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Promoter Hypermethylation Profiling Identifies Subtypes of Head and Neck Cancer with Distinct Viral, Environmental, Genetic and Survival Characteristics.

Choudhury JH, Ghosh SK - PLoS ONE (2015)

Bottom Line: Unsupervised hierarchical clustering analysis based on methylation pattern had identified two tumor clusters, which significantly differ by CpG island methylator phenotype (CIMP), tobacco, GSTM1, CYP1A1, HPV and survival status.Analyzing methylation of genes/loci individually, we have found significant higher methylation of DAPK, RASSF1, p16 and MINT31 genes (P = 0.031, 0.013, 0.031 and 0.015 respectively) in HPV (+) cases compared to HPV (-).Furthermore, a CIMP-high and Cluster-1 characteristic was also associated with poor survival.

View Article: PubMed Central - PubMed

Affiliation: Molecular Medicine Laboratory, Department of Biotechnology,Assam University, Silchar, Pin-788011, Assam, India.

ABSTRACT

Background: Epigenetic and genetic alteration plays a major role to the development of head and neck squamous cell carcinoma (HNSCC). Consumption of tobacco (smoking/chewing) and human papilloma virus (HPV) are also associated with an increase the risk of HNSCC. Promoter hypermethylation of the tumor suppression genes is related with transcriptional inactivation and loss of gene expression. We investigated epigenetic alteration (promoter methylation of tumor-related genes/loci) in tumor tissues in the context of genetic alteration, viral infection, and tobacco exposure and survival status.

Methodology: The study included 116 tissue samples (71 tumor and 45 normal tissues) from the Northeast Indian population. Methylation specific polymerase chain reaction (MSP) was used to determine the methylation status of 10 tumor-related genes/loci (p16, DAPK, RASSF1, BRAC1, GSTP1, ECAD, MLH1, MINT1, MINT2 and MINT31). Polymorphisms of CYP1A1, GST (M1 & T1), XRCC1and XRCC2 genes were studied by using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and multiplex-PCR respectively.

Principal findings: Unsupervised hierarchical clustering analysis based on methylation pattern had identified two tumor clusters, which significantly differ by CpG island methylator phenotype (CIMP), tobacco, GSTM1, CYP1A1, HPV and survival status. Analyzing methylation of genes/loci individually, we have found significant higher methylation of DAPK, RASSF1, p16 and MINT31 genes (P = 0.031, 0.013, 0.031 and 0.015 respectively) in HPV (+) cases compared to HPV (-). Furthermore, a CIMP-high and Cluster-1 characteristic was also associated with poor survival.

Conclusions: Promoter methylation profiles reflecting a correlation with tobacco, HPV, survival status and genetic alteration and may act as a marker to determine subtypes and patient outcome in HNSCC.

No MeSH data available.


Related in: MedlinePlus

(A) Kaplan-Meier survival plots: (i) HPV (+) HNSCC tumors showing better survival compared to HPV (-) tumors. (ii) CIMP-high group of HNSCC tumors showing poorer survival compared to other. (iii) Two epigenetic cluster also showed differential survival with cluster-1 had a poor survival. (B) Frequency of promoter methylation of 10 tumor-related genes/loci in HPV (+) and HPV (-) HNSCC [*P<0.05 (Mantel–Cox Log–rank)]. (C) Methylation index (MI) in three CIMP-groups of HNSCC tumors.
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pone.0129808.g002: (A) Kaplan-Meier survival plots: (i) HPV (+) HNSCC tumors showing better survival compared to HPV (-) tumors. (ii) CIMP-high group of HNSCC tumors showing poorer survival compared to other. (iii) Two epigenetic cluster also showed differential survival with cluster-1 had a poor survival. (B) Frequency of promoter methylation of 10 tumor-related genes/loci in HPV (+) and HPV (-) HNSCC [*P<0.05 (Mantel–Cox Log–rank)]. (C) Methylation index (MI) in three CIMP-groups of HNSCC tumors.

Mentions: In the study, HPV was detected in 37 out of 71 cases (52.11%) using consensus primers. The correlation between methylation of tumor-related genes and HPV was summarized in Table 3. Results shown that promoter methylation of DAPK, RASSF1, p16 and MINT31 were significantly higher in HPV positive (+) HNSCC patients compared to HPV negative (-) patients (P = 0.031, 0.013, 0.031 and 0.015) (Fig 2B). A highly significant association was found between HPV positive (+) tumors and CIMP-high group (P = 0.028). However, there was no correlation between CIMP-low and HPV (+) HNSCC (P = 0.477), when compared with HPV (-) HNSCC tumors.


Promoter Hypermethylation Profiling Identifies Subtypes of Head and Neck Cancer with Distinct Viral, Environmental, Genetic and Survival Characteristics.

Choudhury JH, Ghosh SK - PLoS ONE (2015)

(A) Kaplan-Meier survival plots: (i) HPV (+) HNSCC tumors showing better survival compared to HPV (-) tumors. (ii) CIMP-high group of HNSCC tumors showing poorer survival compared to other. (iii) Two epigenetic cluster also showed differential survival with cluster-1 had a poor survival. (B) Frequency of promoter methylation of 10 tumor-related genes/loci in HPV (+) and HPV (-) HNSCC [*P<0.05 (Mantel–Cox Log–rank)]. (C) Methylation index (MI) in three CIMP-groups of HNSCC tumors.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4476679&req=5

pone.0129808.g002: (A) Kaplan-Meier survival plots: (i) HPV (+) HNSCC tumors showing better survival compared to HPV (-) tumors. (ii) CIMP-high group of HNSCC tumors showing poorer survival compared to other. (iii) Two epigenetic cluster also showed differential survival with cluster-1 had a poor survival. (B) Frequency of promoter methylation of 10 tumor-related genes/loci in HPV (+) and HPV (-) HNSCC [*P<0.05 (Mantel–Cox Log–rank)]. (C) Methylation index (MI) in three CIMP-groups of HNSCC tumors.
Mentions: In the study, HPV was detected in 37 out of 71 cases (52.11%) using consensus primers. The correlation between methylation of tumor-related genes and HPV was summarized in Table 3. Results shown that promoter methylation of DAPK, RASSF1, p16 and MINT31 were significantly higher in HPV positive (+) HNSCC patients compared to HPV negative (-) patients (P = 0.031, 0.013, 0.031 and 0.015) (Fig 2B). A highly significant association was found between HPV positive (+) tumors and CIMP-high group (P = 0.028). However, there was no correlation between CIMP-low and HPV (+) HNSCC (P = 0.477), when compared with HPV (-) HNSCC tumors.

Bottom Line: Unsupervised hierarchical clustering analysis based on methylation pattern had identified two tumor clusters, which significantly differ by CpG island methylator phenotype (CIMP), tobacco, GSTM1, CYP1A1, HPV and survival status.Analyzing methylation of genes/loci individually, we have found significant higher methylation of DAPK, RASSF1, p16 and MINT31 genes (P = 0.031, 0.013, 0.031 and 0.015 respectively) in HPV (+) cases compared to HPV (-).Furthermore, a CIMP-high and Cluster-1 characteristic was also associated with poor survival.

View Article: PubMed Central - PubMed

Affiliation: Molecular Medicine Laboratory, Department of Biotechnology,Assam University, Silchar, Pin-788011, Assam, India.

ABSTRACT

Background: Epigenetic and genetic alteration plays a major role to the development of head and neck squamous cell carcinoma (HNSCC). Consumption of tobacco (smoking/chewing) and human papilloma virus (HPV) are also associated with an increase the risk of HNSCC. Promoter hypermethylation of the tumor suppression genes is related with transcriptional inactivation and loss of gene expression. We investigated epigenetic alteration (promoter methylation of tumor-related genes/loci) in tumor tissues in the context of genetic alteration, viral infection, and tobacco exposure and survival status.

Methodology: The study included 116 tissue samples (71 tumor and 45 normal tissues) from the Northeast Indian population. Methylation specific polymerase chain reaction (MSP) was used to determine the methylation status of 10 tumor-related genes/loci (p16, DAPK, RASSF1, BRAC1, GSTP1, ECAD, MLH1, MINT1, MINT2 and MINT31). Polymorphisms of CYP1A1, GST (M1 & T1), XRCC1and XRCC2 genes were studied by using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and multiplex-PCR respectively.

Principal findings: Unsupervised hierarchical clustering analysis based on methylation pattern had identified two tumor clusters, which significantly differ by CpG island methylator phenotype (CIMP), tobacco, GSTM1, CYP1A1, HPV and survival status. Analyzing methylation of genes/loci individually, we have found significant higher methylation of DAPK, RASSF1, p16 and MINT31 genes (P = 0.031, 0.013, 0.031 and 0.015 respectively) in HPV (+) cases compared to HPV (-). Furthermore, a CIMP-high and Cluster-1 characteristic was also associated with poor survival.

Conclusions: Promoter methylation profiles reflecting a correlation with tobacco, HPV, survival status and genetic alteration and may act as a marker to determine subtypes and patient outcome in HNSCC.

No MeSH data available.


Related in: MedlinePlus