Gene Signature Research Articles

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

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

Integrated single-cell transcriptomic analyses identify a novel lineage plasticity-related cancer cell type involved in prostate cancer progression

Cancer cell plasticity is the ability of neoplastic cells to alter their identity and acquire new biological properties under microenvironmental pressures. In prostate cancer (PCa), lineage plasticity often results in therapy resistance and trans-differentiation to neuroendocrine (NE) lineage. However, identifying the cancer cells harboring lineage plasticity-related status remains challenging. Based on 13 multi-center human PCa bulk transcriptomic cohorts (samples=3314) and 9 bulk transcriptomic datasets derived from PCa experimental models, we established an integrated lineage plasticity-related gene signature, termed LPSig. Leveraging this gene signature, AUCell enrichment analysis was applied to identify the cell population with high lineage plasticity from a comprehensive single-cell RNA-sequencing (scRNA-seq) meta-atlas assembled by us, which consisted of 10 public human PCa scRNA-seq datasets (samples=93, cells=222,529). Moreover, additional scRNA-seq dataset of human PCa, multiplex immunohistochemistry staining for human PCa tissues, invitro and invivo functional experiments, as well as qPCR and Western blot analyses were employed to validate our findings. We found that LPSig could finely capture the dynamics of tumor lineage plasticity throughout the progression of PCa, accurately estimating the status of lineage plasticity. Based on LPSig, we identified a previously undefined minority population of lineage plasticity-related PCa cells (LPCs) from the human PCa scRNA-seq meta-atlas assembled by this study. Furthermore, in-depth dissection revealed pivotal roles of LPCs in trans-differentiation, tumor recurrence, and poor patient survival during PCa progression. Furthermore, we identified HMMR as a representative cell surface marker for LPCs, which was validated using additional scRNA-seq datasets and multiplexed immunohistochemistry. Moreover, HMMR was transcriptionally inhibited by androgen receptor (AR), and was required for the aggressive adenocarcinoma features and NE phenotype. Our study uncovers a novel population of lineage plasticity-related cells with low AR activity, stemness-like traits, and elevated HMMR expression, that may facilitate poor prognosis in PCa. This work was supported by National Key R&D Program of China (2022YFA0807000), National Natural Science Foundation of China (82160584), Advanced Prostate Cancer Diagnosis and Treatment Technology Innovation Team of Kunming Medical University (CXTD202216), and Reserve Talents of Young and Middle-aged Academic Leaders in Yunnan Province (202105AC160013).

Deciphering Immune-related Gene Signatures in Diabetic Retinopathy: Insights from In silico Analysis and In vitro Experiment.

Diabetes retinopathy (DR) is one of the most common microvascular consequences of diabetes, and the economic burden is increasing. Our aim is to decipher the relevant mechanisms of immune-related gene features in DR and explore biomarkers targeting DR. Provide a basis for the treatment and prevention of DR. The immune infiltration enrichment score of DR patients was evaluated from the single- cell RNA sequencing dataset, and the samples were divided into low immune subgroups and high immune subgroups based on this result. Through weighted gene correlation network analysis, differentially expressed genes (DEGs) between two subgroups were identified and crossed with genes with the strongest immune association, resulting in significant key genes. Then divide the DR individuals into two immune related differentially expressed gene (IDEG) clusters, A and B. Submit cross DEGs between two clusters through Gene Set Enrichment Analysis (GSEA) to further explore their functions. A protein-protein interaction (PPI) network of IDEG was established to further identify central genes associated with DR. Use the discovered central genes to predict the regulatory network involved in the pathogenesis of DR. Then, the role of the identified hub gene in the pathogenesis of DR was further studied through in vitro experiments. We found that the immune scores of DR and control groups were different, and 27 IDEGs were found in the DR subgroup. Compared with cluster A, the proportion of cytotoxic lymphocytes, B lineage, monocyte lineage, and fibroblasts in DR patients in cluster B is significantly enriched. GSEA indicates that these genes are associated with T cell activation, regulation of immune response processes, lymphocyte-mediated immunity, TNF signaling pathway, and other signaling pathways. The PPI network subsequently identified 10 hub genes in DR, including SIGLEC10, RGS10, PENK, FGD2, LILRA6, CIITA, EGR2, SIGLEC7, LILRB1, and CD300LB. The upstream regulatory network and lncRNA miRNA mRNA ceRNA network of these hub genes were ultimately constructed. The discovery and identification of these genes will provide biomarkers for targeted prediction and treatment of DR. By integrating bioinformatics analysis and in vitro experiments, we have identified a set of central genes, indicating that these genes can serve as potential biomarkers for DR, which may be promising targets for future DR immunotherapy interventions.

Integrating molecular imaging and transcriptomic profiling in advanced HER2-positive breast cancer receiving trastuzumab emtansine (T-DM1): an analysis of the ZEPHIR clinical trial.

The ZEPHIR clinical trial evaluated the role of [89Zr]trastuzumab-PET/CT (HER2-PET/CT) and 2-[18F]fluoro-2-deoxy-D-glucose PET/CT ([18F]FDG-PET/CT) in predicting outcomes in patients with advanced HER2-positive breast cancer treated with trastuzumab emtansine (T-DM1). Here, we combined molecular/metabolic imaging and transcriptomic data to investigate the biological processes associated with [89Zr]trastuzumab and [18F]FDG uptake, and to dissect the mechanisms involved in T-DM1 resistance. RNA was extracted from metastasis biopsies obtained in the ZEPHIR trial. HER2-PET/CT and [18F]FDG-PET/CT imaging data of biopsied lesions were integrated with transcriptomic data. Lesions were compared based on the level of [89Zr]trastuzumab uptake as well as on the presence/absence of metabolic response, defined comparing baseline and on-treatment [18F]FDG-PET/CT. We analyzed matched transcriptomic and molecular/metabolic imaging data for 24 metastases. Genes and pathways involved in extracellular matrix (ECM) organization and glycosylphosphatidylinositol synthesis were enriched in lesions presenting low [89Zr]trastuzumab uptake. [18F]FDG uptake at baseline correlated with proliferation and immune-related processes. Hypoxia and ECM-related processes were enriched in lesions showing no metabolic response to T-DM1, while immune-related processes were associated with high [89Zr]trastuzumab uptake and metabolic response. Gene signatures including differentially expressed genes according to [89Zr]trastuzumab uptake and metabolic response showed predictive value in an external cohort. To our knowledge, this study represents the first correlative analysis between [89Zr]trastuzumab tumor uptake and gene expression profiling in humans. Our findings suggest a role of ECM in impairing [89Zr]trastuzumab tumor uptake and T-DM1 metabolic response in advanced HER2-positive breast cancer, highlighting the potential of molecular imaging to depict tumor microenvironment features.

ScLTdb: a comprehensive single-cell lineage tracing database.

Single-cell lineage tracing (scLT) is a powerful technique that integrates cellular barcoding with single-cell sequencing technologies. This new approach enables the simultaneous measurement of cell fate and molecular profiles at single-cell resolution, uncovering the gene regulatory program of cell fate determination. However, a comprehensive scLT database is not yet available. Here, we present the single-cell lineage tracing database (scLTdb, https://scltdb.com) containing 109 datasets that are manually curated and analyzed through a standard pipeline. The scLTdb provides interactive analysis modules for visualizing and re-analyzing scLT datasets, especially the comprehensive cell fate analysis and lineage relationship analysis. Importantly, scLTdb also allows users to identify fate-related gene signatures. In conclusion, scLTdb provides an interactive interface of scLT data exploration and analysis, and will facilitate the understanding of cell fate decision and lineage commitment in development and diseases.

Screening of m6A-associated ferroptosis-related genes in atherosclerosis based on WGCNA

BackgroundN6-methyladenosine (m6A) has been shown to mediate ferroptosis but its role in atherosclerosis (AS) is unclear.MethodsDifferentially expressed m6A-associated ferroptosis-related genes (DE-m6A-Ferr-RGs) were obtained using differential expression analysis and Pearson correlation analysis. Weighted gene co-expression network analysis (WGCNA) was also performed. The intersection of the module genes and the DE-m6A-Ferr-RGs were recorded as candidate m6A-Ferr-related signature genes. Finally, the m6A-Ferr-related signature genes were screened using least absolute shrinkage and selection operator (LASSO) analysis. Expression validation, receiver operating characteristic ( mapping, and immune correlation analysis were also performed based on the m6A-Ferr-related signature genes. The expression of m6A-Ferr-related signature genes was further validated using a real-time polymerase chain reaction (RT-qPCR).ResultsIn total, 6,167 differentially expressed genes were intersected with 24 m6A- and 259 ferroptosis-related genes, respectively, resulting in 113 DE-m6A-Ferr-RGs obtained using Pearson’s correlation analysis. The module genes obtained from the WGCNA and the 113 DE-m6A-Ferr-RGs were intersected to obtain 48 candidate m6A-Ferr-related signature genes. LASSO analysis was performed and six m6A-Ferr-related signature genes were screened. In addition, the area under the curve values of all six m6A-Ferr-related signature genes were greater than 0.7, indicating that they had potential diagnostic value. Furthermore, the RT-qPCR results revealed that the expression of SLC3A2, NOX4, and CDO1 was consistent with the transcriptome level. Moreover, there was a significant difference in two types of immune cells between the AS and control groups. Naive B cells, CD8+ T cells, regulatory T cells, and activated natural killer cells were positively correlated with CDO1 and NOX4 but negatively correlated with ATG7, CYBB, and SLC3A2.ConclusionIn total, three m6A-Ferr-related signature genes (NOX4, CDO1, and SLC3A2) were obtained through a series of bioinformatics analyses and an RT-qPCR.

Unlocking the secrets of Cardiac development and function: the critical role of FHL2.

FHL2 (Four-and-a-half LIM domain protein 2) is a crucial factor involved in cardiac morphogenesis, the process by which the heart develops its complex structure. It is expressed in various tissues during embryonic development, including the developing heart, and has been shown to play important roles in cell proliferation, differentiation, and migration. FHL2 interacts with multiple proteins to regulate cardiac development as a coactivator or a corepressor. It is involved in cardiac specification and determination of cell fate, cardiomyocyte growth, cardiac remodeling, myofibrillogenesis, and the regulation of HERG channels. Targeting FHL2 has therapeutic implications as it could improve cardiac function, control arrhythmias, alleviate heart failure, and maintain cardiac integrity in various pathological conditions. The identification of FHL2 as a signature gene in atrial fibrillation suggests its potential as a diagnostic marker and therapeutic target for this common arrhythmia.

Nuclear receptor corepressor 1 controls regulatory T cell subset differentiation and effector function.

FOXP3+ regulatory T cells (Treg cells) are key for immune homeostasis. Here, we reveal that nuclear receptor corepressor 1 (NCOR1) controls naïve and effector Treg cell states. Upon NCOR1 deletion in T cells, effector Treg cell frequencies were elevated in mice and in in vitro-generated human Treg cells. NCOR1-deficient Treg cells failed to protect mice from severe weight loss and intestinal inflammation associated with CD4+ T cell transfer colitis, indicating impaired suppressive function. NCOR1 controls the transcriptional integrity of Treg cells, since effector gene signatures were already upregulated in naïve NCOR1-deficient Treg cells while effector NCOR1-deficient Treg cells failed to repress genes associated with naïve Treg cells. Moreover, genes related to cholesterol homeostasis including targets of liver X receptor (LXR) were dysregulated in NCOR1-deficient Treg cells. However, genetic ablation of LXRβ in T cells did not revert the effects of NCOR1 deficiency, indicating that NCOR1 controls naïve and effector Treg cell subset composition independent from its ability to repress LXRβ-induced gene expression. Thus, our study reveals that NCOR1 maintains naïve and effector Treg cell states via regulating their transcriptional integrity. We also reveal a critical role for this epigenetic regulator in supporting the suppressive functions of Treg cells in vivo.

Vitamin K2 and the Vitamin-K-Cycle-Enzyme VKORC1L1 improve endothelial regeneration by inhibiting endothelial-mesenchymal transition, inflammatory cell activation and ferroptosis

Abstract Introduction Vascular inflammation is a crucial contributor to atherosclerosis, in which oxidative stress, endoplasmic reticulum (ER) stress and transition of endothelial to mesenchymal cells (EndMT) are of critical importance. Vitamin-K-antagonists (VKA) promote vascular dysfunction, while dietary vitamin K intake was proposed to reduce incidence of coronary artery disease, but the mechanisms remain unresolved. Key enzyme for regeneration of vitamin K is the Vitamin K epoxide reductase complex subunit 1 (VKORC1), which also represents the pharmacological target of VKA. VKOR-like1 (VKORC1L1) is an isoenzyme of VKORC1, which resides at the ER-membrane, exerts antioxidative properties and is involved in vitamin K maintenance. Aim of this study was to investigate the role of Vitamin K2 and the VKOR-enzymes in endothelial cell inflammation. Methods and Results In human coronary artery endothelial cells (HCAEC), Vitamin K2 improves endothelial regeneration by increasing proliferation and cell viability and by reducing both apoptosis and ferroptosis (relative viability: RSL3 0.11 ± 0.01 vs 0.32 ± 0.05 RSL3+K2-1µM vs. 0.44 ± 0.11 RSL3+K2-10µM, p<0.001). Moreover, Vitamin K2-supplementation inhibits EndMT by reducing expression of mesenchymal markers (Calponin, SM22; Fig.1). In silico analyses of the proteome of human coronary atherosclerosis revealed increased expression of VKORC1L1, but not of VKORC1. In vitro induction of oxidative stress and ER-Stress promoted time- and dose-dependent enhanced expression of VKORC1L1, without altering VKORC1 expression (H2O2: 2.3-fold vs. 0.8-fold after 40 minutes, p=0.04; tunicamycin: 1 μg/ml: 1.43-fold vs. 0.8-fold, p<0.01). Likewise, siRNA-mediated VKORC1L1 knockdown induces an inflammatory gene signature with upregulation of NFkB-signalling and endoplasmic reticulum stress (NF-κB: 1.95-fold ± 0.13, GRP78: 1.32-fold ± 0.04 vs. control, p<0.01). Furthermore, VKORC1L1 downregulation increased formation of reactive oxygen species (ROS) and reduced proliferation (EdU signal: 0.56 ± 0.02 vs. control, p < 0.01). In contrast, VKORC1-knockdown does not impair endothelial regeneration and function (Fig.2). Vitamin K2 reduces vascular inflammation and endoplasmic reticulum stress in the case of VKORC1-, but not VKORC1L1-knockdown. In addition, inducing EndMT resulted in a reduction of VKORC1L1, but not of VKORC1, while VKORC1L1-knockdown aggravates EndMT. Conclusion VKORC1 and its isoenzyme VKORC1L1 exhibit divergent effects on endothelial cell inflammation. Further studies are warranted to shed light on the regulation of the enzymes to improve our understanding regarding vascular side effects of VKA treatment and beneficial effects of vitamin K supplementation.

Single-cell and bulk transcriptomic datasets enable the development of prognostic models based on dynamic changes in the tumor immune microenvironment in patients with hepatocellular carcinoma and portal vein tumor thrombus

BackgroundHepatocellular carcinoma (HCC) patients exhibiting portal vein tumor thrombosis (PVTT) face a high risk of rapid malignant progression and poor outcomes, with this issue being compounded by a lack of effective treatment options. The integration of bulk RNA-sequencing (RNA-seq) and single-cell RNA-seq (scRNA-seq) datasets focused on samples from HCC patients with PVTT has the potential to yield unprecedented insight into the dynamic changes in the tumor microenvironment (TME) and associated immunological characteristics in these patients, providing an invaluable tool for the reliable prediction of disease progression and treatment responses.MethodsscRNA-seq data from both primary tumor (PT) and PVTT cells were downloaded from the Gene Expression Omnibus (GEO) database, while the International Cancer Genome Consortium (ICGC) and Cancer Genome Atlas (TCGA) databases were used to access bulk RNA-seq datasets. scRNA-seq, clustering, GSVA enrichment, mutational profiling, and predictive immunotherapeutic treatment analyses were conducted using these data with the goal of systematically assessing the heterogeneity of PT and PVTT cells and establishing a model capable of predicting immunotherapeutic and prognostic outcomes in patients with HCC.ResultsThese analyses revealed that PVTT cells exhibited patterns of tumor proliferation, stromal activation, and low levels of immune cell infiltration, presenting with immune desert and immune rejection-like phenotypes. PT cells, in contrast, were found to exhibit a pattern of immunoinflammatory activity. Core PVTT-associated genes were clustered into three patterns consistent with the tumor immune rejection and immune desert phenotypes. An established clustering model was capable of predicting tumor inflammatory stage, subtype, TME stromal activity, and patient outcomes. PVTT signature genes were further used to establish a risk model, with the risk scores derived from this model providing a tool to evaluate patient clinicopathological features including clinical stage, tumor differentiation, histological subtype, microsatellite instability status, and tumor mutational burden. These risk scores were also able to serve as an independent predictor of patient survival outcomes, responses to adjuvant chemotherapy, and responses to immunotherapy. In vitro experiments were used to partially validate the biological prediction results.ConclusionThese results offer new insight into the biological and immunological landscape of PVTT in HCC patients, By utilizing individual patient risk scores, providing an opportunity to guide more effective immunotherapeutic interventional efforts.

Predicting transcriptional responses to novel chemical perturbations using deep generative model for drug discovery

Understanding transcriptional responses to chemical perturbations is central to drug discovery, but exhaustive experimental screening of disease-compound combinations is unfeasible. To overcome this limitation, here we introduce PRnet, a perturbation-conditioned deep generative model that predicts transcriptional responses to novel chemical perturbations that have never experimentally perturbed at bulk and single-cell levels. Evaluations indicate that PRnet outperforms alternative methods in predicting responses across novel compounds, pathways, and cell lines. PRnet enables gene-level response interpretation and in-silico drug screening for diseases based on gene signatures. PRnet further identifies and experimentally validates novel compound candidates against small cell lung cancer and colorectal cancer. Lastly, PRnet generates a large-scale integration atlas of perturbation profiles, covering 88 cell lines, 52 tissues, and various compound libraries. PRnet provides a robust and scalable candidate recommendation workflow and successfully recommends drug candidates for 233 diseases. Overall, PRnet is an effective and valuable tool for gene-based therapeutics screening.

Genetic profile of ferroptosis in non-small cell lung carcinoma and pharmaceutical options for ferroptosis induction.

Lung cancer (LC) is the leading cause of cancer-related deaths and the second most commonly diagnosed malignancy worldwide. Lung adenocarcinoma (LUAD) and lung squamous cell LC (LUSCC) are the most common subtypes of non-small cell LC (NSCLC). Early diagnosis of LC can be challenging due to a lack of biomarkers. The overall survival (OS) of patients with NSCLC is still poor despite the enormous efforts that have been made to develop novel treatments. Understanding fundamental molecular and genetic mechanisms is necessary to develop new therapeutic approaches for NSCLC. A recently identified type of programmed cell death known as ferroptosis is one potential approach. Ferroptosis causes oxidative damage and the death of cancerous cells by peroxidizing unsaturated phospholipids and accumulating reactive oxygen species (ROS) in an iron-dependent manner. Ferroptosis-related gene (FRG) signatures have recently been evaluated for their ability to predict patient OS and prognosis. These analyses show FRGs are involved in cancer progression, and may serve as promising biomarkers for tumor diagnosis and therapy. Moreover, we summarize the current pharmaceutical options of ferroptosis induction and their underlying molecular mechanism in LC. Therefore, this review aims to provide a comprehensive summary of FRG-based prognostic models, their associated metabolic and signaling pathways, and promising therapeutic options for ferroptosis induction in NSCLC.

Chronic interferon-stimulated gene transcription promotes oncogene-induced breast cancer.

The MRE11 complex (comprising MRE11, RAD50, and NBS1) is integral to the maintenance of genome stability. We previously showed that a hypomorphic Mre11 mutant mouse strain (Mre11 ATLD1/ATLD1 ) was highly susceptible to oncogene-induced breast cancer. Here we used a mammary organoid system to examine which MRE11-dependent responses are tumor-suppressive. We found that Mre11 ATLD1/ATLD1 organoids exhibited an elevated interferon-stimulated gene (ISG) signature and sustained changes in chromatin accessibility. This Mre11 ATLD1/ATLD1 phenotype depended on DNA binding of a nuclear innate immune sensor, IFI205. Ablation of Ifi205 in Mre11 ATLD1/ATLD1 organoids restored baseline and oncogene-induced chromatin accessibility patterns to those observed in WT. Implantation of Mre11 ATLD1/ATLD1 organoids and activation of the oncogene led to aggressive metastatic breast cancer. This outcome was reversed in implanted Ifi205 -/- Mre11 ATLD1/ATLD1 organoids. These data reveal a connection between innate immune signaling and tumor development in the mammary epithelium. Given the abundance of aberrant DNA structures that arise in the context of genome instability syndromes, the data further suggest that cancer predisposition in those contexts may be partially attributable to chronic innate immune transcriptional programs.

Differential Host Gene Expression in Response to Infection by Different Mycobacterium tuberculosis Strains—A Pilot Study

Tuberculosis (TB) represents a global public health threat and is a leading cause of morbidity and mortality worldwide. Effective control of TB is complicated with the emergence of multidrug resistance. Yet, there is a fundamental gap in understanding the complex and dynamic interactions between different Mycobacterium tuberculosis strains and the host. In this pilot study, we investigated the host immune response to different M. tuberculosis strains, including drug-sensitive avirulent or virulent, and rifampin-resistant or isoniazid-resistant virulent strains in human THP-1 cells. We identified major differences in the gene expression profiles in response to infection with these strains. The expression of IDO1 and IL-1β in the infected cells was stronger in all virulent M. tuberculosis strains. The most striking result was the overexpression of many interferon-stimulated genes (ISGs) in cells infected with the isoniazid-resistant strain, compared to the rifampin-resistant and the drug-sensitive strains. Our data indicate that infection with the isoniazid-resistant M. tuberculosis strain preferentially resulted in cGAS-STING/STAT1 activation, which induced a characteristic host immune response. These findings reveal complex gene signatures and a dynamic variation in the immune response to infection by different M. tuberculosis strains.

Identification and validation of M2 macrophage-related gene signature as a novel prognostic model for head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) is a highly heterogeneous tumor. Commonly used tumor staging don’t sufficiently and accurately assess the prognosis of HNSCC patients, resulting in a lack of guidance for clinical treatment decisions. M2 macrophage infiltration has been shown to be strongly associated with the tumor prognosis. In this study, we used the Cancer Genome Atlas (TCGA) data to screen for genes co-expressed with M2 macrophages in HNSCC. We used univariate Cox regression to screen out the genes associated with HNSCC prognosis, and constructed a HNSCC prognosis model by Lasso regression analysis. The results confirmed that the model had good predictive value and accuracy for the prognosis of HNSCC patients by survival analysis, ROC curve and nomogram. We divided the HNSCC samples into high-risk and low-risk groups according to the risk score, and the results showed that patients in the high-risk group were more prone to genetic mutations and had a higher tumor mutational burden. In addition, there were significant differences between risk groups in terms of immune cell infiltration and drug sensitivity. The HNSCC prognostic model established in this study may provide guidance for clinical therapeutic decision-making and provide a theoretical foundation for the development of new immunotherapy methods.

Circadian rhythm genes contribute to the prognosis prediction and potential therapeutic target in gastric cancer

The role of circadian rhythm genes (CRGs) in gastric cancer (GC) is poorly understood. This study aimed to develop a CRG signature to improve understanding of prognosis and immunotherapy responses in GC patients. We integrated the The Cancer Genome Atlas-Stomach adenocarcinoma (TCGA-STAD) dataset with CRGs to develop a prognostic signature for GC. The signature’s predictive ability was validated using Kaplan-Meier and ROC curves. The CIBERSORT algorithm evaluated immune cell proportions, and tumor immune dysfunction and exclusion score, as well as immune phenotype score, determined the response to immunotherapy for STAD patients. Finally, we assessed signature genes expression using real-time quantitative polymerase chain reaction. We developed a 4-CRG signature for STAD, demonstrating accurate prognostic ability. The low-risk group showed increased B cell memory and CD8 + T cells, and decreased M2 Macrophages compared to the high-risk group. Patients in the low-risk group had a higher likelihood of benefiting from immunotherapy. Additionally, gastric cancer tissues exhibited elevated expression of OPN3 and decreased expression of TP53 compared to adjacent tissue. This study successfully established a prognostic signature for CRGs, accurately predicting prognosis and immunotherapeutic response among STAD patients, providing insights for the development of personalized therapeutic strategies for these patients.

Single-Cell Meta-Analysis Uncovers the Pancreatic Endothelial Cell Transcriptomic Signature and Reveals a Key Role for NKX2-3 in PLVAP Expression.

The pancreatic vasculature displays tissue-specific physiological and functional adaptations that support rapid insulin response by β-cells. However, the digestive enzymes have made it difficult to characterize pancreatic endothelial cells (ECs), resulting in the poor understanding of pancreatic EC specialization. Available single-nuclei/single-cell RNA-sequencing data sets were mined to identify pancreatic EC-enriched signature genes and to develop an integrated atlas of human pancreatic ECs. We validated the findings using independent single-nuclei/single-cell RNA-sequencing data, bulk RNA-sequencing data of isolated ECs, spatial transcriptomics data, immunofluorescence, and RNAScope of selected markers. The TF (transcription factor) NKX2-3 was expressed in HUVECs via gene transfection, and the expression of pancreatic EC-enriched signature genes was assessed via RT-qPCR. We defined a pancreatic EC-enriched gene signature conserved across species and developmental stages that included genes involved in ECM (extracellular matrix) composition (COL15A1 and COL4A1), permeability and barrier function (PLVAP, EHD4, CAVIN3, HSPG2, ROBO4, HEG1, and CLEC14A), and key signaling pathways (S1P, TGF-β [transforming growth factor-β], RHO-RAC GTPase, PI3k-AKT, and PDGF [platelet-derived growth factor]). The integrated atlas revealed the vascular hierarchy within the pancreas. We identified and validated a specialized islet capillary subpopulation characterized by genes involved in permeability (PLVAP and EHD4), immune-modulation (FABP5, HLA-C, and B2M), ECM composition (SPARC and SPARCL1), IGF (insulin-like growth factor) signaling (IGFBP7), and membrane transport (SLCO2A1, SLC2A3, and CD320). Importantly, we identified NKX2-3 as a key TF enriched in pancreatic ECs. DNA-binding motif analysis found NKX2-3 motifs in ≈40% of the signature genes. Induction of NKX2-3 in HUVECs promoted the expression of the islet capillary EC-enriched genes PLVAP and SPARCL1. We defined a validated transcriptomic signature of pancreatic ECs and uncovered their intratissue transcriptomic heterogeneity. We showed that NKX2-3 acts upstream of PLVAP and provided a single-cell online resource that can be further explored by the community: https://vasconcelos.shinyapps.io/pancreatic_endothelial/.

RNA-seq and whole-genome re-sequencing reveal Micropterus salmoides growth-linked gene and selection signatures under carbohydrate-rich diet and varying temperature

This study was performed on Micropterus salmoides to determine growth-linked gene and single nucleotide polymorphism (SNP) markers under carbohydrate diet and varying temperature through RNA-seq and whole-genome re-sequencing. The results showed that growth-related genes were primarily enriched in the fat digestion and absorption signaling pathway, playing a role in lipid transport and metabolism. Fatty acid binding protein 6, bile salt-activated lipase-like, lysophosphatidylcholine acyltransferase 2, phospholipase A2, minor isoenzyme-like, and phospholipase A2, group IB (pancreas) were identified as the crucial genes. The differentially expressed genes between high and low temperatures were enriched in the pentose phosphate pathway, with carbohydrate transport and metabolism were most affected by temperature. Major facilitator superfamily domain containing 10, phosphogluconate dehydrogenase, fructose-1,6-bisphosphatase 1a, and spinster homolog 3 transcript variant X1(spns3) were the shared genes affected by temperature. From all the common genes, 10 growth-associated SNP markers were identified. The TT genotype at rs7781 was associated with lower body weight, while AA genotype at rs31434173 and CC genotype at rs31435313 showed positive correlation with body weight. Analogously, the GG genotype at rs31436887 and AA genotype at rs31438769 also found to characterize better growth performance. At low temperature, individuals with the AA genotype at rs11506587 and rs31435313 exhibited the slowest growth. For the genotypes labeled with rs11510589, the GG individual grew faster than the AA individual, whereas the opposite phenomenon occurred in these genotypes when labeled with rs11511314. The genotypes at rs32970704 and rs32967921 showed no growth correlation. The AA genotype at rs31435313 in spns3 had the slowest growth under a carbohydrate-rich diet regardless of the temperature. Our study presents candidate genes and SNP markers associated with growth influenced by carbohydrate and temperature, providing basis for the development of M. salmoides strain that better accepts carbohydrate diets at varying temperature.

Chemogenetic neuronal silencing decouples c-Jun activation from cell death in the temporal cortex.

Initial symptoms of neurodegenerative diseases are often defined by the loss of the most vulnerable neural populations specific to each disorder. In the early stages of Alzheimer's disease, vulnerable circuits in the temporal lobe exhibit diminished activity prior to overt degeneration. It remains unclear whether these functional changes contribute to regional vulnerability or are simply a consequence of pathology. We previously found that entorhinal neurons in the temporal cortex undergo cell death following transient suppression of electrical activity, suggesting a causal role for activity disruption in neurodegeneration. Here we demonstrate that electrical arrest of this circuit stimulates the injury-response transcription factor c-Jun. Entorhinal silencing induces transcriptional changes consistent with c-Jun activation that share characteristics of gene signatures in other neuronal populations vulnerable to Alzheimer's disease. Despite its established role in the neuronal injury response, inhibiting c-Jun failed to ameliorate entorhinal degeneration following activity disruption. Finally, we present preliminary evidence of integrated stress response activity that may serve as an alternative hypothesis to what drives entorhinal degeneration after silencing. Our data demonstrate that c-Jun is activated in response to neuronal silencing in the entorhinal cortex but is decoupled from subsequent neurodegeneration.

Comprehensive single-cell and bulk transcriptomic analyses to develop an NK cell-derived gene signature for prognostic assessment and precision medicine in breast cancer

BackgroundNatural killer (NK) cells play crucial roles in mediating anti-cancer activity in breast cancer (BRCA). However, the potential of NK cell-related molecules in predicting BRCA outcomes and guiding personalized therapy remains largely unexplored. This study focused on developing a prognostic and therapeutic prediction model for BRCA by incorporating NK cell-related genes.MethodsThe data analyzed primarily originated from the TCGA and GEO databases. The prognostic role of NK cells was evaluated, and marker genes of NK cells were identified via single-cell analysis. Module genes closely associated with immunotherapy resistance were identified by bulk transcriptome-based weighted correlation network analysis (WGCNA). Following taking intersection and LASSO regression, NK-related genes (NKRGs) relevant to BRCA prognosis were screened, and the NK-related prognostic signature was subsequently constructed. Analyses were further expanded to clinicopathological relevance, GSEA, tumor microenvironment (TME) analysis, immune function, immunotherapy responsiveness, and chemotherapeutics. Key NKRGs were screened by machine learning and validated by spatial transcriptomics (ST) and immunohistochemistry (IHC).ResultsTumor-infiltrating NK cells are a favorable prognostic factor in BRCA. By combining scRNA-seq and bulk transcriptomic analyses, we identified 7 NK-related prognostic NKRGs (CCL5, EFHD2, KLRB1, C1S, SOCS3, IRF1, and CCND2) and developed an NK-related risk scoring (NKRS) system. The prognostic reliability of NKRS was verified through survival and clinical relevance analyses across multiple cohorts. NKRS also demonstrated robust predictive power in various aspects, including TME landscape, immune functions, immunotherapy responses, and chemotherapeutic sensitivity. Additionally, KLRB1 and CCND2 emerged as key prognostic NKRGs identified through machine learning and external validation, with their expression correlation with NK cells confirmed in BRCA specimens by ST and IHC.ConclusionsWe developed a novel NK-related gene signature that has proven valuable for evaluating prognosis and treatment response in BRCA, expecting to advance precision medicine of BRCA.