Evidence map›Paper›PMID 33558424›Full record

ArticleClinical cancer research : an official journal of the American Association for Cancer Research2021

Transcriptomic Profiling Identifies a Risk Stratification Signature for Predicting Peritoneal Recurrence and Micrometastasis in Gastric Cancer.

In-Seob Lee, Heonyi Lee, Hoon Hur, Mitsuro Kanda, Jeong-Hwan Yook, Byung-Sik Kim, Yanghee Woo, Yasuhiro Kodera, Kwangsoo Kim, Ajay Goel

Open access · bronzeAbstract readValidation Study
In one paragraph

Article in Clinical cancer research : an official journal of the American Association for Cancer Research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
6.0field-weighted citation impact, top 3% 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

25 citing papers in PubMed, 46 citations in OpenAlex.

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  20. Integration of Genomic Biology Into Therapeutic Strategies of Gastric Cancer Peritoneal Metastasis.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2022
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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

10 authors at 6 institutions in 3 countries.

In-Seob LeeDepartment of Molecular Diagnostics and Experimental Therapeutics, Beckman Research Institute of City of Hope Comprehensive Cancer Center, Monrovia, CA, USA.
Heonyi LeeTransdisciplinary Department of Medicine and Advanced Technology, Seoul National University Hospital, Seoul, Republic of Korea (South).
Hoon HurDepartment of Surgery, Ajou University School of Medicine, Suwon, Republic of Korea (South).
Mitsuro KandaDepartment of Gastroenterological Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Jeong-Hwan YookDepartment of Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea (South).
Byung-Sik KimDepartment of Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea (South).
Yanghee WooDepartment of Surgery, City of Hope National Medical Center, Duarte, California.
Yasuhiro KoderaDepartment of Gastroenterological Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Kwangsoo KimTransdisciplinary Department of Medicine and Advanced Technology, Seoul National University Hospital, Seoul, Republic of Korea (South).
Ajay GoelDepartment of Molecular Diagnostics and Experimental Therapeutics, Beckman Research Institute of City of Hope Comprehensive Cancer Center, Monrovia, CA, USA. ajgoel@coh.org.
University of Ulsan · KRNagoya University · JPSeoul National University Hospital · KRAjou University · KRCity of Hope · USCity Of Hope National Medical Center · US

Funding

The Biology and Diagnosis of HNPCCR01CA072851 · NCI · UNIVERSITY OF CALIFORNIA SAN DIEGO · PI GOEL, AJAY · 1996 to 2019
$6.6M
Aspirin and Cancer Prevention in Lynch Syndrome: From Cell to Population DataU01CA187956 · NCI · BECKMAN RESEARCH INSTITUTE/CITY OF HOPE · PI GOEL, AJAY, WODARZ, DOMINIK F · 2014 to 2018
$2.7M
METHYLATION BIOMARKER DEVELOPMENT FOR NONINVASIVE DETECTION OF COLORECTAL CANCERR01CA181572 · NCI · BECKMAN RESEARCH INSTITUTE/CITY OF HOPE · PI GOEL, AJAY · 2014 to 2018
$1.6M
NCI NIH HHS R01 CA072851NCI NIH HHS R01 CA181572NCI NIH HHS U01 CA187956
6 · The paper itself

Abstract

purposeGastric cancer peritoneal carcinomatosis is fatal. Delay in detection of peritoneal metastases contributes to high mortality, highlighting the need to develop biomarkers that can help identify patients at high risk for peritoneal recurrence or metastasis. EXPERIMENTAL

designWe performed a systematic discovery and validation for the identification of peritoneal recurrence prediction and peritoneal metastasis detection biomarkers by analyzing expression profiling datasets from 249 patients with gastric cancer, followed by analysis of 426 patients from three cohorts for clinical validation.

resultsGenome-wide expression profiling identified a 12-gene panel for robust prediction of peritoneal recurrence in patients with gastric cancer (AUC = 0.95), which was successfully validated in a second dataset (AUC = 0.86). Examination of 216 specimens from a training cohort allowed us to establish a six gene-based risk-prediction model [AUC = 0.72; 95% confidence interval (CI): 0.66-0.78], which was subsequently validated in an independent cohort of 111 patients with gastric cancer (AUC = 0.76; 95% CI: 0.67-0.83). In both cohorts, combining tumor morphology and depth of invasion further improved the predictive accuracy of the prediction model (AUC = 0.84). Thereafter, we evaluated the performance of the identical six-gene panel for its ability to detect peritoneal metastasis by analyzing 210 gastric cancer specimens (prior 111 patients plus additional 99 cases), which discriminated patients with and without peritoneal metastasis (AUC = 0.72). Finally, our biomarker panel was also remarkably effective for identifying peritoneal micrometastasis (AUC = 0.72), and its diagnostic accuracy was significantly enhanced when depth of invasion was included in the model (AUC = 0.85).

conclusionsOur novel transcriptomic signature for risk stratification and identification of high-risk patients with peritoneal carcinomatosis might serve as an important clinical decision making in patients with gastric cancer.

Indexed as

Biomarkers, TumorClinical Decision-MakingDatasets as TopicDisease-Free SurvivalFollow-Up StudiesGastrectomyGene Expression ProfilingGene Expression Regulation, NeoplasticHumansNeoplasm MicrometastasisPeritoneal NeoplasmsPrognosisRisk AssessmentStomachStomach NeoplasmsBiomarkers, Tumor

Identifiers

PMID33558424
PMCPMC8103893
OpenAlexW3128411675

What OpenQuestion holds

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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.