ArticleTumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine2016
Combination of genetic variants in cyclin D1 and retinoblastoma genes predict clinical outcome in oral cancer patients.
Article in Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.
- Association between the HOTAIR polymorphisms and cancer risk: an updated meta-analysis.Oncotarget · 2017Pooled it
- Association of CCND1 (c.723G > A, rs9344) variant with elevated risk of breast carcinoma: a retrospective case-control study.Molecular biology reports · 2023Article
- Unanswered Questions on the Optimal Extent of Tongue Cancer Resections.Indian journal of surgical oncology · 2020Article
- High expression of TMEM40 contributes to progressive features of tongue squamous cell carcinoma.Oncology reports · 2019Article
- Association between genetic polymorphisms of long non-coding RNA PRNCR1 and prostate cancer risk in a sample of the Iranian population.Molecular and clinical oncology · 2017Article
- Genetic variants of cell cycle pathway genes predict disease-free survival of hepatocellular carcinoma.Cancer medicine · 2017Article
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Oral cancer is a dreadful disease with a wide variation in geographical distribution. In order to identify some useful biomarkers for the disease prognosis, the present study assessed the influence of single nucleotide polymorphisms (SNPs) in cell cycle genes on survival in a well-annotated set of patients with oral squamous cell carcinoma (OSCC). The study examined 12 sequence variants or SNPs in selected cell cycle genes, with prognostic outcomes in 311 oral cancer patients. Our analysis showed that SNPs in cyclin D1:rs9344 and retinoblastoma:rs427686 genes showed a strong correlation with disease-free survival. In addition, the cumulative effect of these SNPs significantly and independently predicts the survival. Thus, the current study identified genotypes (SNP signature), which can be used as novel prognostic biomarkers to stratify patients based on disease-free survival and therefore maybe helpful in therapeutic decision-making.
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