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September 25, 2025Open Access

Integrating machine learning and single-cell sequencing to reveal the role of kinase-related genes in subtype classification and prognostic significance of lung squamous cell carcinoma

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Authors

YLYan LvXLXinji LiuZXZhihan Xiao

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Overview

Research reveals prognostic significance of kinase-related genes in lung squamous cell carcinoma subtypes, suggesting novel treatment paths.

Key Points

  • Identifying 13 kinase-related genes enhances understanding of subtype prognosis in lung squamous cell carcinoma.
  • Differentially expressed genes led to the classification of lung cancer patients into four subtypes based on prognosis.
  • Machine learning and single-cell sequencing explored tumor microenvironmental differences in relation to immune responses.
  • Prognostic models relying on key genes showed promising potential for predicting chemotherapy responses and patient outcomes.

Cite This Study

Lv et al. (2025) studied this question.

synapsesocial.com/papers/68d5e1ffbd7882ccb9b86710https://doi.org/10.21203/rs.3.rs-6477524/v1
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