Transcriptional Data Research Articles

Continuous prediction for tumor mutation burden based on transcriptional data in gastrointestinal cancers

BackgroundTumor mutation burden (TMB) has been considered a biomarker for utilization of immune checkpoint inhibitors(ICIs), but whole exome sequencing(WES) and cancer gene panel(CGP) based on next generation sequencing for TMB detection are costly. Here, we use transcriptome data of TCGA to construct a model for TMB prediction in gastrointestinal tumors.MethodsTranscriptome data, somatic mutation data and clinical data of four gastrointestinal tumors from TCGA, including esophageal cancer (ESCA), stomach adenocarcinoma (STAD), colon adenocarcinoma (COAD) and rectal adenocarcinoma (READ). Using R, we performed visual analysis of somatic mutation data, differentially expressed genes (DEGs) function enrichment analysis, gene set enrichment analysis (GSEA), and estimated TMB value in clinic. Finally, a deep neural network (DNN) model was constructed for TMB prediction.ResultsVisualization of somatic mutation data summarized the classification of mutation, frequency of each mutation type, and top-mutated genes. GSEA showed the enrichment of CD4+/CD8+ T cells in the high TMB group and the activation of tumor suppressing pathways. Single-sample GSEA (ssGSEA) manifested that the high-TMB group had higher level of multiple immune cells infiltration. In addition, distribution of TMB was related to clinical parameters.Like age, M stage, N stage, AJCC stage, and overall survival(OS). After model optimization using genetic algorithm, in the training set, validation set, and testing set, the Pearson relevance coefficient r between predicted values and actual values reaches 0.98, 0.82, and 0.92, respectively; the coefficient of determination R2 is 0.95, 0.82, and 0.7, respectively.ConclusionTMB correlates with clinicopathological parameters in gastrointestinal carcinoma, and patients with high TMB have higher levels of immune infiltration. In addition, the DNN model based on 31 genes predicts TMB of gastrointestinal tumors in a high accuracy.

Integrating Bioinformatics and Drug Sensitivity Analyses to Identify Molecular Characteristics Associated with Targeting Necroptosis in Breast Cancer and their Clinical Prognostic Significance.

Breast cancer accounts for over 1.8 million new cases worldwide annually, and prompt diagnosis and treatment are imperative to prevent mortality. Necroptosis, a form of programmed cell death, is thought to be a critical pathway for cancer cell apoptosis, yet, its relationship with breast cancer progression and molecular mechanisms remains largely unexplored. Our study aims to investigate the molecular characteristics and clinical prognostic value of necroptosis-related genes in breast cancer using a comprehensive approach that involves integrated bioinformatics analysis along with drug sensitivity assessment. Transcriptional, clinical, and tumor mutation burden (TMB) data related to breast cancer from the TCGA and GEO databases were integrated, and the necroptosis gene set was downloaded from the GSEA website for analysis. The screening conditions were set as adjusted p < 0.05 and |log2FC(fold change)| > 0.585 to screen for differential expression genes related to breast cancer necroptosis. Survival prognosis analysis was conducted on breast cancer necroptosis genes. Further analysis was conducted on prognosis-related necroptosis genes, including immune infiltration analysis and GO/KEGG enrichment analysis, to explore the potential biological functions and signaling pathway mechanisms of breast cancer necroptosis genes. Drug sensitivity screening was conducted on the prognosis-related necroptosis to identify potential drugs that target the promotion of necroptosis gene expression, and ultimately, single-gene analysis was performed on the core target genes obtained. Through integrated bioinformatics analysis, 29 differentially expressed mRNAs related to BRCA-Necroptosis were identified, including 18 upregulated mRNAs and 11 downregulated mRNAs. In addition, single-factor analysis of differential genes showed that the expression of HSPA4, PLK1, TNFRSF1B, FLT3, and LEF1 was closely related to BRCA survival prognosis. Based on the expression of these genes, a breast cancer prognosis model was constructed, and it was found that the area under the curve (AUC) of the curve of the risk genes for necroptosis was the largest, indicating that these genes have a certain clinical predictive significance for the occurrence and prognosis of BRCA. Additionally, there were significant differences in clinical characteristics of BRCA patients with different necroptosis gene expressions. Furthermore, GSVA and immune infiltration analysis revealed that Necroptosis-DEGs mainly affect the occurrence and progression of BRCA by participating in immune functions such as APC co-inhibition, APC costimulation, CCR, checkpoint, as well as infiltrating immune cells such as B cells naive, plasma cells, and T cells CD8. Moreover, the necroptosis gene group column chart indicated a 1-year survival rate of 0.979, a 3-year survival rate of 0.883, and a 5-year survival rate of 0.774. The necroptosis gene group and column chart are important indicators for evaluating BRCA prognosis. Finally, drug sensitivity screening of BRCA-Necroptosis genes showed that compounds such as A- 770041, AC220, AP-24534, Bexarotene, and BMS-509744 have certain effects as potential targeted drugs for the treatment of BRCA necroptosis genes. Necroptosis genes are implicated in the pathogenesis and progression of breast cancer and are thought to impact the prognosis and response to drug treatments in individuals with BRCA. Consequently, understanding the role of these genes in breast cancer may aid in identifying more precise and efficacious therapeutic targets.

Human-specific epigenomic states in spermatogenesis

Infertility is becoming increasingly common, affecting one in six people globally. Half of these cases can be attributed to male factors, many driven by abnormalities in the process of sperm development. Emerging evidence from genome-wide association studies, genetic screening of patient cohorts, and animal models highlights an important genetic contribution to spermatogenic defects, but comprehensive identification and characterization of the genes critical for male fertility remain lacking. High divergence of gene regulation in spermatogenic cells across species poses challenges for delineating the genetic pathways required for human spermatogenesis using common model organisms. In this study, we leveraged post-translational histone modification and gene transcription data for 15,491 genes in four mammalian species (human, rhesus macaque, mouse, and opossum), to identify human-specific patterns of gene regulation during spermatogenesis. We combined H3K27me3 ChIP-seq, H3K4me3 ChIP-seq, and RNA-seq data to define epigenetic states for each gene at two stages of spermatogenesis, pachytene spermatocytes and round spermatids, in each species. We identified 239 genes that are uniquely active, poised, or dynamically regulated in human spermatogenic cells distinct from the other three species. While some of these genes have been implicated in reproductive functions, many more have not yet been associated with human infertility and may be candidates for further molecular and epidemiologic studies. Our analysis offers an example of the opportunities provided by evolutionary and epigenomic data for broadly screening candidate genes implicated in reproduction, which might lead to discoveries of novel genetic targets for diagnosis and management of male infertility and male contraception.

Potential role of TWIST1 and its methylation in bladder urothelial carcinoma.

Bladder urothelial carcinoma (BLCA), like other cancers, is strongly associated with genetic and epigenetic changes. TWIST1 is an epithelial-mesenchymal transition (EMT) promoter that has been linked to the development of many malignancies. It is still unclear, however, what role TWIST1 plays in BLCA, and the relationship between TWIST1 transcript levels and its promoter methylation and immune infiltration has been reported even less. This study aimed to reveal the potential role of TWIST1 promoter methylation-related changes in BLCA. Transcriptional expression data of TWIST1 in BLCA were acquired from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and University of Alabama at Birmingham (UALCAN) databases. TWIST1 methylation levels and prognosis were sourced from Gene Expression Profiling Interactive Analysis 2 (GEPIA2), LinkedOmics, cBio Cancer Genomics Portal (c-BioPortal), MethSurv, and DNA Methylation Information Visualization Database (DNMIVD) databases. The methylation status of the BLCA-associated TWIST1 in preoperative and postoperative urinary exfoliated cells was subsequently analyzed using methylation-specific real-time fluorescence polymerase chain reaction, with validation of accuracy through pyrophosphate sequencing. Finally, from the Gene Set Cancer Analysis (GSCA) and Tumor-Immune System Interaction Database (TISIDB) databases, we obtained the association between TWIST1 transcript expression and DNA methylation and cancer immune infiltration and immunolabelling. Our study demonstrated that TWIST1 expression was down-regulated in BLCA, which was negatively correlated with DNA methylation. The association between TWIST1 promoter hypermethylation and the progression, staging, grading, and recurrence of BLCA is highly significant. Furthermore, we revealed that hypermethylation of both the preoperative and postoperative TWIST1 promoters is useful as a biomarker for monitoring BLCA recurrence, particularly when considering the methylation status of specific CpG sites. Additionally, we observed that TWIST1 expression, promoter methylation, and immune infiltration immunoreactive markers correlated significantly in BLCA. We propose that TWIST1 holds great promise as a diagnostic and therapeutic target for BLCA, with the potential to influence tumor progression and patient prognosis through the regulation of immune cell infiltration. We hope these findings contribute valuable insights to the field of BLCA research.

MiR-155 mediated regulation of PKG1 and its implications on cell invasion, migration, and apoptosis in preeclampsia through NF-κB pathway

BackgroundPreeclampsia (PE) is a severe pregnancy complication characterized by complex molecular interactions. Understanding these interactions is crucial for developing effective therapeutic strategies.MethodsThis study applies a pharmacometabolomics approach to explore the roles of miR-155 and PKG1 in PE, focusing on the regulatory influence of the NF-κB signaling pathway. Blood metabolomic profiles were analyzed, and bioinformatics tools, IHC staining, Western blot (WB) analysis, and immunofluorescence (IF) localization were employed to determine the expression and function of miR-155 and PKG1. Cell invasion, migration, proliferation, and apoptosis assays were conducted to assess miR-155’s modulation of PKG1. Additionally, RT-qPCR and WB analysis elucidated NF-κB-mediated regulation mechanisms.ResultsOur findings indicate significant metabolic alterations associated with miR-155 modulation of PKG1, with NF-κB acting as a critical upstream regulator. The study demonstrates that miR-155 affects cellular functions such as invasion, migration, proliferation, and apoptosis through PKG1 modulation. Furthermore, the NF-κB signaling pathway regulates miR-155 expression, contributing to the pathological processes of PE.ConclusionThis study provides a proof of concept for using pharmacometabolomics to understand the molecular mechanisms of PE, suggesting new therapeutic targets and advancing personalized medicine approaches. These insights highlight the potential of pharmacometabolomics to complement genomic and transcriptional data in disease characterization and treatment strategies, offering new avenues for therapeutic intervention in PE.

A simple MiMIC based approach for tagging endogenous genes to visualise live transcription in Drosophila.

Live imaging of transcription in the Drosophila embryo using the MS2 or PP7 systems is transforming our understanding of transcriptional regulation. However, insertion of MS2/PP7 stem loops into endogenous genes requires laborious CRISPR genome editing. Here we exploit the previously described Minos-mediated integration cassette (MiMIC) transposon system in Drosophila to establish a method for simply and rapidly inserting MS2/PP7 cassettes into any of the thousands of genes carrying a MiMIC insertion. In addition to generating a variety of stem loop donor fly stocks, we have made new stocks expressing the complementary coat proteins fused to different fluorescent proteins. We show the utility of this MiMIC-based approach by MS2/PP7 tagging and live imaging transcription of endogenous genes and the long non-coding RNA, roX1, in the embryo. We also present live transcription data from larval brains, the wing disc and ovary, thereby extending the tissues that can be studied using the MS2/PP7 system. Overall, this first high throughput method for tagging mRNAs in Drosophila will facilitate the study of transcription dynamics of thousands of endogenous genes in a range of Drosophila tissues.

A multi-omic atlas of human embryonic skeletal development

Human embryonic bone and joint formation is determined by coordinated differentiation of progenitors in the nascent skeleton. The cell states, epigenetic processes and key regulatory factors that underlie lineage commitment of these cells remain elusive. Here we applied paired transcriptional and epigenetic profiling of approximately 336,000 nucleus droplets and spatial transcriptomics to establish a multi-omic atlas of human embryonic joint and cranium development between 5 and 11 weeks after conception. Using combined modelling of transcriptional and epigenetic data, we characterized regionally distinct limb and cranial osteoprogenitor trajectories across the embryonic skeleton and further described regulatory networks that govern intramembranous and endochondral ossification. Spatial localization of cell clusters in our in situ sequencing data using a new tool, ISS-Patcher, revealed mechanisms of progenitor zonation during bone and joint formation. Through trajectory analysis, we predicted potential non-canonical cellular origins for human chondrocytes from Schwann cells. We also introduce SNP2Cell, a tool to link cell-type-specific regulatory networks to polygenic traits such as osteoarthritis. Using osteolineage trajectories characterized here, we simulated in silico perturbations of genes that cause monogenic craniosynostosis and implicate potential cell states and disease mechanisms. This work forms a detailed and dynamic regulatory atlas of bone and cartilage maturation and advances our fundamental understanding of cell-fate determination in human skeletal development.

“Having Support at Work ‘Is Different’ and Important”: A Qualitative Study of Virtual Peer Discussion Groups With Medical School Faculty

Abstract Purpose In response to the need to support health care professionals during the COVID-19 pandemic, an innovative, peer-led discussion group program for medical school faculty, called CIRCLE (Colleague Involved in Reaching Colleagues through Listening and Empathy), was developed at Rutgers Health. This article describes results of a qualitative analysis of the participants’ experiences, explores virtual communication platform use during this peer support program, and identifies the program’s beneficial elements. Method CIRCLE was inaugurated in October 2020 at Rutgers New Jersey Medical School and Rutgers Robert Wood Johnson Medical School using evidence-informed topics. The inaugural CIRCLE peer-led discussion groups included 50 physicians who met twice monthly in groups of 5 to 8 between October 2020 and April 2021. Deidentified transcript data were iteratively reviewed using conventional content analysis, including familiarization, thematic framework creation, indexing, charting, mapping, and interpretation. Themes were grouped into 4 conceptual framework categories based on social support theory in the context of work-related stress: emotional, appraisal, informational, and instrumental support. Results Themes emerged based on the framework: emotional support (connecting on a deeper level, importance of support at work, COVID-19 made virtual connections needed), relevant appraisal support (feeling “not alone,” safe space to connect and share), informational support (sharing self-care strategies), and instrumental support (incentives to join are helpful but connection leads to engagement, some structure but “not too much” is important, virtual modalities are convenient and conducive to connection). Conclusions Benefits of peer discussion groups include deeper connections at work, reduced isolation, safe sharing, and exchange of information on self-care. Connection and balancing structure and autonomy were important to engagement. Virtual modalities were viewed as feasible, convenient, and conducive to connection. This article highlights the benefits and convenience of virtual peer-led discussion groups for medical school clinical faculty and provides evidence for content development of these programs.

Metabolic Flux Analysis of Xanthomonas oryzae Treated with Bismerthiazol Revealed Glutathione Oxidoreductase in Glutathione Metabolism Serves as an Effective Target.

Bacterial blight (BB) of rice caused by Xanthomonas oryzae pathovar oryzae (Xoo) is a serious global rice disease. Due to increasing bactericide resistance, developing new inhibitors is urgent. Drug repositioning offers a potential strategy to address this issue. In this study, we integrated transcriptional data into a genome-scale metabolic model (GSMM) to screen novel anti-Xoo targets. Two RNA-seq datasets (before and after bismerthiazol treatment) were used to constrain the GSMM and simulate metabolic processes. Metabolic fluxes were calculated using parsimonious flux balance analysis (pFBA) identifying reactions with significant changes for target screening. Glutathione oxidoreductase (GSR) was selected as a potential anti-Xoo target and validated through antibacterial experiments. Virtual screening based on the target identified DB12411 as a lead compound with the potential for new antibacterial agents. This approach demonstrates that integrating metabolic networks and transcriptional data can aid in both understanding antibacterial mechanisms and discovering novel drug targets.

Examining healthcare access with physical vs. telehealth options: Promise and peril for socially vulnerable older adults

IntroductionThis paper seeks to understand barriers to healthcare access faced by socially vulnerable older adults in Chicago using qualitative analysis. As the U.S. population ages, ease of healthcare access by older adults grows in importance. Yet, current literature lacks an examination of pain points and coping strategies in accessing healthcare, specifically by socially vulnerable older adults. This is especially relevant as virtual telehealth access and transportation options that shape healthcare access evolve rapidly. MethodsIn this work, we conduct three listening sessions with 40 total participants to understand the lived experiences of Black and Latino older adults living in low-income areas of Chicago. Transcript data was analyzed using qualitative concept and emotion coding to identify vulnerabilities that older patients face in accessing care. ResultsThis work highlights five key takeaways from the qualitative analysis: 1) technology struggles and prospects in accessing healthcare, 2) social resources for coping give rise to tension between dependence and autonomy, 3) system disconnects (medical-pharmacy-transportation) represent key pain points, 4) different means of accessing healthcare (traditional transportation vs. telehealth) are value and emotion ladened, 5) different means of observing lead to new methodological insights. ConclusionOvercoming healthcare access barriers for older adults ultimately requires analysis of specific interfaces between infrastructure, healthcare, and communications systems. Solutions should prioritize the autonomy of older adults by offering physical accessibility and customized technology. The three intervention policies recommended in this paper include: health kiosks implementation, digital access classes, and specialized training for transit drivers and medical staff.

NCBI RefSeq: reference sequence standards through 25years of curation and annotation.

Reference sequences and annotations serve as the foundation for many lines of research today, from organism and sequence identification to providing a core description of the genes, transcripts and proteins found in an organism's genome. Interpretation of data including transcriptomics, proteomics, sequence variation and comparative analyses based on reference gene annotations informs our understanding of gene function and possible disease mechanisms, leading to new biomedical discoveries. The Reference Sequence (RefSeq) resource created at the National Center for Biotechnology Information (NCBI) leverages both automatic processes and expert curation to create a robust set of reference sequences of genomic, transcript and protein data spanning the tree of life. RefSeq continues to refine its annotation and quality control processes and utilize better quality genomes resulting from advances in sequencing technologies as well as RNA-Seq data to produce high-quality annotated genomes, ortholog predictions across more organisms and other products that are easily accessible through multiple NCBI resources. This report summarizes the current status of the eukaryotic, prokaryotic and viral RefSeq resources, with a focus on eukaryotic annotation, the increase in taxonomic representation and the effect it will have on comparative genomics. The RefSeq resource is publicly accessible at https://www.ncbi.nlm.nih.gov/refseq.

CCRG-03. DETECTION OF HETEROGENEOUS CELL CYCLE ALTERATIONS UPON TMZ CHEMOTHERAPY TREATMENT THROUGH ADVANCED MACHINE LEARNING

Abstract Glioblastoma (GB), the most aggressive central nervous system tumor, is hallmarked by its frequent relapse under alkylating chemotherapy. GB cells frequently exhibit changes in cell cycle phases during TMZ treatment, with a reduction in the G0-G1 phase and an increase in the S and G2 phases. This indicate both tumor cell re-entry into the cell cycle and a TMZ-induced arrest, contributing to resistance and progression. In this study, we leverage dynamic protein abundance of Ki-67, a proliferation marker peaking during S, G2, and M phases, to analyse cellular responses to TMZ in various cell lines and tissue samples. We designed an image-based machine learning approach for pattern recognition to reconstruct and analyse the cell cycle at the single-cell level. Six primary cell lines were characterized through whole-genome DNA, methylation and RNA sequencing. Functional read-outs were performed with large-scale, time- and concentration-dependent TMZ treatments in cell culture and GB-tissue slice models. Our model successfully reconstructed detailed cell cycle stages, showing that untreated cells were predominantly in the G0-G1 phase. TMZ treatment significantly shifted cells toward the S/G2 phase (p &amp;lt; 0.02) in 3 of 6 cell lines and the pseudo-time reconstruction highlighted dose-dependent cell cycle changes. Cell lines with enhanced stem-like features, defined based on epigenetic and transcriptional data signature, showed no cell cycle changes at high TMZ doses (&amp;gt;150µM), regardless the MGMT promoter methylation status. This heterogeneity in cell cycle response emphasizes the complexity of GB and the need for personalized treatments. Our study provides insights into GB MGMT cell cycle alterations and resistance mechanisms that are independent of MGMT methylation status, a known TMZ response biomarker. Therefore, the observed TMZ-induced cell cycle changes may serve as novel biomarkers for assessing treatment response, paving the way for personalized therapeutic approaches.

Identity Work: A Qualitative Study of Residents' Experiences Navigating Identity Struggles.

Medical training traditionally holds a deterministic view of professional socialization wherein many medical learners struggle to construct a professional identity. Previous research has demonstrated the dysfunctional norms and conflicting ideologies that create identity struggle, disproportionally affecting women and individuals underrepresented in medicine. Symbolic interactionism can help explain identity struggles, emphasizing the influence of socio-contextual factors on identity construction. The purpose of this study was to explore how residents navigate identity struggles during residency training. We conducted a qualitative exploration of 12 residents in three specialties at three academic institutions in the United States. Participants engaged in rich picture drawings followed by one-on-one interviews. We coded transcript data and met regularly to identify themes related to residents' experiences with navigating professional identity struggles. We identified three main themes on navigating identity struggles: the weight of identity work, the isolating nature of identity work, and the navigation that occurs with and against socio-contextual currents. Residents described identity work as navigation like a boat at sea. This work felt weighty and at times overwhelming and residents often felt unable to discuss their identity struggles with others. Residents utilized what agency they had to either navigate with the current, navigating towards acceptable-albeit imperfect-paths forward, or attempting to go against the current to forge new paths through resistance. This study highlights how context enables and constrains identity construction, how contextual constraints can create dissonance between identities, and the considerable effort required to reconcile dissonance and construct professional identities. Training program adjustments, enhanced resident support, and cultural shifts are required to sustain residents' identity work. Medical professionals should engage in collective identity work to reimagine the profession's identity by addressing dysfunctional cultural norms.

Information Correspondence on Automatic Translation (Closed Caption) of Speeches on The White House Youtube Channel

This study examines the information correspondence between the source and target language by analyzing the translation equivalence according to Nida and Taber’s theory. This project aims to analyze transcript data from a speech video on The White House YouTube channel. This study employs a qualitative descriptive methodology. Data was obtained using note-taking and transcription methods, then processed in three stages: reduction, presentation, and verification. Based on the findings; there are 110 data (55.8%) which are dominated by Formal equivalence, whereas 73 data (37%) are classified as Dynamic equivalence. Meanwhile, 14 data sets (7.1%) contain errors in the translation. As for the conformity of information, out of 197 data, only 14 data show errors or inconsistencies in essential areas such, proper nouns, terms, and keywords. Other translation information produced 74 data that captured meaning and emotional nuances related to the cultural context, and 109 data that maintained the structure of the translated text using a literal approach, resulting in stiff, awkward, and strange translations.

CITMIC: Comprehensive Estimation of Cell Infiltration in Tumor Microenvironment based on Individualized Intercellular Crosstalk.

The tumor microenvironment (TME) cells interact with each other and play a pivotal role in tumor progression and treatment response. A comprehensive characterization of cell and intercellular crosstalk in the TME is essential for understanding tumor biology and developing effective therapies. However, current cell infiltration analysis methods only partially describe the TME's cellular landscape and overlook cell-cell crosstalk. Here, this approach, CITMIC, can infer the cell infiltration of TME by simultaneously measuring 86 different cell types, constructing an individualized cell-cell crosstalk network based on functional similarities between cells, and using only gene transcription data. This is a novel approach to estimating the relative cell infiltration levels, which are shown to be superior to the current methods. The TME cell-based features generated by analyzing melanoma data are effective in predicting prognosis and treatment response. Interestingly, these features are found to be particularly effective in assessing the prognosis of high-stage patients, and this method is applied to multiple high-stage adenocarcinomas, where more significant prognostic performance is also observed. In conclusion, CITMIC offers a more comprehensive description of TME cell composition by considering cell-cell crosstalk, providing an important reference for the discovery of predictive biomarkers and the development of new therapeutic strategies.

Spectators’ opinions about purchasing tickets from a smoke/vape-free stadium in Ireland: a qualitative study

This study sought to qualitatively explore spectators’ opinions of purchasing tickets in the future if Croke Park (a large stadium in Ireland) were to implement a smoke/vape-fee policy. During 2022 semi-final matches, a total of 107 spectators who were smoking/vaping at Croke Park’s designated areas were briefly interviewed. Transcript data was qualitatively analyzed, showing that most (80%) participants would continue to purchase tickets because of two common reasons: supporting their county at Croke Park was more important than smoking/vaping, and they would find a way to smoke/vape regardless of the rules. Reasons for not purchasing future tickets included: needing to smoke/vape, smoking/vaping is a human right, and smoking/vaping is part of the experience. The implications from the findings, and prior literature, suggest that a smoke/vape-free policy might not impact future ticket sales, given the rich sports heritage of Croke Park.

OHDLF: A Method for Selecting Orthologous Genes for Phylogenetic Construction and Its Application in the Genus Camellia.

Accurate phylogenetic tree construction for species without reference genomes often relies on de novo transcriptome assembly to identify single-copy orthologous genes. However, challenges such as whole-genome duplication (WGD), heterozygosity, gene duplication, and loss can hinder the selection of these genes, leading to limited data for constructing reliable species trees. To address these issues, we developed a new analytical pipeline, OHDLF (Orthologous Haploid Duplication and Loss Filter), which filters orthologous genes from transcript data and adapts parameter settings based on genomic characteristics for further phylogenetic tree construction. In this study, we applied OHDLF to the genus Camellia and evaluated its effectiveness in constructing phylogenetic trees. The results highlighted the pipeline's ability to handle challenges like high heterozygosity and recent gene duplications by selectively retaining genes with a missing rate and merging duplicates with high similarity. This approach ensured the preservation of informative sites and produced a highly supported consensus tree for Camellia. Additionally, we evaluate the accuracy of the OHDLF phylogenetic trees for different species, demonstrating that the OHDLF pipeline provides a flexible and effective method for selecting orthologous genes and constructing accurate phylogenetic trees, adapting to the genomic characteristics of various plant groups.

Cells of the adult mouse cardiac conduction system in wild type and Nkx2-5 heterozygous loss-of-function mutation

Abstract Background Specialised cardiomyocytes in the cardiac conduction system (CCS) generate and spread the electrical impulse that initiates synchronised heartbeats. Disrupted signal transduction in the atrioventricular (AV) node, a key electrical connection between atria and ventricles, causes AV block. AV block potentially leads to electromechanical uncoupling and sudden cardiac death. Nkx2-5 encodes a cardiac transcription factor that is critical for embryonic CCS formation. Heterozygous loss-of-function mutation of Nkx2-5 (Nkx2-5+/–) results in a hypoplastic CCS in humans and mice and progressive AV block. Purpose We aimed to create a cell atlas of the adult mouse CCS and define the consequences of Nkx2-5 haploinsufficiency on the structural organisation and transcript expression of CCS cells. Methods We performed single-nucleus RNA sequencing on the sinoatrial nodes, AV nodes, His bundles, right bundle branches (RBB) and moderator bands of 17 wild type and 14 Nkx2-5+/– mice (aged 13 to 35 weeks, 5159 CCS cells). Employing single-molecule fluorescent RNA in situ hybridisation (smFISH), we validated selected transcripts and examined the spatial organisation of identified cell populations. Results In the AV node, we identified two subpopulations of pacemaker cells that were spatially separated in the proximal and distal pacemaker region (Fig1). Within these subpopulations, expressed transcripts indicated an atrial-to-ventricular gradient of electrical activity, corresponding to their respective topography. We determined two subpopulations in the His bundle and RBB that were enriched for either slow or fast conduction markers. Spatially, the slow-conducting populations seemed to surround the fast-conducting ones and might act as electrical isolation (Fig1). In Nkx2-5+/- cells of the pacemaker AV node, His bundle, RBB and Purkinje fibres, genes involved in Slit-Robo signalling were dysregulated. Slit-Robo signalling was previously reported in neuronal differentiation and embryonic heart lumen formation. Slit ligand 3 was downregulated in Nkx2-5+/- pacemaker AV node cells (Slit3, log2FC = -2.22, p = 7.0e-42), as was the roundabout guidance receptor 1 (Robo1, log2FC = -0.96, p = 1.6e-4). By contrast, there was upregulation of neural EGF-like 1 (Nell1, log2FC = 3.18, p = 5.3e-6), an alternative ligand of roundabout guidance receptors. Altered Nell1 and Slit3 expressions were confirmed by smFISH (Fig2). Conclusions Our cell atlas defines new CCS cell populations with informative transcriptomic profiles and spatial organisation, providing insights into subpopulations in the AV junction where electrical signals switch from slow to fast conduction. We identified disrupted Slit-Robo signalling in Nkx2-5+/-, possibly impairing differentiation and maturation of the CCS and altering electrophysiologic functions. Our normative anatomical and transcription data on the CCS can inform future studies of cardiac electrophysiology and arrhythmias.Fig1 - Subpopulations in AV junctionFig2 - Nell1 smFISH in pacemaker AV node

The prognostic significance of twist in pancreatic cancer and its role in cancer promotion through the regulation of the immune microenvironment and EMT mechanisms

ObjectivePancreatic cancer has a poor prognosis due to its high malignancy and rapid progression. The limited immunogenicity of pancreatic cancer (PAAD) contributes to its low responsiveness to immunotherapy, yet its underlying mechanism remains poorly understood. As a cancer promoting gene, Twist participates in EMT in various tumors and promotes tumor progression. The interplay between EMT and the tumor microenvironment (TME) emerges as a pivotal factor influencing tumor immunity and response to immunotherapy. Twist therefore has potential as a biomarker for gauging the outcome of tumour immunotherapy.This research aimed to assess the Twist's prognostic significance in PAAD and its relationship to immunotherapy response.MethodsIn this research, transcriptional data and epigenetic alterations of Twist in pancreatic cancer, along with their impact on the prognosis of PAAD patients, were analyzed using databases. Functional enrichment analysis elucidated the biological role of Twist in PAAD. Subsequently, databases including CIBERSORT and TIDE were employed to investigate the association between Twist expression and immune cell infiltration, immune checkpoint genes, and immunotherapy sensitivity within the pancreatic cancer immune microenvironment.Paraffinized specimens from patients with pancreatic ductal adenocarcinoma confirmed by postoperative pathology were selected for Twist expression verification, and the difference was analyzed by Chi-square test; uncontaminated pancreatic cancer cell lines were used for Twist expression verification, and the differences were analyzed by Student t-test.ResultsTwist mRNA expression was notably upregulated in PAAD, positively correlating with gene methylation levels. Analyses of Kaplan–Meier and Cox regression showed a correlation between better overall survival and lower Twist expression. Functional annotation indicated that Twist-associated differentially expressed genes (DEGs) were involved in EMT regulation and acute inflammation. High expression of Twist leads to a significant reduction in the infiltration of anti-tumor immune cells such as Monocytes, NKcellsactivated, and TcellsCD8, further supporting its creation of a typical immunosuppressive microenvironment in pancreatic cancer. Twist expression is positively correlated with the expression of HARVCR2, LAIR1, LGALS3 and other genes, which may be related to the treatment response to immune checkpoint inhibitors (ICIs). TIDE analysis predicts that patients with high expression of Twist will be insensitive to immunotherapy. Twist is significantly over-expressed in pancreatic cancer cell lines and tissues, and is negatively correlated with E-cadhrin expression, but positively correlated with N-cadherin,Snail, and ZEB1.ConclusionHigh Twist expression in PAAD signifies a grim prognosis. Its elevated levels not only contribute to tumor progression through EMT induction but also exert regulatory control over the immune microenvironment, leading to immunosuppression and diminished effectiveness of immunotherapy.

Development and validation of a novel endoplasmic reticulum stress-related lncRNAs signature in osteosarcoma

Osteosarcoma (OS) is a cancerous tumor, and its development is greatly influenced by long non-coding RNA (lncRNA). Endoplasmic reticulum stress (ERS) is an essential biological defense process in cells and contributes to the progression of tumors. However, the exact mechanisms remain elusive. This study aims to develop a signature of lncRNAs associated with ERS in OS. This signature will guide the prognosis prediction and the determination of appropriate treatment strategies. The UCSC Xena database collected transcriptional and clinical data of OS and muscle, after identifying ERS differentially expressed genes, we utilized correlation analysis to determine the endoplasmic reticulum stress lncRNAs (ERLs). The Least Absolute Shrinkage and Selection Operator (LASSO) and Cox regression analysis were utilized to develop an ERLs signature. To clarify the fundamental mechanisms controlling gene expression in low and high-risk groups, Gene Set Variation Analysis (GSVA) were conducted. In addition, the distinction between the two groups regarding drug sensitivity and immune-related activity was investigated to determine the immunotherapy effects. Utilizing RT-qPCR, the expression of model lncRNAs in OS cell lines was ascertained. The functional analysis of LINC02298 was carried out through in vitro experiments and pan-cancer analysis. This study successfully constructed an ERLs prognostic signature for OS, which comprised 5 lncRNAs (AC023157.3, AL031673.1, LINC02298, LINC02328, SNHG26). The risk signature predicted overall survival in patients with OS and was confirmed by assessing the validation and whole cohorts. Further, it was discovered that individuals classified as high-risk displayed suppressed immune activation, decreased infiltration of immune cells, and decreased responsiveness to immunotherapy. The RT-qPCR showed that the constructed risk prognosis model is reliable. Experimental validation has demonstrated that LINC02298 can promote OS cells’ invasion, migration, and proliferation. In addition, LINC02298 exhibited significant differential expression in many types of cancer. Moreover, LINC02298 is an important biomarker in a variety of tumors. This study established a novel ERLs signature, which successfully predicted the prognosis of OS. The function of LINC02298 in OS was elucidated via in vitro experiments. Therefore, it offers new opportunities for predicting the clinical prognosis of OS and establishes the basis for targeted therapy in OS.