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Precise Gene Signature for Predicting Outcomes in PDAC

NCT05441189 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 70

Last updated 2022-07-07

No results posted yet for this study

Summary

The current TNM staging system is not sufficient for prediction of prognosis and cannot precisely identify the patients who are in greater need of adjuvant therapy in pancreatic ductal adenocarcinoma (PDAC). Tumor mutation and copy number variation (CNV) markers may have a higher predictive value. In this study, whole exosome sequencing was performed for patients with stage I-II PDAC undergoing R0 resection. The investigators aimed to identify genes with discrepant statuses of mutations or CNVs between patients with and without relapse within 1 year after R0 resection, and then to construct a support vector machine (SVM)-based prognostic classifier (the SVM signature) for PDAC using machine learning; the investigators then aimed to further validate the SVM signature in an independent cohort.

Conditions

  • Stage I-II Pancreatic Ductal Adenocarcinoma (PDAC)
  • Precise Prognostic and Predictive Signature

Interventions

PROCEDURE

Resection

radical R0 resection of pancreatic adenocarcinoma

Sponsors & Collaborators

  • The Fourth Affiliated Hospital of Anhui Medical University

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2021-04-19
Primary Completion
2022-05-01
Completion
2022-06-22

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05441189 on ClinicalTrials.gov