Evidence map›Paper›PMID 30942874›Full record

ArticleJAMA surgery2019

Identification and Validation of a Biomarker Signature in Patients With Resectable Pancreatic Cancer via Genome-Wide Screening for Functional Genetic Variants.

Christos Dimitrakopoulos, Bart Vrugt, Renata Flury, Peter Schraml, Uwe Knippschild, Peter Wild, Simon Hoerstrup, Doris Henne-Bruns, Peter Wuerl, Rolf Graf and 4 more

Registry-linked trialOpen access · bronzeAbstract readMulticenter Study
In one paragraph

Article in JAMA surgery, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05298722 (Prediction of Surgical Resectability After FOLFIRINOX Chemotherapy for Borderline Resectable and Locally Advanced Pancreatic Cancer), which is not on this map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
1.9field-weighted citation impact, top 12% 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.

NCT05298722 narecruitingnot on this mapstarted 2022, after this paper: background citation

Prediction of Surgical Resectability After FOLFIRINOX Chemotherapy for Borderline Resectable and Locally Advanced Pancreatic Cancer: the Role of Diffusion Weighted Magnetic Resonance Imaging, Radiomics and Liquid Biopsy

TypeinterventionalSponsorUniversity Hospital, GhentRan2022 to 2028Enrolled45ConditionsPancreatic CancerArmsImaging analysis of CT-scan and MRI with radiomics and genetic analysis of peripheral blood samples and questionnaires.
3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 1 synthesis or guideline pooled it, 33 citations in OpenAlex.

  1. Pooled it
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  4. Observational
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  9. HumanInternational journal of biological sciences · 2022
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  14. Identification of genetic variants in mArchives of toxicology · 2021
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors at 7 institutions in 3 countries.

Christos DimitrakopoulosComputational Biology Group, Department of Biosystems Science and Engineering, ETH Zurich, Zurich, Switzerland.
Bart VrugtDepartment of Pathology and Molecular Pathology, University Hospital Zurich, Zurich, Switzerland.
Renata FluryInstitute for Pathology, Cantonal Hospital of Winterthur, Winterthur, Switzerland.
Peter SchramlDepartment of Pathology and Molecular Pathology, University Hospital Zurich, Zurich, Switzerland.
Uwe KnippschildDepartment of General and Visceral Surgery, Ulm University Hospital, Ulm, Germany.
Peter WildDepartment of Pathology and Molecular Pathology, University Hospital Zurich, Zurich, Switzerland.
Simon HoerstrupInstitute for Regenerative Medicine, University of Zurich, Zurich, Switzerland.
Doris Henne-BrunsDepartment of General and Visceral Surgery, Ulm University Hospital, Ulm, Germany.
Peter WuerlDepartment of General, Visceral and Thoracic Surgery, Klinikum Dessau, Dessau, Germany.
Rolf GrafDepartment of Visceral and Transplantation Surgery, University Hospital Zurich, Zurich, Switzerland.
Stefan BreitensteinDepartment of Visceral and Thoracic Surgery, Cantonal Hospital of Winterthur, Winterthur, Switzerland.
Gareth BondLudwig Institute for Cancer Research, University of Oxford, Oxford, United Kingdom.
Niko BeerenwinkelComputational Biology Group, Department of Biosystems Science and Engineering, ETH Zurich, Zurich, Switzerland.
Lukasz Filip GrocholaInstitute for Regenerative Medicine, University of Zurich, Zurich, Switzerland.
University Hospital of Zurich · CHKantonsspital Winterthur · CHSIB Swiss Institute of Bioinformatics · CHUniversity Hospital Ulm · DELudwig Cancer Research · GBStädtisches Klinikum Dessau · DEUniversity of Zurich · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Surgery currently offers the only chance for a cure in pancreatic ductal adenocarcinoma (PDAC), but it carries a significant morbidity and mortality risk and results in varying oncologic outcomes. At present, to our knowledge, there are no tests available before surgical resection to identify tumors with an aggressive biological phenotype that could guide personalized treatment strategies. Objective: Identification of noninvasive genetic biomarkers that could direct therapy in patients whose cases are amenable to pancreatic cancer resection. Design, Setting, and Participants: This multicenter study combined a prospective European cohort of patients with PDAC who underwent pancreatic resection (from University Hospital of Zurich, Zurich, Switzerland; Cantonal Hospital of Winterthur, Winterthur, Switzerland; and University Clinic of Ulm, Ulm, Germany) with data from the Cancer Genome Atlas database in the United States, which includes prospectively registered patients with PDAC. A genome-wide screening for functional single-nucleotide polymorphisms (SNPs) that affect PDAC survival was conducted using the European cohort for identification and the Cancer Genome Atlas cohort for validation. We used Cox proportional hazards models to screen for high-frequency polymorphic variants that are associated with allelic differences in tumor-associated survival and either result in an altered protein structure and function or reside in known regulatory noncoding genomic regions. The false-discovery rate method was applied for multiple hypothesis-testing corrections. Data analysis occurred from November 2017 to May 2018. Exposures: Pancreatic resection. Main Outcomes and Measures: Tumor-associated survival. Results: A total of 195 patients in the European cohort were included, as well as 136 patients in the Cancer Genome Atlas cohort (overall median [range] age, 66 [19-87] years; 156 [47.1%] were women, and 175 [52.9%] were men). Two SNPs in noncoding, functional regions of genes that regulate cancer progression, invasion, and metastasis were identified (CHI3L2 SNP rs684559 and CD44 SNP rs353630). These were associated with survival after PDAC resection; patients who carry the risk alleles at 1 of both SNP loci had a 2.63-fold increased risk for tumor-associated death compared with those with protective genotypes (hazard ratio for survival, 0.38 [95% CI, 0.27-0.53]; P = 1.0 × 10-8). Conclusions and Relevance: The identified polymorphisms may serve as a noninvasive biomarker signature of prospective survival after pancreatic resection that is readily available at the time of PDAC diagnosis. This signature can be used to identify a subset of high-risk patients with PDAC with very low survival probability who might be eligible for inclusion in clinical trials of new therapeutic strategies, including neoadjuvant chemotherapy protocols. In addition, the biological knowledge about these SNPs could help guide the development of individualized genomic strategies for PDAC therapies.

Indexed as

Decision MakingPancreatectomyPolymorphism, Single NucleotideAdultAgedAged, 80 and overBiomarkers, TumorCarcinoma, Pancreatic DuctalDNA, NeoplasmEarly Detection of CancerFemaleFollow-Up StudiesGenome-Wide Association StudyHumansMaleMiddle AgedBiomarkers, TumorDNA, Neoplasm

Identifiers

PMID30942874
PMCPMC6583393
OpenAlexW2926613039

What OpenQuestion holds

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Registered trials

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.