Multimodal analysis of cfDNA methylomes for early detecting esophageal squamous cell carcinoma and precancerous lesions.

Detecting early-stage esophageal squamous cell carcinoma (ESCC) and precancerous lesions is critical for improving survival. Here, we conduct whole-genome bisulfite sequencing (WGBS) on 460 cfDNA samples from patients with non-metastatic ESCC or precancerous lesions and matched healthy controls. We develop an expanded multimodal analysis (EMMA) framework to simultaneously identify cfDNA methylation, copy number variants (CNVs), and fragmentation markers in cfDNA WGBS data. cfDNA methylation markers are the earliest and most sensitive, detectable in 70% of ESCCs and 50% of precancerous lesions, and associated with molecular subtypes and tumor microenvironments. CNVs and fragmentation features show high specificity but are linked to late-stage disease. EMMA significantly improves detection rates, increasing AUCs from 0.90 to 0.99, and detects 87% of ESCCs and 62% of precancerous lesions with >95% specificity in validation cohorts. Our findings demonstrate the potential of multimodal analysis of cfDNA methylome for early detection and monitoring of molecular characteristics in ESCC.

Metabolite profiling, antioxidant and anti-glycemic activities of Tartary buckwheat processed by solid-state fermentation(SSF)with Ganoderma lucidum.

The aim of this study was to investigate the effect of Ganoderma lucidum fermentation on antioxidant and anti-glycemic activities of Tartary buckwheat. Xylanase, total cellulase (CMCase and FPase) and ß-glucosidase in fermented Tartary buckwheat (FB) increased significantly to 242.06 U/g, 17.99 U/g and 8.67 U/g, respectively. And the polysaccharides, total phenols, flavonoids and triterpenoids, which is increased by 122.19%, 113.70%, 203.74%, and 123.27%, respectively. Metabolite differences between non-fermented Tartary buckwheat (NFB) and FB pointed out that 445 metabolites were substantially different, and were involved in related biological metabolic pathways. There was a considerable rise in the concentrations of hesperidin, xanthotoxol and quercetin 3-O-malonylglucoside by 240.21, 136.94 and 100.77 times (in Fold Change), respectively. The results showed that fermentation significantly increased the antioxidant and anti-glycemic activities of buckwheat. This study demonstrates that the fermentation of Ganoderma lucidum provides a new idea to enhance the health-promoting components and bioactivities of Tartary buckwheat.

Radiomics for predicting MGMT status in cerebral glioblastoma: comparison of different MRI sequences.

Using radiomics to predict O6-methylguanine-DNA methyltransferase promoter methylation status in patients with newly diagnosed glioblastoma and compare the performances of different MRI sequences. Preoperative MRI scans from 215 patients were included in this retrospective study. After image preprocessing and feature extraction, two kinds of machine-learning models were established and compared for their performances. One kind was established using all MRI sequences (T1-weighted image, T2-weighted image, contrast enhancement, fluid-attenuated inversion recovery, DWI_b_high, DWI_b_low and apparent diffusion coefficient), and the other kind was based on single MRI sequence as listed above. For the machine-learning model based on all sequences, a total of seven radiomic features were selected with the Maximum Relevance and Minimum Redundancy algorithm. The predictive accuracy was 0.993 and 0.750 in the training and validation sets, respectively, and the area under curves were 1.000 and 0.754 in the two sets, respectively. For the machine-learning model based on single sequence, the numbers of selected features were 8, 10, 10, 13, 9, 7 and 6 for T1-weighted image, T2-weighted image, contrast enhancement, fluid-attenuated inversion recovery, DWI_b_high, DWI_b_low and apparent diffusion coefficient, respectively, with predictive accuracies of 0.797-1.000 and 0.583-0.694 in the training and validation sets, respectively, and the area under curves of 0.874-1.000 and 0.538-0.697 in the two sets, respectively. Specifically, T1-weighted image-based model performed best, while contrast enhancement-based model performed worst in the independent validation set. The machine-learning models based on seven different single MRI sequences performed differently in predicting O6-methylguanine-DNA methyltransferase status in glioblastoma, while the machine-learning model based on the combination of all sequences performed best.

Iron deficiency at birth and risk of hidden hearing loss in infants modification by socioeconomic status: mother-newborn cohort in Shenyang, China.

OBJECTIVE: The diagnosis of hidden hearing loss (HHL) in calm state has not yet been determined, while the nutritional status is not involved in its pathogenic risk factors. In utero iron deficiency (ID) may delay auditory neural maturation in infants. We evaluated the association between ID and HHL as well as the modification effect of socioeconomic status (SES) on this association in newborns. STUDY DESIGN: We included 859 mother-newborns from the baseline of this observational northeast cohort. Data on exposure assessment included iron status [maternal hemoglobin (Hb) and neonatal heel prick serum ferritin (SF)] and SES (occupation, education and income). Auditory neural maturation was reflected by auditory brainstem response (ABR) testing and electrocochleography (ECochG). RESULTS: Iron status and SES were independently and jointly associated with the prediction of neonatal HHL by logistic and linear regression model. The mediation effects were performed by Process. ID increased absolute latency wave V, interpeak latency (IPL) III-V, and summting potentials (SP) /action potentials (AP), which were combined as HHL. Low SES showed the highest risk of HHL and the highest levels of related parameters in ID newborns. Moreover, after Corona Virus Disease 2019 (COVID-19) were positive, preschool children who experience ID in neonatal period were more likely to suffer from otitis media with effusion (OME). High SES also showed similar risk effects. CONCLUSION: Both low and high SES may strengthen the risk of ID on neonatal HHL in Northeast China.

Inference of Developmental Hierarchy and Functional States of Exhausted T Cells from Epigenetic Profiles with Deep Learning.

Exhausted T cells are a key component of immune cells that play a crucial role in the immune response against cancer and influence the efficacy of immunotherapy. Accurate assessment and measurement of T-cell exhaustion (TEX) are critical for understanding the heterogeneity of TEX in the tumor microenvironment (TME) and tailoring individualized immunotherapeutic strategies. In this study, we introduced DeepEpiTEX, a novel computational framework based on deep neural networks, for inferring the developmental hierarchy and functional states of exhausted T cells in the TME from epigenetic profiles. DeepEpiTEX was trained using various modalities of epigenetic data, including DNA methylation data, microRNA expression data, and long non-coding RNA expression data from 30 bulk solid cancer types in the TCGA pan-cancer cohort, and identified five optimal TEX subsets with significant survival differences across the majority of cancer types. The performance of DeepEpiTEX was further evaluated and validated in external multi-center and multi-type cancer cohorts, consistently demonstrating its generalizability and applicability in different experimental settings. In addition, we discovered the potential relationship between TEX subsets identified by DeepEpiTEX and the response to immune checkpoint blockade therapy, indicating that individuals with immune-favorable TEX subsets may experience the greatest benefits. In conclusion, our study sheds light on the role of epigenetic regulation in TEX and provides a powerful and promising tool for categorizing TEX in different disease settings.

Risk factors for premature rupture of membranes in pregnant women: a systematic review and meta-analysis.

OBJECTIVE: To identify risk factors for premature rupture of membranes (PROM) in pregnant women. DESIGN: Systematic review and meta-analysis. DATA SOURCES: Web of Science, PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure, Wanfang Database, Chinese Scientific Journal Database (VIP) and China Biology Medicine Disc were searched from inception to October 2022. ELIGIBILITY CRITERIA: Cross-sectional, case-control and cohort studies published in English or Chinese that reported the risk factors for PROM were eligible for inclusion. DATA EXTRACTION AND SYNTHESIS: Two reviewers independently extracted the data and evaluated the risk of bias using the Newcastle-Ottawa Scale and American Agency for Healthcare Research and Quality tools. Analyses were performed using RevMan 5.4 software, and heterogeneity was assessed using χ2 tests and I2 statistics. The sensitivity analyses included a methodological transition between fixed-effect and random-effect models and the systematic stepwise exclusion of studies. RESULTS: A total of 21 studies involving 18 174 participants with 18 risk factors were included. The significant risk factors were low Body Mass Index (BMI) (OR 2.18, 95% CI 1.32 to 3.61), interpregnancy interval (IPI) <2 years (OR 2.99, 95% CI 1.98 to 4.50), previous abortion (OR 2.35, 95% CI 1.76 to 3.14), previous preterm birth (OR 5.72, 95% CI 3.44 to 9.50), prior PROM (OR 3.95, 95% CI 2.48 to 6.28), history of caesarean section (OR 3.06, 95% CI 1.72 to 5.43), gestational hypertension (OR 3.84, 95% CI 2.36 to 6.24), gestational diabetes mellitus (GDM) (OR 2.16, 95% CI 1.44 to 3.23), abnormal vaginal discharge (OR 2.17, 95% CI 1.45 to 3.27), reproductive tract infection (OR 2.16, 95% CI 1.70 to 2.75), malpresentation (OR 2.26, 95% CI 1.78 to 2.85) and increased abdominal pressure (OR 1.45, 95% CI 1.07 to 1.97). The sensitivity analysis showed that the pooled estimates were stable. CONCLUSIONS: This meta-analysis indicated that low BMI, IPI <2 years, previous abortion, previous preterm birth, prior PROM, history of caesarean section, gestational hypertension, GDM, abnormal vaginal discharge, reproductive tract infection, malpresentation and increased abdominal pressure might be associated with a greater risk of PROM. Associations between smoking status, short cervical length, fine particulate matter (PM2.5) and PROM require further investigation. PROSPERO REGISTRATION NUMBER: CRD42022381485.

The diagnostic efficiency of integration of 2HG MRS and IVIM versus individual parameters for predicting IDH mutation status in gliomas in clinical scenarios: A retrospective study.

PURPOSE: Currently, there remains a scarcity of established preoperative tests to accurately predict the isocitrate dehydrogenase (IDH) mutation status in clinical scenarios, with limited research has explored the potential synergistic diagnostic performance among metabolite, perfusion, and diffusion parameters. To address this issue, we aimed to develop an imaging protocol that integrated 2-hydroxyglutarate (2HG) magnetic resonance spectroscopy (MRS) and intravoxel incoherent motion (IVIM) by comprehensively assessing metabolic, cellular, and angiogenic changes caused by IDH mutations, and explored the diagnostic efficiency of this imaging protocol for predicting IDH mutation status in clinical scenarios. METHODS: Patients who met the inclusion criteria were categorized into two groups: IDH-wild type (IDH-WT) group and IDH-mutant (IDH-MT) group. Subsequently, we quantified the 2HG concentration, the relative apparent diffusion coefficient (rADC), the relative true diffusion coefficient value (rD), the relative pseudo-diffusion coefficient (rD*) and the relative perfusion fraction value (rf). Intergroup differences were estimated using t-test and Mann-Whitney U test. Finally, we performed receiver operating characteristic (ROC) curve and DeLong's test to evaluate and compare the diagnostic performance of individual parameters and their combinations. RESULTS: 64 patients (female, 21; male, 43; age, 47.0 ± 13.7 years) were enrolled. Compared with IDH-WT gliomas, IDH-MT gliomas had higher 2HG concentration, rADC and rD (P < 0.001), and lower rD* (P = 0.013). The ROC curve demonstrated that 2HG + rD + rD* exhibited the highest areas under curve (AUC) value (0.967, 95%CI 0.889-0.996) for discriminating IDH mutation status. Compared with each individual parameter, the predictive efficiency of 2HG + rADC + rD* and 2HG + rD + rD* shows a statistically significant enhancement (DeLong's test: P < 0.05). CONCLUSIONS: The integration of 2HG MRS and IVIM significantly improves the diagnostic efficiency for predicting IDH mutation status in clinical scenarios.

A comprehensive database of exosome molecular biomarkers and disease-gene associations.

Exosomes play a crucial role in intercellular communication and can be used as biomarkers for diagnostic and therapeutic clinical applications. However, systematic studies in cancer-associated exosomal nucleic acids remain a big challenge. Here, we developed ExMdb, a comprehensive database of exosomal nucleic acid biomarkers and disease-gene associations curated from published literature and high-throughput datasets. We performed a comprehensive curation of exosome properties including 4,586 experimentally supported gene-disease associations, 13,768 diagnostic and therapeutic biomarkers, and 312,049 nucleic acid subcellular locations. To characterize expression variation of exosomal molecules and identify causal factors of complex diseases, we have also collected 164 high-throughput datasets, including bulk and single-cell RNA sequencing (scRNA-seq) data. Based on these datasets, we performed various bioinformatics and statistical analyses to support our conclusions and advance our knowledge of exosome biology. Collectively, our dataset will serve as an essential resource for investigating the regulatory mechanisms of complex diseases and improving the development of diagnostic and therapeutic biomarkers.

Impact of Ganoderma lucidum fermentation on the nutritional composition, structural characterization, metabolites, and antioxidant activity of Soybean, sweet potato and Zanthoxylum pericarpium residues.

One of the major issues in the food sector is the lack of resource utilization and the contamination of the environment caused by by-products. This study aimed to investigate the effects of Ganoderma lucidum (GL) fermentation on the nutritional components, structural characterization, metabolites, and antioxidant activity of soybean residue (SR), sweet potato residue (SPR), and zanthoxylum pericarpium residue (ZPR). The results showed that the nutrient contents of SR, SPR and ZPR increased. The active substances, amino acids (umami, aromatic and basic), metabolites and antioxidant activity (DPPH, ABTS, FRAP) (SR and SPR increased by 11.43, 32.64, 40.19 µmol Trolox/100 g and 19.29, 17.7, 32.35 µmol Trolox/100 g, respectively) of SR and SPR were increased. However, the results of ZPR showed a decrease in the content of bioactive substances, amino acids, and antioxidant activity. The results show that using GL fermentation can provide novel ideas and theoretical basis for improving SR and SPR to obtain new raw materials for antioxidant products.

Association Between Serum Glycated Hemoglobin Levels at Early Gestation and the Risk of Subsequent Pregnancy Loss in Pregnant Women Without Diabetes Mellitus: Prospective Cohort Study.

BACKGROUND: As a severe morbidity during pregnancy, the etiology of spontaneous pregnancy loss (SPL) remains largely unknown. Serum glycated hemoglobin (HbA1c) level is an established predictor of SPL risk among women with diabetes, but little is known about whether such an association exists among pregnant women without diabetes when glycemic levels are within the normal range. OBJECTIVE: This study aimed to quantify the association between maternal HbA1c levels in early pregnancy and subsequent SPL risk in a cohort of pregnant women without diabetes. METHODS: This prospective cohort study involved 10,773 pregnant women without diabetes enrolled at their first antenatal care visit at a hospital's early pregnancy clinic from March 2016 to December 2018 in Shanghai, China. HbA1c and fasting blood glucose (FBG) levels were examined at enrollment. Participants with diabetes before or pregnancy or those diagnosed with gestational diabetes were excluded. Diagnosis of SPL, defined as fetal death occurring before 28 gestational weeks, was derived from medical records and confirmed via telephone interviews. We used generalized linear models to quantify the associations of continuous and dichotomized maternal HbA1c levels with SPL risk and reported crude and adjusted risk ratios (RRs) and 95% CIs. A restricted cubic spline (RCS) regression model was used to assess the potential nonlinear dose-response relationship. Adjusted covariates included maternal age, education level, preconception BMI, gestational weeks, gravidity, history of adverse pregnancy outcomes, family history of diabetes, folic acid supplementation, and smoking and drinking during the periconception period. RESULTS: In total, 273 (2.5%) SPL cases occurred. Every 0.5% increase in HbA1c levels was linearly associated with a 23% increase in SPL risk (adjusted RR [aRR] 1.23; 95% CI 1.01-1.50). The RCS model revealed that this association was linear (P=.77 for the nonlinearity test). Analyses based on dichotomized HbA1c levels showed a significantly increased risk of SPL when HbA1c levels were ≥5.9% (aRR 1.67; 95% CI 0.67-3.67), and the significance threshold was ≥5.6% (aRR 1.60; 95% CI 1.01-2.54). Sensitivity analyses showed similar results when including the participants with missing SPL records or HbA1c data. Linear associations of HbA1c levels remained significant even in the subgroups without overweight, alcohol consumption, and a family history of diabetes and adverse pregnancy outcomes. Every 1 mmol/L increment in maternal FBG levels was associated with a >2-fold higher risk of SPL (aRR 2.12; 95% CI 1.61-2.80; P<.001). CONCLUSIONS: Higher HbA1c levels in early pregnant women without diabetes are associated with an increased SPL risk in a dose-response manner. Pregnant women with an HbA1c level above 5.6% at early gestation need attention for its potentially increased risk for SPL. Our findings support the need to monitor HbA1c levels to identify individuals at high risk of subsequent SPL in the general population of pregnant women. TRIAL REGISTRATION: ClinicalTrials.gov NCT02737644; https://clinicaltrials.gov/study/NCT02737644.

Androgen Receptor/AP-1 Activates UGT2B15 Transcription to Promote Esophageal Squamous Cell Carcinoma Invasion.

Esophageal squamous cell carcinoma (ESCC) is an aggressive epithelial malignancy with poor prognosis. Interestingly, ESCC is strongly characterized by a male-predominant propensity. Our previous study showed that androgen receptor (AR) orchestrated a transcriptional repression program to promote ESCC growth, but it remains unclear whether AR can also activate oncogenic signaling during ESCC progression. In this study, by analyzing our previous AR cistromes and androgen-regulated transcriptomes, we identified uridine diphosphate glucuronosyltransferase family 2 member B15 (UGT2B15) as a bona fide target gene of AR. Mechanistically, AP-1 cofactors played important and collaborative roles in AR-mediated UGT2B15 upregulation. Functional studies have revealed that UGT2B15 promoted invasiveness in vitro and lymph node metastasis in vivo. UGT2B15 was partially responsible for the AR-induced invasive phenotype in ESCC cells. Importantly, simultaneous blocking of AP-1 and AR resulted in stronger inhibition of cell invasiveness compared to inhibiting AP-1 or AR alone. In conclusion, our study reveals the molecular mechanisms underlying the AR-driven ESCC invasion and suggests that the AR/AP1/UGT2B15 transcriptional axis can be potentially targeted in suppressing metastasis in male ESCC patients.

Radiogenomic Analysis of Vascular Endothelial Growth Factor in Patients With Glioblastoma.

OBJECTIVES: This article aims to predict the presence of vascular endothelial growth factor (VEGF) expression and to predict the expression level of VEGF by machine learning based on preoperative magnetic resonance imaging (MRI) of glioblastoma (GBM). METHODS: We analyzed the axial T2-weighted images (T2WI) and T1-weighted contrast-enhancement images of preoperative MRI in 217 patients with pathologically diagnosed GBM. Patients were divided into negative and positive VEGF groups, with the latter group further subdivided into low and high expression. The machine learning models were established with the maximum relevance and minimum redundancy algorithm and the extreme gradient boosting classifier. The area under the receiver operating curve (AUC) and accuracy were calculated for the training and validation sets. RESULTS: Positive VEGF in GBM was 63.1% (137/217), with a high expression ratio of 53.3% (73/137). To predict the positive and negative VEGF expression, 7 radiomic features were selected, with 3 features from T1CE and 4 from T2WI. The accuracy and AUC were 0.83 and 0.81, respectively, in the training set and were 0.73 and 0.74, respectively, in the validation set. To predict high and low levels, 7 radiomic features were selected, with 2 from T1CE, 1 from T2WI, and 4 from the data combinations of T1CE and T2WI. The accuracy and AUC were 0.88 and 0.88, respectively, in the training set and were 0.72 and 0.72, respectively, in the validation set. CONCLUSION: The VEGF expression status in GBM can be predicted using a machine learning model. Radiomic features resulting from data combinations of different MRI sequences could be helpful.

Progenitor-like exhausted SPRY1+CD8+ T cells potentiate responsiveness to neoadjuvant PD-1 blockade in esophageal squamous cell carcinoma.

Neoadjuvant immune checkpoint blockade (ICB) demonstrates promise in operable esophageal squamous cell carcinoma (ESCC), but lacks available efficacy biomarkers. Here, we perform single-cell RNA-sequencing of tumors from patients with ESCC undergoing neoadjuvant ICB, revealing a subset of exhausted CD8+ T cells expressing SPRY1 (CD8+ Tex-SPRY1) that displays a progenitor exhausted T cell (Tpex) phenotype and correlates with complete response to ICB. We validate CD8+ Tex-SPRY1 cells as an ICB-specific predictor of improved response and survival using independent ICB-/non-ICB cohorts and demonstrate that expression of SPRY1 in CD8+ T cells enforces Tpex phenotype and enhances ICB efficacy. Additionally, CD8+ Tex-SPRY1 cells contribute to proinflammatory phenotype of macrophages and functional state of B cells, which thereby promotes antitumor immunity by enhancing CD8+ T cell effector functions. Overall, our findings unravel progenitor-like CD8+ Tex-SPRY1 cells' role in effective responses to ICB for ESCC and inform mechanistic biomarkers for future individualized immunotherapy.

Characterization of tumour microenvironment reprogramming reveals invasion in epithelial ovarian carcinoma.

BACKGROUND: Patients with epithelial ovarian carcinoma (EOC) are usually diagnosed at an advanced stage with tumour cell invasion. However, identifying the underlying molecular mechanisms and biomarkers of EOC proliferation and invasion remains challenging. RESULTS: Herein, we explored the relationship between tumour microenvironment (TME) reprogramming and tissue invasion based on single-cell RNA sequencing (scRNA-seq) datasets. Interestingly, hypoxia, oxidative phosphorylation (OXPHOS) and glycolysis, which have biologically active trajectories during epithelial mesenchymal transition (EMT), were positively correlated. Moreover, energy metabolism and anti-apoptotic activity were found to be critical contributors to intratumor heterogeneity. In addition, HMGA1, EGR1 and RUNX1 were found to be critical drivers of the EMT process in EOC. Experimental validation revealed that suppressing EGR1 expression inhibited tumour cell invasion, significantly upregulated the expression of E-cadherin and decreased the expression of N-cadherin. In cell components analysis, cancer-associated fibroblasts (CAFs) were found to significantly contribute to immune infiltration and tumour invasion, and the accumulation of CAFs was associated with poorer patient survival. CONCLUSION: We revealed the molecular mechanism and biomarkers of tumour invasion and TME reprogramming in EOC, which provides effective targets for the suppression of tumour invasion.

Insight of novel biomarkers for papillary thyroid carcinoma through multiomics.

Introduction: The overdiagnosing of papillary thyroid carcinoma (PTC) in China necessitates the development of an evidence-based diagnosis and prognosis strategy in line with precision medicine. A landscape of PTC in Chinese cohorts is needed to provide comprehensiveness. Methods: 6 paired PTC samples were employed for whole-exome sequencing, RNA sequencing, and data-dependent acquisition mass spectrum analysis. Weighted gene co-expression network analysis and protein-protein interactions networks were used to screen for hub genes. Moreover, we verified the hub genes' diagnostic and prognostic potential using online databases. Logistic regression was employed to construct a diagnostic model, and we evaluated its efficacy and specificity based on TCGA-THCA and GEO datasets. Results: The basic multiomics landscape of PTC among local patients were drawn. The similarities and differences were compared between the Chinese cohort and TCGA-THCA cohorts, including the identification of PNPLA5 as a driver gene in addition to BRAF mutation. Besides, we found 572 differentially expressed genes and 79 differentially expressed proteins. Through integrative analysis, we identified 17 hub genes for prognosis and diagnosis of PTC. Four of these genes, ABR, AHNAK2, GPX1, and TPO, were used to construct a diagnostic model with high accuracy, explicitly targeting PTC (AUC=0.969/0.959 in training/test sets). Discussion: Multiomics analysis of the Chinese cohort demonstrated significant distinctions compared to TCGA-THCA cohorts, highlighting the unique genetic characteristics of Chinese individuals with PTC. The novel biomarkers, holding potential for diagnosis and prognosis of PTC, were identified. Furthermore, these biomarkers provide a valuable tool for precise medicine, especially for immunotherapeutic or nanomedicine based cancer therapy.

DNA damage repair profiling of esophageal squamous cell carcinoma uncovers clinically relevant molecular subtypes with distinct prognoses and therapeutic vulnerabilities.

BACKGROUND: DNA damage repair (DDR) is a critical process that maintains genomic integrity and plays essential roles at both the cellular and organismic levels. Here, we aimed to characterize the DDR profiling of esophageal squamous cell carcinoma (ESCC), investigate the prognostic value of DDR-related features, and explore their potential for guiding personalized treatment strategies. METHODS: We analyzed bulk and single-cell transcriptomics data from 377 ESCC cases from our institution and other publicly available cohorts to identify major DDR subtypes. The heterogeneity in cellular and functional properties, tumor microenvironment (TME) characteristics, and prognostic significance of these DDR subtypes were investigated using immunogenomic analysis and in vitro experiments. Additionally, we experimentally validated a combinatorial immunotherapy strategy using syngeneic mouse models of ESCC. FINDINGS: DDR alteration profiling enabled us to identify two distinct DDR subtypes, DDRactive and DDRsilent, which exhibited independent prognostic values in locoregional ESCC but not in metastatic ESCC. The DDRsilent subtype was characterized by an inflamed but immune-suppressed microenvironment with relatively high immune cell infiltration, abnormal immune checkpoint expression, T-cell exhaustion, and enrichment of cancer-related pathways. Moreover, DDR subtyping indicates that BRCA1 and HFM1 are robust and independent prognostic factors in locoregional ESCC. Finally, we proposed and verified that the concomitant triggering of GITR or blockade of BTLA with PD-1 blockade or cisplatin chemotherapy represents effective combination strategies for high-risk locoregional ESCC tumors. INTERPRETATION: Our discovery of DDR-based molecular subtypes will enhance our understanding of tumor heterogeneity and have significant clinical implications for the therapeutic and management strategies of locoregional ESCC. FUNDING: This study was supported by the National Key R&D Program of China (2021YFC2501000, 2022YFC3401003), National Natural Science Foundation of China (82172882), the Beijing Natural Science Foundation (7212085), the CAMS Innovation Fund for Medical Sciences (2021-I2M-1-018, 2021-I2M-1-067), the Fundamental Research Funds for the Central Universities (3332021091), and the Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences (2019PT310027).

Crosstalk between gut microbiota and RNA N6-methyladenosine modification in cancer.

The gut microbiota plays a crucial role in regulating various host metabolic, immune, and neuroendocrine functions, and has a significant impact on human health. Several lines of evidence suggest that gut dysbiosis is associated with a variety of diseases, including cancer. The gut microbiota can impact the development and progression of cancer through a range of mechanisms, such as regulating cell proliferation and death, modulating the host immune response, and altering the host metabolic state. Gene regulatory programs are considered critical mediators between the gut microbiota and host phenotype, of which RNA N6-methyladenosine (m6A) modifications have attracted much attention recently. Aberrant m6A modifications have been shown to play a crucial role in cancer development. This review aims to provide an overview of the diverse roles of gut microbiota and RNA m6A modifications in cancer and highlight their potential interactions in cancer development.

CGRP-Loaded Porous Microspheres Protect BMSCs for Alveolar Bone Regeneration in the Periodontitis Microenvironment.

Periodontitis is a prevalent dental disease marked by progressive destruction of tooth-supporting tissues, and the recovery of bone defects after periodontitis remains challenging. Although stem cell-based therapy is a promising treatment for periodontal tissue regeneration, the function of mesenchymal stem cells is constantly impaired by the inflammatory microenvironment, leading to compromised treatment outcomes. Herein, calcitonin gene-related peptide (CGRP)-loaded porous microspheres (PMs) are prepared to protect bone marrow mesenchymal stem cells (BMSCs) against inflammatory mediators in periodontitis. The released CGRP can effectively ameliorate the inflammation-induced dysfunction of BMSCs, which may involve suppressing the ROS (reactive oxygen species)/NLRP3 (NOD-, LRR-, and pyrin domain-containing protein 3)/Caspase-1 (CASP1) pathway. Moreover, the porous architecture of PMs provides effective cell-carrying capacity and physical protection for BMSCs during transplantation. In vivo experiments demonstrate that CGRP/BMSC-loaded PMs can effectively inhibit inflammation and improve osteogenic activity, resulting in better periodontal bone regeneration. This study focuses on the protection of stem cell function in the inflammatory microenvironment, which is important for stem cell-mediated tissue regeneration and repair under inflammatory conditions.

Deep learning identifies a T-cell exhaustion-dependent transcriptional signature for predicting clinical outcomes and response to immune checkpoint blockade.

Immune checkpoint blockade (ICB) therapies have brought unprecedented advances in cancer treatment, but responses are limited to a fraction of patients. Therefore, sustained and substantial efforts are required to advance clinical and translational investigation on managing patients receiving ICB. In this study, we investigated the dynamic changes in molecular profiles of T-cell exhaustion (TEX) during ICB treatment using single-cell and bulk transcriptome analysis, and demonstrated distinct exhaustion molecular profiles associated with ICB response. By applying an ensemble deep-learning computational framework, we identified an ICB-associated transcriptional signature consisting of 16 TEX-related genes, termed ITGs. Incorporating 16 ITGs into a machine-learning model called MLTIP achieved reliable predictive power for clinical ICB response with an average AUC of 0.778, and overall survival (pooled HR = 0.093, 95% CI, 0.031-0.28, P < 0.001) across multiple ICB-treated cohorts. Furthermore, the MLTIP consistently demonstrated superior predictive performance compared to other well-established markers and signatures, with an average increase in AUC of 21.5%. In summary, our results highlight the potential of this TEX-dependent transcriptional signature as a tool for precise patient stratification and personalized immunotherapy, with clinical translation in precision medicine.