Evidence map›Paper›PMID 38948919›Full record

ArticleMolecular therapy. Oncology2024

Prognostic insights, immune infiltration, and therapeutic response: Cytoplasmic poly(A) tail regulators in hepatocellular carcinoma.

Yi Liu, Yan Huang, Yunting Le, Yating Gao, Hui Wang, Jing Yang, Jialin Wang, Chaoxia Zou, Qiang Li

Abstract read
In one paragraph

Article in Molecular therapy. Oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Yi LiuDepartment of Biochemistry and Molecular Biology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Yan HuangDepartment of Neurobiology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Yunting LeDepartment of Biochemistry and Molecular Biology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Yating GaoDepartment of Biochemistry and Molecular Biology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Hui WangDepartment of Biochemistry and Molecular Biology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Jing YangDepartment of Biochemistry and Molecular Biology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Jialin WangDepartment of Biochemistry and Molecular Biology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Chaoxia ZouDepartment of Biochemistry and Molecular Biology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Qiang LiDepartment of General Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang 150081, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The presence of a poly(A) tail is indispensable for the post-transcriptional regulation of gene expression in cancer. This dynamic and modifiable feature of transcripts is under the control of various nuclear and cytoplasmic proteins. This study aimed to develop a novel cytoplasmic poly(A)-related signature for predicting prognosis, clinical attributes, tumor immune microenvironment (TIME), and treatment response in hepatocellular carcinoma (HCC). Utilizing RNA sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA), non-negative matrix factorization (NMF), and principal-component analysis (PCA) were employed to categorize HCC patients into three clusters, thus demonstrating the pivotal prognostic role of cytoplasmic poly(A) tail regulators. Furthermore, machine learning algorithms such as least absolute shrinkage and selection operator (LASSO), survival analysis, and Cox proportional hazards modeling were able to distinguish distinct cytoplasmic poly(A) subtypes. As a result, a 5-gene signature derived from TCGA was developed and validated using International Cancer Genome Consortium (ICGC) HCC datasets. This novel classification based on cytoplasmic poly(A) regulators has the potential to improve prognostic predictions and provide guidance for chemotherapy, immunotherapy, and transarterial chemoembolization (TACE) in HCC.

Indexed as

bioinformaticshepatocellular carcinomaMT: Regular Issuepoly(A) tailprognostic signaturetumor immune microenvironment

Identifiers

PMID38948919
PMCPMC11214399

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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.