Abstract:
Breast cancer is a significant global health concern and one of the primary causes of cancer
related mortality among women. The current diagnostic methods often suffer from limitations
in sensitivity, specificity, and multiplex detection capacity, especially in early-stage cancers.
This study presents a novel approach that leverages synthetic biology and CRISPR technology
to design a programmable biosensing system for breast cancer detection. The core objective
was to computationally develop a Clustered Regularly Interspaced Short Palindromic Repeats
- CRISPR-associated protein 13 (CRISPRCas13) based biosensor capable of detecting three
critical breast cancer biomarkers HER2, MUC1, and EGFR, using synthetic genetic logic circuits.
Specific guide RNAs (gRNAs) were designed to selectively bind and activate the Cas13
enzyme in response to target mRNA sequences. Logic circuits implementing AND, OR, and
NOT gates were constructed using synthetic promoters, terminators, and fluorescent reporters
such as GFP and RFP. These gene circuits were modeled and simulated using COPASI software
to assess logic functionality, signal dynamics, and noise robustness. Results demonstrated that
the AND gate activated only when HER2 and MUC1 were simultaneously present, the OR gate
responded to any of the three biomarkers, and the NOT gate suppressed output in the presence
of EGFR. Simulation outputs confirmed high specificity, sensitivity, and system stability under
varying biomarker concentrations. The circuits are conceptually adaptable for microfluidic integration
and point of care applications. This computational framework shows significant promise
in building next-generation diagnostic tools with customisable logic-based biosensing capabilities.
Future directions include experimental validation, real-time reporter optimisation, and
integration into portable diagnostic platforms. This work lays the groundwork for personalised
and logic-based diagnostics, offering a flexible platform for broader clinical and translational
applications.
