ArticleJournal of cancer research and clinical oncology2023
Development and validation of a ubiquitin-proteasome system gene signature for prognostic prediction and immune microenvironment evaluation in hepatocellular carcinoma.
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.
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
2 citing papers in PubMed, 3 citations in OpenAlex.
- Pro-tumourigenic effects of DCAF13 on the progression of colorectal cancer.Oncology letters · 2026Article
- Establishment of a prognosis predictive model for liver cancer based on expression of genes involved in the ubiquitin-proteasome pathway.World journal of clinical oncology · 2024Article
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 at 4 institutions in 1 country.
Funding
Abstract
backgroundThe ubiquitin proteasome has a major role in the development of many tumors. However, the prognostic importance of ubiquitin proteasome-system genes (UPSGs) in hepatocellular carcinoma (HCC) is not fully defined.
methodsThe TCGA and ICGC datasets were utilized to obtain transcriptional profiling data as well as clinicopathological information about HCC. The 3-UPSGs signature for the TCGA cohort was developed via univariate and LASSO Cox regression analyses. Differential expression of genes was demonstrated by qRT-PCR and immunohistochemistry (IHC). Biological pathways were studied using GSVA and GSEA. Six algorithms were used to compare immune infiltration between the two risk groups. Furthermore, drug sensitivity was measured using the "pRRophetic" R package. The predictive capacity of the 3-UPSGs signature for sensitivity to immunotherapy was also explored. Moreover, we performed a pan-cancer analysis of the 3-UPSGs signature.
resultsA risk model containing 3 UPSGs (DCAF13, CDC20 and PSMB5) was developed. IHC and qRT-PCR results showed that signature genes were significantly overexpressed in HCC tissues. The high-risk group had a worse prognosis, with a higher clinicopathological grade, higher levels of tumor mutation burden (TMB), elevated levels of immune checkpoint (IC) expression, as well as increased sensitivity to immunotherapy. The two risk groups also differ in their sensitivity to chemotherapeutic drugs. Furthermore, the three UPSGs may play crucial roles in the progression of multiple types of cancers.
conclusionWe created a 3-UPSGs signature to estimate the prognosis of HCC and to assist in individualized treatment.
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.