Evidence map›Paper›PMID 38333684›Full record

ArticleFrontiers in oncology2024

In-depth analysis of immune cell landscapes reveals differences between lung adenocarcinoma and lung squamous cell carcinoma.

Xinfeng Wang, Keao Zheng, Zhiying Hao

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.5field-weighted citation impact, top 11% 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

4 citing papers in PubMed, 6 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

3 authors at 1 institution in 1 country.

Xinfeng WangDepartment of Pharmacy, Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, Shanxi, China.
Keao ZhengDepartment of Pharmacy, Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, Shanxi, China.
Zhiying HaoDepartment of Pharmacy, Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, Shanxi, China.
Shanxi Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Lung cancer is the leading cause of cancer deaths globally, with lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) being major subtypes. Immunotherapy has emerged as a promising approach for the treatment of lung cancer, but understanding the underlying mechanisms of immune dysregulation is crucial for the development of effective therapies. This study aimed to investigate the distinctive cellular features of LUAD and LUSC and identify potential biomarkers associated with the pathogenesis and clinical outcomes of each subtype. Methods: We used digital cytometry techniques to analyze the RNA-Seq data of 1128 lung cancer patients from The Cancer Genome Atlas (TCGA) database. The abundance of cell subtypes and ecotypes in LUAD and LUSC patients was quantified. Univariate survival analysis was used to investigate their associations with patient overall survival (OS). Differential gene expression analysis and gene co-expression network construction were carried out to explore the gene expression patterns of LUSC patients with distinct survival outcomes. Scratch wound-healing assay, colony formation assay, and transwell assay were used to validate the candidate drugs for LUSC treatment. Results: We found differential expression of cell subtypes between LUAD and LUSC, with certain cell subtypes being prognostic for survival in both subtypes. We also identified differential gene expression and gene co-expression modules associated with macrophages.3/PCs.2 ratio in LUSC patients with distinct survival outcomes. Furthermore, ecotype ratios were found to be prognostic in both subtypes and machine learning models showed that certain cell subtypes, such as epithelial.cells.1, epithelial.cells.5, and endothelial.cells.2 are important for predicting LUSC. Ginkgolide B and triamterene can inhibit the proliferation, invasion, and migration of LUSC cell lines. Conclusion: We provide insight into the distinctive cellular features of LUAD and LUSC, and identify potential biomarkers associated with the pathogenesis and clinical outcomes of each subtype. Ginkgolide B and triamterene could be promising drugs for LUSC treatment.

Indexed as

biomarkersdigital cytometrylung adenocarcinomamachine learningsquamous cell carcinoma

Identifiers

PMID38333684
PMCPMC10850392
OpenAlexW4391227943

What OpenQuestion holds

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LicenceCC BY
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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.