Evidence map›Paper›PMID 36731460›Full record

ArticleCancer research and treatment2023

Genomic and Transcriptomic Characterization Revealed the High Sensitivity of Targeted Therapy and Immunotherapy in a Subset of Endometrial Stromal Sarcoma.

Nan Kang, Yinli Zhang, Shichao Guo, Ran Chen, Fangzhou Kong, Shuchun Wang, Mingming Yuan, Rongrong Chen, Danhua Shen, Jianliu Wang

Abstract read
In one paragraph

Article in Cancer research and treatment, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
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

11 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Review
  5. Review
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Single-cell RNA-seq revealsFrontiers in immunology · 2024
    Article
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

10 authors.

Nan KangDepartment of Pathology, Peking University People's Hospital, Beijing, China.
Yinli ZhangDepartment of Pathology, Peking University People's Hospital, Beijing, China.
Shichao GuoState Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Ran ChenDepartment of Pathology, Peking University People's Hospital, Beijing, China.
Fangzhou KongDepartment of Pathology, Peking University People's Hospital, Beijing, China.
Shuchun WangGeneplus-Beijing, Beijing, China.
Mingming YuanGeneplus-Beijing, Beijing, China.
Rongrong ChenGeneplus-Beijing, Beijing, China.
Danhua ShenDepartment of Pathology, Peking University People's Hospital, Beijing, China.
Jianliu WangDepartment of Obstetrics and Gynecology, Peking University People's Hospital, Beijing, China.

Funding

Key Technologies Research and Development Program 2019YFC1005200Key Technologies Research and Development Program 2019YFC1005201Key Technologies Research and Development Program 2019YFC1005204National Natural Science Foundation of China 81874108Peking University People's Hospital RDJP2022-25
6 · The paper itself

Abstract

purposeThe unique chromosomal rearrangements of endometrial stromal sarcoma (ESS) make it possible to distinguish high-grade ESS (HGESS) and low-grade ESS (LGESS) from the molecular perspective. Analysis of ESS at the genomic and transcriptomic levels can help us achieve accurate diagnosis of ESS and provide potential therapy options for ESS patients. Materials and Methods: A total of 36 ESS patients who conducted DNA- and/or RNA-based next-generation sequencing were retrospectively enrolled in this study. The molecular characteristics of ESS at genomic and transcriptomic levels, including mutational spectrum, fusion profiles, gene expression and pathway enrichment analysis and features about immune microenvironment were comprehensively explored.

resultsTP53 and DNMT3A mutations were the most frequent mutations. The classical fusions frequently found in HGESS (ZC3H7B-BCOR and NUTM2B-YWHAE) and LGESS (JAZF1-SUZ12) were detected in our cohort. CCND1 was significantly up-regulated in HGESS, while the expression of GPER1 and PGR encoding estrogen receptor (ER) and progesterone receptor (PR) did not differ significantly between HGESS and LGESS. Actionable mutations enriched in homologous recombination repair, cell cycle, and phosphoinositide 3-kinase/AKT/mammalian target of rapamycin pathways were detected in 60% of HGESS patients. Genes with up-regulated expression in HGESS were significantly enriched in five immune-related pathways. Most HGESS patients (85.7%) had positive predictors of immunotherapy efficacy. Moreover, immune microenvironment analysis showed that HGESS had relatively high immune infiltration. The degree of immune infiltration in HGESS patients with ZC3H7B-BCOR fusion was relatively higher than that of those with NUTM2B-YWHAE fusion.

conclusionThis study investigated the molecular characteristics of ESS patients at the genomic and transcriptomic levels and revealed the potentially high sensitivity of targeted therapy and immunotherapy in a subset of HGESS with specific molecular features, providing a basis for guiding decision-making of treatment and the design of future clinical trials on precision therapy.

Indexed as

Endometrial NeoplasmsSarcoma, Endometrial StromalFemaleGenomicsHumansImmunotherapyPhosphatidylinositol 3-KinasesRetrospective StudiesTranscription FactorsTranscriptomeTumor MicroenvironmentPhosphatidylinositol 3-KinasesTranscription FactorsDNA-based panel sequencingHigh-grade endometrial stromal sarcomaImmunotherapyTargeted therapyWhole transcriptome sequencing

Identifiers

PMID36731460
PMCPMC10372608

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.