Evidence map›Paper›PMID 37903936›Full record

ArticleJournal of cancer research and clinical oncology2023

Establishment and validation of a novel lysosome-related gene signature for predicting prognosis and immune landscape in hepatocellular carcinoma.

Haoling Li, Jing Li, Xiangyu Qu, Hengwen Dai, Junjie Liu, Mengxi Ma, Jian Wang, Wei Dong, Wenrui Wang

Open access · greenAbstract read
In one paragraph

Article in Journal of cancer research and clinical oncology, 2023. 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
1.3field-weighted citation impact, top 18% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  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

9 authors at 3 institutions in 1 country.

Haoling Li *Anhui Province Key Laboratory of Translational Cancer Research, Bengbu Medical College, Anhui, 233030, China.
Jing Li *Department of Pharmacy, Shanghai Pudong New Area People's Hospital, Shanghai, 201299, China.
Xiangyu QuDepartment of Clinical Medicine, Bengbu Medical College, Anhui, 233030, China.
Hengwen DaiDepartment of Clinical Medicine, Bengbu Medical College, Anhui, 233030, China.
Junjie LiuDepartment of Clinical Medicine, Bengbu Medical College, Anhui, 233030, China.
Mengxi MaDepartment of Clinical Medicine, Bengbu Medical College, Anhui, 233030, China.
Jian WangDepartment of Pharmacy, Shanghai Pudong New Area People's Hospital, Shanghai, 201299, China. wangjian@shpdph.com.
Wei DongDepartment of Hepatic Surgery, The Eastern Hepatobiliary Surgery Hospital, Naval Medical University, Shanghai, 200438, China. weirdong@sina.com.
Wenrui WangAnhui Province Key Laboratory of Translational Cancer Research, Bengbu Medical College, Anhui, 233030, China. wenrui-wang1983@163.com.
Bengbu Medical College · CNPudong New Area People's Hospital · CNSecond Military Medical University · CN

Funding

the 512 Talent Cultivation Program of Bengbu Medical College 51201206the Shanghai Pudong New Area Health Commission PW2022A-43Youth program of National Natural Science Foundation of China 82000483
6 · The paper itself

Abstract

backgroundRecent studies have shown that lysosomes not only provide energy for tumor cell growth, but also participate in the occurrence and development of malignant tumors by regulating various ways of tumor cell death. However, the role of lysosome associated genes (LSAGs) in hepatocellular carcinoma (HCC) remains unclear.

methodsTranscriptome data and clinical data of HCC were downloaded from the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) databases. We identified differential expression of LSAGs by comparing tumor tissue with normal liver tissue. Subsequently, we used univariate COX analysis and least absolute shrinkage and selection operator (LASSO) COX regression to construct the prognostic feature of LSAGs. Kaplan-Meier survival curve and receiver operating characteristic curve were used to evaluate the predictive ability of LSAGs feature. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used for functional enrichment analysis of risk differential genes. The relationship between LSAGs score and tumor microenvironment and chemotherapy drug sensitivity was analyzed. Finally, the cellular communication of tumor cells with high and low expression of model LSAGs was explored.

resultsWe identified sixteen prognostic associated LSAGs, four of which were selected to construct prognostic feature of LSAGs. Patients in the low LSAGs group had a better prognosis than those in the high LSAGs group. GO and KEGG analyses showed that risk differential genes were enriched in leukocyte migration, cytokine-cytokine receptor interaction and PI3K-Akt signaling pathway. The group with low LSAGs score had lower immune score. Patients in the high LSAGs group were more sensitive to drugs for chemotherapy. In addition, tumor cells with high expression of model LSAGs showed stronger association with immune cells through the interleukin-2 (IL2), fibroblast growth factor (FGF), adiponectin, and bone morphogenetic proteins (BMP) signaling pathways.

conclusionWe established a LSAGs signature that had the ability to predict clinical prognosis and immune landscape, proposing potential therapeutic targets for HCC.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsHumansLysosomesPhosphatidylinositol 3-KinasesPrognosisTumor MicroenvironmentPhosphatidylinositol 3-KinasesHepatocellular carcinomaLysosomePrognostic modelSingle-cell sequencing analysisTumor microenvironment

Identifiers

PMID37903936
PMCPMC11797982
OpenAlexW4388034423

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.