Identify Transcription Factors Research Articles

Comprehensive analysis of transcription factors involved in odontoblast differentiation mechanism.

Primary cultured odontoblasts rapidly lose their tissue-specific phenotype. To identify transcription factors (TF) that are important for the maintenance of the odontoblast phenotype, primary cultures of C57BL/6J mouse dental mesenchymal cells (DMC) were isolated, and expression of TF and odontoblast marker genes in cells immediately after isolation and 2days after culture were comprehensively evaluated and compared using RNA-sequencing (RNA-seq). The expression of odontoblast markers in mouse dental mesenchymal cells decreased rapidly after isolation. In addition, the expression of Hedgehog-related, Notch-related, and immediate- early gene (IEG)-related transcription factors significantly decreased. Forced expression of these genes in lentiviral vectors, together with fibroblast growth factor 4 (FGF4), fibroblast growth factor 9 (FGF9), and the Wnt pathway activator CHIR99021, significantly induced the expression of odontogenic marker genes. These results indicate, for the first time, that Notch signaling and early genes may be important for maintaining odontoblast cultures. Furthermore, simultaneous stimulation of FGF, Wnt, Hedgehog, Notch pathways, and IEG transcription factors cooperatively promoted the maintenance of the odontoblast phenotype. These results suggest that the Hedgehog and Notch signaling pathways may play an important role in maintaining odontoblast phenotypes, in addition to FGF and Wnt signaling.

Gene expression correlates of adagrasib response in KRASG12C mutated non-small cell lung cancer (NSCLC).

8529 Background: KRASG12C inhibitors such as adagrasib and sotorasib have shown clinical promise in targeting KRASG12C-mutated lung cancers; however, most patients develop primary or secondary resistance. A biomarker of response to KRASG12C inhibitor is needed for better patient stratification and to understand the resistance mechanism. Methods: We analyzed transcriptional correlates of adagrasib treatment outcome in 68 patients in the KRYSTAL-1 trial, a phase 1/2 clinical trial of adagrasib monotherapy in the second line and beyond treatment for NSCLC. We also treated KRAS-mutated lung cancer mouse models and organoids with a KRAS inhibitor for the long term and characterized the resistant tumors’ transcriptional profile to identify resistance mechanisms. We also performed serial gene expression analysis of KrasG12D mutated lung organoids undergoing squamous transformation to identify transcription factor involved in the resistance process. Results: In patients with lung adenocarcinoma with KRASG12C and STK11/ LKB1 co-mutations, we find an enrichment of the squamous cell carcinoma gene signature in pre-treatment biopsies correlates with a poor response to adagrasib. Studies of Lkb1-deficient KRASG12C and KrasG12D lung cancer mouse models and organoids, treated with KRAS inhibitors adagrasib and MRTX1133, respectively, reveal that tumors invoke a lineage plasticity program, adeno-to-squamous transition (AST), that enables resistance to KRAS inhibition. We identify TP63 to be a transcription factor whose expression correlated with squamous transformation. The analysis of lineage plasticity program, adagrasib resistant tumors, and p63 regulon revealed KRT6A to be a common biomarker whose expression correlated with overall survival in the KRYSTAL-1 cohort. Conclusions: KRASG12C mutated lung adenocarcinoma patients with a higher expression of squamous cell carcinoma gene expression signature respond poorly to adagrasib treatment. Expression of the AST plasticity signature and KRT6A at baseline correlates with poor adagrasib responses. These data indicate the role of AST in KRAS inhibitor resistance and provide predictive biomarkers for KRAS-targeted therapies in lung cancer.

Comprehensive comparative analysis of the periodontal pathogen Porphyromonas gingivalis: exploring the pan-genome, the reconstruction of the gene regulatory network and genome-scale metabolic network.

Porphyromonas gingivalis is a nonmotile, obligate anaerobic, Gram-negative bacterium known for its association with periodontal disease and its involvement in systemic diseases such as atherosclerosis, cardiovascular disease, colon cancer, and Alzheimer's disease. This bacterium produces several virulence factors, including capsules, fimbriae, lipopolysaccharides, proteolytic enzymes, and hemagglutinins. A comparative genomic analysis revealed the open pangenome of P. gingivalis and identified complete type IV secretion systems in strain KCOM2805 and almost complete type VI secretion systems in strains KCOM2798 and ATCC49417, which is a new discovery as previous studies did not find the proteins involved in secretion systems IV and VI. Conservation of some virulence factors between different strains was observed, regardless of their genetic diversity and origin. In addition, we performed for the first time a reconstruction analysis of the gene regulatory network, identifying transcription factors and proteins involved in the regulatory mechanisms of bacterial pathogenesis. In particular, QseB regulates the expression of hemagglutinin and arginine deaminase, while Rex may suppress the release of gingipain through interactions with PorV and the formatum/nitrate transporter. Our study highlights the central role of conserved virulence factors and regulatory pathways, particularly QseB and Rex, in P. gingivalis and provides insights into potential therapeutic targets.

FUDNC1-dependent mitophagy ameliorate motor neuron death in an amyotrophic lateral sclerosis mouse model

Amyotrophic lateral sclerosis (ALS) is one of the most common neurodegenerative diseases, yet effective treatment is lacking. Moreover, the underlying pathomechanisms of ALS remain unclear, with impaired mitophagy function being increasingly recognized as a contributing factor. FUN14 domain-containing protein 1 (FUNDC1) is an autophagy receptor localized to the outer mitochondrial membrane and a mitochondrial membrane protein that mediates mitophagy and therefore considered as important factor in neurodegenerative diseases. However, its specific role in ALS is not yet clear. Therefore, this study aimed to investigate the regulatory role of FUNDC1 in ALS and determine its regulatory mechanisms. ALS transgenic mice were obtained and maintained under standard conditions. Cell lines were generated by stable transfection with hSOD1G93A or control vectors. Mice received intrathecal injections of AAV9 vectors expressing FUNDC1 or EGFP. Motor function was assessed through behavioral tests, and histological and immunostaining analyses were performed. Colocalization analysis was conducted in transfected cells, and protein expression was evaluated via western blotting. We first observed that FUNDC1 was significantly downregulated in the spinal cord tissues of SOD1G93A mice. FUNDC1 overexpression considerably improved locomotor activity and prolonged survival time in SOD1G93A mice. Mechanistically, reduced expression of FUNDC1 resulted in decreased mitophagy, as indicated by decreased recruitment through LC3 in SOD1G93A mice and cellular models. Consequently, this led to increased mitochondrial accumulation and cell apoptosis, exacerbating the ALS phenotype. Furthermore, we identified transcription factor FOXD3 as an essential upstream factor of FUNDC1, resulting in reduced transcription of FUNDC1 in ALS lesions. This study suggests a novel strategy of targeting FUNDC1-mediated mitophagy for developing therapeutic interventions to mitigate disease progression and improve outcomes for ALS patients.

Machine learning unveils an immune-related DNA methylation profile in germline DNA from breast cancer patients

BackgroundThere is an unmet need for precise biomarkers for early non-invasive breast cancer detection. Here, we aimed to identify blood-based DNA methylation biomarkers that are associated with breast cancer.MethodsDNA methylation profiling was performed for 524 Asian Chinese individuals, comprising 256 breast cancer patients and 268 age-matched healthy controls, using the Infinium MethylationEPIC array. Feature selection was applied to 649,688 CpG sites in the training set. Predictive models were built by training three machine learning models, with performance evaluated on an independent test set. Enrichment analysis to identify transcription factors binding to regions associated with the selected CpG sites and pathway analysis for genes located nearby were conducted.ResultsA methylation profile comprising 51 CpGs was identified that effectively distinguishes breast cancer patients from healthy controls achieving an AUC of 0.823 on an independent test set. Notably, it outperformed all four previously reported breast cancer-associated methylation profiles. Enrichment analysis revealed enrichment of genomic loci associated with the binding of immune modulating AP-1 transcription factors, while pathway analysis of nearby genes showed an overrepresentation of immune-related pathways.ConclusionThis study has identified a breast cancer-associated methylation profile that is immune-related to potential for early cancer detection.

HIF-1α participates in the regulation of S100A16-HRD1-GSK3β/CK1α pathway in renal hypoxia injury

S100 calcium-binding protein 16 (S100A16) is implicated in both chronic kidney disease (CKD) and acute kidney injury (AKI). Previous research has shown that S100A16 contributes to AKI by facilitating the ubiquitylation and degradation of glycogen synthase kinase 3β (GSK3β) and casein kinase 1α (CK1α) through the activation of HMG-CoA reductase degradation protein 1 (HRD1). However, the mechanisms governing S100A16-induced HRD1 activation and the upregulation of S100A16 expression in renal injury are not fully understood. In this study, we observed elevated expression of Hypoxia-inducible Factor 1-alpha (HIF-1α) in the kidneys of mice subjected to ischemia-reperfusion injury (IRI). S100A16 deletion attenuated the increased HIF-1α expression induced by IRI. Using a S100A16 knockout rat renal tubular epithelial cell line (NRK-52E cells), we found that S100A16 knockout effectively mitigated apoptosis during hypoxic reoxygenation (H/R) and cell injury induced by TGF-β1. Our results revealed that H/R injuries increased both protein and mRNA levels of HIF-1α and HRD1 in renal tubular cells. S100A16 knockout reversed the expressions of HIF-1α and HRD1 under H/R conditions. Conversely, S100A16 overexpression in NRK-52E cells elevated HIF-1α and HRD1 levels. HIF-1α overexpression increased HRD1 and β-catenin while decreasing GSK-3β. HIF-1α inhibition restored HRD1 and β-catenin upregulation and GSK-3β downregulation by cellular H/R injury. Notably, Chromatin immunoprecipitation (ChIP) and luciferase reporter assays demonstrated HIF-1α binding signals on the HRD1 promoter, and luciferase reporter gene assays confirmed HIF-1α‘s transcriptional regulation of HRD1. Additionally, we identified Transcription Factor AP-2 Beta (TFAP2B) as the upregulator of S100A16. ChIP and luciferase reporter assays confirmed TFAP2B as a transcription factor for S100A16. In summary, this study identifies TFAP2B as the transcription factor for S100A16 and demonstrates HIF-1α regulation of HRD1 transcription within the S100A16-HRD1-GSK3β/CK1α pathway during renal hypoxia injury. These findings provide crucial insights into the molecular mechanisms of kidney injury, offering potential avenues for therapeutic intervention.

Excitatory Spinal Lhx9-Derived Interneurons Modulate Locomotor Frequency in Mice.

Locomotion allows us to move and interact with our surroundings. Spinal networks that control locomotion produce rhythm and left-right and flexor-extensor coordination. Several glutamatergic populations, Shox2 non-V2a, Hb9-derived interneurons, and, recently, spinocerebellar neurons have been proposed to be involved in the mouse rhythm generating networks. These cells make up only a smaller fraction of the excitatory cells in the ventral spinal cord. Here, we set out to identify additional populations of excitatory spinal neurons that may be involved in rhythm generation or other functions in the locomotor network. We use RNA sequencing from glutamatergic, non-glutamatergic, and Shox2 cells in the neonatal mice from both sexes followed by differential gene expression analyses. These analyses identified transcription factors that are highly expressed by glutamatergic spinal neurons and differentially expressed between Shox2 neurons and glutamatergic neurons. From this latter category, we identified the Lhx9-derived neurons as having a restricted spinal expression pattern with no Shox2 neuron overlap. They are purely glutamatergic and ipsilaterally projecting. Ablation of the glutamatergic transmission or acute inactivation of the neuronal activity of Lhx9-derived neurons leads to a decrease in the frequency of locomotor-like activity without change in coordination pattern. Optogenetic activation of Lhx9-derived neurons promotes locomotor-like activity and modulates the frequency of the locomotor activity. Calcium activities of Lhx9-derived neurons show strong left-right out-of-phase rhythmicity during locomotor-like activity. Our study identifies a distinct population of spinal excitatory neurons that regulates the frequency of locomotor output with a suggested role in rhythm-generation in the mouse alongside other spinal populations.

DeepReg: a deep learning hybrid model for predicting transcription factors in eukaryotic and prokaryotic genomes

Deep learning models (DLMs) have gained importance in predicting, detecting, translating, and classifying a diversity of inputs. In bioinformatics, DLMs have been used to predict protein structures, transcription factor-binding sites, and promoters. In this work, we propose a hybrid model to identify transcription factors (TFs) among prokaryotic and eukaryotic protein sequences, named Deep Regulation (DeepReg) model. Two architectures were used in the DL model: a convolutional neural network (CNN), and a bidirectional long-short-term memory (BiLSTM). DeepReg reached a precision of 0.99, a recall of 0.97, and an F1-score of 0.98. The quality of our predictions, the bias-variance trade-off approach, and the characterization of new TF predictions were evaluated and compared against those produced by DeepTFactor, as well as against experimental data from three model organisms. Predictions based on our DLM tended to exhibit less variance and bias than those from DeepTFactor, thus increasing reliability and decreasing overfitting.

Single-Cell RNA-Sequencing Reveals Heterogeneity and Transcriptional Dynamics in Porcine Circulating CD8+ T Cells.

Pigs are the most important source of meat and valuable biomedical models. However, the porcine immune system, especially the heterogeneity of CD8 T cell subtypes, has not been fully characterized. Here, using single-cell RNA sequencing, we identified 14 major cell types from peripheral blood circulating cells of pigs and observed remarkable heterogeneity among CD8 T cell types. Upon re-clustering of CD8+ T cells, we defined four CD8 T cell subtypes and revealed their potential differentiation trajectories and transcriptomic differences among them. Additionally, we identified transcription factors with potential regulatory roles in maintaining CD8 T cell differentiation. The cell-cell communication analysis inferred an extensive interaction between CD8 T cells and other immune cells. Finally, cross-species analysis further identified species-specific and conserved cell types across different species. Overall, our study provides the first insight into the extensive functional heterogeneity and state transitions among porcine CD8 T cell subtypes in pig peripheral blood, complements the knowledge of porcine immunity, and enhances its potential as a biomedical model.

Manzamine A reduces androgen receptor transcription and synthesis by blocking E2F8-DNA interactions and effectively inhibits prostate tumor growth in mice.

The androgen receptor (AR) is the main driver in the development of castration-resistant prostate cancer, where the emergence of AR splice variants leads to treatment-resistant disease. Through detailed molecular studies of the marine alkaloid manzamine A (MA), we identified transcription factor E2F8 as a previously unknown regulator of AR transcription that prevents AR synthesis in prostate cancer cells. MA significantly inhibited the growth of various prostate cancer cell lines and was highly effective in inhibiting xenograft tumor growth in mice without any pathophysiological perturbations in major organs. MA suppressed the full-length AR (AR-FL), its spliced variant AR-V7, and the AR-regulated prostate-specific antigen (PSA; also known as KLK3) and human kallikrein 2 (hK2; also known as KLK2) genes. RNA sequencing (RNA-seq) analysis and protein modeling studies revealed E2F8 interactions with DNA as a potential novel target of MA, suppressing AR transcription and its synthesis. This novel mechanism of blocking AR biogenesis via E2F8 may provide an opportunity to control therapy-resistant prostate cancer over the currently used AR antagonists designed to target different parts of the AR gene.

FOXO1 enhances CAR T cell stemness, metabolic fitness and efficacy

Chimeric antigen receptor (CAR) T cell therapy has transformed the treatment of haematological malignancies such as acute lymphoblastic leukaemia, B cell lymphoma and multiple myeloma1–4, but the efficacy of CAR T cell therapy in solid tumours has been limited5. This is owing to a number of factors, including the immunosuppressive tumour microenvironment that gives rise to poorly persisting and metabolically dysfunctional T cells. Analysis of anti-CD19 CAR T cells used clinically has shown that positive treatment outcomes are associated with a more ‘stem-like’ phenotype and increased mitochondrial mass6–8. We therefore sought to identify transcription factors that could enhance CAR T cell fitness and efficacy against solid tumours. Here we show that overexpression of FOXO1 promotes a stem-like phenotype in CAR T cells derived from either healthy human donors or patients, which correlates with improved mitochondrial fitness, persistence and therapeutic efficacy in vivo. This work thus reveals an engineering approach to genetically enforce a favourable metabolic phenotype that has high translational potential to improve the efficacy of CAR T cells against solid tumours.

The heat shock factor 20-HSF4-cellulose synthase A2 module regulates heat stress tolerance in maize.

Temperature shapes the geographical distribution and behavior of plants. Understanding the regulatory mechanisms underlying the plant heat stress response is important for developing climate-resilient crops, including maize (Zea mays). To identify transcription factors (TFs) that may contribute to the maize heat stress response, we generated a dataset of short- and long-term transcriptome changes following a heat treatment time course in the inbred line B73. Co-expression network analysis highlighted several TFs, including the class B2a heat shock factor (HSF) ZmHSF20. Zmhsf20 mutant seedlings exhibited enhanced tolerance to heat stress. Furthermore, DNA affinity purification sequencing and Cleavage Under Targets and Tagmentation assays demonstrated that ZmHSF20 binds to the promoters of Cellulose synthase A2 (ZmCesA2) and three class A Hsf genes, including ZmHsf4, repressing their transcription. We showed that ZmCesA2 and ZmHSF4 promote the heat stress response, with ZmHSF4 directly activating ZmCesA2 transcription. In agreement with the transcriptome analysis, ZmHSF20 inhibited cellulose accumulation and repressed the expression of cell wall-related genes. Importantly, the Zmhsf20 Zmhsf4 double mutant exhibited decreased thermotolerance, placing ZmHsf4 downstream of ZmHsf20. We proposed an expanded model of the heat stress response in maize, whereby ZmHSF20 lowers seedling heat tolerance by repressing ZmHsf4 and ZmCesA2, thus balancing seedling growth and defense.

Single cell analysis reveals the roles and regulatory mechanisms of type-I interferons in Parkinson’s disease

The pathogenesis of Parkinson’s disease (PD) is strongly associated with neuroinflammation, and type I interferons (IFN-I) play a crucial role in regulating immune and inflammatory responses. However, the specific features of IFN in different cell types and the underlying mechanisms of PD have yet to be fully described. In this study, we analyzed the GSE157783 dataset, which includes 39,024 single-cell RNA sequencing results for five PD patients and six healthy controls from the Gene Expression Omnibus database. After cell type annotation, we intersected differentially expressed genes in each cell subcluster with genes collected in The Interferome database to generate an IFN-I-stimulated gene set (ISGs). Based on this gene set, we used the R package AUCell to score each cell, representing the IFN-I activity. Additionally, we performed monocle trajectory analysis, and single-cell regulatory network inference and clustering (SCENIC) to uncover the underlying mechanisms. In silico gene perturbation and subsequent experiments confirm NFATc2 regulation of type I interferon response and neuroinflammation. Our analysis revealed that microglia, endothelial cells, and pericytes exhibited the highest activity of IFN-I. Furthermore, single-cell trajectory detection demonstrated that microglia in the midbrain of PD patients were in a pro-inflammatory activation state, which was validated in the 1-Methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced PD mouse model as well. We identified transcription factors NFATc2, which was significantly up-regulated and involved in the expression of ISGs and activation of microglia in PD. In the 1-Methyl-4-phenylpyridinium (MPP+)-induced BV2 cell model, the suppression of NFATc2 resulted in a reduction in IFN-β levels, impeding the phosphorylation of STAT1, and attenuating the activation of the NF-κB pathway. Furthermore, the downregulation of NFATc2 mitigated the detrimental effects on SH-SY5Y cells co-cultured in conditioned medium. Our study highlights the critical role of microglia in type I interferon responses in PD. Additionally, we identified transcription factors NFATc2 as key regulators of aberrant type I interferon responses and microglial pro-inflammatory activation in PD. These findings provide new insights into the pathogenesis of PD and may have implications for the development of novel therapeutic strategies.

Exploring the molecular mechanisms by which per- and polyfluoroalkyl substances induce polycystic ovary syndrome through in silico toxicogenomic data mining

The pathogeny of polycystic ovary syndrome (PCOS) is intricate, with endocrine disruptors (EDCs) being acknowledged as significant environmental factors. Research has shown a link between exposure to per- and polyfluoroalkyl substances (PFAS) and the development and progression of PCOS, although the precise mechanism is not fully understood. This study utilized toxicogenomics and comparative toxicogenomics databases to analyze data and investigate how PFAS mixtures may contribute to the development of PCOS. The results indicated that 74 genes are associated with both PFAS exposure and PCOS progression. Enrichment analysis suggested that cell cycle regulation and steroid hormone synthesis may be crucial pathways through which PFAS mixtures participate in the development of PCOS, involving important genes such as CCNB1 and SRD5A1. Furthermore, the study identified transcription factors (TFs) and miRNAs that may be involved in the onset and progression of PCOS, constructing regulatory networks encompassing TFs-mRNA interactions and miRNA-mRNA relationships to elucidate their regulatory roles in gene expression. By utilizing data mining techniques based on toxicogenomic databases, this study provides relatively comprehensive insights into the association between exposure factors and diseases compared to traditional toxicology studies. These findings offer new perspectives for further in vivo or in vitro investigations and contribute to understanding the pathogenesis of PCOS, thereby providing valuable references for identifying clinical treatment targets.

Rs822336 binding to C/EBPβ and NFIC modulates induction of PD-L1 expression and predicts anti-PD-1/PD-L1 therapy in advanced NSCLC

Efficient predictive biomarkers are needed for immune checkpoint inhibitor (ICI)-based immunotherapy in non-small cell lung cancer (NSCLC). Testing the predictive value of single nucleotide polymorphisms (SNPs) in programmed cell death 1 (PD-1) or its ligand 1 (PD-L1) has shown contrasting results. Here, we aim to validate the predictive value of PD-L1 SNPs in advanced NSCLC patients treated with ICIs as well as to define the molecular mechanisms underlying the role of the identified SNP candidate. rs822336 efficiently predicted response to anti-PD-1/PD-L1 immunotherapy in advanced non-oncogene addicted NSCLC patients as compared to rs2282055 and rs4143815. rs822336 mapped to the promoter/enhancer region of PD-L1, differentially affecting the induction of PD-L1 expression in human NSCLC cell lines as well as their susceptibility to HLA class I antigen matched PBMCs incubated with anti-PD-1 monoclonal antibody nivolumab. The induction of PD-L1 expression by rs822336 was mediated by a competitive allele-specificity binding of two identified transcription factors: C/EBPβ and NFIC. As a result, silencing of C/EBPβ and NFIC differentially regulated the induction of PD-L1 expression in human NSCLC cell lines carrying different rs822336 genotypes. Analysis by binding microarray further validated the competitive allele-specificity binding of C/EBPβ and NFIC to PD-L1 promoter/enhancer region based on rs822336 genotype in human NSCLC cell lines. These findings have high clinical relevance since identify rs822336 and induction of PD-L1 expression as novel biomarkers for predicting anti-PD-1/PD-L1-based immunotherapy in advanced NSCLC patients.

Abstract 2531: rs822336 as a predictive biomarker for anti-PD-1/PD-L1 immunotherapy in advanced NSCLC: Unraveling molecular mechanisms

Abstract Efficient predictive biomarkers are needed for immune checkpoint inhibitor (ICI)-based immunotherapy in non-small-cell lung cancer (NSCLC). So far, testing the predictive value of single nucleotide polymorphisms (SNPs) in programmed cell death 1 (PD-1) or its ligand 1 (PD-L1) has shown contrasting results. Here, we aimed to validate the predictive value of PD-L1 SNPs in advanced NSCLC patients treated with ICIs as well as to define the molecular mechanisms underlying the role of identified SNP candidate. rs822336 SNP efficiently predicted response to anti-PD-1/PD-L1-based immunotherapy in advanced NSCLC patients as compared to rs2282055 and rs4143815 SNPs. rs822336 SNP mapped on promoter/enhancer region of PD-L1, differentially affecting the induction of PD-L1 expression in human NSCLC cell lines. The induction of PD-L1 expression by rs822336 SNP was predicted by allele-specificity binding of two identified transcription factors: C/EBPβ and NFIC. As a result, silencing of C/EBPβ and NFIC differentially modulated the induction of PD-L1 expression in human NSCLC cell lines carrying different rs822336 genotypes. In addition, binding microarray validated the allele- specificity binding of C/EBPβ and NFIC to PD-L1 promoter/enhancer region based on rs822336 genotype in human NSCLC cell lines. Lastly, the induction of PD-L1 expression by rs822336 genotype differentially affected the susceptibility to anti-PD-1 monoclonal antibody nivolumab of human NSCLC cell lines co-cultured with HLA class I antigen matched PBMC. These results have clinical relevance since identified rs822336 SNP and the induction of PD-L1 expression as novel biomarkers for predicting ICI-based immunotherapy in NSCLC patients. Citation Format: Giovanna Polcaro, Luigi Liguori, Valentina Manzo, Annalisa Chianese, Giuliana Donadio, Alessandro Caputo, Giosuè Scognamiglio, Federica Dell'Annunziata, Maddalena Langella, Graziamaria Corbi, Alessandro Ottaiano, Marco Cascella, Francesco Perri, Margot De Marco, Jessica Dal Col, Valentina Pagliara, Pio Zeppa, Amelia Filippelli, Gianluigi Franci, Fabrizio Dal Piaz, Valeria Conti, Stefano Pepe, Francesco Sabbatino. rs822336 as a predictive biomarker for anti-PD-1/PD-L1 immunotherapy in advanced NSCLC: Unraveling molecular mechanisms [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2531.

Abstract 1721: Epigenetic heterogeneity of osteosarcoma reveals distinct cellular states driven by enhancer regulation

Abstract Osteosarcoma (OS) is characterized by structural rearrangements and copy number changes which drive considerable heterogeneity. What is less clear is how these genetic rearrangements alter are in turn regulated at the epigenetic level to drive gene expression. Defining the epigenetic circuitry of osteosarcoma could help to understand the role of chromatin accessibility in determining cell plasticity. Chromatin accessibility can prime gene expression and define a cellular state. As chromatin accessibility is a major determinant of epigenetic transcriptional regulation, understanding the variability of chromatin accessibility could identify clinically-relevant subtypes and biomarkers of therapy response in Osteosarcoma, a disease that has seen few advances in therapy for over 40 years. Using ATAC-seq, we identified two epigenetic subtypes (EC1 and EC2) of OS with distinct chromatin accessibility. These studies were done in a panel of 11 PDX-derived cell lines and 9 established OS cell lines. We also performed ATACseq on the matching PDX for the 11 PDX-derived lines as well as 8 primary tumor samples. Analysis of transcription factor (TF) motifs and footprints of ATAC-seq peaks identified transcription factors distinctly activated in these two subtypes. For example, EC1 is characterized by high level of activity of developmental transcription factors including RUNX2, MEF2C and homeobox TFs. In contrast, EC2 is characterized by high activity of AP1 transcription factors such as FOSL1 and FOSL2. In order to understand the underlying transcriptional circuitry of these cell states, we performed CUT&RUN assay for the complete panel of PDX-derived cell lines. We found that the subtypes are driven by enhancer regulation (H3K27ac). We defined the specific Core Regulatory Circuitry (CRC) per subtype by defining the superenhancers by ROSE. We overlapped ATAC-seq data in the acetylated regions to demarcate TF binding regions dramatically and reduce the search space for TF cis-regulatory sites. In parallel, we used our PDX-derived cell line panel to screen cluster-specific targeted therapies and found differential responses dependent on cellular states defined by chromatin accessibility. For example, cell lines in the EC2 cluster are marked by upregulation of AP1 transcription factors, have evidence of ERK activation and are highly responsive to ERK inhibitors. In contrast cell lines in the EC1 cluster are sensitive to AURKA and AURKB inhibitors. Single-cell RNAseq analysis indicates that these subtypes may coexist within a single tumor. In summary, we discovered two epigenetically distinct cell states that are controlled by a state-specific collection of transcription factors, creating a gene signature that may aid in distinguishing osteosarcoma subclasses and predicting treatment response. Citation Format: Eunice Lopez Fuentes, Andrew Clugston, Alex Lee, Leanne Sayles, Maria Pons, Alejandro Sweet-Cordero. Epigenetic heterogeneity of osteosarcoma reveals distinct cellular states driven by enhancer regulation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1721.

Abstract 5425: MITF/TFE regulatory programs in neural crest migration are co-opted in melanoma metastasis

Abstract Introduction: Microphthalmia-associated transcription factor (MITF) is a critical regulator of melanocyte differentiation and melanoma oncogenesis. Melanoma expression profiling has revealed a strong trend between low MITF expression levels and invasive behavior. However, it is unclear how low levels of MITF are connected to invasive behavior. Preliminary data from our lab has identified transcription factor E3 (TFE3), a MITF paralog, as a transcriptional regulator in MITF-low melanoma states. We hypothesize that in melanoma cells with low MITF levels, TFE3 promotes invasion. To assess the possibility that the antagonistic regulatory interaction between MITF and a paralog was coopted from the embryo, we examine migratory behavior of neural crest cells in zebrafish embryos that are wild-type, mitfa loss-of-function (LOF) mutants, tfec (TF3 ortholog) LOF mutants, or mitfa/tfec double LOF embryos. Methods: We evaluated TFE3 levels by Western blot in a panel of melanoma cell lines known to express a range of MITF expression levels. We mutated TFE3 exon 4, which encodes the DNA binding domain, using a single guide RNA, and assessed cellular invasive potential using an in vitro transwell invasion assay. CUT&RUN sequencing was used to profile TFE3 genomic binding. Zebrafish embryos were generated in which the mitfa promoter drove expression of RNA encoding green fluorescent protein (GFP), and of the genotypes mentioned above. From transgenic wild-type and mitfa LOF mutant embryos we isolated GFP-expressing cells and conducted single cell-RNA sequencing. We assessed migration of GFP-labeled cells by fluorescent microscopy in 20-48 hour post fertilization zebrafish embryos of all genotypes mentioned above. Results: We found that melanoma cell lines with high levels of MITF (SKMEL3 and SKMEL28) had low levels of TFE3 protein, and those with low levels of MITF (A375 and RPMI 7952) had high levels of TFE3 protein. The TFE3-high cell lines were more invasive in vitro than the TFE3-low cell lines. TFE3-high cell lines depleted of TFE3 were less in invasive in vitro than parental cells. CUT&RUN profiling of TFE3 demonstrates that TFE3 binds mesenchymal-like enhancers in MITF-low cell lines. Single cell RNA sequencing revealed that in a melanocyte precursor cluster present in both wild types and in mitfa mutants, expression of tfec was higher in the latter. Finally, migration of GFP-expressing cells was higher in mitfa LOF mutant embryos than in mitfa/tfec double LOF mutant embryos. Conclusion: These data indicate that reduction of MITF expression up-regulates TFE3 expression in melanoma and tfec in zebrafish melanocytes, although the mechanism of this regulation is unclear. They also show that TFE3 and Tfec promote migration of metastatic melanoma and melanocyte precursors, respectively. Because regulatory mechanisms in cancer are often coopted from embryonic cells, studying the embryo may illuminate cancer pathogenesis. Citation Format: Jeremy Chang, Katelyn Campbell, Rachel Moore, Robert Cornell, Colin Kenny. MITF/TFE regulatory programs in neural crest migration are co-opted in melanoma metastasis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5425.

Abstract 860: Pan-tissue master regulator inference reveals mechanisms of MHC alterations in cancers

Abstract Introduction: Major histocompatibility complex (MHC) genes are an integral part of the adaptive immune system. The T-cells can detect and kill cancer cells through the recognition of mutant peptides on the cell surface via the MHC. As a result, many cancers evade the immune system by altering their MHC regulation which can also lead to resistance to immune checkpoint blockade (ICB). Therefore, understanding MHC regulation in both baseline (normal state) and cancer is critical for uncovering mechanisms behind MHC alterations. Here, we have undertaken a pan-tissue evaluation to comprehensively decode MHC transcriptional regulation in healthy tissues and various cancers using a large compendium of single-cell RNA-seq (scRNA-seq) datasets. Methods: To study MHC class I (MHC-I) and MHC class II (MHC-II) transcriptional regulation at baseline we leveraged a large-scale scRNA-seq dataset encompassing 18 tissues and 124 epithelial cell types. Upon re-clustering and annotation, we investigated MHC expression across cell types and tissues and quantified its heterogeneity using the Gini coefficient. Next, we sought to identify transcription factors (TF) predictive of MHC-I and MHC-II expression, for that, we employed a master regulator inference that utilizes uni- and multi- regression models. Further, to investigate MHC and nominated TFs dysregulation in cancer, we curated a compendium of scRNA-seq datasets comprising 43 datasets, 20 cancer types, across 538 patients. Results: In normal epithelial cell types, we observed a large range (~8 fold) in MHC-I expression. We also detected MHC-II expression in unexpected cell types such as club cells in the prostate. We found that lung epithelial cells showed elevated MHC-II expression. Immunohistochemistry was performed to validate these findings. Using master regulator inference, we nominated 104 and 107 TFs which predict MHC-I and MHC-II expression, respectively. The nominated TFs showed significant enrichment (p < 0.001) for known TFs, alongside putative novel transcriptional regulators such as YBX1 (MHC-I p < 2e-16, MHC-II p = 8e-07) and XBP1 (MHC-I p < 2e-16, MHC-II p = 7e-04). Using our single-cell compendium of 20 cancer types we also observed a pan-cancer repression in MHC genes (p < 0.001). Next, we utilized an ICB cohort to identify specific TFs that could predict therapeutic benefits. Interestingly, XBP1 (p < 1e-16) and SP100 (p < 2.2e-08) were strong predictors of patients' survival. We also observed a large heterogeneity in MHC-II expression among colon cancer patients. Upon investigation, we found that patients with high MHC-II expression were mismatch repair deficient, this implicates MHC-II upregulation as an immune evasion mechanism. Conclusion: In conclusion, we have comprehensively evaluated MHC expression in 124 epithelial cell types and across 20 cancers identifying TFs predictive of MHC-I and MHC-II expression and their effects on patient outcomes. Citation Format: Mahnoor N. Gondal, Rahul Mannan, Yi Bao, Jing Hu, Marcin Cieslik, Arul M. Chinnaiyan. Pan-tissue master regulator inference reveals mechanisms of MHC alterations in cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 860.

Abstract 6883: Investigation of tumor-immune interactions in pediatric sarcomas using single-cell multi-omics

Abstract Background: Pediatric sarcoma represents the second most common solid tumor in children. Despite advances in multimodal therapies, one-third of sarcoma patients do not survive the disease. Over the past few decades, the development of novel therapeutic strategies for sarcoma has been impeded by an insufficient understanding of the tumor microenvironment (TME). In particular, the potential of immunotherapy remains constrained by the gap of knowledge about the molecular and functional phenotypes of the immune cells in the sarcoma TME. Methods: To address this knowledge gap, we collected treatment-naïve tumor samples from 32 patients with five pediatric sarcoma subtypes. We employed a single-nuclei RNA+ATAC-Seq multi-omics assay to comprehensively characterize the transcriptomic and epigenomic heterogeneity of tumor and immune cells within the sarcoma TME. Results: Our analysis revealed that tumor-associated macrophages (TAMs) were the most abundant immune cell type in the sarcoma TME. We identified seven distinct TAM subpopulations, each exhibiting unique gene expression and chromatin accessibility patterns. Among these, TAM subsets with higher expression of SPP1 and C1QC genes displayed the strongest immunosuppressive potential. Transcriptional regulatory network (TRN) analysis identified transcription factors that were most likely to drive the phenotypes of SPP1+ and C1QC+ TAMs, including ELF2, JUND and RUNX1. Through cell-cell communication analysis, we discovered that SPP1+ TAMs interact with T cells via SPP1-CD44 signaling, while C1QC+ TAMs interact with NK cells through HLA-E-KLRC1 signaling, suggesting the potential involvement of these signaling pathways in TAM-mediated suppression of these cytotoxic lymphocytes. We prioritized ligand-receptor gene pairs, such as SEMA3D-NRP1 and LTBP3-ITGB5, which likely mediate the interaction between malignant sarcoma cells and SPP1+/C1QC+ TAMs based on their dominance across sarcoma subtypes and association with poorer clinical outcomes. On the other hand, our analysis revealed that sarcoma subtype-specific interactions between TAMs and malignant cells are common, highlighting the heterogeneity of signaling events across sarcoma subtypes. Conclusion and Significance: Our study presents a comprehensive single-cell multi-omics characterization of pediatric sarcomas and sheds light on its tumor microenvironment. By identifying unique markers for immunosuppressive TAM subpopulations and elucidating intercellular interactions promoting tumor development, this study proposes potential therapeutic targets for sarcoma treatment based on the role of TAMs in sarcoma TME. Citation Format: Zhan Zhang, Kyung Jin Ahn, Changya Chen, Rumeysa Biyik Sit, Hesham Mohei, Brian Lockhart, Malay Haldar, Kathrin Bernt, Vinodh Pillai, Kai Tan. Investigation of tumor-immune interactions in pediatric sarcomas using single-cell multi-omics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6883.