Evidence map›Paper›PMID 35223867›Full record

ArticleFrontiers in cell and developmental biology2021

Multi-Omics Characterization of Tumor Microenvironment Heterogeneity and Immunotherapy Resistance Through Cell States-Based Subtyping in Bladder Cancer.

Rixin Hu, Tao Tao, Lu Yu, Qiuxia Ding, Guanghui Zhu, Guoyu Peng, Shiwen Zheng, Leyun Yang, Song Wu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in cell and developmental biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 22% 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, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Review
  4. Review
  5. Review
  6. Review
  7. Review
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

9 authors at 4 institutions in 1 country.

Rixin HuHealth Science Center, School of Basic Medical Sciences, Shenzhen University, Shenzhen, China.
Tao TaoDepartment of Urology, The Affiliated Luohu Hospital of Shenzhen University, Shenzhen University, Shenzhen, China.
Lu YuDepartment of Urology, The Affiliated Luohu Hospital of Shenzhen University, Shenzhen University, Shenzhen, China.
Qiuxia DingDepartment of Urology, The Affiliated Luohu Hospital of Shenzhen University, Shenzhen University, Shenzhen, China.
Guanghui ZhuDepartment of Urology, The Affiliated Luohu Hospital of Shenzhen University, Shenzhen University, Shenzhen, China.
Guoyu PengDepartment of Urology, The Affiliated Luohu Hospital of Shenzhen University, Shenzhen University, Shenzhen, China.
Shiwen ZhengDepartment of Urology, The Affiliated Luohu Hospital of Shenzhen University, Shenzhen University, Shenzhen, China.
Leyun YangDepartment of Urology, The Affiliated Luohu Hospital of Shenzhen University, Shenzhen University, Shenzhen, China.
Song WuHealth Science Center, School of Basic Medical Sciences, Shenzhen University, Shenzhen, China.
Shenzhen University · CNShenzhen Luohu People's Hospital · CNShantou University Medical College · CNShenzhen University Health Science Center · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

bladder cancercell statesheterogeneityimmunotherapy resistancemulti-omicsprognosissubtypetumor microenvironment

Identifiers

PMID35223867
PMCPMC8864284
OpenAlexW4210844071

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.