Unraveling breast cancer prognosis: a novel model based on coagulation-related genes.

Objective: Breast cancer is highly heterogeneous, presenting challenges in prognostic assessment. Developing a universally applicable prognostic model could simplify clinical decision-making. This study aims to develop and validate a novel breast cancer prognosis model using coagulation-related genes with broad clinical applicability. Methods: A total of 203 genes related to coagulation were obtained from the KEGG database, and the mRNA data of 1,099 tumor tissue samples and 572 samples of normal tissue were retrieved from the TCGA-BRCA cohort and GTEx databases. The R package "limma" was utilized to detect variations in gene expression related to coagulation between the malignancies and normal tissue. A model was constructed in the TCGA cohort through a multivariable Cox regression analysis, followed by validation using the GSE42568 dataset as the testing set. Constructing a nomogram incorporating clinical factors to enhance the predictive capacity of the model. Utilizing the ESTIMATE algorithm to investigate the immune infiltration levels in groups with deferent risk. Performing drug sensitivity analysis using the "oncoPredict" package. Results: A risk model consisting of six coagulation-associated genes (SERPINA1, SERPINF2, C1S, CFB, RASGRP1, and TLN2) was created and successfully tested for validation. Identified were 6 genes that serve as protective factors in the model's development. Kaplan-Meier curves revealed a worse prognosis in the high-risk group compared to the low-risk group. The ROC analysis showed that the model accurately forecasted the overall survival (OS) of breast cancer patients at 1, 3, and 5 years. Nomogram accompanied by calibration curves can also provide better guidance for clinical decision-making. The low-risk group is more likely to respond well to immunotherapy, whereas the high-risk group may show improved responses to Gemcitabine treatment. Furthermore, individuals in distinct risk categories displayed different responses to various medications within the identical therapeutic category. Conclusion: We established a breast cancer prognostic model incorporating six coagulation-associated genes and explored its clinical utility. This model offers valuable insights for clinical decision-making and drug selection in breast cancer patients, contributing to personalized and precise treatment advancements.

TripHLApan: predicting HLA molecules binding peptides based on triple coding matrix and transfer learning.

Human leukocyte antigen (HLA) recognizes foreign threats and triggers immune responses by presenting peptides to T cells. Computationally modeling the binding patterns between peptide and HLA is very important for the development of tumor vaccines. However, it is still a big challenge to accurately predict HLA molecules binding peptides. In this paper, we develop a new model TripHLApan for predicting HLA molecules binding peptides by integrating triple coding matrix, BiGRU + Attention models, and transfer learning strategy. We have found the main interaction site regions between HLA molecules and peptides, as well as the correlation between HLA encoding and binding motifs. Based on the discovery, we make the preprocessing and coding closer to the natural biological process. Besides, due to the input being based on multiple types of features and the attention module focused on the BiGRU hidden layer, TripHLApan has learned more sequence level binding information. The application of transfer learning strategies ensures the accuracy of prediction results under special lengths (peptides in length 8) and model scalability with the data explosion. Compared with the current optimal models, TripHLApan exhibits strong predictive performance in various prediction environments with different positive and negative sample ratios. In addition, we validate the superiority and scalability of TripHLApan's predictive performance using additional latest data sets, ablation experiments and binding reconstitution ability in the samples of a melanoma patient. The results show that TripHLApan is a powerful tool for predicting the binding of HLA-I and HLA-II molecular peptides for the synthesis of tumor vaccines. TripHLApan is publicly available at https://github.com/CSUBioGroup/TripHLApan.git.

PD-1/PD-L1 Inhibitor - Related Adverse Events and Their Management in Breast Cancer.

As the positive results of multiple clinical trials were released, the Programmed cell death 1 (PD-1) and Programmed cell death ligand 1 (PD-L1) inhibitors emerge as the focus of integrative breast cancer treatment. PD-1/PD-L1 inhibitors are often used as a sequential agent to be combined with other agents such as chemotherapeutic agents, targeted agents, and radiation therapy. As multiple therapies are administered simultaneously or in sequence, they are prone to a variety of adverse effects on patients while achieving efficacy. It is a challenge for clinicians to maintaining the balance between immune-related adverse effects(irAEs) and treatment efficacy. Previous literatures have paid lots of attention on the adverse effects caused by immunosuppressive agents themselves, while there is a dearth of the research on the management of adverse immune effects during the combination of immunotherapy with other treatments. In this review, we discuss the overall incidence of irAEs caused by PD-1/PD-L1 inhibitors in combination with various types of treatments in breast cancer, including chemotherapy, CTLA-4 inhibitors, targeted therapy, and radiotherapy, and systematically summarizes the clinical management to each organ-related adverse immune reaction. It is important to emphasize that in the event of irAEs such as neurological, hematologic, and cardiac toxicity, there is no alternative treatment but to terminate immunotherapy. Thus, seeking more effective strategy of irAEs' management is imminent and clinicians are urged to raise the awareness of the management of adverse immune reactions.

Collaborative effects of 2019-nCoV-Spike mutants on viral infectivity.

Background: The emerging mutants of the 2019-nCoV coronavirus are posing unprecedented challenges to the pandemic prevention. A thorough, understanding of the mutational characterization responsible for the pathogenic mechanisms of mutations in 2019-nCoV-Spike is indispensable for developing effective drugs and new vaccines. Methods: We employed computational methods and viral infection assays to examine the interaction pattern and binding affinity between ACE2 and both single- and multi-mutants of the Spike proteins. Results: Using data from the CNCB-NGDC databank and analysis of the 2019-nCoV-Spike/ACE2 interface crystal structure, we identified 31 amino acids that may significantly contribute to viral infectivity. Subsequently, we performed molecular dynamics simulations for 589 single-mutants that emerged from the nonsynonymous substitutions of the aforementioned 31 residues. Ultimately, we discovered 8 single-mutants that exhibited significantly higher binding affinities (<-65.00 kcal/mol) to ACE2 compared with the wild-type Spike protein (-55.07 kcal/mol). The random combination of these 8 single-mutants yielded 184 multi-mutants, of which 60 multi-mutants exhibit markedly enhanced binding affinities (<-65.00 kcal/mol). Moreover, the binding free energy analyses of all 773 mutants (including 589 single- and 184 multi-mutants) revealed that Y449R and S494R had a synergistic effect on the binding affinity with other mutants, which were confirmed by virus infection assays of six randomly selected multi-mutants. More importantly, the findings of virus infection assay further validated a strong association between the binding free energy of Spike/ACE2 complex and the viral infectivity. Conclusions: These findings will greatly contribute to the future surveillance of viruses and rational design of therapeutics.

ST6GALNAC1 promotes the invasion and migration of breast cancer cells via the EMT pathway.

BACKGROUND: A specific sialyl-transferases called ST6GALNAC1 has been proven to up-regulate abnormal O-glycosylation, which is strongly associated with tumorigenesis and cancer progression. However, the precise pathological outcome of ST6GALNAC1 expression in breast cancer cells remains unknown. Therefore, our study aims to investigate the functional role of ST6GALNAC1 and its impact on the epithelial-mesenchymal transition (EMT) pathway in breast cancer cells. METHODS: Plasmids with siRNA were used to construct ST6GALNAC1 knockoff (si-ST6GALNAC1) MDA-MB-231 and MDA-MB-453 cells, while lentiviruses were used to construct ST6GALNAC1 over-expression (oe-ST6GALNAC1) MCF-7 and BT474 cells. Transfer efficiency was verified by Western Blot. Then we selected transfected cells and assessed the changes in cell proliferation, invasion, migration, and EMT markers. RESULTS: The expression of ST6GALNAC1 significantly enhanced cell migration and invasion, which was confirmed by Wound Scratch Assay and Transwell Assay. Particularly, ST6GALNAC1 expression directly induced the EMT signaling pathway. E-cadherin was markedly decreased in oe-ST6GALNAC1 cells, accompanied by an up-regulation of mesenchymal markers including N-cadherin, snail, and ZEB1. However, no significant correlation was found between ST6GALNAC1 expression and cell proliferation. All of the outcomes were reversely validated in si-ST6GALNAC1 cells. CONCLUSIONS: The expression of ST6GALNAC1 promotes cell migration and invasion probably by triggering the molecular process of the EMT pathway in breast cancer cells, which may provide new clues for designing novel molecular targeted drugs in breast cancer treatment.

StackCPA: A stacking model for compound-protein binding affinity prediction based on pocket multi-scale features.

Accurately predicting compound-protein binding affinity is a crucial task in drug discovery. Computational models offer the advantages of short time, low cost and safety compared to traditional drug development. Pocket is the key binding region of the protein, which provides invaluable information for drug repositioning and drug design. In this study, we propose an ensemble learning model, called StackCPA, to predict the compound-protein binding affinity. The model integrates multi-scale features of protein pocket and compound through a transfer learning strategy. The protein pocket is described in a fine-grained way by atomic level, residue level and subdomain level. The proposed model StackCPA is evaluated on three binding affinity benchmark datasets. The experiment results show that StackCPA achieves the best performance on all the three datasets in comparison with other state-of-the-art deep learning models. The ablation study shows that the protein pocket can provide sufficient information for affinity prediction and its multi-scale features enable the model to further improve the prediction performance. In addition, the case study for epidermal growth factor receptor erbB1 (EGFR) indicates that StackCPA could serve as an effective tool for drug repurposing. Source codes and data of StackCPA are available at https://github.com/CSUBioGroup/StackCPA.

AGR2: a secreted protein worthy of attention in diagnosis and treatment of breast cancer.

AGR2 is a secreted protein widely existing in breast. In precancerous lesions, primary tumors and metastatic tumors, the expression of AGR2 is increased, which has aroused our interest. This review introduces the gene and protein structure of AGR2. Its endoplasmic reticulum retention sequence, protein disulfide isomerase active site and multiple protein binding sequences endow AGR2 with diverse functions inside and outside breast cancer cells. This review also enumerates the role of AGR2 in the progress and prognosis of breast cancer, and emphasizes that AGR2 can be a promising biomarker and a target for immunotherapy of breast cancer, providing new ideas for early diagnosis and treatment of breast cancer.

In Silico Prediction of New Mutations That Can Improve the Binding Abilities Between 2019-nCoV Coronavirus and Human ACE2.

The Coronavirus Disease 2019 (COVID-19) has become an international public health emergency, posing a serious threat to human health and safety around the world. The 2019-nCoV coronavirus spike protein was confirmed to be highly susceptible to various mutations, which can trigger apparent changes of virus transmission capacity and the pathogenic mechanism. In this article, the binding interface was obtained by analyzing the interaction modes between 2019-nCoV coronavirus and the human ACE2. Based on the "SIFT server" and the "bubble" identification mechanism, 9 amino acid sites were selected as potential mutation-sites from the 2019-nCoV-S1-ACE2 binding interface. Subsequently, a total number of 171 mutant systems for 9 mutation-sites were optimized for binding-pattern comparsion analysis, and 14 mutations that may improve the binding capacity of 2019-nCoV-S1 to ACE2 were selected. The Molecular Dynamic Simulations were conducted to calculate the binding free energies of all the 14 mutant systems. Finally, we found that most of the 14 mutations on the 2019-nCoV-S1 protein could enhance the binding ability between 2019-nCoV coronavirus and human ACE2. Among which, the binding capacities for G446R, Y449R and F486Y mutations could be increased by 20 percent, and that for S494R mutant increased even by 38.98 percent. We hope this research could provide significant help for the future epidemic detection, drug and vaccine development.

Potential Prospective Biomarkers for Non-small Cell Lung Cancer: Mini-Chromosome Maintenance Proteins.

Minichromosome maintenance proteins (MCMs) are considered to be essential factors coupling DNA replication to both cell cycle progression and checkpoint regulation. Previous studies have shown that dysregulation of MCMs are implicated in tumorigenesis of lung cancer. However, the distinct expression/mutation patterns and prognostic values of MCMs in lung cancer have yet to be systematically elucidated. In the present study, we analyzed the transcriptional levels, mutations, and prognostic value of MCM1-10 in non-small cell lung cancer (NSCLC) patients using multiple bioinformatics tools, including ONCOMINE, GEPIA, Kaplan-Meier Plotter, cBioPortal, and GESA. The analysis results from GEPIA dataset showed that MCM2/4/10 was significantly high expressed in both lung adenocarcinoma (LUAD) and squamous cell lung carcinomas (LUSCs). Meanwhile, the expression levels of MCM2/4/6/7/8 were associated with advanced tumor stages. Subsequent survival analysis using the Kaplan-Meier Plotter indicated that high expression levels of MCM1/2/3/4/5/6/7/8/10 were associated with worse overall survival (OS), while high expression level of MCM9 predicted better OS in these patients. Furthermore, we experimentally validated overexpression of MCM2 and MCM4 in NSCLC, thus the results from this study support a view that they may serve as potential prospective biomarkers to identify high-risk subgroups of NSCLC patients.

Multi-center investigation of breast reconstruction after mastectomy from Chinese Society of Breast Surgery: A survey based on 31 tertiary hospitals (CSBrS-004).

OBJECTIVE: Multi-center data on the current status and trends of breast reconstruction after mastectomy in China are lacking. Herein, we conducted a cross-sectional survey to investigate the current clinical practice pattern of postmastectomy breast reconstruction among Chinese female patients with breast cancer. METHODS: A standardized questionnaire used to collect information on breast reconstruction among females diagnosed with breast cancer was distributed by 31 members of the Chinese Society of Breast Surgery between January 1, 2018 and December 31, 2018. Information was collected on tumor characteristics, treatment, mesh application, nipple-areola complex (NAC) preservation, postoperative complications, bilateral reconstruction, patient satisfaction and local recurrence. The overall rate of breast reconstruction was assessed, and the characteristics were compared across patient groups with different reconstruction approaches. RESULTS: A total of 1,554 patients underwent breast reconstruction after total mastectomy, with a reconstruction rate of 9.6%. Among them, 1,190 were implant-based, and 262 underwent autologous reconstructions, while 102 cases underwent a combination of both. Patients who underwent implant-based reconstruction were younger than those who received autologous reconstruction (40.1±4.6 vs. 45.0±5.9, P=0.004). Compared to patients with autologous reconstruction, mesh application (25.5% vs. 6.5%), NAC preservation (51.8% vs. 40.5%) and reconstruction failure (1.8% vs. 0) were more frequently reported among those with implant-based reconstruction. There was no significant difference in general satisfaction across three reconstruction approaches, though patients with autologous reconstruction reported the highest aesthetic satisfaction among the three groups (P=0.044). CONCLUSIONS: Implant-based breast reconstruction remains the dominant choice among patients, while autologous reconstruction was associated with higher aesthetic satisfaction. Our multi-center investigation based on the findings of the tertiary hospitals of Chinese Society of Breast Surgery may guide a future series of clinical studies on breast reconstruction in China.

Key residues influencing binding affinities of 2019-nCoV with ACE2 in different species.

The Novel Coronavirus Disease 2019 (COVID-19) has become an international public health emergency, which poses the most serious threat to the human health around the world. Accumulating evidences have shown that the new coronavirus could not only infect human beings, but also can infect other species which might result in the cross-species infections. In this research, 1056 ACE2 protein sequences are collected from the NCBI database, and 173 species with >60% sequence identity compared with that of human beings are selected for further analysis. We find 14 polar residues forming the binding interface of ACE2/2019-nCoV-Spike complex play an important role in maintaining protein-protein stability. Among them, 8 polar residues at the same positions with that of human ACE2 are highly conserved, which ensure its basic binding affinity with the novel coronavirus. 5 of other 6 unconserved polar residues (positions at human ACE2: Q24, D30, K31, H34 and E35) are proved to have an effect on the binding patterns among species. We select 21 species keeping close contacts with human beings, construct their ACE2 three-dimensional structures by Homology Modeling method and calculate the binding free energies of their ACE2/2019-nCoV-Spike complexes. We find the ACE2 from all the 21 species possess the capabilities to bind with the novel coronavirus. Compared with the human beings, 8 species (cow, deer, cynomys, chimpanzee, monkey, sheep, dolphin and whale) present almost the same binding abilities, and 3 species (bat, pig and dog) show significant improvements in binding affinities. We hope this research could provide significant help for the future epidemic detection, drug and vaccine development and even the global eco-system protections.

Patient satisfaction in one-stage immediate breast reconstruction after mastectomy: A multi-center comparative patient evaluation of prosthesis, LDMF, and TRAM techniques.

To analyze patient satisfaction and the predictive factors characterizing three types of one-stage immediate breast reconstruction (IBR) after mastectomy, including prosthesis, latissimus dorsi myocutaneous flap (LDMF), transverse rectus abdominis myocutaneous (TRAM) flap techniques.Data were collected via face-to-face or telephone interviews from eight breast centers in China from January 2012 to December 2016. A standardized questionnaire that evaluated the general satisfaction and aesthetic satisfaction was sent to patients who had undergone IBR. Logistic regression analysis was performed to identify risk factors associated with patient satisfaction among the three types of breast reconstruction.A total of 412 questionnaires were sent out, and 309 copies were collected including 226 prosthesis, 46 LDMF, and 37 pedicle TRAM reconstruction. Logistic regression analysis showed that general satisfaction and aesthetic satisfaction were significantly correlated with radiotherapy (P < .001, P = .018), respectively. Besides, the aesthetic satisfaction was also associated with nipple-areola complex (NAC) preservation (P < .001).Our multi-center study identified factors of higher patient satisfaction, like NAC preservation and absence of radiotherapy, in order to help breast surgeons make better decisions about individualized reconstruction plan.

Accuracy for cytological evaluation in the detection of breast cancer among patients with pathologic nipple discharge: a PRISMA-compliant meta-analysis.

BACKGROUND: Nipple discharge cytology is a simple non-invasive method that may provide valuable information for detecting underlying malignancy. Several studies have investigated the diagnostic value of cytology in breast cancer patients with pathological nipple discharge, but the results have been highly variable. Herein we presented a systematic review and meta-analysis of published studies pertaining to the diagnostic capacity of nipple discharge cytology in patients with breast cancer. METHODS: A systematic literature search was performed (Medline/PubMed, Embase, Cochrane Library databases, and Google Scholar) to identify studies that investigated the diagnostic capacity of cytology with regard to breast cancer in patients with pathologic nipple discharge. Two independent researchers identified articles that assessed the sensitivity and specificity of cytological evaluation for breast cancer detection in patients with pathologic nipple discharge published between January 2000 and October 2018. Articles were only included in the meta-analysis if they met predetermined criteria. The characteristics of each study and the data they yielded were summarized. Quality assessment of all articles included was performed using the Methodological Index for Non-randomized Studies Criteria (MINORS) and the Quality Assessment of Diagnostic Accuracy Study 2 (QUADAS-2). Heterogeneity was tested via Cochran Q test and the I statistic using Stata 12.0 and Meta-DiSc 1.4 software, and meta-analysis was performed. RESULTS: A total of 286 articles were identified, of which 12 articles including a total of 1476 patients were deemed eligible for inclusion in the meta-analysis. A random-effects model assessing the capacity of nipple discharge cytology to predict breast cancer yielded pooled sensitivity 63% (95% confidence interval [CI]: 53%-72%), specificity 95% (95% CI: 87%-98%), positive likelihood ratio 12.35 (95% CI: 4.87-31.34), and negative likelihood ratio 0.39 (95% CI: 0.30-0.50). The diagnostic odds ratio was 31.88 (95% CI: 11.30-89.98). The area under the summary receiver operating characteristic curve was 0.79 (95% CI: 0.75-0.82). CONCLUSION: The current meta-analysis suggests that nipple discharge cytology is a useful diagnostic modality for detection of breast cancer in patients with pathological nipple discharge, with moderate sensitivity and high specificity.

An EZ-Diffusion Model Analysis of Attentional Ability in Patients With Retinal Pigmentosa.

Retinitis pigmentosa (RP) is characterized by visual acuity decrease and visual field loss. However, the impact of visual field loss on the cognitive performance of RP patients remains unknown. In the present study, in order to understand whether and how RP affects spatial processing and attentional function, one spatial processing task and three attentional tasks were conducted on RP patients and healthy controls. In addition, an EZ-diffusion model was performed for further data analysis with four parameters, mean decision time, non-decision time, drift rate, and boundary separation. It was found that in the spatial processing task, compared with the control group, the RP group exhibited a slower response speed in large and medium visual eccentricities, and slower drift rate for the large stimulus, which is strongly verified by the significant linear correlation between the visual field eccentricity with both reaction time (p = 0.047) and non-decision time (p = 0.043) in RP patients. In the attentional orienting task and the attentional switching task, RP exerted a reduction of speed and an increase of non-decision time on every condition, with a decrease of drift rate in the orienting task and boundary separation in the switching task. In addition, the switching cost for large stimulus was observed in the control group but not in the RP group. The stop-signal task demonstrated similar inhibition function between the two groups. These findings implied that RP exerted the impairment of spatial cognition correlated with the visual field eccentricity, mainly in the peripheral visual field. Moreover, specific to the peripheral visual field, RP patients had deficits in the attentional orienting and flexibility but not in the attentional inhibition.