Evidence map›Paper›PMID 35484177›Full record

ArticleScientific reports2022

Identification and validation of prognosis-associated DNA repair gene signatures in colorectal cancer.

Dingli Song, Dai Zhang, Sisi Chen, Jie Wu, Qian Hao, Lili Zhao, Hong Ren, Ning Du

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.3field-weighted citation impact, top 11% 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

10 citing papers in PubMed, 17 citations in OpenAlex.

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

8 authors at 2 institutions in 1 country.

Dingli Song *Department of Thoracic Surgery, The First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China.
Dai Zhang *Department of Oncology, The Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China.
Sisi ChenDepartment of Thoracic Surgery, The First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China.
Jie WuDepartment of Thoracic Surgery, The First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China.
Qian HaoDepartment of Oncology, The Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China.
Lili ZhaoDepartment of Neurology, The Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China.
Hong RenDepartment of Thoracic Surgery, The First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China. renh_med@163.comcom.
Ning DuDepartment of Thoracic Surgery, The First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China. andrewdu@126.com.
First Affiliated Hospital of Xi'an Jiaotong University · CNSecond Affiliated Hospital of Xi'an Jiaotong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Colorectal cancer (CRC) is the third most common malignant tumor. DNA damage plays a crucial role in tumorigenesis, and abnormal DNA repair pathways affect the occurrence and progression of CRC. In the current study, we aimed to construct a DNA repair-related gene (DRG) signature to predict the overall survival (OS) of patients with CRC patients. The differentially expressed DRGs (DE-DRGs) were analyzed using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The prognostic gene signature was identified by univariate Cox regression and least absolute shrinkage and selection operator (LASSO)-penalized Cox proportional hazards regression analysis. The predictive ability of the model was evaluated using the Kaplan-Meier curves and time-dependent receiver operating characteristic (ROC) curves. The gene set enrichment analysis (GSEA) was performed to explore the underlying biological processes and signaling pathways. ESTIMATE and CIBERSORT were implemented to estimate the tumor immune score and immune cell infiltration status between the different risk group. The half-maximal inhibitory concentration (IC50) was evaluated to representing the drug response of this signature. Nine DE-DRGs (ESCO2, AXIN2, PLK1, CDC25C, IGF1, TREX2, ALKBH2, ESR1 and MC1R) signatures was constructed to classify patients into high- and low-risk groups. The risk score was an independent prognostic indicator of OS (hazard ratio > 1, P < 0.001). The genetic alteration analysis indicated that the nine DE-DRGs in the signature were changed in 63 required samples (100%), and the major alteration was missense mutation. Function enrichment analysis revealed that the immune response and mtotic sister chromatid segregation were the main biological processes. The high-risk group had higher immune score than the low-risk group. What's more, low-risk patients were more sensitive to selumetinib and dasatinib. The nine DE-DRGs signature was significantly associated with OS and provided a new insight for the diagnosis and treatment of CRC.

Indexed as

Biomarkers, TumorColorectal NeoplasmsAcetyltransferasesChromosomal Proteins, Non-HistoneDNA RepairHumansKaplan-Meier EstimatePrognosisAcetyltransferasesBiomarkers, TumorChromosomal Proteins, Non-HistoneESCO2 protein, human

Identifiers

PMID35484177
PMCPMC9050689
OpenAlexW4225303678

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.