Performed Gene Set Enrichment Analysis Research Articles

Altered pathways of keratinization, extracellular matrix generation, angiogenesis, and stromal stem cells proliferation in patients with systemic sclerosis.

Systemic sclerosis is characterized by endothelial dysfunction, autoimmunity abnormalities, and fibrosis of the skin and internal organs. The pathogenetic mechanisms underlying systemic sclerosis vasculopathy are still not clarified. A complex cellular and extracellular network of interactions has been studied, but it is currently unclear what drives the activation of fibroblasts/myofibroblasts and the extracellular matrix deposition. Using RNA sequencing, the aim of the work was to identify potential functional pathways implied in systemic sclerosis pathogenesis and markers of endothelial dysfunction and fibrosis in systemic sclerosis patients. RNA-sequencing analysis was performed on RNA obtained from biopsies from three systemic sclerosis patients and three healthy controls enrolled in our University Hospital. RNA was used to generate sequencing libraries that were sequenced according to proper transcriptomic analyses. Subsequently, we performed gene set enrichment analysis of differentially expressed genes on the entire list of genes that compose the RNA-sequencing expression matrix. Gene set enrichment analysis revealed that healthy controls were characterized by gene signatures related to stromal stem cells proliferation, cytokine-cytokine receptor interaction, macrophage-enriched metabolic network, whereas systemic sclerosis tissues were enriched in signatures associated with keratinization, cornification, retinoblastoma 1 and tumor suppressor 53 signaling. According to our data, RNA-sequencing and pathway analysis revealed that systemic sclerosis subjects display a discrete pattern of gene expression associated with keratinization, extracellular matrix generation, and negative regulation of angiogenesis and stromal stem cells proliferation. Further analysis on larger numbers of patients is needed; however, our findings provide an interesting framework for the development of biomarkers useful to explore potential future therapeutic approaches.

AML-426 A Prospective Study to Evaluate the Prognostic Implications of PRDM16 Gene in Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is a complex hematologic malignancy distinguished by the accumulation of abnormally differentiated and uncontrolled proliferation of immature myeloid cells in the bone marrow induced due to diverse genetic alterations with recurrent cytogenetic abnormalities. PR domain-containing 16 (PRDM16) is a transcriptional coregulatory encoder for zinc finger transcription factor crucial for both normal and malignant hematopoiesis and essential for hematopoietic stem cells (HSCs) maintenance. However, to our knowledge, the molecular interaction, biological and immunological role, as well as its clinical diagnostic and prognostic value in AML is still incompletely known. This study aimed to characterize the potential role and molecular functions of PRDM16 in AML. In this study, PRDM16 expression level was studied using GEPIA2 database. Kaplan-Meier survival investigation was performed to estimate the prognostic significance of PRDM16 using UALCAN platforms. We explore the molecular mechanisms of PRDM16 in AML, its correlation, and biological function analysis by performing Gene set enrichment analysis (GSEA) and Linked Omics database. The relationship of PRDM16 expression with immune infiltration level was analyzed using TIMER 2.0 and CIBERSORT database. In our analyses, PRDM16 mRNA was significantly overexpressed in TCGA-LAML cohorts and closely associated with a worse prognosis in TCGA-LAML cohorts (P<0.05). Enrichment analysis revealed that PRDM16 was involved in tumor immunity. Notably, the PRDM16 mRNA expression was negatively linked with the infiltration of immune cells and stromal cells. In this study, we found that PRDM16 plays a significant role in AML progression and may serve as a potential prognostic biomarker and therapeutic target for the effective management of AML.

Single-cell sequencing and establishment of an 8-gene prognostic model for pancreatic cancer patients.

BackgroundSingle-cell sequencing (SCS) technologies enable analysis of gene structure and expression data at single-cell resolution. However, SCS analysis in pancreatic cancer remains largely unexplored.MethodsWe downloaded pancreatic cancer SCS data from different databases and applied appropriate dimensionality reduction algorithms. We identified 10 cell types and subsequently screened differentially expressed marker genes of these 10 cell types using FindAllMarkers analysis. Also, we evaluated the tumor immune microenvironment based on ESTIMATE and MCP-counter. Statistical enrichment was evaluated using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis. We used all candidate gene sets in KEGG database to perform gene set enrichment analysis. We used LASSO regression to reduce the number of genes in the pancreatic risk model by R package glmnet, followed by rtPCR to validate the expression of the signature genes in different pancreatic cancer cell lines.ResultsWe identified 15 cell subpopulations by dimension reduction and data clustering. We divided the 15 subpopulations into 10 distinct cell types based on marker gene expression. Then, we performed functional enrichment analysis for the 352 marker genes in pancreatic cancer cells. Based on RNA expression data and prognostic information from TCGA and GEO datasets, we identified 42 prognosis-related genes, including 5 protective genes and 37 high-risk genes, which we used to identified two molecular subtypes. C1 subtype was associated with a better prognosis, whereas C2 subtype was associated with a worse prognosis. Moreover, chemokine and chemokine receptor genes were differentially expressed between C1 and C2 subtypes. Functional and pathway enrichment uncovered functional differences between C1 and C2 subtype. We identified eight genes that could serve as potential biomarkers for prognosis prediction in pancreatic cancer patients. These genes were used to establish an 8-gene pancreatic cancer prognostic model.ConclusionsWe established an 8-gene pancreatic cancer prognostic model. This model can meaningfully predict prognosis and treatment response in pancreatic cancer patients.

Identify novel, shared and disorder-specific genetic architecture of major depressive disorder, insomnia and chronic pain

Major depressive disorder (MDD), insomnia (INS) and chronic pain (CP) often have high comorbidity and show high genetic correlation. Here we aimed to better characterize their novel, shared and disorder-specific genetic architecture. Based on genome-wide association study (GWAS) summary data, we applied the conditional false discovery rate (condFDR) and conjunctional FDR (conjFDR) approach to investigate the novel and overlapped genetic loci for MDD, INS and CP. In addition, putative disorder-specific SNP associations were analyzed by conditioning the other two traits. The functions of the identified genomic loci were explored by performing gene set enrichment analysis (GSEA) for the loci mapped genes. We identified 22, 43 and 91 novel risk loci for MDD, INS and CP. GSEA for the loci mapped genes highlighted olfactory signaling pathway for MDD novel loci, breast cancer related gene set for both INS and CP novel loci, and nervous system related development, structure and activity for CP. Furthermore, we identified three loci jointly associated with the three disorders, including 13q14.3 locus with nearby gene OLFM4, 14q21.1 locus with nearby gene LRFN5 and 5q21.2 locus located in intergenic region. In addition, we identified one specific loci for MDD, 7 for INS and 11 for CP respectively by conditioning the other two traits, which were mapped to 68 genes for MDD, 85 for INS and 100 for CP. The MDD specific genes are enriched in immune system related pathways. This study increases understanding of the genetic architectures underlying MDD, INS and CP. The shared underlying genetic risk may help to explain the high comorbidity rates of the disorders.

Regulation Networks of Non-Coding RNA-Associated ceRNAs in Cisplatin-Induced Acute Kidney Injury.

Cisplatin is widely used as a chemotherapeutic drug to treat various solid tumors. However, it often induces severe side effects, including nephrotoxicity, which limits its application in clinical settings. Furthermore, the underlying mechanisms of action are unclear. Here, we applied whole-transcriptome RNA sequencing to a cisplatin-induced acute kidney injury (CP-AKI) mouse model to evaluate competing endogenous RNA (ceRNA) networks. We found 4460 mRNAs, 1851 long non-coding RNAs, 101 circular RNAs, and 102 microRNAs significantly differentially expressed between CP-AKI and control mice. We performed gene set enrichment analysis to reveal the biological functions of the mRNAs and constructed non-coding RNA-associated ceRNA networks in CP-AKI mice. Two ceRNA regulatory pathways, Lhx1os-203/mmu-miR-21a-3p/Slc7a13 and circular RNA_3907/mmu-miR-185-3p/Ptprn, were validated using quantitative real-time PCR. The protein–protein interaction network indicated that Il6, Cxcl1, Cxcl2, and Plk1 serve as hub genes and are highly connected with the inflammatory response or DNA damage. Transcription factors, such as Stat3, Cebpb, and Foxm1, regulate gene expression levels in CP-AKI. Our study provides insight into non-coding RNA-associated ceRNA networks and mRNAs in CP-AKI and identifies potential treatment targets.

Upregulation of circ_0008812 and circ_0001583 predicts poor prognosis and promotes breast cancer proliferation.

Background: Accumulating evidence suggests that circular RNAs (circRNAs) are highly correlated with tumor progression and pathogenesis in breast cancer. Whereas, their regulatory roles and corresponding mechanisms in breast cancer are still not exhaustive. Thus, we intended to establish circRNA-mediated competive endogenous RNA (ceRNA) network to uncover the possible roles and clinical implications of circRNAs in breast cancer. Methods: Microarray and RNA-sequencing (RNA-seq) data were download from GEO and TCGA database to screen for differentially expressed RNAs (DEcircRNAs, DEmiRNAs, DEmRNAs) in breast cancer. By implementing online databases, we established ceRNA networks, performed gene set enrichment analysis, constructed protein-protein interaction (PPI) networks, and assessed the expression levels and prognostic significance of hub genes. Subsequently, we explored the functions of prognosis-related genes and constructed gene-drug interaction networks. Finally, the functional roles of DEcircRNAs in breast cancer were revealed via MTT and colony formation assay. Results: Based on the identified 8 DEcircRNAs, 25 miRNAs and 216 mRNAs, a ceRNA regulatory network was established. Further analysis revealed that prominent enrichments were transcription factor binding, transforming growth factor-beta (TGF-β) and Apelin signaling pathway etc. PPI network and survival curves analysis showed that elevated levels of hub genes (RACGAP1 and KPNA2) were associated with poorer prognosis. They were found to be positively relevant to cell cycle and proliferation. Then a prognostic sub-network of ceRNA was constructed, consisting of 2 circRNAs, 4 miRNAs and 2 mRNAs. The gene-drug interaction network showed that numerous drugs could regulate the expression of these two prognosis-related genes. Functional experiments showed that depletion of circ_0008812 and circ_0001583 could significantly inhibit the proliferation of MCF-7 cells. Conclusion: Our study constructed 4 prognostic regulatory axes that are significantly correlated with tumor prognosis in breast cancer patients, and uncover the roles of circ_0008812 and circ_0001583 in breast cancer, providing a new perspective into the molecular mechanisms of breast cancer pathogenesis.

N7-methylguanosine-related lncRNAs: Distinction between hot and cold tumors and construction of predictive models in colon adenocarcinoma.

Colon adenocarcinoma (COAD) is a prevalent malignant tumor that severely threatens human health across the globe. Immunotherapy is an essential need for patients with COAD. N7-methylguanosine (m7G) has been associated with human diseases, and non-coding RNAs (lncRNAs) regulate various tumor-related biological processes. Nonetheless, the m7G-related lncRNAs involved in COAD regulation are limited. This study aims to construct the clustering features and prognostic model of m7G-related lncRNAs in COAD. First, The Cancer Genome Atlas (TCGA) database was used to identify m7G-related differentially expressed lncRNAs (DELs), based on which COAD cases could be classified into two subtypes. Subsequently, univariate Cox analysis was used to identify 9 prognostic m7G-related lncRNAs. Further, Five candidates were screened by LASSO-Cox regression to develop new models. The patients were divided into high-risk and low-risk groups based on the median risk score. Consequently, the Kaplan-Meier survival curve demonstrated a statistically significant overall survival (OS) between the high- and low-risk groups (P<0.001). Multivariate Cox regression analysis revealed that risk score is an independent prognostic factor in COAD patients (P<0.001). This confirms the clinical applicability of the model. Additionally, we performed Gene Set Enrichment Analysis (GSEA), which uncovered the biological and functional differences between risk subgroups, i.e., enrichment of immune-related diseases in the high-risk group and enrichment of metabolic-related pathways in the low-risk group. In a drug sensitivity analysis, high-risk group were more sensitive to some chemotherapeutics and targeted drugs than low-risk group. Eventually, the stability of the model was confirmed by qRT-PCR. Our study unraveled the features of different immune states of COAD and established a prognostic model, including five m7G-related lncRNAs for COAD patients. These results will bolster clinical treatment and survival prediction of COAD.

Expression profiling suggests the involvement of hormone-related, metabolic, and Wnt signaling pathways in pterygium progression.

BackgroundPterygium is an ocular surface disease that can cause visual impairment if it progressively invades the cornea. Although many pieces of research showed ultraviolet radiation is a trigger of pterygium pathological progress, the underlying mechanism in pterygium remains indistinct.MethodsIn this study, we used microarray to evaluate the changes of transcripts between primary pterygium and adjacent normal conjunctiva samples in China. Then, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses. Moreover, we constructed protein-protein interaction (PPI) and miRNA-mRNA regulatory networks to predict possible regulatory relationships. We next performed gene set enrichment analysis (GSEA) to explore the similarities and differences of transcripts between Asian studies from the Gene Expression Omnibus database. Furthermore, we took the intersection of differentially expressed genes (DEGs) with other data and identified hub genes of the development of pterygium. Finally, we utilized real-time quantitative PCR to verify the expression levels of candidate genes.ResultsA total of 49 DEGs were identified. The enrichment analyses of DEGs showed that pathways such as the Wnt-signaling pathway and metabolism-related pathways were upregulated, while pathways such as hormone-related and transcription factor-associated pathways were downregulated. The PPI and miRNA-mRNA regulatory networks provide ideas for future research directions. The GSEA of selecting Asian data revealed that epithelial-mesenchymal transition and myogenesis existed in the pathology of pterygium in the Asian group. Furthermore, five gene sets (interferon-gamma response, Wnt beta-catenin signaling, oxidative phosphorylation, DNA repair, and MYC targets v2) were found only in our Chinese datasets. After taking an intersection between selecting datasets, we identified two upregulated (SPP1 and MYH11) and five downregulated (ATF3, FOS, EGR1, FOSB, and NR4A2) hub genes. We finally chose night genes to verify their expression levels, including the other two genes (SFRP2 and SFRP4) involved in Wnt signaling; Their expression levels were significantly different between pterygium and conjunctiva.ConclusionsWe consider hormone-related, metabolic, and Wnt signaling pathways may be important in the pathology of pterygium development. Nine candidate genes we identified deserve further study and can be potential therapeutic targets.

Identification of diagnostic mRNA biomarkers in whole blood for ankylosing spondylitis using WGCNA and machine learning feature selection.

Ankylosing spondylitis (AS) is a common inflammatory spondyloarthritis affecting the spine and sacroiliac joint that finally results in sclerosis of the axial skeleton. Aside from human leukocyte antigen B27, transcriptomic biomarkers in blood for AS diagnosis still remain unknown. Hence, this study aimed to investigate credible AS-specific mRNA biomarkers from the whole blood of AS patients by analyzing an mRNA expression profile (GSE73754) downloaded Gene Expression Omnibus, which includes AS and healthy control blood samples. Weighted gene co-expression network analysis was performed and revealed three mRNA modules associated with AS. By performing gene set enrichment analysis, the functional annotations of these modules revealed immune biological processes that occur in AS. Several feature mRNAs were identified by analyzing the hubs of the protein-protein interaction network, which was based on the intersection between differentially expressed mRNAs and mRNA modules. A machine learning-based feature selection method, SVM-RFE, was used to further screen out 13 key feature mRNAs. After verifying by qPCR, IL17RA, Sqstm1, Picalm, Eif4e, Srrt, Lrrfip1, Synj1 and Cxcr6 were found to be significant for AS diagnosis. Among them, Cxcr6, IL17RA and Lrrfip1 were correlated with severity of AS symptoms. In conclusion, our findings provide a framework for identifying the key mRNAs in whole blood of AS that is conducive for the development of novel diagnostic markers for AS.

Krüppel-like factor 5 promotes the progression of oral squamous cell carcinoma via the baculoviral IAP repeat containing 5 gene.

BackgroundKrüppel-like factor 5 (KLF5) is highly expressed in a variety of tumors, and our study aimed to investigate the role of KLF5 in oral squamous cell carcinoma (OSCC).MethodsTo explore the differential expression of KLF5, next-generation sequencing (NGS) and further analyses were conducted in paired premalignant and tumor tissues and adjacent normal mucosa. We then analyzed the mRNA expression data from The Cancer Genome Atlas (TCGA) and performed gene set enrichment analysis (GSEA) to predict the function of KLF5. Small interfering RNA (siRNA) targeting KLF5 was used to knock down its expression in cells and further evaluate the changes in cell apoptosis, proliferation, and migration. We predicted whether baculoviral inhibitor of apoptosis protein (IAP) repeat containing 5 (BIRC5) was the potential target gene of KLF5 via the NCBI and JASPAR databases. Furthermore, we analyzed BIRC5 expression after KLF5 knockdown and explored its function in athymic BALB/c nude mice.ResultsKLF5 expression in clinical samples gradually increased from normal mucosa tissues to premalignant and then to OSCC tissues. Analysis of TCGA data and GSEA also suggested that KLF5 was expressed at higher levels in OSCC and involved apoptosis and the protein 53 (P53), transforming growth factor-β (TGF-β), and wingless/integrated (Wnt) signaling pathways. Cell apoptosis was promoted, whereas proliferation and migration were inhibited after KLF5 knockdown. Furthermore, we found KLF5 transcription binding sites on the BIRC5 promoter and BIRC5 expression was inhibited after suppressing KLF5 in vitro and in vivo.ConclusionsOur findings indicate that KLF5 promotes the development of OSCC via BIRC5, and could be a potential diagnostic and therapeutic target for OSCC.

Extracellular Matrix Interactions Provide Tumor Cells With an Escape Mechanism for Commitment to Differentiation

Extracellular Matrix Interactions Provide Tumor Cells With an Escape Mechanism for Commitment to Differentiation

Effects of Two Distinct Psychoactive Microbes, Lacticaseibacillus rhamnosus JB-1 and Limosilactobacillus reuteri 6475, on Circulating and Hippocampal mRNA in Male Mice.

Discovery of the microbiota-gut–brain axis has led to proposed microbe-based therapeutic strategies in mental health, including the use of mood-altering bacterial species, termed psychobiotics. However, we still have limited understanding of the key signaling pathways engaged by specific organisms in modulating brain function, and evidence suggests that bacteria with broadly similar neuroactive and immunomodulatory actions can drive different behavioral outcomes. We sought to identify pathways distinguishing two psychoactive bacterial strains that seemingly engage similar gut–brain signaling pathways but have distinct effects on behaviour. We used RNAseq to identify mRNAs differentially expressed in the blood and hippocampus of mice following Lacticaseibacillus rhamnosus JB-1, and Limosilactobacillus reuteri 6475 treatment and performed Gene Set Enrichment Analysis (GSEA) to identify enrichment in pathway activity. L. rhamnosus, but not L. reuteri treatment altered several pathways in the blood and hippocampus, and the rhamnosus could be clearly distinguished based on mRNA profile. In particular, L. rhamnosus treatment modulated the activity of interferon signaling, JAK/STAT, and TNF-alpha via NF-KB pathways. Our results highlight that psychobiotics can induce complex changes in host gene expression, andin understanding these changes, we may help fine-tune selection of psychobiotics for treating mood disorders.

Interferon signalling contributes to therapy‐resistant prostate cancer progression

Interferon signalling contributes to therapy‐resistant prostate cancer progression

Ferroptosis-related lncRNA signature predicts prognosis and immunotherapy efficacy in cutaneous melanoma.

PurposeFerroptosis-related lncRNAs are promising biomarkers for predicting the prognosis of many cancers. However, a ferroptosis-related signature to predict the prognosis of cutaneous melanoma (CM) has not been identified. The purpose of this study was to construct a ferroptosis-related lncRNA signature to predict prognosis and immunotherapy efficacy in CM.MethodsFerroptosis-related differentially expressed genes (FDEGs) and lncRNAs (FDELs) were identified using TCGA, GTEx, and FerrDb datasets. We performed Cox and LASSO regressions to identify key FDELs, and constructed a risk score to stratify patients into high- and low-risk groups. The lncRNA signature was evaluated using the areas under the receiver operating characteristic curves (AUCs) and Kaplan-Meier analyses in the training, testing, and entire cohorts. Multivariate Cox regression analyses including the lncRNA signature and common clinicopathological characteristics were performed to identify independent predictors of overall survival (OS). A nomogram was developed for clinical use. We performed gene set enrichment analyses (GSEA) to identify significantly enriched pathways. Differences in the tumor microenvironment (TME) between the 2 groups were assessed using 7 algorithms. To predict the efficacy of immune checkpoint inhibitors (ICI), we analyzed the association between PD1 and CTLA4 expression and the risk score. Finally, differences in Tumor Mutational Burden (TMB) and molecular drugs Sensitivity between the 2 groups were performed.ResultsWe identified 5 lncRNAs (AATBC, AC145423.2, LINC01871, AC125807.2, and AC245041.1) to construct the risk score. The AUC of the lncRNA signature was 0.743 in the training cohort and was validated in the testing and entire cohorts. Kaplan-Meier analyses revealed that the high-risk group had poorer prognosis. Multivariate Cox regression showed that the lncRNA signature was an independent predictor of OS with higher accuracy than traditional clinicopathological features. The 1-, 3-, and 5-year survival probabilities for CM patients were 92.7%, 57.2%, and 40.2% with an AUC of 0.804, indicating a good accuracy and reliability of the nomogram. GSEA showed that the high-risk group had lower ferroptosis and immune response. TME analyses confirmed that the high-risk group had lower immune cell infiltration (e.g., CD8+ T cells, CD4+ memory-activated T cells, and M1 macrophages) and lower immune functions (e.g., immune checkpoint activation). Low-risk patients whose disease expressed PD1 or CTLA4 were likely to respond better to ICIs. The analysis demonstrated that the TMB had significantly difference between low- and high- risk groups. Chemotherapy drugs, such as sorafenib, Imatinib, ABT.888 (Veliparib), Docetaxel, and Paclitaxel showed Significant differences in the estimated IC50 between the two risk groups.ConclusionOur novel ferroptosis-related lncRNA signature was able to accurately predict the prognosis and ICI outcomes of CM patients. These ferroptosis-related lncRNAs might be potential biomarkers and therapeutic targets for CM.

Abstract 3973: Transcriptomic profiling of in-vitro modelled drug resistant AML cell lines unravel metabolic and stemness gene signatures

Abstract Disease recurrence is the major cause of treatment failure and mortality in acute myeloid leukemia (AML). A small fraction of leukemic cells that withstand chemotherapeutic insult can rewire cellular processes to re-emerge with lethal disease. Approaches to decipher drug resistance mechanisms in these drug persister cells can pave the way for newer therapies and improve survival in patients. To uncover drug resistant mechanisms that are clinically relevant, we generated in-house Cytarabine (AraC) and Arsenic trioxide (ATO) resistant cells from naïve MV4-11 AML cell line by incremental dose exposure method. Single cell clones were generated from AraC (MV411-AraC-R)/ATO (MV411-ATO-R) drug tolerant cells. Both the AraC-R and ATO-R clones were resistant to AraC (600-fold) and ATO (2-fold) respectively compared to the naïve cells. AraC-R cells were marginally cross resistant to daunorubicin (DNR) and ATO. Interestingly, the ATO-R cells were highly cross resistant to both AraC (600-fold) and DNR (4-fold) demonstrating altered drug resistance mechanism. We next subjected the AraC-R, ATO-R and the naïve cells to RNAseq analysis to identify transcriptomic changes post resistance development. 1218 transcripts in AraC-R cells and 7654 transcripts in ATO-R cells were differentially expressed compared to the naïve cells, suggesting ATO exposure alters the transcriptome drastically compared to AraC. We performed gene set enrichment analysis (GSEA) with these differentially expressed gene signatures. AraC-R gene signatures were highly enriched (NES-2.8 &amp; 2.0 FDR-0.00) for oxidative phosphorylation and mitochondrial related signatures, consistent with previous report suggesting AraC exposed residual cells are highly enriched for oxidative phosphorylation and are not enriched for stemness gene signatures (Farge et al). ATO-R gene signatures were positively enriched (NES- 2.0 &amp; 1.4 FDR 0.005 &amp; 0.03) for Leukemic stem cell gene signatures (Eppert_LSC and Gentles_LSC) and relapse (NES- 2.0 &amp; 1.5 FDR 0.0 &amp; 0.01) gene signatures (CALCRL_RIC and Hackles_relapse) and negatively enriched for mitochondrial gene signatures showing reduced reliance on mitochondrial metabolism. Since AraC-R cells showed high dependency on mitochondrial metabolism, we treated these cells with venetoclax (VEN) a known oxphos inhibitor for 48 hours and assessed the viability. Ven markedly sensitized the AraC-R cells compared to naïve cells (IC50 13nM and 323nM), while ATO-R cells were markedly resistant to Ven (IC50 8049nM) corroborating our transcriptomic findings. These finding suggest transcriptome profiling of in-vitro modelled drug resistant cell lines can mimic clinically relevant drug resistant mechanism and could aide in identifying alternate therapies to circumvent disease relapse. Further metabolomic characterization and mechanistic studies are ongoing to substantiate these findings. Citation Format: Raveen Stephen Illangeswaran, Daniel Zechariah Jebanesan, Kezia Kanimozhi Sivakumar, Rakhi Thalayattu Vidhyadharan, Vikram Mathews, Shaji Ramachandran Velayudhan, Poonkuzhali Balasubramanian. Transcriptomic profiling of in-vitro modelled drug resistant AML cell lines unravel metabolic and stemness gene signatures [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3973.

Abstract 3082: Leveraging 3D organoids to identify molecular changes underlying HNSC initiation and development

Abstract Head and neck squamous cell carcinoma (HNSC) is a devastating disease accounting for 570,000 newly diagnosed cases and resulting in 344,000 deaths annually. HNSC arises from its histological precursor lesion, squamous dysplasia (HNSD); however, most patients are diagnosed with late-stage HNSC with no prior identification of pre-malignant disease. Earlier diagnosis and intervention could ameliorate the outsized burden of HNSC; therefore, there is an urgent unmet need to characterize the molecular changes underlying progression through HNSD to HNSC. To identify novel therapeutic targets or biomarkers that predict progression to HNSC, we have generated a three dimensional (3D) organoid library derived from dysplastic oral tissue harvested from mice treated with 4-Nitriquinoline N-oxide (4-NQO), a potent mimetic of tobacco smoke. Through RNA sequencing analysis of these organoids, we have identified two distinct gene expression states that accompany either early or late dysplasia. By performing gene set enrichment analysis of these two distinct gene signatures, we have identified c-Jun N-terminal Kinase (JNK) signaling as a potential biomarker that predicts or progression from HNSD to HNSC. Together, we have identified the salient transcriptional changes that accompany progression through the histological precursor lesion of HNSC. This study positions JNK signaling as a potential biomarker or therapeutic target for early intervention during the treatment of a deadly disease. Citation Format: Robert Agee, Samuel Flashner, Masataka Shimonosono, Andres Klein-Szanto, Hiroshi Nakagawa. Leveraging 3D organoids to identify molecular changes underlying HNSC initiation and development [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3082.

The immune landscape of solid pediatric tumors

BackgroundLarge immunogenomic analyses have demonstrated the prognostic role of the functional orientation of the tumor microenvironment in adult solid tumors, this variable has been poorly explored in the pediatric counterpart.MethodsWe performed a systematic analysis of public RNAseq data (TARGET) for five pediatric tumor types (408 patients): Wilms tumor (WLM), neuroblastoma (NBL), osteosarcoma (OS), clear cell sarcoma of the kidney (CCSK) and rhabdoid tumor of the kidney (RT). We assessed the performance of the Immunologic Constant of Rejection (ICR), which captures an active Th1/cytotoxic response. We also performed gene set enrichment analysis (ssGSEA) and clustered more than 100 well characterized immune traits to define immune subtypes and compared their outcome.ResultsA higher ICR score was associated with better survival in OS and high risk NBL without MYCN amplification but with poorer survival in WLM. Clustering of immune traits revealed the same five principal modules previously described in adult tumors (TCGA). These modules divided pediatric patients into six immune subtypes (S1-S6) with distinct survival outcomes. The S2 cluster showed the best overall survival, characterized by low enrichment of the wound healing signature, high Th1, and low Th2 infiltration, while the reverse was observed in S4. Upregulation of the WNT/Beta-catenin pathway was associated with unfavorable outcomes and decreased T-cell infiltration in OS.ConclusionsWe demonstrated that extracranial pediatric tumors could be classified according to their immune disposition, unveiling similarities with adults’ tumors. Immunological parameters might be explored to refine diagnostic and prognostic biomarkers and to identify potential immune-responsive tumors.

Lentiviral interferon: A novel method for gene therapy in bladder cancer

Interferon alpha (IFNα) gene therapy is emerging as a new treatment option for patients with non-muscle invasive bladder cancer (NMIBC). Adenoviral vectors expressing IFNα have shown clinical efficacy treating bacillus Calmette-Guerin (BCG)-unresponsive bladder cancer (BLCA). However, transient transgene expression and adenoviral immunogenicity may limit therapeutic activity. Lentiviral vectors can achieve stable transgene expression and are less immunogenic. In this study, we evaluated lentiviral vectors expressing murine IFNα (LV-IFNα) and demonstrate IFNα expression by transduced murine BLCA cell lines, bladder urothelium, and within the urine following intravesical instillation. Murine BLCA cell lines (MB49 and UPPL1541) were sensitive to IFN-mediated cell death after LV-IFNα, whereas BBN975 was inherently resistant. Upregulation of interleukin-6 (IL-6) predicted sensitivity to IFN-mediated cell death mediated by caspase signaling, which when inhibited abrogated IFN-mediated cell killing. Intravesical therapy with LV-IFNα/Syn3 in a syngeneic BLCA model significantly improved survival, and molecular analysis of treated tumors revealed upregulation of apoptotic and immune-cell-mediated death pathways. In particular, biomarker discovery analysis identified three clinically actionable targets, PD-L1, epidermal growth factor receptor (EGFR), and ALDHA1A, in murine tumors treated with LV-IFNα/Syn3. Our findings warrant the comparison of adenoviral and LV-IFNα and the study of novel combination strategies with IFNα gene therapy for the BLCA treatment.

Transcriptomic Characteristics Associated With Aging in the Thyroid Gland.

The aging thyroid is associated with a plethora of morphological and functional changes. Limited studies have addressed the gene expression signature in the aging thyroid, except for sporadic reports using data from postmortem samples in the Genotype-Tissue Expression (GTEx) project. In this investigation, we analyzed the RNA sequencing data of 58 samples of normal-appearing counterpart thyroid tissues from The Cancer Genome Atlas. Aging-correlated genes were identified by determining the Spearman rank-order correlation between patient age and gene expression level. Additionally, we performed gene set enrichment analysis and conducted a weighted correlation network analysis. The results were compared with those analyzed using the GTEx data. The over-represented protein class of aging-correlated genes is mainly metabolite interconversion enzymes. Our analyses identified alterations in immune and inflammatory responses, mitochondrial functions, cytoskeletal proteins, as well as amino acid and cytochrome P450 metabolism. There was no significant association between thyroid differentiation and age. Our findings may shed molecular light on thyroid disorders in the geriatric population.

High DKK3 expression related to immunosuppression was associated with poor prognosis in glioblastoma: machine learning approach

BackgroundGlioblastoma multiforme (GBM) is an aggressive malignant primary brain tumor. Wnt/β-catenin is known to be related to GBM stemness. Cancer stem cells induce immunosuppressive and treatment resistance in GBM. We hypothesized that Wnt/β-catenin-related genes with immunosuppression could be related to the prognosis in patients with GBM.MethodsWe obtained the clinicopathological data of 525 patients with GBM from the brain cancer gene database. The fraction of tumor-infiltrating immune cells was evaluated using in silico flow cytometry. Among gene sets of Wnt/β-catenin pathway, Dickkopf-3 (DKK3) gene related to the immunosuppressive response was found using machine learning. We performed gene set enrichment analysis (GSEA), network-based analysis, survival analysis and in vitro drug screening assays based on Dickkopf-3 (DKK3) expression.ResultsIn analyses of 31 genes related to Wnt/β-catenin signaling, high DKK3 expression was negatively correlated with increased antitumoral immunity, especially CD8 + and CD4 + T cells, in patients with GBM. High DKK3 expression was correlated with poor survival and disease progression in patients with GBM. In pathway-based network analysis, DKK3 was directly linked to the THY1 gene, a tumor suppressor gene. Through in vitro drug screening, we identified navitoclax as an agent with potent activity against GBM cell lines with high DKK3 expression.ConclusionsThese results suggest that high DKK3 expression could be a therapeutic target in GBM. The results of the present study could contribute to the design of future experimental research and drug development programs for GBM.Graphical abstract