scholarly journals Small Nucleolar RNAs (snoRNAs)-Based Risk Score Classifier Predicts Overall Survival in Bladder Carcinoma

2020 ◽  
Vol 26 ◽  
Author(s):  
Rong-Quan He ◽  
Zhi-Guang Huang ◽  
Gao-Qiang Zhai ◽  
Su-Ning Huang ◽  
Yong-Yao Gu ◽  
...  
Keyword(s):  
Overall Survival ◽  
Risk Score ◽  
Bladder Carcinoma ◽  
Small Nucleolar Rnas ◽  
Nucleolar Rnas

scholarly journals Emerging Data on the Diversity of Molecular Mechanisms Involving C/D snoRNAs

2021 ◽  
Vol 7 (2) ◽  
pp. 30
Author(s):  
Laeya Baldini ◽  
Bruno Charpentier ◽  
Stéphane Labialle
Keyword(s):  
Ribosomal Rna ◽  
Molecular Mechanisms ◽  
Molecular Level ◽  
Accurate Description ◽  
Small Nucleolar Rnas ◽  
Age Of Maturity ◽  
Non Coding Rnas ◽  
And Function ◽  
Nucleolar Rnas

Box C/D small nucleolar RNAs (C/D snoRNAs) represent an ancient family of small non-coding RNAs that are classically viewed as housekeeping guides for the 2′-O-methylation of ribosomal RNA in Archaea and Eukaryotes. However, an extensive set of studies now argues that they are involved in mechanisms that go well beyond this function. Here, we present these pieces of evidence in light of the current comprehension of the molecular mechanisms that control C/D snoRNA expression and function. From this inventory emerges that an accurate description of these activities at a molecular level is required to let the snoRNA field enter in a second age of maturity.

scholarly journals A prognostic model based on seven immune-related genes predicts the overall survival of patients with hepatocellular carcinoma

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Qian Yan ◽  
Wenjiang Zheng ◽  
Boqing Wang ◽  
Baoqian Ye ◽  
Huiyan Luo ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
High Risk ◽  
Risk Score ◽  
Immune Cells ◽  
Prognostic Model ◽  
Risk Groups ◽  
Low Risk ◽  
Prognostic Performance ◽  
Immune Related Genes

Abstract Background Hepatocellular carcinoma (HCC) is a disease with a high incidence and a poor prognosis. Growing amounts of evidence have shown that the immune system plays a critical role in the biological processes of HCC such as progression, recurrence, and metastasis, and some have discussed using it as a weapon against a variety of cancers. However, the impact of immune-related genes (IRGs) on the prognosis of HCC remains unclear. Methods Based on The Cancer Gene Atlas (TCGA) and Immunology Database and Analysis Portal (ImmPort) datasets, we integrated the ribonucleic acid (RNA) sequencing profiles of 424 HCC patients with IRGs to calculate immune-related differentially expressed genes (DEGs). Survival analysis was used to establish a prognostic model of survival- and immune-related DEGs. Based on genomic and clinicopathological data, we constructed a nomogram to predict the prognosis of HCC patients. Gene set enrichment analysis further clarified the signalling pathways of the high-risk and low-risk groups constructed based on the IRGs in HCC. Next, we evaluated the correlation between the risk score and the infiltration of immune cells, and finally, we validated the prognostic performance of this model in the GSE14520 dataset. Results A total of 100 immune-related DEGs were significantly associated with the clinical outcomes of patients with HCC. We performed univariate and multivariate least absolute shrinkage and selection operator (Lasso) regression analyses on these genes to construct a prognostic model of seven IRGs (Fatty Acid Binding Protein 6 (FABP6), Microtubule-Associated Protein Tau (MAPT), Baculoviral IAP Repeat Containing 5 (BIRC5), Plexin-A1 (PLXNA1), Secreted Phosphoprotein 1 (SPP1), Stanniocalcin 2 (STC2) and Chondroitin Sulfate Proteoglycan 5 (CSPG5)), which showed better prognostic performance than the tumour/node/metastasis (TNM) staging system. Moreover, we constructed a regulatory network related to transcription factors (TFs) that further unravelled the regulatory mechanisms of these genes. According to the median value of the risk score, the entire TCGA cohort was divided into high-risk and low-risk groups, and the low-risk group had a better overall survival (OS) rate. To predict the OS rate of HCC, we established a gene- and clinical factor-related nomogram. The receiver operating characteristic (ROC) curve, concordance index (C-index) and calibration curve showed that this model had moderate accuracy. The correlation analysis between the risk score and the infiltration of six common types of immune cells showed that the model could reflect the state of the immune microenvironment in HCC tumours. Conclusion Our IRG prognostic model was shown to have value in the monitoring, treatment, and prognostic assessment of HCC patients and could be used as a survival prediction tool in the near future.

scholarly journals Site-Specific Pseudouridine Formation in Preribosomal RNA Is Guided by Small Nucleolar RNAs

Cell ◽  
1997 ◽  
Vol 89 (5) ◽  
pp. 799-809 ◽  
Author(s):  
Philippe Ganot ◽  
Marie-Line Bortolin ◽  
Tamás Kiss
Keyword(s):  
Small Nucleolar Rnas ◽  
Site Specific ◽  
Nucleolar Rnas

scholarly journals Development of an immune-related gene pairs signature for predicting clinical outcome in lung adenocarcinoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chunlei Wu ◽  
Quanteng Hu ◽  
Dehua Ma
Keyword(s):  
Overall Survival ◽  
Regression Analysis ◽  
Lung Adenocarcinoma ◽  
Risk Score ◽  
Cox Regression ◽  
Related Gene ◽  
Cox Regression Analysis ◽  
Gene Pairs ◽  
Immune Related Gene ◽  
Pathological Subtype

AbstractLung adenocarcinoma (LUAD) is the main pathological subtype of Non-small cell lung cancer. We downloaded the gene expression profile and immune-related gene set from the TCGA and ImmPort database, respectively, to establish immune-related gene pairs (IRGPs). Then, IRGPs were subjected to univariate Cox regression analysis, LASSO regression analysis, and multivariable Cox regression analysis to screen and develop an IRGPs signature. The receiver operating characteristic curve (ROC) was applied for evaluating the predicting accuracy of this signature by calculating the area under ROC (AUC) and data from the GEO set was used to validate this signature. The relationship of 22 tumor-infiltrating immune cells (TIICs) to the immune risk score was also investigated. An IRGPs signature with 8 IRGPs was constructed. The AUC for 1- and 3-year overall survival in the TCGA set was 0.867 and 0.870, respectively. Similar results were observed in the AUCs of GEO set 1, 2 and 3 (GEO set 1 [1-year: 0.819; 3-year: 0.803]; GEO set 2 [1-year: 0.834; 3-year: 0.870]; GEO set 3 [1-year: 0.955; 3-year: 0.827]). Survival analysis demonstrated high-risk LUAD patients exhibited poorer prognosis. The multivariable Cox regression indicated that the risk score was an independent prognostic factor. The immune risk score was highly associated with several TIICs (Plasma cells, memory B cells, resting memory CD4 T cells, and activated NK cells). We developed a novel IRGPs signature for predicting 1- and 3- year overall survival in LUAD, which would be helpful for prognosis assessment of LUAD.

Three new small nucleolar RNAs that are psoralen cross-linked in vivo to unique regions of pre-rRNA

1993 ◽  
Vol 13 (7) ◽  
pp. 4382-4390
Author(s):  
O J Rimoldi ◽  
B Raghu ◽  
M K Nag ◽  
G L Eliceiri
Keyword(s):  
Small Rnas ◽  
18S Rrna ◽  
Rnase H ◽  
Antisense Oligodeoxynucleotide ◽  
28S Rrna ◽  
Small Nucleolar Rnas ◽  
Rrna Sequence ◽  
Nucleolar Rna ◽  
Nucleolar Rnas

We have recently described three novel human small nucleolar RNA species with unique nucleotide sequences, which were named E1, E2, and E3. The present article describes specific psoralen photocross-linking in whole HeLa cells of E1, E2, and E3 RNAs to nucleolar pre-rRNA. These small RNAs were cross-linked to different sections of pre-rRNA. E1 RNA was cross-linked to two segments of nucleolar pre-rRNA; one was within residues 697 to 1163 of the 5' external transcribed spacer, and the other one was between nucleotides 664 and 1021 of the 18S rRNA sequence. E2 RNA was cross-linked to a region within residues 3282 to 3667 of the 28S rRNA sequence. E3 RNA was cross-linked to a sequence between positions 1021 and 1639 of the 18S rRNA sequence. Primer extension analysis located psoralen adducts in E1, E2, and E3 RNAs that were enriched in high-molecular-weight fractions of nucleolar RNA. Some of these psoralen adducts might be cross-links of E1, E2, and E3 RNAs to large nucleolar RNA. Antisense oligodeoxynucleotide-targeted RNase H digestion of nucleolar extracts revealed accessible segments in these three small RNAs. The accessible regions were within nucleotide positions 106 to 130 of E1 RNA, positions 24 to 48 and 42 to 66 of E2 RNA, and positions 7 to 16 and about 116 to 122 of E3 RNA. Some of the molecules of these small nucleolar RNAs sedimented as if associated with larger structures when both nondenatured RNA and a nucleolar extract were analyzed.

Combination of quantitative features from H&E biopsies and CT scans predicts response to chemotherapy and overall survival in small cell lung cancer (SCLC).

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 8572-8572
Author(s):  
Cristian Barrera ◽  
Mohammadhadi Khorrami ◽  
Prantesh Jain ◽  
Pingfu Fu ◽  
Kate Butler ◽  
...  
Keyword(s):  
Overall Survival ◽  
Regression Model ◽  
Risk Score ◽  
Risk Group ◽  
Image Features ◽  
Small Cell ◽  
Ct Scans ◽  
Small Cell Lung ◽  
Kaplan Meier ◽  
Response To Chemotherapy

8572 Background: Small Cell Lung Cancer (SCLC) is an aggressive malignancy with a rapid growth, and Chemotherapy remains mainstay of treatment. Identifying therapeutic targets in SCLC presents a challenge, partially due to a lack of accurate and consistently predictive biomarkers. In this study we sought to evaluate the utility of a combination of computer-extracted radiographic and pathology features from pretreatment baseline CT and H&E biopsy images to predict sensitivity to platinum-based chemotherapy and overall survival (OS) in SCLC. Methods: Seventy-eight patients with extensive and limited-stage SCLC who received platinum-doublet chemotherapy were selected. Objective response to chemotherapy (RECIST criteria) and overall survival (OS) as clinical endpoints were available for 51 and 78 patients respectively. The patients were divided randomly into two sets (Training (Sd), Validation (Sv)) with a constraint (equal number of responders and nonresponders in Sd)—Sd comprised twenty-one patients with SCLC. Sv included thirty patients. CT scans and digitized Hematoxylin Eosin-stained (H&E) biopsy images were acquired for each patient. A set of CT derived (46%) and tissue derived (53%) image features were captured. These included shape and textural patterns of the tumoral and peritumoral regions from CT scans and of tumor regions on H&E images. A random forest feature selection and linear regression model were used to identify the most predictive CT and H&E derived image features associated with chemotherapy response from Sd. A Cox proportional hazard regression model was used with these features to compute a risk score for each patients in Sd. Patients in Sv were stratified into high and low-risk groups based on the median risk score. Kaplan-Meier survival analysis was used to assess the prognostic ability of the risk score on Sv. Results: The risk score comprised nine CT (intra and peri-tumoral texture) and six H&E derived (cancer cell texture and shape) features. A linear regression model in conjunction with these 15 features was significantly associated with chemo-sensitivity in Sv (AUC = 0.76, PRC = 0.81). A multivariable model with these 15 features was significantly associated with OS in Sv (HR = 2.5, 95% CI: 1.3-4.9, P = 0.0043). Kaplan-Meier survival analysis revealed a significantly reduced OS in the high-risk group compared to the low-risk group. Conclusions: A combined CT and H&E tissue derived image signature model predicted response to chemotherapy and improved OS in SCLC patients. Image features from baseline CT scans and H&E tissue slide images may help in better risk stratification of SCLC patients. Additional independent validation of these quantitative image-based biomarkers is warranted.

Abstract 15984: Rpl13a Small Nucleolar RNAs Promote Oxidative Stress and Atherosclerosis

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Lisheng Zhang ◽  
Jiaohui Wu ◽  
Andrew J Vista ◽  
Leigh Brian ◽  
Yushi Bai ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
Carotid Arteries ◽  
Neointimal Hyperplasia ◽  
Foam Cells ◽  
Slice Thickness ◽  
Small Nucleolar Rnas ◽  
And Migration ◽  
Nucleolar Rnas ◽  
Proliferation And Migration

Reactive oxygen species (ROS) contribute to atherogenesis. An unusual mechanism that increases cellular ROS levels and oxidative stress involves 4 ubiquitously expressed noncoding small nucleolar RNAs (snoRNAs) from introns of the ribosomal protein L13a ( Rpl13a ) locus: U32a , U33 , U34 , and U35a . We tested the hypothesis that these snoRNAs promote aortic smooth muscle cell (SMC) activation and vascular inflammation, by using “snoKO” mice with targeted deletion of the 4 snoRNAs (but not Rpl13a ). Compared with congenic WT SMCs, snoKO SMCs showed 40±20% lower ROS levels, assessed by DCF fluorescence ( p <0.02). Congruently, ROS levels were 35±5% lower in snoKO than WT aorta and carotid frozen sections ( p <0.01), assessed by CellROX Orange fluorescence. Proliferation and migration evoked by FBS and PDGF-BB, respectively, were each 30±10% less in snoKO than WT SMCs ( p <0.01 for each). To assess SMC migration and proliferation in vivo, we performed carotid artery endothelial denudation. Before injury, snoKO and WT carotid arteries were morphologically equivalent. Four wk after injury, carotid neointimal hyperplasia was 57±9% less and luminal area was 40±20 % more in snoKO than in WT mice ( p <0.01). WT and snoKO mice had equivalent heart rates and systolic blood pressures by tail-cuff plethysmography: 480±20 vs 420±80 beats/min; 133±5, 132±7 mm Hg, respectively (n=5/group). To test whether snoRNAs affect atherosclerosis, we orthotopically transplanted carotid arteries from WT and snoKO mice into congenic Apoe -/- mice. Six wk post-op, atherosclerotic neointima was 70±10% smaller in snoKO than in WT carotids ( p <0.01). To assess SMC-to-foam-cell transdifferentiation, which is ROS-dependent, carotid cross-sections were stained for apoE to identify graft-derived cells and for cholesteryl ester with BODIPY. BODIPY + foam cells comprised 21±3% and 11±7% of neointimal area in WT and snoKO carotids, respectively ( p <0.05). Confocal co-localization of apoE and BODIPY (optical slice thickness 1 μm) showed that graft-derived foam cells were 2.0±0.6-fold more prevalent in WT than in snoKO carotids ( p <0.01). We conclude that Rpl13a snoRNAs promote SMC ROS levels, proliferation and migration in vitro and in vivo, and that these snoRNAs augment atherosclerosis.

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