Systematic dissection of tumor-normal single-cell ecosystems across a thousand tumors of 30 cancer types.

The complexity of the tumor microenvironment poses significant challenges in cancer therapy. Here, to comprehensively investigate the tumor-normal ecosystems, we perform an integrative analysis of 4.9 million single-cell transcriptomes from 1070 tumor and 493 normal samples in combination with pan-cancer 137 spatial transcriptomics, 8887 TCGA, and 1261 checkpoint inhibitor-treated bulk tumors. We define a myriad of cell states constituting the tumor-normal ecosystems and also identify hallmark gene signatures across different cell types and organs. Our atlas characterizes distinctions between inflammatory fibroblasts marked by AKR1C1 or WNT5A in terms of cellular interactions and spatial co-localization patterns. Co-occurrence analysis reveals interferon-enriched community states including tertiary lymphoid structure (TLS) components, which exhibit differential rewiring between tumor, adjacent normal, and healthy normal tissues. The favorable response of interferon-enriched community states to immunotherapy is validated using immunotherapy-treated cancers (n = 1261) including our lung cancer cohort (n = 497). Deconvolution of spatial transcriptomes discriminates TLS-enriched from non-enriched cell types among immunotherapy-favorable components. Our systematic dissection of tumor-normal ecosystems provides a deeper understanding of inter- and intra-tumoral heterogeneity.

Predicting prognosis through the discovery of specific biomarkers according to colorectal cancer lymph node metastasis.

Colorectal cancer (CRC) is a prevalent cancer worldwide, ranking as the third most common cancer and the second leading cause of cancer-related deaths. The presence or absence of lymph node metastases is one of the representative markers for predicting CRC prognosis, but often yields heterogeneous results. In this study, we conducted an integrative molecular analysis of CRC using publicly available data from The Cancer Genome Atlas database and NCBI's Gene Expression Omnibus. Through our analysis, we identified 372 upregulated genes that were differentially expressed in CRC patients. Additionally, Kyoto Encyclopedia of Genes and Genomes analysis revealed five significant pathways, including Hippo, FC-gamma, and forkhead box O signaling pathways, which are known to be associated with cancer. Survival analysis of 28 genes involved in these pathways led to the identification of 13 genes with prognostic significance (P < 0.05). To validate our findings, logistic regression models were generated and tested in multiple cohorts, demonstrating significant accuracy. Moreover, we identified six genes (BNIP3, CD63, RDX, RGCC, WASF1, and WASF3) whose combination predicted the best prognosis based on survival analysis. This predictive model holds promise as a potential biomarker for prognosis, survival, and treatment efficacy. In conclusion, our study provides valuable insights into the molecular characteristics of CRC and identifies prognostic biomarkers. The combination of differentially expressed genes and their involvement in cancer-related pathways enhances our understanding of CRC pathogenesis and opens avenues for personalized treatment approaches and improved patient outcomes.

AXL+SIGLEC6+ dendritic cells in cerebrospinal fluid and brain tissues of patients with autoimmune inflammatory demyelinating disease of CNS.

Inflammatory demyelinating disease of the CNS (IDD) is a heterogeneous group of autoimmune diseases, and multiple sclerosis is the most common type. Dendritic cells (DCs), major antigen-presenting cells, have been proposed to play a central role in the pathogenesis of IDD. The AXL+SIGLEC6+ DC (ASDC) has been only recently identified in humans and has a high capability of T cell activation. Nevertheless, its contribution to CNS autoimmunity remains still obscure. Here, we aimed to identify the ASDC in diverse sample types from IDD patients and experimental autoimmune encephalomyelitis (EAE). A detailed analysis of DC subpopulations using single-cell transcriptomics for the paired cerebrospinal fluid (CSF) and blood samples of IDD patients (total n = 9) revealed that three subtypes of DCs (ASDCs, ACY3+ DCs, and LAMP3+ DCs) were overrepresented in CSF compared with their paired blood. Among these DCs, ASDCs were also more abundant in CSF of IDD patients than in controls, manifesting poly-adhesional and stimulatory characteristics. In the brain biopsied tissues of IDD patients, obtained at the acute attack of disease, ASDC were also frequently found in close contact with T cells. Lastly, the frequency of ASDC was found to be temporally more abundant in acute attack of disease both in CSF samples of IDD patients and in tissues of EAE, an animal model for CNS autoimmunity. Our analysis suggests that the ASDC might be involved in the pathogenesis of CNS autoimmunity.

Single-cell analysis of platelets from patients with periodontitis and diabetes.

Background: Blood platelets are known to play a role in the development of atherosclerotic disease, thrombi, and hemostasis. Investigation of blood platelet transcriptome could provide evidence of disorders that increase vulnerability to cardiovascular disease. However, research on the molecular insights of platelet activation in patients with periodontitis and patients with periodontitis and type 2 diabetes mellitus (DM) is still lacking. Objectives: In this study, we analyzed expression in blood platelets from patients with periodontitis and patients with concurrent periodontitis and DM to examine the transcriptomic profile of platelets induced by periodontitis and the modifying effects of DM. Methods: We obtained the transcriptional profiles of blood platelets from 11 healthy donors, 10 patients with periodontitis, and 6 patients with periodontitis and DM using single-cell RNA sequencing. The biological processes and coexpressed modules of transcriptionally altered genes were further explored. Results: Both the patients with periodontitis and DM and those with periodontitis without DM showed higher levels of platelet activation and coagulation signals than the healthy individuals. Platelets from the patients with periodontitis had higher expression levels of genes for RHO GTPase effectors, whereas platelets from the patients with periodontitis and DM demonstrated higher expression of genes involved in oxidative phosphorylation and cellular responses to stress than those from the controls. However, compared with the patients with only periodontitis, those with periodontitis and DM presented a lower expression level of genes for hemostasis and platelet receptors. Conclusion: These results suggest that periodontitis contributes to establishment of blood coagulation via platelet dysregulation, whereas the comorbidities of patients with periodontitis and DM impair the components of platelets, thus preventing normal functions.

Single-cell mapping of combinatorial target antigens for CAR switches using logic gates.

Identification of optimal target antigens that distinguish cancer cells from normal surrounding tissue cells remains a key challenge in chimeric antigen receptor (CAR) cell therapy for tumors with intratumoral heterogeneity. In this study, we dissected tissue complexity to the level of individual cells through the construction of a single-cell expression atlas that integrates ~1.4 million tumor, tumor-infiltrating normal and reference normal cells from 412 tumors and 12 normal organs. We used a two-step screening method using random forest and convolutional neural networks to select gene pairs that contribute most to discrimination between individual malignant and normal cells. Tumor coverage and specificity are evaluated for the AND, OR and NOT logic gates based on the combinatorial expression pattern of the pairing genes across individual single cells. Single-cell transcriptome-coupled epitope profiling validates the AND, OR and NOT switch targets identified in ovarian cancer and colorectal cancer.

Differential microbiota network in gingival tissues between periodontitis and periodontitis with diabetes.

Periodontitis and diabetes mellitus (DM) have a bidirectional relationship. Periodontitis is initiated by dysbiosis of oral microorganisms, and in particular, the characteristics of the microorganisms that have penetrated the tissue are directly related to the disease; therefore, we investigated the effect of DM on intragingival microbial profiling of patients with periodontitis. A total of 39 subjects were recruited and divided into three groups in this case control study as follows: healthy (NA, 10), periodontitis only (PD, 18), and periodontitis with DM (PD_DM, 11). Gingival tissue was collected, DNA was extracted, and whole-genome sequencing was performed. PD and PD_DM showed different characteristics from NA in diversity and composition of the microbial community; however, no difference was found between the PD nad PD_DM. PD_DM showed discriminatory characteristics for PD in the network analysis. PD showed a network structure in which six species were connected, including three red complex species, and PD_DM's network was more closely connected and expanded, with six additional species added to the PD network. Although DM did not significantly affect α- and ß-diversity or abundance of phyla and genera of microbiota that invaded the gingival tissue of patients with periodontitis, DM will affect the progression of periodontitis by strengthening the bacterial network in the gingival tissue.

Single-cell RNA sequencing reveals rebalancing of immunological response in patients with periodontitis after non-surgical periodontal therapy.

BACKGROUND: Periodontitis is a major inflammatory disease of the oral mucosa that is not limited to the oral cavity but also has systemic consequences. Although the importance of chronic periodontitis has been emphasized, the systemic immune response induced by periodontitis and its therapeutic effects remain elusive. Here, we report the transcriptomes of peripheral blood mononuclear cells (PBMCs) from patients with periodontitis. METHODS: Using single-cell RNA sequencing, we profiled PBMCs from healthy controls and paired pre- and post-treatment patients with periodontitis. We extracted differentially expressed genes and biological pathways for each cell type and calculated activity scores reflecting cellular characteristics. Intercellular crosstalk was classified into therapy-responsive and -nonresponsive pathways. RESULTS: We analyzed pan-cellular differentially expressed genes caused by periodontitis and found that most cell types showed a significant increase in CRIP1, which was further supported by the increased levels of plasma CRIP1 observed in patients with periodontitis. In addition, activated cell type-specific ligand-receptor interactions, including the BTLA, IFN-γ, and RESISTIN pathways, were prominent in patients with periodontitis. Both the BTLA and IFN-γ pathways returned to similar levels in healthy controls after periodontal therapy, whereas the RESISTIN pathway was still activated even after therapy. CONCLUSION: These data collectively provide insights into the transcriptome changes and molecular interactions that are responsive to periodontal treatment. We identified periodontitis-specific systemic inflammatory indicators and suggest unresolved signals of non-surgical therapy as future therapeutic targets.

Observation of spin-glass-like characteristics in ferrimagnetic TbCo through energy-level-selective approach.

Rare earth (RE)-transition metal (TM) ferrimagnetic alloys are gaining increasing attention because of their potential use in the field of antiferromagnetic spintronics. The moment from RE sub-lattice primarily originates from the 4f-electrons located far below the Fermi level (EF), and the moment from TM sub-lattice arises from the 3d-electrons across the EF. Therefore, the individual magnetic moment configurations at different energy levels must be explored to clarify the microscopic mechanism of antiferromagnetic spin dynamics. Considering these issues, here we investigate the energy-level-selective magnetic moment configuration in ferrimagnetic TbCo alloy. We reveal that magnetic moments at deeper energy levels are more easily altered by the external magnetic field than those near the EF. More importantly, we find that the magnetic moments at deeper energy levels exhibit a spin-glass-like characteristics such as slow dynamics and magnetic moment freezing whereas those at EF do not. These unique energy-level-dependent characteristics of RE-TM ferrimagnet may provide a better understanding of ferrimagnet, which could be useful in spintronic applications as well as in spin-glass studies.

Role of PCK2 in the proliferation of vascular smooth muscle cells in neointimal hyperplasia.

Vascular smooth muscle cell (VSMC) proliferation is a hallmark of neointimal hyperplasia (NIH) in atherosclerosis and restenosis post-balloon angioplasty and stent insertion. Although numerous cytotoxic and cytostatic therapeutics have been developed to reduce NIH, it is improbable that a multifactorial disease can be successfully treated by focusing on a preconceived hypothesis. We, therefore, aimed to identify key molecules involved in NIH via a hypothesis-free approach. We analyzed four datasets (GSE28829, GSE43292, GSE100927, and GSE120521), evaluated differentially expressed genes (DEGs) in wire-injured femoral arteries of mice, and determined their association with VSMC proliferation in vitro. Moreover, we performed RNA sequencing on platelet-derived growth factor (PDGF)-stimulated human VSMCs (hVSMCs) post-phosphoenolpyruvate carboxykinase 2 (PCK2) knockdown and investigated pathways associated with PCK2. Finally, we assessed NIH formation in Pck2 knockout (KO) mice by wire injury and identified PCK2 expression in human femoral artery atheroma. Among six DEGs, only PCK2 and RGS1 showed identical expression patterns between wire-injured femoral arteries of mice and gene expression datasets. PDGF-induced VSMC proliferation was attenuated when hVSMCs were transfected with PCK2 siRNA. RNA sequencing of PCK2 siRNA-treated hVSMCs revealed the involvement of the Akt-FoxO-PCK2 pathway in VSMC proliferation via Akt2, Akt3, FoxO1, and FoxO3. Additionally, NIH was attenuated in the wire-injured femoral artery of Pck2-KO mice and PCK2 was expressed in human femoral atheroma. PCK2 regulates VSMC proliferation in response to vascular injury via the Akt-FoxO-PCK2 pathway. Targeting PCK2, a downstream signaling mediator of VSMC proliferation, may be a novel therapeutic approach to modulate VSMC proliferation in atherosclerosis.

DeepCIA: a novel deep-learning model for cancer type identification using class activation map via transcription factor expression.

Deep learning methods are powerful analytical tools for large-scale data analysis. Here, we introduce DeepCIA as a novel diagnostic deep-learning model for cancer type identification using a class activation map via transcription factor expression. Although many deep learning researches attempts have recently been made in relation to cancer diagnosis, there are difficulties in using cancer data due to a large-scale problem. Therefore, From The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) public databases, we selected transcription factor expression profiles of eight cancer types. TCGA included 3496 samples and divided the train and validation sets in an 8:2 ratio. ICGC included 552 samples and was used as a test set for external validation. To compare the performance of 1D-CNN models, we also used SVM and KNN from machine learning. In external validation, 1D-CNN showed a high average accuracy of 98% and was superior to support vector machine (SVM) and k-nearest neighbor (KNN) with a difference in the accuracy of 10-12%. Also, 1D-CNN performed very well in several performance metrics (98.2% Recall, 98.1% Precision, 98.2% F score, 99.8% Specificity, 99.8% AUC, and 99.0% Balanced Accuracy). In each data set evaluation, 1-network, 5-network, and 2-network with high accuracy were selected and visualized through the Class Activation Map. We identified the Cys2Hys2 zinc finger group with the highest distribution across all cancer types. Collectively, DeepCIA can be used as a decision support system for cancer and a classifier for diagnosing unknown primary cancer, while emphasizing its usefulness in cancer diagnosis.

Risk stratification of patients with right-sided colorectal cancer based on the tumor-infiltrating M1 macrophage.

The homing of M1 and M2 macrophages may play distinct roles in the tumor microenvironment (TME). However, these roles of macrophages in the TME remain unclear. We downloaded RNA sequencing data from The Cancer Genome Atlas (TCGA) database for patients with CRC. Subsequently, Kaplan-Meier survival curves were generated to assess the differential infiltration of M1 and M2 macrophages based on CRC location. Differentially expressed gene (DEG) and functional analyses were performed to screen the roles of DEGs. Critical prognostic genes were identified using least absolute shrinkage and selection operator regression. The risk scores were calculated for each patient. In patients with right-sided CRC, reduced M1 macrophage infiltration was associated with poor prognosis. M1 macrophage infiltration positively correlated with CD8+ T cell infiltration. A risk model was developed and validated for performance using GSE103479 and GSE72970. Nine genes were identified as independent prognostic genes that could be potential biomarkers for effectively predicting survival in patients with right-sided CRC. Kaplan-Meier curves for overall survival and progression-free survival analyses revealed that the high-risk group of patients with right-sided CRC had a poor prognosis. This novel M1 macrophage-related risk model may provide a gene signature for predicting the survival outcomes of patients with right-sided CRC and facilitate further studies examining the relationship between infiltration of M1 macrophages and the prognosis of such patients.

Genetic factors affecting dopaminergic deterioration during the premotor stage of Parkinson disease.

To estimate dopaminergic dysfunction in patients with Parkinson disease (PD) during the premotor stage and to investigate the effect of genetic factors on the trajectories. Using longitudinal dopamine transporter single-photon emission computed tomography data from 367 sporadic PD (sPD), 72 LRRK2 (G2019S), and 39 GBA (N370S) PD patients in the Parkinson's Progression Markers Initiative (PPMI) study, we estimated the temporal trajectories of putaminal-specific binding ratios using an integrating function between baseline values and their annual change rates. In order to test reproducibility, we computed another trajectory for sPD using positron emission tomography data of 38 sPD patients at Gangnam Severance Hospital (GSH). Temporal trajectories of sPD were compared between the groups separated by age at onset (AAO) and polygenic load for common PD risk variants, and also compared with genetic PD. sPD patients in both the PPMI and GSH cohorts showed similar onset of dopaminergic degeneration around 10 years before motor onset. Early-onset PD patients exhibited later onset of degeneration and a faster decline in dopaminergic activity during the premotor period than late-onset patients. sPD patients with high polygenic load were associated with earlier onset and slower progression of dopaminergic dysfunction. Compared to the sPD and LRRK2 PD groups, GBA PD patients exhibited faster deterioration of dopaminergic function during the premotor stage. Dopaminergic dysfunction in PD appears to start about 10 years before motor onset. Genetic factors may be contributing to the heterogeneity of dopaminergic deterioration during the premotor stage.

SOCS3 is Related to Cell Proliferation in Neuronal Tissue: An Integrated Analysis of Bioinformatics and Experiments.

Glioma is the most common primary malignant tumor that occurs in the central nervous system. Gliomas are subdivided according to a combination of microscopic morphological, molecular, and genetic factors. Glioblastoma (GBM) is the most aggressive malignant tumor; however, efficient therapies or specific target molecules for GBM have not been developed. We accessed RNA-seq and clinical data from The Cancer Genome Atlas, the Chinese Glioma Genome Atlas, and the GSE16011 dataset, and identified differentially expressed genes (DEGs) that were common to both GBM and lower-grade glioma (LGG) in three independent cohorts. The biological functions of common DEGs were examined using NetworkAnalyst. To evaluate the prognostic performance of common DEGs, we performed Kaplan-Meier and Cox regression analyses. We investigated the function of SOCS3 in the central nervous system using three GBM cell lines as well as zebrafish embryos. There were 168 upregulated genes and 50 downregulated genes that were commom to both GBM and LGG. Through survival analyses, we found that SOCS3 was the only prognostic gene in all cohorts. Inhibition of SOCS3 using siRNA decreased the proliferation of GBM cell lines. We also found that the zebrafish ortholog, socs3b, was associated with brain development through the regulation of cell proliferation in neuronal tissue. While additional mechanistic studies are necessary, our results suggest that SOCS3 is an important biomarker for glioma and that SOCS3 is related to the proliferation of neuronal tissue.

Possible respiratory syncytial virus infection presenting as diffuse alveolar hemorrhage in an elderly treated with systemic corticosteroid: A case report.

INTRODUCTION: Respiratory syncytial virus infection is gaining interest in the elderly due to its growing morbidity and mortality. We present a Case of respiratory syncytial virus infection presenting as diffuse alveolar hemorrhage that was highly responsive to systemic corticosteroid in an elderly patient. CASE PRESENTATION: An 82-year old man was admitted to the intensive care unit with worsening hypoxic respiratory failure. Chest radiograph showed non-homogeneous air space opacities. Bronchoalveolar lavage showed a finding of alveolar hemorrhage. The diagnosis of diffuse alveolar hemorrhage was made and high-dose systemic corticosteroid was given. However, concomitant respiratory syncytial virus infection was later confirmed. Therefore, ribavirin and human immunoglobulin were added. During the course of his treatment, the steroid was stopped and restarted. Interestingly, the clinical course was highly responsive to systemic corticosteroid. CONCLUSION: It appears that diffuse alveolar hemorrhage in this patient may have been due to an immunological process caused by respiratory syncytial virus. Therefore, corticosteroid therapy was highly effective in improving the patient's hemoptysis and hypoxic respiratory failure. We suggest that further studies are required on the use of steroid in this subset of patients with respiratory syncytial virus lower respiratory tract infection.

Novel deep learning-based survival prediction for oral cancer by analyzing tumor-infiltrating lymphocyte profiles through CIBERSORT.

The tumor microenvironment (TME) within mucosal neoplastic tissue in oral cancer (ORCA) is greatly influenced by tumor-infiltrating lymphocytes (TILs). Here, a clustering method was performed using CIBERSORT profiles of ORCA data that were filtered from the publicly accessible data of patients with head and neck cancer in The Cancer Genome Atlas (TCGA) using hierarchical clustering where patients were regrouped into binary risk groups based on the clustering-measuring scores and survival patterns associated with individual groups. Based on this analysis, clinically reasonable differences were identified in 16 out of 22 TIL fractions between groups. A deep neural network classifier was trained using the TIL fraction patterns. This internally validated classifier was used on another individual ORCA dataset from the International Cancer Genome Consortium data portal, and patient survival patterns were precisely predicted. Seven common differentially expressed genes between the two risk groups were obtained. This new approach confirms the importance of TILs in the TME and provides a direction for the use of a novel deep-learning approach for cancer prognosis.

Proton Pump Inhibitor Use and the Efficacy of Chemotherapy in Metastatic Colorectal Cancer: A Post Hoc Analysis of a Randomized Phase III Trial (AXEPT).

BACKGROUND: Concomitant use of proton pump inhibitors (PPIs) with capecitabine was suggested to be associated with poor outcomes in gastrointestinal cancers. We analyzed the differential impact of PPI use on capecitabine and fluorouracil using the data set from the AXEPT trial, a phase III randomized trial that demonstrated the noninferiority of mXELIRI (modified XELIRI: capecitabine plus irinotecan) to FOLFIRI (leucovorin, fluorouracil, and irinotecan), either with or without bevacizumab in patients with metastatic colorectal cancer. PATIENTS AND METHODS: Out of the per-protocol set (n = 620), patients with information on concomitant medications (n = 482) were included in this post hoc analysis. PPI use was defined as concomitant exposure of capecitabine and the use of any PPI for 20% or more of the study period. The treatment-by-PPI-use interaction was examined after adjusting for stratification factors. RESULTS: Of the 482 patients, 49 (10.1%) used PPI. Among the PPI users, the mXELIRI group tended to have poorer overall survival compared with the FOLFIRI group. In contrast, among the nonusers, the overall survival of the mXELIRI group was significantly better than that of the FOLFIRI group. Similarly, a trend of worse progression-free survival with mXELIRI compared with FOLFIRI was observed in PPI users but not in nonusers. Treatment-by-PPI-use interaction was significant for overall survival and progression-free survival. CONCLUSION: The significant interaction between PPI use and the type of fluoropyrimidine in terms of overall and progression-free survival suggests that fluorouracil could be a more favorable option than capecitabine for patients with metastatic colorectal cancer using PPIs. IMPLICATIONS FOR PRACTICE: This study showed a significant interaction between the use of proton pump inhibitors (PPIs) and the type of fluoropyrimidines. This interaction mainly comes from the positive impact of PPIs in the survival outcomes in the fluorouracil arm rather than a negative impact of PPIs in the capecitabine arm. The possible drug-drug interaction shown in this study suggests that fluorouracil, rather than capecitabine, could be a more appropriate choice of fluoropyrimidine for patients who are taking PPIs in the treatment of metastatic colorectal cancer.

Identification of Shared Genes and Pathways in Periodontitis and Type 2 Diabetes by Bioinformatics Analysis.

Introduction: It is well known that the presence of diabetes significantly affects the progression of periodontitis and that periodontitis has negative effects on diabetes and diabetes-related complications. Although this two-way relationship between type 2 diabetes and periodontitis could be understood through experimental and clinical studies, information on common genetic factors would be more useful for the understanding of both diseases and the development of treatment strategies. Materials and Methods: Gene expression data for periodontitis and type 2 diabetes were obtained from the Gene Expression Omnibus database. After preprocessing of data to reduce heterogeneity, differentially expressed genes (DEGs) between disease and normal tissue were identified using a linear regression model package. Gene ontology and Kyoto encyclopedia of genes and genome pathway enrichment analyses were conducted using R package 'vsn'. A protein-protein interaction network was constructed using the search tool for the retrieval of the interacting genes database. We used molecular complex detection for optimal module selection. CytoHubba was used to identify the highest linkage hub gene in the network. Results: We identified 152 commonly DEGs, including 125 upregulated and 27 downregulated genes. Through common DEGs, we constructed a protein-protein interaction and identified highly connected hub genes. The hub genes were up-regulated in both diseases and were most significantly enriched in the Fc gamma R-mediated phagocytosis pathway. Discussion: We have identified three up-regulated genes involved in Fc gamma receptor-mediated phagocytosis, and these genes could be potential therapeutic targets in patients with periodontitis and type 2 diabetes.

Molecular differences between stable idiopathic pulmonary fibrosis and its acute exacerbation.

INTRODUCTION: The molecular mechanisms underlying acute exacerbations (AEs) of idiopathic pulmonary fibrosis (IPF) are poorly understood. To understand the gene expression patterns of the AEs of IPF, we studied gene expression profiling of AEs of IPF. METHODS: The GEO datasets included in this study are GSE44723 and GSE10667, and in-house RNA-seq data were used. DEG analysis used the limma package, and the STRING database was used to construct the protein-protein interaction (PPI) network, and its functional role was investigated through gene ontology analysis. RESULTS: The results of DEG analysis indicated 76 upregulated and 135 downregulated genes associated with an AE of IPF compared to stable IPF. The PPI network included three core modules containing 24 of the 211 DEGs. Eleven upregulated and six downregulated genes were evident in AEs of IPF compared with stable IPF after validation. The upregulated genes were associated with cell division. The downregulated genes were related to skeletal muscle differentiation and development. CONCLUSION: In previous studies, 17 genes were strongly associated with cell proliferation in various cell types. In particular, cyclin A2 (CCNA2) was overexpressed in the alveolar epithelium of the lungs presenting AEs of IPF. Aside from the previously described CCNA2, this study reveals 16 genes associated with AEs of IPF. This data could indicate new therapeutic targets and potential biomarkers for the AEs of IPF.

FRZB as a key molecule in abdominal aortic aneurysm progression affecting vascular integrity.

Abdominal aortic aneurysm (AAA), when ruptured, results in high mortality. The identification of molecular pathways involved in AAA progression is required to improve AAA prognosis. The aim of the present study was to assess the key genes for the progression of AAA and their functional role. Genomic and clinical data of three independent cohorts were downloaded from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) (GSE57691, GSE7084, and GSE98278). To develop AAA diagnosis and progression-related differentially expressed genes (DEGs), we used a significance analysis of microarray (SAM). Spearman correlation test and gene set analysis were performed to identify potential enriched pathways for DEGs. Only the Frizzled-related protein (FRZB) gene and chromosome 1 open reading frame 24 (C1orf24) exhibited significant down-regulation in all analyses. With FRZB, the pathways were associated with RHO GTPase and elastin fiber formation. With C1orf24, the pathways were elastic fiber formation, extracellular matrix organization, and cell-cell communication. Since only FRZB was evolutionally conserved in the vertebrates, function of FRZB was validated using zebrafish embryos. Knockdown of frzb remarkably reduced vascular integrity in zebrafish embryos. We believe that FRZB is a key gene involved in AAA initiation and progression affecting vascular integrity.