Tufts University Medford

NIH Research Projects · FY 2025 · 2022-08

PROJECT SUMMARY Head and neck squamous cell carcinoma (HNSCC), particularly the oral cavity cancer (OrCa) is a debilitating disease with no increase in overall survival rate for the past decade and the patients undergo significant physical and psychological toll due to function loss of key organs in the region and cosmetic appearance. Currently the frontline treatment is surgery, where >5-12 mm of normal tissue region beyond tumor margins are resected to achieve clear margins and reduce loco-regional recurrence. Adjuvant radiotherapy and chemotherapy are administered based on the tumor stage, however these therapies had severe toxicity and provided no added benefit. Overall, there is a dire need for spatially localized therapeutic tools that can aid in tumor eradication entirely or reduce the tumor burden sufficiently for optimal surgical resection with reduced normal tissue removal. Photodynamic Therapy (PDT) is an effective, spatially localized cancer treatment with minimal damage to healthy tissues. Despite its low-cost, success in reducing tumor burden, and excellent healing post-treatment of the oral mucosa, PDT has yet to become a mainstream frontline therapy primarily because PDT efficacy in solid tumors depends on significant accumulation of the photosensitizer (PS) at the tumor site, availability of oxygen near the PS, and effective dosing of the PS-light irradiation combination. Our new nano-platform, Verosite, enhances all three of these parameters, in addition to aiding image-guided surgery, poising it to significantly improve HNSCC patient outcomes. Verosite (Verteporfin, Oxygen and Sensing Targeted platform) is a perfluorocarbon (PFC) based nanoplatform that contains Indocyanine green (ICG) dye for photoacoustic (PAI) and fluorescence (FLI) imaging contrast, PS verteporfin and oxygen for effective PDT, and will be targeted to Epidermal Growth Factor Receptor (EGFR), a cell surface biomarker significantly overexpressed in OrCa. Once specifically accumulated at the tumor, absorption of light by ICG will trigger a liquid to gas phase change of the PFC serves the purpose to spatio-temporally deliver PS and O2 for effective PDT. Motivated by our promising preliminary data, we hypothesize that best treatment outcomes (reduced tumor burden, low recurrence and enhanced quality of life with minimal loss of normal tissue and function) will be obtained with Verosite enabled image-guided surgery and oxygen enhanced PDT. We evaluate the hypothesis in three specific aims: Aim-1: Synthesize, optimize, and characterize the Verosite platform, Aim-2: Establish Verosite NDs biodistribution, pharmacokinetics and dose requirements for PDT in orthotopic OrCa murine models with varying EGFR expression and Aim-3: Demonstrate that Verosite enabled oxygen enhanced PDT and fluorescence image-guided surgery will aid in minimal normal tissue resection and enhance survival in various orthotopic OrCa models. Overall, our customizable multi-functional Verosite platform will enhance PDT efficacy and can be adapted to alleviate hypoxia in many oxygen-dependent therapies for a broad array of solid tumors.

NIH Research Projects · FY 2025 · 2022-06

Project Summary This R21/R33 proposal is submitted in response to PAR-20-133. The proposal focuses on the development of an ingestible device termed “micro-pill”. The micro-pill will be designed to autonomously sample intestinal content from predetermined anatomical sites in the gastrointestinal (GI) tract, a process which currently requires invasive methods. The development of the micro-pill benefits from the applicants' experimentation with an earlier version of the pill that utilizes an osmotic pump for sampling. To ensure accurate sampling of GI luminal content from specific anatomical sites, the micro-pill will be fitted with a miniaturized motor controlled by pH and pO2 sensors. The concept takes advantage of the proximal-to-distal rising pH and falling oxygen gradient, such that the micro-pill will sample autonomously based on pre-programmed pH and O2 thresholds. This innovative control mechanism is optimal for this application because it dispenses with the need for tomography or built-in camera that may be needed to track the pill's location for spatially selective sampling. The new micro-pill will run on power from a coin cell battery and will also support wireless magnetic activation in individuals where pH/pO2 levels may be altered due to atypical GI tract conditions. The architecture of the micro-pill is optimized to enable sampling of viscous intestinal content and reduce leakage and contamination, while maximizing the volume of sample collected and maintaining low specific weight for improved buoyancy and motility through the GI tract. During the R21 phase micro-pill prototypes will be built and tested in vitro in conditions simulating the viscosity of the GI lumen and ex vivo in pig intestines. Optimized designs will be tested in live pigs. The R21 phase is organized in 3 specific aims: (1), To design, fabricate and validate in vitro a motorized micro-pill; (2) To design, integrate and test pH/pO2 sensors in vitro and ex vivo using electronics integrated in the micro-pill; (3) To test the ingestible micro-pill in live pigs in vivo. The aims of the R33 phase are to assess the efficacy of the micro- pill (4) and conducting a 2-phase randomized controlled cross-over diet trial in humans (5). In Specific aim 4 the feasibility of sampling human adults' luminal content from pre-determined GI tract regions will be tested in a clinical trial. The trial will not only assess the micro-pill's function, but also compare the effects of a plant-based and a meat-based diet on the GI tract microbiota collected from different anatomical GI sites. This proposal was conceived by three Tufts University researchers with complementary expertise. PI Dr. Sameer Sonkusale from the School of Engineering heads an interdisciplinary Nano Lab and specializes in micro- and nano-fabrication, and biomedical devices. Dr. Giovanni Widmer from the School of Veterinary Medicine has extensive experience with animal models, microbiota analysis and bioinformatics. Dr. Alice H Lichtenstein at the Jean Mayer USDA Human Nutrition Research Center for Aging brings to the project years of experience with diet-related human intervention trials.

NIH Research Projects · FY 2026 · 2022-01

Project Summary Chemotherapy remains the standard of care for patients with triple-negative breast cancer (TNBC), which affects 20% of patients with breast cancer. However, 50% of patients with localized TNBC treated with neoadjuvant chemotherapy display residual cancer burden after treatment and up to 25% of patients who receive this treatment will suffer metastatic recurrence within five years. The poor association between chemotherapy and patient outcome emphasizes two major problems for TNBC patients: chemoresistance, where tumor cells within the local environment are protected and do not die in response to chemotherapy, and chemotherapy-induced metastasis, where chemotherapy-induced changes in tumor intrinsic properties and the tumor microenvironment drive invasion which leads to recurrence. Previous studies have demonstrated that cell migration and extracellular matrix (ECM) remodeling are associated with chemoresistant TNBC. The goal of this proposal is to understand the mechanisms by which the ECM contributes to chemoresistance and chemotherapy-induced metastasis in TNBC. We provide preliminary data that individual proteins upregulated in TNBC tumors drive resistance to chemotherapy drug Paclitaxel and that expression of Cathepsin B (CTSB), a protease which degrades these ECM proteins into small fragments, protects against the development of chemoresistance. We will dissect the mechanism by which the protease CTSB and the ECM proteins it degrades influence response to Paclitaxel in TNBC and whether these fragments can be used to track and target chemoresistance in vivo. We have also found that chemotherapy treatment leads to changes in the ECM composition of mammary tumors. Specifically, Paclitaxel treatment leads to an increased abundance of Collagen IV, an ECM protein which promote invasion and metastasis in TNBC. Our goal is to determine the cell types that secrete ECM proteins such as Collagen IV after chemotherapy treatment, determine the contribution of these ECM proteins to chemotherapy-induced metastasis, and whether these pathways can be targeted to prevent the development of recurrence. Upon successful completion of the proposed research, our contribution is expected to be an understanding of how ECM proteins upregulated in TNBC tumors contribute to chemoresistance and how chemotherapy alters the ECM to promote recurrence and metastatic dissemination. These contributions will be significant because all TNBC patients receive chemotherapy and metastatic recurrence is a current unmet clinical need. Results from these studies will provide novel conceptual insights on mechanisms of chemoresistance and chemotherapy-induced metastasis and will allow us to develop new strategies to track, predict and overcome chemoresistance in TNBC.

NIH Research Projects · FY 2026 · 2022-01

Project Summary/Abstract Almost half of the human genome is composed of repetitive DNA elements, and about three percent of the genome is composed of microsatellites, short tandem repeats of 1-6 DNA bases. Many repeat sequences can form alternative DNA structures that interfere with replication and repair. This can lead to disease-causing repeat expansions, such as the CAG/CTG expansions that cause Huntington’s disease, myotonic dystrophy, and many spinocerebellar ataxias. Breaks within structure-forming repeats cause chromosome deletions and rearrangements, which are common in cancer cells undergoing replication stress. The goal of my laboratory is to study mechanisms of genome instability caused by structure-forming repeats, and to elucidate cellular pathways that have evolved to prevent these deleterious mutations. We recently discovered that long tracts of structure-forming CAG repeats relocate to the nuclear periphery to facilitate replication through the tract and prevent chromosome breakage and repeat expansions. This pathway depends on modification of proteins at the replication fork by sumoylation, and subsequent interaction of the sumoylated proteins with components of the nuclear pore complex (NPC) in late S phase, followed by release back into the nuclear interior in G2 phase. Recent data shows that this pathway is relevant for several types of replication barriers, including protein blocks and other structure-forming repeats. Therefore, it is vital to better understand the purpose of this relocation to the NPC and its role in facilitating replication and preventing genome instability, which is our long- term goal. We have developed a system to follow the location of an expanded CAG tract or other structure- forming repeats in the cell nucleus using microscopy, complemented by biochemical techniques to detect proteins interacting with the repeat locus. We will use the budding yeast (S. cerevisiae) system which allows us to combine these approaches with the powerful genetics of the yeast system. Yeast replication and repair pathways retain a high level of conservation with human cells, but the smaller size of the yeast genome and proteome and wild-type (non-transformed) state of cells are advantages that will allow us to make significant progress on our goals. We plan to elucidate the purpose of relocation of stalled replication forks to the nuclear pore complex and the mechanisms that occur there to allow restart of replication forks, using both established and novel approaches. We will also determine how nuclear pore-linked fork restart prevents chromosome breaks and repeat instability and determine how repeat expansions occur during fork recovery. Our aim is to understand NPC-dependent modification of replisome-associated proteins and fork remodeling that occurs at replication barriers, and in so doing understand vital cellular processes that maintain genome stability. This is important because understanding how mutations arise is critical to developing strategies to prevent their occurrence.

NIH Research Projects · FY 2024 · 2021-09

Project summary Metastasis, the dissemination of cells from the primary tumor to other organs in the body, leads to 90% of the 1,800 daily cancer deaths. Cell invasion is an essential feature of tumorigenesis, which is necessary for tumor growth, local invasion and metastatic outgrowth. The local tumor microenvironment, composed of stromal and immune cells, the vasculature and extracellular matrix, provides tumor cells with numerous chemical, biophysical and electrical cues that promote local invasion and support tumorigenesis. However, one major component of the TME whose function has not been well studied and whose therapeutic potential in cancer has not been explored is nerves. Perineural invasion has been associated with tumor aggressiveness by providing a path for cancer cell invasion, however, for a long time, these nerves were not seen as major drivers of tumor growth and metastasis. The lack of clinical approaches to prevent, diagnose and treat metastatic disease are largely due to a poor understanding of targetable pathways for preventing and treating migrating cells. My goal is to investigate a poorly studied component of tumors: their neuronal identity, which will provide new strategies for prevention and targeting of metastatic cancer. First, we will focus on elucidating the mechanisms by which neoneurogenesis of solid tumors occurs, which will lead us to evaluate the systemic effects of nerves on local invasion and metastasis. Second, we will dissect the neuronal identity of epithelial tumors, by studying how neuronal mimicry in metastasizing cells contributes to tumor progression. Together, our findings will contribute to the development of non-invasive monitoring of neuronal activity in solid tumors and the repurposing of FDA-approved drugs that target neuronal function for use in metastatic disease. The research described in this proposal has the potential to impact both our basic understanding of the role of the TME in tumor metastasis as well as lead to the development of novel detection and treatment approaches for metastatic disease. The neuronal identity of tumors is not well understood. Nerves have mostly been regarded as passive bystanders to dissemination and deemed to contribute to tumor phenotypes only via the molecules they secrete. A thorough literature review identified fewer than 40 primary papers directly investigating tumor cell-cancer crosstalk in solid tumors, and fewer than 7 papers focused on breast cancer. The majority of published studies focus on the central nervous system. With over 90% of tumors occurring outside of the brain, it is critical that we gain a better understanding of how peripheral nerves interact with tumor cells. The extensive and unique expertise of Dr. Oudin in both in neuroscience and cancer metastasis suggests her lab provides the perfect setting in which to study this novel topic.

NIH Research Projects · FY 2024 · 2021-08

Project Summary The need for efficient methods for the production of well-defined oligosaccharides continues to present a major bottleneck in the field of microbial glycobiology. Although automated oligosaccharide synthesizers have been developed, most rely on solid-phase synthesis, which can limit the chemistry and scale of synthesis available to them. Furthermore, existing automated approaches to oligosaccharide synthesis have focused almost exclusively on glycosylation reactions, and do not address the time-consuming and tedious process of converting monosaccharide feedstocks into fully-substituted glycosyl donors ready for coupling. The incredible number of building blocks required for microbial glycan synthesis also makes keeping every possible block in stock impossible. All these issues could be addressed by the development of automated continuous flow platforms. Continuous flow reactions can be more easily automated than multi-step batch processes and thereby provide greater batch-to-batch reproducibility. Through proper selection of conditions it is also possible to telescope several reactions into a single run. The objective of this proposal is to generate platform technologies for automated continuous flow-based oligosaccharide that is capable of automating every step of oligosaccharide synthesis, from on-demand donor/acceptor production to assembly of these larger molecules into target structures. We will achieve this by pursuing the following Specific Aims. Specific Aim 1 will examine the automated production of glycosylation ready monosaccharides. By telescoping multiple reactions into a single run and designing and controlling the system with open-source MechWolf software, this approach will allow for the construction of these important intermediates from commercial feedstock in much more rapid timescales than is currently possible. This will include developing rapid chemo-enzymatic syntheses of otherwise difficult to access nonulosonic (9-carbon) acid carbohydrate building blocks commonly associated with several pathogenic microbes. In addition, the MechWolf program will provide an open-source chemical repository for optimal conditions for the production of any protected monosaccharide to ensure batch-to-batch reproducibility and on-demand access of these building blocks. Specific Aim 2 will extend this technology to the automated production of oligosaccharides. The flexible and modular nature of continuous flow synthesis will allow for the construction of glycosidic linkages that are not trivial to make on existing platforms and for which few if any enzymes are available. As proof of principle, the system will be used to construct several capsular polysaccharides associated with the ESKAPE pathogen Acinetobacter baumannii; however, these technologies and concepts could be used for the construction of any oligosaccharide. Taken together, the technologies developed through this research will lead to a rapid, robust, reproducible, and affordable method for automated oligosaccharide production with minimal need for human optimization and intervention.

NIH Research Projects · FY 2025 · 2021-08

PROJECT SUMMARY/ABSTRACT Bladder cancer is common cancer with an estimated 81,190 new cases and 17,240 deaths in 2018 (with > 500,000 survivors) only in the US. The gold standard for diagnosis of bladder cancer includes an invasive optical bladder examination (cystoscopy) and tumor resection for pathology examination. Because of a high recurrence rate of this cancer (50-80%), frequent (once every 3-6-12 months) costly and invasive cystoscopy exams are required to monitor patients for recurrence and/or progression to a more advanced stage. It makes bladder cancer the most expensive cancer to monitor/follow up and treat per patient. Moreover, the invasive nature of the current standard of care, cystoscopy, causes rather low compliance of patient to follow this procedure. There is an urgent unmet need for a bladder cancer screening and monitoring test, which will be noninvasive, rapid, objective, reproducible, easy to perform and interpret, and highly accurate. Such a test will reduce the need in frequent cystoscopies and greatly expand the participation of patients in screening and early detection programs because it decreases the patient discomfort and post-procedural complications. Here we propose to develop such a test for identification of the presence of bladder cancer and its aggressiveness (grade). It will be based on non-invasive analysis of individual cells extracted from urine (extraction technology already exists in hospitals for voided urine cytology tests, (VUC) the current standard-of- care, a non-invasive examination of cells in urine used to assist with cancer diagnosis and surveillance). A novel modality of Atomic Force Microscopy (AFM) will be used for nanoscale imaging of cells extracted from urine, mapping/imaging of the physical properties of the cell surface. The collected images will further be analyzed using machine-learning methods and novel advanced statistical approaches to identify a “digital signature” of cancer. The proposed technology is fundamentally different from previously studied urine biomarkers and all existing physical methods because it is based on the analysis of physical properties of the cell surface, not cell bulk or presence of biochemical markers or genetic analysis. Our strong preliminary results demonstrate the feasibility of the proposed approach, its presumed superiority compared to the currently used non-invasive methods, and lead us to the central hypothesis that bladder cancer can be identified by analyzing a small number of cells randomly chosen from urine samples, with a low sampling error. This is a substantial departure from VUC tests, which require a visual analysis of many cells. Supported by the preliminary data, we propose (1) to optimize and expand the method, (2) to define the accuracy of cancer detection on a large cohort of patients, and (3) to assess the accuracy of identification of aggressiveness (low versus high grade) of bladder cancer. Our long-term goal is to develop a non-invasive clinical method for accurate detecting of presence and monitoring bladder cancer as well as many other cancers, in which cells can be extracted from easily accessible bodily fluids without the need for tissue biopsy (e.g urine-bladder & upper urinary tract cancer, stool- colorectal cancer, sputum-aerodigestive cancer, cervical smears-cervical cancer etc.), using methods based on the analysis of physical characteristics of the cell surface. The proposed research, which is the first step in pursuit of this overarching goal.

NIH Research Projects · FY 2026 · 2019-07

Antibodies and other binding proteins are indispensable tools for molecular recognition, but these protein- based reagents lack key chemical features found in small molecules that mediate enzyme inhibition, covalent target engagement, and other function-disrupting bioactivities. I hypothesize that “chemically expanding” antibodies using genetic code manipulation offers opportunities to discover unique, function-disrupting hybrids that cannot be accessed using conventional proteins or small molecules. To realize the full potential of this approach, my group is integrating noncanonical amino acid (ncAA) incorporation with yeast display. We have previously A) characterized and improved genetic code expansion in yeast to broaden access to ncAAs during yeast display; and B) discovered potent, “chemically expanded” enzyme inhibitors in high-throughput screens. Building off of these initial successes, we propose to pursue the following three directions: Direction 1: “Harmonize” yeast ncAA incorporation systems with tools available in other cell types to expand antibody chemical diversity. Most tools for genetic code expansion are incompatible with the yeast translation apparatus or are otherwise poorly active in yeast. We propose to adapt a versatile existing orthogonal translation system (OTS) used in E. coli and mammalian cells for use in yeast. Our engineering approach leverages our OTS engineering expertise and has the potential to dramatically but efficiently expand the chemistries available for genetic code expansion in yeast. Direction 2: Elucidate combinations of molecular and genetic/genomic engineering strategies that improve ncAA incorporation in yeast. Our prior work has identified several approaches to enhancing ncAA incorporation in yeast, including unprecedented strain engineering and translation apparatus engineering. We propose to investigate which combinations of strategies yield additive or synergistic improvements to ncAA incorporation. These are fundamentally important investigations of genetic code expansion systems that, to our knowledge, have never been studied in any organism. Direction 3: Illuminate the interplay between chemical functionality and synthetic antibody diversity during enzyme inhibitor discovery. NcAAs enable presentation of chemistries that inhibit enzymes via rapid bioorthogonal conjugations and directly through ncAA side chain chemistries. We propose to use first-generation and newly designed second-generation ncAA-containing antibody libraries in combination with metalloproteinase and protein tyrosine phosphatase targets to understand how to best leverage both conjugates and directly encoded chemistries during inhibitor discovery. Our uniquely positioned research program will reveal crucial principles of protein biosynthesis and enzyme inhibitor discovery while establishing powerful tools (genetic code expansion systems and enzyme inhibitors) for understanding and treating human disease.

NIH Research Projects · FY 2026 · 2019-03

Project Summary The focus of my lab is to understand the mechanisms of genome instability caused by structure-prone DNA repeats. We are particularly interested in the mechanisms of repeat expansions that are responsible for over fifty hereditary diseases in humans. Recent advances in long-read sequencing revealed a new paradigm: massive genome-wide expansions of structure-prone DNA repeats in human cancers. Thus, understanding the mechanisms responsible for large-scale repeat expansions is fundamentally important and has broad biomedical implications. My lab was the first to show that expandable DNA repeats stall replication fork progression in every experimental system studied, including bacteria, yeast, and human cells. This led us to propose that repeats can be added while replication fork escapes from a “repetitive trap”. We first confirmed this idea in a yeast experimental system. Depending on the mode of replication fork progression through a repeat, expansions occur by incorporation of unprocessed flaps during Okazaki fragments maturation, replicative or post-replicative template-switching, or break-induced replication. Recently, we developed a new experimental system to study large-scale expansions in human cells, which implicates DNA replication as well. Repeat expansions also occur in terminally differentiated somatic cells that do not undergo DNA replication. We have, therefore, adjusted our experimental system to study repeat expansions in non- dividing yeast cells. Our results point to DNA nick repair as a possible mechanism. We plan to move our research in several directions. First, we will elucidate the role of DNA nick repair in expansions of Friedreich’s ataxia (FRDA) (GAA)n repeats in dividing and non-dividing yeast cells by introducing targeted nicks with Cas9 nickases. We will establish its genetic controls and study the role of the human FAN1 nuclease expressed in yeast. Second, we will unravel the mechanisms of large-scale repeat expansions in human cells by conducting candidate gene analysis in a plasmid system utilizing SV40 replication machinery. We will also study the effects of compounds that disrupt or stabilize DNA triplexes formed by these repeats on their replication and expansion. We will further extend our studies into a different system based on the EBNA1-dependent replication which involves regular cellular replication fork. Third, we will carry out structure-functional analysis of other expandable homopurine-homopyrimidine repeats, including the (AAGGG)n repeat, which is responsible for cerebellar ataxia, neuropathy, vestibular areflexia syndrome (CANVAS), the (CCCTCT)n repeat that modifies the expressivity of X-linked dystonia parkinsonism (XDP), and the (GAAA)n repeat, which recurrently expands in many human cancers. At present, there are no data on DNA structures formed by those repeats or on the mechanisms of their expansions. We will address these matters by using the broad arsenal of methods and experimental systems developed and existing in the lab.

NIH Research Projects · FY 2025 · 2017-09

A robust ability to selectively modulate protein–protein interactions (PPIs) would provide a valuable means to control specific biological processes for therapeutic intervention. Unfortunately, owing to their flat and large interfaces, PPIs are challenging targets for traditional small molecule drugs. Cyclic peptides represent a promising solution to target PPIsthey can directly mimic the binding functionalities at the PPIs and have enhanced biostability and bioavailability compared to their linear counterparts. However, there are only ~50 cyclic peptide drugs. Most are simply natural products or their derivatives, rather than deriving from successful de novo cyclic peptide development. A major reason why the design of novel, functional cyclic peptides has proven difficult is the need to simultaneously optimize multiple drug-related properties of cyclic peptides, e.g., binding affinity, water solubility, and membrane permeability. Because cyclic peptides often have ≤12 residues and are connected in a ring, even changing one amino acid can dramatically alter the properties of cyclic peptides. Hence, changing cyclic peptide sequences to optimize for one property often negatively impacts other properties. Machine learning (ML), now widely used to build predictive models for drug properties, holds enormous potential to guide successful cyclic peptide design. Unfortunately, the few attempts at ML models to predict cyclic peptide properties perform quite poorly. The core challenge is that most cyclic peptides, including the current cyclic peptide drugs, adopt multiple conformations in water. It is, therefore, difficult for ML models to decipher how sequence modifications impact the complicated structural ensembles of cyclic peptides, which in turn influence their properties. If we can provide the ML models with this missing structural information, we will greatly improve their performance in predicting cyclic peptide properties. Since no robust experimental methods are available to characterize and quantify the conformations in a cyclic peptide structural ensemble, computational chemistry represents a logical alternative. Although recent work has revealed that explicit-solvent molecular dynamics (MD) simulation is capable of providing high-quality structural predictions of cyclic peptides, it is far too slow to be used at scale. On the other hand, computational methods that provide speedy predictions for cyclic peptide structural ensembles are inaccurate. Our long-term objective is a reliable, robust, and user-friendly platform for the computational design of potent, bioavailable cyclic peptides targeting PPIs. In our first aim, we use explicit-solvent MD results of diverse sequences as training datasets to build novel ML models that can predict cyclic peptide structural ensembles, preserving both accuracy and speed. In our second aim, we use these high-quality structural ensembles as a new descriptor for ML inputs to enable the training of high-performing ML models to predict cyclic peptide properties. In our third aim, we demonstrate that these new computational platforms allow us to develop potent cyclic peptide protein binders and PPI inhibitors.