WES), mRNA sequencing and (phosphor-)proteomics were systematically conducted and comprehensively analyzed. The primary end point of the study was the pathological complete response (pCR) rate. The Cancer Genome Atlas (TCGA) BC dataset and GSE130787 set were used to validate our analysis. Cancer cell line encyclopedia (CCLE) dataset was utilized to screen putative small molecular inhibitors to BC cells with molecular features of resistance. Results: Through integrated analysis of multi-omics data, three subtypes with distinct molecular features were identified: immune-activated (IA) subtype, vesicular transport pathways activation (VTs) subtype, and kinase activation (KA) subtype. Same scenario of molecular subtypes can be repeated in TCGA dataset and prognosis of these subtypes can be differentiate ( p= 0.02). Patients with IA subtype majorly favored cisplatin-based treatment ( p= 0.005). And this phenomenon was confirmed in external dataset (GSE130787, n = 26, HER2-positive BC receiving TCbH treatment). Patients with VTs subtype, with significant enrichment of vesicular transport-related pathways, displayed anthracycline sensitivity. Anthracycline transporter, ABCB1 expression was significantly reduced in VTs subtype at both mRNA ( p < 0.001) and protein ( p < 0.05) levels. CCLE breast cancer cells with the characteristics of VTs subtype and lower ABCB1 expression also displayed the sensitivity of epirubicin ( p = 0.0037). Patient with KA subtype was insensitive to both platinum and anthracycline-based therapy. Multiple kinase pathways, especially, non-canonical TGF-β signaling pathway-related genes were overexpressed (p < 0.05), and significantly correlated with non-pCR ( p= 0.002). Phosphor-proteomic analysis indicated TGFβ1-mediated RhoA/ROCK pathway (Cofilin, RhoA kinase, MYH14 proteins) were highly activated. Eleven drugs were found in CCLE inhibiting growth of BC cell lines with upregulated non-canonical TGF-β pathway genes ( p < 0.05). Conclusions: Three multi-omic subtypes with distinct response to anthracycline or platinum-based therapy were identified. Moreover, activated non-canonical TGF-β pathway may mediate therapeutic resistance, but also indicated therapeutic vulnerabilities of several kinase inhibitors.

Background:Recent studies have shown that homologous recombination deficiency (HRD) may be correlated with the pathological complete response (pCR) rate. This meta-analysis aimed to determine the predictive value of HRD for the pCR rate in patients with triple-negative breast cancer (TNBC) receiving platinum-based neoadjuvant chemotherapy (NCT). Methods:Published articles were searched in the PubMed, Embase, Medline, Web of Science, and Cochrane databases up to 1 June 2021, and studies reporting the pCR rate for HRD carriers on platinum-based NCT were selected. Odds ratios (ORs) with 95% confidence intervals (CIs) were determined for the pCR rate, clinical response rate, and Grade 3 or higher adverse events (AEs) using the random-effects model. Bias risk was evaluated using the Cochrane Collaboration tool (PROSPERO, registration number CRD42021249874). Results:Seven studies were eligible. The results showed that HRD carriers had higher pCR rates than non-HRD carriers across all treatment arms (OR = 3.84, 95% CI = [1.93, 7.64], p = 0.0001). Among HRD carriers, the pCR rate was higher in patients on platinum-based NCT than in those without platinum exposure (OR = 1.95, 95% CI = [1.17, 3.23], p = 0.01). We did not observe marked pCR improvements in non-HRD carriers. Among HRD carriers, the pCR rates in the mutant and wild-type breast cancer susceptibility gene (BRCA) groups did not differ significantly (OR = 2.00, 95% CI = [0.77, 5.23], p = 0.16), but HRD carriers with wild-type BRCA had a significant advantage over non-HRD carriers on platinum-based NCT (OR = 3.64, 95% CI = [1.83, 7.21], p = 0.0002). Conclusion:HRD is an effective predictor of increased pCR rates in platinum-based NCT, especially in wild-type BRCA patients. Adding platinum to NCT for non-HRD carriers can increase the incidence of AEs but may not improve the therapeutic effect.

Background: For patients with breast cancer who receive docetaxel chemotherapy, taxane-associated acute pain syndrome (T-APS), considered a form of neural pathology, is a significant clinical problem. We evaluated the effect of prophylactic etoricoxib on T-APS in patients with breast cancer. Materials and methods: We conducted a phase II randomised trial including 144 patients with breast cancer receiving four cycles of docetaxel-based chemotherapy. Patients were randomised in the ratio 1:1 to receive prophylactic etoricoxib (60 mg, Day 1 to Day 8) or no prophylactic treatment. The primary end-point was the overall incidence of T-APS across all cycles. Secondary end-points included the incidence of severe pain (greater than 5 on a scale 0-10); severity and duration of T-APS; Functional Assessment of Cancer Therapy-Breast subscale; chronic sensory and motor neurotoxicity and adverse events. Results: The overall incidence of T-APS across all cycles of chemotherapy in the etoricoxib group was 57.1%, while that in the control group was 91.5% (P < 0.001). The incidences of severe T-APS were 11.4% and 54.9% for the etoricoxib and control groups, respectively (P < 0.001). The mean Functional Assessment of Cancer Therapy-Breast subscale score of the etoricoxib group (103.79-107.24) was significantly higher than that of the control group (93.88-96.71) (P = 0.001 at cycle 1 and P < 0.001 at cycles 2-4). After four cycles of docetaxel chemotherapy, the etoricoxib group demonstrated a significantly higher mean Functional Assessment of Cancer Treatment Neurotoxicity subscale score than the control group (38.46, 95% CI: 37.63-39.29; 34.59, 95% CI: 33.73-35.45, respectively; P < 0.001). Electromyography showed that most peripheral sensory nerves in the etoricoxib group had significantly improved action potential amplitudes and conduction velocities compared with those in the control group. Conclusion: Prophylactic use of etoricoxib could significantly reduce the incidence and severity of docetaxel-induced acute pain syndrome and potentially decrease docetaxel-induced peripheral neuropathy. (C) 2022 Elsevier Ltd. All rights reserved.