Prostate cancer heterogeneity assessment with multi-regional sampling and alignment-free methods

Area of Science:

• Genomics
• Computational Biology
• Oncology

Background:

• Intra-patient tumor heterogeneity poses challenges for effective cancer treatment.
• Traditional methods may not adequately capture the genetic diversity within a single patient's tumor.
• Accurate assessment of tumor heterogeneity is crucial for selecting optimal therapies.

Purpose of the Study:

• To assess intra-patient tumor heterogeneity using alignment-free phylogenetic methods and multi-regional sampling.
• To validate the utility of these methods in identifying distinct tumor lesions within a patient.
• To demonstrate the potential for rapid identification of aberrant biomarkers and targetable pathways.

Main Methods:

• Application of alignment-free phylogenetic analysis to multi-regional next-generation sequencing data.
• Utilizing a novel alignment-free method for single-nucleotide variant calling.
• Analysis of clinical multi-regional samples from prostate cancer patients.

Main Results:

• Successfully validated two distinct lesions within a patient's prostate, highlighting genetic divergence.
• Demonstrated the capacity to rapidly decipher intra-patient heterogeneity and identify potential biomarkers.
• Identified specific variants and genomic locations differentiating major tumor branching patterns.

Conclusions:

• Alignment-free approaches combined with multi-regional sampling offer a powerful tool for assessing tumor heterogeneity.
• This methodology can significantly reduce the time required for heterogeneity analysis compared to traditional methods.
• The findings support the use of these tools for personalized medicine, enabling more robust identification of therapeutic strategies and patient-aligned treatment indications.