Identify Gene Expression Patterns Research Articles

Whole-blood transcriptome unveils altered immune response in acute myocardial infarction patients with aortic valve sclerosis

Abstract Funding Acknowledgements Type of funding sources: Foundation. Main funding source(s): Fondazione Umberto Veronesi (Research Grant 2011-12 to GIC) Fondazione Gigi e Pupa Ferrari ONLUS (FPF-14 to PP) Background Aortic valve sclerosis (AVSc) presents similar pathogenetic mechanisms to coronary artery disease (CAD) and is associated with short- and long-term mortality in CAD patients. Evidence of AVSc-specific pathophysiological traits in acute myocardial infarction (AMI) is currently lacking. Purpose We aimed to identify a blood-based transcriptional signature that could differentiate AVSc from non-AVSc patients during AMI. Methods Whole-blood transcriptome of AVSc (n = 44) and no-AVSc (n = 66) patients with AMI was assessed by RNA-sequencing on hospital admission. Feature selection, differential expression, and enrichment analyses were performed to identify gene expression patterns discriminating AVSc from no-AVSc and infer functional associations. Multivariable Cox regression analysis was used to estimate the hazard ratios of cardiovascular events in AVSc versus no-AVSc patients. Results This cross-sectional study identified a panel of 100 informative genes capable of distinguishing AVSc from no-AVSc patients with 94% accuracy. Further analysis revealed significant mean differences in 143 genes, of which 30 genes withstood correction for age and previous AMI or coronary interventions. Functional inference unveiled a significant association between AVSc and key biological processes, including acute inflammatory responses, type I interferons (IFN) response, platelet activation, and hemostasis. Notably, AMI patients with AVSc exhibited a significantly higher incidence of adverse cardiovascular events during a 10-year follow-up period, with a full adjusted hazard ratio of 2.4 (95% CI: 1.3–4.5). Conclusions Our findings shed light on the molecular mechanisms underlying AVSc and provide potential prognostic insights for AMI patients with AVSc. During AMI, AVSc patients showed increased type I IFN response and earlier adverse cardiovascular outcomes. Novel pharmacological therapies aiming at limiting type I IFN response during or immediately after AMI might improve poor cardiovascular outcomes of AMI patients with AVSc.

TRANSCRIPTOMIC DIFFERENCES IN PERIPHERAL MONOCYTE POPULATIONS IN SEPTIC PATIENTS BASED ON OUTCOME.

Postsepsis early mortality is being replaced by survivors who experience either a rapid recovery and favorable hospital discharge or the development of chronic critical illness with suboptimal outcomes. The underlying immunological response that determines these clinical trajectories remains poorly defined at the transcriptomic level. As classical and nonclassical monocytes are key leukocytes in both the innate and adaptive immune systems, we sought to delineate the transcriptomic response of these cell types. Using single-cell RNA sequencing and pathway analyses, we identified gene expression patterns between these two groups that are consistent with differences in TNF-α production based on clinical outcome. This may provide therapeutic targets for those at risk for chronic critical illness in order to improve their phenotype/endotype, morbidity, and long-term mortality.

Abstract PO5-15-09: DNA damage induced necroptosis predicts response to radioimmunotherapy

Abstract Background: More than half of all cancer patients receive radiotherapy (RT) during their cancer experience. DNA damage induced by RT can initiate a pro-inflammatory immune response within the tumor microenvironment (TME), yet this response is not uniformly observed across all tumors. Mre11 is one of the first responders to double stranded breaks and coordinates the DNA damage response. Recent work in our lab reveals that Mre11 is required for cGAS mediated detection of cytoplasmic DNA, in turn activating STING to engage the type I interferon signaling pathway, downstream of which can activate ZBP1/RIPK3/MLKL mediated necroptosis. The purpose of this study is to determine if expression of the necroptotic pathway may predict whether breast tumors benefit from RT to overcome ICI resistance and induce systemic anti-tumor immunity in the form of an abscopal response. Methods: Four Trp53-/- Balb/c breast cancer syngeneic allograft models with low tumor mutational burden and resistance to dual ICI (anti-PD1 and anti-CTLA4, BioXcell) were used. Mice were implanted with bilateral tumors and randomly divided into four treatment cohorts: untreated, RT, ICI, or RT+ICI, where RT (8Gyx3) was administered to one tumor. Two lines exhibited abscopal responses to RT+ICI (i.e., “abscopal models”), whereas the other two did not (i.e., “non-abscopal models”). To identify gene expression patterns associated with abscopal responding breast tumors, we performed spatial transcriptomic analysis of tumors 10 days after initiating treatment using the GeoMx whole transcriptome assay targeting panCK+ tumor cells and tumor adjacent CD45+ immune cells (N >5 for each treatment group and tumor type). Unsupervised hierarchical clustering was performed to identify gene expression patterns across areas of interest. Genes selectively induced by RT+ICI in abscopal models that were not induced in non-abscopal models were identified using two-tailed t-test and FDR correction for multiple testing (FDR< 5%). DeSEQ2 and GSEA analysis were performed using publicly available mouse gene sets (Broad Institute). Results: The TME in untreated tumors in the abscopal models demonstrate upregulation in the B cell survival pathway and apoptotic pathways compared to untreated tumors in non-abscopal models. Hierarchical clustering of immune related genes in CD45+ segments of RT+ICI treated tumors exhibiting an abscopal response revealed a global shift in gene expression profiles after treatment. GSEA analysis of CD45+ segments from abscopal models shows that RT+ICI treatment results in enrichment of the interferon mediated signaling pathway including interferon alpha (p< 0.0001), interferon beta (p< 0.0001), type II interferon response (p< 0.0001), and antigen processing and presentation (p< 0.0001). In tumor cells of breast cancers demonstrating the abscopal response, Isg15 and Zbp1 are highly induced by RT+ICI. The necroptotic pathway, including Zbp1, Ripk3, and Mlkl, are significantly higher expressed in the panCK+ tumors known to demonstrate the abscopal response. Conclusion: Breast cancer models with an abscopal response to RT+ICI demonstrate higher expression of Isg15 and Zbp1, both of which are involved in secreted inflammatory signaling. The TME in these models have increased interferon signaling and antigen presentation in response to RT+ICI. The role of DNA damage induced necroptosis in generating an abscopal response in breast cancer warrants further investigation as a potential biomarker for response to RT+ICI combination therapy. Citation Format: Anna Goddard, Qinhong Wang, Minguk Cho, Lynn Lerner, Gaorav Gupta. DNA damage induced necroptosis predicts response to radioimmunotherapy [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-15-09.

Strand-Specific RNA Sequencing Reveals Gene Expression Patterns in F1 Chick Breast Muscle and Liver after Hatching.

Heterosis refers to the phenomenon where hybrids exhibit superior performance compared to the parental phenotypes and has been widely utilized in crossbreeding programs for animals and crops, yet the molecular mechanisms underlying this phenomenon remain enigmatic. A better understanding of the gene expression patterns in post-hatch chickens is very important for exploring the genetic basis underlying economically important traits in the crossbreeding of chickens. In this study, breast muscle and liver tissues (n = 36) from full-sib F1 birds and their parental pure lines were selected to identify gene expression patterns and differentially expressed genes (DEGs) at 28 days of age by strand-specific RNA sequencing (ssRNA-seq). This study indicates that additivity is the predominant gene expression pattern in the F1 chicken post-hatch breast muscle (80.6% genes with additivity) and liver (94.2% genes with additivity). In breast muscle, Gene Ontology (GO) enrichment analysis revealed that a total of 11 biological process (BP) terms closely associated with growth and development were annotated in the identified DEG sets and non-additive gene sets, including STAT5A, TGFB2, FGF1, IGF2, DMA, FGF16, FGF12, STAC3, GSK3A, and GRB2. Kyoto Encyclopedia of Genes and Genomes (KEGG) annotation presented that a total of six growth- and development-related pathways were identified, involving key genes such as SLC27A4, GLUL, TGFB2, COX17, and GSK3A, including the PPAR signaling pathway, TGF-beta signaling pathway, and mTOR signaling pathway. Our results may provide a theoretical basis for crossbreeding in domestic animals.

Abstract 7609: Potential gene expression meta-signatures predict neoadjuvant chemotherapy response in invasive breast cancer

Abstract Early prediction of Neoadjuvant Chemotherapy (NAC) response is crucial for women with locally advanced breast cancer (BC), given their low response rates. This study aims to identify gene expression patterns and tumor microenvironment (TME) characteristics associated with resistance to NAC, which could significantly impact tumor progression and treatment outcomes. The study encompassed differential gene expression comparing non-responders and responders, enrichment analysis, tumor microenvironment estimation, and cytokines identification from a female patient's cohort with distinct molecular subtypes and candidates to NAC at the Colombian National Cancer Institute. Candidate differentially expressed genes validated with RT-PCR in a larger validation cohort and corroborated in several publicly available databases, including associated treatment drugs. Distinct gene expression profiles were observed between responders and non-responders, emphasizing immune system-related pathways such as IL-17 signaling, B cell receptor signaling, complement and coagulation cascades, natural killer cell-mediated cytotoxicity, and NF-kB signaling. Immune-related genes (AGTR1, APOD, CCL19, CGA, ECEL1, NPY1R, NTNG1, PCSK1, PFDN2, S100B, TPRG1, WDR5B, ZNF385B) were identified as biomarkers correlated with non-response and worse prognosis. Responders showed increased B cell populations, CD4+ and CD8+ effector memory T-cells in lymphoid groups, while non-responders displayed elevated levels of CD8+ naive T-cells. Additionally, responders revealed upregulated myeloid cell populations like macrophages and dendritic cells. Several cytokines like IL1B, IL-2, IL-4, IL-12, IL-21, IL-22, IL-36, and TWEAK showed elevated expression in non-responders. Dexamethasone, Vinblastine, and Streptozocin were candidate drugs that interacted with AGTR1, CGA, and S100B, respectively and are associated with progression and metastasis. Logistic regression revealed that overexpression of CGA showed a higher probability (OR:1.83, p=0.03) while ECEL1 had a lower probability (OR=0.44, p=0.04) in non-responders compared to responders who lacked expression of these genes. Immune-related genes and various subtypes of immune cells within the TME exhibit correlations with response to NAC, and several cell fractions significantly changed before and after NAC. These results suggest meta-signatures that warrant further evaluation as concordance assessment between immunohistochemistry (IHC) and gene expression profiling, in addition to an extensive validation to triage patients before NAC and target personalized interventions. Detection and evaluation of TME components are essential to predict NAC efficacy and avoid disease relapse. Finally, these findings emphasize the importance of assessing admixed populations to facilitate novel findings and alleviate disparities. Citation Format: Hedda Michelle Guevara-Nieto, Rafael S. Parra-Medina, Jovanny Zabaleta, Liliana Lopez-Kleine, Alba L. Combita. Potential gene expression meta-signatures predict neoadjuvant chemotherapy response in invasive breast cancer [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 7609.

Identification of genetics and hormonal factors involved in Quercus robur root growth regulation in different cultivation system

Understanding the molecular processes and hormonal signals that govern root growth is of paramount importance for effective forest management. While Arabidopsis studies have shed light on the role of the primary root in root system development, the structure of root systems in trees is considerably more intricate, posing challenges to comprehend taproot growth in acorn-sown and nursery-cultivated seedlings. In this study, we investigated Quercus robur seedlings using rhizotrons, containers, and transplanted containers to rhizotrons, aiming to unravel the impact of forest nursery practices on processes governing taproot growth and root system development. Root samples were subjected to RNA-seq analysis to identify gene expression patterns and perform differential gene expression and phytohormone analysis. Among studied cultivation systems, differentially expressed genes (DEGs) exhibited significant diversity, where the number of co-occurring DEGs among cultivation systems was significantly smaller than the number of unique DEGs in different cultivation systems. Moreover, the results imply that container cultivation triggers the activation of several genes associated with linolenic acid and peptide synthesis in root growth. Upon transplantation from containers to rhizotrons, rapid enhancement in gene expression occurs, followed by gradual reduction as root growth progresses, ultimately reaching a similar expression pattern as observed in the taproot of rhizotron-cultivated seedlings. Phytohormone analysis revealed that taproot growth patterns under different cultivation systems are regulated by the interplay between auxin and cytokinin concentrations. Moreover, the diversification of hormone levels within the root zone and cultivation systems allows for taproot growth inhibition and prompt recovery in transplanted seedlings. Our study highlights the crucial role of hormone interactions during the early stages of taproot elongation, influencing root system formation across.

Whole-Blood Transcriptome Unveils Altered Immune Response in Acute Myocardial Infarction Patients With Aortic Valve Sclerosis.

Aortic valve sclerosis (AVSc) presents similar pathogenetic mechanisms to coronary artery disease and is associated with short- and long-term mortality in patients with coronary artery disease. Evidence of AVSc-specific pathophysiological traits in acute myocardial infarction (AMI) is currently lacking. Thus, we aimed to identify a blood-based transcriptional signature that could differentiate AVSc from no-AVSc patients during AMI. Whole-blood transcriptome of AVSc (n=44) and no-AVSc (n=66) patients with AMI was assessed by RNA sequencing on hospital admission. Feature selection, differential expression, and enrichment analyses were performed to identify gene expression patterns discriminating AVSc from no-AVSc and infer functional associations. Multivariable Cox regression analysis was used to estimate the hazard ratios of cardiovascular events in AVSc versus no-AVSc patients. This cross-sectional study identified a panel of 100 informative genes capable of distinguishing AVSc from no-AVSc patients with 94% accuracy. Further analysis revealed significant mean differences in 143 genes, of which 30 genes withstood correction for age and previous AMI or coronary interventions. Functional inference unveiled a significant association between AVSc and key biological processes, including acute inflammatory responses, type I IFN (interferon) response, platelet activation, and hemostasis. Notably, patients with AMI with AVSc exhibited a significantly higher incidence of adverse cardiovascular events during a 10-year follow-up period, with a full adjusted hazard ratio of 2.4 (95% CI, 1.3-4.5). Our findings shed light on the molecular mechanisms underlying AVSc and provide potential prognostic insights for patients with AMI with AVSc. During AMI, patients with AVSc showed increased type I IFN (interferon) response and earlier adverse cardiovascular outcomes. Novel pharmacological therapies aiming at limiting type I IFN response during or immediately after AMI might improve poor cardiovascular outcomes of patients with AMI with AVSc.

SPI1 Is the Master Regulator of the Small Cell Variant of Anaplastic Large Cell Lymphoma Controlled By Methylation of SPI1 Gene Promoter Region

Introduction The small cell variant of anaplastic large cell lymphoma (SC-ALCL) is a subtype of anaplastic lymphoma kinase (ALK)-positive ALCL characterized by chemoresistance and poor prognosis, necessitating novel treatment strategies. Recent advances in targeted therapies have resulted in significant responses in various chemoresistant hematological malignancies. Therefore, understanding the underlying oncogenic mechanisms and identifying potential therapeutic targets are critical for overcoming SC-ALCL. Immunohistochemically, SC-ALCL comprises two distinct tumor cell populations: small tumor cells demonstrating negative to weak ALK and CD30 protein expression, and large tumor cells with robust expression of these proteins. We previously reported that small tumor cells display particular resistance to chemotherapy; however, the mechanisms underlying chemoresistance and the molecular characteristics of small tumor cells remain elusive. This study aimed to elucidate the molecular attributes of small tumor cells and pave the way for the development of innovative treatment approaches. Methods We investigated the characteristics of small tumor cells using patient blood samples diagnosed with SC-ALCL leukemic presentation and publicly available RNA-seq data from eight ALK-positive ALCL cell lines. Small and large tumor cells were separated from blood samples based on CD30 expression using CD30 - a phycoerythrin antibody and a magnetic bead separation kit. The presence of the NPM-ALK fusion gene was confirmed in both populations by PCR analysis. Bulk RNA-seq analysis was performed on four samples: small and large tumor cells at the onset and at the first (mainly occupied by small tumor cells) and second (mainly occupied by large tumor cells) relapses. Gene set enrichment analysis was used to identify gene expression patterns in small tumor cells. Signature genes of small tumor cells were identified by filtering with the following thresholds: false discovery rate-adjusted P-value <0.05, and fold-change >2 compared to large tumor cells. The transcription factors regulating the signature genes of small tumor cells were predicted using the g:Profiler software. Result Bulk RNA sequencing analysis of the four blood samples revealed that the SPI1 gene was significantly upregulated in small tumor cells compared to that in large tumor cells. SPI1 has emerged as the highest-scoring transcription factor, regulating the expression of 570 genes that characterize small tumor cells. Approximately 70% of these signature genes overlapped with the SPI1 target genes. Furthermore, gene set enrichment analysis revealed that small tumor cells display increased anti-apoptotic gene activity and decreased cell proliferation gene activity. These observations were validated by integrated gene expression analysis using publicly available RNA-seq data from eight ALK-positive ALCL cell lines (Figure 1). The study found high expression of SPI1 and SPI1 targeted genes in small tumor cells, accompanied by low expression of anti-apoptotic genes in ALK-positive ALCL cell lines, which were more analogous to large tumor cells than small tumor cells. Single-cell RNA-seq analysis validated the high expression of the SPI1 gene in small tumor cells. To explore the mechanism regulating SPI1 gene expression, we examined DNA methylation patterns in the SPI1 promoter region using conventional bisulfite sequencing. Conventional bisulfite sequencing revealed a hypomethylated SPI1 promoter region in small tumor cells and a hypermethylated region in large tumor cells, potentially accounting for the differential SPI1 expression. Conclusion This study highlights SPI1gene as the master regulator determining the unique characteristics of small tumor cells in SC-ALCL. Furthermore, the regulation of SPI1 gene expression appeared to be mediated by DNA methylation patterns within the SPI1 promoter region. These findings pave the way for innovative treatment strategies for SC-ALCL such as SPI1 targeting therapy and methylation-based therapies, offering promising avenues for treating SC-ALCL.

Gene selection and tumor identification based on a hybrid of the multi-filter embedded recursive mountain gazelle algorithm

Microarray gene expression data are useful for identifying gene expression patterns associated with cancer outcomes; however, their high dimensionality make it difficult to extract meaningful information and accurately classify tumors. Hence, developing effective methods for reducing dimensionality while preserving relevant information is a crucial task. Hybrid-based gene selection methods are widely proposed in the gene expression analysis domain and can still be enhanced in terms of efficiency and reliability. This study proposes a new hybrid-based gene selection method, called multi-filter embedded mountain gazelle optimizer (MUL-MGO), which utilizes two filters and an embedded method to remove irrelevant genes, followed by selecting the most relevant genes using recently developed MGO algorithm. To the best of our knowledge, this is the first work to exploit MGO as a gene or feature selection method. A new version of MGO, called recursive mountain gazelle optimizer (RMGO), which implements MGO algorithm recursively to avoid local optima, minimize search space, and obtain minimum gene count without decreasing the classifier’s performance, is developed. The proposed RMGO is used to develop a new hybrid gene selection method employing similar filters and embedded methods as MUL-MGO, but with a recursive MGO algorithm version. The resulting method is called multi-filter embedded recursive mountain gazelle optimizer (MUL-RMGO). Several classifiers are used for cancer classification. Accordingly, several experimental studies are performed on eight microarray gene expression datasets to demonstrate the proficiencies of MUL-MGO and MUL-RMGO methods. The experimental findings indicate the efficiency and productivity of the suggested MUL-MGO and MUL-RMGO methods for gene selection. The methods outperform cutting-edge methods in the literature, with MUL-RMGO exceeding MUL-MGO in terms of accuracy and selected gene count.

Genomic Characterization of Cervical Tumors Driven by Rare High-Risk HPV Subtypes Utilizing a Deep Learning Framework

As many as 30-50% of patients with locally advanced cervical cancer (LACC) experience recurrence after chemoradiation therapy (CRT). More sophisticated prognostic schemes and targeted therapeutic options are urgently needed. Human papillomavirus (HPV) is responsible for the majority of invasive cervical carcinomas, most commonly HPV 16 and 18 subtypes. In large part due to their rarity, little is known about the biologic behavior of LACC driven by non-16/18 HPV genotypes. We hypothesized that rare HPV subtypes drive distinct gene expression patterns. To aid in the common dilemma of limited sample procurement, we developed a tool which leverages population data and generative adversarial neural network (GAN) modelling to exploit patterns of gene expression of small phenotypic groups for downstream analysis. Here, we employed a deep learning approach to identify gene expression patterns unique to tumors caused by rare HPV subtypes. Whole transcriptome analysis of tumor biopsies from an institutional LACC tumor bank were employed including 130 HPV16/18 positive, and at least 3 each of rare HPV subtypes 31, 33, 39, 45, 52, 58, and 59. A Wasserstein GAN model (WGAN) was trained for each rare HPV subtype, and used to generate augmented rare HPV population data for downstream differential expression testing between rare HPV subtypes and HPV16/18. K-means clustering analysis was performed using R stats package. Differential gene expression testing between rare HPV subtype populations was performed using the EdgeR R-package. Pathway Enrichment analysis was conducted using EnrichR software. By minimizing intergroup clustering distance, 3 clusters of HPV driven disease were demonstrated. The first cluster demonstrated biology similar to HPV16 and HPV18. Namely, pathway enrichment analysis performed on lists of differentially expressed genes between GAN augmented rare HPV subtypes (HPV45, HPV52, and HPV58) and classical HPV subtypes 16 and 18, yielded no significant statistical differences. The second cluster demonstrated enriched gene expression in proinflammatory IL-1 and IL-6 family cytokines and focal adhesion signaling (HPV31, HPV33, HPV39) (IL-1 regulation of extracellular matrix, p = 5.0e-6; Oncostatin M signaling, p = 2.0e-7; Integrin Signaling, 2.5e-7). The last cluster demonstrated an increased Th2/myeloid signature (HPV59) (T helper cell surface molecules 1.2e-7, myeloid cell signature 8.5e-9). Utilizing a deep learning architecture to model gene expression of rare HPV subtypes we demonstrate 3 groups of HPV driven cervical cancer biology. These groups include a classical subtype, a high IL-1/IL-6 high subtype, and a myeloid associated subtype. Knowledge of such tumor heterogeneity can aid in the future development of targeted treatment plans and patient prognosis.

Association between gene expression and functional-metabolic architecture in Parkinson's disease.

Gene expression plays a critical role in the pathogenesis of Parkinson's disease (PD). How gene expression profiles are correlated with functional-metabolic architecture remains obscure. We enrolled 34 PD patients and 25 age-and-sex-matched healthy controls for simultaneous 18 F-FDG-PET/functional MRI scanning during resting state. We investigated the functional gradients and the ratio of standard uptake value. Principal component analysis was used to further combine the functional gradients and glucose metabolism into functional-metabolic architecture. Using partial least squares (PLS) regression, we introduced the transcriptomic data from the Allen Institute of Brain Sciences to identify gene expression patterns underlying the affected functional-metabolic architecture in PD. Between-group comparisons revealed significantly higher gradient variation in the visual, somatomotor, dorsal attention, frontoparietal, default mode, and subcortical network (pFDR < .048) in PD. Increased FDG-uptake was found in the somatomotor and ventral attention network while decreased FDG-uptake was found in the visual network (pFDR < .008). Spatial correlation analysis showed consistently affected patterns of functional gradients and metabolism (p = 2.47 × 10-8 ). PLS analysis and gene ontological analyses further revealed that genes were mainly enriched for metabolic, catabolic, cellular response to ions, and regulation of DNA transcription and RNA biosynthesis. In conclusion, our study provided genetic pathological mechanism to explain imaging-defined brain functional-metabolic architecture of PD.

Molecular techniques drive cutting edge advancements in management of cutaneous T cell lymphoma.

Cutaneous 5T cell lymphoma (CTCL), characterized by malignant T cells infiltrating the skin with potential for dissemination, remains a challenging disease to diagnose and treat due to disease heterogeneity, treatment resistance, and lack of effective and standardized diagnostic and prognostic clinical tools. Currently, diagnosis of CTCL practically relies on clinical presentation, histopathology, and immunohistochemistry. These methods are collectively fraught with limitations in sensitivity and specificity. Fortunately, recent advances in flow cytometry, polymerase chain reaction, high throughput sequencing, and other molecular techniques have shown promise in improving diagnosis and treatment of CTCL. Examples of these advances include T cell receptor clonotyping via sequencing to detect CTCL earlier in the disease course and single-cell RNA sequencing to identify gene expression patterns that commonly drive CTCL pathogenesis. Experience with these techniques has afforded novel insights which may translate into enhanced diagnostic and therapeutic approaches for CTCL.

Gene expression profiling of soaked dry beans (Phaseolus vulgaris L.) reveals cell wall modification plays a role in cooking time.

Dry beans (Phaseolus vulgaris L.) are a nutritious food, but their lengthy cooking requirements are barriers to consumption. Presoaking is one strategy to reduce cooking time. Soaking allows hydration to occur prior to cooking, and enzymatic changes to pectic polysaccharides also occur during soaking that shorten the cooking time of beans. Little is known about how gene expression during soaking influences cooking times. The objectives of this study were to (1) identify gene expression patterns that are altered by soaking and (2) compare gene expression in fast-cooking and slow-cooking bean genotypes. RNA was extracted from four bean genotypes at five soaking time points (0, 3, 6, 12, and 18h) and expression abundances were detected using Quant-seq. Differential gene expression analysis and weighted gene coexpression network analysis were used to identify candidate genes within quantitative trait loci for water uptake and cooking time. Genes related to cell wall growth and development as well as hypoxic stress were differentially expressed between the fast- and slow-cooking beans due to soaking. Candidate genes identified in the slow-cooking beans included enzymes that increase intracellular calcium concentrations and cell wall modification enzymes. The expression of cell wall-strengthening enzymes in the slow-cooking beans may increase their cooking time and ability to resist osmotic stress by preventing cell separation and water uptake in the cotyledon.

Transcriptome-Wide Structural Equation Modeling of 13 Major Psychiatric Disorders for Cross-Disorder Risk and Drug Repurposing

Psychiatric disorders display high levels of comorbidity and genetic overlap, necessitating multivariate approaches for parsing convergent and divergent psychiatric risk pathways. Identifying gene expression patterns underlying cross-disorder risk also stands to propel drug discovery and repurposing in the face of rising levels of polypharmacy. To identify gene expression patterns underlying genetic convergence and divergence across psychiatric disorders along with existing pharmacological interventions that target these genes. This genomic study applied a multivariate transcriptomic method, transcriptome-wide structural equation modeling (T-SEM), to investigate gene expression patterns associated with 5 genomic factors indexing shared risk across 13 major psychiatric disorders. Follow-up tests, including overlap with gene sets for other outcomes and phenome-wide association studies, were conducted to better characterize T-SEM results. The Broad Institute Connectivity Map Drug Repurposing Database and Drug-Gene Interaction Database public databases of drug-gene pairs were used to identify drugs that could be repurposed to target genes found to be associated with cross-disorder risk. Data were collected from database inception up to February 20, 2023. Gene expression patterns associated with genomic factors or disorder-specific risk and existing drugs that target these genes. In total, T-SEM identified 466 genes whose expression was significantly associated (z ≥ 5.02) with genomic factors and 36 genes with disorder-specific effects. Most associated genes were found for a thought disorders factor, defined by bipolar disorder and schizophrenia. Several existing pharmacological interventions were identified that could be repurposed to target genes whose expression was associated with the thought disorders factor or a transdiagnostic p factor defined by all 13 disorders. The findings from this study shed light on patterns of gene expression associated with genetic overlap and uniqueness across psychiatric disorders. Future versions of the multivariate drug repurposing framework outlined here have the potential to identify novel pharmacological interventions for increasingly common, comorbid psychiatric presentations.

Abstract 2859: High-resolution lineage tracing for the study of cancer drug persistence at the single-cell level

Abstract Cancer drug persistence allows small fractions of otherwise drug-sensitive populations of cancer cells to survive treatment with anti-cancer drugs. Unlike drug resistance, persistence mechanisms are not driven by genetic mutations, and are thus considered reversible after a ‘drug holiday’ period. While most persistent cells remain in cell cycle arrest under drug treatment, recent work with EGFR-mutant Non-Small Cell Lung Cancer (NSCLC) cell lines has demonstrated that a small fraction of persister cells continue to undergo cell divisions under treatment with EGFR inhibitors. Thus, persister cells have a two-fold potential clinical significance: (i) they can serve as an intermediate state, allowing a non-resistant cancer cell to survive long enough and continue to divide under drug treatment to acquire a resistance mutation; and (ii) cycling persister cells might directly contribute to relapse, without a secondary resistance-driving mutation. Despite this, little is known about the underlying mechanisms by which affect the potential of a given cell to persist, or about the epigenetic traits that govern the distribution of persistence potential in a cell population. In this work, we use high-resolution lineage tracing to study lineages of drug persistent cells within a cancer cell population. Using the PC9 NSCLC cell line as a model, we demonstrate that while most lineages within the PC9 cell population can generate persisters, certain branches within the lineage tree have significantly higher persistence potentials than other branches, suggesting that inherited events determine the probability of a cell to persist under treatment. Moreover, we analyze the rate of change of the potential to persist within a single-cell-derived lineage of NSCLC cells and assess which branches within the lineage tree generate cycling persisters. Furthermore, we couple single-cell RNAseq data with lineage tracing information to identify gene expression patterns that correlate with the probability of drug-naïve cells to persist under drug treatment, allowing for insight into the cellular and molecular mechanisms underlying the continuum of the probability to persist. Finally, we demonstrate that while persistent-derived PC9 cells are indeed resensitized after a drug holiday, they give rise to a significantly higher proportion of cycling persister cells upon resumption of drug treatment, allowing for a rapid repopulation of the cell culture by cycling persisters. These results suggest that lineage tracing is a powerful tool to study drug-induced persistence and resistance and we will apply it to multiple other cell lines and tumor types. Citation Format: Benny Zhitomirsky, Jideofor Ezike, Elizabeth Hopkins, Brian P. Danysh, Laxmi Parida, Yaara Oren, Gad Getz. High-resolution lineage tracing for the study of cancer drug persistence at the single-cell level [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2859.

Transcriptomic analyses reveal three distinct molecular subgroups of Merkel cell carcinoma with differing prognoses.

Merkel cell carcinoma (MCC) is a cutaneous neuroendocrine malignancy with a poor prognosis and an unknown cell of origin. Proffered cells of origin include epithelial stem cells of the hair follicle or interfollicular epidermis, dermal stem cells and pro/pre- or pre-B cells. MCC has also been proposed to have more than one cell of origin and indeed to represent more than one type of carcinoma, currently grouped together due to phenotypic similarities. We explored the heterogeneous nature of MCC by studying the most variably expressed genes with the goal of identifying gene expression patterns that are either clinically relevant or have implications regarding the cell(s) of origin. We performed RNA sequencing on primary tumor samples from 102 patients and identified the top 200 most variably expressed genes. These genes and the tumor samples were hierarchically clustered based on their expression. The functions of three gene clusters exhibiting clearly divergent expression between samples were studied by cross-referencing the lists of genes with online databases. High expression of a gene cluster related to embryonic developmental processes and low expression of a gene cluster related to neuroendocrine processes distinguished Merkel cell polyomavirus (MCPyV)-negative tumors from MCPyV-positive tumors. Furthermore, two prognostically relevant subgroups of MCPyV-positive MCC were identified based on dichotomic expression of genes related to epidermal structures and processes. We identified three distinct molecular subgroups of MCC with prognostic relevance. We propose that the dichotomic expression of epidermis-related genes might reflect both an epidermal and a nonepidermal origin for MCPyV-positive MCC.

Screening genes related to embryo implantation in Dazu black goats (Capra Hircus) by morphological and transcriptome analyses.

Embryo implantation is a critical step in the establishment of pregnancy. However, the mechanisms of embryo implantation during early pregnancy in goats remain unclear due to the lack of published studies examining the genes involved in embryo implantation. As a popular goat breed in southwest China, Dazu black goats (DBGs) are highly adaptable and exhibit high fertility, making this breed a good model in which to study reproductive performance of goats. Here, morphological analysis showed that compared with the non-pregnant (NP) groups, the endometrial thickness of the goats in the P15 and P19 groups (15 and 19-day pregnant groups, respectively) were increased (P < 0.01). Proliferating Cell Nuclear Antigen (PCNA) staining showed that PCNA was expressed in the NP, P15, and P19 groups. Transcriptome analysis was then conducted to identify gene expression patterns in uterine tissue during DBG embryo implantation. By comparing uterine tissue at different stages of embryonic implantation, 48 in NP_vs._P15, 318 in NP_vs._P19, and 1439 in P15_vs._P19, differentially expressed mRNAs were identified. Gene Ontology (GO) enrichments of the differentially expressed genes were enriched in the extracellular region, extracellular space, transporter activity, extracellular region, immune system process, immune response, and defense response etc. Through Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, the biological metabolic pathways with which the differentially expressed genes are associated were explored. Through KEGG analysis, the DBGs were associated with oxidative phosphorylation, complement and coagulation cascades, arginine and proline metabolism, metabolic pathways, arachidonic acid metabolism, and ECM-receptor interaction. These candidate genes (CSF1, C1S, CST6, SLC24A4, HOXA10, HOXA11, MMP9, and ITGA11) and enriched signaling pathways could be valuable references for exploring the molecular mechanisms underlying goat embryo implantation.

Abstract P038: Transcriptome-wide association study identifies novel genes associated with bladder cancer risk

Abstract Background: Genome-wide association studies (GWAS) have identified several common germline variants associated with bladder cancer risk. However, the genetic architecture of bladder cancer risk is still largely unknown. Therefore, we conducted a transcriptome-wide association study (TWAS) to identify gene expression patterns associated with bladder cancer risk. Methods: Individual-level genotype data from bladder cancer cases and controls was accessed from dbGaP (phs000346.v2.p2). We included 3,630 muscle invasive and non-muscle invasive bladder cancer cases and 3,356 controls from the Spanish Bladder Cancer Study (1,145 cases and 1,083 controls) and the New England Bladder Cancer Study (Maine and Vermont, 2,485 cases and 2,273 controls) with imputed genotype data for 22 million single-nucleotide polymorphisms (SNPs). We used PrediXcan to predict gene expression in whole blood using reference data from the Depression Genes and Networks (DGN). Covariate-adjusted logistic regression was used to estimate the associations between gene expression and bladder cancer risk. Results were validated using data from 280 non-muscle invasive bladder cancer cases and 353 controls of the New Hampshire Bladder Cancer Study. Results: We identified five genes associated with bladder cancer risk, including a previously reported locus (1p13.3: GSTM1) and four other loci (4p16.3: FAM53A, 7q22.3: RP11-325F22.2, 8p23.1: RP11-297N6.4, 11q24.1: JHY). Among them, higher predicted expression of GSTM1 in whole blood was associated with lower risk of bladder cancer (Discovery dataset OR = 0.78, 95% CI = 0.67, 0.92; Validation dataset OR = 0.58, 95% CI = 0.34, 0.98). Higher predicted expression of FAM53A (Discovery OR = 1.34, 95% CI = 1.08, 1.68; Validation OR = 3.79, 95% CI = 1.76, 8.29), RP11-325F22.2 (Discovery OR = 1.34, 95% CI = 1.09, 1.65; Validation OR = 2.11, 95% CI = 1.05, 4.30), RP11-297N6.4 (Discovery OR = 1.78, 95% CI = 1.22, 2.60; Validation OR = 6.32, 95% CI = 1.74, 23.34) and JHY (Discovery OR = 1.94, 95% CI = 1.30, 2.91; Validation OR = 6.78, 95% CI = 1.85, 25.76) in whole blood was associated with higher risk of bladder cancer. Conclusion: Our TWAS identified five genes associated with bladder cancer risk: GSTM1, a previously reported locus associated with bladder cancer risk, is related to metabolic detoxification. Four novel loci were identified: FAM53A (related to neural tube development and was previously reported to be related to breast cancer progression), JHY (related to axoneme structure), RP11-325F22.2 (lincRNA), and RP11-297N6.4 (lncRNA). These loci require further validation and may help to reveal the underlying mechanism of the relationship between gene expression and bladder cancer risk. Citation Format: Siting Li, Jiang Gui, Margaret R. Karagas, Michael N. Passarelli. Transcriptome-wide association study identifies novel genes associated with bladder cancer risk. [abstract]. In: Proceedings of the AACR Special Conference: Precision Prevention, Early Detection, and Interception of Cancer; 2022 Nov 17-19; Austin, TX. Philadelphia (PA): AACR; Can Prev Res 2023;16(1 Suppl): Abstract nr P038.

In vitro immune evaluation of adenoviral vector-based platform for infectious diseases.

New prophylactic vaccine platforms are imperative to combat respiratory infections. The efficacy of T and B memory cell-mediated protection, generated through the adenoviral vector, was tested to assess the effectiveness of the new adenoviral-based platforms for infectious diseases. A combination of adenovirus AdV1 (adjuvant), armed with costimulatory ligands (ICOSL and CD40L), and rRBD (antigen: recombinant nonglycosylated spike protein rRBD) was used to promote the differentiation of T and B lymphocytes. Adenovirus AdV2 (adjuvant), without ligands, in combination with rRBD, served as a control. In vitro T-cell responses to the AdV1+rRBD combination revealed that CD8+ platform-specific T-cells increased (37.2 ± 0.7% vs. 23.1 ± 2.1%), and T-cells acted against SARS-CoV-2 via CD8+TEMRA (50.0 ± 1.3% vs. 36.0 ± 3.2%). Memory B cells were induced after treatment with either AdV1+rRBD (84.1 ± 0.8% vs. 82.3 ± 0.4%) or rRBD (94.6 ± 0.3% vs. 82.3 ± 0.4%). Class-switching from IgM and IgD to isotype IgG following induction with rRBD+Ab was observed. RNA-seq profiling identified gene expression patterns related to T helper cell differentiation that protect against pathogens. The analysis determined signaling pathways controlling the induction of protective immunity, including the MAPK cascade, adipocytokine, cAMP, TNF, and Toll-like receptor signaling pathway. The AdV1+rRBD formulation induced IL-6, IL-8, and TNF. RNA-seq of the VERO E6 cell line showed differences in the apoptosis gene expression stimulated with the platforms vs. mock. In conclusion, AdV1+rRBD effectively generates T and B memory cell-mediated protection, presenting promising results in producing CD8+ platform-specific T cells and isotype-switched IgG memory B cells. The platform induces protective immunity by controlling the Th1, Th2, and Th17 cell differentiation gene expression patterns. Further studies are required to confirm its effectiveness.

Activation of the JAK1/STAT1 signaling pathway is associated with peroxiredoxin 6 expression levels in human epididymis epithelial cells.

Peroxiredoxin 6 (Prdx6) is widely expressed in mammalian tissues. Our previous study demonstrated that Prdx6 was expressed in human epididymis, present in human seminal fluid, and in spermatozoa. The protective role of Prdx6 in maintaining the viability and DNA integrity of human spermatozoa was also detected. Here, we demonstrate the potential role and mechanism of Prdx6 in human epididymis epithelial cells (HEECs). Western blotting was used to measure expression levels of key proteins in the Janus kinase/signal transducer and activator of transcription (JAK/STAT) signaling pathway. The malonaldehyde (MDA) levels and antioxidant capacity in HEECs were detected with the commercial kits. Digital gene expression analysis (DGE) was used to identify gene expression patterns in control and Prdx6-interference HEECs. Reverse transcriptase-polymerase chain reaction (RT-PCR) was used to validate the DGE findings. Compared to control HEECs, the expression levels of JAK1, STAT1, phosphorylated JAK1 and STAT1 were significantly increased, while the expression level of SOCS3 was significantly decreased in Prdx6-interference HEECs. The MDA level and total antioxidant capacity in Prdx6-interference HEECs were significantly increased and decreased compared to that of control, respectively. DGE analysis identified 589 up-regulated and 314 down-regulated genes (including Prdx6) in Prdx6-interference HEECs. Thirteen significantly different pathways were identified between the two groups, with the majority of genes belonging to the CCL, CXCL, IL, and IFIT family of proteins and were related to immunity. In particular, the expression levels of IL6, IL6ST, and eighteen IFN-related genes were significantly increased in Prdx6-interference HEECs compared to control HEECs. We found that reduced Prdx6 expression induced higher ROS levels in HEECs, which resulted in the activation of the IL-6 receptor and IFNγ expression to induce the JAK1/STAT1 signaling pathway.