Distinct roles of core autophagy-related genes in zebrafish definitive hematopoiesis

Despite the well-described discrepancy between ATG (macroautophagy/autophagy-related) genes in the regulation of hematopoiesis, varying essentiality of core ATG proteins in vertebrate definitive hematopoiesis remains largely unclear. Here, we employed zebrafish (Danio rerio) to compare the functions of six core atg genes, including atg13, becn1 (beclin1), atg9a, atg2a, atg5, and atg3, in vertebrate definitive hematopoiesis via clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 ribonucleoprotein and morpholino targeting. Zebrafish with various atg mutations showed autophagic deficiency and presented partially consistent hematopoietic abnormalities during early development. All six atg mutations led to a declined number of spi1b+ (Spi-1 proto-oncogene b) myeloid progenitor cells. However, only becn1 mutation resulted in the expansion of myb+ (v-myb avian myeloblastosis viral oncogene homolog) hematopoietic stem and progenitor cells (HSPCs) and transiently increased coro1a+ (coronin, actin binding protein, 1A) leukocytes, whereas atg3 mutation decreased the number of HSPCs and leukocytes. Proteomic analysis of caudal hematopoietic tissue identified sin3aa (SIN3 transcription regulator family member Aa) as a potential modulator of atg13- and becn1-regulated definitive hematopoiesis. Disruption of sin3aa rescued the expansion of HSPCs and leukocytes in becn1 mutants and exacerbated the decrease of HSPCs in atg13 mutants. Double mutations were also performed to examine alternative functions of various atg genes in definitive hematopoiesis. Notably, becn1 mutation failed to induce HSPCs expansion with one of the other five atg mutations. These findings demonstrated the distinct roles of atg genes and their interplays in zebrafish definitive hematopoiesis, thereby suggesting that the vertebrate definitive hematopoiesis is regulated in an atg gene-dependent manner.Abbreviations: AGM: aorta-gonad-mesonephros; AO: acridine orange; atg: autophagy related; becn1: beclin 1, autophagy related; CHT: caudal hematopoietic tissue; CKO: conditional knockout; coro1a: coronin, actin binding protein, 1A; CQ: chloroquine; CRISPR: clustered regularly interspaced short palindromic repeats; dpf: days post fertilization; FACS: fluorescence-activated cell sorting; hbae1.1: hemoglobin, alpha embryonic 1.1; HSCs: hematopoietic stem cells; HSPCs: hematopoietic stem and progenitor cells; KD: knockdown; KO: knockout; map1lc3/lc3: microtubule-associated protein 1 light chain 3; MO: morpholino; mpeg1.1: macrophage expressed 1, tandem duplicate 1; mpx: myeloid-specific peroxidase; myb: v-myb avian myeloblastosis viral oncogene homolog; PE: phosphatidylethanolamine; p-H3: phospho-H3 histone; PtdIns3K: class 3 phosphatidylinositol 3-kinase; rag1: recombination activating 1; rb1cc1/fip200: RB1-inducible coiled-coil 1; RFLP: restriction fragment length polymorphism; RNP: ribonucleoprotein; sin3aa: SIN3 transcription regulator family member Aa; spi1b: Spi-1 proto-oncogene b; ulk: unc-51 like autophagy activating kinase; vtg1: vitellogenin 1; WISH: whole-mount in situ hybridization.

Identification of differentially expressed autophagy-related genes in cases of intracranial aneurysm: Bioinformatics analysis

OBJECTIVE

Recent research indicates that autophagy is essential for the rupture of intracranial aneurysm (IA). This study aimed to examine and validate potential autophagy-related genes (ARGs) in cases of IA using bioinformatics analysis.

METHODS

Two expression profiles (GSE54083 and GSE75436) were obtained from the Gene Expression Omnibus database. Differentially expressed ARGs (DEARGs) in cases of IA were screened using GSE75436, and enrichment analysis and Protein-Protein Interaction (PPI) networks were used to identify the hub genes and related pathways. Furthermore, a novel predictive diagnostic signature for IA based on the hub genes was constructed. The area under the Receiver Operating Characteristic curve (AUC) was used to evaluate the signature performance in GSE75436.

RESULTS

In total, 75 co-expressed DEARGs were identified in the GSE75436 and GSE54083 dataset (28 upregulated and 47 downregulated genes). Enrichment analysis of DEARGs revealed several enriched terms associated with proteoglycans in cancer and human immunodeficiency virus 1 infection. PPI analysis revealed interactions between these genes. Hub DEARGs included insulin-like growth factor 1, clusters of differentiation 4, cysteine-aspartic acid protease 8, Bcl-2-like protein 11, mouse double mutant 2 homolog, toll-like receptor 4, growth factor receptor-bound protein 2, Jun proto-oncogene, AP-1 transcription factor subunit, hypoxia inducible factor 1 alpha, and erythroblastic oncogene B-2. Notably, the signature showed good performance in distinguishing IA (AUC = 0.87). The sig calibration curves showed good calibration.

CONCLUSION

Bioinformatic analysis identified 75 potential DEARGs in cases of IA. This study revealed that IA is affected by autophagy, which could explain the pathogenesis of IA and aid in its diagnosis and treatment. However, future research with experimental validation is necessary to identify potential DEARGs in cases of IA.

Identification and verification of a prognostic autophagy-related gene signature in hepatocellular carcinoma

This study aimed to investigate the potential of autophagy-related genes (ATGs) as a prognostic signature for HCC and explore their relationships with immune cells and immune checkpoint molecules. A total of 483 samples were collected from the GEO database (n = 115) and The Cancer Genome Atlas (TCGA) database (n = 368). The GEO dataset was used as the training set, while the TCGA dataset was used for validation. The list of ATGs was obtained from the human autophagy database (HADB). Using Cox regression and LASSO regression methods, a prognostic signature based on ATGs was established. The independent use of this prognostic signature was tested through subgroup analysis. Additionally, the predictive value of this signature for immune-related profiles was explored. Following selection through univariate Cox regression analysis and iterative LASSO Cox analysis, a total of 11 ATGs were used in the GEO dataset to establish a prognostic signature that stratified patients into high- and low-risk groups based on survival. The robustness of this prognostic signature was validated using an external dataset. This signature remained a prognostic factor even in subgroups with different clinical features. Analysis of immune profiles revealed that patients in the high-risk group exhibited immunosuppressive states characterized by lower immune scores and ESTIMATE scores, greater tumour purity, and increased expression of immune checkpoint molecules. Furthermore, this signature was found to be correlated with the infiltration of different immune cell subpopulations. The results suggest that the ATG-based signature can be utilized to evaluate the prognosis of HCC patients and predict the immune status within the tumour microenvironment (TME). However, it is important to note that this study represents a preliminary attempt to use ATGs as prognostic indicators for HCC, and further validation is necessary to determine the predictive power of this signature.

Polymorphism in autophagy-related genes LRP1 and CAPZA1 may promote gastric mucosal atrophy

BACKGROUND

Helicobacter pylori secretes cytotoxin-associated gene A (CagA) into the gastric epithelium, causing gastric mucosal atrophy (GMA) and gastric cancer. In contrast, host cells degrade CagA via autophagy. However, the association between polymorphisms in autophagy-related genes and GMA must be fully elucidated.

RESULTS

We evaluated the association between single nucleotide polymorphisms (SNPs) in autophagy-related genes (low-density lipoprotein receptor-related protein 1, LRP1; capping actin protein of muscle Z-line alpha subunit 1, CAPAZ1; and lysosomal-associated membrane protein 1, LAMP1) and GMA in 200 H. pylori-positive individuals. The frequency of the T/T genotype at rs1800137 in LRP1 was significantly lower in the GMA group than in the non-GMA group (p = 0.018, odds ratio [OR] = 0.188). The frequencies of the G/A or A/A genotype at rs4423118 and T/A or A/A genotype at rs58618380 of CAPAZ1 in the GMA group were significantly higher than those in the non-GMA group (p = 0.029 and p = 0.027, respectively). Multivariate analysis revealed that C/C or C/T genotype at rs1800137, T/A or A/A genotype at rs58618380, and age were independent risk factors for GMA (p = 0.038, p = 0.023, and p = 0.006, respectively). Furthermore, individuals with the rs1800137 C/C or C/T genotype of LRP1 had a 5.3-fold higher susceptibility to GMA. These genetic tests may provide future directions for precision medicine for individuals more likely to develop GMA.

CONCLUSION

LRP1 and CAPZA1 polymorphisms may be associated with the development of GMA.

Comprehensive analysis of autophagy-related gene expression profiles identified five gene biomarkers associated with immune infiltration and advanced plaques in carotid atherosclerosis

BACKGROUND

Autophagy plays an important role in the progression of carotid atherosclerosis (CAS). This study aimed to identify hub autophagy-related genes (ATGs) associated with CAS.

METHODS

GSE43292 and GSE28829 datasets of early and advanced CAS plaques were enrolled from the Gene Expression Omnibus (GEO) database. A comprehensive analysis of differentially expressed ATGs (DE-ATGs) was conducted. Functional enrichment assay was used to explore biological functions of DE-ATGs. The hub ATGs were identified by protein-protein interaction (PPI) network. Immunohistochemistry (IHC) and Real-time reverse transcription-quantitative polymerase chain reaction (RT-qPCR) were used to validate hub ATGs at the protein level and mRNA level. Correlation analysis of hub ATGs with immune cells was also conducted. In addition, a competitive endogenous RNA (ceRNA) network was constructed, and diagnostic value of hub ATGs was evaluated.

RESULTS

A total of 19 DE-ATGs were identified in early and advanced CAS plaques. Functional enrichment analysis of DE-ATGs suggested that they were closely correlated to autophagy, apoptosis, and lipid regulation. Moreover, 5 hub ATGs, including TNFSF10, ITGA6, CTSD, CCL2, and CASP1, were identified and further verified by IHC. The area under the curve (AUC) values of the 5 hub ATGs were 0.818, 0.732, 0.792, 0.814, and 0.812, respectively. Competing endogenous RNA (ceRNA) networks targeting the hub ATGs were also constructed. In addition, the 5 hub ATGs were found to be closely associated with immune cell infiltration in CAS.

CONCLUSION

In this study, we identified 5 hub ATGs including CASP1, CCL2, CTSD, ITGA6 and TNFSF10, which could serve as candidate diagnostic biomarkers and therapeutic targets.

Identification of potential key autophagy-related genes in asthma with bioinformatics approaches

OBJECTIVES

Asthma is a chronic respiratory disease characterized by airway remodeling and inflammation. Recent studies have demonstrated that multiple autophagy-related genes are involved in the pathogenesis of asthma. However, the roles of many of these autophagy-related genes in asthma remain unclear, particularly with regard to the diagnosis of asthma.

METHODS

In this study, autophagy-related differentially expressed genes (DEGs) in asthma were identified by bioinformatics analysis of the GSE76262 datasets. Hub genes were screened by protein-protein interaction (PPI) network and module analyses. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were used to explore potential signaling pathways. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic value of autophagy-related biomarkers in asthma.

RESULTS

A total of 17 autophagy-related DEGs were identified, most of which were involved in autophagy and protein processing in the endoplasmic reticulum signaling pathway. ROC curve analysis demonstrated that the hub genes (HIF1A, ERN1, and DNAJB1) identified from the PPI network exhibited good performance in the diagnosis of asthma. The GSE137268 and GSE43696 databases were used to verify the expression of 17 autophagy-related DEGs in asthma. Interestingly, ERN1 was an overlapping gene defined by the intersection of hub autophagy-related DEGs and key modules (including HIF1A, ERN1, and DNAJB1). We also analyzed the interaction between miRNAs and mRNAs for 14 autophagy-related DEGs with an area under the curve > 0.7. The identified genes were involved in the glypican, interferon-gamma, and plasma membrane estrogen receptor signaling pathways.

CONCLUSIONS

The results of this study indicate that specific signaling pathways and autophagy-related DEGs are potential diagnostic biomarkers related to the inception and progression of asthma.

A seven-autophagy-related gene signature for predicting the prognosis of differentiated thyroid carcinoma

Background

Numerous studies have implicated autophagy in the pathogenesis of thyroid carcinoma. This investigation aimed to establish an autophagy-related gene model and nomogram that can help predict the overall survival (OS) of patients with differentiated thyroid carcinoma (DTHCA).

Methods

Clinical characteristics and RNA-seq expression data from TCGA (The Cancer Genome Atlas) were used in the study. We also downloaded autophagy-related genes (ARGs) from the Gene Set Enrichment Analysis website and the Human Autophagy Database. First, we assigned patients into training and testing groups. R software was applied to identify differentially expressed ARGs for further construction of a protein-protein interaction (PPI) network for gene functional analyses. A risk score-based prognostic risk model was subsequently developed using univariate Cox regression and LASSO-penalized Cox regression analyses. The model’s performance was verified using Kaplan-Meier (KM) survival analysis and ROC curve. Finally, a nomogram was constructed for clinical application in evaluating the patients with DTHCA. Finally, a 7-gene prognostic risk model was developed based on gene set enrichment analysis.

Results

Overall, we identified 54 differentially expressed ARGs in patients with DTHCA. A new gene risk model based on 7-ARGs (CDKN2A, FGF7, CTSB, HAP1, DAPK2, DNAJB1, and ITPR1) was developed in the training group and validated in the testing group. The predictive accuracy of the model was reflected by the area under the ROC curve (AUC) values. Univariate and multivariate Cox regression analysis indicated that the model could independently predict the prognosis of patients with THCA. The constrained nomogram derived from the risk score and age also showed high prediction accuracy.

Conclusions

Here, we developed a 7-ARG prognostic risk model and nomogram for differentiated thyroid carcinoma patients that can guide clinical decisions and individualized therapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-022-02590-6.

Screening and identification of NOTCH1, CDKN2A, and NOS3 as differentially expressed autophagy-related genes in erectile dysfunction

Background

Loss of function of key autophagy genes are associated with a variety of diseases. However specific role of autophagy-related genes in erectile dysfunction ED remains unclear. This study explores the autophagy-related differentially expressed genes (ARGs) profiles and related molecular mechanisms in Corpus Cavernosum endothelial dysfunction, which is a leading cause of ED.

Methods

The Gene Expression Omnibus (GEO) database was used to identify the key genes and pathways. Differentially expressed genes (DEGs) were mined using the limma package in R language. Next, ARGs were obtained by matching DEGs and autophagy-related genes from GeneCard using Venn diagrams. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of ARGs were described using clusterProfiler and org.Hs.eg.db in R. Moreover, hub ARGs were screened out through protein-protein interaction (PPI), gene-microRNAs, and gene-transcription factors (TFs) networks then visualized using Cytoscape. Of note, the rat model of diabetic ED was established to validate some hub ARGs with qRT-PCR and Western blots.

Results

Twenty ARGs were identified from four ED samples and eight non-ED samples. GO analysis revealed that molecular functions (MF) of upregulated ARGs were mainly enriched in nuclear receptor activity. Also, MF of downregulated ARGs were mainly enriched in oxidoreductase activity, acting on NAD(P)H and heme proteins as acceptors. Moreover, six hub ARGs were identified by setting high degrees in the network. Additionally, hsa-mir-24-3p and hsa-mir-335-5p might play a central role in several ARGs regulation, and the transcription factors-hub genes network was centered with 13 ARGs. The experimental results further showed that the expression of Notch1, NOS3, and CDKN2A in the diabetic ED group was downregulated compared to the control.

Conclusions

Our study deepens the autophagy-related mechanistic understanding of endothelial dysfunction of ED. NOTCH1, CDKN2A, and NOS3 are involved in the regulation of endothelial dysfunction and may be potential therapeutic targets for ED by modulating autophagy.

Identification and validation of autophagy-related prognostic signature for head and neck squamous cell carcinoma

•

Identify novel autophagy-related signature for OS and DSS in HNSCC patients.

•

The role of autophagy in tumor immune microenvironment.

•

Provide promising targets that can enhance the efficacy of cancer immunotherapy.

Background

Many studies have demonstrated that autophagy plays a significant role in regulating tumor growth and progression. However, the effect of autophagy-related genes (ARGs) on the prognosis have rarely been analyzed in head and neck squamous cell carcinoma (HNSCC).

Methods

We obtained differentially expressed ARGs from HNSCC mRNA data in The Cancer Genome Atlas (TCGA) database. And then we performed gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses to explore the autophagy-related biological functions. The overall survival (OS)-related and disease specific survival (DSS)-related ARGs were identified by univariate Cox regression analyses. With these genes, we established OS-related and DSS-related risk signature by LASSO regression method, respectively. We validated the reliability of the risk signature with receiver operating characteristic (ROC) analysis, Kaplan-Meier survival curves, clinical correlation analysis, and nomogram. Then we analyzed relationships between risk signature and immune cell infiltration.

Results

We established the prognostic signatures based on 14 ARGs for OS and 12 ARGs for DSS. The ROC curves, survival analysis, and nomogram validated the predictive accuracy of the models. Clinic correlation analysis showed that the risk group was closely related to Stage, pathological T stage, pathological N stage and human papilloma virus (HPV) subtype. Cox regression demonstrated that the risk score was an independent predictor for the prognosis of HNSCC patients. Furthermore, patients in low-risk score group exhibited higher immunescore and distinct immune cell infiltration than high-risk score group. And we further analysis revealed that the copy number alterations (CNAs) of ARGs-based signature affected the abundance of tumor-infiltrating immune cells.

Conclusion

In this study, we identified novel autophagy-related signature for the prediction of OS and DSS in patients with HNSCC. Meanwhile, our study provides a novel sight to understand the role of autophagy and elucidate the important role of autophagy in tumor immune microenvironment (TIME) of HNSCC.

Construction autophagy-related prognostic risk signature combined with clinicopathological validation analysis for survival prediction of kidney renal papillary cell carcinoma patients

BACKGROUND

Little data is available on prognostic biomarkers and effective treatment options for Kidney Renal Papillary Cell Carcinoma (KIRP) patients, to find potential prognostic biomarkers and new targets was an urgent mission for KIRP therapy.

METHODS

The differentially expressed autophagy-related genes (DEARGs) were screened out according to the RNA sequencing data in The Cancer Genome Atlas database, then identified survival-related DEARGs to establish a prognostic model for survival predicting of KIRP patients. Then we verified the robustness and validity of the prognostic risk model through clinicopathological data. At last, we evaluate the prognostic value of genes that formed the prognostic risk model individually.

RESULTS

We analyzed the expression of 232 autophagy-related genes (ARGs) in 289 KIRP and 32 non-tumor tissue cases, and 40 mRNAs were screened out as DEARGs. The functional and pathway enrichment analysis was done and protein-protein interaction network was constructed for all DEARGs. To sift candidate DEARGs associated with KIRP patients' survival and create an autophagy-related risk prognostic model, univariate and multivariate Cox regression analysis were did separately. Eventually 3 desirable independent prognostic DEARGs (P4HB, NRG1, and BIRC5) were picked out and used for construct the autophagy-related risk model. The accuracy of the prognostic risk model for survival prediction was assessed by Kaplan-Meier plotter, receiver-operator characteristic curve, and clinicopathological correlational analyses. The prognostic value of above 3 genes was verified individually by survival analysis and expression analysis on mRNA and protein level.

CONCLUSIONS

The autophagy-related prognostic model is accurate and applicable, it can predict OS independently for KIRP patients. Three independent prognostic DEARGs can benefit for facilitate personalized target treatment too.

Construction autophagy-related prognostic risk signature to facilitate survival prediction, individual treatment and biomarker excavation of epithelial ovarian cancer patients

Background

Existing clinical methods for prognosis evaluating for Epithelial Ovarian Cancer (EOC) patients had defects of invasive, unsystematic and subjective and little data are available for individualizing treatment, therefore, to identify potential prognostic markers and new therapeutic targets for EOC is urgently required.

Results

Expression of 232 autophagy-related genes (ARGs) in 354 EOC and 56 human ovarian surface epithelial specimens from 7 independent laboratories were analyzed, 31 mRNAs were identified as DEARGs. We did functional and pathway enrichment analysis and constructed protein–protein interaction network for all DEARGs. To screen out candidate DEARGs related to EOC patients’ survival and construct an autophagy-related prognostic risk signature, univariate and multivariate Cox proportional hazards models were established separately. Finally, 5 optimal independent prognostic DEARGs (PEX3, DNAJB9, RB1, HSP90AB1 and CXCR4) were confirmed and the autophagy-related risk model was established by the 5 prognostic DEARGs. The accuracy and robustness of the prognostic risk model for survival prediction were evaluated and verified by analyzing the correlation between EOC patients’ survival status, clinicopathological features and risk scores.

Conclusions

The autophagy-related prognostic risk model can be independently used to predict overall survival in EOC patients, it can also potentially assist in individualizing treatment and biomarker development.

Systematic profiling of diagnostic and prognostic value of autophagy-related genes for sarcoma patients

BACKGROUND

Autophagy-related genes (ARGs) have been confirmed to have an important role in tumorigenesis and tumor microenvironment formation. Nevertheless, a systematic analysis of ARGs and their clinical significance in sarcoma patients is lacking.

METHODS

Gene expression files from The Cancer Genome Atlas (TCGA) database and Genotype-Tissue Expression (GTEx) were used to select differentially expressed genes (DEGs). Differentially expressed ARGs (DEARGs) were determined by matching the DEG and HADb gene sets, which were evaluated by functional enrichment analysis. Unsupervised clustering of the identified DEARGs was conducted, and associations with tumor microenvironment (TME), immune checkpoints, and immune cells were analyzed simultaneously. Two prognostic signatures, one for overall survival (OS) and one for disease-free survival (DFS), were established and validated in an independent set.

RESULTS

In total, 84 DEARGs and two clusters were identified. TME scores, five immune checkpoints, and several types of immune cells were found to be significantly different between two clusters. Two prognostic signatures incorporating DEARGs showed favorable discrimination and were successfully validated. Two nomograms combining signature and clinical variables were generated. The C-indexes were 0.818 and 0.747 for the OS and DFS nomograms, respectively.

CONCLUSION

This comprehensive analyses of the ARG landscape in sarcoma showed novel ARGs related to carcinogenesis and the immune microenvironment. These findings have implications for prognosis and therapeutic responses, which reveal novel potential prognostic biomarkers, promote precision medicine, and provide potential novel targets for immunotherapy.

Development of prognosis model for colon cancer based on autophagy-related genes

BACKGROUND

Autophagy is an orderly catabolic process for degrading and removing unnecessary or dysfunctional cellular components such as proteins and organelles. Although autophagy is known to play an important role in various types of cancer, the effects of autophagy-related genes (ARGs) on colon cancer have not been well studied.

METHODS

Expression profiles from ARGs in 457 colon cancer patients were retrieved from the TCGA database ( https://portal.gdc.cancer.gov ). Differentially expressed ARGs and ARGs related to overall patient survival were identified. Cox proportional-hazard models were used to investigate the association between ARG expression profiles and patient prognosis.

RESULTS

Twenty ARGs were significantly associated with the overall survival of colon cancer patients. Five of these ARGs had a mutation rate ≥ 3%. Patients were divided into high-risk and low-risk groups based on Cox regression analysis of 8 ARGs. Low-risk patients had a significantly longer survival time than high-risk patients (p < 0.001). Univariate and multivariate Cox regression analysis showed that the resulting risk score, which was associated with infiltration depth and metastasis, could be an independent predictor of patient survival. A nomogram was established to predict 1-, 3-, and 5-year survival of colon cancer patients based on 5 independent prognosis factors, including the risk score. The prognostic nomogram with online webserver was more effective and convenient to provide information for researchers and clinicians.

CONCLUSION

The 8 ARGs can be used to predict the prognosis of patients and provide information for their individualized treatment.

Role and mechanism of autophagy-regulating factors in tumorigenesis and drug resistance

A hallmark feature of tumorigenesis is uncontrolled cell division. Autophagy is regulated by more than 30 genes and it is one of several mechanisms by which cells maintain homeostasis. Autophagy promotes cancer progression and drug resistance. Several genes play important roles in autophagy-induced tumorigenesis and drug resistance including Beclin-1, MIF, HMGB1, p53, PTEN, p62, RAC3, SRC3, NF-2, MEG3, LAPTM4B, mTOR, BRAF and c-MYC. These genes alter cell growth, cellular microenvironment and cell division. Mechanisms involved in tumorigenesis and drug resistance include microdeletions, genetic mutations, loss of heterozygosity, hypermethylation, microsatellite instability and translational modifications at a molecular level. Disrupted or altered autophagy has been reported in hematological malignancies like lymphoma, leukemia and myeloma as well as multiple solid organ tumors like colorectal, hepatocellular, gall bladder, pancreatic, gastric and cholangiocarcinoma among many other malignancies. In addition, defects in autophagy also play a role in drug resistance in cancers like osteosarcoma, ovarian and lung carcinomas following treatment with drugs such as doxorubicin, paclitaxel, cisplatin, gemcitabine and etoposide. Therapeutic approaches that modulate autophagy are a novel future direction for cancer drug development that may help to prevent issues with disease progression and overcome drug resistance.

Pharmacological and nutritional modulation of autophagy in a rainbow trout (Oncorhynchus mykiss) gill cell line, RTgill-W1

Autophagy is involved in the modulation of nutrition, immunity, and disease in humans and animals. To understand the impact of autophagy modulation on a rainbow trout gill cell line, RTgill-W1, treatments including reduced nutrition (2% fetal bovine serum compared with 10% control), rapamycin, 3-methyladenine, deoxynivalenol, and chloroquine were tested. Western blot and immunofluorescence were used to detect microtubule-associated protein 1A/1B-light chain protein and quantitative polymerase chain reaction was used to detect the expression of 10 autophagy-related genes. At 3-d post-treatment, reduced nutrition significantly (p < 0.05) increased autophagy while deoxynivalenol significantly (p < 0.01) suppressed it compared to controls. These phenomena were confirmed by using immunofluorescence to detect the number of autophagosomes in RTgill-W1. Chloroquine is critical to allow observation of microtubule-associated protein 1A/1B-light chain protein in this model. The commonly used autophagy-modulating chemicals rapamycin and 3-methyladenine either activated or suppressed microtubule-associated protein 1A/1B-light chain protein, respectively, as expected from the literature, but did not act in a consistently significant manner. Expression of five of the 10 Atg genes, including lc3, gabarap, atg4, atg7, and atg12, were altered in a similar pattern to microtubule-associated protein 1A/1B-light chain protein. The consistent trend of autophagy-related gene upregulation including becn1, lc3, gabarap, and atg9 following treatment with 3-methyladenine and chloroquine is suggestive of a novel feedback regulation in the autophagy machinery.

Identification of an autophagy-related gene signature that can improve prognosis of hepatocellular carcinoma patients

Background

Autophagy is a programmed cell degradation mechanism that has been associated with several physiological and pathophysiological processes, including malignancy. Improper induction of autophagy has been proposed to play a pivotal role in the progression of hepatocellular carcinoma (HCC).

Methods

Univariate Cox regression analysis of overall survival (OS) was performed to identify risk-associated autophagy-related genes (ARGs) in HCC data set from The Cancer Genome Atlas (TCGA). Multivariate cox regression was then performed to develop a risk prediction model for the prognosis of 370 HCC patients. The multi-target receiver operating characteristic (ROC) curve was used to determine the model’s accuracy. Besides, the relationship between drug sensitivity and ARGs expression was also examined.

Results

A total of 62 differentially expressed ARGs were identified in HCC patients. Univariate and multivariate regression identified five risk-associated ARGs (HDAC1, RHEB, ATIC, SPNS1 and SQSTM1) that were correlated with OS in HCC patients. Of importance, the risk-associated ARGs were independent risk factors in the multivariate risk model including clinical parameters such as malignant stage (HR = 1.433, 95% CI = 1.293–1.589, P < 0.001). In addition, the area under curve for the prognostic risk model was 0.747, which indicates the high accuracy of the model in prediction of HCC outcomes. Interestingly, the risk-associated ARGs were also correlated with drug sensitivity in HCC cell lines.

Conclusion

We developed a novel prognostic risk model by integrating the molecular signature and clinical parameters of HCC, which can effectively predict the outcomes of HCC patients.

Prognostic value of an autophagy-related gene expression signature for endometrial cancer patients

Background

Autophagy is associated with cancer development. Autophagy-related genes play significant roles in endometrial cancer (EC), a major gynecological malignancy worldwide, but little was known about their value as prognostic markers. Here we evaluated the value of a prognostic signature based on autophagy-related genes for EC.

Methods

First, various autophagy-related genes were obtained via the Human Autophagy Database and their expression profiles were downloaded from The Cancer Genome Atlas. Second, key prognostic autophagy-related genes were identified via univariate, LASSO and multivariate Cox regression analyses. Finally, a risk score to predict the prognosis of EC was calculated and validated by using the test and the entire data sets. Besides, the key genes mRNA expression were validated using quantitative real-time PCR in clinical tissue samples.

Results

A total of 40 differentially expressed autophagy-related genes in EC were screened and five of them were prognosis-related (CDKN1B, DLC1, EIF4EBP1, ERBB2 and GRID1). A prognostic signature was constructed based on these five genes using the train set, which stratified EC patients into high-risk and low-risk groups (p < 0.05). In terms of overall survival, the analyses of the test set and the entire set yielded consistent results (test set: p < 0.05; entire set: p < 0.05). Time-dependent ROC analysis suggested that the risk score predicted EC prognosis accurately and independently (0.674 at 1 year, 0.712 at 3 years and 0.659 at 5 years). A nomogram with clinical utility was built. Patients in the high-risk group displayed distinct mutation signatures compared with those in the low-risk group. For clinical sample validation, we found that EIF4EBP1and ERBB2 had higher level in EC than that in normal tissues while CDKN1B, DLC1 and GRID1 had lower level, which was consistent with the results predicted.

Conclusions

Based on five autophagy-related genes (CDKN1B, DLC1, EIF4EBP1, ERBB2 and GRID1), our model can independently predict the OS of EC patients by combining molecular signature and clinical characteristics.

The identification of tick autophagy-related genes in Ixodes scapularis responding to amino acid starvation

Ticks are obligate hematophagous arthropods and must tolerate starvation during off-host periods. Macroautophagy (hereafter autophagy) is a well-conserved self-eating mechanism of cell survival and is essential for recycling cellular contents during periods of starvation, stress, and injury in organisms. Although the genome sequence of Ixodes scapularis (Say) is available, the characteristics and functions of autophagy-related gene families remain largely unknown. To advance our understanding of autophagy in I. scapularis, we used comprehensive genomic approaches to identify Atg genes. Homologues of 14 Atg genes were identified, and their protein motif compositions were predicted. Phylogenetic analysis indicated that ATGs in I. scapularis were evolutionarily closely related to their homologues in Haemaphysalis longicornis and Rhipicephalus microplus ticks. Expression patterns of Atg genes differed across tick developmental stages. Immunofluorescence results by monodansylcadaverine (MDC) staining indicated that autophagy was activated after amino acid starvation treatments in I. scapularis embryo-derived cell lines ISE6 and IDE8. Subsequently, the expression of key Atg genes involved in autophagy pathway in both cell lines were examined. In ISE6 cells, the expression levels of three Atg genes (Atg4B, Atg6 and Atg8A) increased significantly after amino acid starvation; similarly, four Atg genes (Atg4A, Atg4B, Atg6 and Atg8B) were upregulated in IDE8 cells in response to starvation. In parallel, the MDC and lysotracker staining results indicated that autophagy was triggered after amino acid starvation treatments in R. microplus embryo-derived cell line BME26. Our observations showed that Atg family genes are highly conserved in ticks and function in autophagy pathway induced by amino acid starvation. These results also provide valuable insight for further autophagy-related research as a new strategy for blocking the transmission of tick-borne pathogens.

Autophagy-related genes prognosis signature as potential predictive markers for immunotherapy in hepatocellular carcinoma

Autophagy-related genes (ATGs) depress tumorigenesis. However, in tumor tissue, it promotes tumor progression. Here, we demonstrated that 63 ATGs were differentially expressed in normal tissues and tumor tissues of hepatocellular carcinoma (HCC), and seven prognostic-related genes were chosen to establish prognostic risk signatures. It is not just an independent prognostic factor for HCC, but also closely related to the degree of malignancy of HCC. Further, the hallmarks of PI3K–AKT–mTOR signaling was significantly enriched in the high-risk group. Moreover, AKT–pS473 and mTOR–pS2448 expression was down-regulated and correlated with patient prognosis in high-risk group. Finally, we demonstrate that the prognosis signature of ATGs is closely related to immune cell infiltration and PD-L1 expression. In conclusion, ATGs are a crucial factor in the malignant progression of HCC and will be a new prognostic marker for diagnosis and treatment. ATGs prognostic signatures are potentially useful for predicting PD-L1 therapeutic effects.

Gintonin stimulates autophagic flux in primary cortical astrocytes

Background

Gintonin (GT), a novel ginseng-derived exogenous ligand of lysophosphatidic acid (LPA) receptors, has been shown to induce cell proliferation and migration in the hippocampus, regulate calcium-dependent ion channels in the astrocytes, and reduce β-amyloid plaque in the brain. However, whether GT influences autophagy in cortical astrocytes is not yet investigated.

Methods

We examined the effect of GT on autophagy in primary cortical astrocytes using immunoblot and immunocytochemistry assays. Suppression of specific proteins was performed via siRNA. LC3 puncta was determined using confocal microscopy.

Results

GT strongly upregulated autophagy marker LC3 by a concentration- as well as time-dependent manner via G protein–coupled LPA receptors. GT-induced autophagy was further confirmed by the formation of LC3 puncta. Interestingly, on pretreatment with an mammalian target of rapamycin (mTOR) inhibitor, rapamycin, GT further enhanced LC3-II and LC3 puncta expression. However, GT-induced autophagy was significantly attenuated by inhibition of autophagy by 3-methyladenine and knockdown Beclin-1, Atg5, and Atg7 gene expression. Importantly, when pretreated with a lysosomotropic agent, E-64d/peps A or bafilomycin A1, GT significantly increased the levels of LC3-II along with the formation of LC3 puncta. In addition, GT treatment enhanced autophagic flux, which led to an increase in lysosome-associated membrane protein 1 and degradation of ubiquitinated p62/SQSTM1.

Conclusion

GT induces autophagy via mTOR-mediated pathway and elevates autophagic flux. This study demonstrates that GT can be used as an autophagy-inducing agent in cortical astrocytes.

Genome-wide identification of 99 autophagy-related (Atg) genes in the monogonont rotifer Brachionus spp. and transcriptional modulation in response to cadmium

Autophagy originated from the common ancestor of all life forms, and its function is highly conserved from yeast to humans. Autophagy plays a key role in various fundamental biological processes including defense, and has developed through serial interactions of multiple gene sets referred to as autophagy-related (Atg) genes. Despite their significance in metazoan life and evolution, few studies have been conducted to identify these genes in aquatic invertebrates. In this study, we identified whole Atg genes in four Brachionus rotifer spp., namely B. calyciflorus, B. koreanus, B. plicatilis, and B. rotundiformis, through searches of their entire genomes; and we annotated them according to the yeast nomenclature. Twenty-four genes orthologous to yeast genes were present in all of the Brachionus spp. while three additional gene duplicates were identified in the genome of B. koreanus, indicating that these genes had diversified during the speciation. Also, their transcriptional responses to cadmium exposure indicated regulation by cadmium-induced oxidative-stress-related signaling pathways. This study provides valuable information on 99 conserved Atg genes involved in autophagosome formation in Brachionus spp., with transcriptional modulation in response to cadmium, in the context of the role of autophagy in the damage response.

Is amyotrophic lateral sclerosis/frontotemporal dementia an autophagy disease?

Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are neurodegenerative disorders that share genetic risk factors and pathological hallmarks. Intriguingly, these shared factors result in a high rate of comorbidity of these diseases in patients. Intracellular protein aggregates are a common pathological hallmark of both diseases. Emerging evidence suggests that impaired RNA processing and disrupted protein homeostasis are two major pathogenic pathways for these diseases. Indeed, recent evidence from genetic and cellular studies of the etiology and pathogenesis of ALS-FTD has suggested that defects in autophagy may underlie various aspects of these diseases. In this review, we discuss the link between genetic mutations, autophagy dysfunction, and the pathogenesis of ALS-FTD. Although dysfunction in a variety of cellular pathways can lead to these diseases, we provide evidence that ALS-FTD is, in many cases, an autophagy disease.

Downregulation of autophagy gene expression in endometria from women with polycystic ovary syndrome

Autophagy, a process of controlled cellular self-digestion, could be involved in cyclic remodeling of the human endometrium. We investigated endometrial mRNA expression of 23 autophagy-related (ATG) genes and transcription factors in healthy controls (n = 12) and anovulatory polycystic ovary syndrome (PCOS) patients (n = 24), as well as in their subgroup (n = 12) before and after metformin treatment. The mRNA levels of transcription factor forkhead box protein O1 (FOXO1) and several molecules involved in autophagosome formation (ATG13, RB1-inducible coiled-coil 1), autophagosome nucleation (ATG14, beclin 1, SH3-domain GRB2-like endophilin B1), autophagosome elongation (ATG3, ATG5, γ-aminobutyric acid receptor-associated protein - GABARAP), and delivery of ubiquitinated proteins to autophagosomes (sequestosome 1), were significantly reduced in anovulatory PCOS compared to healthy endometrium. Free androgen index, but not free estrogen index, insulin levels, or body mass index, negatively correlated with the endometrial expression of ATG3, ATG14, and GABARAP in PCOS patients. Treatment of PCOS patients with metformin (2 g/day for 3 months) significantly increased the endometrial mRNA levels of FOXO1, ATG3, and UV radiation resistance-associated gene. These data suggest that increased androgen availability in PCOS is associated with metformin-sensitive transcriptional downregulation of endometrial autophagy.

Fine mapping of autophagy-related proteins during autophagosome formation in Saccharomyces cerevisiae

Autophagy is a bulk degradation system mediated by biogenesis of autophagosomes under starvation conditions. In Saccharomyces cerevisiae, a membrane sac called the isolation membrane (IM) is generated from the pre-autophagosomal structure (PAS); ultimately, the IM expands to become a mature autophagosome. Eighteen autophagy-related (Atg) proteins are engaged in autophagosome formation at the PAS. However, the cup-shaped IM was visualized just as a dot by fluorescence microscopy, posing a challenge to further understanding the detailed functions of Atg proteins during IM expansion. In this study, we visualized expanding IMs as cup-shaped structures using fluorescence microscopy by enlarging a selective cargo of autophagosomes, and finely mapped the localizations of Atg proteins. The PAS scaffold proteins (Atg13 and Atg17) and phosphatidylinositol 3-kinase complex I were localized to a position at the junction between the IM and the vacuolar membrane, termed the vacuole-IM contact site (VICS). By contrast, Atg1, Atg8 and the Atg16-Atg12-Atg5 complex were present at both the VICS and the cup-shaped IM. We designate this localization the 'IM' pattern. The Atg2-Atg18 complex and Atg9 localized to the edge of the IM, appearing as two or three dots, in close proximity to the endoplasmic reticulum exit sites. Thus, we designate these dots as the 'IM edge' pattern. These data suggest that Atg proteins play individual roles at spatially distinct locations during IM expansion. These findings will facilitate detailed investigations of the function of each Atg protein during autophagosome formation.