Cancer remains one of the leading causes of mortality worldwide, with treatments like chemotherapy for malignancies such as leukemia, breast cancer, and non-small cell lung cancer often relying on "one-size-fits-all" guidelines derived from population-level statistics. This approach frequently results in suboptimal outcomes, including drug resistance, severe side effects, and missed therapeutic windows. APOPTO-SENSE 2.0 is an innovative synthetic biology platform designed to enable rapid, quantitative ex vivo drug sensitivity testing using a dual-cell biosensing system. By engineering sensor cells to detect apoptosis in patient-like tumor cells, our system provides a proof-of-concept for personalized medicine, transforming cancer treatment from empirical to precise and individualized.
Drawing from advances in synthetic Notch (synNotch) receptors and apoptosis biomarkers, APOPTO-SENSE 2.0 integrates live-cell engineering with co-culture assays to convert phosphatidylserine (PS) exposure—a hallmark of early apoptosis—into measurable fluorescent signals. This not only addresses current limitations in drug screening but also paves the way for broader applications in oncology, including multiplexed detection of diverse cell death pathways.
Current chemotherapy regimens for aggressive cancers are selected based on large-scale clinical data, often ignoring individual tumor biology. This leads to significant challenges:
As a result, there is an urgent need for a fast, affordable, and scalable platform to predict drug responses at the individual level, enabling truly personalized oncology.
APOPTO-SENSE 2.0 aims to develop an intelligent biosensing system that rapidly quantifies chemotherapy-induced apoptosis in tumor cells, providing actionable insights for personalized treatment. By leveraging synthetic biology, we create a "oracle-like" dual-cell system where engineered sensor cells "sense" apoptotic signals from target tumor cells and report them via amplified, dose-dependent outputs.
Core Innovation: Our system detects PS externalization on apoptotic cells—a reliable, early apoptosis marker—using a modular synNotch receptor. This non-enzymatic signal transduction ensures specificity and avoids interference with endogenous pathways. As a minimum viable product (MVP), we focus on linear amplification for dose-dependent responses, with future expansions to feedback loops and multiplexed detection.
This proof-of-concept validates the feasibility of synthetic biology in oncology, potentially reducing treatment failures and improving patient outcomes. For details on experimental validation, see Experiments and Results.
APOPTO-SENSE 2.0 comprises two complementary cell types in a co-culture setup:
Workflow:
We engineered a synNotch receptor, a highly modular synthetic biology tool previously used in iGEM for antigen sensing, to recognize PS on apoptotic cells.
Rationale: SynNotch's modularity allows customization, ensuring specificity to apoptosis without cross-reactivity to healthy cells.
To convert sensor activation into a quantifiable output, we designed a linear amplification circuit as our MVP, avoiding "all-or-nothing" responses from positive feedback loops.
Rationale: This design ensures linearity (proportional to apoptotic cell input), critical for dose-response curves in drug testing. Future iterations could incorporate orthogonal systems (e.g., TetR) for multiplexing.
For engineering details and iterations, see Engineering.
Our wet lab validation focused on HL-60 (leukemia model) and HEK293T cells:
Results demonstrated specific, dose-dependent activation (see Results for figures showing elevated TagBFP in apoptotic co-cultures).
APOPTO-SENSE 2.0 represents a paradigm shift in cancer diagnostics, bridging synthetic biology with clinical oncology. Its significance lies in enabling rapid (hours to days) prediction of drug responses, potentially reducing chemotherapy failures by 20-30% based on PDC correlation studies.
This project not only contributes standardized BioBricks to the iGEM registry but also inspires future teams through our "Mammalian Synthetic Receptor Design Toolkit" (see Contributions).