Evidence map›Paper›PMID 41674942›Full record

ArticleTranslational cancer research2026

Integrated single-cell and transcriptomic analysis of CD8

Feifeng Ran, Zhang Jiang, Lilin Que, Lan Luo, Li Liang, Mei Gan, Rensheng Wang, Leifeng Liang

Abstract read
In one paragraph

Article in Translational cancer research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

8 authors.

Feifeng Ran *Department of Radiation Oncology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.ORCID https://orcid.org/0000-0002-6655-6373
Zhang Jiang *Department of Plastic Surgery, The Sixth Affiliated Hospital of Guangxi Medical University, Nanning, China.
Lilin QueDepartment of Radiation Oncology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
Lan LuoDepartment of Oncology, The Sixth Affiliated Hospital of Guangxi Medical University, The First People's Hospital of Yulin, Yulin, China.
Li LiangDepartment of Oncology, The Sixth Affiliated Hospital of Guangxi Medical University, The First People's Hospital of Yulin, Yulin, China.
Mei GanDepartment of Oncology, The Sixth Affiliated Hospital of Guangxi Medical University, The First People's Hospital of Yulin, Yulin, China.
Rensheng WangDepartment of Radiation Oncology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.ORCID https://orcid.org/0000-0002-0768-9344
Leifeng LiangDepartment of Oncology, The Sixth Affiliated Hospital of Guangxi Medical University, The First People's Hospital of Yulin, Yulin, China.ORCID https://orcid.org/0000-0003-1935-4100

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Hepatocellular carcinoma (HCC) ranks as a leading global cause of cancer-related mortality. Our study investigates the functional role between CD8 Methods: We utilized single-cell RNA sequencing (scRNA-seq) to delineate the transcriptional landscapes and intercellular crosstalk of CCT and CD8 Results: Our results indicated that T cell re-clustering revealed four functionally distinct subsets: CD8 Conclusions: Our findings elucidate the functional alterations of CCT and precursor cells within the context of HCC. The novel prognostic framework provides actionable insights for stratifying patients likely to benefit from combinatorial immunotherapy and chemotherapy.

Indexed as

CD8+CD101+TIM3+ T cellsHepatocellular carcinoma (HCC)prognosissingle-cell RNA-sequencing (scRNA-seq)tumor microenvironment (TME)

Identifiers

PMID41674942
PMCPMC12885813

What OpenQuestion holds

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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.