Biology subjects

Chaudhari, R.

Publications and source records attributed to Chaudhari, R..

8 recordsLinked to original sources

bioRxiv2025

Guiding treatment response by spatiotemporal control of α-particle deposition in solid tumors: the case for 'affinity cocktails' of antibody-radioconjugates

Antibody-radioconjugates are leading the investigational targeted alpha-particle (-particle) therapies for the treatment of solid tumors that do not respond to approved therapies. Yet, there is still treatment failure in the clinic largely attributed to the heterogenous patterns of tumor irradiation by -particles. Although -particles are essentially impervious to resistance, attributed to the complex double-strand DNA breaks they cause while traversing cells, cells not being directly hit by -particles will likely not be killed. The diffusion-limited poor tumor penetration of high-affinity (strongly-binding) antibody-radioconjugates combined with -particles short-range in tissue (only 40-80m), let tumor regions far from vasculature inadequately irradiated, therefore, possibly escaping treatment. METHODSTo improve penetration of delivered activity within tumors, we engineered separate actinium-225 antibody-radioconjugates of variable affinities ( affinity cocktails) targeting the same marker on cancer cells, that were chosen based on their preferential irradiation of complementary regions of the same tumors. The cocktails comprise: (a) high-affinity antibody-radioconjugates (as the ones on clinical trials), which mostly deliver their cargo in tumor cells close to the vasculature, where the low(er)-affinity antibody-radioconjugates fail to deliver effective doses, due to their fast clearance; and (b) low(er)-affinity antibody-radioconjugates, that penetrate the deeper parts of tumors farther from the vasculature, where the high-affinity antibodies fail to reach. The efficacy of affinity cocktails was assessed in spheroids, that were employed as surrogates of tumor avascular regions, and on mice with subcutaneous xenografts of different cancer origin, expression levels and/or type of the targeted receptor: HER2 highly-expressing BT-474 breast cancer cells, HER2 moderately-expressing HEPG2 hepatoma cells, and/or HER1 low-expressing BxPC-3 pancreatic cancer cells. RESULTSAlthough the high-affinity antibody-radioconjugates were most lethal against cancer cells in monolayers, affinity cocktails were most effective in inhibiting spheroid growth, due to better collective spreading of the antibody-conjugates within the spheroids volume. On all mouse models, and for the same total injected activity, affinity cocktails resulted in the best tumor growth inhibition, even at lower tumor absorbed doses, compared to the high-affinity antibody-radioconjugates alone. CONCLUSIONSThis proof-of-concept study in -particle antibody-delivery to solid tumors demonstrates that separating the two key processes of diffusion and reaction/binding improves treatment efficacy. This generalizable approach may augment antibody-radioconjugates already in clinical trials.

bioengineering↗

bioRxiv2025

Inflammatory Agonists Modulate the Host Response to Type 2 ECM scaffold Immune Environment and Long-Term Remodeling After Severe Traumatic Injury

The immune system is a vital regulator of tissue repair after trauma and the response to implantable scaffolds for regenerative medicine. Decellularized extracellular matrix (ECM) scaffolds promote tissue integration and remodeling following traumatic injury in part due initiating a pro-reparative Type-2 immune response. However, exogenous soluble inflammatory immune signals can be introduced during scaffold implantation, including microbial products in contaminated surgical fields or during immunotherapy to treat autoimmunity and cancer. It remains largely unknown how such immune mediators modulate the ECM scaffold immune environment and subsequent scaffold remodeling. In the present study, we co-delivered 3 distinct inflammatory immune adjuvants (cyclic di-AMP [CDA], monophosphoryl lipid A [MPLA], and granulocyte colony stimulating factor [GM-CSF]) with small intestinal submucosa (SIS) ECM in a murine volumetric muscle loss injury model, evaluating acute (1 week) and long-term (8-week) immune environments and scaffold remodeling. High parameter spectral cytometry, histologic analysis, and PCR revealed differential potentiation of the ECM scaffold microenvironment. Type 2 immune programs including IL-4, eosinophils, CD4 T cells, and CD206/CD86 macrophage ratios were induced in all ECM groups but attenuated by varying amounts with the CDA and MPLA co-delivery. By 8-weeks, inflammation had largely subsided, and histologically ECM with GM-CSF or MPLA showed the greatest degradation and remodeling into adipose tissue. These findings suggest that early pro-inflammatory compound delivery does not abrogate the ECM immune environment but does attenuate some programs while inducing others. These have long-term effects on scaffold remodeling and should be a consideration for surgical reconstruction in patients receiving immune stimulatory therapies.

immunology↗

bioRxiv2025

Overcoming Immune Checkpoint Inhibitor Resistance via Potent and Selective Dual αvβ6/8 Inhibitors Based on Engineered Lasso Peptides

Integrins v{beta}6 and v{beta}8 in the tumor microenvironment (TME) have been shown to activate immunosuppressive TGF-{beta}, which serves as an important mechanism for immune checkpoint inhibitor resistance in a range of tumors. In this study, we demonstrate the utility of lasso peptides as versatile scaffolds for designing new therapeutics. A series of highly potent and selective dual v{beta}6/8 inhibitors were engineered through a combination of epitope scanning, computational design, and directed evolution. Several analogs, such as lassotides 36 and 47, were fully characterized and physicochemical, in vitro pharmacological, and in vivo data are reported. Lassotide 47, a half-life extended derivative of 36, was shown to strongly sensitize anti-mPD-1-resistant tumors in mice when dosed in combination with the checkpoint inhibitor. The 47/anti-mPD-1 combination was shown to halt tumor growth and regress tumors in mouse models of triple negative breast and ovarian cancers. Dual inhibition of v{beta}6/8 integrins expressed in the TME thus represents a promising tumor-specific strategy to overcome TGF-{beta}-driven resistance and enhance the anti-tumor efficacy of immune checkpoint inhibitors.

cancer biology↗

bioRxiv2024

Structure of a lasso peptide bound ETB receptor provides insights into the mechanism of GPCR inverse agonism

Lasso peptides exhibit a unique lariat-like knotted structure imparting exceptional stability and thus show promise as therapeutic agents that target cell-surface receptors. One such receptor is the human endothelin ETB receptor, which is implicated in challenging cancers with poor immunotherapy responsiveness. The Streptomyces-derived lasso peptide, RES-701-3, is a selective inhibitor for ETB and a compelling candidate for therapeutic development. However, meager production from a genetically recalcitrant host has limited further structure-activity relationship studies of this potent inhibitor. Here, we report cryo-electron microscopy structures of ETB receptor in both its apo form and complex with RES-701-3, facilitated by a calcineurin-fusion strategy. Hydrophobic interactions between RES-701-3 and the transmembrane region of the receptor, especially involving two tryptophan residues, play a crucial role in RES-701-3 binding. Furthermore, RES-701-3 prevents conformational changes associated with G-protein coupling, explaining its inverse agonist activity. A comparative analysis with other lasso peptides and their target proteins highlights the potential of lasso peptides as precise drug candidates for G-protein-coupled receptors. This structural insight into RES-701-3 binding to ETB receptor offers valuable information for the development of novel therapeutics targeting this receptor and provides a broader understanding of lasso peptide interactions with human cell-surface receptors.

biochemistry↗

bioRxiv2023

Extracellular matrix scaffold-assisted tumor vaccines induce tumor regression and long-term immune memory

Injectable scaffold delivery is an immune engineering strategy to enhance the efficacy and reliability of cancer vaccine immunotherapy. The composition and structure of the biomaterial scaffold determines both vaccine release kinetics and inherent immune stimulation via the scaffold host response. Extracellular matrix (ECM) scaffolds prepared from decellularized tissues initiate an acute alternative inflammatory response following implantation, which facilitates wound healing following tumor resection and promotes local cancer immune surveillance. However, it remains unknown whether this environment is compatible with generating protective anti-tumor cytotoxic immunity with local immunotherapy delivery. Here, we engineered an ECM scaffold-assisted therapeutic cancer vaccine that maintained an immune microenvironment consistent with tissue reconstruction. Immune adjuvants MPLA, GM-CSF, and CDA were screened in a cancer vaccine formulated for decellularized small intestinal submucosa (SIS) ECM scaffold co-delivery. Though MPLA and GM-CSF showed the greatest increase in local myeloid cell infiltration, we found that the STING pathway adjuvant CDA was the most potent inducer of cytotoxic immunity with SIS-ECM scaffold delivery. Further, CDA did not diminish hallmark ECM immune responses needed in wound healing such as high Il4 cytokine expression. SIS scaffold delivery enhanced therapeutic vaccine efficacy using CDA and the antigen ovalbumin, curing greater than 50% of established EG.7 tumors in young mice and 75% in 24-week-old mature mice, compared to soluble components alone (0% cured). SIS-ECM scaffold assisted vaccination extended antigen exposure, was dependent on CD8+ cytotoxic T cells, and generated long term anti-tumor memory at least 7 months post-vaccination in both young and mature-aged mice. This study shows that an ECM scaffold is a promising delivery vehicle to enhance cancer vaccine efficacy while being orthogonal to characteristics of pro-healing immune hallmarks.

bioengineering↗

bioRxiv2022

Sequence-based Optimized Chaos Game Representation and Deep Learning for Peptide/Protein Classification

As an effective graphical representation method for 1D sequence (e.g., text), Chaos Game Representation (CGR) has been frequently combined with deep learning (DL) for biological analysis. In this study, we developed a unique approach to encode peptide/protein sequences into CGR images for classification. To this end, we designed a novel energy function and enhanced the encoder quality by constructing a Supervised Autoencoders (SAE) neural network. CGR was used to represent the amino acid sequences and such representation was optimized based on the latent variables with SAE. To assess the effectiveness of our new representation scheme, we further employed convolutional neural network (CNN) to build models to study hemolytic/non-hemolytic peptides and the susceptibility/resistance of HIV protease mutants to approved drugs. Comparisons were also conducted with other published methods, and our approach demonstrated superior performance. Supplementary informationavailable online

bioinformatics↗

bioRxiv2020

JavaDL: a Java-based Deep Learning Tool to Predict Drug Responses

MotivationAccurate prediction of drug response in each patient is the holy grail in personalized medicine. Recently, deep learning techniques have been witnessed with revival in a variety of areas such as image processing and genomic data analysis, and they will be useful for the coming age of big data analysis in pharmaceutical research and chemogenomic applications. This provides us an impetus to develop a novel deep learning platform to accurately and reliably predict the response of cancer to different drug treatments. ResultsIn this study, we describe a Java-based implementation of deep neural network (DNN) method, termed JavaDL, to predict cancer responses to drugs solely based on their chemical features. To this end, we devised a novel cost function by adding a regularization term which suppresses overfitting. We also adopted an "early stopping" strategy to further reduce overfit and improve the accuracy and robustness of our models. Currently the software has been integrated with a genetic algorithm-based variable selection approach and implemented as part of our JavaDL package. To evaluate our program, we compared it with several machine learning programs including SVM and kNN. We observed that JavaDL either significantly outperforms other methods in model building and prediction or obtains better results in handling big data analysis. Finally, JavaDL was employed to predict drug responses of several highly aggressive triple-negative breast cancer cell lines, and the results showed robust and accurate predictions with r2 as high as 0.80. AvailabilityThe program is freely available at https://imdlab.mdanderson.org/JavaDL/JavaDL.php.

bioinformatics↗

bioRxiv2017

Glutathione And Thioredoxin Systems Of The Malaria Parasite Plasmodium falciparum: Partners In Crime?

In P. falciparum, antioxidant proteins of the glutathione and thioredoxin systems are compartmentalized. Some subcellular compartments have only a partial complement of these proteins. This lack of key anti-oxidant proteins in certain sub-cellular compartments might be compensated by functional complementation between these systems. By assessing the cross-talk between these systems, we show for the first time, that the glutathione system can reduce thioredoxins that are poor substrates for thioredoxin reductase (Thioredoxin-like protein 1 and Thioredoxin 2) and thioredoxins that lack access to thioredoxin reductase (Thioredoxin 2). Our data suggests that crosstalk between the glutathione and thioredoxin systems does exist; this could compensate for the absence of certain antioxidant proteins from key subcellular compartments.

biochemistry↗