Evidence map›Paper›PMID 37277784›Full record

ArticleBMC medical genomics2023

Single-cell RNA sequencing reveals sexual diversity in the human bladder and its prospective impacts on bladder cancer and urinary tract infection.

Ribao Wu, Xiahong Teng, Qiong Song, Shuai Chen, Lihui Wang, Jinling Liao, Chunlin Zou

Open access · goldAbstract read
In one paragraph

Article in BMC medical genomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.2field-weighted citation impact, top 21% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 8 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Ribao WuCenter for Translational Medicine, Key Laboratory of Longevity and Aging-related Diseases of Chinese Ministry of Education, Institute of Neuroscience and Guangxi Key Laboratory of Brain Science, School of Basic Medical Sciences, Guangxi Medical University, Nanning, Guangxi, China.
Xiahong TengSchool of International Education, Guangxi Medical University, Nanning, Guangxi, China.
Qiong SongCenter for Translational Medicine, Key Laboratory of Longevity and Aging-related Diseases of Chinese Ministry of Education, Institute of Neuroscience and Guangxi Key Laboratory of Brain Science, School of Basic Medical Sciences, Guangxi Medical University, Nanning, Guangxi, China.
Shuai ChenCenter for Translational Medicine, Key Laboratory of Longevity and Aging-related Diseases of Chinese Ministry of Education, Institute of Neuroscience and Guangxi Key Laboratory of Brain Science, School of Basic Medical Sciences, Guangxi Medical University, Nanning, Guangxi, China.
Lihui WangCenter for Translational Medicine, Key Laboratory of Longevity and Aging-related Diseases of Chinese Ministry of Education, Institute of Neuroscience and Guangxi Key Laboratory of Brain Science, School of Basic Medical Sciences, Guangxi Medical University, Nanning, Guangxi, China.
Jinling LiaoCenter for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China.
Chunlin ZouCenter for Translational Medicine, Key Laboratory of Longevity and Aging-related Diseases of Chinese Ministry of Education, Institute of Neuroscience and Guangxi Key Laboratory of Brain Science, School of Basic Medical Sciences, Guangxi Medical University, Nanning, Guangxi, China. zouchunlin@sohu.com.
Guangxi Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSome bladder-related diseases, such as bladder urinary tract infection (UTI) and bladder cancer (BCa), have significant six differences in incidence and prognosis. However, the molecular mechanisms underlying these sex differences are still not fully understood. Understanding the sex-biased differences in gene expression in normal bladder cells can help resolve these problems.

methodsWe first collected published single-cell RNA sequencing (scRNA-seq) data of normal human bladders from females and males to map the bladder transcriptomic landscape. Then, Gene Ontology (GO) analysis and gene set enrichment analysis (GSEA) were used to determine the significant pathways that changed in the specific cell populations. The Monocle2 package was performed to reconstruct the differentiation trajectories of fibroblasts. In addition, the scMetabolism package was used to analyze the metabolic activity at the single-cell level, and the SCENIC package was used to analyze the regulatory network.

resultsIn total, 27,437 cells passed stringent quality control, and eight main cell types in human bladder were identified according to classical markers. Sex-based differential gene expression profiles were mainly observed in human bladder urothelial cells, fibroblasts, B cells, and T cells. We found that urothelial cells in males demonstrated a higher growth rate. Moreover, female fibroblasts produced more extracellular matrix, including seven collagen genes that may mediate BCa progression. Furthermore, the results showed that B cells in female bladders exhibited more B-cell activated signals and a higher expression of immunoglobulin genes. We also found that T cells in female bladders exhibited more T-cell activated signals. These different biological functions and properties of these cell populations may correlate with sex differences in UTI and BCa, and result in different disease processes and outcomes.

conclusionsOur study provides reasonable insights for further studies of sex-based physiological and pathological disparities in the human bladder, which will contribute to the understanding of epidemiological differences in UTI and BCa.

Indexed as

Urinary BladderUrinary Bladder NeoplasmsUrinary Tract InfectionsGene Expression RegulationHumansProspective StudiesSequence Analysis, RNASingle-Cell AnalysisBladder cancerExtracellular matrixScRNA-seqSex-based differential geneUrinary tract infection

Identifiers

PMID37277784
PMCPMC10242993
OpenAlexW4379469504

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.