MulTFBS: A Spatial-Temporal Network with Multichannels for Predicting Transcription Factor Binding Sites.

Revealing the mechanisms that influence transcription factor binding specificity is the key to understanding gene regulation. In previous studies, DNA double helix structure and one-hot embedding have been used successfully to design computational methods for predicting transcription factor binding sites (TFBSs). However, DNA sequence as a kind of biological language, the method of word embedding representation in natural language processing, has not been considered properly in TFBS prediction models. In our work, we integrate different types of features of DNA sequence to design a multichanneled deep learning framework, namely MulTFBS, in which independent one-hot encoding, word embedding encoding, which can incorporate contextual information and extract the global features of the sequences, and double helix three-dimensional structural features have been trained in different channels. To extract sequence high-level information effectively, in our deep learning framework, we select the spatial-temporal network by combining convolutional neural networks and bidirectional long short-term memory networks with attention mechanism. Compared with six state-of-the-art methods on 66 universal protein-binding microarray data sets of different transcription factors, MulTFBS performs best on all data sets in the regression tasks, with the average R2 of 0.698 and the average PCC of 0.833, which are 5.4% and 3.2% higher, respectively, than the suboptimal method CRPTS. In addition, we evaluate the classification performance of MulTFBS for distinguishing bound or unbound regions on TF ChIP-seq data. The results show that our framework also performs well in the TFBS classification tasks.

Infiltrating myeloid cell diversity determines oncological characteristics and clinical outcomes in breast cancer.

BACKGROUND: Breast cancer presents as one of the top health threats to women around the world. Myeloid cells are the most abundant cells and the major immune coordinator in breast cancer tumor microenvironment (TME), target therapies that harness the anti-tumor potential of myeloid cells are currently being evaluated in clinical trials. However, the landscape and dynamic transition of myeloid cells in breast cancer TME are still largely unknown. METHODS: Myeloid cells were characterized in the single-cell data and extracted with a deconvolution algorithm to be assessed in bulk-sequencing data. We used the Shannon index to describe the diversity of infiltrating myeloid cells. A 5-gene surrogate scoring system was then constructed and evaluated to infer the myeloid cell diversity in a clinically feasible manner. RESULTS: We dissected the breast cancer infiltrating myeloid cells into 15 subgroups including macrophages, dendritic cells (DCs), and monocytes. Mac_CCL4 had the highest angiogenic activity, Mac_APOE and Mac_CXCL10 were highly active in cytokine secretion, and the DCs had upregulated antigen presentation pathways. The infiltrating myeloid diversity was calculated in the deconvoluted bulk-sequencing data, and we found that higher myeloid diversity was robustly associated with more favorable clinical outcomes, higher neoadjuvant therapy responses, and a higher rate of somatic mutations. We then used machine learning methods to perform feature selection and reduction, which generated a clinical-friendly scoring system consisting of 5 genes (C3, CD27, GFPT2, GMFG, and HLA-DPB1) that could be used to predict clinical outcomes in breast cancer patients. CONCLUSIONS: Our study explored the heterogeneity and plasticity of breast cancer infiltrating myeloid cells. By using a novel combination of bioinformatic approaches, we proposed the myeloid diversity index as a new prognostic metric and constructed a clinically practical scoring system to guide future patient evaluation and risk stratification.

Evaluation of Male Breast Cancer and the Application of Sentinel Lymph Node Biopsy: A Multicenter Retrospective Study.

Sentinel lymph node biopsy (SLNB) is currently used as a routine treatment for patients with breast cancer. However, it may not be applicable for patients with male breast cancer (MBC), because they have notably different clinicopathological features from those occurring in females. There is a lack of evidence of SLNB application and safe exemption from axillary lymph node dissection (ALND) in patients with MBC. This study aimed to evaluate the application of SLNB to provide information for the standardized treatment of patients with MBC. The MBC patient records from 4 institutions ranging from January 2001 to November 2020 were retrospectively reviewed. There were 220 patients with MBC with a median age of 60 (range 24-88) years and an average tumor size of 2.3 cm (range 0.5 cm-6.5 cm). Sixty-six percent of patients underwent SLNB, and 39% of them showed positive results. A total of 157 patients underwent ALND, while only half of them had positive nodes, causing unnecessary complications. For patients in the clinical early stage, we found that the SLNB showed a noninferiority to the ALND treatment in DFS (P = .18) and OS (P = .055). In conclusion, there are certain obstacles to the broad application of SLNB due to the lower proportion of patients with clinically negative lymph nodes. However, it is undeniable that SLNB can safely and effectively exempt patients with MBC at early stage with clinically negative nodes from ALND to reduce subsequent complications. It is still an ideal criterion for the axillary staging of patients with MBC.

Reduced Proteolipid Protein 2 promotes endoplasmic reticulum stress-related apoptosis and increases drug sensitivity in acute myeloid leukemia.

BACKGROUND: The Proteolipid Protein 2 (PLP2), a protein in the Endoplasmic Reticulum (ER) membrane, has been reported to be highly expressed in various tumors. Previous studies have demonstrated that the reduced PLP2 can induce apoptosis and autophagy through ER stress-related pathways, leading to a decreased proliferation and aggressiveness. However, there is no research literature on the role of PLP2 in Acute Myeloid Leukemia (AML). METHODS: PLP2 expression, clinical data, genetic mutations, and karyotype changes from GEO, TCGA, and timer2.0 databases were analyzed through the R packages. The possible functions and pathways of cells were explored through GO, KEGG, and GSEA enrichment analysis using the clusterProfiler R package. Immuno-infiltration analysis was conducted using the Cibersort algorithm and the Xcell R package. RT-PCR and western blot techniques were employed to identify the PLP2 expression, examine the knockdown effects in THP-1 cells, and assess the expression of genes associated with endoplasmic reticulum stress and apoptosis. Flow cytometry was utilized to determine the apoptosis and survival rates of different groups. RESULTS: PLP2 expression was observed in different subsets of AML and other cancers. Enrichment analyses revealed that PLP2 was involved in various tumor-related biological processes, primarily apoptosis and lysosomal functions. Additionally, PLP2 expression showed a strong association with immune cell infiltration, particularly monocytes. In vitro, the knockdown of PLP2 enhanced endoplasmic reticulum stress-related apoptosis and increased drug sensitivity in THP-1 cells. CONCLUSIONS: PLP2 could be a novel therapeutic target in AML, in addition, PLP2 is a potential endoplasmic reticulum stress regulatory gene in AML.

The prognostic value of IPI in patients with primary breast lymphoma, a multicenter retrospective study.

BACKGROUND: Due to the rarity of PBL and the lack of large-scale studies, the prognostic value of IPI in PBL was controversial. Especially in the rituximab era, the ability of IPI to stratify prognosis in patients receiving immunochemotherapy was severely reduced. Then revised IPI (R-IPI) and National Comprehensive Cancer Network IPI (NCCN-IPI) were introduced. The present study aimed to evaluate the prognostic value of IPI and the other IPIs in patients with PBL in a Chinese population. METHODS: We performed a multicenter retrospective study of 71 patients with PBL from 3 institutions in China. The Kaplan-Meier method and log-rank tests were used for the survival analysis. Cox regression analysis was performed to evaluate the prognostic factors. Subgroup analysis was performed to assess the prognostic significance of IPI scores, R-IPI scores, and NCCN-IPI scores. RESULTS: The median follow-up was 4.7 years (0.7-21.8 years). The 5-year progression-free survival (PFS) and overall survival (OS) rates were 90.2% and 96.3%. In the multivariate analysis, only IPI scores and radiotherapy were significantly associated with OS and PFS (P < 0.05). Applying the R-IPI in our patient cohort indicates a significant difference in PFS between the two groups of R-IPI (P = 0.034) but not for OS (P = 0.072). And the NCCN-IPI was prognostic for OS (P = 0.025) but not for PFS (P = 0.066). Subgroup analyses of IPI showed that survival analysis of IPI scores for the PFS and OS of patients using rituximab were not significantly different (P > 0.05). CONCLUSIONS: Our study confirms the prognostic value of IPI in patients with PBL, but the predictive value of IPI proved to be relatively low with the addition of the rituximab. The R-IPI and NCCN-IPI can accurately assess the high and low-risk groups of PBL patients but were insufficient to evaluate the intermediate risk group.

Cellular Antioxidant Properties of Ischnoderma Resinosum Polysaccharide.

A predominant polysaccharide isolated from Ischnoderma resinosum underwent evaluation for its capacity to scavenge free radicals and its potential antioxidant properties at a cellular-oriented level. This proved that Ischnoderma resinosum polysaccharide (IRP) remarkably curtailed AAPH-induced erythrocyte hemolysis through the inhibition of the generation of ROS (p < 0.05). Rather, it caused the restoration of intracellular antioxidant enzyme (SOD, GSH-Px, and CAT) activities at an acceptable pace and the silencing of intracellular MDA formation, as well as the rescaling of LDH leakage. Furthermore, a model of oxidative stress in HepG2 cells was established by adopting 400 µM of hydrogen peroxide, which suggested that IRP manifests promising antioxidant activity. Notably, after the intervention of IRP in the H2O2-induced HepG2 cells, there was a statistical elevation in cell survivability (p < 0.05). IRP diminished the morphological alterations in the nucleus and decreased the secretion of ROS (p < 0.05), with a dose-dependent abrogation of apoptosis (p < 0.05). Consequently, IRP, which was isolated and purified, was able to scavenge free radicals and possessed favorable antioxidant activity that could dampen the occurrence of oxidative stimulation and effectively alleviate the AAPH-induced erythrocyte hemolysis and H2O2-induced oxidative damage in HepG2 cells. This provides a basis and theoretical reference for the development and utilization of IRP as a natural antioxidant, with emphasis on the exploitation of environmentally friendly and cost-effective antioxidants.

Protective Effect of Flavonoids from Mulberry Leaf on AAPH-Induced Oxidative Damage in Sheep Erythrocytes.

To evaluate the antioxidant activity of flavonoids extracted from Chinese herb mulberry leaves (ML), flavonoids from mulberry leaves (FML) were extracted and purified by using ultrasonic-assisted enzymatic extraction and D101 macroporous resin. Using LC-MS/MS-Liquid Chromatography with tandem mass spectrometry analysis, hesperidin, rutoside, hyperoside, cyanidin-3-o-glucoside, myricitrin, cyanidin, and quercetin were identified, and NMR and UV were consistent with the verification of IR flavonoid characteristics. The antioxidant activity of FML has also been evaluated as well as the protective effect on 2,2 0-azobis (2-amidinopropane) dihydrochloride (AAPH)-induced oxidative stress. The results showed that FML exhibited powerful antioxidant activity. Moreover, FML showed dose-dependent protection against AAPH-induced sheep erythrocytes' oxidative hemolysis. In the enzymatic antioxidant system, pretreatment with high FML maintained the balance of SOD, CAT, and GSH-Px; in the non-enzymatic antioxidant system, the content of MDA can be effectively reduced after FML treatment. This study provides a research basis for the development of natural products from mulberry leaves.

Overexpression of IncRNA SAMMSON Promotes Triple-Negative Breast Cancer Cell Proliferation by Interacting with p53.

This study was carried out to explore the role of the long noncoding RNA (lncRNA) SAMMSON in triple-negative breast cancer (TNBC). The research patients in this study included 68 TNBC patients. Cell Counting Kitcck-8 were utilized to determine cell proliferation abilities, respectively. Proteins and mRNAs were estimated by western blot and Methylation-specific polymerase chain reaction, respectively. We found that SAMMSON was upregulated, while p53 was downregulated in cancer (TNBC) tissues than in non-cancer tissues of TNBC patients. SAMMSON expression levels in TNBC tissues increased with the increase of clinical stages of TNBC patients. SAMMSON and p53 were inversely correlated in TNBC tissues. In TNBC cells, SAMMSON overexpression decreased p53 expression, while p53 overexpression failed to affect SAMMSON expression. In addition, SAMMSON overexpression increased TNBC cell proliferation, while p53 overexpression decreased the proliferation rates of TNBC cells. In addition, p53 overexpression attenuated the effects of SAMMSON overexpression. Therefore, overexpression of SAMMSON could promote TNBC cell proliferation by interacting with p53.

Contralateral risk-reducing local therapy in breast cancer patients with BRCA1/2 mutations: systemic review and meta-analysis.

BACKGROUND: Unilateral breast cancer (UBC) patients with germline pathogenic BRCA1/2 variants have a higher risk of developing contralateral breast cancer (CBC) and need contralateral risk-reducing local treatments, including contralateral risk-reducing mastectomy (CRRM) and prophylactic irradiation (CPI). The aim of our study was to systematically explore the efficacy of CRRM and CPI in reducing CBC risk and increasing survival. METHODS: A search was done, and eligible randomized trials and cohort studies should include and compare UBC patients with germline pathogenic BRCA1/2 variants who have and have not received contralateral risk-reducing local treatment. Random-effects meta-analysis was used in this study. Primary outcomes of the studies included overall survival (OS) and the incidence of contralateral breast cancer (CBC), and secondary outcomes included breast cancer-specific survival (BCSS). RESULTS: A total of five studies with 1769 UBC patients with germline pathogenic BRCA1/2 variants were enrolled in our meta-analysis. CRRM was correlated with a lower risk of CBC in UBC patients with germline pathogenic BRCA1/2 variants (summary RR = 0.07; 95%CI 0.03-0.13, I2 = 3%), a significantly increased OS (summary RR, 1.15; 95%CI 1.04-1.26, I2 = 26%) and a significantly increased BCSS (summary RR, 1.18; 95%CI 1.07-1.31, I2 = 64%) compared with surveillance. CPI also decreased the risk of CBC (RR 0.02; 95%CI 0.05-0.88) but did not significantly improve OS (RR 0.97; 95%CI 0.90-1.05) and BCSS (RR 0.97; 95%CI 0.90-1.05) compared with surveillance. CONCLUSIONS: CRRM reduces CBC risk and increases OS and BCSS in UBC patients with germline pathogenic BRCA1/2 variants, and could be offered as a risk-reducing local treatment. For those who oppose CRRM, CPI could be offered for CBC-risk reduction, while its survival benefit is still uncertain.

'Repair' Treg Cells in Tissue Injury.

Studies in mice and humans have elucidated an important role for Tregs in promoting tissue repair and restoring tissue integrity. Emerging evidence has revealed that Tregs promoted wound healing and repair processes at multiple tissue sites, such as the heart, liver, kidney, muscle, lung, bone and central nervous system. The localization of repair Tregs in the lung, muscle and liver exhibited unique phenotypes and functions. Epidermal growth factor receptor, amphiregulin, CD73/CD39 and keratinocyte growth factor are important repair factors that are produced or expressed by repair Tregs; these factors coordinate with parenchymal cells to limit injury and promote repair. In addition, repair Tregs can be modulated by IL-33/ST2, TCR signals and other cytokines in the context of injured microenvironment cues. In this review, we provide an overview of the emerging knowledge about Treg-mediated repair in damaged tissues and organs.

Fabrication of a core-shell nanofibrous wound dressing with an antioxidant effect on skin injury.

Oxidative stress is one of the obstacles preventing wound regeneration, especially for chronic wounds. Herein, designing a wound dressing with an anti-oxidant function holds great appeal for enhancing wound regeneration. In this study, a biocompatible and degradable nanofiber with a core-shell structure was fabricated via coaxial electrospinning, in which polycaprolactone (PCL) was applied as the core structure, while the shell was composed of a mixture of silk fibroin (SF) and tocopherol acetate (TA). The electrospun PST nanofibers were proven to have a network structure with significantly enhanced mechanical properties. The PSTs exhibited a diameter distribution with an average of 321 ± 134 nm, and the water contact angle of their surface is 124 ± 2°. The PSTs also exhibited good tissue compatibility, which can promote the adhesion and proliferation of L929 cells. Besides, the dissolution of silk fibroin encourages the release of TA, which could play a synergistic effect and regulate the oxidative stress effect in the damaged area, for it promotes the adhesion and proliferation of skin fibroblasts (L929), reduces the cytotoxicity of hydrogen peroxide to cells, and lowers the level of reactive oxygen species. The animal experiment indicated that the PSTs would promote the reconstruction of skin. These nanofibers are expected to repair skin ulcers related to diabetes.

Association between oral microbiome and breast cancer in the east Asian population: A Mendelian randomization and case-control study.

BACKGROUND: The causal relationship between breast cancer (BC) and the oral microbiome remains unclear. In this case-control study, using two-sample Mendelian randomization (MR), we thoroughly explored the relationship between the oral microbiome and BC in the East Asian population. METHODS: Genetic summary data related to oral microbiota and BC were collected from genome-wide association studies involving participants of East Asian descent. MR estimates were generated by conducting various analyses. Sequencing data from a case-control study were used to verify the validity of these findings. RESULTS: MR analysis revealed that 30 tongue and 37 salivary bacterial species were significantly associated with BC. Interestingly, in both tongue and salivary microbiomes, we observed the causal effect of six genera, namely, Aggregatibacter, Streptococcus, Prevotella, Haemophilus, Lachnospiraceae, Oribacterium, and Solobacterium, on BC. Our case-control study findings suggest differences in specific bacteria between patients with BC and healthy controls. Moreover, sequencing data confirmed the MR analysis results, demonstrating that compared with the healthy control group, the BC group had a higher relative abundance of Pasteurellaceae and Streptococcaceae but a lower relative abundance of Bacteroidaceae. CONCLUSIONS: Our MR analysis suggests that the oral microbiome exerts a causative effect on BC risk, supported by the sequencing data of a case-control study. In the future, studies should be undertaken to comprehensively understand the complex interaction mechanisms between the oral microbiota and BC.

An exploration of causal relationships between nine neurological diseases and the risk of breast cancer: a Mendelian randomization study.

BACKGROUND: Some preceding researches have observed that certain neurological disorders, such as Alzheimer's disease and multiple sclerosis, may affect breast cancer risk. However, whether there are causal relationships between these neurological conditions and breast cancer is inconclusive. This study was designed to explore whether neurological disorders affected the risks of breast cancer overall and of the two subtypes (ER+ and ER-). METHODS: In the course of this study, genome-wide association study (GWAS) data for nine neurological diseases (Alzheimer's disease, multiple sclerosis, Parkinson's disease, myasthenia gravis, generalized epilepsy, intracerebral haemorrhage, cerebral atherosclerosis, brain glioblastoma, and benign meningeal tumour) were collected from the Complex Trait Genetics lab and the MRC Integrative Epidemiology Unit, and single-nucleotide polymorphisms (SNPs) extensively associated with these neurological ailments had been recognized as instrumental variables (IVs). GWAS data on breast cancer were collected from the Breast Cancer Association Consortium (BCAC). Two-sample Mendelian randomization (MR) analyses as well as multivariable MR analyses were performed to determine whether these SNPs contributed to breast cancer risk. Additionally, the accuracy of the results was evaluated using the false discovery rate (FDR) multiple correction method. Both heterogeneity and pleiotropy were evaluated by analyzing sensitivities. RESULTS: According to the results of two-sample MR analyses, Alzheimer's disease significantly reduced the risks of overall (OR 0.925, 95% CI [0.871-0.982], P = 0.011) and ER+ (OR 0.912, 95% CI [0.853-0.975], P = 0.007) breast cancer, but there was a negative result in ER- breast cancer. However, after multiple FDR corrections, the effect of Alzheimer's disease on overall breast cancer was not statistically significant. In contrast, multiple sclerosis significantly increased ER+ breast cancer risk (OR 1.007, 95% CI [1.003-1.011], P = 0.001). In addition, the multivariable MR analyses showed that Alzheimer's disease significantly reduced the risk of ER+ breast cancer (IVW: OR 0.929, 95% CI [0.864-0.999], P=0.047; MR-Egger: OR 0.916, 95% CI [0.846-0.992], P=0.031); however, multiple sclerosis significantly increased the risk of ER+ breast cancer (IVW: OR 1.008, 95% CI [1.003-1.012], P=4.35×10-4; MR-Egger: OR 1.008, 95% CI [1.003-1.012], P=5.96×10-4). There were no significant associations between the remainder of the neurological diseases and breast cancer. CONCLUSIONS: This study found the trends towards a decreased risk of ER+ breast cancer in patients with Alzheimer's disease and an increased risk in patients with multiple sclerosis. However, due to the limitations of Mendelian randomization, we cannot determine whether there are definite causal relationships between neurological diseases and breast cancer risk. For conclusive evidences, more prospective randomized controlled trials will be needed in the future.

Prognostic Impact of HER2-Low and HER2-Zero in Resectable Breast Cancer with Different Hormone Receptor Status: A Landmark Analysis of Real-World Data from the National Cancer Center of China.

BACKGROUND: The prognostic impact of HER2-low on overall survival (OS) and disease-free survival (DFS) in patients with resectable breast cancer (BC) remains controversial, partly resulting from the hormone receptor (HR) status. OBJECTIVE: To investigate the prognostic impact of HER2-low in different HR subgroups. PATIENTS AND METHODS: We retrospectively retrieved medical records of treatment-naive primary HER2-low and HER2-zero BC patients who were diagnosed with invasive ductal carcinoma and underwent surgery in the Cancer Hospital of the Chinese Academy of Medical Sciences from January 2009 to September 2017 (n = 7371). We compared the clinicopathologic features and performed Cox regression and landmark survival analyses to explore the prognostic impact of HER2-low on survival outcomes during distinct post-surgery intervals-36 months, 60 months, and 120 months. RESULTS: HER2-low BC, compared to HER2-zero BC, exhibited less aggressive clinicopathologic features, such as smaller invasion size, lower grade, increased nerve invasion, higher HR positivity, and a higher proportion of low-Ki67 cases. In the HR-positive subgroup, HER2-low demonstrated improved OS (p = 0.046) and DFS (p = 0.026) within 60 months. Conversely, HER2-low displayed worse DFS (p = 0.046) in the HR-negative subgroup after 36 months from surgery. The findings remained robust in uni- and multi-variable Cox models. CONCLUSIONS: HER2-low BCs manifested less aggressive clinicopathologic features than the HER2-zero cases. The prognostic impact of HER2-low in resectable BCs exhibits variability contingent upon the patients' HR status.

An exploratory study of whether axillary lymph node dissection can be avoided in breast cancer patients with positive lymph nodes.

Background: Breast cancer patients with positive axillary lymph nodes usually require axillary lymph node dissection (ALND), with many postoperative complications, such as lymphedema. For these patients, whether sentinel lymph node biopsy (SLNB) can replace ALND has been a research hotspot in the field of breast cancer. This study developed two risk stratification models for predicting the clinical outcomes of breast cancer patients with positive axillary lymph nodes receiving SLNB alone or ALND to determine which patients could potentially avoid ALND. Methods: A total of 21,942 breast cancer patients, including a training set (n=15,362) and a testing set (n=6,580), were enrolled in this study from Surveillance, Epidemiology, and End Results (SEER) between 2000 and 2017. The risk factors associated with breast cancer-specific survival (BCSS) and overall survival (OS) were evaluated using multivariate Cox regression analysis and then integrated into nomograms and risk stratification models examined by receiver operating characteristic (ROC) curves and calibration curves. The survival discrepancies were compared between the SLNB and ALND subgroups with different risk scores with Kaplan-Meier plots. Results: In multivariate Cox regression analyses, grade, marital status, T stage, radiotherapy and lymph node metastasis (GMTRL) were independent risk factors in breast cancer patients with both OS and BCSS status in the ALND cohort from the training set. Nomograms have been developed based on these factors to predict 3- and 5-year OS and BCSS in patients with ALND. Calibration curves and ROC curves in both the training and testing sets confirmed the excellent overall predictive performance of the nomograms. Furthermore, we developed two risk stratification models based on OS and BCSS status, revealing that patients with low GMTRL scores might avoid ALND in both OS and BCSS status [OS: hazard ratio (HR) =0.929, 95% confidence interval (CI): 0.841-1.027, P=0.150; BCSS: HR =0.953, 95% CI: 0.831-1.094, P=0.495], but patients with moderate (OS: HR =0.756, 95% CI: 0.666-0.859, P<0.001; BCSS: HR =0.643, 95% CI: 0.537-0.768, P<0.001) and high GMTRL scores could not (OS: HR =0.719, 95% CI: 0.549-0.940, P=0.014; BCSS: HR =0.731, 95% CI: 0.549-0.974, P=0.031). Conclusions: Breast cancer patients with positive nodes could be treated with SLNB alone rather than ALND without affecting prognosis based on GMTRL scores. Patients with high or moderate GMTRL scores benefited greatly from ALND, but not for patients with low GMTRL scores. This study may assist clinicians in tailoring treatments.

Association between oral microbiome and seven types of cancers in East Asian population: a two-sample Mendelian randomization analysis.

Background: The oral microbiome has been intricately linked to various pathological conditions, notably cancer, though clear causal links remain elusive. This study aimed to investigate the potential causal relationships between the oral microbiome and seven major cancers: breast, lung, pancreatic, colorectal, gastric, ovarian, and prostate cancers, leveraging Mendelian randomization (MR). Methods: A two-sample MR analysis was conducted using genome-wide association study (GWAS) data specific to oral microbiota in individuals of East Asian descent. Single nucleotide polymorphisms (SNPs) independent of confounders served as instrumental variables (IVs) to deduce causality. MR methodologies such as the inverse variance weighted (IVW) method, weighted median (WM) method, and Mendelian randomization-Egger (MR-Egger) method were employed. The study utilized datasets encapsulating a multitude of cancer cases and controls, focusing on Asian populations. Results: Our analysis revealed intricate associations between specific bacterial genera of the oral microbiome and diverse cancers. Notably, Fusobacterium showed mixed associations with various cancers, while genera like Prevotella and Streptococcus exhibited nuanced roles across malignancies. The genus Aggregatibacter demonstrated a multifaceted influence, positively correlating with some cancers while inhibiting others. Conclusion: Our findings underscore the profound implications of the oral microbiome in systemic malignancies, suggesting potential modulatory roles in cancer etiology. These insights, though preliminary, accentuate the need for deeper exploration and could pave the way for novel therapeutic strategies.

Relationships among breast, gut, and oral microbiota across diverse pathological types of breast cancer, a Chinese cohort study.

Background: Recent research has unveiled the association between microbiota and the onset and progression of breast cancer (BC). This study investigates the microbiota in breast tissue, the gut, and the oral cavity in relation to different pathological types of breast diseases, aiming to unveil the microbiota-BC relationship and provide new perspectives for BC diagnosis and treatment. Methods: The study encompassed a total of 98 breast cancer patients, with 52 diagnosed with Luminal A BC, 17 with Luminal B BC, 18 with HER2 BC, and 11 with TNBC. In addition, there were 46 patients with non-malignant breast diseases. The V3-V5 region of the 16S rRNA gene of breast tissue, feces, and the oral cavity was sequenced. Based on Amplicon Sequence Variants (ASV) representative sequences and abundance information, a series of statistical analyses were conducted including community diversity analysis, community composition analysis, species difference analysis, correlation analysis, and functional prediction analysis. Results: Notable divergences in α-diversity and ß-diversity were discerned in breast tissue between BC patients and non-malignant breast disease patients. The linear discriminant analysis effect size (LEfSe) and random forest examinations pinpoint Pasteurellaceae as a significant predictor in BC cohorts. Further exploration revealed significant microbial distribution divergences across distinct pathological types of BC, with notable variations in the relative abundance of microbial species such as Streptococcus, Serratia, and Pseudomonas, underscoring the diverse microbial diversity across BC subtypes and sample origins. Conclusion: This venture sheds light on the complex microbiota milieu across varying body sites and pathological types of BC, emphasizing microbiota-BC connectivity. This articulation of a multisite microbiota-BC interrelation significantly advances a holistic grasp of BC pathogenesis.

GNet: An integrated context-aware neural framework for transcription factor binding signal at single nucleotide resolution prediction.

Transcription factors (TFs) are important factors that regulate gene expression. Revealing the mechanism affecting the binding specificity of TFs is the key to understanding gene regulation. Most of the previous studies focus on TF-DNA binding sites at the sequence level, and they seldom utilize the contextual features of DNA sequences. In this paper, we develop an integrated spatiotemporal context-aware neural network framework, named GNet, for predicting TF-DNA binding signal at single nucleotide resolution by achieving three tasks: single nucleotide resolution signal prediction, identification of binding regions at the sequence level, and TF-DNA binding motif prediction. GNet extracts implicit spatial contextual information with a gated highway neural mechanism, which captures large context multi-level patterns using linear shortcut connections, and the idea of it permeates the encoder and decoder parts of GNet. The improved dual external attention mechanism, which learns implicit relationships both within and among samples, and improves the performance of the model. Experimental results on 53 human TF ChIP-seq datasets and 6 chromatin accessibility ATAC-seq datasets shows that GNet outperforms the state-of-the-art methods in the three tasks, and the results of cross-species studies on 15 human and 18 mouse TF datasets of the corresponding TF families indicate that GNet also shows the best performance in cross-species prediction over the competitive methods.

Role of aggressive locoregional surgery in treatment strategies for ipsilateral supraclavicular lymph node metastasis of breast cancer: a real-world cohort study.

Background: Breast cancer patients with synchronous ipsilateral supraclavicular lymph node metastases (ISLNM) have unfavorable prognoses. The role of supraclavicular lymph node dissection (SLND) as a surgical intervention in the treatment of this condition remains controversial. In this study, we aimed to evaluate the prognostic factors associated with breast cancer with ISLNM and to assess the potential impact of aggressive locoregional surgical management on patient outcomes. Methods: We conducted a retrospective analysis of 250 breast cancer patients with ISLNM who were treated with curative intent at our institution between 2000 and 2020. The cohort was stratified into groups based on the extent of axillary surgery. The first group, comprising 185 patients, underwent level I/II axillary dissection. The second group, consisting of 65 patients, underwent aggressive locoregional surgery, including levels I/II/III (infraclavicular) dissection in 37 patients and levels I/II/III + SLND in 28 patients. Our study evaluated overall survival (OS) and disease-free survival (DFS) as primary endpoints, and locoregional recurrence-free survival (LRRFS) and distant metastasis-free survival (DMFS) as secondary endpoints. Results: The median follow-up time among all patients was 5.92 years (1.05-15.36 years). The 5-year OS rate was 71.89%, while the DFS rate, LRRFS rate, and DMFS rates were 59.25%, 66.38%, and 64.98%, respectively. A significant difference in OS, DFS, LRRFS, and DMFS was observed between the second group and the first group (p < 0.01). No beneficial impact on recurrence, metastasis, or survival outcomes was observed in the levels I/II/III + SLND group compared to the levels I/II/III dissection group. Multivariate logistic regression analysis revealed that levels I/II/III ± SLND surgery and T stage were associated with OS (p = 0.006 and p = 0.026), while levels I/II/III ± SLND surgery, ER+/HER2-, and histologic grade were associated with DFS (p = 0.032, p = 0.001, p = 0.032). Conclusion: Breast cancer with ISLNM may be considered a locoregional disease, requiring a combination of systemic and local therapies. Aggressive locoregional surgery has been shown to positively impact recurrence, metastasis, and survival outcomes. This approach may provide improved management of the ISLNM for breast cancer patients.

EnILs: A General Ensemble Computational Approach for Predicting Inducing Peptides of Multiple Interleukins.

Interleukins (ILs) are a group of multifunctional cytokines, which play important roles in immune regulations and inflammatory responses. Recently, IL-6 has been found to affect the development of COVID-19, and significantly elevated levels of IL-6 cytokines have been reported in patients with severe COVID-19. IL-10 and IL-17 are anti-inflammatory and proinflammatory cytokines, respectively, which play multiple protective roles in host defense against pathogens. At present, a number of machine learning methods have been proposed to predict ILs inducing peptides, but their predictive performance needs to be further improved, and the inducing peptides of different ILs are predicted separately, rather than using a general approach. In our work, we combine the statistical features of peptide sequence with word embedding to design a general ensemble model named EnILs to predict inducing peptides of different ILs, in which the predictive probabilities of random forest, eXtreme Gradient Boosting and neural network are integrated in an average way. Compared with the state-of-the-art machine learning methods, EnILs shows considerable performance in the prediction of IL-6, IL-10, and IL-17 inducing peptides. In addition, we predict the most promising IL-6 inducing peptides in Severe Acute Respiratory Syndrome Coronavirus 2 spike protein in the case study for further experimental verification.