Performed Gene Set Enrichment Analysis Research Articles

Unveiling HOXB7 as a novel diagnostic and prognostic biomarker through pan-cancer computer screening

We attempted to investigate the role of HOXB7 in tumor progression and evolution by means of an extensive computer screening analysis of various cancer types. We performed univariate Cox regression and Kaplan-Meier survival analyses to assess the impact of HOXB7 on overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) in different types of cancer. Furthermore, we examined the relationship between HOXB7 and several clinical features: tumor microenvironment, immune regulatory genes, immune checkpoints, tumor mutational burden (TMB), and microsatellite instability (MSI). We performed gene set enrichment analysis to gain deeper insights into the potential molecular mechanisms of HOXB7, and validated our findings through functional assays in cells, including methyl thiazolyl tetrazolium cytotoxicity and Transwell invasion assays. HOXB7 expression was associated with different clinical characteristics in numerous malignancies. Higher HOXB7 expression was associated with worse OS, DSS, and PFI in some cancer types. In particular, HOXB7 expression was favorably associated with immune cell infiltration, immune regulatory genes, immunological checkpoints, TMB, and MSI in malignancies. Furthermore, we identified a strong link between copper death-associated gene expression and HOXB7 expression. According to the findings of this study, HOXB7 might serve as an appealing focus for tumor diagnosis and immunotherapy and a prospective indicator of prognosis.

Abstract PO5-24-11: An integrated approach for comprehensive molecular and tumor microenvironment characterization of invasive lobular carcinoma

Abstract Introduction: Although recent studies have shown that invasive lobular carcinoma (ILC) is associated with worse long-term outcomes compared to invasive breast cancer of no special type (NST), they are treated in a similar manner. Therefore, classification approaches to help understand the molecular characteristics associated with the different BC subtypes are needed to personalize therapy. Here, we describe an integrated analytical approach to comprehensively characterize ILC samples. Methods: We collected genomic and transcriptomic data for 16,087 ILC and NST samples, with clinical and pathological annotation, from 59 datasets and used an internally developed algorithm based on clustering performed after gene expression analysis to classify them into 5 intrinsic subtypes: Basal, Luminal A (LumA), Luminal B (LumB), HER2 high, and HER2 low. We performed gene set enrichment analyses and utilized the DESeq2 algorithm to perform differential expression analysis of RNA-seq data. We performed molecular grade subtyping using methods described by Antysheva et al. (Cancer Res., 2022). Samples that were listed as ILC or had an inactivated CDH1 gene by mutation, deletion or low expression (< −2.5 MAD after median scaling) were defined as having an ILC histomolecular subtype. Using methods described by Bagaev et. al. (Cancer Cell, 2021), 29 functional gene expression signatures were selected, and unsupervised dense Louvain clustering was performed to identify TME subtypes. The Mann-Whitney U test was used for statistical analysis. The tertiary lymphoid structures (TLS) gene signature was evaluated using methods described by Sautès-Fridman et al. (Nat. Rev. Cancer, 2019). Results: In the ILC samples (n=1,887), we identified LumA (46%), LumB (40%), Basal (8%,), HER2 high (3%), and HER2 low (3%) subtypes. In contrast, the NST samples were classified as LumB (41%), LumA (25%), Basal (19%), HER2 high (9%), and HER2 low (5%). Molecular grade subtyping revealed that 67% of ILC samples were low grade and 33% were high grade, compared to NST where 55% were high grade and 45% were low grade. Notably, among high-grade ILC, LumB (64%) and Basal (23%) subtypes were predominant. Key differentially expressed genes included downregulated CDH1 and upregulated MMP23B, IGF1, and TFAP2B across LumA and LumB ILC samples. Further analysis revealed downregulation of TACSTD2 and CDH3 in the Basal subtype for ILC samples compared to NST samples. Transcriptomic-based TME subtyping revealed distinct TME distributions across the BC subtypes and molecular grades for ILC samples (Table 1). In high-grade ILC LumB samples, 38% had a Desert (D; predictive of poor immunotherapy response) and 39% had an Immune-Enriched (IE; predictive of favorable immunotherapy response) TME. In low-grade ILC LumB samples we found that while 51% had a D TME, only 14% had an IE TME. We found an overrepresentation of the TLS signature [Solid TLS] in ILC compared to NST samples, and higher matrix remodeling and CAF signatures in LumA compared to the LumB subtype among low-grade ILC samples. Samples with high CD274 expression levels had higher percentages of T cells and M1 macrophages, and LumA samples had significantly higher (p < 0.001) CD274 expression compared to the other BC subtypes. Conclusion: These results provide in-depth molecular and tumor microenvironment characterization of ILC. Further optimization of this analytical approach could lead to the development of more effective therapeutic strategies. Table 1. ILC subtypes classification Citation Format: Jason Mouabbi, Konstantin Chernyshov, Oleg Baranov, Vladimir Kushnarev, Polina Turova, Anna Butusova, Sofia Menshikova, Jessica Brown, Nikita Kotlov, Patrick Clayton, Krystle Nomie, Nathan Fowler, Debu Tripathy. An integrated approach for comprehensive molecular and tumor microenvironment characterization of invasive lobular carcinoma [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 PO5-24-11.

Regulation of TMEM100 expression by epigenetic modification, effects on proliferation and invasion of esophageal squamous carcinoma.

Esophageal squamous cell carcinoma (ESCC) is a prevalent malignancy with a high morbidity and mortality rate. TMEM100 has been shown to be suppressor gene in a variety of tumors, but there are no reports on the role of TMEM100 in esophageal cancer (EC). To investigate epigenetic regulation of TMEM100 expression in ESCC and the effect of TMEM100 on ESCC proliferation and invasion. Firstly, we found the expression of TMEM100 in EC through The Cancer Genome Atlas database. The correlation between TMEM100 gene expression and the survival of patients with EC was further confirmed through Kaplan-Meier analysis. We then added the demethylating agent 5-AZA to ESCC cell lines to explore the regulation of TMEM100 expression by epigenetic modification. To observe the effect of TMEM100 expression on tumor proliferation and invasion by overexpressing TMEM100. Finally, we performed gene set enrichment analysis using the Kyoto Encyclopaedia of Genes and Genomes Orthology-Based Annotation System database to look for pathways that might be affected by TMEM100 and verified the effect of TMEM100 expression on the mitogen-activated protein kinases (MAPK) pathway. In the present study, by bioinformatic analysis we found that TMEM100 was lowly expressed in EC patients compared to normal subjects. Kaplan-meier survival analysis showed that low expression of TMEM100 was associated with poor prognosis in patients with EC. Then, we found that the demethylating agent 5-AZA resulted in increased expression of TMEM100 in ESCC cells [quantitative real-time PCR (qRT-PCR) and western blotting]. Subsequently, we confirmed that overexpression of TMEM100 leads to its increased expression in ESCC cells (qRT-PCR and western blotting). Overexpression of TMEM100 also inhibited proliferation, invasion and migration of ESCC cells (cell counting kit-8 and clone formation assays). Next, by enrichment analysis, we found that the gene set was significantly enriched in the MAPK signaling pathway. The involvement of TMEM100 in the regulation of MAPK signaling pathway in ESCC cell was subsequently verified by western blotting. TMEM100 is a suppressor gene in ESCC, and its low expression may lead to aberrant activation of the MAPK pathway. Promoter methylation may play a key role in regulating TMEM100 expression.

A Novel Gene Signature Based on Immune Cell Infiltration Landscape Predicts Prognosis in Lung Adenocarcinoma Patients.

The tumor microenvironment (TME) is created by the tumor and dominated by tumor-induced interactions. Long-term survival of lung adenocarcinoma (LUAD) patients is strongly influenced by immune cell infiltration in TME. The current article intends to construct a gene signature from LUAD ICI for predicting patient outcomes. For the initial phase of the study, the TCGA-LUAD dataset was chosen as the training group for dataset selection. We found two datasets named GSE72094 and GSE68465 in the Gene Expression Omnibus (GEO) database for model validation. Unsupervised clustering was performed on the training cohort patients using the ICI profiles. We employed Kaplan-Meier estimators and univariate Cox proportional-hazard models to identify prognostic differentially expressed genes in immune cell infiltration (ICI) clusters. These prognostic genes are then used to develop a LASSO Cox model that generates a prognostic gene signature. Validation was performed using Kaplan-Meier estimation, Cox, and ROC analysis. Our signature and vital immune-relevant signatures were analyzed. Finally, we performed gene set enrichment analysis (GSEA) and immune infiltration analysis on our finding gene signature to further examine the functional mechanisms and immune cellular interactions. Our study found a sixteen-gene signature (EREG, HPGDS, TSPAN32, ACSM5, SFTPD, SCN7A, CCR2, S100P, KLK12, MS4A1, INHA, HOXB9, CYP4B1, SPOCK1, STAP1, and ACAP1) to be prognostic based on data from the training cohort. This prognostic signature was certified by Kaplan-Meier, Cox proportional-hazards, and ROC curves. 11/15 immune-relevant signatures were related to our signature. The GSEA results indicated our gene signature strongly correlates with immune-related pathways. Based on the immune infiltration analysis findings, it can be deduced that a significant portion of the prognostic significance of the signature can be attributed to resting mast cells. We used bioinformatics to determine a new, robust sixteen-gene signature. We also found that this signature's prognostic ability was closely related to the resting mast cell infiltration of LUAD patients.

Abstract 1107: Prospective observational study to evaluate the efficacy of oxygen saturation endoscopic imaging for radiotherapeutic response in head and neck squamous cell carcinoma

Abstract Background: Radiotherapy (RT) has a pivotal role in the management of head and neck squamous cell carcinoma (HNSCC), providing effective tumor control and functional preservation. Hypoxia is a cause of radioresistance in HNSCC. We have developed an oxygen saturation endoscopic imaging (OXEI) method to assess real-time tissue oxygenation levels. However, the clinical significance of OXEI in patients with HNSCC receiving RT remains unclear. We evaluated the association between pretreatment tumor oxygen saturation (StO2) quantified by OXEI and clinical outcomes of patients with HNSCC receiving RT. Methods: We prospectively recruited patients with HNSCC scheduled to receive RT at 2 institutions. The primary endpoint was the association between pretreatment tumor StO2 and complete response (CR) rate 8 weeks after completion of RT. Secondary endpoints evaluated the impact of StO2 on 1-year overall survival (OS) and progression-free survival (PFS) rates after RT initiation. We also evaluated the cumulative incidence of local failure (LF). To explore the relationship between tumor hypoxia assessed by OXEI and gene expression profile, we performed RNA sequencing of 4 tumor samples collected from 2 patients (2 samples/patient) before RT. The hypoxia score for each sample was calculated by gene set variation analysis based on HNSCC mRNA-based hypoxia signatures. We performed gene set enrichment analysis (GSEA) to evaluate whether the biological pathways (Hallmark, Reactome, and KEGG gene sets) showed significant associations with tumor hypoxia. Results: Of the 50 patients enrolled from March 2019 to February 2022, we analyzed 37 who underwent RT and OXEI. Thirty-six (97%) patients received current platinum-based chemotherapy. The median (range) pretreatment tumor StO2 of 60 (45-84)% was lower than that of normal mucosa, 66 (56-84)% (P < 0.01). Patients with tumor StO2 < 60% were classified as the hypoxia group (n =19), and those with tumor StO2 ≥ 60% as the non-hypoxia group (n =18). The CR rate 8 weeks after RT was not significantly different between the hypoxia and non-hypoxia groups (84% vs. 100%, respectively; P = 0.23). After a median (range) follow-up of 33 (9-45) months, the hypoxia group had worse 1-year PFS (74% vs. 94%, P = 0.017) and OS (89% vs. 100%, P = 0.015) and higher LF rates (21% vs. 6%, P = 0.036) compared with the non-hypoxia group. RNA sequencing confirmed that tumor StO2 reflected expression-based hypoxia scores. GSEA showed upregulation of reactive oxygen species (ROS) and KEAP1-NFE2L2 pathways in hypoxic samples (StO2 of 59%) compared with non-hypoxic samples (StO2 of 70%; adjusted P < 0.01), consistent with the fact that hypoxic stress increases ROS production. Conclusion: Our findings suggest that pretreatment tumor StO2 quantified by OXEI correlates with 1-year PFS, OS, and LF rates of patients with HNSCC receiving RT. Citation Format: Kento Tomizawa, Atsushi Motegi, Hidenari Hirata, Hiroki Yamashita, Hironori Sunakawa, Wataru Okano, Tomohiro Enokida, Takeshi Fujisawa, Sadamoto Zenda, Masaki Nakamura, Hidehiro Hojo, Seiichiro Abe, Madoka Sakuramachi, Hiroshi Igaki, Yutaka Saito, Kazuto Matsuura, Makoto Tahara, Tomonori Yano, Tetsuo Akimoto. Prospective observational study to evaluate the efficacy of oxygen saturation endoscopic imaging for radiotherapeutic response in head and neck squamous cell carcinoma [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 1107.

Abstract 1254: Integration of human omics analysis and new syngeneic tumor organoid models reveals that aberrant RAS/PI3K crosstalk triggers refractoriness in high-grade serous carcinoma

Abstract Refractory high-grade serous carcinoma (HGSC) is one of the most severe clinical problems in gynecology, but we have barely grasped the underlying mechanism of aggressiveness and chemo-resistance. Previous study has shown that homologous recombination genes, BRCA1/2-unmutated HGSC patients possess the potential to be in refractory condition, and their primary response to chemotherapy was heterogenous; thus, there can be subtype-specific determinant factors hatching refractoriness in BRCA1/2-unmutated HGSC patients. To explore the determinant factors, we performed gene set variation analysis and comprehensive log-rank tests on TCGA advanced serous ovarian cancer datasets. As a result, regulation of small GTPase signaling prominently correlated with poor prognosis uniquely in BRCA1/2-unmutated HGSC patients (p-value < 0.001), and eventually, pathway clustering analysis by variational Bayesian Gaussian mixture model discovered aberrant RAS/PI3K crosstalk as peculiar poor prognostic signature of BRCA1/2-unmutated HGSC patients. To elucidate the mechanism of poor progression triggered by RAS/PI3K, we utilized our syngeneic HGSC organoid models newly established from murine fallopian tube epithelium by making Myc overexpressing, and knocking out Trp53 and Rb1; as a supplement, the propriety of these genetic alterations to develop HGSC models was backed up by genetic profiles of high-grade serous ovarian cancer patients in AACR Project GENIE. After that, we knocked out Nf1 and Pten whose deletions were detected relatively with high frequency in HGSC to induce aberrant RAS/PI3K crosstalk in the primitive HGSC model. In-vivo evaluation and growth comparison indicated that aberrant RAS/PI3K crosstalk transformed Brca1/2-unmutated HGSC modeling cells into aggressive phenotypes such as poor survival (p-value < 0.01) and high growth rate (p-value < 0.001). Chemo-sensitivity assay also showed that the genetic manipulation made Brca1/2-unmutated HGSC modeling cells more tolerant to anti-tumor agents like carboplatin (p-value < 0.001), paclitaxel (p-value < 0.01), and olaparib (p-value < 0.01). To investigate biological processes that induce the aggressive and chemo-resistant phenotype, we performed gene set enrichment analysis among our HGSC models. The result showed that aberrant RAS/PI3K crosstalk induces cell cycle acceleration and downregulation of apoptosis in the HGSC cells, which backed up aggressive phenotype and chemo-resistance in our HGSC models. In conclusion, aberrant RAS/PI3K crosstalk transforms Brca1/2-unmutated HGSC modeling cells more aggressive and chemo-resistant, which was well recapitulated by our HGSC modeling organoids. The integration of our computational approach and experimental models will lead us to detect peculiar therapeutic targets against refractory HGSC. Citation Format: Tomohiro Tamura, Kenta Masuda, Shimpei Nagai, Keiyo Imaeda, Juntaro Yamasaki, Eiji Sugihara, Hiroyuki Nobusue, Yuji Otsuki, Rui Yamaguchi, Kazuhiro Sakurada, Wataru Yamagami, Hideyuki Saya, Osamu Nagano. Integration of human omics analysis and new syngeneic tumor organoid models reveals that aberrant RAS/PI3K crosstalk triggers refractoriness in high-grade serous carcinoma [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 1254.

Abstract 7060: Mitochondrial metabolism and racial disparity of bladder cancer

Abstract Bladder cancer mortality is significantly higher in African American patients compared to their European American counterparts. This inferior survival of African American cancer patients is driven at least in part by distinctive intrinsic tumor biology, more specifically altered metabolic activity. However, underlying molecular mechanism for the African American bladder cancer mortality are largely unexplored. Our pioneering metabolomic findings demonstrate alterations in metabolic pathways between African American and European American bladder cancer, specifically those involved in driving energy metabolism. Along these line, we observed increased electron transport chain activity and ATP production in African American bladder cancer could be a result of distinctive rewiring of energy metabolism compared to their European American counterparts. We further performed gene set enrichment analysis by mapping metabolites to genes and observed that oxidative phosphorylation pathway was uniquely enriched in African American tumors compared to European American tumors. In addition, from in vitro assays, mitochondrial complex protein and activity were altered in African American bladder cancer. To determine the role of glutamine mediated increased electron transport chain activity and ATP production in African American bladder cancer, we evaluated the metabolic flux using 13C labeled tracers in both African American and European American bladder cancer cell lines. Metabolic flux analysis revealed that African American cell lines are more glutamine dependent and that producing increased tricarboxylic acid intermediates. Overall, our data indicate that elevated mitochondrial metabolism and oxidative phosphorylation driven by enhanced glutaminolysis may facilitate African American bladder cancer progression. These findings provide the rationale to use mitochondrial-specific inhibitors to target at least a subset of African American bladder cancer patients. Citation Format: Karthik Reddy Kami Reddy, Jun Hyoung Park, Roni J. Bollag, Martha K. Terris, Seth P. Lerner, Minhaj Siddiqui, Yair Lotan, Jianjun Gao, Benny Abraham Kaipparettu, Nagireddy Putluri. Mitochondrial metabolism and racial disparity of bladder 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 7060.

Abstract 1637: EPHB4 is a key regulator of G1/S transition in hepatocellular carcinoma

Abstract Effective therapeutic regimens against advanced hepatocellular carcinoma (HCCs) have recently improved but it remains very limited. Targeting receptor tyrosine kinases (RTKs) has proven to one of the main ways of achieving better survival outcome in HCC patients, yet the precise mechanism for this success remains to be elusive. We have systematically investigated the expression profiles of RTKs transcriptomic datasets i.e. The Cancer Genome Atlas - Liver hepatocellular carcinoma (TCGA-LIHC) (n=371) and our in-house cohort of paired i.e. HKU-QMH (n=41), and identified EPHB4 as one of the most abundantly expressed and frequently mutated RTKs in human HCCs. EPHB4 expression was found to be significantly correlated with Alpha Fetoprotein (AFP) expression, a factor commonly used in the diagnosis of HCCs. Furthermore, EphB4 has been demonstrated to play a regulatory role in VEGF/VEGFR-mediated angiogenesis, critical targets for current successful drugs. We confirmed abundant membrane EphB4 expression in HCC clinical specimens and human HCC cell line models using immunohistochemistry. Clinicopathological correlation analysis of EPHB4 mRNA expression revealed that its overexpression is associated with aggressive tumor features including presence of tumor microsatellite, liver invasion, venous invasion, and absence of tumor encapsulation. Functionally, stably knocking down EPHB4 (shEPHB4) resulted in a strong reduction of proliferation and self-renewal rates of multiple HCC cell lines in vitro. It significantly reduced tumor growth rates in subcutaneous and liver orthotopic models in vivo. Furthermore, limiting dilution assay showed EPHB4 plays a role in tumor initiation property of HCC cells. Mechanistically, we performed Gene Set Enrichment Analysis (GSEA) of transcriptome profiles for shEPHB4 with respective controls and found that knocking down EPHB4 causes HCC cells undergo drastic changes in several cell cycle checkpoints including G1/S transition. Using thymidine blockade, we further confirmed that knockdown of significantly hinders the transition of HCC cells from G1 to S phase of cell cycle. Our data suggests a strong link between EphB4 and cell cycle. Conclusion: We found EphB4 plays a functional role in regulating G1/S transition in human HCCs and understanding regulatory role of EphB4 on cell cycle progression may provide mechanistic insights into the how to effectively target HCC in the clinic. Citation Format: Abdullah Husain, Elley Y. Chiu, Hoi-Tang Ma, Daniel W. Ho, Karen M. Sze, Lo-Kong Chan, Irene O. Ng. EPHB4 is a key regulator of G1/S transition in hepatocellular carcinoma [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 1637.

Mining phase separation-related diagnostic biomarkers for endometriosis through WGCNA and multiple machine learning techniques: a retrospective and nomogram study.

The objective of this study was to investigate the role of phase separation-related genes in the development of endometriosis (EMs) and to identify potential characteristic genes associated with the condition. We used GEO database data, including 74 non-endometriosis and 74 varying-degree EMs patients. Our approach involved identifying significant gene modules, exploring gene intersections, identifying core genes, and screening for potential EMs biomarkers using weighted gene co-expression network analysis (WGCNA) and various machine learning approaches. We also performed gene set enrichment analysis (GSEA) to understand relevant pathways. This comprehensive approach helps investigate EMs genetics and potential biomarkers. Nine genes were identified at the intersection, suggesting their involvement in EMs. GSEA linked DEGs to pathways like complement and coagulation cascades, DNA replication, chemokines, apical plasma membrane processes, and diseases such as Hepatitis B, Human T-cell leukemia virus 1 infection, and COVID-19. Five feature genes (FOS, CFD, CCNA1, CA4, CST1) were selected by machine learning for an effective EMs diagnostic nomogram. GSEA indicated their roles in mismatch repair, cell cycle regulation, complement and coagulation cascades, and IL-17 inflammation. Notable differences in immune cell proportions (CD4 T cells, CD8 T cells, DCs, macrophages) were observed between normal and disease groups, suggesting immune involvement. This study suggests the potential involvement of phase separation-related genes in the pathogenesis of endometriosis (EMs) and identifies promising biomarkers for diagnosis. These findings have implications for further research and the development of new therapeutic strategies for EMs.

Unveiling the mitophagy puzzle in non-alcoholic fatty liver disease (NAFLD): Six hub genes for early diagnosis and immune modulatory roles

BackgroundNon-alcoholic fatty liver disease (NAFLD) stands as a predominant chronic liver ailment globally, yet its pathogenesis remains elusive. This study aims to identify Hub mitophagy-related genes (MRGs), and explore the underlying pathological mechanisms through which these hub genes regulate NAFLD. MethodsA total of 3 datasets were acquired from the GEO database and integrated to identify differentially expressed genes (DEGs) in NAFLD and perform Gene Set Enrichment Analysis (GSEA). By intersecting DEGs with MRGs, mitophagy-related differentially expressed genes (MRDEGs) were obtained. Then, hub MRGs with diagnostic biomarker capability for NAFLD were screened and a diagnostic prediction model was constructed and assessed using Nomogram, Decision Curve Analysis (DCA), and ROC curves. Functional enrichment analysis was conducted on the identified hub genes to explore their biological significance. Additionally, regulatory networks were constructed using databases. NAFLD was stratified into high and low-risk groups based on the Riskscore from the diagnostic prediction model. Furthermore, single-sample gene set enrichment analysis (ssGSEA) and CIBERSORT algorithms were employed to analyze immune cell infiltration patterns and the relationship between Hub MRGs and immune cells. ResultsThe integrated dataset comprised 122 NAFLD samples and 31 control samples. After screening, 18 MRDEGs were identified. Subsequently, six hub MRGs (NR4A1, PPP2R2A, P4HA1, TUBB6, DUSP1, NAMPT) with diagnostic potential were selected through WGCNA, logistic regression, SVM, RF, and LASSO models, all significantly downregulated in NAFLD samples compared to the control group. A diagnostic prediction model based on these six genes demonstrated robust predictive performance. Functional enrichment analysis of the six hub genes revealed involvement in processes such as protein phosphorylation or dephosphorylation. Correlation analysis demonstrated a significant association between hub MRGs and infiltrating immune cells. ConclusionWe identified six hub MRGs in NAFLD and constructed a diagnostic prediction model based on these six genes, applicable for early NAFLD diagnosis. These genes may participate in regulating NAFLD progression through the modulation of mitophagy and immune activation. Our findings may contribute to subsequent clinical and basic research on NAFLD.

Identification of Potentially Repurposable Drugs for Lewy Body Dementia Using a Network-Based Approach.

The conventional method of one drug being used for one target has not yielded therapeutic solutions for Lewy body dementia (LBD), which is a leading progressive neurological disorder characterized by significant loss of neurons. The age-related disease is marked by memory loss, hallucinations, sleep disorder, mental health deterioration, palsy, and cognitive impairment, all of which have no known effective cure. The present study deploys a network medicine pipeline to repurpose drugs having considerable effect on the genes and proteins related to the diseases of interest. We utilized the novel SAveRUNNER algorithm to quantify the proximity of all drugs obtained from DrugBank with the disease associated gene dataset obtained from Phenopedia and targets in the human interactome. We found that most of the 154 FDA-approved drugs predicted by SAveRUNNER were used to treat nervous system disorders, but some off-label drugs like quinapril and selegiline were interestingly used to treat hypertension and Parkinson's disease (PD), respectively. Additionally, we performed gene set enrichment analysis using Connectivity Map (CMap) and pathway enrichment analysis using EnrichR to validate the efficacy of the drug candidates obtained from the pipeline approach. The investigation enabled us to identify the significant role of the synaptic vesicle pathway in our disease and accordingly finalize 8 suitable antidepressant drugs from the 154 drugs initially predicted by SAveRUNNER. These potential anti-LBD drugs are either selective or non-selective inhibitors of serotonin, dopamine, and norepinephrine transporters. The validated selective serotonin and norepinephrine inhibitors like milnacipran, protriptyline, and venlafaxine are predicted to manage LBD along with the affecting symptomatic issues.

Increased PIEZO1 Expression Is Associated with Worse Clinical Outcomes in Hormone-Receptor-Negative Breast Cancer Patients.

PIEZO1 plays a crucial role in the human body as a mechanosensory ion channel. It has been demonstrated that PIEZO1 is important in tissue development and regulating many essential physiological processes. Studies have suggested that the PIEZO1 ion channel plays a role in invasion and progression in cancer; elevated levels of PIEZO1 have been correlated with increased migration in breast cancer cells, chemo-resistance and invasion in gastric cancer cells, and increased invasion of osteosarcoma cells. In addition, high PIEZO1 expression levels were correlated with a worse prognosis in glioma patients. On the other hand, studies in lung cancer have attributed high PIEZO1 levels to better patient outcomes. However, the clinical impact of PIEZO1 in breast cancer is not well characterized. Therefore, our goal was to determine the clinical relevance of PIEZO1 in breast cancer. An analysis of breast cancer data from The Cancer Genome Atlas (TCGA) was conducted to investigate PIEZO1 expression levels and correlation to survival, followed by validation in an independent dataset, GSE3494. We also performed gene set enrichment analysis (GSEA) and pathway enrichment analysis. We also analyzed the immune cell composition in breast tumors from TCGA through a CIBERSORT algorithm. Our results demonstrated that the PIEZO1 expression levels are higher in hormone-receptor (HR)-negative than in HR-positive cohorts. High PIEZO1 expression is correlated with a significant decrease in survival in HR-negative cohorts, especially in triple-negative breast cancer (TNBC), suggesting that PIEZO1 could be utilized as a prognostic biomarker in HR-negative breast cancer. GSEA showed that various signaling pathways associated with more invasive phenotypes and resistance to treatments, including epithelial-mesenchymal transition (EMT), hypoxia, and multiple signaling pathways, are enriched in high-PIEZO1 HR-negative tumors. Our results also demonstrated a decrease in CD8+ and CD4+ T cell infiltration in high-PIEZO1 HR-negative tumors. Further investigations are necessary to elucidate the mechanistic roles of PIEZO1 in HR-negative breast cancer.

Identification of CXC Chemokine Receptor 2 (CXCR2) as a Novel Eosinophils-Independent Diagnostic Biomarker of Pediatric Eosinophilic Esophagitis by Integrated Bioinformatic and Machine-Learning Analysis.

Eosinophilic esophagitis (EoE) is a complex allergic condition frequently accompanied by various atopic comorbidities in children, which significantly affects their life qualities. Therefore, this study aimed to evaluate pivotal molecular markers that may facilitate the diagnosis of EoE in pediatric patients. Three available EoE-associated gene expression datasets in children: GSE184182, GSE 197702, GSE55794, along with GSE173895 were downloaded from the GEO database. Differentially expressed genes (DEGs) identified by "limma" were intersected with key module genes identified by weighted gene co-expression network analysis (WGCNA), and the shared genes went through functional enrichment analysis. The protein-protein interaction (PPI) network and the machine learning algorithms: least absolute shrinkage and selection operator (LASSO), random forest (RF), and XGBoost were used to reveal candidate diagnostic markers for EoE. The receiver operating characteristic (ROC) curve showed the efficacy of differential diagnosis of this marker, along with online databases predicting its molecular regulatory network. Finally, we performed gene set enrichment analysis (GSEA) and assessed immune cell infiltration of EoE/control samples by using the CIBERSORT algorithm. The correlations between the key diagnostic biomarker and immune cells were also investigated. The intersection of 936 DEGs and 1446 key module genes in EoE generated 567 genes, which were primarily enriched in immune regulation. Following the construction of the PPI network and filtration by machine learning, CXCR2 served as a potential diagnostic biomarker of pediatric EoE with a perfect diagnostic efficacy (AUC = ~1.00) in regional tissue/peripheral whole blood samples. Multiple infiltrated immune cells were observed to participate in disrupting the homeostasis of esophageal epithelium to varying degrees. The immune-correlated CXCR2 gene was proved to be a promising diagnostic indicator for EoE, and dysregulated regulatory T cells (Tregs)/neutrophils might play a crucial role in the pathogenesis of EoE in children.

Development and Validation of Potential Molecular Subtypes and Signatures of Thyroid Carcinoma Based on Aging-related Gene Analysis.

Thyroid carcinoma (THCA) is a cancer of the endocrine system that most commonly affects women. Aging-associated genes play a critical role in various cancers. Therefore, we aimed to gain insight into the molecular subtypes of thyroid cancer and whether senescence-related genes can predict the overall prognosis of THCA patients. Thyroid carcinoma (THCA) transcriptome-related expression profiles were obtained from The Cancer Genome Atlas (TCGA) database. These profiles were randomly divided into training and validation subsets at a ratio of 1:1. Unsupervised clustering algorithms were used to compare differences between the two subtypes; prognosis-related senescence genes were used to further construct our prognostic models by univariate and multivariate Cox analyses and construct a nomogram to predict the 1-, 3-, and 5-year overall survival probability of THCA patients. In addition, we performed gene set enrichment analysis (GSEA) to predict the immune microenvironment and somatic mutations between the different risk groups. Finally, real-time PCR was used to verify the expression levels of key model genes. The 'ConsensusClusterPlus' R package was used to cluster thyroid cancer into two categories (Cluster1 and Cluster2) on the basis of 46 differentially expressed aging-related genes (DE-ARGs); patients in Cluster1 demonstrated a better prognosis than those in Cluster2. Cox analysis was used to screen six prognosis-related DE-ARGs. Finally, our real-time PCR results confirmed our hypothesis. Differences exist between the two subtypes of thyroid cancer that help guide treatment decisions. The six DE-ARG genes have a high predictive value for risk stratifying THCA patients.

Low CDKN1B Expression Associated with Reduced CD8+ T Lymphocytes Predicts Poor Outcome in Breast Cancer in a Machine Learning Analysis.

The cyclin-dependent kinase inhibitor 1B (CDKN1B) gene, which encodes the p27Kip1 protein, is important in regulating the cell cycle process and cell proliferation. Its role in breast cancer prognosis is controversial. We evaluated the significance and predictive role of CDKN1B expression in breast cancer prognosis. We investigated the clinicopathologic factors, survival rates, immune cells, gene sets, and prognostic models according to CDKN1B expression in 3794 breast cancer patients. We performed gene set enrichment analysis (GSEA), in silico cytometry, pathway network analyses, gradient boosting machine (GBM) learning, and in vitro drug screening. High CDKN1B expression levels in breast cancer correlated with high lymphocyte infiltration signature scores and increased CD8+ T cells, both of which were associated with improved prognosis in breast cancer. which were associated with a better prognosis. CDKN1B expression was associated with gene sets for the upregulation of T-cell receptor signaling pathways and downregulation of CD8+ T cells. Pathway network analysis revealed a direct link between CDKN1B and the pathway involved in the positive regulation of the protein catabolic process pathway. In addition, an indirect link was identified between CDKN1B and the T-cell receptor signaling pathway. In in vitro drug screening, BMS-345541 demonstrated efficacy as a therapeutic targeting of CDKN1B, effectively impeding the growth of breast cancer cells characterized by low CDKN1B expression. The inclusion of CDKN1B expression in GBM models increased the accuracy of survival predictions. CDKN1B expression plays a significant role in breast cancer progression, implying that targeting CDKN1B might be a promising strategy for treating breast cancer.

Transcriptomic Analysis of Tight Junction Proteins Demonstrates the Aberrant Expression and Function of Zona Occludens 2 (ZO-2) Protein in Stanford Type A Aortic Dissection.

Thoracic aortic aneurysm dissection (TAAD) represents a cardiac surgery emergency characterized by the disrupted integrity of the aortic wall and is associated with poor prognosis. In this context, the identification of biomarkers implicated in the pathobiology of TAAD is crucial. Our aim in the present original in silico study is to assess the differential gene expression profile of the tight junction proteins (TJPs) in patients with TAAD and to propose novel biomarkers for the diagnosis and prognosis of this disease. We implemented bioinformatics methodology in order to construct the gene network of the TJPs family, identify the differentially expressed genes (DEGs) in pathologic aortic tissue excised from patients with TAAD as compared to healthy aortic tissue, and assess the related biological functions and the associated miRNA families. Data regarding the transcriptomic profile of selected genes were retrieved and incorporated from three microarray datasets, including 23 TAAD and 20 healthy control samples. A total of 32 TJPs were assessed. The zona occludens 2 (ZO-2) protein encoded by the gene TJP2 was significantly under-expressed in patients with TAAD compared to the control group (p = 0.009). ZO-2 was associated with fair discrimination and calibration traits in predicting the TAAD presentation. CpG islands of ZO-2 were demonstrated. No important difference was found regarding ZO-2 expression between aneurysmal non-dissected and healthy control aortic tissue. Finally, we performed gene set enrichment analysis (GSEA) and uncovered the major biological functions and miRNA families (hsa-miR-155-5p, hsa-miR-1-3p, hsa-miR-2118-5p, hsa-miR-4691-3p, and hsa-miR-1229-3p) relevant to ZO-2. These outcomes demonstrated the important role of ZO-2 in the pathobiology of TAAD.

Single‐nuclei RNA sequencing provides evidence for glial senescence in Alzheimer’s disease

AbstractBackgroundAgeing is the greatest risk factor for Alzheimer’s disease (AD). While accumulation of senescent cells is one of the major hallmarks of ageing, the effect of the senescence burden is yet to be explored in AD. The aims of this study were to i) quantify senescent microglia, oligodendrocyte and astrocyte in human brain in AD, ii) determine the driver of cell senescence in AD, and iii) AD pathology associated senescence.MethodWe multiplexed Image Mass Cytometry (IMC) to co‐localise cell type markers (IBA1, OLIG2, GFAP), senescence markers (GLB1 and p16) and β‐amyloid (4G8) to detect senescence in tissues from Middle Temporal Gyrus (MTG) of 10 AD and 10 non‐disease control (NDC). We also generated snRNA‐seq from three different brain regions of the same subject namely Entorhinal (EC), MTG (Mid‐temporal Cortex) and Somatosensory Cortex (SSC) of 9 AD and 9 NDC. We performed geneset enrichment analysis using a set of curated senescence associated genesets in snRNA‐seq using AUcell and dream (variancePartition). We further performed trajectory analysis using Monocle3 to characterise β‐amyloid associated senescence signatures in the snRNAseq data.ResultMore than 25% microglia, oligodendrocyte and astrocyte were positive for GLB1 in AD brains while only around 5% glia showed GLB1 expression in NDC. Around 25% peri‐plaque microglia within 10 µm around β‐amyloid plaques in AD showed expression of GLB1 while only 3% of microglia >10 µm had associated senescence markers. Senescence genes were significantly upregulated in AD compared to NDC and were positively correlated with increase amyloid densities in all three glial cells (not in neurons). Trajectories of the glial nuclei described increased expression of pathways related to replicative senescence, cellular activation and stress response in microglia and oxidative stress in oligodendroglia, and astrocyte. Senescence gene signatures were positively associated with both β‐amyloid and pTau.ConclusionOur results highlight the high burden of senescent glia and provide evidence for distinct mechanisms of senescence in microglia (both replicative and stress‐induced) relative to oligodendroglia and astrocyte (stress‐induced) in AD. Both β‐amyloid and pTau associated increase in senescence gene signatures suggest that senescence is an important feature in the late stage of AD.

XPO2 Is Essential for a Subset of AML Cells and Is a Biomarker for Poor Response and Survival in Pediatric and AYA AML

Importins & exportins regulate protein transport across the nuclear membrane. Twenty nuclear transport receptors (NTRs) have been identified; six are involved in nuclear export. NTRs contribute to cancer development, through abnormal localization of protein cargos. The exportin, XPO1, is associated with high risk AML & shorter survival times. However, little is known regarding the functional importance of the related exportin, XPO2 (alias CSE1L). We analyzed a public database of CRISPR/Cas9 depletion screens in 26 AML cell lines. XPO2 ranked in the top 1.4% of essential genes, along with XPO1 (top 1.3%) (DepMap 22Q2 Public+Score, Chronos). An RNAi depletion screen confirmed this, with XPO2 ranked in the top 0.2% of AML genes. Leukemia cells were more dependent on XPO2 vs solid tumors (P = 0.0394) & gene dependency scores indicated a greater reliance on XPO2 vs XPO1 (P <0.0001). Increased expression of XPO2 mRNA was associated with decreased event free survival (EFS) (P = 0.0014) & overall survival (OS) (P = 0.00091) in pediatric & adolescent/young adult (AYA) AML patients (TARGET dataset). In the BeatAML dataset, increased XPO2 mRNA expression was associated with decreased OS in patients <40 years, but not in patients >40 years (P <0.0001). We analyzed protein expression databases & identified XPO2 as the highest expressed exportin in AML cells lines & patient samples. Increased XPO2 expression was detected in 7/7 primary AML samples & 9 AML cell lines by immunoblot (HL60, MV4-11, MOML13, NB4, OCI-AML2, OCI-M2, TEX, U937 & 1254 cells), compared to normal hematopoietic cells. Expression of XPO2 was increased in younger (<40 years) vs older patients (>70 years) (P = 0.0454). Genetic silencing of XPO2 decreased growth & viability of OCI-AML2, TEX, NB4 & 1254 cells. Gambogic acid is an inhibitor of XPO2-mediated nuclear transport. In OCI-AML2, TEX & NB4 cell lines, gambogic acid decreased viability of AML cells (TEX IC50 = 369nM, OCI-AML2 IC50 = 433nM, NB4 IC50 = 161nM). Next, we interrogated a BioID database (PXD007976) & performed gene set enrichment analysis on XPO2 targets. Processes related to ribosome biogenesis were enriched in XPO2 cargo, whereas XPO1 cargo were enriched for snRNA transcription processes (P <0.05). A gene expression signature encompassing XPO2 & its associated cargo genes was enriched in functionally defined LSCs (P = 0.001, in patients with more primitive AML subtypes (P < 2.22 x 10 -16), in more primitive AML blasts as defined by FAB subtype and in high risk subsets, including WT1 mutated pediatric AML. Additionally, the XPO2 gene signature was associated with minimal-residual-disease (MRD) positive disease after induction cycle I (P < 5.1x 10 -6) and II (P = 0.0013), decreased complete remission (CR) rates after cycle I (P = 0.00025) and II (P = 0.02), worse EFS (P = 0.019) and worse OS (P = 0.02) in pediatric and AYA AML patients. In summary, we identified XPO2 as an essential gene for AML . XPO2 is increased in AML cells & primary samples from younger patients. Increased XPO2 expression & increased expression of XPO2 mediated processesare associated with worse outcomes in pediatric AML & correlate with LSC enrichment & primitive AML subtypes. XPO2 may function to enhance ribosomal biogenesis, demonstrating a critical role in leukemogenesis. Thus, this work demonstrates a new dependency of pediatric AML on XPO2 highlighting a new target and biomarker for this disease.

Genome-Wide Methylome and Transcriptome Profiling of Acute Myeloid Leukemia Derived Bone Marrow Mesenchymal Cells Identify Age Group Specific Biological Pathway Dysregulation in the Bone Marrow Microenvironment of AML

Adult patients with acute myeloid leukemia (AML) have a proportionate increase in mortality from their disease and therapy as age increases. In great part, this mortality is due to disease relapse that occurs at a higher rate irrespective of genetic assigned risk. While intensification of therapy in patients with favorable genomics such as core-binding-factor AML (CBF-AML) has yielded a high proportion of long-term remission and potential cure, this benefit has been less frequently observed in patients with AML age 60 and older despite receipt of similar therapy. Moreover, even less benefit has been observed in patients with unfavorable genomics such when bearing a complex karyotype (karyotype with ≥ 3 chromosome abnormalities). Reasons for this unfavorable outcome among older patients is unknown. We hypothesized that tumor-induced aging in cells of bone marrow microenvironment, specifically, in bone marrow mesenchymal stromal cells (BMSCs) plays a significant role in AML survival and progression in older compared to younger patients and that the difference in prognosis may depend on specific aging induced changes in the BMSCs. We expanded BMSCs under physiologic hypoxic conditions (91% nitrogen, 4% oxygen and 5% CO 2) to mimic the bone marrow microenvironment, isolated DNA and RNA from early passaged cells and performed methylation analysis using 850k Illumina DNAmehtylation arrays and gene expression analysis using mRNAseq. We used the Horvath Skin and Blood clock to calculate epigenetic age (DNA methylation age). We determined differentially expressed genes with increasing epigenetic or chronological age in the different AML genetic risk groups (n=9 CBF-AML, n=11 CK-AML and n=7 Normal donor BMSC) as well as in older (>60) and younger (<60) AML-BMSCs, and performed Gene Set Enrichment Analysis (GSEA) for the Hallmarks as well as aging and senescence related genesets (n=33 genesets). We found that BMSCs derived from AML bone marrow cells are more age accelerated than normal donor BMSCs. Our GSEA analysis revealed enrichment for age-associated gene networks that reflected hallmarks of aging, including mitochondrial dysfunction, inflammation, and cellular senescence. Specifically, we observed a positive enrichment for the SenMayo gene signature ( Saul et al. 2022, Nature Communications) and a negative enrichment of proliferation and mitotic gene sets with increasing epigenetic and chronological age (padj<0.05). Gene sets that are related to inhibition of adipogenesis were positively enriched in the CBF-AML BMSCs compared to the CK-AML BMSCs. Our integrated analysis revealed novel observations regarding the cellular changes that occur in the AML stromal microenvironment with increasing age. Most interestingly, our findings suggest that AML derived BMSCs have increased epigenetic age compared to normal donor BMSCs. Additional experiments are ongoing to functionally validate the findings predicted by the enrichment analysis. Our study is the first to suggest an increased epigenetic age in the stromal bone marrow microenvironment of older AML patients.

A Functional Genomic Screen to Identify Novel Genes Involved in Multiple Myeloma Tumour Development

Multiple myeloma (MM) is an incurable malignancy characterised by uncontrolled proliferation of plasma cells (PCs) in the bone marrow (BM). MM is a genetically heterogeneous disease with each patient's PCs harbouring unique genetic mutations, however the development of MM tumours is not only dependent on the underlying genetics but also on the selective pressures applied by the BM microenvironment. Hence, we hypothesise that identifying the dependencies which promote MM cell outgrowth in the BM microenvironment will allow for the identification of new drug targets. This project aims to use an in vivo functional screen, combining CRISPR-Cas9 gene editing, using a single guide RNA (sgRNA) library targeting thousands of genes, with a murine model of MM, to identify novel genes involved in MM tumour development. The Bassik human apoptosis and cancer CRISPR knockout library (Addgene #101926) was used to transduce MM cells with 31,324 unique sgRNAs targeting 3,015 genes and 1,500 control regions. The human MM cell line OPM2 was transduced with the Cas9 transgene (FuCas9GFP), followed by the sgRNA expression vector (pMCB320) generating OPM2-Cas9-sgRNA cells. These cells were then injected (5x10 5 cells/mouse, n=8 mice + 1 tumour-naive control) into the tibiae of immunodeficient NOD.Cg-Prkdc scid Il2rg tm1Wjl/SzJ (NSG) mice. Four weeks post-injection, the primary tumour within the injected tibia was isolated and sgRNA frequencies were assessed via next generation sequencing and compared with that of the initial library and the injected cells using the MAGeCK algorithm. To identify genes that play roles in MM tumour formation in patients, we assessed the expression of our identified genes in CD138-selected BM PCs from newly diagnosed MM patients (n=155) when compared with normal PCs from healthy donors (n=5) in microarray dataset E-MTAB-363 (ArrayExpress). Furthermore, to identify potential pathway involvement of our identified genes we performed gene set enrichment analysis (GSEA) using the University of California San Diego and Broad Institute developed GSEA software, comparing to Hallmark Gene Sets. Comparison of the in vitro cultured cells with the initial library identified 34 genes with undetectable (p<0.05) sgRNAs post in vitro culture, suggesting these genes play key roles in the survival of OPM2 cells. This list contained a number of genes known to control MM cell survival, such as IRF4 and CCND2. Additionally, sgRNAs targeting a further 115 genes were significantly depleted (p<0.05) in vitro and were completely undetectable in vivo, suggesting that these are implicated in cell proliferation and tumour formation in vivo. This gene list contained some already known MM drivers such as MYC, KRAS and DIS3. Furthermore, we identified 28 genes where CRISPR knockout had no significant effect in vitro but were critical dependencies for tumour development, with sgRNAs being undetectable (p<0.05) in vivo. This list contained genes known to be important for MM and BM stromal cell interaction such as ALCAM and SPP1. Notably, 25% of the genes identified as critical dependencies for OPM2 cells in vitro and/or in vivo are significantly upregulated >2-fold (p<0.05; limma) in MM patient PCs when compared with normal PCs (E-MTAB-363), suggesting these may play a role in tumour development in patients. Gene set enrichment analysis revealed that the genes that were essential in vitro were predominantly involved in cell survival related pathways such as cell cycle regulation (G2M checkpoint) and DNA replication/repair; however, the uniquely in vivo genes are predominantly involved in cell metabolism pathways such as MTORC1 signalling, oxidative phosphorylation and glycolysis. Overall, this study has successfully used a functional genetic screen to identify novel gene dependencies required for in vitro MM cell growth and in vivo MM tumour development. A secondary genetic screen will be performed in vivo to validate and refine this list of candidate genes. These validated genes will be further investigated using patient derived data sets to determine if they represent common vulnerabilities in patients and in multiple MM cell lines to investigate their specific mechanistic and pathway involvement. Identification and understanding the driving dependencies which promote MM cell outgrowth in the BM microenvironment will allow for the identification and development of new drug targets to improve patient outcomes.