Evidence map›Paper›PMID 38997411›Full record

ArticleScientific reports2024

Immune cell landscapes are associated with high-grade serous ovarian cancer survival.

Guoan Zhang, Yan Zhang, Jingjing Zhang, Xiaohui Yang, Wenjie Sun, Ying Liu, Yingfu Liu

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. 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

7 authors.

Guoan Zhang *Science and Technology Experiment Center, Cangzhou Medical College, Cangzhou, 061001, People's Republic of China.
Yan Zhang *Science and Technology Experiment Center, Cangzhou Medical College, Cangzhou, 061001, People's Republic of China.
Jingjing ZhangScience and Technology Experiment Center, Cangzhou Medical College, Cangzhou, 061001, People's Republic of China.
Xiaohui YangCangzhou Nanobody Technology Innovation Center, Cangzhou Medical College, Cangzhou, 061001, People's Republic of China.
Wenjie SunUniversity Nanobody Application Technology Research and Development Center of Hebei Provice, Cangzhou, 061001, People's Republic of China.
Ying LiuScience and Technology Experiment Center, Cangzhou Medical College, Cangzhou, 061001, People's Republic of China. 76275567@qq.com.
Yingfu LiuCangzhou Nanobody Technology Innovation Center, Cangzhou Medical College, Cangzhou, 061001, People's Republic of China. liu_yingfu@126.com.

Funding

Key Research and Development Projects of Hebei Province, China 19272404D
6 · The paper itself

Abstract

High-grade serous ovarian cancer (HGSOC) is an aggressive disease known to develop resistance to chemotherapy. We investigated the prognostic significance of tumor cell states and potential mechanisms underlying chemotherapy resistance in HGSOC. Transcriptome deconvolution was performed to address cellular heterogeneity. Kaplan-Meier survival curves were plotted to illustrate the outcomes of patients with varying cellular abundances. The association between gene expression and chemotherapy response was tested. After adjusting for surgery status and grading, several cell states exhibited a significant correlation with patient survival. Cell states can organize into carcinoma ecotypes (CE). CE9 and CE10 were proinflammatory, characterized by higher immunoreactivity, and were associated with favorable survival outcomes. Ratios of cell states and ecotypes had better prognostic abilities than a single cell state or ecotype. A total of 1265 differentially expressed genes were identified between samples with high and low levels of C9 or CE10. These genes were partitioned into three co-expressed modules, which were associated with tumor cells and immune cells. Pogz was identified to be linked with immune cell genes and the chemotherapy response of paclitaxel. Collectively, the survival of HGSOC patients is correlated with specific cell states and ecotypes.

Indexed as

Cystadenocarcinoma, SerousOvarian NeoplasmsAgedDrug Resistance, NeoplasmFemaleGene Expression Regulation, NeoplasticHumansKaplan-Meier EstimateMiddle AgedNeoplasm GradingPrognosisTranscriptomeCell ratiosHigh-grade serous ovarian cancerMacrophageOverall survivalT cell activation

Identifiers

PMID38997411
PMCPMC11245545

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.