Evidence map›Paper›PMID 25813036›Full record

ReviewCurrent treatment options in oncology2015

Molecular classification of gastric adenocarcinoma: translating new insights from the cancer genome atlas research network.

Yu Sunakawa, Heinz-Josef Lenz

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current treatment options in oncology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed
–field-weighted citation impact
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

39 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Viral oncogenesis in cancer: from mechanisms to therapeutics.Signal transduction and targeted therapy · 2025
    Review
  5. The influence ofFrontiers in immunology · 2025
    Article
  6. Therapeutic opportunities in EBV-positive gastric cancer subtypes.Therapeutic advances in medical oncology · 2025
    Review
  7. Article
  8. Review
  9. Review
  10. Review
  11. Review
  12. Review
  13. Review
  14. Review
  15. Review
  16. Article
  17. Article
  18. Identification of anti-Epstein-Barr virus (EBV) antibody signature in EBV-associated gastric carcinoma.Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association · 2021
    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

2 authors.

Yu SunakawaDivision of Medical Oncology, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, 1441 Eastlake Ave, Suite 5410, Los Angeles, CA, 90033, USA, y.suna0825@gmail.com.
Heinz-Josef Lenz

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gastric cancer is a heterogenous cancer, which may be classified into several distinct subtypes based on pathology and epidemiology, each with different initiating pathological processes and each possibly having different tumor biology. A classification of gastric cancer should be important to select patients who can benefit from the targeted therapies or to precisely predict prognosis. The Cancer Genome Atlas (TCGA) study collaborated with previous reports regarding subtyping gastric cancer but also proposed a refined classification based on molecular characteristics. The addition of the new molecular classification strategy to a current classical subtyping may be a promising option, particularly stratification by Epstein-Barr virus (EBV) and microsatellite instability (MSI) statuses. According to TCGA study, EBV gastric cancer patients may benefit the programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) antibodies or phosphoinositide 3-kinase (PI3K) inhibitors which are now being developed. The discoveries of predictive biomarkers should improve patient care and individualized medicine in the management since the targeted therapies may have the potential to change the landscape of gastric cancer treatment, moreover leading to both better understanding of the heterogeneity and better outcomes. Patient enrichment by predictive biomarkers for new treatment strategies will be critical to improve clinical outcomes. Additionally, liquid biopsies will be able to enable us to monitor in real-time molecular escape mechanism, resulting in better treatment strategies.

Indexed as

AdenocarcinomaGenomicsHumansStomach Neoplasms

Identifiers

What OpenQuestion holds

Textmetadata
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.