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Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
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Biomarker for personalized immunotherapy.

Si-Yang Liu1,2, Yi-Long Wu1,2

  • 1Guangdong Lung Cancer Institute, Guangdong Provincial Key Laboratory of Translational Medicine in Lung Cancer, Guangdong Provincial People's Hospital & Guangdong Academy of Medical Sciences, Guangzhou 510080, China.

Translational Lung Cancer Research
|December 21, 2019
PubMed
Summary
This summary is machine-generated.

Checkpoint blockade immunotherapy shows promise, but programmed cell death 1/programmed death ligand 1 (PD-1/PD-L1) expression and tumor mutation burden (TMB) aren't perfect predictors. Further research into combined biomarkers is crucial for effective patient selection.

Keywords:
Immunotherapybiomarkerprogrammed death ligand 1 (PD-L1)tumor mutation burden (TMB)

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Area of Science:

  • Immunology
  • Oncology
  • Biomarker Discovery

Background:

  • The interaction between Programmed Cell Death 1 (PD-1) and its ligand (PD-L1) is a key mechanism tumors use to evade immune destruction.
  • Checkpoint blockade (CPB) immunotherapy, which targets the PD-1/PD-L1 pathway, has revolutionized cancer treatment by enabling T cells to attack tumor cells.
  • Current biomarkers like PD-L1 expression and tumor mutation burden (TMB) have limitations in predicting patient response to CPB immunotherapy.

Purpose of the Study:

  • To review existing clinical biomarkers for CPB immunotherapy.
  • To explore novel and emerging biomarkers for improved patient stratification.
  • To highlight the potential of combined biomarker strategies in predicting immunotherapy efficacy.

Main Methods:

  • Literature review of clinical studies and preclinical research on cancer immunotherapy biomarkers.
  • Analysis of current data on PD-L1 expression and TMB as predictive markers.
  • Synthesis of evidence regarding other immune-related factors and their potential as biomarkers.

Main Results:

  • PD-L1 expression and TMB are imperfect predictors of response to CPB immunotherapy.
  • Several other immune-related factors show potential as biomarkers for immunotherapy.
  • Combined biomarker approaches demonstrate promise for enhancing patient selection.

Conclusions:

  • Optimizing patient selection for CPB immunotherapy requires moving beyond single biomarkers.
  • Further investigation into a broader range of immune-related biomarkers and their combinations is essential.
  • Future research should focus on developing and validating multi-biomarker panels for personalized cancer immunotherapy.