Evidence map›Paper›PMID 36544679›Full record

ArticleAnnals of translational medicine2022

Multi-omics profiling identifies C1QA/B

Fei Zheng, Wei Zhang, Baihua Yang, Mingqiu Chen

Open access · diamondAbstract read
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Article in Annals of translational medicine, 2022. 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
0.6field-weighted citation impact, top 35% 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, 7 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

4 authors at 2 institutions in 1 country.

Fei ZhengDepartment of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.
Wei ZhangDepartment of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.
Baihua YangDepartment of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.
Mingqiu ChenDepartment of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.
Fujian Medical University · CNFujian Provincial Cancer Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Esophageal squamous cell carcinoma (ESCC) is a highly lethal malignant tumor lacking effective treatments; 20% of ESCC patients develop liver metastasis with an extremely short survival time of ≈5 months. The tumor microenvironment (TME) plays a crucial role in tumor homeostasis, but the relationship between the ESCC TME and liver metastasis is still unknown. Methods: To identify potential cell populations contributing to ESCC liver metastasis, single-cell RNA (scRNA) sequencing data were analyzed to identify the major cell populations within the TME. Each of the major cell populations was re-clustered to define detailed cell subsets. Thereafter, the gene set variation analysis (GSVA) score was calculated for the bulk RNA-seq data based on the gene signatures of each cell subset. The relationship between the GSVA score of each cellular subset and clinical outcome was further analyzed to identify the cellular subset associated with ESCC liver metastasis, which was validated by multiplex immunohistochemistry. Results: C1QA/B Conclusions: Our results comprehensively revealed the landscape of tumor-infiltrating immune cells associated with ESCC prognosis and metastasis, and suggest a novel strategy for developing immunotherapies for ESCC liver metastasis by targeting C1QA/B

Indexed as

C1QA/B+ tumor-associated macrophages (C1QA/B+ TAMs)Esophageal squamous cell carcinoma (ESCC)multi-omics profiling

Identifiers

PMID36544679
PMCPMC9761157
OpenAlexW4310220267

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.