Evidence map›Paper›PMID 34510657›Full record

ReviewCancer science2021

SCRUM-Japan GI-SCREEN and MONSTAR-SCREEN: Path to the realization of biomarker-guided precision oncology in advanced solid tumors.

Yoshiaki Nakamura, Takao Fujisawa, Hiroya Taniguchi, Hideaki Bando, Wataru Okamoto, Katsuya Tsuchihara, Takayuki Yoshino, Atsushi Ohtsu

Open access · goldAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Cancer science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed
3.4field-weighted citation impact, top 6% 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

48 citing papers in PubMed, 54 citations in OpenAlex.

  1. Trial
  2. Trial
  3. Review
  4. Comprehensive Genomic and Transcriptomic Characterization of MTAP Loss across Advanced Solid Tumors.Clinical cancer research : an official journal of the American Association for Cancer Research · 2026
    Observational
  5. Article
  6. Observational
  7. Article
  8. Identification of a NovelJCO precision oncology · 2026
    Article
  9. Article
  10. Article
  11. Current Status and Future Perspectives of Molecular Residual Disease Testing in Genitourinary Cancers.International journal of urology : official journal of the Japanese Urological Association · 2025
    Review
  12. Resistance mechanism to pembrolizumab inInternational cancer conference journal · 2025
    Article
  13. Review
  14. Observational
  15. Review
  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

8 authors at 3 institutions in 1 country.

Yoshiaki NakamuraDepartment of Gastroenterology and Gastrointestinal Oncology, National Cancer Center Hospital East, Kashiwa, Japan.
Takao FujisawaTranslational Research Support Section, National Cancer Center Hospital East, Kashiwa, Japan.
Hiroya TaniguchiDepartment of Gastroenterology and Gastrointestinal Oncology, National Cancer Center Hospital East, Kashiwa, Japan.
Hideaki BandoDepartment of Gastroenterology and Gastrointestinal Oncology, National Cancer Center Hospital East, Kashiwa, Japan.ORCID https://orcid.org/0000-0001-5041-2765
Wataru OkamotoCancer Treatment Center, Hiroshima University Hospital, Hiroshima, Japan.
Katsuya TsuchiharaDivision of Translational Informatics, Exploratory Oncology Research and Clinical Trial Center, National Cancer Center, Kashiwa, Japan.ORCID https://orcid.org/0000-0001-7507-2349
Takayuki YoshinoDepartment of Gastroenterology and Gastrointestinal Oncology, National Cancer Center Hospital East, Kashiwa, Japan.ORCID https://orcid.org/0000-0002-0489-4756
Atsushi OhtsuDepartment of Gastroenterology and Gastrointestinal Oncology, National Cancer Center Hospital East, Kashiwa, Japan.
National Cancer Center Hospital East · JPAichi Cancer Center · JPHiroshima University Hospital · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Comprehensive genomic profiling enables the detection of genomic biomarkers in advanced solid tumors. However, efficient patient screening for the success of precision oncology remains challenging due to substantial barriers, such as genotyping costs and accessibility to matched therapies. To address these challenges, we launched GI-SCREEN, a nationwide gastrointestinal cancer genomic screening project within the SCRUM-Japan network in 2015 with the specific purpose of matching patients with a diverse portfolio of affiliated interventional targeted therapy trials. Subsequently, we initiated the molecular profiling projects GOZILA, MONSTAR-SCREEN-1, and MONSTAR-SCREEN-2, which incorporate tissue and plasma multiomics approaches to accurately identify patients with advanced solid tumors who would benefit from matched therapies. These projects have led to a significant increase in patient participation in targeted clinical trials and the approval of several therapeutics and companion diagnostics. Additionally, clinicogenomic analyses utilizing the SCRUM-Japan database have provided new insights into the molecular mechanisms of advanced solid tumors. In this review, we describe the path to the realization of cancer precision medicine for patients with advanced solid tumors based on the SCRUM-Japan GI-SCREEN and MONSTAR-SCREEN platforms.

Indexed as

Circulating Tumor DNADatabases, GeneticGastrointestinal NeoplasmsGene Expression ProfilingGenetic MarkersHigh-Throughput Nucleotide SequencingHumansJapanMedical OncologyPrecision MedicineRegistriesCirculating Tumor DNAGenetic Markerscirculating tumor DNAmultiomicsnext-generation sequencingprecision oncologyreal-world data

Identifiers

PMID34510657
PMCPMC8586659
OpenAlexW3200888272

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.