Evidence map›Paper›PMID 36803844›Full record

ArticleClinical epigenetics2023

Utility of promoter hypermethylation in malignant risk stratification of intraductal papillary mucinous neoplasms.

Ankit Chhoda, Anup Sharma, Bethsebie Sailo, Haoyu Tang, Nensi Ruzgar, Wan Ying Tan, Lee Ying, Rishabh Khatri, Anand Narayanan, Shrikant Mane and 8 more

Open access · goldAbstract read
In one paragraph

Article in Clinical epigenetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.6field-weighted citation impact, top 15% 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

4 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Review
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

18 authors at 6 institutions in 1 country.

Ankit Chhoda *Division of Gastroenterology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, USA.
Anup Sharma *Department of Surgery, Yale School of Medicine, New Haven, USA.
Bethsebie SailoDepartment of Surgery, Yale School of Medicine, New Haven, USA.
Haoyu TangYale Systems Biology Institute, Yale University, New Haven, USA.
Nensi RuzgarDepartment of Surgery, Yale School of Medicine, New Haven, USA.
Wan Ying TanDepartment of Surgery, Yale School of Medicine, New Haven, USA.
Lee YingDepartment of Surgery, Yale School of Medicine, New Haven, USA.
Rishabh KhatriDepartment of Internal Medicine, Temple University Hospital, Philadelphia, USA.
Anand NarayananYale Center for Genome Analysis, New Haven, USA.
Shrikant ManeYale Center for Genome Analysis, New Haven, USA.
Bony De KumarYale Center for Genome Analysis, New Haven, USA.
Laura D WoodDepartment of Pathology, Johns Hopkins University, Baltimore, USA.
Christine Iacobuzio-DonahueDepartment of Pathology, Memorial Sloan Kettering, New York City, USA.
Christopher L WolfgangDepartment of Surgery, NYU Langone Health, New York City, USA.
John W KunstmanDepartment of Surgery, Yale School of Medicine, New Haven, USA.
Ronald R SalemDepartment of Surgery, Yale School of Medicine, New Haven, USA.
James J FarrellSection of Digestive Diseases, Department of Internal Medicine, Yale School of Medicine, New Haven, USA. james.j.farrell@yale.edu.
Nita AhujaDepartment of Surgery, Yale School of Medicine, New Haven, USA. nita.ahuja@yale.edu.
Yale University · USBeth Israel Deaconess Medical Center · USJohns Hopkins University · USMemorial Sloan Kettering Cancer Center · USNYU Langone Health · USTemple University Hospital · US

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Hongbiao Carl Lekaye · 1985 to 2026
$347.4M
Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Yale Pathology Tissue Services Shared ResourceP30CA016359 · NCI · YALE UNIVERSITY · PI MEGAN C KING · 1985 to 2026
$85.0M
(PQD3)Molecular Profiles associated with Long-Term Survival in pancreas CancerR01CA185357 · NCI · YALE UNIVERSITY · PI AHUJA, NITA, EASWARAN, HARIHARAN · 2014 to 2017
$1.8M
NCATS NIH HHS UL1 TR001863NCI NIH HHS P30 CA008748NCI NIH HHS R01 CA185357NIH HHS P30CA016359
6 · The paper itself

Abstract

backgroundIntraductal papillary mucinous neoplasms (IPMNs), a type of cystic pancreatic cancer (PC) precursors, are increasingly identified on cross-sectional imaging and present a significant diagnostic challenge. While surgical resection of IPMN-related advanced neoplasia, i.e., IPMN-related high-grade dysplasia or PC, is an essential early PC detection strategy, resection is not recommended for IPMN-low-grade dysplasia (LGD) due to minimal risk of carcinogenesis, and significant procedural risks. Based on their promising results in prior validation studies targeting early detection of classical PC, DNA hypermethylation-based markers may serve as a biomarker for malignant risk stratification of IPMNs. This study investigates our DNA methylation-based PC biomarker panel (ADAMTS1, BNC1, and CACNA1G genes) in differentiating IPMN-advanced neoplasia from IPMN-LGDs.

methodsOur previously described genome-wide pharmaco-epigenetic method identified multiple genes as potential targets for PC detection. The combination was further optimized and validated for early detection of classical PC in previous case-control studies. These promising genes were evaluated among micro-dissected IPMN tissue (IPMN-LGD: 35, IPMN-advanced neoplasia: 35) through Methylation-Specific PCR. The discriminant capacity of individual and combination of genes were delineated through Receiver Operating Characteristics curve analysis.

resultsAs compared to IPMN-LGDs, IPMN-advanced neoplasia had higher hypermethylation frequency of candidate genes: ADAMTS1 (60% vs. 14%), BNC1 (66% vs. 3%), and CACGNA1G (25% vs. 0%). We observed Area Under Curve (AUC) values of 0.73 for ADAMTS1, 0.81 for BNC1, and 0.63 for CACNA1G genes. The combination of the BNC1/ CACNA1G genes resulted in an AUC of 0.84, sensitivity of 71%, and specificity of 97%. Combining the methylation status of the BNC1/CACNA1G genes, blood-based CA19-9, and IPMN lesion size enhanced the AUC to 0.92.

conclusionDNA-methylation based biomarkers have shown a high diagnostic specificity and moderate sensitivity for differentiating IPMN-advanced neoplasia from LGDs. Addition of specific methylation targets can improve the accuracy of the methylation biomarker panel and enable the development of noninvasive IPMN stratification biomarkers.

Indexed as

Neoplasms, Cystic, Mucinous, and SerousPancreatic Intraductal NeoplasmsPancreatic NeoplasmsBiomarkers, TumorDNADNA MethylationHumansRisk AssessmentBiomarkers, TumorDNAMethylation-specific biomarkerPancreatic cancerPancreatic cyst

Identifiers

PMID36803844
PMCPMC9942382
OpenAlexW4321371595

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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.