Evidence map›Paper›PMID 41275215›Full record

Observational studyMolecular cancer2025

A machine-learning powered liquid biopsy predicts response to paclitaxel plus ramucirumab in advanced gastric cancer: results from the prospective IVY trial.

Katsutoshi Shoda, Caiming Xu, Takeshi Nagasaka, Daisuke Ichikawa, Ajay Goel

Registry-linked trialAbstract readMulticenter StudyObservational Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in Molecular cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06490055 (Predicting the Efficacy of Paclitaxel Plus Ramucirumab in Advanced Gastric Cancer.), which is not on this 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.

NCT06490055 completednot on this map

Predicting the Efficacy of Paclitaxel Plus Ramucirumab in Advanced Gastric Cancer.

Typeobservational_patient_registrySponsorCity of Hope Medical CenterRan2018 to 2025Enrolled162ConditionsGastric Cancer, Chemotherapy Effect, Paclitaxel, RamucirumabArmsPaclitaxel
3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
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

5 authors.

Katsutoshi Shoda *Department of Molecular Diagnostics and Experimental Therapeutics, Beckman Research Institute of City of Hope, Biomedical Research Center, 1218 S. Fifth Avenue, Suite 2226, Monrovia, CA, 91016, USA.
Caiming Xu *Department of Molecular Diagnostics and Experimental Therapeutics, Beckman Research Institute of City of Hope, Biomedical Research Center, 1218 S. Fifth Avenue, Suite 2226, Monrovia, CA, 91016, USA.
Takeshi NagasakaDepartment of Clinical Oncology, Kawasaki Medical School, Okayama, Japan.
Daisuke IchikawaFirst Department of Surgery, Faculty of Medicine, University of Yamanashi, Yamanashi, Japan.
Ajay GoelDepartment of Molecular Diagnostics and Experimental Therapeutics, Beckman Research Institute of City of Hope, Biomedical Research Center, 1218 S. Fifth Avenue, Suite 2226, Monrovia, CA, 91016, USA. ajgoel@coh.org.

Funding

Noncoding RNA Biomarkers for Noninvasive and Early Detection of Pancreatic CancerU01CA214254 · NCI · BECKMAN RESEARCH INSTITUTE/CITY OF HOPE · PI Ajay Goel, DANIEL D VON HOFF · 2017 to 2026
$8.9M
The Biology and Diagnosis of HNPCCR01CA072851 · NCI · UNIVERSITY OF CALIFORNIA SAN DIEGO · PI GOEL, AJAY · 1996 to 2019
$6.6M
Exosomal biomarkers for the early detection of hepatocellular carcinomaR01CA271443 · NCI · BECKMAN RESEARCH INSTITUTE/CITY OF HOPE · PI Ajay Goel · 2023 to 2026
$2.9M
Aspirin and Cancer Prevention in Lynch Syndrome: From Cell to Population DataU01CA187956 · NCI · BECKMAN RESEARCH INSTITUTE/CITY OF HOPE · PI GOEL, AJAY, WODARZ, DOMINIK F · 2014 to 2018
$2.7M
Exosomal Biomarkers for the Noninvasive Detection of Colorectal CancerR01CA227602 · NCI · BECKMAN RESEARCH INSTITUTE/CITY OF HOPE · PI GOEL, AJAY · 2019 to 2023
$2.5M
METHYLATION BIOMARKER DEVELOPMENT FOR NONINVASIVE DETECTION OF COLORECTAL CANCERR01CA181572 · NCI · BECKMAN RESEARCH INSTITUTE/CITY OF HOPE · PI GOEL, AJAY · 2014 to 2018
$1.6M
NCI NIH HHS R01 CA072851NCI NIH HHS R01 CA181572NCI NIH HHS R01 CA227602NCI NIH HHS R01 CA271443NCI NIH HHS U01 CA187956NCI NIH HHS U01 CA214254NIH HHS CA72851, CA181572, CA187956, CA227602, CA214254, and CA271443
6 · The paper itself

Abstract

backgroundPaclitaxel plus ramucirumab (PTX + RAM) is a widely used second-line treatment for advanced gastric cancer, yet no validated biomarkers exist to predict therapeutic response. Identifying non-invasive predictors could enable patient stratification and optimize outcomes.

methodsWe conducted a prospective observational multicenter study (IVY trial; NCT06490055) enrolling 115 patients with advanced gastric cancer treated with PTX + RAM. Serum was collected prior to the initiation of treatment. Small RNA sequencing identified differentially expressed exosomal microRNAs (exo-miRNAs) in patients with controlled disease versus those with progressive disease. Machine learning and logistic regression were employed to construct a predictive model, which was subsequently validated using quantitative real-time polymerase chain reaction (qRT-PCR) in the entire cohort.

resultsTen candidate exo-miRNAs were initially discovered, and a five-miRNA panel (miR-10a-5p, miR-25-5p, miR-125a-5p, miR-139-5p, and miR-450a-5p) was selected via stepwise elimination. This 5-exo-miRNA model achieved high accuracy in distinguishing controlled disease patients from progressive disease patients (AUC = 0.84). When combined with body mass index (BMI), the composite model (EXEMPLAR) demonstrated enhanced predictive performance (AUC = 0.87). High-risk patients exhibited significantly shorter progression-free survival (PFS: median, 1.9 vs. 4.2 months, p = 0.019) and overall survival (OS: median, 1.1 vs. 1.7 years, p < 0.001). Decision curve analysis confirmed the clinical benefit of the model. A nomogram was developed to facilitate personalized risk assessment.

conclusionsThis study identifies and validates a novel 5-exo-miRNA panel for predicting response to second-line PTX plus RAM therapy in gastric cancer. The combined exosomal signature and BMI risk model provides a clinically applicable, non-invasive tool for personalized treatment selection.

Indexed as

Antineoplastic Combined Chemotherapy ProtocolsBiomarkers, TumorMachine LearningStomach NeoplasmsAdultAgedAntibodies, Monoclonal, HumanizedFemaleHumansLiquid BiopsyMaleMicroRNAsMiddle AgedPaclitaxelPrognosisProspective StudiesAntibodies, Monoclonal, HumanizedBiomarkers, TumorMicroRNAsPaclitaxelRamucirumabBiomarkerExosomal microRNAsGastric cancerLiquid biopsyMachine learningPaclitaxelRamucirumab

Identifiers

PMID41275215
PMCPMC12903554

What Socratic holds

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LicenceCC BY-NC-ND
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Registered trials

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 Socratic graph.