Unlocking the Genetic Enigma: Estimating the Hidden Horde of Barcoded Cancer Cells using a Molecular German Tank Problem Approach

Abstract

Abstract Accurate estimation of the number of undetected cancer cells after treatment is of paramount importance in oncology to gauge treatment efficacy and potential disease recurrence. Drawing inspiration from the German tank problem, we present a novel sampling-based molecular approach to estimate the population of elusive cancer cells that remain undetected by current molecular techniques. This study proposes an innovative approach to be undertaken in the future for estimating the number of undetected cancer cells post-treatment. Inspired by the renowned German tank problem, our sampling-based molecular methodology involves creating a unique molecular barcode representing the increasing mutations in cancerous cells over time. By collecting serial samples from cancer patients after treatment, we aim to statistically analyze and develop a robust estimation model to infer the total number of undetected cancer cells. The validation of this approach using an independent patient cohort would help ensure its reliability. Successful implementation of this methodology has the potential to revolutionize cancer research, providing crucial insights into residual cancer cell populations and facilitating the development of personalized treatment strategies. Ultimately, this future research endeavor could significantly impact cancer care, leading to improved patient outcomes and advancing our understanding of post-treatment cancer dynamics. This innovative approach may transform cancer research and improve patient outcomes by offering insights into the post-treatment cancer landscape that was hitherto concealed.