Comprehensive Bioinformatics Analysis Research Articles

The CC2D2B is a novel genetic modifier of the clinical phenotype in patients with hereditary angioedema due to C1 inhibitor deficiency

Hereditary angioedema due to C1 inhibitor deficiency (HAE-C1-INH) is a rare genetic disorder caused by pathogenic variants in the SERPING1 gene and characterised by swelling and a highly variable clinical phenotype. We aimed to identify novel modifying genetic factors predisposing to the clinical symptoms. We performed whole exome sequencing (WES) and comprehensive bioinformatic analysis in symptomatic and asymptomatic (three duos) family members with HAE-C1-INH. Selected variants identified using WES (present in all asymptomatic and absent in symptomatic patients) were determined using Sanger sequencing. We included 88 clinically well-characterised HAE-C1-INH patients from south-eastern Europe (nine asymptomatic) from 42 unrelated families. We identified 39 variants in 23 genes (ANKRD36C, ARGFX, CC2D2B, IL5RA, IRF2BP2, LGR6, MRPL45, MUC3A, NPIPA1, NRG1, OR5M1, OR5M3, OR5M10, OR8U3, PLCL1, PRSS3, PSKH2, PTPRA, RTP4, SEZ6, SLC25A5, VWA3A, and ZNF790). We selected variants in CC2D2B and PLCL1, which were analysed using Sanger sequencing in the entire group of HAE-C1-INH. We found significant differences in the frequencies of the CC2D2B c.190A>G (rs17383738) variant between symptomatic and asymptomatic patients, where heterozygotes were more common in asymptomatic HAE-C1-INH patients in comparison to symptomatic patients (55 % vs 23%; P = 0.049, OR = 4.24, 95% CI 1.07‐14.69). Our study identified novel genetic factors that modify the clinical variability of HAE-C1-INH. We further demonstrated, in a large cohort, the importance of the CC2D2B gene as a disease-modifying factor. Based on linkage disequilibrium analysis, the CCNJ and ZNF518A genes might also be involved in the clinical variability of HAE-C1-INH.

HIF-1α-mediated LAMC1 overexpression is an unfavorable predictor of prognosis for glioma patients: evidence from pan-cancer analysis and validation experiments

BackgroundLaminin subunit gamma-1 (LAMC1) is a major extracellular matrix molecule involved in the tumor microenvironment. Knowledge of the biological features and clinical relevance of LAMC1 in cancers remains limited.MethodsWe conducted comprehensive bioinformatics analysis of LAMC1 gene expression and clinical relevance in pan-cancer datasets of public databases and validated LAMC1 expression in glioma tissues and cell lines. The association and regulatory mechanism between hypoxia inducible factor-1α (HIF-1α) and LAMC1 expression were explored.ResultsLAMC1 expression in most cancers in The Cancer Genome Atlas (TCGA) including glioma was significantly higher than that in normal tissues, which had a poor prognosis and were related to various clinicopathological features. Data from the Chinese Glioma Genome Atlas also showed high expression of LAMC1 in glioma associated with poor prognoses. In clinical glioma tissues, LAMC1 protein was highly expressed and correlated to poor overall survival. LAMC1 knockdown in Hs683 glioma cells attenuated cell proliferation, migration, and invasion, while overexpression of LAMC1 in U251 cells leads to the opposite trend. Most TCGA solid cancers including glioma showed enhancement of HIF-1α expression. High HIF-1α expression leads to adverse prognosis in gliomas, besides, HIF-1α expression was positively related to LAMC1. Mechanistically, HIF-1α directly upregulated LAMC1 promotor activity. Hypoxia (2% O2)-treated Hs683 and U251 cells exhibited upregulated HIF-1α and LAMC1 expression, which was significantly attenuated by HIF-1α inhibitor YC-1 and accompanied by attenuated cell proliferation and invasion.ConclusionsHigh expression of LAMC1 in some solid tumors including gliomas suggests a poor prognosis. The hypoxic microenvironment in gliomas activates the HIF-1α/LAMC1 signaling, thereby promoting tumor progression. Targeted intervention on the HIF-1α/LAMC1 signaling attenuates cell growth and invasion, suggesting a new strategy for glioma treatment.

Nobiletin Inhibits Breast Cancer Stem Cell by Regulating the Cell Cycle: A Comprehensive Bioinformatics Analysis and In Vitro Experiments

Inhibiting breast cancer stem cell (BCSC) signaling pathways is a strategic method for successfully treating breast cancer. Nobiletin (NOB) is a compound widely found in orange peel that exhibits a toxic effect on various types of cancer cells, and inhibits the signaling pathways that regulate the properties of BCSCs; however, the effects of NOB on BCSCs remain elusive. The purpose of this study was to determine the target genes of NOB for inhibiting BCSCs using in vitro three-dimensional breast cancer cell culture (mammospheres) and in silico approaches. We combined in vitro experiments to develop mammospheres and conducted cytotoxicity, next-generation sequencing, and bioinformatics analyses, such as gene ontology, the Reactome pathway enrichment, network topology, gene set enrichment analysis, hub genes selection, genetic alterations, prognostic value related to the mRNA expression, and mRNA and protein expression of potential NOB target genes that inhibit BCSCs. Here, we show that NOB inhibited BCSCs in mammospheres from MCF-7 cells. We also identified CDC6, CHEK1, BRCA1, UCHL5, TOP2A, MTMR4, and EXO1 as potential NOB targets inhibiting BCSCs. NOB decreased G0/G1, but increased the G2/M cell population. These findings showed that NOB is a potential therapeutic candidate for BCSCs treatment by regulating cell cycle.

Comprehensive bioinformatics analysis of NOX4 as a biomarker for pan-cancer prognosis and immune infiltration.

NADPH oxidase 4 (NOX4) has been proven to be associated with the prognosis of tumors in multiple cancers and can serve as a potential immunotherapy target to provide new treatment options for various tumors. In this study, our aim is to conduct an in-depth investigation of NOX4 across a range of cancer types to determine the relationship between NOX4 and tumors. Utilizing large-scale transcriptomic and clinical data from public databases, a systematic examination of NOX4 expression patterns was performed in pan-cancer cohorts. Survival analysis, methylation analysis, and correlation studies were employed to assess the diagnostic and prognostic significance of NOX4 in diverse cancer types. Additionally, an exploration of the relationship between NOX4 expression and immune infiltration across various tumors was conducted. The analyses unveiled a consistent upregulation of NOX4 expression in multiple cancer types relative to normal tissues, indicating its potential as a universal cancer biomarker. Elevated NOX4 expression significantly correlated with poor overall survival in several cancers. Furthermore, the study demonstrated a robust correlation between NOX4 expression and immune cell infiltration, signifying its involvement in the modulation of the tumor microenvironment. This study imparts valuable insights into the potential applications of NOX4 in cancer research, highlighting its significance as a multifaceted biomarker with diagnostic, prognostic, and immunomodulatory implications across diverse malignancies.

Unraveling the immunogenetic landscape of autism spectrum disorder: a comprehensive bioinformatics approach.

Autism spectrum disorder (ASD) is a disease characterized by social disorder. Recently, the population affected by ASD has gradually increased around the world. There are great difficulties in diagnosis and treatment at present. The ASD datasets were obtained from the Gene Expression Omnibus database and the immune-relevant genes were downloaded from a previously published compilation. Subsequently, we used WGCNA to screen the modules related to the ASD and immune. We also choose the best combination and screen out the core genes from Consensus Machine Learning Driven Signatures (CMLS). Subsequently, we evaluated the genetic correlation between immune cells and ASD used GNOVA. And pleiotropic regions identified by PLACO and CPASSOC between ASD and immune cells. FUMA was used to identify pleiotropic regions, and expression trait loci (EQTL) analysis was used to determine their expression in different tissues and cells. Finally, we use qPCR to detect the gene expression level of the core gene. We found a close relationship between neutrophils and ASD, and subsequently, CMLS identified a total of 47 potential candidate genes. Secondly, GNOVA showed a significant genetic correlation between neutrophils and ASD, and PLACO and CPASSOC identified a total of 14 pleiotropic regions. We annotated the 14 regions mentioned above and identified a total of 6 potential candidate genes. Through EQTL, we found that the CFLAR gene has a specific expression pattern in neutrophils, suggesting that it may serve as a potential biomarker for ASD and is closely related to its pathogenesis. In conclusion, our study yields unprecedented insights into the molecular and genetic heterogeneity of ASD through a comprehensive bioinformatics analysis. These valuable findings hold significant implications for tailoring personalized ASD therapies.

Genome-Wide Identification, Characterization, and Expression Profile of SWEETs Gene Family in Grapevine (Vitis vinifera L.)

SWEET (Sugars Will Eventually Be Exported Transporter) proteins, identified recently as a novel class of sugar transporters, play pivotal roles in the transport and distribution of photosynthetic products in plants. They are integral to physiological processes such as response to biotic and abiotic stress, growth and development, and fruit quality formation. In this study, leveraging the latest grapevine genomic data, we identified 18 members of the grapevine SWEET family and named them based on their homologs in Arabidopsis. We conducted a detailed analysis of these protein-encoding genes, focusing on their structure, conserved domains, and phylogenetic relationships. Phylogenetic analysis revealed that the grapevine SWEET family members could be categorized into four clades, with the majority of members displaying relatively conserved gene structures and motifs. Chromosomal localization and homology analysis indicated an uneven distribution of VvSWEETs across 11 chromosomes, with evidence of two segmental duplication events during evolution. Furthermore, we investigated the transcription levels of SWEET genes across different tissues, organs, and developmental stages of fruit, as well as their response patterns under abiotic stress (drought, cold, and salt stress) and biotic stress (Botrytis cinerea infection). Expression profiling demonstrated strong tissue-specificity and temporal-spatial specificity of VvSWEETs, correlated with their respective clades. It is noteworthy that the expression levels of most members within Clade 1 of the VvSWEET gene family, especially VvSWEET1, were markedly upregulated in response to a broad range of stress conditions. Our results provide a comprehensive bioinformatic characterization and analysis of the grapevine SWEET gene family, unveiling the potential functions of grapevine SWEET genes and offering a vital reference for further functional studies.

48 Next-generation sequencing with comprehensive bioinformatics analysis simplifies diagnosis of patients with hereditary angioedema

48 Next-generation sequencing with comprehensive bioinformatics analysis simplifies diagnosis of patients with hereditary angioedema

Trimethyl chitosan–cysteine-based nanoparticles as an effective delivery system for portulacerebroside A in the management of hepatocellular carcinoma cells in vitro and in vivo

Portulacerebroside A (PCA), a cerebroside compound extracted from Portulaca oleracea L., has been shown to suppress hepatocellular carcinoma (HCC) cells. This study aims to investigate the effectiveness of trimethyl chitosan–cysteine (TMC-Cys) nanocarrier in delivering PCA for HCC management and to elucidate the molecular mechanisms behind PCA’s function. TMC-Cys nanocarriers notably augmented PCA’s function, diminishing the proliferation, migration, and invasiveness of HCC cells in vitro, reducing hepatocellular tumorigenesis in immunocompetent mice, and impeding metastasis of xenograft tumours in nude mice. Comprehensive bioinformatics analyses, incorporating Super-PRED systems alongside pathway enrichment analysis, pinpointed toll-like receptor 4 (TLR4) and epidermal growth factor receptor (EGFR) as two promising targets of PCA, enriched in immune checkpoint pathway. PCA/nanocarrier (PCA) reduced levels of TLR4 and EGFR and their downstream proteins, including programmed cell death ligand 1, thereby increasing populations and activity of T cells co-cultured with HCC cells in vitro or in primary HCC tumours in mice. However, these effects were counteracted by additional artificial activation of TLR4 and EGFR. In conclusion, this study provides novel evidence of PCA’s function in immunomodulation in addition to its direct tumour suppressive effect. TMC-Cys nanocarriers significantly enhance PCA efficacy, indicating promising application as a drug delivery system.

Nucleic acid-sensing-related gene signature in predicting prognosis and treatment efficiency of small cell lung cancer patients.

Nucleic acid-sensing (NAS) pathways could induce innate and adaptive immune responses. However, rare evidence exhibited how the core genes of the NAS pathways affected the immune response and prognosis of small cell lung cancer (SCLC) patients. We conducted a comprehensive bioinformatic analysis based on the RNA profiles of 114 SCLC patients, including 79 from cBioPortal, 21 from GSE30219, and 14 from our sequencing data. The multiplex immunohistochemistry (mIHC) was used to characterize the role of NAS related genes in the tumor microenvironment (TME) of SCLC. A prognostic model (7NAS risk model) was constructed based on 7 NAS-related genes which was demonstrated as an independent prognostic index. The low-risk group was identified to have a better prognosis and an immune-activated microenvironment in both the public datasets and our dataset. Intriguingly, mIHC data showed that CD45+ immune cells, CD8+ T lymphocytes, and CD68+ macrophages were prevalently enriched in low-risk SCLC patients and positively correlated with IRF1 expression. Additionally, Patients in the low-risk group might have superior responses to chemotherapy and immunotherapy. Conclusively, this study created a new risk model based on genes associated with NAS pathways which could predict the prognosis and response of treatment in patients with SCLC.

Glutathione S-Transferase Genes Involved in Response to Short-Term Heat Stress in Tetranychus urticae (Koch).

Tetranychus urticae, a globally ubiquitous mite, poses a significant threat to agriculture. Elevated temperatures exacerbate the growth, development, and reproduction of T. urticae, leading to substantial crop damage. In this study, we employed comparative transcriptomic approaches with whole-genome information of T. urticae to identify six Glutathione S-transferase genes (GSTs) implicated in heat stress response. Through comprehensive bioinformatics analyses, we elucidated the tertiary structure and active sites of the corresponding proteins, providing a thorough characterization of these GST genes. Furthermore, we investigated the expression patterns of these six GST genes under short-term heat shock conditions. Our findings unveiled the involvement of T. urticae GST genes in combating oxidative stress induced by heat, underscoring their role in antioxidant defense mechanisms. This study contributes valuable insights into the molecular mechanisms underlying the response of T. urticae to heat stress, laying a foundation for the development of strategies aimed at mitigating its impact in high-temperature environments.

Comprehensive bioinformatics analysis unveils THEMIS2 as a carcinogenic indicator related to immune infiltration and prognosis of thyroid cancer.

The aim of this study was to identify biomarkers associated with the initiation and prognosis of thyroid cancer and elucidate the underlying pathogenic mechanisms. We obtained expression profiles and clinical information from the Cancer Genome Atlas (TCGA)-THCA and three datasets (GSE53157, GSE82208, and GSE76039). The three microarray datasets were combined using Perl and the sva package in R and termed 'merged dataset'. Weighted gene co-expression network analysis (WGCNA) identified 15 gene co-expression modules in the merged dataset and 235 hub genes. Venn diagram analysis revealed 232 overlapping genes between the merged and THCA datasets. Overlapping genes were subjected to gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The least absolute shrinkage and selection operator (LASSO) regression identified THEMIS2 as a candidate hub gene. Cox, Kaplan-Meier (K-M) survival and gene set enrichment analysis (GSEA) confirmed the correlation of THEMIS2 with overall survival, its enrichment in immunologic processes, and its association with the p53 and JAK-STAT signaling pathways. Its expression was positively correlated with those of immune checkpoints and the infiltration level of immune cells. Receiver operating characteristic curve (ROC) analysis confirmed that THEMIS2, a diagnostic biomarker, could distinguish between tumor and normal specimens. The nomogram (ROC or DCA) model containing THEMIS2, age, and stage predicted favourable prognoses. Thus, THEMIS2 was a biomarker of immune infiltration and prognosis in thyroid cancer.

Unlocking Overexpressed Membrane Proteins to Guide Breast Cancer Precision Medicine.

Breast cancer (BC) is a prevalent form of cancer affecting women worldwide. However, the effectiveness of current BC drugs is limited by issues such as systemic toxicity, drug resistance, and severe side effects. Consequently, there is an urgent need for new therapeutic targets and improved tumor tracking methods. This study aims to address these challenges by proposing a strategy for identifying membrane proteins in tumors that can be targeted for specific BC therapy and diagnosis. The strategy involves the analyses of gene expressions in breast tumor and non-tumor tissues and other healthy tissues by using comprehensive bioinformatics analysis from The Cancer Genome Atlas (TCGA), UALCAN, TNM Plot, and LinkedOmics. By employing this strategy, we identified four transcripts (LRRC15, EFNA3, TSPAN13, and CA12) that encoded membrane proteins with an increased expression in BC tissue compared to healthy tissue. These four transcripts also demonstrated high accuracy, specificity, and accuracy in identifying tumor samples, as confirmed by the ROC curve. Additionally, tissue microarray (TMA) analysis revealed increased expressions of the four proteins in tumor tissues across all molecular subtypes compared to the adjacent breast tissue. Moreover, the analysis of human interactome data demonstrated the important roles of these proteins in various cancer-related pathways. Taken together, these findings suggest that LRRC15, EFNA3, TSPAN13, and CA12 can serve as potential biomarkers for improving cancer diagnosis screening and as suitable targets for therapy with reduced side effects and enhanced efficacy.

Unraveling the molecular interplay of ferroptosis and immune regulation in stroke pathogenesis: A comprehensive bioinformatics analysis

Neurological disorders, particularly stroke, pose significant public health challenges, prompting a comprehensive investigation into the intricate interplay between ferroptosis and immune responses. This study aims to uncover the molecular mechanisms of stroke, emphasizing the connection between ferroptosis and immune regulation. Objectives include identifying differentially expressed genes in stroke patients, assessing immune cell subtype activation, employing advanced predictive modeling to pinpoint key candidate genes such as STMN1 and ATG16L1, exploring associations with immune cell subtypes, and revealing critical pathways, such as matrix degradation and inflammatory responses, activated in stroke through Gene Set Variation Analysis (GSVA). A comprehensive approach was adopted, involving differential gene expression analysis, functional enrichment analysis, weighted gene co-expression network analysis, Lasso regularization, random forest models, and the CIBERSORT (https://cibersortx.stanford.edu) algorithm, to assess immune cell subtypes. The study pinpointed genes with significant expression differences in stroke patients, highlighting the activation of Th17 cells and the NF-κ B signaling pathway. Key candidate genes, including STMN1 and ATG16L1, were identified using advanced predictive modeling. The relative abundance of immune cell subtypes, particularly natural killer cells (NK cells) and T cell subgroups, was associated with stroke through CIBERSORT. GSVA uncovered the activation of critical biological pathways such as matrix degradation and inflammatory responses. The analysis pinpointed STMN1 and ATG16L1 as robust predictors, emphasizing their potential as therapeutic targets. Th17 cells and the NF-κ B signaling pathway emerged as pivotal contributors to stroke pathogenesis. Notably, NK cells and specific T cell subgroups demonstrated significant associations with stroke. GSVA further illuminated the activation of key pathways, providing deeper insights into the biological processes underlying stroke. This study sheds light on crucial genes and pathways implicated in stroke, emphasizing the roles of ferroptosis and immune cell subtypes. The identified genes and pathways offer promising avenues for targeted therapeutic interventions in stroke, with a broader implication for advancing neurological disorder treatments through innovative perspectives on ferroptosis and immune regulation.

Identification of GMFG as a novel biomarker in IgA nephropathy based on comprehensive bioinformatics analysis

BackgroundIgA nephropathy (IgAN) stands as the most prevalent form of glomerulonephritis and ranks among the leading causes of end-stage renal disease worldwide. Regrettably, we continue to grapple with the absence of dependable diagnostic markers and specific therapeutic agents for IgAN. Therefore, this study endeavors to explore novel biomarkers and potential therapeutic targets in IgAN, while also considering their relevance in the context of tumors. MethodsWe gathered IgAN datasets from the Gene Expression Omnibus (GEO) database. Subsequently, leveraging these datasets, we conducted an array of analyses, encompassing differential gene expression, weighted gene co-expression network analysis (WGCNA), machine learning, receiver operator characteristic (ROC) curve analysis, gene expression validation, clinical correlations, and immune infiltration. Finally, we carried out pan-cancer analysis based on hub gene. ResultsWe obtained 1391 differentially expressed genes (DEGs) in GSE93798 and 783 DGEs in GSE14795, respectively. identifying 69 common genes for further investigation. Subsequently, GMFG was identified the hub gene based on machine learning. In the verification set and the training set, the GMFG was higher in the IgAN group than in the healthy group and all of the GMFG area under the curve (AUC) was more 0.8. In addition, GMFG has a close relationship with the prognosis of malignancies and a range of immune cells. ConclusionsOur study suggests that GMFG could serve as a promising novel biomarker and potential therapeutic target for both IgAN and certain types of tumors.

APAF1 Silencing Ameliorates Diabetic Retinopathy by Suppressing Inflammation, Oxidative Stress, and Caspase-3/GSDME-Dependent Pyroptosis.

Diabetic retinopathy (DR) can cause permanent blindness with unstated pathogenesis. We aim to find novel biomarkers and explore the mechanism of apoptotic protease activating factor 1 (APAF1) in DR. Differential expression genes (DEGs) were screened based on GSE60436 dataset to find hub genes involved in pyroptosis after comprehensive bioinformatics analysis. DR mice model was constructed by streptozotocin injection. The pathological structure of retina was observed using hematoxylin-eosin staining. The enzyme-linked immunosorbent assay was applied to assess inflammatory factors, vascular endothelial growth factor (VEGF), and oxidative stress. The mRNA and protein expression levels were detected using quantitative real-time polymerase-chain reaction and Western blot. Cell counting kit and flow cytometry were employed to detect proliferation and apoptosis in high glucose-induced ARPE-19 cells. Total 71 pyroptosis-related DEGs were screened. BIRC2, CXCL8, APAF1, PPARG, TP53, and CYCS were identified as hub genes of DR. APAF1 was selected as a potential regulator of DR, which was up-regulated in DR mice. APAF1 silencing alleviated retinopathy and inhibited pyroptosis in DR mice with decreased levels of inflammatory factors, VEGF, and oxidative stress. Moreover, APAF1 silencing promoted proliferation while inhibiting apoptosis and caspase-3/GSDME-dependent pyroptosis with a decrease in TNF-α, IL-1β, IL-18, and lactate dehydrogenase in high glucose-induced ARPE-19 cells. Additionally, caspase-3 activator reversed the promotion effect on proliferation and inhibitory effect on apoptosis and pyroptosis after APAF1 silencing in high glucose-induced ARPE-19 cells. APAF1 is a novel biomarker for DR and APAF1 silencing inhibits the development of DR by suppressing caspase-3/GSDME-dependent pyroptosis.

A Novel Nucleic Acid Sensing-related Genes Signature for Predicting Immunotherapy Efficacy and Prognosis of Lung Adenocarcinoma.

As a novel pillar for lung adenocarcinoma (LUAD) treatment, immunotherapy has limited efficiency in LUAD patients. The nucleic acid sensing (NAS) pathways are critical in the anti-tumor immune response, but their role in LUAD remains controversial. The study aims to develop a classification system to identify immune subtypes of LUAD based on nucleic acid sensing-related genes so that it can help screen patients who may respond to immunotherapy. We performed a comprehensive bioinformatics analysis of the NAS molecule expression profiles across multiple public datasets. Using qRT-PCR to verify the NAS genes in multiple lung cancer cell lines. Molecular docking was performed to screen drug candidates. The NAS-activated subgroup and NAS-suppressed subgroup were validated based on the different patterns of gene expression and pathways enrichment. The NAS-activated subgroup displayed a stronger immune infiltration and better prognosis of patients. Moreover, we constructed a seven nucleic acid sensing-related risk score (NASRS) model for the convenience of clinical application. The predictive values of NASRS in prognosis and immunotherapy were subsequently fully validated in the lung adenocarcinoma dataset and the uroepithelial carcinoma dataset. Additionally, five potential drugs binding to the core target of the NAS signature were predicted through molecular docking. We found a significant correlation between nucleic acid sensing function and the immune treatment efficiency in LUAD. The NASRS can be used as a robust biomarker for the predicting of prognosis and immunotherapy efficiency and may help in clinical decisions for LUAD patients.

Comprehensive bioinformatics analysis of KIF20A as a prognosis biomarker for clear cell renal cell carcinoma.

It has been shown that kinesin family member 20A (KIF20A) is involved in the development of several cancers. However, research on clear cell renal cell carcinoma (ccRCC) and KIF20A is still exploratory. The current research was carried out to determine whether KIF20A expression has any prognosis value in ccRCC. Data were downloaded from The Cancer Genome Atlas (TCGA) database to validate the KIF20A mRNA expression and to perform clinicopathological analysis. Receiver operating characteristic (ROC) curves were used in evaluating KIF20A's diagnostic performance for ccRCC. The prognostic value of KIF20A in ccRCC was estimated by the Kaplan-Meier survival curve and Cox regression analysis. Gene set enrichment analysis (GSEA), functional annotations, and immune infiltration analysis were used to determine the potential mechanism of KIF20A's role in ccRCC. The increase in KIF20A mRNA expression was associated with sex, clinical stage, histologic grade, and TNM stage. ROC curve indicated that KIF20A could distinguish ccRCC from normal kidney samples. Survival study showed that high KIF20A expression predicted poor ccRCC prognosis. Thus, KIF20A expression could be used as an independent overall survival (OS) risk factor for ccRCC patients. Co-expression analysis identified TPX2 as a strong, positively correlated factor with KIF20A in ccRCC. Functional enrichment analyses and GSEA showed that KIF20A and TPX2 participated in various tumor-related pathways. Moreover, KIF20A and TPX2 expression were significantly associated with the level of immune infiltration into ccRCC. KIF20A may be a therapeutic target and a prognostic biomarker for ccRCC.

Network Pharmacology and Molecular Docking Technology-based Strategy to Explore the Potential Mechanism of Diabecon Formulation Botanicals

This study presents network pharmacology and a molecular docking-centered approach to elucidate the possible mechanism of action underlying the therapeutic effects of diabecon, a formulation containing Gymnema sylvestre, Pterocarpus marsupium, and Asphaltum punjabinum botanicals. Through comprehensive bioinformatics analysis, a collection of bioactive compounds present in these botanicals was identified, and their potential targets were forecasted using Swiss Target Prediction and STITCH. Disease-related genes were retrieved from Genecards and OMIM, and common genes between potential targets and disease-related genes were determined. Pathway analysis using the DAVID database revealed significant enrichment in pathways related to metabolic processes, xenobiotic metabolism, and signaling pathways, such as the insulin signaling pathway and pathways in cancer. Network construction using cytoscape highlighted interactions among identified genes, providing insights into the molecular pathways modulated by diabecon. Molecular docking analysis further elucidated the possible connections amongst biologically active compounds and target proteins, with (2S)-7-hydroxyflavanone exhibiting strong binding affinity with DPP-IV enzyme. Overall, this integrated approach offers valuable insights into the potential mechanisms of action of diabecon, contributing to our understanding of its therapeutic effects in the management of diabetes mellitus

Abstract 1525: Integration of high-plex tumor-Immune phenotyping and checkpoint interactions for deeper spatial characterization of human cancer tissues

Abstract Background: Immune evasion is a key cancer hallmark, and one of the primary mechanisms is the PD-1/PD-L1 checkpoint axis. While immunotherapies that target these interactions have reshaped cancer treatment, the variable efficacy in patients is not fully understood. Due to the weak correlation between PD-1/PD-L1 expression measured by single-plex assays and observed clinical outcomes, there is a need to understand protein interactions at the cellular and subcellular level. Proximity Ligation Assays, detecting spatial interactions between ligand-receptor targets, provide insights into the activation of signaling pathways. Coupled with high-plex spatial phenotyping with tumor and immune profiling biomarkers, the integration of cellular and functional information will be beneficial for a deeper characterization of the tumor microenvironment (TME), understanding immune responses, and identifying spatial signatures for patient stratification and targeted treatment strategies. Methods: In this study, we phenotyped biopsies from head and neck cancer patients enrolled in immune checkpoint inhibitor therapies. We integrated Naveni® PD-1/PD-L1 proximity ligation assays and a customizable high-plex PhenoCode™ Signature Panel (CD3ε/CD8/CD20/CD68/PanCK) for high-throughput profiling of the TME utilizing the PhenoImager® HT 2.0 platform. Comprehensive bioinformatic analyses were conducted for whole-slide segmentation, identifying cellular phenotypes, spatial neighborhoods, functional interactions, and distinct spatial signatures via the open-source image analysis software QuPath. Results: Our analyses revealed key differences in the localization of the PD-1/PD-L1 interactions within the TME of head and neck cancers. Areas of PD-1/PD-L1 interactions are associated with immune cell types on the periphery of the tumor and some within the tumor-infiltrating lymphocytes. The PhenoCode Signature panels helped resolve the localization of PD-1/PD-L1 interactions to immune cell types within the TME and provided a dual workflow for spatial co-localization of interacting receptor/ligand interactions and cell phenotypes within the TME. Conclusions: By combining spatial immune profiling with Akoya’s PhenoCode Signature panels and protein-protein interaction data from Navinci’s Naveni® PD-1/PD-L1 assay, deep correlative insights of the TME can be applied to improve predictions of clinical outcomes. This innovative approach enriches our comprehension of underlying mechanisms and stands as a promising tool for refining patient selection and optimizing treatment outcomes in immunotherapy. Citation Format: Sara Bodbin, Ning Ma, Aditya Pratapa, Nadya Nikulina, James Monkman, Niyati Jhaveri, Hampus Elofsson, Subham Basu, Agata Zieba-Wicher, Arutha Kulasinghe. Integration of high-plex tumor-Immune phenotyping and checkpoint interactions for deeper spatial characterization of human cancer tissues [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 1525.

Studying Salt-Induced Shifts in Gene Expression Patterns of Glucosinolate Transporters and Glucosinolate Accumulation in Two Contrasting Brassica Species.

Brassica crops are well known for the accumulation of glucosinolates-secondary metabolites crucial for plants' adaptation to various stresses. Glucosinolates also functioning as defence compounds pose challenges to food quality due to their goitrogenic properties. Their disruption leaves plants susceptible to insect pests and diseases. Hence, a targeted reduction in seed glucosinolate content is of paramount importance to increase food acceptance. GLUCOSINOLATE TRANSPORTERS (GTRs) present a promising avenue for selectively reducing glucosinolate concentrations in seeds while preserving biosynthesis elsewhere. In this study, 54 putative GTR protein sequences found in Brassica were retrieved, employing Arabidopsis GTR1 and GTR2 templates. Comprehensive bioinformatics analyses, encompassing gene structure organization, domain analysis, motif assessments, promoter analysis, and cis-regulatory elements, affirmed the existence of transporter domains and stress-related regulatory elements. Phylogenetic analysis revealed patterns of conservation and divergence across species. Glucosinolates have been shown to increase under stress conditions, indicating a potential role in stress response. To elucidate the role of GTRs in glucosinolate transportation under NaCl stress in two distinct Brassica species, B. juncea and B. napus, plants were subjected to 0, 100, or 200 mM NaCl. Based on the literature, key GTR genes were chosen and their expression across various plant parts was assessed. Both species displayed divergent trends in their biochemical profiles as well as glucosinolate contents under elevated salt stress conditions. Statistical modelling identified significant contributors to glucosinolate variations, guiding the development of targeted breeding strategies for low-glucosinolate varieties. Notably, GTR2A2 exhibited pronounced expressions in stems, contributing approximately 52% to glucosinolate content variance, while GTR2B1/C2 displayed significant expression in flowers. Additionally, GTR2A1 and GTR1A2/B1 demonstrated noteworthy expression in roots. This study enhances our understanding of glucosinolate regulation under stress conditions, offering avenues to improve Brassica crop quality and resilience.