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Related Experiment Video

Updated: May 28, 2026

Primary Sjogren's Syndrome Associated with Lung Adenocarcinoma: Probing the Potential Common Pathogenic Mechanisms and Experimental Verification
10:21

Primary Sjogren's Syndrome Associated with Lung Adenocarcinoma: Probing the Potential Common Pathogenic Mechanisms and Experimental Verification

Published on: September 20, 2024

Integrative Multi-Omics Analysis Identifies IL18R1 as a Circulating Prognostic Biomarker for Risk Stratification in

Shengjuan Hu1, Sicong Li2, Yiyuan Cui2

  • 1Department of Hematology and Oncology, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing 100700, China.

Cancers
|May 27, 2026
PubMed
Summary

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Non-LTR Retrotransposons03:18

Non-LTR Retrotransposons

As the name suggests, non-LTR retrotransposons lack the long terminal repeats characteristic of the LTR retrotransposons. Additionally, both LTR and non-LTR retrotransposons use distinct mechanisms of mobilization. Non-LTR retrotransposons are further divided into two classes - Long interspersed nuclear elements (LINEs) and short interspersed nuclear elements (SINEs), both of which occur abundantly in most mammals, including humans. Some of the active non-LTR retrotransposons in humans are L1...

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This summary is machine-generated.

This study identifies ACE, AGER, and IL18R1 as protective factors against small cell lung cancer (SCLC) progression. Plasma IL18R1 combined with clinical data offers a new prognostic tool for extensive-stage SCLC patients.

Area of Science:

  • Oncology
  • Genomics
  • Biomarker Discovery

Background:

  • Small cell lung cancer (SCLC) has a poor prognosis and lacks effective biomarkers for risk stratification.
  • Identifying circulating prognostic biomarkers is crucial for improving patient outcomes.
  • This study focuses on discovering novel biomarkers for SCLC risk stratification.

Purpose of the Study:

  • To identify circulating prognostic biomarkers for small cell lung cancer (SCLC).
  • To develop a diagnostic and prognostic model using machine learning and multi-omics data.
  • To validate the prognostic utility of the identified biomarker IL18R1 in a prospective cohort.

Main Methods:

  • Integrative multi-omics analysis (pQTL/eQTL, differential expression, WGCNA) to prioritize SCLC risk-associated genes.
Keywords:
IL18R1biomarkermachine learningsingle-cell analysissmall cell lung cancer

Related Experiment Videos

Last Updated: May 28, 2026

Primary Sjogren's Syndrome Associated with Lung Adenocarcinoma: Probing the Potential Common Pathogenic Mechanisms and Experimental Verification
10:21

Primary Sjogren's Syndrome Associated with Lung Adenocarcinoma: Probing the Potential Common Pathogenic Mechanisms and Experimental Verification

Published on: September 20, 2024

  • Machine learning approaches (Elastic Net, LASSO-Cox) to develop diagnostic and prognostic models.
  • Single-cell transcriptomics and prospective clinical cohort validation of IL18R1 as a prognostic biomarker.
  • Main Results:

    • ACE, AGER, and IL18R1 were identified as SCLC-protective genes.
    • A two-gene signature (AGER, IL18R1) demonstrated robust diagnostic accuracy.
    • Lower plasma IL18R1 levels independently predicted shorter progression-free survival (PFS) in extensive-stage SCLC patients.
    • A prognostic model integrating plasma IL18R1 and clinical parameters stratified patients into distinct risk groups.

    Conclusions:

    • ACE, AGER, and IL18R1 are protective factors against SCLC progression.
    • Plasma IL18R1 is a promising prognostic biomarker for extensive-stage SCLC.
    • Integrating plasma IL18R1 with clinical variables provides a valuable prognostic tool for extensive-stage SCLC.