Biology subjects

Hamoudi, R. A.

Publications and source records attributed to Hamoudi, R. A..

6 recordsLinked to original sources

bioRxiv2026

Discovery of a Systemic Immune-Inflammatory Axis Bridging the Neuroendocrine System and Breast Tumor Microenvironment via MMD-Regularized Cross-Tissue Latent Alignment

The breast tumor immune microenvironment (TIME) is predominantly studied as a localized phenomenon. However, emerging evidence suggests tumor immune evasion may be systemically linked to master neuroendocrine regulatory centers. Investigating this systemic axis is computationally intractable due to the impossibility of sampling paired brain and breast transcriptomes from living patients. Here we present a novel in silico framework utilizing MMD-regularized cross-tissue latent alignment to bridge unpaired transcriptomic profiles from GTEx neuroendocrine tissues and the TCGA-BRCA cohort. By projecting high-dimensional RNA-seq data into a shared topological space via a Domain Adaptation Autoencoder optimized with Maximum Mean Discrepancy ([L]MMD), we established a robust mathematical bridge across tissues. Interrogation of the aligned 128-dimensional latent space isolated a dominant systemic immune-inflammatory signature rather than canonical endocrine hormone amplification. Dimension 31 of the aligned space was anchored by T-cell receptor variable chains (TRAV35, TRAV8-4, TRBV2), immunoglobulins (IGHG1, IGHGP), and the lipid-inflammatory mediator PLA2G2D, orthogonally linking pituitary neuroinflammation to a "hot" breast TIME. Independent cross-platform validation on the METABRIC microarray cohort (n = 1,980) recovered the same underlying mechanism via latent axis rotation, capturing the systemic acute-phase secretome: PLA2G2A, LBP, SAA1, and CXCL17. These findings suggest a population-level latent correspondence between neuroendocrine inflammatory programs and breast tumor immune phenotypes, revealing candidate targets for liquid biopsy and systemic immunotherapeutic investigation that warrant prospective experimental validation.

cancer biology↗

bioRxiv2025

A Systems Biology Approach to Unveil Shared Therapeutic Targets and Pathological Pathways Across Major Human Cancers

Cancer is a leading global cause of mortality, responsible for nearly 10 million deaths annually, with breast, lung, colorectal, and prostate cancers among the most prevalent. Despite extensive research on individual cancer types, identifying shared molecular signatures could unlock pan-cancer diagnostic tools and therapeutic targets. This study leveraged RNA-seq data from The Cancer Genome Atlas (TCGA) to analyze our selected cancer types (SCTs)--breast, lung, colorectal, and prostate, employing a multi-step bioinformatics pipeline. Differentially expressed genes (DEGs) between tumors and normal tissues were identified and validated using an Elastic Net regression model. Weighted Gene Co-expression Network Analysis (WGCNA) revealed highly correlated gene modules linked to clinical traits, pinpointing 179 shared signature genes across the SCTs. Protein-protein interaction (PPI) network and clustering analyses further refined these to 26 hub genes, enriched in cancer hallmark pathways. Nine hub genes--KIF18B, RRM2, MYBL2, IQGAP3, TPX2, SLC7A11, RHPN1, HJURP, and SKA3--stood out due to consistent upregulation in metastatic tumors (breast, colorectal, prostate) and their high expression across more than 18 different cancer types, suggesting roles as oncogenes, prognostic markers, or therapeutic targets. The expression patterns of hub genes were further validated across larger cancer patient cohorts of SCTs, confirming relevance across multiple datasets, and their prognostic significance was assessed by their influence on overall survival (OS). Notably, these hub genes also correlated with immune-related functions, potentially influencing tumor microenvironment modulation. This integrative approach provides a strong framework for identifying cross-cancer potential biomarkers, advancing pan-cancer insights, and supporting improved diagnosis, prognosis, and therapy development.

bioinformatics↗

bioRxiv2024

An Emirati pangenome incorporating a diploid telomere-to-telomere reference

Reference data on genomic variation form the basis of genetic research. Limitations in identifying genetic variation from single reference sequences have been recently overcome, as improvements in sequencing technologies have allowed the generation of pangenomic references from multiple accurate, chromosome-level de novo assemblies. Here, we present a comprehensive Emirati telomere-to-telomere (T2T) pangenome generated from 58 individuals, comprising 28 trio-based and 30 single-sample assemblies. The resulting 116 haplotype-resolved assemblies demonstrate high contiguity, with a median continuity of 150 Mb and a median quality value (QV) of 59, achieving T2T-level scaffold status for 71.9% of chromosomes. These assemblies form the foundation of the Emirati T2T pangenome graph. The graph reveals levels of genomic diversity comparable to those reported by the Human Pangenome Reference Consortium, while also capturing regionally enriched and difficult-to-assemble variation, uniquely accessible through the Emirati T2T assemblies. This reference makes a valuable global contribution to human pangenomics and serves as a critical resource for advancing precision medicine in the United Arab Emirates.

genomics↗

bioRxiv2023

Deciphering Neuronal Deficit and Protein Profile Changes in Human Brain Organoids from Patients with Creatine Transporter Deficiency

Creatine transporter deficiency (CTD) is an X-linked disease caused by mutations in the SLC6A8 gene. The impaired creatine uptake in the brain results in intellectual disability, behavioral disorders, language delay, and seizures. In this work, we generated human brain organoids from induced pluripotent stem cells of healthy subjects and CTD patients. Brain organoids from CTD donors had reduced creatine uptake compared with those from healthy donors. The expression of neural progenitor cell markers SOX2 and PAX6 was reduced in CTD derived organoids, while GSK3{beta}, a key regulator of neurogenesis, was up-regulated. Shotgun proteomics combined with integrative bioinformatic and statistical analysis identified changes in abundance of proteins associated with intellectual disability, epilepsy, and autism. Re-establishment of the expression a functional SLC6A8 in CTD-derived organoids restored creatine uptake and normalized the expression of SOX2, GSK3{beta} and other key proteins associated with clinical features of CTD patients. Our brain organoid model opens new avenues for further characterizing the CTD pathophysiology and supports the concept that reinstating creatine levels in patients with CTD could result in therapeutic efficacy. Summary HeadingTherapeutic targets associated with Creatine Transporter Deficiency

neuroscience↗

bioRxiv2022

Dodecyl Creatine Ester Improves Cognitive Function and Identifies Drivers of Creatine Deficiency.

Creatine transporter deficiency prevents creatine uptake into the brain, leading to mental retardation. To better understand the pathophysiology, this study focuses on the identification of biomarkers related to cognitive improvement in a Slc6a8 knockout mouse model (Slc6a8/y) engineered to mimic the clinical features of CTD patients which have low brain creatine content. Shotgun proteomics analysis of 4,035 proteins in four different brain regions; the cerebellum, cortex, hippocampus (associated with cognitive functions) and brain stem, and muscle as a control, was performed in 24 mice. Comparisons of the protein abundance in the four brain regions between DCE-treated intranasally Slc6a8-/y mice and wild type and DCE-treated Slc6a8-/y and vehicle group identified 14 biomarkers, shedding light on the mechanism of action of DCE. Integrative bioinformatics and statistical modeling identified key proteins associated with CTD, including KIF1A and PLCB1. The abundance of these proteins in the four brain regions was significantly correlated with both the object recognition and the Y-maze tests. Functional analysis confirmed their key roles and associated molecules in CTD pathogenesis.

neuroscience↗

bioRxiv2019

The Personal Genome Project-UK: an open access resource of human multi-omics data

Integrative analysis of multi-omics data is a powerful approach for gaining functional insights into biological and medical processes. Conducting these multifaceted analyses on human samples is often complicated by the fact that the raw sequencing output is rarely available under open access. The Personal Genome Project UK (PGP-UK) is one of few resources that recruits its participants under open consent and makes the resulting multi-omics data freely and openly available. As part of this resource, we describe the PGP-UK multi-omics reference panel consisting of ten genomic, methylomic and transcriptomic data. Specifically, we outline the data processing, quality control and validation procedures which were implemented to ensure data integrity and exclude sample mix-ups. In addition, we provide a REST API to facilitate the download of the entire PGP-UK dataset. The data are also available from two cloud-based environments, providing platforms for free integrated analysis. In conclusion, the genotype-validated PGP-UK multi-omics human reference panel described here provides a valuable new open access resource for integrated analyses in support of personal and medical genomics.

bioinformatics↗