Evidence map›Paper›PMID 33575083›Full record

ArticleAmerican journal of cancer research2021

A new 7-gene survival score assay for pancreatic cancer patient prognosis prediction.

Lisi Luo, Yufang Li, Chumei Huang, Yujing Lin, Yonghui Su, Hong Cen, Yutong Chen, Siqi Peng, Tianyi Ren, Rongzhi Xie and 1 more

Open access · greenAbstract read
In one paragraph

Article in American journal of cancer research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.1field-weighted citation impact, top 20% 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

14 citing papers in PubMed, 17 citations in OpenAlex.

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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

11 authors at 1 institution in 1 country.

Lisi LuoDepartment of Abdominal Oncology, The Cancer Center of The Fifth Affiliated Hospital, Sun Yat-sen University Zhuhai 519000, Guangdong Province, China.
Yufang LiDepartment of Abdominal Oncology, The Cancer Center of The Fifth Affiliated Hospital, Sun Yat-sen University Zhuhai 519000, Guangdong Province, China.
Chumei HuangDepartment of Gastroenterology, The Seventh Affiliated Hospital of Sun Yat-sen University Shenzhen 518107, China.
Yujing LinDepartment of Pathology, The Fifth Affiliated Hospital of Sun Yat-sen University Zhuhai, China.
Yonghui SuDepartment of General Surgery, The Fifth Affiliated Hospital of Sun Yat-sen University Zhuhai 519000, Guangdong Province, China.
Hong CenDepartment of General Surgery, The Fifth Affiliated Hospital of Sun Yat-sen University Zhuhai 519000, Guangdong Province, China.
Yutong ChenDepartment of Abdominal Oncology, The Cancer Center of The Fifth Affiliated Hospital, Sun Yat-sen University Zhuhai 519000, Guangdong Province, China.
Siqi PengCenter for Interventional Medicine, The Fifth Affiliated Hospital, Sun Yat-sen University Zhuhai 519000, Guangdong Province, China.
Tianyi RenDepartment of Abdominal Oncology, The Cancer Center of The Fifth Affiliated Hospital, Sun Yat-sen University Zhuhai 519000, Guangdong Province, China.
Rongzhi XieDepartment of Abdominal Oncology, The Cancer Center of The Fifth Affiliated Hospital, Sun Yat-sen University Zhuhai 519000, Guangdong Province, China.
Linjuan ZengDepartment of Abdominal Oncology, The Cancer Center of The Fifth Affiliated Hospital, Sun Yat-sen University Zhuhai 519000, Guangdong Province, China.
Sun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gene expression features that are valuable for pancreatic ductal adenocarcinoma (PDAC) prognosis are still largely unknown. We aimed to explore pivotal molecular signatures for PDAC progression and establish an efficient survival score to predict PDAC prognosis. Overall, 163 overlapping genes were identified from three statistical methods, including differentially expressed genes (DEGs), coexpression network analysis (WGCNA), and target genes for miRNAs that were significantly related to PDAC patients' overall survival (OS). Then, according to the optimal value of the cross-validation curve (lambda = 0.031), 7 non-zero coefficients (ARNTL2, DSG3, PTPRR, ANLN, S100A14, ANKRD22, and TSPAN7) were selected to establish a prognostic prediction model of PDAC patients. We further confirmed the expression level of 7 genes using RT-PCR, western blot, and immunohistochemistry staining in PDAC patients' tissues. Our results showed that the ROC curve of the 7-mRNA model indicated good predictive ability for 1- and 2-year OS in three datasets (TCGA: 0.71, 0.69; ICGC: 0.8, 0.74; GEO batch: 0.61, 0.7, respectively). The hazard ratio (HR) of the low-risk group had a similar significant result (TCGA: HR = 0.3723; ICGC: HR = 0.2813; GEO batch: HR = 0.4999; all P < 0.001). Furthermore, Log-rank test results in three cohorts showed that the 7-mRNA assay excellently predicted the prognosis and metastasis, especially in TNM stage I&II subgroups of PDAC. In conclusion, the strong validation of our 7-mRNA signature indicates the promising effectiveness of its clinical application, especially in patients with TNM stages I&II.

Indexed as

a prediction modelbioinformaticsmolecular signaturePancreatic cancer

Identifiers

PMID33575083
PMCPMC7868749
OpenAlexW3127392879

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Registered trials

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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.