Evidence map›Paper›PMID 39971948›Full record

ArticleCell death discovery2025

Comparative microRNA signatures based on liquid biopsy to identify lymph node metastasis in T1 colorectal cancer patients undergoing upfront surgery or endoscopic resection.

Kazuaki Okamoto, Hiroaki Nozawa, Tsuyoshi Ozawa, Yoko Yamamoto, Yuichiro Yokoyama, Shigenobu Emoto, Koji Murono, Kazuhito Sasaki, Mitsuhiro Fujishiro, Soichiro Ishihara

Abstract read
In one paragraph

Article in Cell death discovery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
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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.

Kazuaki OkamotoDepartment of Surgical Oncology, The University of Tokyo, Tokyo, Japan. okamotok-sur@h.u-tokyo.ac.jp.ORCID http://orcid.org/0000-0003-4708-4654
Hiroaki NozawaDepartment of Surgical Oncology, The University of Tokyo, Tokyo, Japan.
Tsuyoshi OzawaDepartment of Surgical Oncology, The University of Tokyo, Tokyo, Japan.
Yoko YamamotoDepartment of Surgical Oncology, The University of Tokyo, Tokyo, Japan.
Yuichiro YokoyamaDepartment of Surgical Oncology, The University of Tokyo, Tokyo, Japan.
Shigenobu EmotoDepartment of Surgical Oncology, The University of Tokyo, Tokyo, Japan.
Koji MuronoDepartment of Surgical Oncology, The University of Tokyo, Tokyo, Japan.
Kazuhito SasakiDepartment of Surgical Oncology, The University of Tokyo, Tokyo, Japan.
Mitsuhiro FujishiroDepartment of Gastroenterology, The University of Tokyo, Tokyo, Japan.
Soichiro IshiharaDepartment of Surgical Oncology, The University of Tokyo, Tokyo, Japan.

Funding

MEXT | Japan Society for the Promotion of Science (JSPS) 24K10376
6 · The paper itself

Abstract

After endoscopic resection of T1 colorectal cancer (CRC) with a high risk of lymph node metastasis (LNM), additional surgery is required. However, the actual frequency of LNM based on conventional risk factors is less than 16%. There is a need for biomarkers to identify T1 CRC carrying a high risk of metastasis to avoid unnecessary radical surgery. Based on the comparison of serum miRNA between stage I/II and stage III from a large-scale in silico dataset, we conducted a validation analysis of the selected miRNAs using plasma samples from LNM-positive and LNM-negative T1 CRC patients who underwent endoscopic treatment followed by radical surgery at our hospital. In the validation cohort, the three-miRNA classifiers (miR-195-5p, miR-221-3p, and miR-193b-3p) effectively identified LNM-positive T1 CRC patients who received upfront surgery with an area under the curve (AUC) value of 0.74. Moreover, in T1 CRC patients after endoscopic resection, miR-195-5p and miR-221-3p were able to predict LNM with an AUC of 0.74. Plasma miRNA signatures may serve as effective predictors for LNM in T1 CRC both before upfront surgery and after endoscopic resection.

Identifiers

PMID39971948
PMCPMC11840149

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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.