Evidence map›Paper›PMID 39397204›Full record

ArticleDiscover oncology2024

Identified a novel prognostic model of HCC basing on virus signature for guiding immunotherapy.

Shizhuan Huang, Dehai Wu, Guanqun Liao, Ming Liang, Yaohui Zhang, Haotian Wu, Daowei Tang, Dixiang Wen, Bo Jiang, Shan Yu and 1 more

Abstract read
In one paragraph

Article in Discover oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

11 authors.

Shizhuan Huang *Department of Hepatic Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, China.
Dehai Wu *Department of Hepatic Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, China.
Guanqun LiaoDepartment of Hepatobiliary Surgery, Foshan Hospital Affiliated to Southern Medical University, Foshan, China.
Ming LiangDepartment of Infectious Diseases, Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, China.
Yaohui ZhangDepartment of Hepatic Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, China.
Haotian WuDepartment of Hepatic Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, China.
Daowei TangDepartment of Hepatic Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, China.
Dixiang WenDepartment of Hepatic Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, China.
Bo JiangDepartment of Hepatic Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, China.
Shan YuDepartment of Pathology, Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, China. Yushan@hrbmu.edu.cn.
Sheng TaiDepartment of Hepatic Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, China. taisheng1973@163.com.

Funding

Medical Scientific Research Foundation of Guangdong Province of China 2020,A2020439The Cancer Research Foundation of CSCO-Moshadong (Y-MSDPU2022-0862)the Natural Science Foundation of China 81972724The Natural Science Foundation of Guangdong Province 2020,2020A1515110097The postdoctor of Heilongjiang Province of China 21042220024
6 · The paper itself

Abstract

Oncolytic viral immunotherapy is a cancer treatment that uses native or genetically modified viruses that selectively replicate and destroy tumor cells. In this study, we aimed to construct a virus-based prognostic model for risk assessment and prognosis prediction in patients with hepatocellular carcinoma (HCC) and determine the most appropriate virus as a candidate vector for oncolytic virus immunotherapy. Microbiome and RNA sequencing data and clinical information were obtained from The Cancer Genome Atlas, and viruses with prognostic value were identified (Deltabaculovirus, Sicinivirus, and Cytomegalovirus) to construct the prognostic model. Correlation analyses were performed to evaluate the predictive function of the viral signature. Bioinformatics analyses were conducted to explore the functional enrichment of viral expression in HCC. The risk score generated by this model could distinguish patients with different survival outcomes, have excellent reliability and accuracy, and could be used as an independent prognostic indicator. The high-risk score group showed significantly lower overall survival, and this trend was also observed in subgroups with different clinicopathological features. Furthermore, Deltabaculovirus positively correlated with amino acid metabolism, energy metabolism signaling pathways, peroxisomes, and complement coagulation cascades. In addition, Deltabaculovirus was significantly related to immune cell infiltration; therefore, patients with high Delta-baculovirus expression might respond better to HCC immunotherapy. Our study identified a promising predictive viral signature for assessing clinical prognosis and guiding immunotherapy in HCC. Deltabaculovirus might be a suitable viral vector for oncolytic virus immunotherapy.

Indexed as

Hepatocellular carcinomaImmune infiltrationMetabolismPrognosisViruses

Identifiers

PMID39397204
PMCPMC11471745

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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.