Evidence map›Paper›PMID 27654712›Full record

ArticleClinical cancer research : an official journal of the American Association for Cancer Research2016

Development and Validation of a Six-Gene Recurrence Risk Score Assay for Gastric Cancer.

Keun-Wook Lee, Sung Sook Lee, Jun-Eul Hwang, Hee-Jin Jang, Hyun-Sung Lee, Sang Cheul Oh, Sang Ho Lee, Bo Hwa Sohn, Sang Bae Kim, Jae-Jun Shim and 11 more

Open access · bronzeAbstract read
In one paragraph

Article in Clinical cancer research : an official journal of the American Association for Cancer Research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the 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
1.2field-weighted citation impact, top 19% 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

21 citing papers in PubMed, 1 synthesis or guideline pooled it, 28 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Review
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. RP11-323N12.5 promotes the malignancy and immunosuppression of human gastric cancer by increasing YAP1 transcription.Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association · 2021
    Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
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

21 authors at 1 institution in 1 country.

Keun-Wook LeeDepartment of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Sung Sook LeeDepartment of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Jun-Eul HwangDepartment of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Hee-Jin JangDepartment of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Hyun-Sung LeeDepartment of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Sang Cheul OhDivision of Hemato-Oncology, Department of Internal Medicine, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Korea.
Sang Ho LeeDepartment of Surgery, Kosin University College of Medicine, Busan, Korea.
Bo Hwa SohnDepartment of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Sang Bae KimDepartment of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Jae-Jun ShimDepartment of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Woojin JeongDepartment of Life Science, Research Center for Cellular Homeostasis, Ewha Womans University, Seoul, Korea.
Minse ChaDepartment of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Jae-Ho CheongDepartment of Surgery, Yonsei University College of Medicine, Seoul, Korea.
Jae Yong ChoDepartment of Medical Oncology, Yonsei University College of Medicine, Seoul, Korea.
Jae Yun LimDepartment of Medical Oncology, Yonsei University College of Medicine, Seoul, Korea.
Eun Sung ParkCollege of Medicine, Inha University, Incheon, Korea.
Sang Cheol KimDepartment of Biomedical Informatics, Center for Genome Science, National Institute of Health, KCDC, Choongchung-Buk-do, Korea.
Yoon-Koo KangDepartment of Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
Sung Hoon NohDepartment of Surgery, Yonsei University College of Medicine, Seoul, Korea.
Jaffer A AjaniDepartment of Gastrointestinal Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Ju-Seog LeeDepartment of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas. jlee@mdanderson.org.
Seoul National University Bundang Hospital · KR

Funding

Prediction of Pathologic Complete Response by Gene Expression Profiling in EsophaR01CA138671 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI AJANI, JAFFER A. · 2010 to 2014
$1.5M
Inhibition of Hedgehog Signaling in Gli-1+Adeno CA of the Esoph or GE junctionR01CA172741 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI AJANI, JAFFER A. · 2013 to 2017
$1.4M
DEVELOPMENT AND VALIDATION OF PROGNOSTIC MODEL FOR GASTRIC CANCERR01CA150229 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI LEE, JU-SEOG · 2010 to 2013
$1.1M
Molecular Biomarkers as Classifiers to Individualize Therapy of Esophagus CancerR21CA129906 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI AJANI, JAFFER A. · 2009 to 2010
$367k
Molecular Markers of Response to Chemoradiation in Localized Esophageal CancerR21CA127672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI AJANI, JAFFER A. · 2008 to 2009
$312k
NCI NIH HHS R01 CA138671NCI NIH HHS R01 CA150229NCI NIH HHS R01 CA172741NCI NIH HHS R21 CA127672NCI NIH HHS R21 CA129906
6 · The paper itself

Abstract

purposeThis study was aimed at developing and validating a quantitative multigene assay for predicting tumor recurrence after gastric cancer surgery. EXPERIMENTAL

designGene expression data were generated from tumor tissues of patients who underwent surgery for gastric cancer (n = 267, training cohort). Genes whose expression was significantly associated with activation of YAP1 (a frequently activated oncogene in gastrointestinal cancer), 5-year recurrence-free survival, and 5-year overall survival were first identified as candidates for prognostic genes (156 genes, P < 0.001). We developed the recurrence risk score (RRS) by using quantitative RT-PCR to identify genes whose expression levels were significantly associated with YAP1 activation and patient survival in the training cohort.

resultsWe based the RRS assay on 6 genes, IGFBP4, SFRP4, SPOCK1, SULF1, THBS, and GADD45B, whose expression levels were significantly associated with YAP1 activation and prognosis in the training cohort. The RRS assay was further validated in an independent cohort of 317 patients. In multivariate analysis, the RRS was an independent predictor of recurrence [HR, 1.6; 95% confidence interval (CI), 1.02-2.4; P = 0.03]. In patients with stage II disease, the RRS had an HR of 2.9 (95% CI, 1.1-7.9; P = 0.03) and was the only significant independent predictor of recurrence.

conclusionsThe RRS assay was a valid predictor of recurrence in the two cohorts of patients with gastric cancer. Independent prospective studies to assess the clinical utility of this assay are warranted. Clin Cancer Res; 22(24); 6228-35. ©2016 AACR.

Indexed as

AdultAgedAged, 80 and overDisease-Free SurvivalFemaleGene ExpressionGene Expression ProfilingHumansMaleMiddle AgedNeoplasm Recurrence, LocalPrognosisRiskStomach Neoplasms

Identifiers

PMID27654712
PMCPMC5458637
OpenAlexW2521062450

What OpenQuestion holds

Textmetadata
LicenceTDM
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.