Clinical efficacy of tumor organoid-guided cancer therapy for locally advanced unresectable or metastatic breast cancer.

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.

CircXPO6 promotes breast cancer progression through competitively inhibiting the ubiquitination degradation of c-Myc.

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.

Neoadjuvant docetaxel plus carboplatin vs epirubicin plus cyclophosphamide followed by docetaxel in triple-negative, early-stage breast cancer (NeoCART): Results from a multicenter, randomized controlled, open-label phase II trial.

Previous studies have shown that the addition of carboplatin to neoadjuvant chemotherapy improved the pathologic complete response (pCR) rate in patients suffering from triple-negative breast cancer (TNBC) and patients who obtained a pCR could achieve prolonged event-free survival (EFS) and overall survival (OS). However, no studies have assessed the effects of the combination of docetaxel and carboplatin without anthracycline with taxane-based and anthracycline-based regimens. The NeoCART study was designed as a multicenter, randomized controlled, open-label, phase II trial to assess the efficacy and safety of docetaxel combined with carboplatin in untreated stage II-III TNBC. All eligible patients were randomly assigned, at a 1:1 ratio, to an experimental docetaxel plus carboplatin (DCb) for six cycles group (DCb group) or an epirubicin plus cyclophosphamide for four cycles followed by docetaxel for four cycles group (EC-D group). PCR (ypT0/is ypN0) was evaluated as the primary outcome. Between 1 September 2016 and 31 December 2019, 93 patients were randomly assigned and 88 patients were evaluated for the primary endpoint (44 patients in each group). In the primary endpoint analysis, 27 patients in the DCb group (61.4%, 95% CI 47.0-75.8) and 17 patients in the EC-D group achieved a pCR (38.6%, 95% CI 24.3-53.0; odds ratio 2.52, 95% CI 2.4-43.1; Pnoninferiority = .004). Noninferiority was met, and the DCb regimen was confirmed to be superior to the EC-D regimen (P = .044, superiority margin of 5%). At the end of the 37-month median follow-up period, OS and EFS rates were equivalent in both groups.

Ultrasound-assisted carbon nanoparticle suspension mapping versus dual tracer-guided sentinel lymph node biopsy in patients with early breast cancer (ultraCars): phase III randomized clinical trial.

BACKGROUND: Appropriate tracing methods for sentinel lymph node biopsy (SLNB) play a key role in accurate axillary staging. This prospective, non-inferiority, phase III RCT compared the feasibility and diagnostic performance of ultrasound-assisted carbon nanoparticle suspension (CNS) mapping with dual tracer-guided SLNB in patients with early breast cancer. METHODS: Eligible patients had primary breast cancer without nodal involvement (cN0), or had clinically positive lymph nodes (cN1) that were downstaged to cN0 after neoadjuvant chemotherapy. Patients were randomly assigned (1 : 1) to undergo either ultrasound-assisted CNS sentinel lymph node (SLN) mapping (UC group) or dual tracer-guided mapping with CNS plus indocyanine green (ICG) (GC group). The primary endpoint was the SLN identification rate. RESULTS: Between 1 December 2019 and 30 April 2021, 330 patients were assigned randomly to the UC (163 patients) or GC (167 patients) group. The SLN identification rate was 94.5 (95 per cent c.i. 90.9 to 98.0) per cent in the UC group and 95.8 (92.7 to 98.9) per cent in the GC group. The observed difference of -1.3 (-5.9 to 3.3) per cent was lower than the prespecified non-inferiority margin of 6 per cent (Pnon-inferiority = 0.024). No significant difference was observed in metastatic node rate (30.5 versus 24.4 per cent; P = 0.222), median number of SLNs harvested (3 (range 1-7) versus 3 (1-8); P = 0.181), or duration of surgery (mean(s.d.) 7.53(2.77) versus 7.63(3.27) min; P = 0.316) between the groups. Among the subgroup of patients who had undergone neoadjuvant treatment, the SLN identification rate was 91.7 (82.2 to 100) per cent in the UC group and 90.7 (81.7 to 99.7) per cent in the GC group. CONCLUSION: The diagnostic performance of ultrasound-assisted CNS mapping was non-inferior to that of dual tracer-guided SLN mapping with CNS plus ICG in patients with early breast cancer. REGISTRATION NUMBER: NCT04951245 (http://www.clinicaltrials.gov).

A nomogram to predict non-sentinel lymph node metastasis in patients with initial cN+ breast cancer that downstages to cN0 after neoadjuvant chemotherapy.

BACKGROUND AND OBJECTIVES: This study mainly explored the factors that influence non-sentinel lymph node (NSLN) metastasis in patients with breast cancer (BC) whose axillary lymph nodal status changed from clinically node positive (cN+) to clinically node negative (cN0) after neoadjuvant chemotherapy (NAC). METHODS: We retrospectively analyzed the clinicopathological factors affecting NSLN metastasis in a total of 179 patients with cN+ BC downstaged to cN0 (120 in the training set and 59 in the validation set) who underwent both sentinel lymph node (SLN) biopsy and axillary lymph node dissection following NAC. RESULTS: Among 179 patients enrolled, the overall NSLN metastatic rate was 24.0% (95% confidence interval [CI]: 17.7%-30.3%). In multivariate logistic regression analysis, the number of positive SLNs achieving a pathological complete remission of the breast and clinical node staging was independent predictors of NSLN metastasis. A nomogram was established based on these factors and displayed a good discriminatory capability, with an area under the curve of 0.919 (95% CI: 0.865-0.973) for the training set and 0.900 (95% CI: 0.812-0.988) for the validation set and its clinical utility was confirmed by the decision curve analysis. CONCLUSIONS: The nomogram established showed the ability to predict NSLN metastases in patients with initial cN+ BC that downstaged to cN0 after NAC.

Application of a carbon nanoparticle suspension for sentinel lymph node mapping in patients with early breast cancer: a retrospective cohort study.

BACKGROUND: To stage axillary lymph nodes in women with early-stage breast cancer, sentinel lymph node biopsy (SLNB), rather than axillary lymph node dissection (ALND), has been employed. Moreover, different tracer methods have various advantages and disadvantages. In recent years, carbon nanoparticle suspensions (CNSs) have been used as lymph node tracers during surgeries for thyroid cancer, gastric cancer, and colorectal cancer. The study retrospectively analyzed the feasibility and accuracy of CNS for sentinel lymph node (SLN) mapping in patients with early breast cancer. METHODS: This single-center, retrospective study included breast cancer patients who underwent SLNB from January 1, 2016, to December 31, 2017, in the Department of Breast Cancer, Guangdong General Hospital. All patients received standard SLNB surgery using a CNS tracer. RESULTS: A total of 332 cases were included in this study. The SLN identification rate was 99.1% (329/332), and the mean number of SLNs was 2.6 (range, 1-6). SLN metastasis was found in 62 (18.8%) cases, of which 90.3% were found to be macrometastases. The sensitivity of SLNB was 95.9% (47/49), with a specificity of 100% (42/42), a positive predictive value of 100% (47/47), a negative predictive value of 95.5% (42/44), and a false-negative rate of 4.1% (2/49). CONCLUSION: The identification and predictive values of a CNS tracer for SLNB were satisfactory.

Neoadjuvant Chemotherapy and Neoadjuvant Chemotherapy With Immunotherapy Result in Different Tumor Shrinkage Patterns in Triple-Negative Breast Cancer.

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 = 0.004). The postoperative pathological complete response (pCR) rate was 45% and 82% in the NAC and NACI groups (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 = 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. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04909554.

Multifactor artificial intelligence model assists axillary lymph node surgery in breast cancer after neoadjuvant chemotherapy: multicenter retrospective cohort study.

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.

Longitudinal MRI-based fusion novel model predicts pathological complete response in breast cancer treated with neoadjuvant chemotherapy: a multicenter, retrospective study.

Background: Accurate identification of pCR to neoadjuvant chemotherapy (NAC) is essential for determining appropriate surgery strategy and guiding resection extent in breast cancer. However, a non-invasive tool to predict pCR accurately is lacking. Our study aims to develop ensemble learning models using longitudinal multiparametric MRI to predict pCR in breast cancer. Methods: From July 2015 to December 2021, we collected pre-NAC and post-NAC multiparametric MRI sequences per patient. We then extracted 14,676 radiomics and 4096 deep learning features and calculated additional delta-value features. In the primary cohort (n = 409), the inter-class correlation coefficient test, U-test, Boruta and the least absolute shrinkage and selection operator regression were used to select the most significant features for each subtype of breast cancer. Five machine learning classifiers were then developed to predict pCR accurately for each subtype. The ensemble learning strategy was used to integrate the single-modality models. The diagnostic performances of models were evaluated in the three external cohorts (n = 343, 170 and 340, respectively). Findings: A total of 1262 patients with breast cancer from four centers were enrolled in this study, and pCR rates were 10.6% (52/491), 54.3% (323/595) and 37.5% (66/176) in HR+/HER2-, HER2+ and TNBC subtype, respectively. Finally, 20, 15 and 13 features were selected to construct the machine learning models in HR+/HER2-, HER2+ and TNBC subtypes, respectively. The multi-Layer Perception (MLP) yields the best diagnostic performances in all subtypes. For the three subtypes, the stacking model integrating pre-, post- and delta-models yielded the highest AUCs of 0.959, 0.974 and 0.958 in the primary cohort, and AUCs of 0.882-0.908, 0.896-0.929 and 0.837-0.901 in the external validation cohorts, respectively. The stacking model had accuracies of 85.0%-88.9%, sensitivities of 80.0%-86.3%, and specificities of 87.4%-91.5% in the external validation cohorts. Interpretation: Our study established a novel tool to predict the responses of breast cancer to NAC and achieve excellent performance. The models could help to determine post-NAC surgery strategy for breast cancer. Funding: This study is supported by grants from the National Natural Science Foundation of China (82171898, 82103093), the Deng Feng project of high-level hospital construction (DFJHBF202109), the Guangdong Basic and Applied Basic Research Foundation (grant number, 2020A1515010346, 2022A1515012277), the Science and Technology Planning Project of Guangzhou City (202002030236), the Beijing Medical Award Foundation (YXJL-2020-0941-0758), and the Beijing Science and Technology Innovation Medical Development Foundation (KC2022-ZZ-0091-5). Funding sources were not involved in the study design, data collection, analysis and interpretation, writing of the report, or decision to submit the article for publication.

Organic solvent-tolerant elastase efficiently hydrolyzes insoluble, cross-linked, protein fiber of eggshell membranes.

Eggshell membrane is a mechanically stable and insoluble cross-linked fibrous protein. Pseudomonas aeruginosa strain ME-4 synthesizes a metalloprotease that degrades the eggshell membrane. We cloned the encoding gene in Escherichia coli. The recombinant protease, over-expressed in E. coli, was inactive but addition of acetone to crude cell extracts restored the activity and removed many E. coli proteins. We purified the active, acetone-treated protease to homogeneity in a single chromatography step with 57% recovery. The recombinant protease partially hydrolyzed eggshell membrane and produced more soluble peptides and proteins than commercial elastase, α-chymotrypsin, and collagenase. The soluble peptides produced from hydrolyzed eggshell membrane inhibited angiotensin-I-converting enzyme activity. The degradation of eggshell membrane by the recombinant elastase could be applied to the production of soluble bioactive peptides.