Biology subjects

Chadokiya, J.

Publications and source records attributed to Chadokiya, J..

3 recordsLinked to original sources

bioRxiv2026

Patient-Derived Melanoma Organoids Preserve Tumor-Immune Heterogeneity and Reveal Context-Dependent Responses to Immune Checkpoint Blockade

Abstract Background: Experimental models that retain endogenous tumor immune complexity are needed to investigate heterogeneous responses to immune checkpoint inhibitors (ICIs) in melanoma. We established patient-derived melanoma organoids (PDMOs) to examine retention of parental tumor cellular components and investigate patient-specific and context-dependent responses to checkpoint blockade. Methods: Fresh melanoma specimens (n=50), including primary tumors, neoadjuvant-treated tumors and tumor-infiltrating lymphocyte (TIL) associated samples were processed for Matrigel-embedded culture of patient-derived melanoma organoids (PDMOs). Characterization and functional studies were performed in subsets of established cultures. Immunofluorescence assessed tumor, stromal, immune, and checkpoint-marker expression in PDMOs and matched parental tissues. NGFR expression was evaluated in relation to organoid establishment and growth. Responses to anti PD1 alone or combined with anti-LAG3 or anti-CTLA4 therapies were evaluated using viability and morphological analyses, with selected models undergoing immune phenotyping and multiplex cytokine profiling. Available clinical outcomes were used for exploratory comparison. PDMOs and matched two-dimensional cultures were evaluated under 21% and 5% oxygen conditions. Results: PDMOs were established from 30 of 50 specimens (60%) and retained melanoma, stromal, lymphoid, and myeloid components identified in matched parental tissues during early culture, together with immune checkpoint expression. Higher NGFR (CD271) expression was associated with greater organoid-forming capacity in an exploratory subset. Responses to checkpoint blockade varied across patient-derived models and regimens, with combination blockade not uniformly producing lower viability than PD1 monotherapy. Ex vivo responses showed parallels with available clinical outcomes, with discordant cases also observed. In three selected PDMOs, divergent PD-1 responses were accompanied by differences in T-cell and myeloid representation, MHCII and AXL expression, and inflammatory versus immunoregulatory cytokine profiles. Under normoxic conditions, PDMOs and matched two-dimensional cultures exhibited divergent treatment sensitivities, including clinically responding cases in which sensitivity was retained in PDMOs but attenuated in monolayers. Changing oxygen tension further altered checkpoint sensitivity within individual PDMOs, with the direction and magnitude of the observed shifts varying by model and regimen. Conclusions: Early passage PDMOs retain key endogenous tumor, immune, and stromal components and support functional investigation of patient-derived melanoma biology. Their heterogenous responses across checkpoint regimens and oxygen conditions provide a platform for investigating how tumor-immune composition and environmental context influence treatment sensitivity.

immunology↗

bioRxiv2025

Predicting targeted- and immunotherapeutic response outcomes in melanoma with single-cell Raman Spectroscopy and AI

PURPOSEIdentifying reliable predictors of immunotherapeutic response in melanoma remains an outstanding challenge. Existing transcriptomic and proteomic profiling methods for the tumor-immune microenvironment (TIME) are costly and may not faithfully capture modifications actively impacting tumor behavior. Here, we present a non-destructive, single-cell approach combining Raman spectroscopy and machine learning (ML) that enables rapid cell profiling and therapeutic response prediction. METHODSWe analyzed single-cell Raman spectra of mouse and human melanoma cell lines alongside nine melanoma patient-derived samples with known resistance profiles to targeted and immunotherapeutic inhibitors bemcentinib, cabozantinib, dabrafenib, nivolumab, and a combination of nivolumab and relatlimab. We assessed cell phenotyping classification and treatment resistance using random forests and feature importance analysis. For patient samples, we constructed a two-stage evaluation workflow to determine clinical drug resistance through aggregated single-cell predictions and identified corresponding highly variant spectral signatures using computational methods adapted from single-cell RNA sequencing methods. RESULTSIn cell lines, our approach achieved >96% differentiation accuracy across tumor microenvironment cell types and induced functional phenotypes. Persistent (drug-resistant) cells formed subclusters based on genetic mutations rather than sample origin, with Raman signatures reflecting biochemical changes relevant to therapeutic pathways. For patient samples, our workflow correctly inferred resistance likelihoods for 30 of 33 clinically-relevant patient-drug combinations (91% accuracy). CONCLUSIONSingle-cell Raman spectroscopy combined with machine learning offers a scalable, prognostic platform to predict therapeutic resistance likelihood, with further potential to advance clinical, multi-omic biomarker efforts for melanoma. Our approach may improve first-and second-line therapy selection assessments for precision medicine by providing rapid, non-destructive prediction of therapeutic response based on cellular spectral profiles. Context SummaryO_ST_ABSKey objectiveC_ST_ABSCan label-free, single-cell Raman spectroscopy and machine learning approach accurately profile melanoma cell states and therapeutic resistance likelihood to targeted and immunotherapeutic agents? Knowledge generatedRaman spectroscopy with machine learning differentiated tumor microenvironment cell types and functional phenotypes with >96% accuracy in cell lines. When applied to patient-derived metastatic melanoma samples, the approach correctly inferred patient response to a panel of targeted and immunotherapeutic inhibitors with 91% accuracy (30 of 33 cases). High-likelihood persistent and sensitive cells across diverse patients exhibited recurrent spectral features. RelevanceSingle-cell Raman-based profiling supports functional-diagnostic assessment or resistance likelihood and may contribute to improved therapeutic selection and precision oncology strategies for melanoma patients.

cancer biology↗

bioRxiv2025

Antibody-Free Immunopeptide Nano-Conjugates for Brain-Targeted Drug Delivery in Glioblastoma Multiforme

Glioblastoma Multiforme (GBM) represents a significant clinical challenge amongst central nervous system (CNS) tumors, with a dismal mean survival rate of less than 8 months, a statistic that has remained largely unchanged for decades (National Brain Society, 2022). The specialized intricate anatomical features of the brain, notably the blood-brain barrier (BBB), pose significant challenges to effective therapeutic interventions, limiting the potential reach of modern advancements in immunotherapy to impact these types of tumors. This study introduces an innovative, actively targeted immunotherapeutic nanoconjugate (P12/AP-2/NCs) designed to serve as an immunotherapeutic agent capable of traversing the BBB via LRP-1 receptor-mediated transcytosis. P12/AP-2/NCs exert its immune-modulating effects by inhibiting the PD-1/PD-L1 axis through a small-size PD-L1/ PD-L2 antagonist peptide Aurigene NP-12 (P12). P12/AP-2/NCs are synthesized from completely biodegradable, functionalized high molecular weight {beta}-poly(L-malic acid) (PMLA) polymer, conjugated with P12 and Angiopep-2 (AP2) to yield P12/AP-2/NCs. Evaluating nanoconjugates for BBB permeability and 3-D tumor model efficacy using an in vitro BBB-Transwell spheroid based model demonstrating successful crossing of the BBB and internalization in brain 3D tumor environments. In addition, the nanoconjugate mediated T cells cytotoxicity on 3D tumor region death in a U87 GBM 3-D spheroid model. AP2/P12/NCs is selectively inhibited in PD1/PDL1 interaction on T cells and tumor site, increasing inflammatory cytokine secretion and T cell proliferation. In an in-vivo murine brain environment, rhodamine fluorophore-labeled AP2/P12/NCs displayed significantly increased accumulation in the brain during 2-6 h time intervals post-injection with a prolonged bioavailability over unconjugated peptides. AP2/P12/NCs demonstrated a safety profile at both low and high doses based on major organ histopathology evaluations. Our findings introduce a novel, programmable nanoconjugate platform capable of penetrating the BBB for directed delivery of small peptides and significant immune environment modulation without utilizing antibodies, offering promise for treating challenging brain diseases like glioblastoma multiforme and beyond.

immunology↗