Bioinformatics Databases Research Articles

Abstract 290: The role of tumor stromal topography-regulated genes in modulating the cellular landscape of tumor stroma in breast cancer

Abstract The tumor remodels the surrounding extracellular matrix fibers to become topographically aligned at the tumor front, further facilitating cancer cell migration. Our recent studies show that aligned tumor stromal topography promotes the detachment of breast cancer cells from the main tumor, then, in the following cell migration, upregulating genes such as genes encoding the cytochrome P450 family 1 subfamily A member 1 (CYP1) and inhibitor of DNA binding (ID) proteins. In this study, we further explored the role of topography-regulated genes in modulating the cellular landscape of tumor stroma. By analyzing the correlation of topography-regulated genes with stromal cell infiltration in bioinformatics databases, we found significant positive correlations between the RNA expression levels of most topography-regulated genes and the infiltration levels of cancer-associated fibroblasts and endothelial cells. Notably, the strongest correlation was between the expression level of ID3 and the infiltration levels of cancer-associated fibroblasts (r = 0.509) and endothelial cells (r = 0.506). Additionally, ID3 remained highly expressed in circulating tumor cells but exhibited low expression at distant metastatic sites. These findings suggest that genes regulated by tumor stromal topography, especially ID3, may play a role in neovascularization and fibrosis of the tumor microenvironment and the survival adaptation of cancer cells in circulation, thereby promoting metastasis. Citation Format: Chia-Yi Su. The role of tumor stromal topography-regulated genes in modulating the cellular landscape of tumor stroma in breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 290.

Identify CTBP1-DT as an immunological biomarker that promotes lipid synthesis and apoptosis resistance in KIRC

Recently, mounting evidence has highlighted the essential function of the C-terminal binding protein-1 divergent transcript (CTBP1-DT) in malignancies. However, its role in kidney renal clear cell carcinoma (KIRC) remains largely unknown. Our study aimed to identify the potential function of CTBP1-DT in KIRC. RT-qPCR, Kaplan-Meier survival analysis, Cox regression analysis, and nomogram analysis were utilized to determine the expression and effects of CTBP1-DT on survival. The subcellular localization of CTBP1-DT was determined using RNA fluorescence in situ hybridization (FISH). To investigate the functions of CTBP1-DT in regulating KIRC cell proliferation, migration, invasion, lipid synthesis, and apoptosis, we conducted CCK8, EdU, Transwell, and Oil Red O staining and cell apoptosis staining assays. The relationships between CTBP1-DT and the tumor microenvironment were investigated with multiple bioinformatics analysis algorithms and databases, including CYBERSORT, TIMER2, Spearman correlation test, tumor mutation burden (TMB), microsatellite instability (MSI), and immunophenoscore (IPS). According to our results, CTBP1-DT is a lncRNA located in the nucleus that is significantly upregulated in KIRC and is correlated with better clinical outcomes. Downregulating CTBP1-DT inhibited cell viability, migration, invasion, and lipid synthesis but triggered cell apoptosis. Additionally, we explored the potential effect of CTBP1-DT in regulating immune cell infiltration in KIRC and other malignancies. Furthermore, CTBP1-DT could be used to predict the effectiveness of targeted drugs and immune checkpoint inhibitors. In conclusion, we identified CTBP1-DT as a potential immunological biomarker and discovered the potential role of CTBP1-DT in regulating lipid synthesis and apoptosis resistance.

Contigs directed gene annotation (ConDiGA) for accurate protein sequence database construction in metaproteomics

BackgroundMicrobiota are closely associated with human health and disease. Metaproteomics can provide a direct means to identify microbial proteins in microbiota for compositional and functional characterization. However, in-depth and accurate metaproteomics is still limited due to the extreme complexity and high diversity of microbiota samples. It is generally recommended to use metagenomic data from the same samples to construct the protein sequence database for metaproteomic data analysis. Although different metagenomics-based database construction strategies have been developed, an optimization of gene taxonomic annotation has not been reported, which, however, is extremely important for accurate metaproteomic analysis.ResultsHerein, we proposed an accurate taxonomic annotation pipeline for genes from metagenomic data, namely contigs directed gene annotation (ConDiGA), and used the method to build a protein sequence database for metaproteomic analysis. We compared our pipeline (ConDiGA or MD3) with two other popular annotation pipelines (MD1 and MD2). In MD1, genes were directly annotated against the whole bacterial genome database; in MD2, contigs were annotated against the whole bacterial genome database and the taxonomic information of contigs was assigned to the genes; in MD3, the most confident species from the contigs annotation results were taken as reference to annotate genes. Annotation tools, including BLAST, Kaiju, and Kraken2, were compared. Based on a synthetic microbial community of 12 species, it was found that Kaiju with the MD3 pipeline outperformed the others in the construction of protein sequence database from metagenomic data. Similar performance was also observed with a fecal sample, as well as in silico mixed datasets of the simulated microbial community and the fecal sample.ConclusionsOverall, we developed an optimized pipeline for gene taxonomic annotation to construct protein sequence databases. Our study can tackle the current taxonomic annotation reliability problem in metagenomics-derived protein sequence database and can promote the in-depth metaproteomic analysis of microbiome. The unique metagenomic and metaproteomic datasets of the 12 bacterial species are publicly available as a standard benchmarking sample for evaluating various analysis pipelines. The code of ConDiGA is open access at GitHub for the analysis of microbiota samples.6yn7yKvS5c7jYK96vohJFUVideo

ThermoPCD: a database of molecular dynamics trajectories of antibody-antigen complexes at physiologic and fever-range temperatures.

Progression of various cancers and autoimmune diseases is associated with changes in systemic or local tissue temperatures, which may impact current therapies. The role of fever and acute inflammation-range temperatures on the stability and activity of antibodies relevant for cancers and autoimmunity is unknown. To produce molecular dynamics (MD) trajectories of immune complexes at relevant temperatures, we used the Research Collaboratory for Structural Bioinformatics (RCSB) database to identify 50 antibody:antigen complexes of interest, in addition to single antibodies and antigens, and deployed Groningen Machine for Chemical Simulations (GROMACS) to prepare and run the structures at different temperatures for 100-500ns, in single or multiple random seeds. MD trajectories are freely available. Processed data include Protein Data Bank outputs for all files obtained every 50ns, and free binding energy calculations for some of the immune complexes. Protocols for using the data are also available. Individual datasets contain unique DOIs. We created a web interface, ThermoPCD, as a platform to explore the data. The outputs of ThermoPCD allow the users to relate thermally-dependent changes in epitopes:paratopes interfaces to their free binding energies, or against own experimentally derived binding affinities. ThermoPCD is a free to use database of immune complexes' trajectories at different temperatures that does not require registration and allows for all the data to be available for download. Database URL: https://sites.google.com/view/thermopcd/home.

Landscape of FLT3 Variations Associated with Structural and Functional Impact on Acute Myeloid Leukemia: A Computational Study.

Acute myeloid leukemia (AML) is hallmarked by the clonal proliferation of myeloid blasts. Mutations that result in the constitutive activation of the fms-like tyrosine kinase 3 (FLT3) gene, coding for a class III receptor tyrosine kinase, are significantly associated with this heterogeneous hematologic malignancy. The fms-related tyrosine kinase 3 ligand binds to the extracellular domain of the FLT3 receptor, inducing homodimer formation in the plasma membrane, leading to autophosphorylation and activation of apoptosis, proliferation, and differentiation of hematopoietic cells in bone marrow. In the present study, we evaluated the association of FLT3 as a significant biomarker for AML and tried to comprehend the effects of specific variations on the FLT3 protein's structure and function. We also examined the effects of I836 variants on binding affinity to sorafenib using molecular docking. We integrated multiple bioinformatics tools, databases, and resources such as OncoDB, UniProt, COSMIC, UALCAN, PyMOL, ProSA, Missense3D, InterProScan, SIFT, PolyPhen, and PredictSNP to annotate the structural, functional, and phenotypic impact of the known variations associated with FLT3. Twenty-nine FLT3 variants were analyzed using in silico approaches such as DynaMut, CUPSAT, AutoDock, and Discovery Studio for their impact on protein stability, flexibility, function, and binding affinity. The OncoDB and UALCAN portals confirmed the association of FLT3 gene expression and its mutational status with AML. A computational structural analysis of the deleterious variants of FLT3 revealed I863F mutants as destabilizers of the protein structure, possibly leading to functional changes. Many single-nucleotide variations in FLT3 have an impact on its structure and function. Thus, the annotation of FLT3 SNVs and the prediction of their deleterious pathogenic impact will facilitate an insight into the tumorigenesis process and guide experimental studies and clinical implications.

Ten common issues with reference sequence databases and how to mitigate them.

Metagenomic sequencing has revolutionized our understanding of microbiology. While metagenomic tools and approaches have been extensively evaluated and benchmarked, far less attention has been given to the reference sequence database used in metagenomic classification. Issues with reference sequence databases are pervasive. Database contamination is the most recognized issue in the literature; however, it remains relatively unmitigated in most analyses. Other common issues with reference sequence databases include taxonomic errors, inappropriate inclusion and exclusion criteria, and sequence content errors. This review covers ten common issues with reference sequence databases and the potential downstream consequences of these issues. Mitigation measures are discussed for each issue, including bioinformatic tools and database curation strategies. Together, these strategies present a path towards more accurate, reproducible and translatable metagenomic sequencing.

HELLS Knockdown Inhibits the Malignant Progression of Lung Adenocarcinoma Via Blocking Akt/CREB Pathway by Downregulating KIF11.

Lung adenocarcinoma (LUAD) is a malignant tumor with the characteristics of progressive advancement and high mortality rate worldwide. We aimed to explore the role and mechanism of helicase Lymphoid-Specific (HELLS) in LUAD. Bioinformatics databases were applied to predict HELLS and kinesin family member (KIF)11 expression in LUAD tissues. The expressions of HELLS and KIF11 before and after HELLS knockdown were detected by RT-qPCR and western blot. After HELLS was knocked down, the proliferative, migratory, and invasive capabilities of A549 cells were evaluated. Cell apoptotic level was assessed using TUNEL. Western blot was employed to evaluate the expressions of Akt/CREB pathway-related proteins. The interaction between HELLS and KIF11 was analyzed using bioinformatics databases, and testified by Co-IP assay. Results revealed that HELLS and KIF11 expressions were significantly upregulated in LUAD cells and tissues. High HELLS and KIF11 expression was correlated with the poor prognosis of patients with LUAD. Additionally, HELLS knockdown suppressed the capabilities of LUAD cells to proliferate, migrate, and invade whereas promoted the cell apoptotic level. Moreover, HELLS could interact with KIF11 and had positive correlation with KIF11. Furthermore, KIF11 overexpression partially counteracted the impacts of HELLS knockdown on cell proliferative, migratory, invasive capabilities, and apoptotic level in LUAD cells. Besides, Akt/CREB pathway was blocked by HELLS silencing, which was restored by KIF11 overexpression. Collectively, HELLS knockdown blocked Akt/CREB pathway by downregulating KIF11 expression, thereby inhibiting LUAD cell proliferation, invasion, migration, and promoting apoptosis.

Hypoxia-induced circRNAs encoded by PPARA are highly expressed in human cardiomyocytes and are potential clinical biomarkers of acute myocardial infarction

BackgroundAcute myocardial infarction (AMI) is a serious cardiovascular disease that adversely affects human health. Circular RNAs (circRNAs) are involved in the pathological and physiological processes of AMI, but the biological mechanism of their involvement and their clinical significance remain unknown. We aimed to identify circRNAs that are significantly associated with morbidity in the peripheral blood of patients with AMI and evaluate their diagnostic utility.MethodsHigh-throughput sequencing was used to screen for differentially expressed circRNAs in peripheral blood samples obtained from five patients with AMI and five sex- and age-matched healthy controls. A series of bioinformatics tools and databases were used to determine the biological functional classification and pathway enrichment of the circRNAs based on data obtained from sequencing. A hypoxia model was established and used to evaluate the effect of hypoxia on circRNA expression in human cardiomyocytes. A cytoplasmic separation assay and enzyme resistance assay were employed to identify the biological characteristics of circRNA. Polymerase chain reaction validity testing and receiver operating characteristic (ROC) curve analysis were used to evaluate the utility of circRNA assessments in the diagnosis of AMI.ResultsA large number of circRNAs were found to be differentially expressed in the peripheral blood of patients with AMI, and significantly more of these circRNAs were highly expressed than lowly expressed. The genes encoding these circRNAs have a wide range of effects on various functions in the body. A hypoxic environment promoted the upregulation of circRNA expression in human cardiomyocytes, and hsa_circ_0116795 encoded by PPARA was highly expressed in the peripheral blood of the patients with AMI. In terms of biological characteristics, under physiological conditions, hsa_circ_0116795 (circ_PPARA) was mainly located in the cytoplasm of cardiomyocytes and found to be resistant to exonuclease. The ROC curve analysis showed that the expression levels of circ_PPARA in the peripheral blood of patients with AMI were significantly different from those in the peripheral blood of healthy controls.ConclusionA large number of abnormally expressed circRNAs are detectable in the peripheral blood of patients with AMI. In particular, circ_PPARA is highly expressed in human myocardial cells under hypoxic conditions, and its biological characteristics indicate that it could be employed as a biomarker for the early diagnosis of AMI.

The lncRNA lnc_AABR07044470.1 promotes the mitochondrial-damaged inflammatory response to neuronal injury via miR-214-3p/PERM1 axis in acute ischemic stroke

PurposeWe investigated the role of lnc_AABR07044470.1 on the occurrence and development of acute ischemic stroke (AIS) and neuronal injury by targeting the miR-214-3p/PERM1 axis to find a novel clinical drug target and prediction and treatment of AIS.MethodsThe mouse AIS animal model was used in vivo experiments and hypoxia/reoxygenation cell model in vitro was established. Firstly, infarction volume and pathological changes of mouse hippocampal neurons were detected using HE staining. Secondly, rat primary neuron apoptosis was detected by flow cytometry assay. The numbers of neuron, microglia and astrocytes were detected using immunofluorescence (IF). Furthermore, binding detection was performed by bioinformatics database and double luciferase reporter assay. Lnc_AABR07044470.1 localization was performed using fluorescence in situ hybridization (FISH).Lnc_AABR07044470.1, miR-214-3pand PERM1mRNA expression was performed using RT-qPCR. NLRP3, ASC, Caspase-1 and PERM1 protein expression was performed using Western blotting. IL-1β was detected by ELISA assay.ResultsMouse four-vessel occlusion could easily establish the animal model, and AIS animal model had an obvious time-dependence. HE staining showed that, compared with the sham group, infarction volume and pathological changes of mouse hippocampal neurons were deteriorated in the model group. Furthermore, compared with the sham group, neurons were significantly reduced, while microglia and astrocytes were significantly activated. Moreover, the bioinformatics prediction and detection of double luciferase reporter confirmed the binding site of lnc_AABR07044470.1 to miR-214-3p and miR-214-3p to Perm1. lnc_AABR07044470.1 and PERM1 expression was significantly down-regulated and miR-214-3pexpression was significantly up-regulated in AIS animal model in vivo. At the same time, the expression of inflammasome NLRP3, ASC, Caspase-1 and pro-inflammatory factor IL-1β was significantly up-regulated in vivo and in vitro. The over-expression of lnc_AABR07044470.1 and miR-214-3p inhibitor could inhibit the neuron apoptosis and the expression of inflammasome NLRP3, ASC, Caspase-1 and pro-inflammatory factor IL-1β and up-regulate the expression of PERM1 in vitro. Finally, over-expression of lnc_AABR07044470.1 and miR-214-3p inhibitor transfected cell model was significant in relieving the AIS and neuronal injury.ConclusionLnc_AABR07044470.1 promotes inflammatory response to neuronal injury via miR-214-3p/PERM1 axis in AIS.

Integration of genomic and transcriptomic data of inbred mouse models for polygenic obesity and leanness revealed “obese” and “lean” candidate alleles in polyadenylation signals

Most mammalian genes have multiple polyadenylation (PA) sites, and alternative polyadenylation (APA) has been linked to diseases such as obesity. Studies have shown that changes in the polyadenylation signal (PAS) can influence the efficiency of cleavage and affect disease susceptibility and phenotype. In our recent study we used inbred mouse models of polygenic obesity and leanness and identified single-nucleotide polymorphisms in PAS (PAS-SNPs) within several obesity candidate genes, including five with differential expression. Nevertheless, to date, there has been no systematic, whole-genome-level approach aiming to prioritise PAS-SNPs potentially affecting APA. Therefore, in this study, we build upon our previous work by integrating existing genomics data with transcriptomics. DEGs were identified in nine tissues by Affymetrix GeneChip. PA and PAS sites were from the PolyASite 2.0 portal. Prioritisation of candidate PAS-SNPs was performed based on whether they were located in DEG, the type of PAS changes they caused, locations of PA sites relative to PAS, and location(s) and expression(s) of Affymetrix probes within a given gene in various tissues. For the candidates, potential consequences due to the alteration in APA events were investigated using bioinformatics databases and tools. The analysis found 127 PAS-SNPs in 101 DEGs across different tissues and identified 12 high-priority and 7 moderate-priority PAS-SNP candidates in 10 and 7 DEGs, respectively. Candidate PAS-SNPs were in 3′ UTR of 12 protein-coding genes (Lean line: Edil3, Eif2s1, Fbxl3, Hlf, Hsf2bp, Knop1, Lair1, Nmrk1; Fat line: Ehd1, Rpl14, Spon1, Txndc9), introns of four protein-coding genes (Lean line: Abi3bp, Prr16; Fat line: Agmo, Itga7) and intron of one lncRNA (Lean line: 1700086O06Rik). The integration of whole-genome sequencing and transcriptome analyses in this study has identified potential genome-wide candidate SNPs that could affect APA by altering/disrupting PAS motifs and be related to obesity in mice. The data provides a foundation for further research into these PAS-SNPs, their genes, and their contribution to the obesity/leanness phenotype, and contributes a part in explaining missing heritability commonly observed in complex traits.

The astounding exhaustiveness and speed of the Astral mass analyzer for highly complex samples is a quantum leap in the functional analysis of microbiomes

BackgroundBy analyzing the proteins which are the workhorses of biological systems, metaproteomics allows us to list the taxa present in any microbiota, monitor their relative biomass, and characterize the functioning of complex biological systems.ResultsHere, we present a new strategy for rapidly determining the microbial community structure of a given sample and designing a customized protein sequence database to optimally exploit extensive tandem mass spectrometry data. This approach leverages the capabilities of the first generation of Quadrupole Orbitrap mass spectrometer incorporating an asymmetric track lossless (Astral) analyzer, offering rapid MS/MS scan speed and sensitivity. We took advantage of data-dependent acquisition and data-independent acquisition strategies using a peptide extract from a human fecal sample spiked with precise amounts of peptides from two reference bacteria.ConclusionsOur approach, which combines both acquisition methods, proves to be time-efficient while processing extensive generic databases and massive datasets, achieving a coverage of more than 122,000 unique peptides and 38,000 protein groups within a 30-min DIA run. This marks a significant departure from current state-of-the-art metaproteomics methodologies, resulting in broader coverage of the metabolic pathways governing the biological system. In combination, our strategy and the Astral mass analyzer represent a quantum leap in the functional analysis of microbiomes.DtQfodvXmxPWcwvjCbxEj1Video

STK3 kinase activation inhibits tumor proliferation through FOXO1-TP53INP1/P21 pathway in esophageal squamous cell carcinoma

PurposeEsophageal squamous cell carcinoma (ESCC) is an aggressive disease with a poor prognosis, caused by the inactivation of critical cell growth regulators that lead to uncontrolled proliferation and increased malignancy. Although Serine/Threonine Kinase 3 (STK3), also known as Mammalian STE20-like protein kinase 2 (MST2), is a highly conserved kinase of the Hippo pathway, plays a critical role in immunomodulation, organ development, cellular differentiation, and cancer suppression, its phenotype and function in ESCC require further investigation. In this study, we report for the first time on the role of STK3 kinase and its activation condition in ESCC, as well as the mechanism and mediators of kinase activation.MethodsIn this study, we investigated the expression and clinical significance of STK3 in ESCC. We first used bioinformatics databases and immunohistochemistry to analyze STK3 expression in the ESCC patient cohort and conducted survival analysis. In vivo, we conducted a tumorigenicity assay using nude mouse models to demonstrate the phenotypes of STK3 kinase. In vitro, we conducted Western blot analysis, qPCR analysis, CO-IP, and immunofluorescence (IF) staining analysis to detect molecule expression, interaction, and distribution. We measured proliferation, migration, and apoptosis abilities in ESCC cells in the experimental groups using CCK-8 and transwell assays, flow cytometry, and EdU staining. We used RNA-seq to identify genes that were differentially expressed in ESCC cells with silenced STK3 or FOXO1. We demonstrated the regulatory relationship of the TP53INP1/P21 gene medicated by the STK3-FOXO1 axis using Western blotting and ChIP in vitro.ResultsWe demonstrate high STK3 expression in ESCC tissue and cell lines compared to esophageal epithelium. Cellular ROS induces STK3 autophosphorylation in ESCC cells, resulting in upregulated p-STK3/4. STK3 activation inhibits ESCC cell proliferation and migration by triggering apoptosis and suppressing the cell cycle. STK3 kinase activation phosphorylates FOXO1Ser212, promoting nuclear translocation, enhancing transcriptional activity, and upregulating TP53INP1 and P21. We also investigated TP53INP1 and P21’s phenotypic effects in ESCC, finding that their knockdown significantly increases tumor proliferation, highlighting their crucial role in ESCC tumorigenesis.ConclusionSTK3 kinase has a high expression level in ESCC and can be activated by cellular ROS, inhibiting cell proliferation and migration. Additionally, STK3 activation-mediated FOXO1 regulates ESCC cell apoptosis and cell cycle arrest by targeting TP53INP1/P21. Our research underscores the anti-tumor function of STK3 in ESCC and elucidates the mechanism underlying its anti-tumor effect on ESCC.

Comprehensive analysis of ADGRE5 gene in human tumors: Clinical relevance, prognostic implications, and potential for personalized immunotherapy

PurposeThe Adhesion G protein receptor E5 (ADGRE5) gene is involved in a wide range of biological functions in human tumors; however, its specific molecular mechanism and significance in the analysis of human tumors have not yet been determined. Here, we provide a comprehensive genomic architecture of ADGRE5 in the tumor immune microenvironment and its clinical relevance across a broad range of solid tumors. MethodsIn this study, we used publicly available bioinformatics databases, with a primary focus on The Cancer Genome Atlas (TCGA) database and GTEx data, to conduct a comprehensive analysis of the impact on patient prognosis associated with ADGRE5. ResultsStatistics of more than 30 solid tumors from TCGA and Cancer Cell Line Encyclopedia (CCLE) were examined. ADGRE5 was differentially expressed in several cancers and was significantly associated with survival outcomes. Higher ADGRE5 levels were associated with worse prognosis in adrenocortical carcinoma, low grade glioma of the brain (LGG), lung squamous cell carcinoma, liver hepatocellular carcinoma, and uveal melanoma (UVM). Additionally, ADGRE5 was found to be an independent risk factor for LGG and UVM. The clinical relevance of ADGRE5 in tumor immunogenicity was further investigated. The expression level of ADGRE5 was not only strongly associated with tumor infiltration, such as tumor-infiltrating immune cells and immune subtypes, but also with tumor mutation burden, pyroptosis, and epithelial-mesenchymal transition in various types of cancer (P < 0.05). Furthermore, we noted that ADGRE5 exhibited a positive association with targeted drug sensitivity and conversely, a negative association with traditional chemotherapeutic drug sensitivity. Thus, ADGRE5 is expected to be a guiding marker gene for clinical prognosis and personalized tumor immunotherapy.

MARS and RNAcmap3: The Master Database of All Possible RNA Sequences Integrated with RNAcmap for RNA Homology Search.

Recent success of AlphaFold2 in protein structure prediction relied heavily on co-evolutionary information derived from homologous protein sequences found in the huge, integrated database of protein sequences (Big Fantastic Database). In contrast, the existing nucleotide databases were not consolidated to facilitate wider and deeper homology search. Here, we built a comprehensive database by incorporating the non-coding RNA (ncRNA) sequences from RNAcentral, the transcriptome assembly and metagenome assembly from metagenomics RAST (MG-RAST), the genomic sequences from Genome Warehouse (GWH), and the genomic sequences from MGnify, in addition to the nucleotide (nt) database and its subsets in National Center of Biotechnology Information (NCBI). The resulting Master database of All possible RNA sequences (MARS) is 20-fold larger than NCBI's nt database or 60-fold larger than RNAcentral. The new dataset along with a new split-search strategy allows a substantial improvement in homology search over existing state-of-the-art techniques. It also yields more accurate and more sensitive multiple sequence alignments (MSAs) than manually curated MSAs from Rfam for the majority of structured RNAs mapped to Rfam. The results indicate that MARS coupled with the fully automatic homology search tool RNAcmap will be useful for improved structural and functional inference of ncRNAs and RNA language models based on MSAs. MARS is accessible at https://ngdc.cncb.ac.cn/omix/release/OMIX003037, and RNAcmap3 is accessible at http://zhouyq-lab.szbl.ac.cn/download/.

Gene Biomarkers in Congenital Hyperinsulinism

Congenital hyperinsulinism (CHI) is a rare type of disease that causes a severe drop in blood sugar in infants. This diseaseprevents reaching enough sugar to the child’s brain and causes lifelong and permanent damage. This study aims to investigate genebiomarkers in congenital hyperinsulinism. In this study, after reviewing the texts and searching for the bioinformatics databases of NCBI,Genecards, Swiss-prot, Diseasome, etc., the genes involved in the disease based on at least one of the methods in-vivo, in-vitro, and insilicohas been extracted as candidate genes. The expression data obtained from each group was standardized compared to the controlgroup to compare the results in case and control groups. Then, the connection network of expression data of candidate genes in patientsand healthy people were drawn separately with the help of MATLAB software (Version 9.1), and the correctness of these networks anddetermined biomarkers were checked using the rectome and diseasome database. All statistical calculations were done using R and Matlabsoftware. In the present study, the essential genes of CHI disease were identified using 5 central criteria, including maximum neighborhoodcomponent, degree, closeness, radiality, and betweeness. Based on the results of the central criteria method, INS-PRKACA-PRKACBPRKACG-AKT1 genes had the most repetitions. According to the identification of the most effective genes related to CHI disease in thepresent study, it is suggested that further studies need to be designed at the in vitro and clinical levels on the identified effective genes asdiagnostic biomarkers of CHI disease.

Biological Clock Genes are Crucial and Promising Biomarkers for the Therapeutic Targets and Prognostic Assessment in Gastric Cancer.

Gastric cancer is one of the major public health problems worldwide. Circadian rhythm disturbances driven by circadian clock genes play a role in the development of cancer. However, whether circadian clock genes can serve as potential therapeutic targets and prognostic biomarkers for gastric cancer remains elusive. In this study, we comprehensively analyzed the potential relationship between circadian clock genes and gastric cancer using online bioinformatics databases such as GEPIA, cBioPortal, STRING, GeneMANIA, Metascape, TIMER, TRRUST, and GEDS. Biological clock genes are expressed differently in human tumors. Compared with normal tissues, only PER1, CLOCK, and TIMELESS expression differences were statistically significant in gastric cancer (p < 0.05). PER1 (p = 0.0169) and CLOCK (p = 0.0414) were associated with gastric cancer pathological stage (p < 0.05). Gastric cancer patients with high expression of PER1 (p = 0.0028) and NR1D1 (p = 0.016) had longer overall survival, while those with high expression of PER1 (p = 0.042) and NR1D1 (p = 0.016) had longer disease-free survival. The main function of the biological clock gene is related to the circadian rhythms and melatonin metabolism and effects. CLOCK, NPAS2, and KAT2B were key transcription factors for circadian clock genes. In addition, we also found important correlations between circadian clock genes and various immune cells in the gastric cancer microenvironment. This study may establish a new gastric cancer prognostic indicator based on the biological clock gene and develop new drugs for the treatment of gastric cancer using biological clock gene targets.

Expression and prognosis analysis of TBX2 subfamily in human lung carcinoma.

Lung cancer has a high morbidity and mortality rate of all cancers worldwide. Therefore, there is an urgent need for reliable cancer markers for diagnosis and prognosis of patients with lung cancer. In this study, we used the bioinformatics database to compare the expression of the TBX2 subfamily at the transcriptional and protein levels in non-small cell lung cancer. Then, to confirm our bioinformatics analysis above, we used western bloting to determine the expression of TBX2, TBX3, TBX4 and TBX5 in human lung squamous carcinoma cell lines. Besides, low expression of TBX2 subfamily predicted a poor prognosis of patients with lung cancer. Finally, The methylation database was used to explore the relationship between the low expression of TBX2 subfamily and methylation of gene promoter region. Our data showed a significant decrease of TBX2 subfamily expression in lung cancer tissues of several histological subtypes. Finally, the methylation of TBX2 subfamily members in the promoter region of NSCLC was significantly higher than that in normal tissues. Our research provided sufficient evidence that TBX2 subfamily might play an inhibitory role in malignancy progression of lung cancer, which is promising to shed light on discovering a novel reliable cancer marker for prognosis of lung cancer patients.

Large language models for science and medicine.

Large language models (LLMs) are a type of machine learning model that learn statistical patterns over text, such as predicting the next words in a sequence of text. Both general purpose and task-specific LLMs have demonstrated potential across diverse applications. Science and medicine have many data types that are highly suitable for LLMs, such as scientific texts (publications, patents and textbooks), electronic medical records, large databases of DNA and protein sequences and chemical compounds. Carefully validated systems that can understand and reason across all these modalities may maximize benefits. Despite the inevitable limitations and caveats of any new technology and some uncertainties specific to LLMs, LLMs have the potential to be transformative in science and medicine.

MiRNA, siRNA, and lncRNA: Recent Development of Bioinformatics Tools and Databases in Support of Combating Different Diseases

Abstract: Today, the bioinformatics tool and database development are one of the most significant research areas in computational biology. Computational biologists are developing diverse bioinformatics tools and databases in the various fields of biological science. Nowadays, several non-coding RNAs (ncRNA) have been studied extensively, which act as a mediator of the regulation of gene expression. ncRNA is a functional RNA molecule that is transcribed from the mammalian genome. It also controls the disease regulation pathway. Based on the size, ncRNA can be classified into three categories such as small ncRNA (~18–30 nt), medium ncRNA (~30–200 nt), and long ncRNA (from 200 nt to several hundred kb). The miRNA and siRNAs are two types of ncRNA. Various bioinformatics tools and databases have recently been developed to understand the different ncRNAs (miRNAs, siRNAs, and lncRNAs) disease association. We have illustrated different bioinformatics resources, such as in silico tools and databases, currently available for researching miRNAs, siRNAs, and lncRNAs. Some bioinformatics- based miRNA tools are miRbase, miRecords, miRCancer, miRSystem, miRGator, miRNEST, mirtronPred and miRIAD, etc. Bioinformatics-based siRNA tools are siPRED, siDRM, sIR, siDirect 2.0. Bioinformatics-based lncRNAs tools are lncRNAdb v2, lncRNAtor, LncDisease, iLoc-lncRNA, etc. These tools and databases benefit molecular biologists, biomedical researchers, and computational biologists.

NR5A2 promotes malignancy progression and mediates the effect of cisplatin in cutaneous squamous cell carcinoma.

Nuclear receptor subfamily five group A member two (NR5A2) plays a key role in the development of many tumor types, while it is uncertain in cutaneous squamous cell carcinoma (cSCC). The aim of this work was to determine the role of NR5A2 in cSCC proliferation, and to determine whether NR5A2 mediates the effect of cisplatin in cSCC. We performed a systematic study of existing data and conducted a preliminary bioinformatics analysis of NR5A2 expression in cSCC using bioinformatics databases. Immunohistochemical staining was performed on cSCC tissues of seven patients to study NR5A2 expression. NR5A2 expression was examined in human keratin-forming cells (HaCaT) and human cSCC cells (A431, Colo-16, SCL-1, SCL-2, and HSC-5). Stable A431 and SCL-2 cell lines consisting of sh-RNA-NR5A2 were constructed to detect changes in cell proliferation, cell cycle, apoptosis, and to determine the key proteins in the Wnt/β-catenin pathway. We also investigated changes in the effects of cisplatin on cSCC cells by CCK-8, clone formation assay, and Flow apoptosis assay after NR5A2 knockdown. NR5A2 showed enhanced expression in cSCC tissues than in healthy tissues. Downregulation of NR5A2 in cSCC cells led to the formation of a less malignant phenotype. In contrast, the proliferative capacity of the cSCC cells was enhanced posttreatment with RJW100, an NR5A2 agonist. Additionally, NR5A2 knockdown led to a decrease in the expression level of the proteins in the Wnt/β-catenin pathway, and this inhibition was reversed by LiCl and recombinant antibody, Wnt3a. Moreover, NR5A2 knockdown resulted in diminished proliferative capacity and increased apoptotic cells after the addition of cisplatin. NR5A2 plays a crucial role in the progression of cSCC, and the Wnt/β-catenin signaling pathway may be involved in the regulation of NR5A2-mediated cSCC. Knockdown of NR5A2 enhanced both the proliferation inhibiting and apoptosis promoting effects of cisplatin on cSCC.