Evidence map›Paper›PMID 25179837›Full record

ArticleTumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine2015

Correlation between PARP-1 Val762Ala polymorphism and the risk of lung cancer in a Chinese population.

Ping Yu, Yun-Peng Liu, Jing-Dong Zhang, Xiu-Juan Qu, Bo Jin, Ye Zhang

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PubMed Publisher
In one paragraph

Article in Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. The Journal of international medical research · 2021
    Pooled it
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Ping YuDepartment of Medical Oncology, The First Hospital of China Medical University, Nanjing South Street No. 155, Heping District, Shenyang, 110001, People's Republic of China.
Yun-Peng Liu
Jing-Dong Zhang
Xiu-Juan Qu
Bo Jin
Ye Zhang

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of this study was to investigate the relationship of the PARP-1 Val762Ala (rs1136410 T>C) polymorphism and the risk of lung cancer. A population-based case-control study of 373 lung cancer patients and 360 healthy control subjects (individually matched on age and gender) in a Chinese population was conducted. Genomic DNA was extracted by the phenol-chloroform method from the peripheral blood. PARP-1 Val762Ala polymorphism was identified using polymerase chain reaction-restriction fragments length polymorphism technique. After adjusting for age, tobacco smoking, gender, smoking index, and drinking status, logistic regression analysis demonstrated that CC genotype in PARP-1 Val762Ala polymorphism had an increased risk of lung cancer compared with TT genotype (OR = 1.59, 95 % CI = 1.03 ~ 2.50, P = 0.048), a statistically difference that still existed when merging CC and TC genotypes (OR = 1.56, 95 % CI = 1.03 ~ 2.44, P = 0.042). However, no obvious difference was found between TT and TC (OR = 1.54, 95 % CI = 0.96 ~ 2.44, P = 0.073). Subgroup analysis by histological type indicated that adenocarcinoma patients had higher frequencies of CC or TC+CC genotypes than healthy controls (CC: OR = 1.85, 95 % CI = 1.12 ~ 3.03, P = 0.015; TC+CC: OR = 1.67, 95 % CI = 1.06 ~ 2.63, P = 0.027, respectively), but no statistically significant difference within each genotype in squamous cell carcinoma or small cell lung cancer (all P > 0.05). Our findings support the view that PARP-1 Val762Ala polymorphism may contribute to an increased risk of lung cancer in the Chinese population, especially for adenocarcinoma.

Indexed as

AdenocarcinomaAdultAmino Acid SubstitutionCarcinoma, Squamous CellCase-Control StudiesChinaFemaleGenetic Association StudiesGenetic Predisposition to DiseaseHumansLung NeoplasmsMaleMiddle AgedPoly (ADP-Ribose) Polymerase-1Poly(ADP-ribose) PolymerasesPolymorphism, Single NucleotidePARP1 protein, humanPoly (ADP-Ribose) Polymerase-1Poly(ADP-ribose) Polymerases

Identifiers

What OpenQuestion holds

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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.