Biology subjects

Salehi, Z.

Publications and source records attributed to Salehi, Z..

4 recordsLinked to original sources

bioRxiv2026

Platelet-programmed circulating tumor cells signal to monocytes through a candidate CD40LG-ITGA5:ITGB1 myeloid checkpoint axis in breast cancer

Circulating tumor cells (CTCs) are key drivers of distant metastasis, while platelets facilitate this process by protecting them from immune surveillance. However, the detection of CTCs exhibiting platelet markers and their communication with monocytes has not been thoroughly investigated. This study seeks to identify the intercellular communication of CTCs that have acquired platelet traits by integrating single-cell RNA-seq data of 377 CTCs and 2,634 white blood cells. Trajectory analysis identified a subpopulation of CTCs with enhanced platelet-related functions, including platelet aggregation and resistance to NK cell-mediated cytotoxicity, termed Platelet-Programmed CTCs. The Dampened Weighted Least Squares method was implemented to estimate the platelet-programmed tumor cell proportion in 1,102 bulk RNA-seq samples from primary breast cancer tumors. A strong inverse association was found between platelet-programmed tumor cell proportion and overall survival (Cox-PH p-value =0.00419, HR=6 per 10% increase in proportion, 95% CI:1.76-20.7). However, this association did not differ significantly between early- and late-stage patients. Cell-cell communication analyses and molecular docking revealed the CD40LG-ITGA5:ITGB1 pair as a potential immune checkpoint candidate for monocytes in cancer (Hex score=-656.83; TNF-TNFR reference complex=-515). However, further experimental and clinical validation is required to translate these findings. In conclusion, these findings deepen our understanding of the immune evasion mechanisms of CTCs by acquiring platelet characteristics. This immune checkpoint axis offers a novel avenue for further experimental validation and future intervention.

cancer biology↗

bioRxiv2025

Ancient DNA indicates 3,000 years of genetic continuity in the Northern Iranian Plateau, from the Copper Age to the Sassanid Empire

In this study, we present new ancient DNA data from prehistoric and historic populations of the Iranian Plateau. By analysing 50 samples from nine archaeological sites across Iran, we report 23 newly sequenced mitogenomes and 13 nuclear genomes, spanning 4700 BCE to 1300 CE. We integrate an extensive reference sample set of previously published ancient DNA datasets from Western and South-Central Asia, enhancing our understanding of genetic continuity and diversity within ancient Iranian populations. A new Early Chalcolithic sample, predating all other Chalcolithic genomes from Iran, demonstrates mostly Early Neolithic Iranian genetic ancestry. This finding reflects long-term cultural and biological continuity in and around the Zagros area, alongside evidence of some western genetic influence. Our sample selection prioritizes northern Iran, with a particular focus on the Achaemenid, Parthian, and Sassanid periods (355 BCE-460 CE). The genetic profiles of historical samples from this region position them as intermediates on an east-west genetic cline across the Persian Plateau. They also exhibit strong connections to local and South-Central Asian Bronze Age populations, underscoring enduring genetic connections across these regions. Diachronic analyses of uniparental lineages on the Iranian Plateau further highlight population stability from prehistoric to modern times.

genomics↗

bioRxiv2023

Mixed data analysis detected Endocrine Fibroblast Growth Factors (FGF19, FGF21, and FGF23) as Prognostic and Diagnostic Markers of Colorectal Neoplasia and Carcinoma

BackgroundEndocrine fibroblast growth factors (eFGFs) play important roles in various cellular signaling processes such as development and differentiation. These genes were also found to be significantly related to several cancer. However, little is known about the role of eFGFs in colon neoplasia and colon adenocarcinoma (COAD). MethodsWe performed systematically and comprehensively investigated the gene expression, DNA methylation, prognostic significance, genetic alteration, co-expressed genes, protein-protein interaction, small molecules pathway, and drug interactions of eFGFs based on the TIMER2.0, GEPIA2, UALCAN, OncoDB, cBioPortal, LinkedOmics, STRING, SMPDB, htfTarget, mirTarBase, circBank and DGIdb databases. Ultimately, the correlations of eFGFs expressions between polyp and COAD tissues compared to normal mucosa were validated using qRT-PCR as a cross-sectional part of our study. ResultsThe results indicated that eFGFs are highly expressed in COAD, and abnormal gene expressions may be related to promoter methylation. In this matter, methylation analysis revealed promotor hypermethylation of FGF19 and FGF21. Conversely, FGF23 was shown to have a tendency for promotor hypomethylation. Moreover, hypermethylation of FGF21 and FGF23 and downregulation of FGF23 were found to be detrimental to the survival of COAD patients. KEGG pathway analyses indicated that the co-expressed genes of eFGF family members were mainly related to the regulation of the actin cytoskeleton and, more notably, in Ras signaling, PI3k-Akt signaling, Rap1 signaling, and cancer pathways. Based on qRT-PCR results, FGF21 was significantly overexpressed in the colon polyps compared to normal mucosa. Additionally, RNA expression of FGF21 and FGF23 was markedly elevated in adenomatous polyps as opposed to hyperplastic polyps. ConclusionCollectively, these findings reveal the critical roles of eFGFs in COAD tumorigenesis and suggest eFGF family members as promising prognostic and diagnostic markers for CRC as well as discriminating markers for high-risk from low-risk polyps.

bioinformatics↗

bioRxiv2018

A relative comparison between Hidden Markov- and Log-Linear- based models for differential expression analysis in a real time course RNA sequencing data

With the advent of the Next Generation Sequencing technologies, RNA-seq has become known as an optimal approach for studying gene expression profiling. Particularly, time course RNA-seq differential expression analysis has been used in many studies to identify candidate genes. However, applying a statistical method to efficiently identify differentially expressed genes (DEGs) in time course studies is challenging due to inherent characteristics of such data including correlation and dependencies over time. Here we aim to relatively compare EBSeq-HMM, a Hidden Markov-based model, with multiDE, a Log-Linear-based model, in a real time course RNA sequencing data. In order to conduct the comparison, common DEGs detected by edgeR, DESeq2 and Voom (referred to as Benchmark DEGs) were utilized as a measure. Each of the two models were compared using different normalization methods. The findings revealed that multiDE identified more Benchmark DEGs and showed a higher agreement with them than EBSeq-HMM. Furthermore, multiDE and EBSeq-HMM displayed their best performance using TMM and Upper-Quartile normalization methods, respectively.

bioinformatics↗