Evidence map›Paper›PMID 39639217›Full record

ArticleBMC cancer2024

Radioresistance-related gene signatures identified by transcriptomics characterize the prognosis and immune landscape of pancreatic cancer patients.

Dandan Wang, Jun Cao, Yanhui Chen, Lisha Zhang, Chan Zhou, Litao Huang, Yanliang Chen

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. 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

7 authors.

Dandan Wang *The First School of Clinical Medicine, Lanzhou University, Lanzhou, Gansu, China.
Jun Cao *Department of Outpatient, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei, China.
Yanhui ChenDepartment of Neuroscience and Endocrinology, Tangshan Caofeidian District Hospital, Tangshan, Hebei, China.
Lisha ZhangDepartment of Obstetrics, Tangshan Caofeidian District Hospital, Tangshan, Hebei, China.
Chan ZhouDepartment of Geriatrics, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei, China.
Litao HuangDepartment of Clinical Research Management, West China Hospital of Sichuan University, Chengdu, China.
Yanliang ChenThe First School of Clinical Medicine, Lanzhou University, Lanzhou, Gansu, China. chenyanliang125@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRadiotherapy (RT) is an important means of local treatment of solid tumors, and radioresistance is the main reason for RT failure for tumors, especially pancreatic cancer (PC). It is urgent to distinguish key genes and mechanisms of radioresistance in PC.

methodsWe acquired the data from The Cancer Genome Atlas (TCGA), obtained the gene modules associated with radioresistance by weighted gene coexpression network analysis (WGCNA), and identified differentially expressed genes (DEGs) between normal and tumor samples. Radioresistance-related genes (RRRGs) were determined with the intersection of WGCNA and DEGs. The hub RRRGs associated with prognosis were distinguished by the least absolute shrinkage and selection operator (LASSO) regression. We established a risk score model using multivariate Cox regression. Immune cell infiltration and drug sensitivity were evaluated through the CIBERSORT algorithm and the "OncoPredict" software package, respectively. The association of the key gene RIC3 and PC clinical features was verified in public databases, and its biological behaviors were explored in vitro.

resultsThe intersection of DEGs and WGCNA confirmed 14 RRRGs, then six hub RRRGs were identified using LASSO. A key four genes (DUSP4, ADORA2B, SCGB2A1, and RIC3) risk score model was constructed and proved to be capable of independently estimating the prognosis of PC. There is no significant difference between risk score groups in various immune cell infiltration and response to immunotherapy. Although the low-risk group seemed to exhibit greater sensitivity to antitumor drugs, the four drugs (5-fluorouracil [5-FU], leucovorin, irinotecan, and oxaliplatin) currently used for PC patients had no statistical difference for the low- and high- group. The overexpression of RIC3 had a synergy effect with irradiation on inhibited malignant biological properties of PC cells, which was verified by detecting the proliferation ability, apoptosis rate, cell cycle distribution, and migration ability of PANC-1 cells.

conclusionsWe herein presented signature genes correlated with radioresistance in PC and established a risk score model competent in estimating patients' clinical outcomes and response to antitumor drugs. The above evidence could contribute to comprehending the mechanisms of radioresistance and identifying the underlying therapy targeting.

Indexed as

Gene Expression ProfilingGene Expression Regulation, NeoplasticPancreatic NeoplasmsRadiation ToleranceTranscriptomeAntineoplastic Combined Chemotherapy ProtocolsBiomarkers, TumorCell Line, TumorFemaleFluorouracilGene Regulatory NetworksHumansIrinotecanLeucovorinMaleOxaliplatinBiomarkers, TumorFluorouracilfolfirinoxIrinotecanLeucovorinOxaliplatinGene signatureImmune landscapePancreatic cancerRadioresistanceRisk score model

Identifiers

PMID39639217
PMCPMC11619475

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.