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Tumor progression is a phenomenon where the pre-formed tumor acquires successive mutations to become clinically more aggressive and malignant. In the 1950s, Foulds first described the stepwise progression of cancer cells through successive stages.
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Inferring evolutionary trajectories from cross-sectional transcriptomic data to mirror lung adenocarcinoma

Kexin Huang1,2, Yun Zhang1, Haoran Gong2

  • 1School of Life Science and Technology, Xidian University, Xi'an, China.

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This study introduces a computational method to map lung adenocarcinoma (LUAD) progression using gene expression data. The findings reveal key molecular events and genetic factors driving LUAD evolution, aiding in cancer management.

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Area of Science:

  • Oncology
  • Computational Biology
  • Genomics

Background:

  • Lung adenocarcinoma (LUAD) is a significant cause of cancer mortality.
  • Understanding the molecular mechanisms driving LUAD progression is crucial for effective treatment.
  • Current methods struggle to fully capture the dynamic evolutionary patterns of LUAD.

Purpose of the Study:

  • To develop a computational approach for inferring LUAD progression trajectories from transcriptomic data.
  • To identify molecular events and genetic factors associated with LUAD development and metastasis.
  • To analyze clonal evolution and mutation accumulation during LUAD progression.

Main Methods:

  • Developed a computational model to infer cancer progression trajectories from cross-sectional transcriptomic data.
  • Analyzed LUAD data across three independent cohorts to validate the inferred trajectory.
  • Utilized genome-wide association analysis to identify LUAD susceptibility genetic variations.
  • Investigated clonal architectures and mutation accumulation along the progression trajectory.

Main Results:

  • Identified a linear progression trajectory with three distinct branches for malignant LUAD.
  • Overexpression of BUB1B, BUB1, and BUB3 was linked to proliferation and metastasis via spindle assembly checkpoint (SAC) disruption.
  • The inferred trajectory facilitated the identification of LUAD susceptibility genetic variations.
  • Observed clear evidence of mutation accumulation and clonal expansion along the LUAD progression pathway.
  • Distinct clones and subclones were identified within different LUAD branches.

Conclusions:

  • Aberrant mitotic spindle checkpoint signaling is a key driver of LUAD progression.
  • Combining genetic factor analysis with disease progression models offers new avenues for LUAD research.
  • The developed computational approach is effective and unbiased for analyzing LUAD evolution and guiding cancer management.