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SIMD: Synergistic integration mutualistic platform based on single-cell and proteotranscriptomics for drug

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A new platform integrates single-cell and proteotranscriptomics for drug repositioning in breast cancer. This approach identifies novel drug candidates by analyzing molecular dynamics and tumor heterogeneity, showing promise for personalized treatments.

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Area of Science:

  • Oncology
  • Computational Biology
  • Genomics

Background:

  • Breast cancer exhibits significant tumor heterogeneity, complicating treatment strategies.
  • Existing drug repositioning methods often overlook the dynamic interplay between protein and transcriptomic data at the single-cell level.

Purpose of the Study:

  • To introduce a synergistic integration platform for drug repositioning (SIMD) in breast cancer.
  • To leverage single-cell and proteotranscriptomics to identify novel drug candidates by considering molecular dynamics and tumor heterogeneity.

Main Methods:

  • Developed the anti-correlated proteotranscriptome perturbation score (ACPS) to measure negative correlations between molecular signatures.
  • Utilized perturbagen repositioning scoring and single-cell RNA sequencing (scRNA-seq) data (PPNE) to rank potential drug candidates.
  • Validated top-ranked drug candidates by assessing their impact on breast cancer cell line viability.

Main Results:

  • The SIMD platform successfully prioritized drug candidates for breast cancer.
  • Many top-ranked candidates have prior clinical trial involvement for various cancers.
  • Experimental validation demonstrated significant reductions in cell viability for most prioritized perturbagens across breast cancer cell lines.
  • Identified overexpressed phosphorylation sites in AKT1 and PI3K genes, suggesting buparlisib's potential efficacy across diverse breast cancer subtypes, including triple-negative breast cancer.

Conclusions:

  • The SIMD platform offers a novel approach for drug repositioning in breast cancer.
  • The findings support buparlisib's potential therapeutic role in breast cancer by targeting the PI3K pathway.
  • This integrated omics strategy holds promise for advancing precision oncology and personalized medicine.