Biology subjects

Irajizad, E.

Publications and source records attributed to Irajizad, E..

7 recordsLinked to original sources

bioRxiv2026

KRAS-driven metabolic reprogramming of enhanced MFSD2A-mediated lysophosphatidylcholine scavenging promotes survival and progression of pancreatic ductal adenocarcinoma

Oncogenic KRAS drives lipid reprogramming in pancreatic ductal adenocarcinoma (PDAC) to promote disease progression, and these changes are manifest in circulation. Using mass spectrometry, we performed lipidomic analyses on plasmas from a cohort of 93 newly-diagnosed resectable PDAC cases, 43 patients with chronic pancreatitis, and 93 age- and sex-matched healthy controls, the results of which revealed pronounced reductions in circulating lysophosphatidylcholines (LysoPC) as a prominent feature associated with PDAC. Using stable-isotope resolved lipidomics, we further found that PDAC cells exhibit a lipid scavenging phenotype characterized by preferential uptake of extracellular unsaturated LysoPCs to sustain pro-growth signals. Restricting bioavailability of extracellular unsaturated LysoPCs shifted the metabolic phenotype of PDAC cells towards enhanced de novo lipogenesis and autophagy, which was accompanied by suppression of AKT signaling activities and increased susceptibility to apoptosis. Using bulk, single-cell, and spatial transcriptomic datasets together with functional experiments, we identified oncogenic KRAS-mediated upregulation of major facilitator superfamily domain-containing protein 2a (MFSD2A) as a key mediator that facilitates extracellular uptake of LysoPCs in PDAC cells. Loss of MFSD2A expression mimicked LysoPC restriction and resulted in inhibition of AKT signaling and increased propensity of PDAC cells to undergo apoptosis in vitro and suppressed tumor growth in vivo. Therapeutic targeting of the KRAS-MFSD2A-LysoPC axis via repurposing of the synthetic alkyl-lysophospholipid edelfosine promoted potent anti-cancer effects in vitro that were mechanistically attributed to reduced extracellular uptake of LysoPCs, and attenuation of AKT signaling. Collectively, our findings describe a previously unrecognized onco-metabolic program of enhanced LysoPC scavenging mediated by MFSD2A that promotes PDAC progression and that is therapeutically targetable via repurposing edelfosine.

cancer biology↗

bioRxiv2025

AUC-PR is a More Informative Metric for Assessing the Biological Relevance of In Silico Cellular Perturbation Prediction Models

In silico perturbation models, computational methods which can predict cellular responses to perturbations, present an opportunity to reduce the need for costly and time-intensive in vitro experiments. Many recently proposed models predict high-dimensional cellular responses, such as gene or protein expression to perturbations such as gene knockout or drugs. However, evaluating in silico performance has largely relied on metrics such as R2, which assess overall prediction accuracy but fail to capture biologically significant outcomes like the identification of differentially expressed genes. In this study, we present a novel evaluation framework that introduces the AUC-PR metric to assess the precision and recall of DE gene predictions. By applying this framework to both single-cell and pseudo-bulked datasets, we systematically benchmark simple and advanced computational models. Our results highlight a significant discrepancy between R2 and AUC-PR, with models achieving high R2 values but struggling to identify Differentially expressed genes accurately, as reflected in their low AUC-PR values. This finding underscores the limitations of traditional evaluation metrics and the importance of biologically relevant assessments. Our framework provides a more comprehensive understanding of model capabilities, advancing the application of computational approaches in cellular perturbation research.

bioinformatics↗

bioRxiv2024

Aberrant expression of CD14 in breast tumor cells is associated with poor outcome

Emerging evidence suggests that cancer cells can mimic features of immune cells during oncogenic transformation to drive disease progression. We assessed the occurrence of immunological markers in breast cancer cells to determine their expression pattern. We initially analyzed 18 immune protein markers (CCR4, CCR6, CCR7, CD11, CD123, CD14, CD16, CD19, CD24, CD25, CD27, CD3, CD38, CD4, CD45, CD56, CD8 and CXCR3) expressed on the surface of 28 breast cancer cell lines using mass spectrometry. CD14 protein expression in tumor cells and its association with clinical outcomes was subsequently evaluated by tissue microarray (TMA) analysis of 346 breast tumors. Single-cell RNA sequencing data from breast cancer tumors and bulk transcriptomic data of breast cancer cell lines were interrogated for molecular signatures associated with CD14 tumor cell expression. Among the markers interrogated, CD14 protein was aberrantly expressed on the surface of 13 out of 15 triple-negative breast cancer (TNBC), one of six hormone receptor positive (HR+), one of five hormone receptors negative (HR-)/Her2+ cell lines. Likewise, RNA expression revealed higher levels of CD14 in TNBC cell lines compared to other subtypes. Tumor tissue microarray analysis revealed elevated levels of CD14 membrane expression predominantly in TNBC and was associated with higher tumor grade and increased incidence of disease recurrence compared to CD14-negative tumors. The CD14-positive subgroup exhibited Nuclear Factor Kappa Beta (NFkB) and TGF-{beta} centric networks at both the protein and Single-cell RNA levels. We have uncovered a novel subset of breast cancers characterized by aberrant surface expression of CD14 associated with aggressive disease. CD14 identifies a subset of breast cancers with poor outcome and is a potential therapeutic target.

cancer biology↗

bioRxiv2024

A novel method to guide biomarker combinations to optimize the sensitivity

Logistic regression has demonstrated its utility in classifying binary labeled datasets through the maximum likelihood approach. However, in numerous biological and clinical contexts, the aim is often to determine coefficients that yield the highest sensitivity at the pre-specified specificity or vice versa. Therefore, the application of logistic regression is limited in such settings. To this end, we have developed an improved regression framework, SMAGS, for binary classification that, for a given specificity, finds the linear decision rule that yields the maximum sensitivity. Furthermore, we employed the method for feature selection to find the features that are satisfying the sensitivity maximization goal. We compared our method with normal logistic regression by applying it to real clinical data as well as synthetic data. In the real application data (colorectal cancer dataset), we found 14% improvement of sensitivity at 98.5% specificity. Availability and implementationSoftware is made available in Python (https://github.com/smahmoodghasemi/SMAGS)

bioinformatics↗

bioRxiv2024

Vesicle-mediated mitochondrial clearance underlies an actionable metabolic vulnerability in triple-negative breast cancer

Selective autophagy of mitochondria is known to promote survival and progression of cancer cells in various malignancies including triple-negative breast cancer (TNBC). Here, we aimed to identify the essential metabolic adaptations that support mitochondrial quality control with the goal to uncover actionable metabolic vulnerabilities with therapeutic potential. Using an integrated approach of proteomics and untargeted and stable-isotope resolved metabolomics, coupled with functional experimental analyses, we define an alternative mechanism to mitophagy enabled by an onco-metabolic program of heightened extracellular sphingomyelin salvaging in TNBC that facilitates extracellular vesicle (EV)-mediated intracellular clearance of mitochondrial damage. Targeting of the cancer cell sphingolipid onco-metabolic pathway via repurposing of eliglustat, a selective small molecule inhibitor of glucosylceramide synthase (UGCG), resulted in ceramide-induced lethal mitophagy and attenuated tumor growth and prolonged overall survival at clinically achievable doses in an orthotopic syngeneic mouse model of TNBC. Our study defines a mechanism of aberrant sphingolipid metabolism that underlies an actionable metabolic vulnerability for anti-cancer treatment.

cancer biology↗

bioRxiv2023

Integrated spatial transcriptomics and lipidomics of precursor lesions of pancreatic cancer identifies enrichment of long chain sulfatide biosynthesis as an early metabolic alteration

BackgroundThe development of diverse spatial profiling technologies has provided an unprecedented insight into molecular mechanisms driving cancer pathogenesis. Here, we conducted the first integrated cross-species assessment of spatial transcriptomics and spatial metabolomics alterations associated with progression of intraductal papillary mucinous neoplasms (IPMN), bona fide cystic precursors of pancreatic ductal adenocarcinoma (PDAC). MethodsMatrix Assisted Laster Desorption/Ionization (MALDI) mass spectrometry (MS)-based spatial imaging and Visium spatial transcriptomics (ST) (10X Genomics) was performed on human resected IPMN tissues (N= 23) as well as pancreata from a mutant Kras;Gnas mouse model of IPMN. Findings were further compared with lipidomic analyses of cystic fluid from 89 patients with histologically confirmed IPMNs, as well as single-cell and bulk transcriptomic data of PDAC and normal tissues. ResultsMALDI-MS analyses of IPMN tissues revealed long-chain hydroxylated sulfatides, particularly the C24:0(OH) and C24:1(OH) species, to be selectively enriched in the IPMN and PDAC neoplastic epithelium. Integrated ST analyses confirmed that the cognate transcripts engaged in sulfatide biosynthesis, including UGT8, Gal3St1, and FA2H, were co-localized with areas of sulfatide enrichment. Lipidomic analyses of cystic fluid identified several sulfatide species, including the C24:0(OH) and C24:1(OH) species, to be significantly elevated in patients with IPMN/PDAC compared to those with low-grade IPMN. Targeting of sulfatide metabolism via the selective galactosylceramide synthase inhibitor, UGT8-IN-1, resulted in ceramide-induced lethal mitophagy and subsequent cancer cell death in vitro, and attenuated tumor growth of mutant Kras;Gnas allografts. Transcript levels of UGT8 and FA2H were also selectively enriched in PDAC transcriptomic datasets compared to non-cancerous areas, and elevated tumoral UGT8 was prognostic for poor overall survival. ConclusionEnhanced sulfatide metabolism is an early metabolic alteration in cystic pre-cancerous lesions of the pancreas that persists through invasive neoplasia. Targeting sulfatide biosynthesis might represent an actionable vulnerability for cancer interception.

cancer biology↗

bioRxiv2023

EGFR inhibition in lung adenocarcinoma upregulates cell surface expression of the placental antigen ALPP and enhances efficacy of ALPP-ADC therapy

Alkaline phosphatase placental type (ALPP) and ALPPL2 are closely related and regulated GPI anchored proteins that are known to be expressed on the cell surface in some cancers, whereas normal tissue expression is largely limited to the placenta. Clinical utility of ALPP is potentially limited by heterogenous expression in tumors. Here, we assessed ALPP and ALPPL2 surfaceome protein levels in 158 cancer cell lines and mRNA expression levels in 10,967 tumors representing 32 cancer types from The Cancer Genome Atlas (TCGA), which revealed ALPP, and to a lesser extent ALPPL2, to be variably expressed in several cancer types including lung adenocarcinoma (LUAD). Surface expression of ALPP was confirmed by tissue microarray analysis of 204 lung tumors. Using LUAD as a model system, we demonstrated that treatment with EGFR inhibitors, or induction of cancer cell quiescence via nutrient deprivation greatly enhanced ALPP surface expression. Mechanistic studies revealed that enhancement of surface ALPP expression in LUAD following gefitinib treatment was mediated through repression of EGFR signaling and activation of the transcription factor FoxO3a, which was identified as an upstream transcriptional regulator of ALPP. Using xenograft models of LUAD, we further demonstrated that gefitinib treatment upregulates surface expression of ALPP in LUAD cells but not in normal tissues. Combination therapy with gefitinib and an ALPP antibody conjugated with Monomethylauristatin F (ALPP-ADC-MAF) resulted in superior anti-cancer efficacy compared with gefitinib or ALPP-ADC-MAF alone. Our findings support a novel combination treatment modality that boosts the efficacy of ALPP-ADC directed therapy.

cancer biology↗