Evidence map›Paper›PMID 36245370›Full record

ArticleCancer biomarkers : section A of Disease markers2022

Salivary DNA methylation markers for cancer of oral cavity.

Shama Prasada Kabekkodu, Sanjiban Chakrabarty, Vinay Koshy Varghese, Supriti Ghosh, Raghu Radhakrishnan, Sandeep P Mallya, Adarsh Kudva

Abstract read
In one paragraph

Article in Cancer biomarkers : section A of Disease markers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.4field-weighted citation impact, top 41% 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

6 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Review
  3. Application of artificial intelligence in oral potentially malignant disorders: current opinions and future barriers.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
    Review
  4. Article
  5. Article
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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

7 authors at 1 institution in 1 country.

Shama Prasada KabekkoduDepartment of Cell and Molecular Biology, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, India.
Sanjiban ChakrabartyDepartment of Cell and Molecular Biology, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, India.
Vinay Koshy VargheseDepartment of Cell and Molecular Biology, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, India.
Supriti GhoshDepartment of Cell and Molecular Biology, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, India.
Raghu RadhakrishnanDepartment of Oral Pathology, Manipal College of Dental Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, India.
Sandeep P MallyaDepartment of Bioinformatics, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, India.
Adarsh KudvaDepartment of Oral and Maxillofacial Surgery, Manipal College of Dental Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, India.
Manipal Academy of Higher Education · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeAberrant DNA methylation plays a crucial role in oral carcinogenesis. Our previous study demonstrated hypermethylation of DAPK1, LRPPRC, RAB6C, and ZNF471 promoters in patients with tongue squamous cell carcinoma compared with normal samples. Methylation profiling using salivary DNA is considered a non-invasive alternative to tissue samples. Hence, the present study tested the DNA methylation status of these four promoters as indicators of oral cancer progression.

methodsWe performed the bisulfite-based targeted next-generation sequencing of four candidate genes in saliva and tissue DNA from normal, premalignant, and squamous cell carcinoma subjects. The clinicopathological association, diagnostic, and prognostic utility of aberrant DNA methylation were evaluated using the TCGA-HNSCC dataset. Using the Xgboost algorithm and logistic regression, CpG sites were prioritized, and Receiver Operating Characteristic was generated. By Log-rank test and Kaplan-Meier (KM) curves, an association between methylation and overall survival (OS), disease-free interval (DFI), and progression-free interval (PFI) were computed.

resultsWe identified all four genes as significantly hypermethylated in premalignant and malignant samples compared with normal samples. The methylation levels were comparable between saliva and tissue samples with an r-value of 0.6297 to 0.8023 and 0.7823 to 0.9419 between premalignant tissue vs. saliva and OC vs. saliva, respectively. We identified an inverse correlation between DAPK1, LRPPRC, RAB6C, and ZNF471 promoter methylation with their expression. A classifier of 8 differentially methylated CpG sites belonging to DAPK1, RAB6C, and ZNF471 promoters was constructed, showing an AUC of 0.984 to differentiate tumors from normal samples. The differential methylation status of DAPK1, LRPPRC, and ZNF71 promoters was prognostically important. Abnormal expression of all four genes was associated with immune infiltration.

conclusionsThus, methylation analysis of these candidate CpG sites from saliva can be helpful as a non-invasive tool for the clinical management of OC.

Indexed as

Carcinoma, Squamous CellHead and Neck NeoplasmsTongue NeoplasmsCpG IslandsDNADNA MethylationHumansrab GTP-Binding ProteinsSalivaDNARAB6C protein, humanrab GTP-Binding Proteinsbisulfite targeted next-generation sequencingDNA hypermethylationnon-invasive markeroral squamous cell carcinomaprognosissaliva

Identifiers

PMID36245370
PMCPMC12364243
OpenAlexW4304192932

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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.