FCN3 functions as a tumor suppressor of lung adenocarcinoma through induction of endoplasmic reticulum stress

HCCDB v2.0: Decompose Expression Variations by Single-cell RNA-seq and Spatial Transcriptomics in HCC

Large-scale transcriptomic data are crucial for understanding the molecular features of hepatocellular carcinoma (HCC). Integrated 15 transcriptomic datasets of HCC clinical samples, the first version of HCC database (HCCDB v1.0) was released in 2018. Through the meta-analysis of differentially expressed genes and prognosis-related genes across multiple datasets, it provides a systematic view of the altered biological processes and the inter-patient heterogeneities of HCC with high reproducibility and robustness. With four years having passed, the database now needs integration of recently published datasets. Furthermore, the latest single-cell and spatial transcriptomics have provided a great opportunity to decipher complex gene expression variations at the cellular level with spatial architecture. Here, we present HCCDB v2.0, an updated version that combines bulk, single-cell, and spatial transcriptomic data of HCC clinical samples. It dramatically expands the bulk sample size by adding 1656 new samples from 11 datasets to the existing 3917 samples, thereby enhancing the reliability of transcriptomic meta-analysis. A total of 182,832 cells and 69,352 spatial spots are added to the single-cell and spatial transcriptomics sections, respectively. A novel single-cell level and 2-dimension (sc-2D) metric is proposed as well to summarize cell type-specific and dysregulated gene expression patterns. Results are all graphically visualized in our online portal, allowing users to easily retrieve data through a user-friendly interface and navigate between different views. With extensive clinical phenotypes and transcriptomic data in the database, we show two applications for identifying prognosis-associated cells and tumor microenvironment. HCCDB v2.0 is available at http://lifeome.net/database/hccdb2.

Ficolin 3 promotes ferroptosis in HCC by downregulating IR/SREBP axis-mediated MUFA synthesis

BACKGROUND

Targeting ferroptosis has been identified as a promising approach for the development of cancer therapies. Monounsaturated fatty acid (MUFA) is a type of lipid that plays a crucial role in inhibiting ferroptosis. Ficolin 3 (FCN3) is a component of the complement system, serving as a recognition molecule against pathogens in the lectin pathway. Recent studies have reported that FCN3 demonstrates inhibitory effects on the progression of certain tumors. However, whether FCN3 can modulate lipid metabolism and ferroptosis remains largely unknown.

METHODS

Cell viability, BODIPY-C11 staining, and MDA assay were carried out to detect ferroptosis. Primary hepatocellular carcinoma (HCC) and xenograft models were utilized to investigate the effect of FCN3 on the development of HCC in vivo. A metabonomic analysis was conducted to assess alterations in intracellular and HCC intrahepatic lipid levels.

RESULTS

Our study elucidates a substantial decrease in the expression of FCN3, a component of the complement system, leads to MUFA accumulation in human HCC specimens and thereby significantly promotes ferroptosis resistance. Overexpression of FCN3 efficiently sensitizes HCC cells to ferroptosis, resulting in the inhibition of the oncogenesis and progression of both primary HCC and subcutaneous HCC xenograft. Mechanistically, FCN3 directly binds to the insulin receptor β (IR-β) and its pro-form (pro-IR), inhibiting pro-IR cleavage and IR-β phosphorylation, ultimately resulting in IR-β inactivation. This inactivation of IR-β suppresses the expression of sterol regulatory element binding protein-1c (SREBP1c), which subsequently suppresses the transcription of genes related to de novo lipogenesis (DNL) and lipid desaturation, and consequently downregulates intracellular MUFA levels.

CONCLUSIONS

These findings uncover a novel regulatory mechanism by which FCN3 enhances the sensitivity of HCC cells to ferroptosis, indicating that targeting FCN3-induced ferroptosis is a promising strategy for HCC treatment.

Identification of Hub Genes in Liver Hepatocellular Carcinoma Based on Weighted Gene Co-expression Network Analysis

Liver hepatocellular carcinoma (LIHC) is a malignant cancer with high incidence and poor prognosis. To investigate the correlation between hub genes and progression of LIHC and to provided potential prognostic markers and therapy targets for LIHC. Our study mainly used The Cancer Genome Atlas (TCGA) LIHC database and the gene expression profiles of GSE54236 from the Gene Expression Omnibus (GEO) to explore the differential co-expression genes between LIHC and normal tissues. The differential co-expression genes were extracted by Weighted Gene Co-expression Network Analysis (WGCNA) and differential gene expression analysis methods. The Genetic Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were carried out to annotate the function of differential genes. Then the hub genes were validated using protein-protein interaction (PPI) network. And the expression level and prognostic analysis were performed. The probable associations between the expression of hub genes and both tumor purity and infiltration of immune cells were explored by TIMER. A total of 68 differential co-expression genes were extracted. These genes were mainly enriched in complement activation (biological process), collagen trimer (cellular component), carbohydrate binding and receptor ligand activity (molecular function) and cytokine - cytokine receptor interaction. Then we demonstrated that the 10 hub genes (CFP, CLEC1B, CLEC4G, CLEC4M, FCN2, FCN3, PAMR1 and TIMD4) were weakly expressed in LIHC tissues, the qRT-PCR results of clinical samples showed that six genes were significantly downregulated in LIHC patients compared with adjacent tissues. Worse overall survival (OS) and disease-free survival (DFS) in LIHC patients were associated with the lower expression of CFP, CLEC1B, FCN3 and TIMD4. Ten hub genes had positive association with tumor purity. CFP, CLEC1B, FCN3 and TIMD4 could serve as novel potential molecular targets for prognosis prediction in LIHC.

Prognostic correlation between specialized capillary endothelial cells and lung adenocarcinoma

Background

In-depth analysis of the functional changes occurring in endothelial cells (ECs) involved in capillary formation can help to elucidate the mechanism of tumour vascular growth.

Methods

Appropriate datasets were retrieved from the GEO database to obtain single-cell data on LUAD samples and adjacent normal tissue samples. ECs were selected by an automatic annotation program in R and further subdivided based on reported EC marker genes. Functional changes in different types of capillary ECs were then visualized, and the concrete expression was classified by genetic data in the TCGA. Finally, a prognostic model was constructed to predict immunoinfiltration status, survival and drug therapy effects.

Results

The LUAD data contained in the GSE183219 dataset were suitable for our analysis. After dimensionality reduction analysis and cell annotation, EC general capillary and EC aerocyte subsets as capillary specialized phenotypes showed a series of functional changes in tumour samples, with a total of 108 genes found to undergo functional changes. Use of CellPhoneDB revealed a close interaction of activity between ECs. After integration of TCGA, GSE68465 and GSE11969 datasets, the genes obtained were analysed by cluster analysis and risk model construction, identifying 8 genes. Drug sensitivity, immune cell and molecular differences can be accurately predicted.

Conclusions

EC general capillary and EC aerocyte subsets are recognized capillary ECs in the tumour microenvironment, and the functional changes between them are relevant to the prognosis and treatment of LUAD patients and have the potential to be used in target therapy.

Ficolin-A/2 Aggravated Severe Lung Injury through Neutrophil Extracellular Traps Mediated by Gasdermin D-Induced Pyroptosis

Neutrophil extracellular traps (NETs) and pyroptosis are critical events in lung injury. This study investigated whether ficolin-A influences NET formation through pyroptosis to exacerbate lipopolysaccharide (LPS)-induced lung injury. The expression of ficolin-A/2, NETs, and pyroptosis-related molecules was investigated in animal and cell models. Knockout and knockdown (recombinant protein) methods were used to elucidate regulatory mechanisms. The Pearson correlation coefficient was used to analyze the correlation between ficolins and pyroptosis- and NET-related markers in clinical samples. In this study, ficolin-2 (similar to ficolin-A) showed significant overexpression in patients with acute respiratory distress syndrome. In vivo, knockout of ficolin-A, but not ficolin-B, attenuated lung inflammation and inhibited NET formation in the LPS-induced mouse model. DNase I further alleviated lung inflammation and NET formation in ficolin-A knockout mice. In vitro, neutrophils derived from Fcna-/- mice showed less pyroptosis and necroptosis than those from the control group after LPS stimulation. Additionally, gasdermin D knockdown or Nod-like receptor protein 3 inhibitor reduced NET formation. Addition of recombinant ficolin-2 protein to human peripheral blood neutrophils promoted NET formation and pyroptosis after LPS stimulation, whereas ficolin-2 knockdown had the opposite effect. Acute respiratory distress syndrome patients showed increased levels of pyroptosis- and NET-related markers, which were correlated positively with ficolin-2 levels. In conclusion, these results suggested that ficolin-A/2 exacerbated NET formation and LPS-induced lung injury via gasdermin D-mediated pyroptosis.

C5a-C5aR1 induces endoplasmic reticulum stress to accelerate vascular calcification via PERK-eIF2α-ATF4-CREB3L1 pathway

AIMS

Vascular calcification (VC) predicts the morbidity and mortality in cardiovascular diseases. Vascular smooth muscle cells (VSMCs) osteogenic transdifferentiation is the crucial pathological basis for VC. To date, the molecular pathogenesis is still largely unclear. Notably, C5a-C5aR1 contributes to the development of cardiovascular diseases, and its closely related to physiological bone mineralization which is similar to VSMCs osteogenic transdifferentiation. However, the role and underlying mechanisms of C5a-C5aR1 in VC remain unexplored.

METHODS AND RESULTS

A cross-sectional clinical study was utilized to examine the association between C5a and VC. Chronic kidney diseases mice and calcifying VSMCs models were established to investigate the effect of C5a-C5aR1 in VC, evaluated by changes in calcium deposition and osteogenic markers. The cross-sectional study identified that high level of C5a was associated with increased risk of VC. C5a dose-responsively accelerated VSMCs osteogenic transdifferentiation accompanying with increased the expression of C5aR1. Meanwhile, the antagonists of C5aR1, PMX 53, reduced calcium deposition, and osteogenic transdifferentiation both in vivo and in vitro. Mechanistically, C5a-C5aR1 induced endoplasmic reticulum (ER) stress and then activated PERK-eIF2α-ATF4 pathway to accelerated VSMCs osteogenic transdifferentiation. In addition, cAMP-response element-binding protein 3-like 1 (CREB3L1) was a key downstream mediator of PERK-eIF2α-ATF4 pathway which accelerated VSMCs osteogenic transdifferentiation by promoting the expression of COL1α1.

CONCLUSIONS

High level of C5a was associated with increased risk of VC, and it accelerated VC by activating the receptor C5aR1. PERK-eIF2α-ATF4-CREB3L1 pathway of ER stress was activated by C5a-C5aR1, hence promoting VSMCs osteogenic transdifferentiation. Targeting C5 or C5aR1 may be an appealing therapeutic target for VC.

Study on Potential Differentially Expressed Genes in Idiopathic Pulmonary Fibrosis by Bioinformatics and Next-Generation Sequencing Data Analysis

Idiopathic pulmonary fibrosis (IPF) is a chronic progressive lung disease with reduced quality of life and earlier mortality, but its pathogenesis and key genes are still unclear. In this investigation, bioinformatics was used to deeply analyze the pathogenesis of IPF and related key genes, so as to investigate the potential molecular pathogenesis of IPF and provide guidance for clinical treatment. Next-generation sequencing dataset GSE213001 was obtained from Gene Expression Omnibus (GEO), and the differentially expressed genes (DEGs) were identified between IPF and normal control group. The DEGs between IPF and normal control group were screened with the DESeq2 package of R language. The Gene Ontology (GO) and REACTOME pathway enrichment analyses of the DEGs were performed. Using the g:Profiler, the function and pathway enrichment analyses of DEGs were performed. Then, a protein-protein interaction (PPI) network was constructed via the Integrated Interactions Database (IID) database. Cytoscape with Network Analyzer was used to identify the hub genes. miRNet and NetworkAnalyst databaseswereused to construct the targeted microRNAs (miRNAs), transcription factors (TFs), and small drug molecules. Finally, receiver operating characteristic (ROC) curve analysis was used to validate the hub genes. A total of 958 DEGs were screened out in this study, including 479 up regulated genes and 479 down regulated genes. Most of the DEGs were significantly enriched in response to stimulus, GPCR ligand binding, microtubule-based process, and defective GALNT3 causes HFTC. In combination with the results of the PPI network, miRNA-hub gene regulatory network and TF-hub gene regulatory network, hub genes including LRRK2, BMI1, EBP, MNDA, KBTBD7, KRT15, OTX1, TEKT4, SPAG8, and EFHC2 were selected. Cyclothiazide and rotigotinethe are predicted small drug molecules for IPF treatment. Our findings will contribute to identification of potential biomarkers and novel strategies for the treatment of IPF, and provide a novel strategy for clinical therapy.

Identification of endoplasmic reticulum stress-related signature characterizes the tumor microenvironment and predicts prognosis in lung adenocarcinoma

Lung adenocarcinoma (LUAD) remains one of the most lethal malignancies worldwide, with a high mortality rate and unfavorable prognosis. Endoplasmic reticulum (ER) stress is a key regulator of tumour growth, metastasis, and the response to chemotherapy, targeted therapies and immune response. It acts via responding to misfolded proteins and triggering abnormal activation of ER stress sensors and downstream signalling pathways. Notably, the expression patterns of ER-stress-related-genes (ERSRGs) are indicative of survival outcomes, especially in the context of immune infiltration. Through consensus clustering of prognosis-associated ERSRGs, we delineated two distinct LUAD subtypes: Cluster 1 and Cluster 2. Comprehensive analyses revealed significant disparities between these subtypes in terms of prognosis, immune cell infiltration, and tumor progression. Leveraging the robustness of LASSO regression and Multivariate stepwise regression, we constructed and validated an ER Stress-associated risk signature for LUAD. This signature underwent assessments for its prognostic value, correlation with clinical attributes, and interaction within the tumour immune microenvironment. By integrating this signature with multivariate cox analysis of distinct pathological stages, we devised an enhanced nomogram, validated through various statistical metrics, with an area under the curve for overall survival at 1, 3, and 5 years post-diagnosis being 0.79, 0.80, and 0.81, respectively. In conclusion, our findings introduce a composite signature of 11 pivotal ERSRGs, holding promise as a potent prognostic tool for LUAD, and offering insights for immunotherapeutic and targeted intervention strategies.

Potential biomarkers in peripheral blood mononuclear cells of patients with sporadic Ménière's disease based on proteomics

BACKGROUND

Ménière's disease (MD) mainly refers to the endolymphatic hydrops in membranous labyrinth of the inner ear. Application of the mass spectrometry-based proteomics techniques has not been applied in the field of MD.

OBJECTIVES

To search for potential differential proteins to identify the disease biomarkers and reveal disease bioinformatics-related mechanisms through applying protein technology to analyze the expression changes of peripheral blood mononuclear cells (PBMCs) in sporadic MD patients.

MATERIAL AND METHODS

15 MD patients and 15 healthy individuals were enrolled. PBMCs from them were extracted, and their protein expression was identified and compared by LC-MS/MS and spectra analysis.

RESULTS

There was significant difference in protein expression between MD patients and the control group. GO and KEGG analysis showed that endocytosis was involved in MD patients. Western blot results of CHMP1A and MMP9 protein showed that the expression of CHMP1A was higher in the MD group than that in the control group, while MMP9 was down-regulated. Immunohistochemistry confirmed that CHMP1A and MMP9 were expressed in the endolymphatic sacs of MD patients and in the inner ear of adult mice.

CONCLUSIONS AND SIGNIFICANCE

Endocytosis may be involved in the pathogenesis of sporadic MD, furthermore CHMP1A, VPS4A, FCN3 and MMP9 could be considered as potential biomarkers.

Loss of ficolin-3 expression is associated with poor prognosis in patients with hepatocellular carcinoma

Background: Ficolin-3 (FCN3) is a well-known circulating pattern recognition molecule which plays a role in host immune responses to cancer via activation of the lectin complement pathway. Nevertheless, the clinical significance of FCN3 in patients with hepatocellular carcinoma (HCC) is unclear. Methods: Eighty-seven HCC patients who received hepatectomy at our hospital were included. Immunohistochemical staining was used to assess the FCN3 expression in both tumorous and non-tumorous tissues from the patients, who were classified into high and low expression groups. Differences in clinicopathological characteristics between the two groups were then analyzed. Results: Survival was significantly associated with FCN3 immunohistochemical score (p for trend = 0.048). Kaplan-Meier analysis revealed a higher overall survival rate in the patients with a high FCN3 expression than in those with a low FCN3 expression (p=0.031). A high FCN3 expression in tumor tissue was independently associated with better overall survival (p=0.042). However, multivariate analysis showed that FCN3 expression was not an independent risk factor for overall survival. Conclusion: Our findings suggest that FCN3 is significantly related to the prognosis of HCC. FCN3 may be a prognostic marker in patients with HCC.

Comprehensive and deep profiling of the plasma proteome with protein corona on zeolite NaY

Proteomic characterization of plasma is critical for the development of novel pharmacodynamic biomarkers. However, the vast dynamic range renders the profiling of proteomes extremely challenging. Here, we synthesized zeolite NaY and developed a simple and rapid method to achieve comprehensive and deep profiling of the plasma proteome using the plasma protein corona formed on zeolite NaY. Specifically, zeolite NaY and plasma were co-incubated to form plasma protein corona on zeolite NaY (NaY-PPC), followed by conventional protein identification using liquid chromatography-tandem mass spectrometry. NaY was able to significantly enhance the detection of low-abundance plasma proteins, minimizing the "masking" effect caused by high-abundance proteins. The relative abundance of middle- and low-abundance proteins increased substantially from 2.54% to 54.41%, and the top 20 high-abundance proteins decreased from 83.63% to 25.77%. Notably, our method can quantify approximately 4000 plasma proteins with sensitivity up to pg/mL, compared to only about 600 proteins identified from untreated plasma samples. A pilot study based on plasma samples from 30 lung adenocarcinoma patients and 15 healthy subjects demonstrated that our method could successfully distinguish between healthy and disease states. In summary, this work provides an advantageous tool for the exploration of plasma proteomics and its translational applications.

New insight of complement system in the process of vascular calcification

The complement system defences against pathogenic microbes and modulates immune homeostasis by interacting with the innate and adaptive immune systems. Dysregulation, impairment or inadvertent activation of complement system contributes to the pathogenesis of some autoimmune diseases and cardiovascular diseases (CVD). Vascular calcification is the pivotal pathological basis of CVD, and contributes to the high morbidity and mortality of CVD. Increasing evidences indicate that the complement system plays a key role in chronic kidney diseases, atherosclerosis, diabetes mellitus and aging-related diseases, which are closely related with vascular calcification. However, the effect of complement system on vascular calcification is still unclear. In this review, we summarize current evidences about the activation of complement system in vascular calcification. We also describe the complex network of complement system and vascular smooth muscle cells osteogenic transdifferentiation, systemic inflammation, endoplasmic reticulum stress, extracellular matrix remodelling, oxidative stress, apoptosis in vascular calcification. Hence, providing a better understanding of the potential relationship between complement system and vascular calcification, so as to provide a direction for slowing the progression of this burgeoning health concern.

Identification of endoplasmic reticulum stress-related lncRNAs in lung adenocarcinoma by bioinformatics and experimental validation

BACKGROUND

Endoplasmic reticulum stress (ERs) is an important cellular self-defence mechanism, which is closely related to tumorigenesis and development. However, the role of endoplasmic reticulum stress state in the development of lung adenocarcinoma (LUAD) has not been clarified.

METHODS

The lncRNAs associated with endoplasmic reticulum stress were identified by co-expression analysis in public databases, and by the least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression modelling, we constructed a prognostic model based on endoplasmic reticulum stress-related lncRNAs (ERs-related lncRNAs), performed immune analysis, TME, TMB and clinical drug prediction for model-related risk scores, and performed correlation validation in public databases and at the human tissue level.

RESULTS

Five ERs-related lncRNAs were used to construct an ERs-related lncRNA signature (ERs-related LncSig), which can predict the prognosis of LUAD. Patients in the high-risk group had worse survival, and differences existed in immune cell infiltration, immune function, immune checkpoint analysis, tumour microenvironment (TME), tumour mutational burden (TMB), immunotherapy efficacy, and sensitivity to some commonly used chemotherapeutic agents between high and low risk groups.

CONCLUSION

Our study demonstrated that ERs-related lncRNA signature can be used for the prognostic evaluation of LUAD patients and may provide new insights into clinical decision-making and personalised medicine for LUAD.

Construction and validation of a prognostic model for lung adenocarcinoma based on endoplasmic reticulum stress-related genes

Lung adenocarcinoma (LUAD) is one of the most universal types of cancer all over the world and its morbidity continues to rise year by year. Growing evidence has demonstrated that endoplasmic reticulum stress is highly activated in cancer cells and plays a key role in regulating the fate of cancer cells. However, the role and mechanism of endoplasmic reticulum stress in lung adenocarcinoma genesis and development remains unclear. In this research, we developed a prognostic model to predict the overall survival of patients with LUAD utilizing endoplasmic reticulum stress-related genes and screened out potential small molecular compounds, which could assist the clinician in making accurate decisions and better treat LUAD patients. Firstly, we downloaded 419 endoplasmic reticulum stress-related genes (ERSRGs) from Molecular Signatures Database (MSigDB). Secondly, we obtained information about the transcriptome profiling and corresponding clinical data of 59 normal samples and 535 lung adenocarcinoma samples from The Cancer Genome Atlas (TCGA) database. Next, we used the DESeq2 package to identify differentially expressed genes related to endoplasmic reticulum stress. We performed univariate Cox, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis to establish a prognostic model for LUAD patients based on ERSRGs. Then, we carried out univariate and multivariate independent prognostic analysis of endoplasmic reticulum stress-related gene (ERSRG) score and some clinical traits of lung adenocarcinoma. Additionally, we developed a clinically applicable nomogram for predicting survival for LUAD patients over one, three, and five years. Moreover, we carried out a drug sensitivity analysis to identify novel small molecule compounds for LUAD treatment. Finally, we examined the tumor microenvironment (TME) and immune cell infiltrating analysis to explore the interactions between immune and cancer cells. 142 differentially expressed ERSRGs were identified by using the DESeq2 package. A prognostic model was built based on 7 differentially expressed ERSRGs after performing univariate Cox regression, LASSO regression, and multivariate Cox regression analysis. According to the results of univariate and multivariate independent prognostic analysis, we found ERSRG score can be used as an independent prognostic maker. Using the Kaplan-Meier curves, we found low-risk patients had higher survival probability than high-risk patients in both training set and test set. A nomogram was drawn to predict 1-, 3-, and 5-year survival probability. The calibration curves explained good performance of the model for the prediction of survival. Phenformin, OSU-03012, GSK-650394 and KIN001-135 were identified as the drugs most likely to provide important information to clinicians about the treatment of LUAD patients. A prognostic prediction model was established based on 7 differentially expressed ERSRGs (PDX1, IGFBP1, DDIT4, PPP1R3G, CFTR, DERL3 and NUPR1), which could effectively predict the prognosis of LUAD patients and give a reference for clinical doctors to help LUAD patients to make better treatment tactics. Based on the 4 small molecule compounds (Phenformin, OSU-03012, GSK-650394 and KIN001-135) we discovered, targeting endoplasmic reticulum stress-related genes may also be a therapeutic approach for LUAD patients.

Endoplasmic Reticulum Stress-Related Signature for Predicting Prognosis and Immune Features in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) with cancer cells under endoplasmic reticulum (ER) stress has a poor prognosis. This study is aimed at discovering credible biomarkers for predicting the prognosis of HCC based on ER stress-related genes (ERSRGs). We constructed a novel four-ERSRG prognostic risk model, including PON1, AGR2, SSR2, and TMCC1, through a series of bioinformatic approaches, which can accurately predict survival outcomes in HCC patients. Higher risk scores were linked to later grade, recurrence, advanced TNM stage, later T stage, and HBV infection. In addition, 20 fresh frozen tumors and normal tissues from HCC patients were collected and used to validate the genes expressed in the signature by qRT-PCR and immunohistochemical (IHC) assays. Moreover, we found the ER stress-related signature could reflect the infiltration levels of different immune cells in the tumor microenvironment (TME) and forecast the efficacy of immune checkpoint inhibitor (ICI) treatment. Finally, we created a nomogram incorporating this ER stress-related signature. In conclusion, our constructed four-gene risk model associated with ER stress can accurately predict survival outcomes in HCC patients, and the model's risk score is associated with the poor clinical classification.

Identifying General Tumor and Specific Lung Cancer Biomarkers by Transcriptomic Analysis

The bioinformatic pipeline previously developed in our research laboratory is used to identify potential general and specific deregulated tumor genes and transcription factors related to the establishment and progression of tumoral diseases, now comparing lung cancer with other two types of cancer. Twenty microarray datasets were selected and analyzed separately to identify hub differentiated expressed genes and compared to identify all the deregulated genes and transcription factors in common between the three types of cancer and those unique to lung cancer. The winning DEGs analysis allowed to identify an important number of TFs deregulated in the majority of microarray datasets, which can become key biomarkers of general tumors and specific to lung cancer. A coexpression network was constructed for every dataset with all deregulated genes associated with lung cancer, according to DAVID’s tool enrichment analysis, and transcription factors capable of regulating them, according to oPOSSUM´s tool. Several genes and transcription factors are coexpressed in the networks, suggesting that they could be related to the establishment or progression of the tumoral pathology in any tissue and specifically in the lung. The comparison of the coexpression networks of lung cancer and other types of cancer allowed the identification of common connectivity patterns with deregulated genes and transcription factors correlated to important tumoral processes and signaling pathways that have not been studied yet to experimentally validate their role in lung cancer. The Kaplan–Meier estimator determined the association of thirteen deregulated top winning transcription factors with the survival of lung cancer patients. The coregulatory analysis identified two top winning transcription factors networks related to the regulatory control of gene expression in lung and breast cancer. Our transcriptomic analysis suggests that cancer has an important coregulatory network of transcription factors related to the acquisition of the hallmarks of cancer. Moreover, lung cancer has a group of genes and transcription factors unique to pulmonary tissue that are coexpressed during tumorigenesis and must be studied experimentally to fully understand their role in the pathogenesis within its very complex transcriptomic scenario. Therefore, the downstream bioinformatic analysis developed was able to identify a coregulatory metafirm of cancer in general and specific to lung cancer taking into account the great heterogeneity of the tumoral process at cellular and population levels.

Comprehensive Analysis of Prognostic Value and Immune Infiltration of Ficolin Family Members in Hepatocellular Carcinoma

Objective: Ficolin (FCN) family proteins are part of the innate immune system, play a role as recognition molecules in the complement system, and are associated with tumor development. The mechanism of its role in immunotherapy of hepatocellular carcinoma (HCC) is unclear.

Methods: In this study, we used the TCGA database, HPA database, Gene Expression Profile Interaction Analysis (GEPIA), Kaplan-Meier plotter, TCGAportal, cBioPortal, GeneMANIA, TIMER, and TISIDB to analyze Ficolin family proteins (FCN1, FCN2 and FCN3, FCNs) in patients with hepatocellular carcinoma for differential expression, prognostic value, genetic alterations, functional enrichment, and immune factor correlation analysis.

Results: The expression levels of FCN1/2/3 were significantly reduced in patients with HCC. Among them, FCN3 showed significant correlation with Overall Survival (OS), Progressive Free Survival (PFS) and Relapse Free Survival (RFS) in HCC. FCN1 and FCN3 may be potential prognostic markers for survival in patients with HCC. In addition, the functions of differentially expressed FCNs were mainly related to complement activation, immune response, apoptotic cell clearance and phagocytosis. FCNs were found to be significantly correlated with multiple immune cells and immune factors. Expression of FCN1 and FCN3 differed significantly in the immune and stromal cell component scores of HCC. analysis of the tumor mutation burden (TMB) and microsatellite instability (MSI) of FCNs with pan-cancer showed that FCN3 was significantly correlated with both.

Conclusions: Our study provides new insights into the link between the FCN family and immunotherapy for HCC, and FCN3 may serve as a prognostic biomarker for HCC.

USP15 negatively regulates lung cancer progression through the TRAF6-BECN1 signaling axis for autophagy induction

TNF receptor-associated factor 6 (TRAF6)-BECN1 signaling axis plays a pivotal role in autophagy induction through ubiquitination of BECN1, thereby inducing lung cancer migration and invasion in response to toll-like receptor 4 (TLR4) stimulation. Herein, we provide novel molecular and cellular mechanisms involved in the negative effect of ubiquitin-specific peptidase 15 (USP15) on lung cancer progression. Clinical data of the TCGA and primary non-small cell lung cancer (NSCLC) patients (n = 41) revealed that the expression of USP15 was significantly downregulated in lung cancer patients. Importantly, USP15-knockout (USP15KO) A549 and USP15KO H1299 lung cancer cells generated with CRISPR-Cas9 gene-editing technology showed increases in cancer migration and invasion with enhanced autophagy induction in response to TLR4 stimulation. In addition, biochemical studies revealed that USP15 interacted with BECN1, but not with TRAF6, and induced deubiquitination of BECN1, thereby attenuating autophagy induction. Notably, in primary NSCLC patients (n = 4) with low expression of USP15, 10 genes (CCNE1, MMP9, SFN, UBE2C, CCR2, FAM83A, ETV4, MYO7A, MMP11, and GSDMB) known to promote lung cancer progression were significantly upregulated, whereas 10 tumor suppressor genes (FMO2, ZBTB16, FCN3, TCF21, SFTPA1B, HPGD, SOSTDC1, TMEM100, GDF10, and WIF1) were downregulated, providing clinical relevance of the functional role of USP15 in lung cancer progression. Taken together, our data demonstrate that USP15 can negatively regulate the TRAF6-BECN1 signaling axis for autophagy induction. Thus, USP15 is implicated in lung cancer progression.

A Novel Gene Signature Based on CDC20 and FCN3 for Prediction of Prognosis and Immune Features in Patients with Hepatocellular Carcinoma

Long-term survivals of patients with hepatocellular carcinoma (HCC) remain unfavorable, which is largely attributed to active carcinogenesis. Growing studies have suggested that the reliable gene signature could act as an independent prognosis factor for HCC patients. We tried to screen the survival-related genes and develop a prognostic prediction model for HCC patients based on the expression profiles of the critical survival-related genes. In this study, we analyzed TCGA datasets and identified 280 genes with differential expressions (125 increased genes and 155 reduced genes). We analyzed the prognosis value of the top 10 dysregulated genes in HCC patients and identified three critical genes, including FCN3, CDC20, and E2F1, which were confirmed to be associated with long-term survival in both TCGA and ICGC datasets. The results of the LASSO model screened CDC20 and FCN3 for the development of the prognostic model. The CDC20 expression was distinctly increased in HCC specimens, while the FCN3 expression was distinctly decreased in HCC. At a suitable cutoff, patients were divided into low-risk and high-risk groups. Survival assays revealed that patients in high-risk groups exhibited a shorter overall survival than those in low-risk groups. Finally, we examine the relationships between risk score and immune infiltration abundance in HCC and observed that risk score was positively correlated with infiltration degree of B cells, T cell CD4+ cells, neutrophil, macrophage, and myeloid dendritic cells. Overall, we identified three critical survival-related genes and used CDC20 and FCN3 to develop a novel model for predicting outcomes and immune landscapes for patients with HCC. The above three genes also have a high potential for targeted cancer therapy of patients with HCC.

Components of the Lectin Pathway of Complement in Solid Tumour Cancers

The complement system is an important branch of the humoral innate immune response that can be activated via three distinct pathways (classical, alternative, lectin), contributing to keeping/restoring homeostasis. It can also interact with cellular innate immunity and with components of acquired immunity. Cross-talk between the complement system and other enzyme-dependent cascades makes it a more influential defence system, but on the other hand, over- or chronic activation can be harmful. This short review is focused on the dual role of the lectin pathway of complement activation in human solid tumour cancers, including those of the female reproductive system, lung, and alimentary tract, with emphasis on the aforementioned cross-talk.