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Systemic inflammation biomarkers can identify high tumor mutation burden in lung adenocarcinoma

  • 0Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, China.
Bmc Cancer +

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October 9, 2025

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October 9, 2025

View abstract on PubMed

Summary

This summary is machine-generated.

Systemic inflammation markers like NLR and PLR can help identify high tumor mutational burden (TMB) lung cancer patients, potentially reducing the need for costly whole-exome sequencing (WES). This offers a more accessible approach to predicting immunotherapy response in non-small cell lung cancer (NSCLC).

Area Of Science

  • Oncology
  • Genomics
  • Immunotherapy

Background

  • Tumor mutational burden (TMB) is a key biomarker for predicting immunotherapy efficacy in non-small cell lung cancer (NSCLC).
  • Whole-exome sequencing (WES) for TMB assessment is costly and has stringent sample requirements, limiting clinical use.
  • Accessible systemic inflammation markers may predict high TMB in lung cancer populations.

Purpose Of The Study

  • To evaluate the predictive value of systemic inflammation markers for identifying high TMB lung cancer.
  • To explore the association between inflammation markers and specific mutation patterns in lung adenocarcinoma.

Main Methods

  • Whole-exome sequencing (WES) on 72 lung adenocarcinoma patients' tumor and blood samples.
  • Analysis of systemic inflammatory markers: neutrophil-to-lymphocyte ratio (NLR), derived neutrophil-to-lymphocyte ratio (dNLR), lymphocyte-to-monocyte ratio (LMR), and platelet-to-lymphocyte ratio (PLR).
  • Statistical modeling (generalized linear models, restricted cubic splines, XGBoost) to assess marker predictive value for TMB.

Main Results

  • High TMB group showed increased C>A variants and higher frequencies of TP53 and TTN mutations.
  • Elevated NLR and PLR, and reduced LMR were significantly associated with higher TMB.
  • Non-linear associations observed between TMB and NLR/PLR; T stage, LMR, and BMI were key predictors in the XGBoost model.

Conclusions

  • Distinct mutational profiles exist across different TMB groups in Chinese lung adenocarcinoma patients.
  • Systemic inflammation markers (NLR, PLR, LMR) show potential as preliminary indicators for high TMB lung cancer.
  • These markers may offer a more accessible method for identifying patients likely to benefit from immunotherapy.

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