Biology subjects

Bagheri, M.

Publications and source records attributed to Bagheri, M..

13 recordsLinked to original sources

bioRxiv2026

Mapping breast cancer lineage in radiation and immunotherapy using the REMAP mouse

We present REMAP (Recording Evolution in Mammary tumors via Active PyMT), a lineage-tracing mouse model that integrates inducible CRISPR recording with the MMTV-PyMT model of hormone receptor-positive (HR+) breast cancer. Inducible Cas9 drives editing of MARC1 homing guide RNAs (hgRNAs), generating heritable lineage marks, and enables reconstruction of clonal relationships. Using REMAP, we profiled tumor evolution and response to radiation combined with anti-PD1 immunotherapy. Treatment reduced tumor burden locally and systemically, and single-cell RNA sequencing revealed remodeling of the tumor microenvironment (TME). We identified metastatic clones present across primary tumors and distant sites, which exhibited elevated epithelial-mesenchymal transition (EMT) programs as a heritable clonal state. Treatment reduced EMT-associated transcriptional programs and reshaped immune composition, with radiation driving clonal expansion of T cells and reduced repertoire diversity. In contrast, cancer-associated fibroblast clones spanned multiple transcriptional states, indicating substantial stromal plasticity. Together, REMAP enables high-resolution coupling of clonal history and cellular state in vivo, revealing that tumor progression, metastasis, and therapeutic response are governed by heritable lineage programs.

cancer biology↗

bioRxiv2026

Relationship Between Gene Expression and Drug Response in Triple-Negative Breast Cancer: Leveraging Single-Cell RNA Sequencing and Machine Learning to Identify Biomarker Profiles

Triple-negative breast cancer (TNBC) is an aggressive subtype characterized by limited therapeutic options and poor prognosis. To address these challenges, we combined single-cell RNA sequencing (scRNA-seq) data with advanced machine learning techniques to find biomarkers that predict treatment response. Using tumor and blood samples from TNBC patients treated with either paclitaxel alone or in combination with atezolizumab, we constructed cellular maps, identified differentially expressed genes, and analyzed co-expression networks. Copy number variation (CNV) profiling and weighted gene co-expression network analysis (WGCNA) identified immune-related genes, including IL7R, CD6, and TNFAIP3, as candidate biomarkers linked to therapeutic response. A feature selection using Random Forest followed by bootstrap-enhanced K-nearest neighbors (K-NN) classification achieved high predictive accuracy across all subgroups (AUC > 0.93). Local Interpretable Model-Agnostic Explanations (LIME) based interpretability further identified important factors influencing treatment sensitivity and resistance, including EGR1, MKI67, C1QA/B/C, GZMB, and PRF1. Notably, blood-derived biomarkers showed strong predictive potential, highlighting the variability of liquid biopsy approaches for non-invasive monitoring. Our results indicate that integration of scRNA-seq with interpretable machine learning facilitates the identification of reliable biomarkers and yields clinically actionable insights for personalized therapeutic strategies in TNBC.

bioinformatics↗

bioRxiv2025

Epithelial-Mesenchymal Transition is Associated with Altered Immune Composition and Cytotoxic Function in Triple-Negative Breast Cancer

Epithelial-mesenchymal transition (EMT) is a dynamic process that contributes to breast cancer progression, metastasis, and therapy resistance. EMT also influences the tumor immune microenvironment, shaping immune cell infiltration and function. Although the immunological features of fully epithelial or fully mesenchymal tumor states have been characterized, the immune landscape associated with intermediate or partial EMT states remains poorly understood. To address this gap, we established five single-cell-derived clonal populations from the triple-negative 4T1 mouse mammary tumor cell line, representing a spectrum of EMT phenotypes, and analyzed tumors derived from these clones using single-cell RNA sequencing. We show that tumors derived from these clones retained their relative EMT states in vivo, and that EMT progression is associated with a graded reduction in tumor immunogenicity, accompanied by alterations in immune cell composition and function. Along the EMT spectrum, tumor cells exhibited progressive downregulation of major histocompatibility complex (MHC) class I and II gene expression, along with decreased infiltration of cytotoxic CD8+ T cells, and reduced expression of key effector and trafficking genes (Gzmb, Ccr5, Cxcr6). B cell composition also shifted, with decreased frequencies of IgG1-producing plasma cells and an enrichment of regulatory-like B cells. Natural killer (NK) cells similarly demonstrated progressive functional suppression, marked by reduced expression of cytotoxic molecules and the downregulation of key effector pathways. These findings reveal that EMT is associated with immune cell recruitment and function in a graded manner, providing a rationale for integrating EMT phenotyping into therapeutic strategies to overcome immune resistance in breast cancer.

cancer biology↗

bioRxiv2024

Genomic alterations and transcriptional phenotypes in circulating tumor DNA and matched metastatic tumor

BackgroundProfiling circulating cell-free DNA (cfDNA) has become a fundamental practice in cancer medicine, but the effectiveness of cfDNA at elucidating tumor-derived molecular features has not been systematically compared to standard single-lesion tumor biopsies in prospective cohorts of patients. The use of plasma instead of tissue to guide therapy is particularly attractive for patients with small cell lung cancer (SCLC), a cancer whose aggressive clinical course making it exceedingly challenging to obtain tumor biopsies. MethodsHere, a prospective cohort of 49 plasma samples obtained before, during, and after treatment from 20 patients with recurrent SCLC, we study cfDNA low pass whole genome (0.1X coverage) and exome (130X) sequencing in comparison with time-point matched tumor, characterized using exome and transcriptome sequencing. ResultsDirect comparison of cfDNA versus tumor biopsy reveals that cfDNA not only mirrors the mutation and copy number landscape of the corresponding tumor but also identifies clinically relevant resistance mechanisms and cancer driver alterations not found in matched tumor biopsies. Longitudinal cfDNA analysis reliably tracks tumor response, progression, and clonal evolution. Genomic sequencing coverage of plasma DNA fragments around transcription start sites shows distinct treatment-related changes and captures the expression of key transcription factors such as NEUROD1 and REST in the corresponding SCLC tumors, allowing prediction of SCLC neuroendocrine phenotypes and treatment responses. Conclusions These findings have important implications for non-invasive stratification and subtype-specific therapies for patients with SCLC, now treated as a single disease.

cancer biology↗

bioRxiv2023

Alteration of DNMT1/DNMT3A by eribulin elicits global DNA methylationchanges with potential therapeutic implications for triple-negative breastcancer

Triple-negative breast cancer (TNBC) is an aggressive disease subtype with limited treatment options. Eribulin is a chemotherapeutic approved for the treatment of advanced breast cancer that has been shown to elicit epigenetic changes. We investigated the effect of eribulin treatment on genome-scale DNA methylation patterns in TNBC cells. Following repeated treatment, The results showed that eribulin-induced changes in DNA methylation patterns evident in persister cells. Eribulin also affected the binding of transcription factors to genomic ZEB1 binding sites and regulated several cellular pathways, including ERBB and VEGF signaling and cell adhesion. Eribulin also altered the expression of epigenetic modifiers including DNMT1, TET1, and DNMT3A/B in persister cells. Data from primary human TNBC tumors supported these findings: DNMT1 and DNMT3A levels were altered by eribulin treatment in human primary TNBC tumors. Our results suggest that eribulin modulates DNA methylation patterns in TNBC cells by altering the expression of epigenetic modifiers. These findings have clinical implications for using eribulin as a therapeutic agent.

cancer biology↗

bioRxiv2023

The variable domain from the mitochondrial fission mechanoenzyme Drp1 promotes liquid-liquid phase separation

Dynamins are an essential superfamily of mechanoenzymes that remodel membranes and often contain a "variable domain" (VD) important for regulation. For the mitochondrial fission dynamin, Drp1, a regulatory role for the VD is demonstrated by mutations that can elongate, or fragment, mitochondria. How the VD encodes inhibitory and stimulatory activity is unclear. Here, isolated VD is shown to be intrinsically disordered (ID) yet undergoes a cooperative transition in the stabilizing osmolyte TMAO. However, the TMAO stabilized state is not folded and surprisingly appears as a condensed state. Other co-solutes including known molecular crowder Ficoll PM 70, also induce a condensed state. Fluorescence recovery after photobleaching experiments reveal this state to be liquid-like indicating the VD undergoes a liquid-liquid phase separation under crowding conditions. These crowding conditions also enhance binding to cardiolipin, a mitochondrial lipid, raising the possibility that phase separation may enable rapid tuning of Drp1 assembly necessary for fission.

biophysics↗

bioRxiv2023

Pharmacological Induction of mesenchymal-epithelial transition chemosensitizes breast cancer cells and prevents metastatic progression

The epithelial-mesenchymal transition (EMT) is a developmental program co-opted by tumor cells that aids the initiation of the metastatic cascade. Tumor cells that undergo EMT are relatively chemoresistant, and there are currently no therapeutic avenues specifically targeting cells that have acquired mesenchymal traits. We show that treatment of mesenchymal-like triple-negative breast cancer (TNBC) cells with the microtubule-destabilizing chemotherapeutic eribulin, which is FDA-approved for the treatment of advanced breast cancer, leads to a mesenchymal-epithelial transition (MET). This MET is accompanied by loss of metastatic propensity and sensitization to subsequent treatment with other FDA-approved chemotherapeutics. We uncover a novel epigenetic mechanism of action that supports eribulin pretreatment as a path to MET induction that curtails metastatic progression and the evolution of therapy resistance. SummaryWhile the advent of targeted therapy has led to vast improvements in outcomes for certain types of breast cancer, a mainstay for triple-negative breast cancer (TNBC) remains cytotoxic chemotherapy. A major clinical hurdle in successfully managing this disease is the eventual development of therapeutic resistance and disease relapse in more aggressive forms. Our data reveal that epigenetic modulation of EMT state using the FDA-approved therapeutic eribulin curtails metastatic propensity of breast tumors and, when administered in the treatment-naive setting, sensitizes to subsequent treatment with other chemotherapeutics.

cancer biology↗

bioRxiv2022

Lumbar time-varying muscle synergies in trunk flexion and bending movements at different velocities

PurposeAlthough the extent of which the central nervous system uses muscle synergies as a movement control strategy remains an open area of research, it is widely agreed that synergies facilitate the robustness of the neuromuscular system, allowing for effective postural control and flexible movement. This work aimed to investigate the muscle activation patterns of the trunk and time-varying muscle synergies using a novel 18-muscle 3-DOF, 3-D musculoskeletal model of the lumbar spine developed by the authors. Methods24 different biaxial trunk movements were simulated via the optimization of kinetic and kinematic measures towards obtaining the corresponding muscle activation patterns at 3 different velocities. These patterns were subsequently used to extract the principal (phasic and tonic) spatiotemporal synergies associated with the observed muscle activation patterns in the range of simulated movements. ResultsFour dominant synergies were able to explain a considerable percent (about 75%) of the variance of the simulated muscle activities. The extracted synergies were spatially tuned in the direction of the main simulated movements (flexion/extension and right/left lateral bending). The temporal patterns demonstrated gradual monotonic shifts in tonic synergies and biphasic modulatory components in phasic synergies with spatially tuned time-delays. The increase in velocity resulted in an elevated amplitude coefficient and accelerated activation of phasic synergies. ConclusionOur results suggest the plausibility of a time-varying synergies strategy in the dynamic control of trunk movement. Further work is needed to explore leveraging these concepts in various applications, such as rehabilitation and musculoskeletal biomechanics, towards providing more insight into the mechanisms underlying trunk stability and flexibility.

bioengineering↗

bioRxiv2021

A 6-CpG Validated Methylation Risk Score Model for Metabolic Syndrome: The HyperGEN and GOLDN Studies

There has been great interest in genetic risk prediction using risk scores in recent years, however, the utility of scores developed in European populations and later applied to non-European populations has not been successful. In this study, we used cross-sectional data from the Hypertension Genetic Epidemiology Network (HyperGEN, N=614 African Americans (AA)) and the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN, N=995 European Americans (EA)), to create a methylation risk score (MRS) for metabolic syndrome (MetS), demonstrating the utility of MRS across race groups. To demonstrate this, we first selected cytosine-guanine dinucleotides (CpG) sites measured on Illumina Methyl450 arrays previously reported to be significantly associated with MetS and/or component conditions (CPT1A cg00574958, PHOSPHO1 cg02650017, ABCG1 cg06500161, SREBF1 cg11024682, SOCS3 cg18181703, TXNIP cg19693031). Second, we calculated the parameter estimates for the 6 CpGs in the HyperGEN data and used the beta estimates as weights to construct a MRS in HyperGEN, which was validated in GOLDN. We performed association analyses using a logistic mixed model to test the association between the MRS and MetS adjusting for covariates. Results showed the MRS was significantly associated with MetS in both populations. In summary, a MRS for MetS was a strong predictor for the condition across two ethnic groups suggesting MRS may be useful to examine metabolic disease risk or related complications across ethnic groups.

genetics↗

bioRxiv2021

Leveraging a founder population to identify novel rare-population genetic determinants of lipidome

Identifying the genetic determinants of inter-individual variation in lipid species (lipidome) may provide deeper understanding and new insight into the mechanistic effect of complex lipidomic pathways in CVD risk and progression beyond simple traditional lipids. Previous studies have been largely population based and thus only powered to discover associations with common genetic variants. Founder populations represent a powerful resource to accelerate discovery of novel biology associated with rare population alleles that have risen to higher frequency due to genetic drift. We performed a GWAS of 355 lipid species in 650 individuals from the Old Order Amish founder population including 127 lipid species not previously tested. We report for the first time the lipid species associated with two rare-population but Amish-enriched lipid variants: APOB_rs5742904 and APOC3_rs76353203. We also identified novel associations for 3 rare-population Amish-enriched loci with several sphingolipids and with proposed potential functional/causal variant in each locus including GLPTD2_rs536055318, CERS5_rs771033566, and AKNA_rs531892793. We replicated 7 previously known common loci including novel associations with two sterols: androstenediol with UGT locus on chromosome 2 and estriol with SLC22A8/A24 locus on chromosome 11. Our results show the power of founder populations to discover novel biology due to genetic drift that can increase the frequency of an allele from only few copies in large sample cohorts such as the UK Biobank to dozens of copies in sample size as small as 650.

genetics↗

bioRxiv2020

Limiting Self-Renewal of the Basal Compartment Induces Differentiation and Alters Evolution of Mammary Tumors

Differentiation therapy is an approach that utilizes our understanding of the hierarchy of cellular systems to pharmacologically induce a shift towards terminal commitment. While this approach has been a paradigm in treating certain hematological malignancies, efforts to translate this success to solid tumors have proven challenging. In this study we show that activation of PKA drives aberrant mammary differentiation by diminishing the self-renewing potential of the basal compartment. PKA activation results in tumors that are more benign, exhibiting reduced metastatic propensity, loss of tumor-initiating potential and increased sensitivity to chemotherapy. Analysis of tumor histopathology revealed features of overt differentiation with papillary characteristics. Longitudinal single cell profiling at the hyperplasia and tumor stages uncovered an altered path of tumor evolution whereby PKA curtails the emergence of aggressive subpopulations. PKA activation represents a promising approach as an adjuvant to chemotherapy for certain breast cancers, reviving the paradigm of differentiation therapy for solid tumors.

cancer biology↗

bioRxiv2019

Self-Incompatibility Alleles in Iranian Pear Cultivars

In the present study, the S-alleles of eighteen pear cultivars, (including fourteen cultivars planted commercially in Iran and four controls) are determined. 34 out of 36 S-alleles are detected using nine allele-specific primers, which are designed for amplification of S101/S102, S105, S106, S107, S108, S109, S111, S112 and S114, as well as consensus primers, PycomC1F and PycomC5R. S104, S101 and S105 were the most common S-alleles observed, respectively, in eight, seven and six cultivars. In 16 cultivars, ( Bartlett (S101S102), Beurre Giffard (S101S106), Comice (S104S105), Doshes (S104S107), Koshia (S104S108), Paskolmar (S101S105), Felestini (S101S107), Domkaj (S104S120), Ghousi (S104S107), Kaftar Bache (S104S120), Konjoni (S104S108), Laleh (S105S108), Natanzi (S104S105), Sebri (S101S104), Se Fasleh (S101S105) and Louise Bonne (S101S108)) both alleles are identified but in two cultivars, ( Pighambari (S105) and Shah Miveh Esfahan (S107)) only one allele is recognized. It is concluded that allele-specific PCR amplification can be considered as an efficient and rapid method to identify S-genotype of Iranian pear cultivars.

molecular biology↗

bioRxiv2019

Taxonomically informed scoring enhances confidence in natural products annotation

Mass spectrometry (MS) hyphenated to liquid chromatography (LC)-MS offers unrivalled sensitivity for metabolite profiling of complex biological matrices encountered in natural products (NP) research. With advanced platforms LC, MS/MS spectra are acquired in an untargeted manner on most detected features. This generates massive and complex sets of spectral data that provide valuable structural information on most analytes. To interpret such datasets, computational methods are mandatory. To this extent, computerized annotation of metabolites links spectral data to candidate structures. When profiling complex extracts spectra are often organized in clusters by similarity via Molecular Networking (MN). A spectral matching score is usually established between the acquired data and experimental or theoretical spectral databases (DB). The process leads to various candidate structures for each MS features. At this stage, obtaining high annotation confidence level remains a challenge notably due to the high chemodiversity of specialized metabolomes.\n\nThe integration of additional information in a meta-score is a way to capture complementary experimental attributes and improve the annotation process. Here we show that integrating unambiguous taxonomic position of analyzed samples and candidate structures enhances confidence in metabolite annotation. A script is proposed to automatically input such information at various granularity levels (species, genus, and family) and weight the score obtained between experimental spectral data and output of available computational metabolite annotation tools (ISDB-DNP, MS-Finder, Sirius). In all cases, the consideration of the taxonomic distance allowed an efficient re-ranking of the candidate structures leading to a systematic enhancement of the recall and precision rates of the tools (1.5 to 7-fold increase in the F1 score). Our results clearly demonstrate the importance of considering taxonomic information in the process of specialized metabolites annotation. This requires to access structural data systematically documented with biological origin, both for new and previously reported NPs. In this respect, the establishment of an open structural DB of specialized metabolites and their associated metadata (particularly biological sources) is timely and critical for the NP research community.

bioinformatics↗