ArticleDiscover oncology2024
IGSF1: a biomarker for predicting prognosis, immunotherapy response, and drug candidates in COVID-19 combined hepatocellular carcinoma.
Article in Discover 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.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Hepatocellular carcinoma (HCC) is a highly heterogeneous malignancy with poor prognosis and a common cause of cancer-related death worldwide, and despite ongoing therapeutic breakthroughs, patient survival benefits are limited. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of coronavirus disease 2019 (COVID-19) and poses a major threat to humanity worldwide. As the epidemic continues to develop, more and more people are infected with SARS-CoV-2, including patients with HCC. However, the relationship between COVID-19 and HCC has not yet been fully elucidated. Our study aimed to identify the shared genetic characteristics and molecular mechanisms between COVID-19 and HCC. The data involved in this study come from Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression(GTEx), and Cancer Cell Line Encyclopedia(CCLE) databases. We used differentially expressed genes to perform enrichment analysis to reveal the biological landscape of COVID-19 combined with HCC. In addition, weighted gene co-expression network analysis (WGCNA) was used to study the co-expression network related to COVID-19 and HCC. We then combined the validation datasets to screen out immunoglobulin superfamily member 1 (IGSF1) as the most important core gene. Finally, we extensively studied the functional expression of IGSF1 in tumor samples, normal tissues, and cancer cell lines. The molecular mechanisms related to COVID-19 and HCC are rarely studied. Our study identifies IGSF1 as a potential therapeutic target and immune-related biomarker for patients with COVID-19 and HCC.
Indexed as
Identifiers
What Socratic holds
Registered trials
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 Socratic graph.