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Bladder carcinoma (BC) recurrence is a major clinical challenge, and targeting the tumor microenvironment (TME) is a promising therapy. However, the relationship between individual TME components, particularly cancer‐associated fibroblasts (CAFs), and tumor recurrence is unclear. Here, TME heterogeneity in primary and recurrent BC is investigated using single‐cell RNA sequence profiling of 62 460 cells. Two cancer stem cell (CSC) subtypes are identified in recurrent BC. An inflammatory CAF subtype, ICAM1+ iCAFs, specifically associated with BC recurrence is also identified. iCAFs are found to secrete FGF2, which acts on the CD44 receptor of rCSC‐M, thereby maintaining tumor stemness and epithelial‐mesenchymal transition. Additionally, THBS1+ monocytes, a group of myeloid‐derived suppressor cells (MDSCs), are enriched in recurrent BC and interacted with CAFs. ICAM1+ iCAFs are found to secrete CCL2, which binds to CCR2 in MDSCs. Moreover, elevated STAT3 , NFKB2 , VEGFA , and CTGF levels in iCAFs reshape the TME in recurrent tumors. CCL2 inhibition in an in situ BC mouse model suppressed tumor growth, decreased MDSCs and Tregs, and fostered tumor immune suppression. The study results highlight the role of iCAFs in TME cell–cell crosstalk during recurrent BC. The identification of pivotal signaling factors driving BC relapse is promising for the development of novel therapies.

Background The gut microbiota evolves from birth and is in early life influenced by events such as birth mode, type of infant feeding, and maternal and infant antibiotics use. However, we still have a gap in our understanding of gut microbiota development in older children, and to what extent early events and pre-school lifestyle modulate the composition of the gut microbiota, and how this impinges on whole body metabolic regulation in school-age children. Results Taking advantage of the KOALA Birth Cohort Study, a long-term prospective birth cohort in the Netherlands with extensive collection of high-quality host metadata, we applied shotgun metagenomics sequencing and systematically investigated the gut microbiota of children at 6–9 years of age. We demonstrated an overall adult-like gut microbiota in the 281 Dutch school-age children and identified 3 enterotypes dominated by the genera Bacteroides , Prevotella , and Bifidobacterium , respectively. Importantly, we found that breastfeeding duration in early life and pre-school dietary lifestyle correlated with the composition and functional competences of the gut microbiota in the children at school age. The correlations between pre-school dietary lifestyle and metabolic phenotypes exhibited a striking enterotype dependency. Thus, an inverse correlation between high dietary fiber consumption and low plasma insulin levels was only observed in individuals with the Bacteroides and Prevotella enterotypes, but not in Bifidobacterium enterotype individuals in whom the gut microbiota displayed overall lower microbial gene richness, alpha-diversity, functional potential for complex carbohydrate fermentation, and butyrate and succinate production. High total fat consumption and elevated plasma free fatty acid levels in the Bifidobacterium enterotype are associated with the co-occurrence of Streptococcus . Conclusions Our work highlights the persistent effects of breastfeeding duration and pre-school dietary lifestyle in affecting the gut microbiota in school-age children and reveals distinct compositional and functional potential in children according to enterotypes. The findings underscore enterotype-specific links between the host metabolic phenotypes and dietary patterns, emphasizing the importance of microbiome-based stratification when investigating metabolic responses to diets. Future diet intervention studies are clearly warranted to examine gut microbe-diet-host relationships to promote knowledge-based recommendations in relation to improving metabolic health in children.

The incidence of pregestational type 2 diabetes mellitus (PGDM) is increasing, with high rates of serious adverse maternal and neonatal outcomes that are strongly correlated with hyperglycemia. Recent studies have shown that type 2 diabetes mellitus is associated with gut microbial dysbiosis; however, the gut microbiome composition and its associations with the metabolic features of patients with PGDM remain largely unknown. Human gut dysbiosis is associated with type 2 diabetes mellitus (T2DM); however, the gut microbiome in pregnant women with pregestational type 2 diabetes mellitus (PGDM) remains unexplored. We investigated the alterations in the gut microbiota composition in pregnant women with or without PGDM. The gut microbiota was examined using 16S rRNA sequencing data of 234 maternal fecal samples that were collected during the first (T1), second (T2), and third (T3) trimesters. The PGDM group presented a reduction in the number of gut bacteria taxonomies as the pregnancies progressed. Linear discriminant analyses revealed that Megamonas , Bacteroides , and Roseburia intestinalis were enriched in the PGDM group, whereas Bacteroides vulgatus , Faecalibacterium prausnitzii , Eubacterium rectale , Bacteroides uniformis , Eubacterium eligens , Subdoligranulum , Bacteroides fragilis , Dialister , Lachnospiraceae , Christensenellaceae R-7, Roseburia inulinivorans , Streptococcus oralis , Prevotella melaninogenica , Neisseria perflava , Bacteroides ovatus , Bacteroides caccae , Veillonella dispar , and Haemophilus parainfluenzae were overrepresented in the control group. Correlation analyses showed that the PGDM-enriched taxa were correlated with higher blood glucose levels during pregnancy, whereas the taxonomic biomarkers of normoglycemic pregnancies exhibited negative correlations with glycemic traits. The microbial networks in the PGDM group comprised weaker microbial interactions than those in the control group. Our study reveals the distinct characteristics of the gut microbiota composition based on gestational ages between normoglycemic and PGDM pregnancies. Further longitudinal research involving women with T2DM at preconception stages and investigations using shotgun metagenomic sequencing should be performed to elucidate the relationships between specific bacterial functions and PGDM metabolic statuses during pregnancy and to identify potential therapeutic targets. IMPORTANCE The incidence of pregestational type 2 diabetes mellitus (PGDM) is increasing, with high rates of serious adverse maternal and neonatal outcomes that are strongly correlated with hyperglycemia. Recent studies have shown that type 2 diabetes mellitus is associated with gut microbial dysbiosis; however, the gut microbiome composition and its associations with the metabolic features of patients with PGDM remain largely unknown. In this study, we investigated the changes in the gut microbiota composition in pregnant women with and without PGDM. We identified differential taxa that may be correlated with maternal metabolic statuses during pregnancy. Additionally, we observed that the number of taxonomic and microbial networks of gut bacteria were distinctly reduced in women with hyperglycemia as their pregnancies progressed. These results extend our understanding of the associations between the gut microbial composition, PGDM-related metabolic changes, and pregnancy outcomes.

The gut microbiome has been established as a key environmental factor to health. Genetic influences on the gut microbiome have been reported, yet, doubts remain as to the significance of genetic associations. Here, we provide shotgun data for whole genome and whole metagenome from a Chinese cohort, identifying no <20% genetic contribution to the gut microbiota. Using common variants-, rare variants-, and copy number variations-based association analyses, we identified abundant signals associated with the gut microbiome especially in metabolic, neurological, and immunological functions. The controversial concept of enterotypes may have a genetic attribute, with the top two loci explaining 11% of the Prevotella–Bacteroides variances. Stratification according to gender led to the identification of differential associations in males and females. Our two-stage metagenome genome-wide association studies on a total of 1295 individuals unequivocally illustrates that neither microbiome nor GWAS studies could overlook one another in our quest for a better understanding of human health and diseases.

Cancer‐associated fibroblasts (CAFs) play a crucial role in tumor progression, with heterogeneity influencing therapeutic response and prognosis, highlighting their potential as viable targets for treatment. In this study, a novel CAF subgroup, MMP11+ mCAF is identified, through single‐cell RNA sequencing, which accumulates progressively during bladder cancer progression and is significantly associated with poor prognosis. This cell population regulates the migration of tip endothelial cell clusters (ESM1+tEC) via the WNT5A‐MCAM signaling axis, and modulates the expression of key transcription factors, SOX18, NFIC, and HOXB9. Additionally, MMP11+ mCAFs recruit SPP1+ macrophages through CCL11/CCL2, promoting VEGFA secretion, which further enhances the pro‐angiogenic activity of ESM1+ tECs. Furthermore, interferon‐associated basal‐like tumor cells secrete BMP2, which induces the expression and activity of NFE2L3, a transcription factor specific to MMP11+ mCAFs, promoting WNT5A expression. Mouse experiments confirmed that inhibiting BMP2 can suppress tumor angiogenesis and growth in bladder cancer. Pan‐cancer analysis revealed that MMP11+ mCAFs are present across various cancer types, including breast cancer, lung adenocarcinoma, gastric cancer, and colorectal cancer. These findings provide insights into the heterogeneity of CAFs and their regulatory role in tumor progression, offering new potential therapeutic targets for CAF‐targeted treatments with broad applicability across cancers. Single‐cell RNA sequencing identifies MMP11⁺ CAFs as pro‐angiogenic cells accumulating during bladder cancer progression. These cells promote angiogenesis by regulating ESM1⁺ tip endothelial cells and recruiting SPP1⁺ macrophages. Tumor‐derived BMP2 promotes their activation. Targeting BMP2 suppresses tumor angiogenesis and growth, highlighting the therapeutic potential of CAF modulation in bladder cancer.

Helicobacter pylori infection (HPI) is a prevalent infectious disease associated with gastric ulcer, gastric cancer, and many nongastrointestinal disorders. To identify genes that may serve as microbial markers for HPI, we performed shotgun metagenomic sequencing of fecal samples from 313 Chinese volunteers who had undergone a C14 breath test. Through comparing differences in intestinal microbial community structure between H. pylori‐positive and H. pylori‐negative individuals, we identified 58 HPI‐associated microbial species (P < 0.05, Wilcoxon test). A classifier based on microbial species markers showed high diagnostic ability for HPI (AUC = 0.84). Furthermore, levels of gut microbial vitamin B12 (VB12) biosynthesis and plasma VB12 were significantly lower in H. pylori‐positive individuals compared with H. pylori‐negative individuals (P < 0.05, Wilcoxon test). This study reveals that certain alterations in gut microbial species and functions are associated with HPI and shows that gut microbial shift in HPI patients may indirectly elevate the risk of VB12 deficiency. Here, we performed metagenomic analyses to identify Helicobacter pylori infection‐related human gut microbial species and functional alterations, and report that gut microbial shift in H. pylori‐infected individuals may indirectly elevate the risk of VB12 deficiency.

Due to the strong heterogeneity of bladder cancer (BC), there is often substantial variation in the prognosis and efficiency of immunotherapy among BC patients. For the precision treatment and assessment of prognosis, the subtyping of BC plays a critical role. Despite various subtyping methods proposed previously, most of them are based on a limited number of molecules, and none of them is developed on the basis of cell states. In this study, we construct a single-cell atlas by integrating single cell RNA-seq, RNA microarray, and bulk RNA-seq data to identify the absolute proportion of 22 different cell states in BC, including immune and nonimmune cell states derived from tumor tissues. To explore the heterogeneity of BC, BC was identified into four different subtypes in multiple cohorts using an improved consensus clustering algorithm based on cell states. Among the four subtypes, C1 had median prognosis and best overall response rate (ORR), which characterized an immunosuppressive tumor microenvironment. C2 was enriched in epithelial-mesenchymal transition/invasion, angiogenesis, immunosuppression, and immune exhaustion. Surely, C2 performed the worst in prognosis and ORR. C3 with worse ORR than C2 was enriched in angiogenesis and almost nonimmune exhaustion. Displaying an immune effective environment, C4 performed the best in prognosis and ORR. We found that patients with just an immunosuppressive environment are suitable for immunotherapy, but patients with an immunosuppressive environment accompanied by immune exhaustion or angiogenesis may resist immunotherapy. Furthermore, we conducted exploration into the heterogeneity of the transcriptome, mutational profiles, and somatic copy-number alterations in four subtypes, which could explain the significant differences related to cell states in prognosis and ORR. We also found that PD-1 in immune and tumor cells could both influence ORR in BC. The level of TGFβ in a cell state can be opposite to the overall level in the tissues, and the level in a specific cell state could predict ORR more accurately. Thus, our work furthers the understanding of heterogeneity and immunotherapy resistance in BC, which is expected to assist clinical practice and serve as a supplement to the current subtyping method from a novel perspective of cell states.

Objectives To determine whether the texture feature analysis of multi-phase abdominal CT can provide a robust prediction of benign and malignant, histological subtype, pathological stage, nephrectomy risk, pathological grade, and Ki67 index in renal tumor. Methods A total of 1051 participants with renal tumor were split into the internal cohort (850 patients from four different hospitals) and the external testing cohort (201 patients from another local hospital). The proposed framework comprised a 3D-kidney and tumor segmentation model by 3D-UNet, a feature extractor for the regions of interest based on radiomics and image dimension reduction, and the six classifiers by XGBoost. A quantitative model interpretation method called SHAP was used to explore the contribution of each feature. Results The proposed multi-phase abdominal CT model provides robust prediction for benign and malignant, histological subtype, pathological stage, nephrectomy risk, pathological grade, and Ki67 index in the internal validation set, with the AUROC values of 0.88 ± 0.1, 0.90 ± 0.1, 0.91 ± 0.1, 0.89 ± 0.1, 0.84 ± 0.1, and 0.88 ± 0.1, respectively. The external testing set also showed impressive results, with AUROC values of 0.83 ± 0.1, 0.83 ± 0.1, 0.85 ± 0.1, 0.81 ± 0.1, 0.79 ± 0.1, and 0.81 ± 0.1, respectively. The radiomics feature including the first-order statistics, the tumor size–related morphology, and the shape-related tumor features contributed most to the model predictions. Conclusions Automatic texture feature analysis of abdominal multi-phase CT provides reliable predictions for multi-tasks, suggesting the potential usage of clinical application. Clinical relevance statement The automatic texture feature analysis framework, based on multi-phase abdominal CT, provides robust and reliable predictions for multi-tasks. These valuable insights can serve as a guiding tool for clinical diagnosis and treatment, making medical imaging an essential component in the process. Key Points • The automatic texture feature analysis framework based on multi-phase abdominal CT can provide more accurate prediction of benign and malignant, histological subtype, pathological stage, nephrectomy risk, pathological grade, and Ki67 index in renal tumor. • The quantitative decomposition of the prediction model was conducted to explore the contribution of the extracted feature. • The study involving 1051 patients from 5 medical centers, along with a heterogeneous external data testing strategy, can be seamlessly transferred to various tasks involving new datasets.

Intravesical chemotherapy is highly recommended after transurethral resection of bladder tumor for patients with bladder cancer (BCa). However, this localized adjuvant therapy has drawbacks of causing indiscriminate damage and inability to penetrate bladder mucosal. Fluorinated polylysine micelles (PLLF) were synthesized by reacting polylysine (PLL) with heptafluorobutyrate anhydride. Anti-apoptotic gene defender against cell death 1 (DAD1) was selected by different gene expression analysis between BCa patients and healthy individuals and identified by several biological function assays. The gene transfection ability of PLLF was verified by multiple and assays. The therapeutic efficiency of PLLF nanoparticles (NPs) targeting DAD1 were confirmed by intravesical administration using an orthotopic BCa mouse model. Decorated with fluorinated chains, PLL can self-assemble to form NPs and condense plasmids with excellent gene transfection efficiency . Loading with the CRISPR-Cas9 system designed to target DAD1 (Cas9-sgDAD1), PLLF/Cas9-sgDAD1 NPs strongly inhibited the expression of DAD1 in BCa cells and induced BCa cell apoptosis through the MAPK signaling pathway. Furthermore, intravesical administration of PLLF/Cas9-sgDAD1 NPs resulted in significant therapeutic outcomes without systemic toxicity . The synthetized PLLF can transmucosally deliver the CRISPR-Cas9 system into orthotopic BCa tissues to improve intravesical instillation therapy for BCa. This work presents a new strategy for targeting DAD1 gene in the intravesical therapy for BCa with high potential for clinical applications.

The gut microbiome has been established as a key environmental factor to health. Genetic influences on the gut microbiome have been reported, yet, doubts remain as to the significance of genetic associations. Here, we provide shotgun data for whole genome and whole metagenome from a Chinese cohort, identifying no less than 20% genetic contribution to the gut microbiota. Using common variants-, rare variants- and copy number variations (CNVs)-based association analyses, we identified abundant signals associated with the gut microbiome especially in metabolic, neurological and immunological functions. The controversial concept of enterotypes may have a genetic attribute, with the top 2 loci explaining 11% of the Prevotella-Bacteroides variances. Stratification according to gender led to the identification of differential associations in males and females. Genetically encoded responses to ectopic presence of oral bacteria in the gut appear to be a common theme in a number of diseases investigated by MWAS (Metagenome-wide association studies). Our two-stage M-GWAS (Microbiome genome-wide association studies) on a total of 1295 individuals unequivocally illustrates that neither microbiome nor GWAS studies could overlook one another in our quest for a better understanding of human health and diseases.