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Open accessJournal ArticleDOI: 10.1002/CAM4.3820

Construction and validation of an autophagy-related long noncoding RNA signature for prognosis prediction in kidney renal clear cell carcinoma patients.

02 Mar 2021-Cancer Medicine (John Wiley & Sons, Ltd)-Vol. 10, Iss: 7, pp 2359-2369
Abstract: Purpose The purpose of this study was to identify autophagy-associated long noncoding RNAs (ARlncRNAs) using the kidney renal clear cell carcinoma (KIRC) patient data from The Cancer Genome Atlas (TCGA) database and to construct a prognostic risk-related ARlncRNAs signature to accurately predict the prognosis of KIRC patients. Methods The KIRC patient data were originated from TCGA database and were classified into a training set and testing set. Seven prognostic risk-related ARlncRNAs, identified using univariate, lasso, and multivariate Cox regression analysis, were used to construct prognostic risk-related signatures. Kaplan-Meier curves and receiver operating characteristic (ROC) curves as well as independent prognostic factor analysis and correlation analysis with clinical characteristics were utilized to evaluate and verify the specificity and sensitivity of the signature in training set and testing set, respectively. Two nomograms were established to predict the probable 1-, 3-, and 5-year survival of the KIRC patients. In addition, the lncRNA-mRNA co-expression network was constructed and Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to identify biological functions of ARlncRNAs. Results We constructed and verified a prognostic risk-related ARlncRNAs signature in training set and testing set, respectively. We found the survival time of KIRC patients with low-risk scores was significantly better than those with high-risk scores in training set and testing set. ROC curves suggested that the area under the ROC (AUC) value for prognostic risk score signature was 0.81 in training set and 0.705 in testing set. And AUC values corresponding to 1-, 3-, and 5 years of OS were 0.809, 0.753, and 0.794 in training set and 0.698, 0.682, and 0.754 in testing set, respectively. We established the two nomograms that confirmed high C-index and accomplished good prediction accuracy. Conclusions We constructed a prognostic risk-related ARlncRNAs signature that could accurately predict the prognosis of KIRC patients.

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5 results found

Open accessJournal ArticleDOI: 10.1002/CAM4.3963
Chuan Zhang1, Dan Dang1, Lele Cong1, Hongyan Sun1  +1 moreInstitutions (1)
22 Jun 2021-Cancer Medicine
Abstract: Background Considering melanoma is the deadliest malignancy among dermatoma and presently lacks effective therapies, there is an urgent need to investigate the potential mechanisms underlying melanoma metastasis and determine prospective therapeutic targets for precise treatment of melanoma. Method Hub genes in melanoma metastasis were identified by analyzing RNA-seq data (mRNA, miRNA, and lncRNA) obtained from TCGA database. Then the identified hub genes were validated in human tissues with qRT-PCR, followed by survival analysis. Competing endogenous RNAs of the hub genes were defined to clarify potential molecular mechanism of melanoma progression. Then central gene-related signaling pathways were analyzed, followed by immune cell abundance analysis in tumor microenvironment with CYTERSORTx. Result A tetrad of IL2RA, IL2RG, IFNG, and IL7R genes were determined as hub genes and verified by qRT-PCR, which were significantly associated with unfavorable prognosis in melanoma. LINC02446, LINC01857, and LINC02384 may act as competing endogenous lncRNAs of IL2RA and IL7R through absorbing their shared miR.891a.5p and miR.203b.3p. JAK-STAT signaling pathway identified as the most relevant pathway in melanoma metastasis, as well as a wealthy of genes including TNFRSF 13B, TNFRSF17, TNFRSF9, TNFRSF8, TNFRSF13C, TNFRSF11B, LAG3, NRP1, ENTPD1, NT5E, CCL21, and CCR7, may induce tumor autoimmune suppression through enhancing regulatory T-cell abundance and performance in the tumor microenvironment. And regulatory T-cell proportion was indeed critically elevated in metastatic melanoma relative to primary melanoma, as well as in highly expressed IL2RA, IL2RG, IL7R, and IFNG group than their respective counterparts. Conclusion Elevated IL2RA, IL2RG, IL7R, and IFNG expression may play a central role in promoting melanoma metastasis through up regulation of intratumoral regulatory T-cell proportion mainly by activation of JAK-STAT signaling pathway. LINC02446, LINC01857, and LINC02384 may stimulate melanoma progression by reducing tumor-protecting miR.891a.5p and miR.203b.3p. A number of identified molecules including TNFRSF13B, LAG3, NRP1, ENTPD1, NT5E, CCL21, and CCR7 can serve as future therapeutic targets in melanoma treatment.

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Topics: Melanoma (55%), Tumor microenvironment (54%), Competing endogenous RNA (51%) ... read more

2 Citations

Open accessJournal ArticleDOI: 10.1155/2021/2042114
Yusa Chen1, Yumei Liang1, Ying Chen1, Sha-Xi OuYang1  +2 moreInstitutions (1)
Abstract: Background. Clear cell renal cell carcinoma (ccRCC) is a cancer with abnormal metabolism. The purpose of this study was to investigate the effect of metabolism-related genes on the prognosis of ccRCC patients. Methods. The data of ccRCC patients were downloaded from the TCGA and the GEO databases and clustered using the nonnegative matrix factorization method. The limma software package was used to analyze differences in gene expression. A random forest model was used to screen for important genes. A novel Riskscore model was established using multivariate regression. The model was evaluated based on the metabolic pathway, immune infiltration, immune checkpoint, and clinical characteristics. Results. According to metabolism-related genes, kidney clear cell carcinoma (KIRC) datasets downloaded from TCGA were clustered into two groups and showed significant differences in prognosis and immune infiltration. There were 667 differentially expressed genes between the two clusters, of which 408 were screened by univariate analysis. Finally, 12 differentially expressed genes (MDK, SLC1A1, SGCB, C4orf3, MALAT1, PILRB, IGHG1, FZD1, IFITM1, MUC20, KRT80, and SALL1) were filtered out using the random forest model. The model of Riskscore was obtained by multiplying the expression levels of these 12 genes with the corresponding coefficients of the multivariate regression. We found that the Riskscore correlated with the expression of these 12 genes; the high Riskscore matched the low survival rate verified in the verification set. The analysis found that the Riskscore model was associated with most of the metabolic processes, immune infiltration of cells such as plasma cells, immune checkpoints such as PD-1, and clinical characteristics such as M stage. Conclusion. We established a new Riskscore model for the prognosis of ccRCC based on metabolism. The genes in the model provided several novel targets for the study of ccRCC.

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Topics: Clear cell renal cell carcinoma (56%), MALAT1 (52%)

Journal ArticleDOI: 10.1016/J.BBCAN.2021.188642
Jianqiang Liang1, Lin Zhang1, Wenjun Cheng1Institutions (1)
Abstract: Autophagy, usually referred to as macroautophagy, is a cytoprotective behavior that helps cells, especially cancer cells, escape crises. However, the role of autophagy in cancer remains controversial. The induction of autophagy is favorable for tumor growth, as it can degrade damaged cell components accumulated during nutrient deficiency, chemotherapy, or other stresses in a timely manner. Whereas the antitumor effect of autophagy might be closely related to its crosstalk with metabolism, immunomodulation, and other pathways. Recent studies have verified that lncRNAs and circRNAs modulate autophagy in carcinogenesis, cancer cells proliferation, apoptosis, metastasis, and chemoresistance via multiple mechanisms. A comprehensive understanding of the regulatory relationships between ncRNAs and autophagy in cancer might resolve chemoresistance and also offer intervention strategies for cancer therapy. This review systematically displays the regulatory effects of lncRNAs and circRNAs on autophagy in the contexts of cancer initiation, progression, and resistance to chemo- or radiotherapy and provides a novel insight into cancer therapy.

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Topics: Autophagy (57%), Cancer (54%), Cancer cell (51%) ... read more

Open accessJournal ArticleDOI: 10.3389/FMED.2021.731214
Xiangyu Che1, Wenyan Su2, Xiaowei Li1, Nana Liu1  +2 moreInstitutions (2)
Abstract: Angiogenesis, a process highly regulated by pro-angiogenic and anti-angiogenic factors, is disrupted and dysregulated in cancer. Despite the increased clinical use of angiogenesis inhibitors in cancer therapy, most molecularly targeted drugs have been less effective than expected. Therefore, an in-depth exploration of the angiogenesis pathway is warranted. In this study, the expression of angiogenesis-related genes in various cancers was explored using The Cancer Genome Atlas datasets, whereupon it was found that most of them were protective genes in the patients with kidney renal clear cell carcinoma (KIRC). We divided the samples from the KIRC dataset into three clusters according to the mRNA expression levels of these genes, with the enrichment scores being in the order of Cluster 2 (upregulated expression) > Cluster 3 (normal expression) > Cluster 1 (downregulated expression). The survival curves plotted for the three clusters revealed that the patients in Cluster 2 had the highest overall survival rates. Via a sensitivity analysis of the drugs listed on the Genomics of Drug Sensitivity in Cancer database, we generated IC50 estimates for 12 commonly used molecularly targeted drugs for KIRC in the three clusters, which can provide a more personalized treatment plan for the patients according to angiogenesis-related gene expression. Subsequently, we investigated the correlation between the angiogenesis pathway and classical cancer-related genes as well as that between the angiogenesis score and immune cell infiltration. Finally, we used the least absolute shrinkage and selection operator (LASSO)-Cox regression analysis to construct a risk score model for predicting the survival of patients with KIRC. According to the areas under the receiver operating characteristic (ROC) curves, this new survival model based on the angiogenesis-related genes had high prognostic prediction value. Our results should provide new avenues for the clinical diagnosis and treatment of patients with KIRC.

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Topics: Cancer (54%), Angiogenesis (51%), Angiogenesis Pathway (50%)

Open accessJournal ArticleDOI: 10.2147/IJGM.S333697
Xiaobo Shi1, Xiaoxiao Liu1, Shupei Pan1, Yue Ke1  +6 moreInstitutions (1)
Abstract: Background Considering the significance of autophagy and long non-coding RNAs (lncRNAs) in the biology of esophageal squamous cell carcinoma (ESCC), the present study aimed to identify a new autophagy-related lncRNA signature to forecast the clinical outcomes of ESCC patients and to guide individualized treatment. Methods The expression profiles were obtained from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) database. We extracted autophagy-related genes from the Human Autophagy Database and identified autophagy-related lncRNAs through Spearman correlation analysis. Univariate, least absolute shrinkage and selection operator and multivariate Cox regression analyses were performed on GSE53625 to construct an autophagy-related lncRNAs prognostic signature. The model was subjected to bootstrap internal validation, and the expression levels of lncRNAs were verified by TCGA database. The potential molecular mechanism of the model was explored by gene set enrichment analysis (GSEA). Spearman correlation coefficient examined the correlation between risk score and ferroptosis-associated genes as well as the response to immunotherapy and chemotherapy. Results We identified and validated an autophagy-related lncRNAs prognostic signature in 179 patients with ESCC. The prognosis of patients in the low-risk group was significantly better than that in the high-risk group (p-value <0.001). The reliability of the model was verified by Brier score and ROC. GSEA results showed significant enrichment of cancer- and autophagy-related signaling pathways in the high-risk group and metabolism-related pathways in the low-risk group. Correlation analysis indicated that the model can effectively forecast the effect of immunotherapy and chemotherapy. About 35.41% (74/209) ferroptosis-related genes were significantly correlated with risk scores. Conclusion In brief, we constructed a novel autophagy-related lncRNAs signature (LINC02024, LINC01711, LINC01419, LCAL1, FENDRR, ADAMTS9-AS1, AC025244.1, AC015908.6 and AC011997.1), which could improve the prediction of clinical outcomes and guide individualized treatment of ESCC patients.

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32 results found

Open accessJournal ArticleDOI: 10.3322/CAAC.21551
Abstract: Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths that will occur in the United States and compiles the most recent data on cancer incidence, mortality, and survival. Incidence data, available through 2015, were collected by the Surveillance, Epidemiology, and End Results Program; the National Program of Cancer Registries; and the North American Association of Central Cancer Registries. Mortality data, available through 2016, were collected by the National Center for Health Statistics. In 2019, 1,762,450 new cancer cases and 606,880 cancer deaths are projected to occur in the United States. Over the past decade of data, the cancer incidence rate (2006-2015) was stable in women and declined by approximately 2% per year in men, whereas the cancer death rate (2007-2016) declined annually by 1.4% and 1.8%, respectively. The overall cancer death rate dropped continuously from 1991 to 2016 by a total of 27%, translating into approximately 2,629,200 fewer cancer deaths than would have been expected if death rates had remained at their peak. Although the racial gap in cancer mortality is slowly narrowing, socioeconomic inequalities are widening, with the most notable gaps for the most preventable cancers. For example, compared with the most affluent counties, mortality rates in the poorest counties were 2-fold higher for cervical cancer and 40% higher for male lung and liver cancers during 2012-2016. Some states are home to both the wealthiest and the poorest counties, suggesting the opportunity for more equitable dissemination of effective cancer prevention, early detection, and treatment strategies. A broader application of existing cancer control knowledge with an emphasis on disadvantaged groups would undoubtedly accelerate progress against cancer.

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Topics: Cancer Death Rate (71%), Cancer prevention (66%), Mortality rate (60%) ... read more

11,980 Citations

Open accessJournal ArticleDOI: 10.1126/SCIENCE.290.5497.1717
Daniel J. Klionsky1, Scott D. Emr2Institutions (2)
01 Dec 2000-Science
Abstract: Macroautophagy is a dynamic process involving the rearrangement of subcellular membranes to sequester cytoplasm and organelles for delivery to the lysosome or vacuole where the sequestered cargo is degraded and recycled. This process takes place in all eukaryotic cells. It is highly regulated through the action of various kinases, phosphatases, and guanosine triphosphatases (GTPases). The core protein machinery that is necessary to drive formation and consumption of intermediates in the macroautophagy pathway includes a ubiquitin-like protein conjugation system and a protein complex that directs membrane docking and fusion at the lysosome or vacuole. Macroautophagy plays an important role in developmental processes, human disease, and cellular response to nutrient deprivation.

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Topics: Membrane docking (56%), Autophagy (54%), Lysosome (53%) ... read more

3,190 Citations

Open accessJournal ArticleDOI: 10.1038/NATURE10398
Mitchell Guttman1, Julie Donaghey1, Bryce W. Carey2, Manuel Garber1  +18 moreInstitutions (4)
15 Sep 2011-Nature
Abstract: Although thousands of large intergenic non-coding RNAs (lincRNAs) have been identified in mammals, few have been functionally characterized, leading to debate about their biological role. To address this, we performed loss-of-function studies on most lincRNAs expressed in mouse embryonic stem (ES) cells and characterized the effects on gene expression. Here we show that knockdown of lincRNAs has major consequences on gene expression patterns, comparable to knockdown of well-known ES cell regulators. Notably, lincRNAs primarily affect gene expression in trans. Knockdown of dozens of lincRNAs causes either exit from the pluripotent state or upregulation of lineage commitment programs. We integrate lincRNAs into the molecular circuitry of ES cells and show that lincRNA genes are regulated by key transcription factors and that lincRNA transcripts bind to multiple chromatin regulatory proteins to affect shared gene expression programs. Together, the results demonstrate that lincRNAs have key roles in the circuitry controlling ES cell state.

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1,683 Citations

Open accessJournal ArticleDOI: 10.1038/NATURE10887
16 Feb 2012-Nature
Abstract: It is clear that RNA has a diverse set of functions and is more than just a messenger between gene and protein. The mammalian genome is extensively transcribed, giving rise to thousands of non-coding transcripts. Whether all of these transcripts are functional is debated, but it is evident that there are many functional large non-coding RNAs (ncRNAs). Recent studies have begun to explore the functional diversity and mechanistic role of these large ncRNAs. Here we synthesize these studies to provide an emerging model whereby large ncRNAs might achieve regulatory specificity through modularity, assembling diverse combinations of proteins and possibly RNA and DNA interactions.

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Topics: Functional genomics (54%), RNA (51%), RNA-binding protein (50%)

1,667 Citations

Open accessJournal ArticleDOI: 10.3322/CAAC.21565
Abstract: The number of cancer survivors continues to increase in the United States because of the growth and aging of the population as well as advances in early detection and treatment. To assist the public health community in better serving these individuals, the American Cancer Society and the National Cancer Institute collaborate every 3 years to estimate cancer prevalence in the United States using incidence and survival data from the Surveillance, Epidemiology, and End Results cancer registries; vital statistics from the Centers for Disease Control and Prevention's National Center for Health Statistics; and population projections from the US Census Bureau. Current treatment patterns based on information in the National Cancer Data Base are presented for the most prevalent cancer types. Cancer-related and treatment-related short-term, long-term, and late health effects are also briefly described. More than 16.9 million Americans (8.1 million males and 8.8 million females) with a history of cancer were alive on January 1, 2019; this number is projected to reach more than 22.1 million by January 1, 2030 based on the growth and aging of the population alone. The 3 most prevalent cancers in 2019 are prostate (3,650,030), colon and rectum (776,120), and melanoma of the skin (684,470) among males, and breast (3,861,520), uterine corpus (807,860), and colon and rectum (768,650) among females. More than one-half (56%) of survivors were diagnosed within the past 10 years, and almost two-thirds (64%) are aged 65 years or older. People with a history of cancer have unique medical and psychosocial needs that require proactive assessment and management by follow-up care providers. Although there are growing numbers of tools that can assist patients, caregivers, and clinicians in navigating the various phases of cancer survivorship, further evidence-based resources are needed to optimize care.

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Topics: Population (57%), Cancer (55%), Survivorship curve (52%) ... read more

1,523 Citations