Biology subjects

Khalaj, M.

Publications and source records attributed to Khalaj, M..

4 recordsLinked to original sources

bioRxiv2026

Quantum-Classical Reservoir Computing to Predict Influenza H3N2 Antigenic Distance

Accurate prediction of antigenic distance between influenza A/H3N2 strains is essential for timely vaccine strain selection, yet traditional hemagglutination inhibition (HI) assays are labour-intensive and limited in throughput. We present FluQRC, a hybrid Quantum-Classical Reservoir Computing framework for sequence-based antigenic distance prediction. FluQRC integrates three novel components: (1) a differentiable gated property ranking network for data-driven property selection, (2) a dimensionality reduction network that compresses the feature representation into a form suitable for quantum processing, and (3) a hybrid quantum-classical reservoir computing architecture for antigenic distance prediction. Experiments on two datasets covering 1963-2002 (271 strains, 73,441 pairs) and 2003-2025 (888 strains, 788,544 pairs) show that FluQRC outperforms four established baselines across all three evaluation metrics (MAE, RMSE, R2). On the larger and more challenging 2003-2025 dataset, FluQRC achieves MAE = 0.369, RMSE = 0.635, and R2 = 0.900, corresponding to a 20.3% reduction in MAE and a 14.3% reduction in RMSE relative to the strongest baseline, while raising R2 from 0.862 to 0.900. These results demonstrate the scalability and effectiveness of FluQRC for large-scale antigenic distance prediction.

bioinformatics↗

bioRxiv2025

High-Throughput Screening on Primary Tumor-Associated Microglia and Macrophages Identifies HDAC Inhibitors as Enhancers of Phagocytosis and Potent Partners for Immunotherapy in Glioblastoma

Glioblastoma multiforme (GBM) is a lethal brain tumor with limited treatment options. Tumor-associated macrophages and microglia (TAMs) drive immune suppression and tumor progression, making them a key therapeutic target for GBM. Enhancing TAM phagocytosis in GBM has shown promise, particularly with innate checkpoint inhibitors, such as CD47-blocking antibodies. However, small molecule approaches, which offer tunable and potentially synergistic mechanisms, remain underexplored in this context. In this study, we conducted the first large-scale chemical screen on primary TAMs from patients with GBM, identifying histone deacetylase (HDAC) inhibitors as potent inducers of phagocytosis. These compounds demonstrated phagocytosis-inducing effects across multiple GBM patient samples, with further amplification when combined with CD47 blockade. In a xenograft GBM model, HDAC inhibitors enhanced phagocytosis and suppressed tumor growth, with even greater efficacy in combination with CD47 antibodies. Our findings highlight HDAC inhibitors as promising agents to reprogram TAMs and synergize with immune checkpoint therapies, offering a novel strategy to bolster anti-tumor immunity in GBM.

cancer biology↗

bioRxiv2024

Perturbation-aware predictive modeling of RNA splicing using bidirectional transformers

Predicting molecular function directly from DNA sequence remains a grand challenge in computational and molecular biology. Here, we engineer and train bidirectional transformer models to predict the chemical grammar of alternative human mRNA splicing leveraging the largest perturbative full-length RNA dataset to date. By combining high-throughput single-molecule long-read "chemical transcriptomics" in human cells with transformer models, we train AllSplice - a nucleotide foundation model that achieves state-of-the-art prediction of canonical and noncanonical splice junctions across the human transcriptome. We demonstrate improved performance achieved through incorporation of diverse noncanonical splice sites in its training set that were identified through long-read RNA data. Leveraging chemical perturbations and multiple cell types in the data, we fine-tune AllSplice to train ChemSplice - the first predictive model of sequence-dependent and cell-type specific alternative splicing following programmed cellular perturbation. We anticipate the broad application of AllSplice, ChemSplice, and other models fine-tuned on this foundation to myriad areas of RNA therapeutics development.

genomics↗

bioRxiv2022

Leukotrienes promote stem cell self-renewal and chemoresistance in acute myeloid leukemia

Acute myeloid leukemia (AML) is characterized by poor clinical outcomes due to high rates of relapse following standard-of-care induction chemotherapy. While many pathogenic drivers have been described in AML, our understanding of the molecular mechanisms mediating chemotherapy resistance remains poor. Therefore, we sought to identify resistance genes to induction therapy in AML and elucidated ALOX5 as a novel mediator of resistance to anthracycline based therapy. ALOX5 is transcriptionally upregulated in AML patient blasts in comparison to normal hematopoietic stem/progenitor cells (HSPCs) and ALOX5 mRNA, and protein expression is increased in response to induction therapy. In vitro, and in vivo genetic, and pharmacologic perturbation studies confirm that ALOX5 positively regulates the leukemogenic potential of AML LSCs, and its loss does not significantly affect the function of normal HSPCs. ALOX5 mediates resistance to daunorubicin (DNR) and promotes AML cell survival and maintenance through its leukotriene (LT) synthetic capacity, specifically via modulating synthesis of LTB4 and its binding to LTB receptor (BLTR). Our study reveals a previously unrecognized role of LTs in AML pathogenesis and chemoresistance, whereby inhibition of ALOX5 mediated LTB4 synthesis and function could be combined with standard chemotherapy, to enhance the overall therapeutic efficacy in AML. Key PointsO_LIAML blasts overexpress and induce ALOX5 expression in response to daunorubicin C_LIO_LI5-Lipoxygenase (ALOX5) promotes blast survival and LSC self-renewal. C_LIO_LIThe effects of ALOX5 on AML blast survival and self-renewal are mediated by the LTB4-BLTR signaling axis. C_LI

cancer biology↗