Evidence map›Paper›PMID 34956426›Full record

ArticleThe EPMA journal2021

Integrated genomic analysis of proteasome alterations across 11,057 patients with 33 cancer types: clinically relevant outcomes in framework of 3P medicine.

Na Li, Xianquan Zhan

Open access · greenAbstract read
In one paragraph

Article in The EPMA journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
0.7field-weighted citation impact, top 31% 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

11 citing papers in PubMed, 15 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. 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

2 authors at 1 institution in 1 country.

Na LiShandong Key Laboratory of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University, 440 Jiyan Road, Jinan, Shandong 250117 People's Republic of China.
Xianquan ZhanShandong Key Laboratory of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University, 440 Jiyan Road, Jinan, Shandong 250117 People's Republic of China.ORCID 0000-0002-4984-3549
Shandong Tumor Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

relevanceProteasome, a cylindrical complex containing 19S regulatory particle lid, 19S regulatory particle base, and 20S core particle, acted as a major mechanism to regulate the levels of intracellular proteins and degrade misfolded proteins, which involved in many cellular processes, and played important roles in cancer biological processes. Elucidation of proteasome alterations across multiple cancer types will directly contribute to cancer medical services in the context of predictive, preventive, and personalized medicine (PPPM / 3P medicine). PURPOSE: This study aimed to investigate proteasome gene alterations across 33 cancer types for discovery of effective biomarkers and therapeutic targets in the framework of PPPM practice in cancers.

methodsProteasome gene data, including gene expression RNAseq, somatic mutation, tumor mutation burden (TMB), copy number variant (CNV), microsatellite instability (MSI) score, clinical characteristics, immune phenotype, 22 immune cells, cancer stemness index, drug sensitivity, and related pathways, were systematically analyzed with publically available database and bioinformatics across 11,057 patients with 33 cancer types.

resultsDifferentially expressed proteasome genes were extensively found between tumor and control tissues. PSMB4 occurred the top mutation event among proteasome genes, and those proteasome genes were significantly associated with TMB and MSI score. Most of proteasome genes were positively related to CNV among single deletion, control copy number, and single gain. Kaplan-Meier curves and COX regression survival analysis showed proteasome genes were significantly associated with patient survival rate across 33 cancer types. Furthermore, the expressions of proteasome genes were significantly different among different clinical stages and immune subtypes. The expressions of proteasome genes were correlated with immune-related scores (ImmuneScore, StromalScore, and ESTIMATEScore), 22 immune cells, and cancer stemness. The sensitivities of multiple drugs were closely related to proteasome gene expressions. The identified proteasome and proteasome-interacted proteins were significantly enriched in various cancer-related pathways.

conclusionsThis study provided the first landscape of proteasome alterations across 11,057 patients with 33 cancer types and revealed that proteasome played a significant and wide functional role in cancer biological processes. These findings are the precious scientific data to reveal the common and specific alterations of proteasome genes among 33 cancer types, which benefits the research and practice of PPPM in cancers. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13167-021-00256-z.

Indexed as

BiomarkerDrug sensitivityImmuneMutationPan-cancerPredictive preventive personalized medicine (PPPM / 3P medicine)ProteasomeRelated pathwaysStemnessTherapeutic targets

Identifiers

PMID34956426
PMCPMC8648926
OpenAlexW3203404607

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.