Evidence map›Paper›PMID 37165046›Full record

ArticleCancer immunology, immunotherapy : CII2023

Improved predictability of pancreatic ductal adenocarcinoma diagnosis using a blood immune cell biomarker panel developed from bulk mRNA sequencing and single-cell RNA-sequencing.

Sung Ill Jang, Hyung Keun Lee, Eun-Ju Chang, Somi Kim, So Young Kim, In Young Hong, Jong Kyoung Kim, Hye Sun Lee, Juyeon Yang, Jae Hee Cho and 1 more

Open access · hybridAbstract read
In one paragraph

Article in Cancer immunology, immunotherapy : CII, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.8field-weighted citation impact, top 13% 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

5 citing papers in PubMed, 8 citations in OpenAlex.

  1. Trial
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  4. Review
  5. 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

11 authors at 4 institutions in 2 countries.

Sung Ill Jang *Department of Internal Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, 712 Eonjuro, Gangnam-gu, Seoul, 135-720, Korea.
Hyung Keun Lee *Department of Ophthalmology, Institute of Vision Research, Yonsei University College of Medicine, Seoul, Korea.
Eun-Ju ChangDepartment of Biomedical Sciences, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
Somi KimDepartment of Life Sciences, Pohang University of Science and Technology (POSTECH), Pohang, Korea.
So Young KimDepartment of Ophthalmology, Institute of Vision Research, Yonsei University College of Medicine, Seoul, Korea.
In Young HongDepartment of Internal Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, 712 Eonjuro, Gangnam-gu, Seoul, 135-720, Korea.
Jong Kyoung KimDepartment of Life Sciences, Pohang University of Science and Technology (POSTECH), Pohang, Korea.
Hye Sun LeeBiostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, Korea.
Juyeon YangBiostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, Korea.
Jae Hee ChoDepartment of Internal Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, 712 Eonjuro, Gangnam-gu, Seoul, 135-720, Korea.
Dong Ki LeeDepartment of Internal Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, 712 Eonjuro, Gangnam-gu, Seoul, 135-720, Korea. dklee@yuhs.ac.ORCID http://orcid.org/0000-0002-0048-9112
Yonsei University · KRPohang University of Science and Technology · KRGangnam Severance Hospital · KRUlsan College · KR

Funding

The Technology Development Program (MSS, Korea) S3301290
6 · The paper itself

Abstract

backgroundPancreatic ductal adenocarcinoma (PDAC) remains a devastating cancer due to its poor survival rate, early detection, and resectability. This study aimed to determine the peripheral blood mononuclear cell (PBMC) immune biomarkers in patients with PDAC and investigate the PDAC-specific peripheral blood biomarker panel and validate its clinical performance.

methodsIn this prospective, blinded, case-control study, a biomarker panel formula was generated using a development cohort-including healthy controls, patients at high risk of PDAC, and patients with benign pancreatic disease, PDAC, or other gastrointestinal malignancies-and its diagnostic performance was verified using a validation cohort, including patients with ≥ 1 lesion suspected as PDAC on computed tomography (CT).

resultsRNA-sequencing of PBMCs from patients with PDAC identified three novel immune cell markers, IL-7R, PLD4, and ID3, as specific markers for PDAC. Regarding the diagnostic performance of the regression formula for the three biomarker panels, the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 84.0%, 78.8%, 47.2%, 95.6%, and 79.8%, respectively. Based on the formula scores for the biomarker panel, the false-negative rate (FNR) of the biomarkers was 8% (95% confidence interval [CI] 3.0-13.0), which was significantly lower than that based on CT in the validation cohort (29.2%, 95% CI 20.8-37.6).

conclusionsThe regression formula constructed using three PBMC biomarkers is an inexpensive, rapid, and convenient method that shows clinically useful performance for the diagnosis of PDAC. It aids diagnoses and differential diagnoses of PDAC from pancreatic disease by lowering the FNR compared to CT. Clinical trial registration Clinical Research Information Service, KCT0004614 (08 January 2020).

Indexed as

Carcinoma, Pancreatic DuctalPancreatic NeoplasmsBiomarkers, TumorCase-Control StudiesHumansLeukocytes, MononuclearProspective StudiesRNARNA, MessengerBiomarkers, TumorRNARNA, MessengerCancer biomarkersInhibitor of DNA binding 3Interleukin-7 receptorPancreatic ductal adenocarcinomaPhospholipase D4

Identifiers

PMID37165046
PMCPMC10361912
OpenAlexW4376131461

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.