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Detection of cancer at an early stage when it is still localized improves patient response to medical interventions for most cancer types. The success of screening tools such as cervical cytology to reduce mortality has spurred significant interest in new methods for early detection (for example, using non-invasive blood-based or biofluid-based biomarkers). Yet biomarkers shed from early lesions are limited by fundamental biological and mass transport barriers - such as short circulation times and blood dilution - that limit early detection. To address this issue, synthetic biomarkers are being developed. These represent an emerging class of diagnostics that deploy bioengineered sensors inside the body to query early-stage tumours and amplify disease signals to levels that could potentially exceed those of shed biomarkers. These strategies leverage design principles and advances from chemistry, synthetic biology and cell engineering. In this Review, we discuss the rationale for development of biofluid-based synthetic biomarkers. We examine how these strategies harness dysregulated features of tumours to amplify detection signals, use tumour-selective activation to increase specificity and leverage natural processing of bodily fluids (for example, blood, urine and proximal fluids) for easy detection. Finally, we highlight the challenges that exist for preclinical development and clinical translation of synthetic biomarker diagnostics.

Detection of cancer at an early stage when it is still localized improves patient response to medical interventions for most cancer types. The success of screening tools such as cervical cytology to reduce mortality has spurred significant interest in new methods for early detection (for example, using non-invasive blood-based or biofluid-based biomarkers). Yet biomarkers shed from early lesions are limited by fundamental biological and mass transport barriers - such as short circulation times and blood dilution - that limit early detection. To address this issue, synthetic biomarkers are being developed. These represent an emerging class of diagnostics that deploy bioengineered sensors inside the body to query early-stage tumours and amplify disease signals to levels that could potentially exceed those of shed biomarkers. These strategies leverage design principles and advances from chemistry, synthetic biology and cell engineering. In this Review, we discuss the rationale for development of biofluid-based synthetic biomarkers. We examine how these strategies harness dysregulated features of tumours to amplify detection signals, use tumour-selective activation to increase specificity and leverage natural processing of bodily fluids (for example, blood, urine and proximal fluids) for easy detection. Finally, we highlight the challenges that exist for preclinical development and clinical translation of synthetic biomarker diagnostics.

This thesis describes the development of DNA-encoded, multi-parametric, sensing platforms for informative cancer diagnostics. In the first part of this thesis, I will present a technology called “DNA-encoded antibody library (DEAL).” In this approach, computationally derived, orthogonal ssDNA sequences are conjugated to antibodies specific for protein targets and cell surface markers. The resulting collection of conjugates is applied to a biological sample of interest, binds to their cognate antigens, and is detected after the complexes are hybridized to a glass substrate printed with spatially distinct complementary DNA sequences. By using DNA assembly, the DEAL platform enables the simultaneous detection of the major classes of biological molecules, namely nucleic acids, proteins and cells. The second part of this thesis focuses on the development of a cell sorting platform that can detect antigen-specific T cells called “Nucleic Acid Cell Sorting (NACS).” In NACS, ssDNA encoding is used to assemble peptide major histocompatability complexes (p/MHC) on glass substrates by hybridization to cDNA microarrays. These assembled peptide/MHC microarrays are then used to sort mixed populations of antigen-specific T cells. This spatially encoded scheme addresses the widespread desire for methods that allow the multiplexed detection of antigen-specific T cells. The sensitivity and selectivity of NACS is similar to flow cytometry, demonstrated in key experiments with T cells derived from multiple sources, including endogenous and TCR-engineered T cells collected from cancer patients. Finally, this platform is used to monitor the persistence of cancer-specific T cells in peripheral blood collected from a patient undergoing T cellular immunotherapy. Lastly, a scheme for the detection of cell surface markers is presented. In this approach, DEAL and NACS conjugates prepared with UV labile ssDNA oligonucleotides are allowed to bind to target cell samples in soluti

Advances in nanomedicine are providing sophisticated functions to precisely control the behavior of nanoscale drugs and diagnostics. Strategies that coopt protease activity as molecular triggers are increasingly important in nanoparticle design, yet the pharmacokinetics of these systems are challenging to understand without a quantitative framework to reveal nonintuitive associations. We describe a multicompartment mathematical model to predict strategies for ultrasensitive detection of cancer using synthetic biomarkers, a class of activity-based probes that amplify cancer-derived signals into urine as a noninvasive diagnostic. Using a model formulation made of a PEG core conjugated with protease-cleavable peptides, we explore a vast design space and identify guidelines for increasing sensitivity that depend on critical parameters such as enzyme kinetics, dosage, and probe stability. According to this model, synthetic biomarkers that circulate in stealth but then activate at sites of disease have the theoretical capacity to discriminate tumors as small as 5 mm in diameter—a threshold sensitivity that is otherwise challenging for medical imaging and blood biomarkers to achieve. This model may be adapted to describe the behavior of additional activity-based approaches to allow cross-platform comparisons, and to predict allometric scaling across species., MIT Desphande Center for Technological Innovation, National Science Foundation (U.S.). Graduate Research Fellowship, Burroughs Wellcome Fund (Career Award at the Scientific Interface)

Antithrombotic therapy is a critical portion of the treatment regime for a number of life-threatening conditions, including cardiovascular disease, stroke, and cancer; yet, proper clinical management of anticoagulation remains a challenge because existing agents increase the propensity for bleeding in patients. Here, we describe the development of a bioresponsive peptide–polysaccharide nanocomplex that utilizes a negative feedback mechanism to self-titrate the release of anticoagulant in response to varying levels of coagulation activity. This nanoscale self-titrating activatable therapeutic, or nanoSTAT, consists of a cationic thrombin-cleavable peptide and heparin, an anionic polysaccharide and widely used clinical anticoagulant. Under nonthrombotic conditions, nanoSTATs circulate inactively, neither releasing anticoagulant nor significantly prolonging bleeding time. However, in response to life-threatening pulmonary embolism, nanoSTATs locally release their drug payload and prevent thrombosis. This autonomous negative feedback regulator may improve antithrombotic therapy by increasing the therapeutic window and decreasing the bleeding risk of anticoagulants., National Institutes of Health (U.S.) (R01CA124427-01), National Cancer Institute (U.S.) (U54CA119349), National Cancer Institute (U.S.) (U54CA119335), National Cancer Institute (U.S.) (Center of Cancer Nanotechnology Excellence at MIT-Harvard U54CA151884), David & Lucile Packard Foundation (Fellowship), David H. Koch Institute for Integrative Cancer Research at MIT (Marie D. and Pierre Casimir-Lambert Fund), National Cancer Institute (U.S.) (Koch Institute Support (Core) Grant P30-CA14051), MIT-Harvard Center of Cancer Nanotechnology Excellence (5 U54 CA151884-03), National Institutes of Health (U.S.). Medical Scientist Training Program (T32GM007753), National Institutes of Health (U.S.) (Ruth L. Kirschstein National Research Service Award F32CA159496-02), Burroughs Wellcome Fund (Career Award at the Scientific Interface)