Biology subjects

Koladiya, A.

Publications and source records attributed to Koladiya, A..

6 recordsLinked to original sources

bioRxiv2026

Trp53 heterozygosity defines novel states impacting tumor plasticity and progression in Kras-initiated non-small cell lung cancer

KRAS and TP53 are frequently mutated in non-small cell lung cancer (NSCLC), the leading cause of cancer-related mortality worldwide. The most common event at the TP53 locus is mutation/loss of one allele and retention of a wild-type allele, which confers better survival outcomes than complete TP53 loss. To study the contribution of TP53 heterozygosity, we generated a murine lung tumor model with a KrasG12D mutation and intact (K) or single-allele loss (KP+/-) of Trp53 and compared it with publicly available complete loss (KP) data. K and KP+/- mice lived longer than KP mice, paralleling clinical survival data. Single-cell transcriptomic analysis of tumor-burdened lungs indicated that Trp53 heterozygosity expanded transcriptional plasticity that was not present in K and KP tumors. Genomic instability was also higher in KP+/- mice relative to the KP genotype. Trp53 gene dosage, thus, regulates phenotypic plasticity and evolutionary trajectories of tumor states across K, KP+/-, and KP tumors. Murine KP+/- tumor signatures and copy-number profiles were present in human NSCLC datasets. Two of these signatures correlated with better and worse patient survival outcomes, respectively. TP53 heterozygosity in KRAS-mutant lung cancers presents a distinct genomic landscape that should be taken into account in the development of novel therapeutic strategies.

cancer biology↗

bioRxiv2025

CellFuse Enables Multi-modal Integration of Single-cell and Spatial Proteomics Data

Single-cell and spatial proteomic technologies capture complementary biological information, yet no single platform can measure all modalities within the same cell. Most existing integration methods are optimized for transcriptomic data and rely on a large set of shared, strongly linked features, an assumption that often fails for low-dimensional proteomic modalities. We present CellFuse, a deep learning-based, modality-agnostic integration framework designed specifically for settings with limited feature overlap. CellFuse leverages supervised contrastive learning to learn a shared embedding space, enabling accurate cell type prediction and seamless integration across modalities and experimental conditions. Across a range of datasets including healthy PBMCs, bone marrow, CAR-T-treated lymphoma, and healthy and tumor tissues--CellFuse consistently outperforms existing methods in both integration quality and runtime efficiency. It maintains high accuracy even in the presence of missing markers and rare cell types, and performs robustly in cross-dataset comparisons, making it a powerful tool for scalable and high-fidelity single-cell data integration in basic and translational research.

bioinformatics↗

bioRxiv2025

Single-cell profiling of CAR-T CD19 cell phenotypes and immune system dynamics in pediatric BCP-ALL

BackgroundChimeric Antigen Receptor T-cell (CAR-T) therapy targeting CD19 has transformed the treatment of relapsed/refractory B-cell precursor acute lymphoblastic leukemia (BCP-ALL). However, the phenotypic heterogeneity of CAR+ T-cells and their interactions with the immune system remain poorly understood. Here, we characterize CAR+ T-cell subsets and persistence in patients receiving standard-of-care tisagenlecleucel in an effort to optimize therapeutic efficacy in pediatric BCP-ALL. MethodsNineteen pediatric patients with relapsed/refractory BCP-ALL treated with tisagenlecleucel in Poland were included in the study. CAR+ T-cell composition and the peripheral blood mononuclear cell (PBMC) immune system were assessed using mass cytometry, with qPCR validation of CAR+ T-cells. Machine learning algorithms in R classified phenotypes. Statistical analyses examined associations between CAR+ T-cell subsets, immune system changes, and CAR-T therapy outcomes, including cytokine release syndrome (CRS). ResultsInfusion product analysis showed a predominance of CD4+ Central Memory (16.6%), MAIT/NKT (7.04%), and Treg memory (63.3%) cells, with high consistency between paired products. Post-infusion, CAR+ Treg memory cells declined to <1%, while CD8+ subsets expanded. PBMC immune system analysis revealed increased monocyte and NK cell counts post-infusion. Patients who experienced CRS had fewer classical monocytes at day 7 and fewer transitional monocytes at day 28. Early and late NK cells increased post-infusion in all patients. However, pre-infusion levels were lower in patients experiencing CRS. CRS correlated with higher CAR+ CD8+ Terminal Effector and MAIT/NKT frequencies in infusion products. While CAR+ composition was not linked to disease burden, prior treatments, or therapy outcomes, changes in monocyte and NK cell dynamics were associated with disease burden, relapse, and CRS. ConclusionsThis study provides a detailed characterization of CAR-T CD19 cell composition and post-infusion dynamics in pediatric BCP-ALL patients treated with tisagenlecleucel. Infusion products were predominantly CAR+ CD4+ T cells with a Central Memory phenotype, including a notable Treg memory subset that declined post-infusion. CAR+ CD8+ subsets expanded, coinciding with immune system shifts. These changes correlated with clinical responses, including CRS, highlighting the role of the immune system in CAR-T therapy outcomes and informing strategies to optimize treatment. Summary boxO_ST_ABSWHAT IS ALREADY KNOWN ON THIS TOPICC_ST_ABSCD19-targeted CAR-T therapy has revolutionized the treatment of relapsed/refractory pediatric BCP-ALL. While studies have examined the diverse composition of CAR-T infusion products in adult large B-cell lymphoma (LBCL), there is limited data in the pediatric BCP-ALL setting. WHAT THIS STUDY ADDSThis study demonstrates that standard-of-care CAR-T infusion products (tisagenlecleucel) are primarily composed of CAR+ CD4+ Central Memory and regulatory T cells, which decline post-infusion as CAR+ CD8+ subsets expand. Additionally, monocyte and NK cell dynamics are closely linked to cytokine release syndrome (CRS) and treatment outcomes, emphasizing the critical role of immune system interactions in CAR-T therapy efficacy. HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE, OR POLICYThese findings indicate that monitoring immune system shifts could enhance CRS risk assessment and improve patient stratification, leading to more personalized CAR-T therapy. Additionally, insights into CAR+ T-cell composition may guide the development of strategies to optimize CAR-T efficacy, potentially improving long-term treatment outcomes in pediatric BCP-ALL.

cancer biology↗

bioRxiv2025

Uridine Metabolism as a Targetable Metabolic Achilles' Heel for chemo-resistant B-ALL

Relapse continues to limit survival for patients with B-cell acute lymphoblastic leukemia (B-ALL). Previous studies have independently implicated activation of B-cell developmental signaling pathways and increased glucose consumption with chemo-resistance and relapse risk. Here, we connect these observations, demonstrating that B-ALL cells with active signaling, defined by high expression of phosphorylated ribosomal protein S6 ("pS6+ cells"), are metabolically unique and glucose dependent. Isotope tracing and metabolic flux analysis confirm that pS6+ cells are highly glycolytic and notably sensitive to glucose deprivation, relying on glucose for de novo nucleotide synthesis. Uridine, but not purine or pyrimidine, rescues pS6+ cells from glucose deprivation, highlighting uridine is essential for their survival. Active signaling in pS6+ cells drives uridine production through activating phosphorylation of carbamoyl phosphate synthetase (CAD), the enzyme catalyzing the initial steps of uridine synthesis. Inhibition of signaling abolishes glucose dependency and CAD phosphorylation in pS6+ cells. Primary pS6+ cells demonstrate high expression of uridine synthesis proteins, including dihydroorotate dehydrogenase (DHODH), the rate-limiting catalyst of de novo uridine synthesis. Gene expression demonstrates that increased expression of DHODH is associated with relapse and inferior event-free survival after chemotherapy. Further, the majority of B-ALL genomic subtypes demonstrate activity of DHODH. Inhibiting DHODH using BAY2402232 effectively kills pS6+ cells in vitro, with its IC50 correlated with the strength of pS6 signaling across 14 B-ALL cell lines and patient-derived xenografts (PDX). In vivo DHODH inhibition prolongs survival and decreases leukemia burden in pS6+ B-ALL cell line and PDX models. These findings link active signaling to uridine dependency in B-ALL cells and an associated risk of relapse. Targeting uridine synthesis through DHODH inhibition offers a promising therapeutic strategy for chemo-resistant B-ALL as a novel therapeutic approach for resistant disease.

cancer biology↗

bioRxiv2020

Early immune response in mice immunized with a semi-split inactivated vaccine against SARS-CoV-2 containing S protein-free particles and subunit S protein

The development of a vaccine against COVID-19 is a hot topic for many research laboratories all over the world. Our aim was to design a semi-split inactivated vaccine offering a wide range of multi-epitope determinants important for the immune system including not only the spike (S) protein but also the envelope, membrane and nucleocapsid proteins. We designed a semi-split vaccine prototype consisting of S protein-depleted viral particles and free S protein. Next, we investigated its immunogenic potential in BALB/c mice. The animals were immunized intradermally or intramuscularly with the dose adjusted with buffer or addition of aluminum hydroxide, respectively. The antibody response was evaluated by plasma analysis at 7 days after the first or second dose. The immune cell response was studied by flow cytometry analysis of splenocytes. The data showed a very early onset of both S protein-specific antibodies and virus-neutralizing antibodies at 90% inhibition regardless of the route of vaccine administration. However, significantly higher levels of neutralizing antibodies were detected in the intradermally (geometric mean titer - GMT of 7.8 {+/-} 1.4) than in the intramuscularly immunized mice (GMT of 6.2 {+/-} 1.5). In accordance with this, stimulation of cellular immunity by the semi-split vaccine was suggested by elevated levels of B and T lymphocyte subpopulations in the murine spleens. These responses were more predominant in the intradermally immunized mice compared with the intramuscular route of administration. The upward trend in the levels of plasmablasts, memory B cells, Th1 and Th2 lymphocytes, including follicular helper T cells, was confirmed even in mice receiving the vaccine intradermally at a dose of 0.5 g. We demonstrated that the semi-split vaccine is capable of eliciting both humoral and cellular immunity early after vaccination. Our prototype thus represents a promising step toward the development of an efficient anti-COVID-19 vaccine for human use.

microbiology↗

bioRxiv2018

Rapid single-cell cytometry data visualization with EmbedSOM

Efficient unbiased data analysis is a major challenge for laboratories handling large cytometry datasets. We present EmbedSOM, a non-linear embedding algorithm based on FlowSOM that improves the analyses by providing high-performance visualization of complex single cell distributions within cellular populations and their transition states. The algorithm is designed for linear scaling and speed suitable for interactive analyses of millions of cells without downsampling. At the same time, the visualization quality is competitive with current state-of-art algorithms. We demonstrate the properties of EmbedSOM on workflows that improve two essential types of analyses: The native ability of EmbedSOM to align population positions in embedding is used for comparative analysis of multi-sample data, and the connection to FlowSOM is exploited for simplifying the supervised hierarchical dissection of cell populations. Additionally, we discuss the visualization of the trajectories between cellular states facilitated by the local linearity of the embedding.

bioinformatics↗