Evidence map›Paper›PMID 35366174›Full record

ArticleTargeted oncology2022

Clinical Utility of Genomic Profiling Tests in Patients with Advanced Gastrointestinal Cancers.

Hiroyuki Takeda, Kiyomi Imoto, Kumiko Umemoto, Ayako Doi, Hiroyuki Arai, Yoshiki Horie, Takuro Mizukami, Tomoyo Oguri, Takashi Ogura, Naoki Izawa and 3 more

Abstract read
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In one paragraph

Article in Targeted oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Digestive cancers: mechanisms, therapeutics and management.Signal transduction and targeted therapy · 2025
    Review
  2. An approach for improvement of the accuracy of cancer gene panel testing.International journal of clinical oncology · 2024
    Article
  3. Article
  4. 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

13 authors.

Hiroyuki TakedaDepartment of Clinical Oncology, St. Marianna University School of Medicine, Kawasaki, Japan.
Kiyomi ImotoCenter for Genomic Medicine, St. Marianna University Hospital, Kawasaki, Japan.
Kumiko UmemotoDepartment of Clinical Oncology, St. Marianna University School of Medicine, Kawasaki, Japan.
Ayako DoiDepartment of Clinical Oncology, St. Marianna University School of Medicine, Kawasaki, Japan.
Hiroyuki AraiDepartment of Clinical Oncology, St. Marianna University School of Medicine, Kawasaki, Japan.
Yoshiki HorieDepartment of Clinical Oncology, St. Marianna University School of Medicine, Kawasaki, Japan.
Takuro MizukamiDepartment of Clinical Oncology, St. Marianna University School of Medicine, Kawasaki, Japan.
Tomoyo OguriDepartment of Clinical Oncology, St. Marianna University School of Medicine, Kawasaki, Japan.
Takashi OguraDepartment of Clinical Oncology, St. Marianna University School of Medicine, Kawasaki, Japan.
Naoki IzawaDepartment of Clinical Oncology, St. Marianna University School of Medicine, Kawasaki, Japan.
Hiroyuki YamamotoDepartment of Bioinformatics, St. Marianna University Graduate School of Medicine, Kawasaki, Japan.
Yoshihisa YamanoDivision of Neurology, Department of Internal Medicine, St. Marianna University School of Medicine, Kawasaki, Japan.
Yu SunakawaDepartment of Clinical Oncology, St. Marianna University School of Medicine, Kawasaki, Japan. y.sunakawa@marianna-u.ac.jp.ORCID http://orcid.org/0000-0002-0163-7543

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundComprehensive analyses of cancer-related genomic alterations are expected to lead to increased availability of targeted therapies. However, in patients with gastrointestinal (GI) cancers, the utility of genomic profiling is unclear because of common non-druggable alterations and rapid disease progression that prevent a sufficient time period to seek targets.

objectiveThe aim of this study was to determine the utility of genomic profiling tests in patients with GI cancers.

methodsThe subjects of this retrospective study were patients with GI cancers and patients with non-GI cancers who underwent tissue-based genomic profiling at a single institution from April 2017 to October 2020. The profile of gene alterations, frequency of tumor mutational burden-high (≥ 10 Muts/Mb), and accessibility of recommended molecular targeted therapy were compared between patients with GI cancers and patients with non-GI cancers.

resultsIn all, 133 patients with GI cancers and 63 patients with non-GI cancers were included. The genomic profiles of GI cancers showed the highest frequencies of TP53, KRAS, and APC mutations and a significantly lower frequency of PIK3CA mutations than those of non-GI cancers. Tumor mutational burden-high was significantly less prevalent in GI cancers (4% vs 20%, p = 0.008). Twenty-nine patients with GI cancers (40%) and 35 patients with non-GI cancers (56%) were recommended for targeted therapies based on the findings. Among them, seven patients each with GI cancers and non-GI cancers received the recommended therapy on their genomic findings, which showed similar treatment accessibility between the GI and non-GI cancer groups (10% vs 11%, p = 0.791). HER2-targeted and BRAF-targeted therapies were the primary treatments administered to patients with GI cancers.

conclusionsAlthough their genomic profiles revealed fewer druggable sites, patients with GI cancers accessed targeted therapies similarly to patients with non-GI cancers. The utility of genomic profile testing in patients with GI cancers was highlighted to determine if patients can receive specific treatments, such as HER2-targeted and BRAF-targeted therapies.

Indexed as

Gastrointestinal NeoplasmsProto-Oncogene Proteins B-rafBiomarkers, TumorHumansMutationRetrospective StudiesBiomarkers, TumorProto-Oncogene Proteins B-raf

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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.