scholarly journals Cancer-associated dynamics and potential regulators of intronic polyadenylation revealed by IPAFinder using standard RNA-seq data

2021 ◽  
pp. gr.271627.120
Author(s):  
Zhaozhao Zhao ◽  
Qiushi Xu ◽  
Ran Wei ◽  
Weixu Wang ◽  
Dong Ding ◽  
...  
Keyword(s):  
De Novo ◽  
Biological Significance ◽  
Rna Seq ◽  
Coding Region ◽  
Dynamic Changes ◽  
Cancer Tumor ◽  
Tumor Types ◽  
Pan Cancer ◽  
Intronic Poly

Intronic polyadenylation (IpA) usually leads to changes in coding region of an mRNA, and its implication in diseases has been recognized, though at its very beginning status. Conveniently and accurately identifying IpA is of great importance for further evaluating its biological significance. Here, we developed IPAFinder, a bioinformatic method for the de novo identification of intronic poly(A) sites and their dynamic changes from standard RNA-seq data. Applying IPAFinder to 256 pan-cancer tumor/normal pairs across six tumor types, we discovered 490 recurrent dynamically changed IpA events, some of which are novel and derived from cancer-associated genes such as TSC1, SPERD2, and CCND2. Furthermore, IPAFinder revealed that IpA could be regulated by factors related to splicing and m6A modification. In summary, IPAFinder enables the global discovery and characterization of biologically regulated IpA with standard RNA-seq data and should reveal the biological significance of IpA in various processes.

scholarly journals De-novo characterization of the soft-shelled turtle Pelodiscus sinensis transcriptome using Illumina RNA-Seq technology

2013 ◽  
Vol 14 (1) ◽  
pp. 58-67 ◽  
Author(s):  
Wei Wang ◽  
Cai-yan Li ◽  
Chu-tian Ge ◽  
Lei Lei ◽  
You-ling Gao ◽  
...  
Keyword(s):  
De Novo ◽  
Rna Seq ◽  
Pelodiscus Sinensis

scholarly journals Deep Learning Based Tumor Type Classification Using Gene Expression Data

2018 ◽  
Author(s):  
Boyu Lyu ◽  
Anamul Haque
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Tumor Type ◽  
Differential Analysis ◽  
Rna Seq ◽  
Heat Map ◽  
Standard Practices ◽  
Tumor Types ◽  
Pan Cancer

ABSTRACTDifferential analysis occupies the most significant portion of the standard practices of RNA-Seq analysis. However, the conventional method is matching the tumor samples to the normal samples, which are both from the same tumor type. The output using such method would fail in differentiating tumor types because it lacks the knowledge from other tumor types. Pan-Cancer Atlas provides us with abundant information on 33 prevalent tumor types which could be used as prior knowledge to generate tumor-specific biomarkers. In this paper, we embedded the high dimensional RNA-Seq data into 2-D images and used a convolutional neural network to make classification of the 33 tumor types. The final accuracy we got was 95.59%, higher than another paper applying GA/KNN method on the same dataset. Based on the idea of Guided Grad Cam, as to each class, we generated significance heat-map for all the genes. By doing functional analysis on the genes with high intensities in the heat-maps, we validated that these top genes are related to tumor-specific pathways, and some of them have already been used as biomarkers, which proved the effectiveness of our method. As far as we know, we are the first to apply convolutional neural network on Pan-Cancer Atlas for classification, and we are also the first to match the significance of classification with the importance of genes. Our experiment results show that our method has a good performance and could also apply in other genomics data.

scholarly journals Pan-cancer characterization of metabolism-related biomarkers identifies potential therapeutic targets

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Guoshu Bi ◽  
Yunyi Bian ◽  
Jiaqi Liang ◽  
Jiacheng Yin ◽  
Runmei Li ◽  
...  
Keyword(s):  
Metabolic Reprogramming ◽  
The Cancer Genome Atlas ◽  
Score System ◽  
Molecular Features ◽  
Cancer Genome Atlas ◽  
Metabolic Heterogeneity ◽  
Tumor Types ◽  
Pan Cancer ◽  
Worse Prognosis

Abstract Background Generally, cancer cells undergo metabolic reprogramming to adapt to energetic and biosynthetic requirements that support their uncontrolled proliferation. However, the mutual relationship between two critical metabolic pathways, glycolysis and oxidative phosphorylation (OXPHOS), remains poorly defined. Methods We developed a “double-score” system to quantify glycolysis and OXPHOS in 9668 patients across 33 tumor types from The Cancer Genome Atlas and classified them into four metabolic subtypes. Multi-omics bioinformatical analyses was conducted to detect metabolism-related molecular features. Results Compared with patients with low glycolysis and high OXPHOS (LGHO), those with high glycolysis and low OXPHOS (HGLO) were consistently associated with worse prognosis. We identified common dysregulated molecular features between different metabolic subgroups across multiple cancers, including gene, miRNA, transcription factor, methylation, and somatic alteration, as well as investigated their mutual interfering relationships. Conclusion Overall, this work provides a comprehensive atlas of metabolic heterogeneity on a pan-cancer scale and identified several potential drivers of metabolic rewiring, suggesting corresponding prognostic and therapeutic utility.

scholarly journals Optimized detection of somatic allelic imbalances specific for homologous recombination deficiency improves the prediction of clinical outcomes in ovarian cancer

2021 ◽  
Author(s):  
Fernando Ramon Perez-Villatoro ◽  
Julia Casado ◽  
Anniina Farkkila
Keyword(s):  
Ovarian Cancer ◽  
Homologous Recombination ◽  
Clinical Outcomes ◽  
Repair Deficiency ◽  
Improve Patient Selection ◽  
Dna Repair Deficiency ◽  
Tumor Types ◽  
Improve Patient ◽  
Pan Cancer

Specific patterns of genomic allelic imbalances (AIs) have been associated with Homologous recombination DNA-repair deficiency (HRD). We performed a systematic pan-cancer characterization of AIs across tumor types, revealing unique patterns in ovarian cancer. Using machine learning on a multi-omics dataset, we generated an optimized algorithm to detect HRD in ovarian cancer (ovaHRDscar). ovaHRDscar improved the prediction of clinical outcomes in three independent validation cohorts (PCAWG, HERCULES, TERVA). Characterization of 98 spatiotemporally distinct tumor samples indicated ovary/adnex as the preferred site to assess HRD. In conclusion, ovaHRDscar improves the detection of HRD in ovarian cancer with the premise to improve patient selection for HR-targeted therapies.

Molecular Characterization of the T(14;18)(q32;q21) Involving the IGH Locus and the MALT1 Gene in MALT Lymphomas

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 4145-4145
Author(s):  
Eva Maria Murga Penas ◽  
Evelyne Callet-Bauchu ◽  
Nadine Albert ◽  
Sophie Gazzo ◽  
Françoise Berger ◽  
...  
Keyword(s):  
Malt Lymphoma ◽  
De Novo ◽  
Molecular Genetic ◽  
Molecular Characteristics ◽  
Coding Region ◽  
Long Distance ◽  
Igh Locus ◽  
First Case ◽  
Igh Genes

Abstract The t(14;18)(q32;q21) involving the MALT1 and IGH genes is a recurrent abnormality in MALT lymphomas. So far, molecular genetic characterization of the t(14;18)/IGHMALT1 has only been performed in 2 cases and revealed a fusion of the entire coding region of MALT1 to the IGH locus. We herein report the molecular genetic analyses of 2 new cases of MALT lymphoma harboring the t(14;18)/IGH-MALT1 using fluorescence in situ hybridization (FISH) and we determined the molecular characteristics at the IGH-MALT1 junctions using long-distance PCR (LD-PCR). The first case, a 71-year-old female, presented with an extranodal MALT lymphoma of the conjunctiva, stage IEA. The second case, a 53-year-old-male patient, was diagnosed as having a MALT lymphoma originating from the lung. FISH with PAC clones 117B5 and 59N7 revealed a translocation involving MALT1. Further FISH assays with probes hybridizing to MALT1 and IGH showed the t(14;18)(q32;q21)/IGH-MALT1. By FISH with specific probes for the P53, P16, RB1, and ATM genes no deletions of these genes were found. The IGH-MALT1 fusion was confirmed by LD-PCR on patients’ DNA with nested primers for the MALT1 and IGH genes. Cloning and sequencing of the purified PCR products revealed a fusion of sequences upstream of the coding region of MALT1 to the JH segment of the IGH locus in both cases. The breaks on chromosome 18 were located in the 5′ non-coding region of MALT1, only 13 nucleotides apart from each other. The breaks at IGH were located in the JH4 joining segment in both cases and showed features of a V(D)J-mediated recombination. Deletion and “de novo” nucleotides additions at the point of joining were observed in case 1. Furthermore, a detailed analysis of the “de novo” nucleotides additions in this case revealed the presence of DH segments of the DH gene D3-10 in the JH/MALT1 junction. Our findings indicate that the pathomechanism underlying the t(14;18)/IGH-MALT1 in MALT lymphomas is probably based on an illegitimate V(D)J recombination at IGH, similar to other IGH-associated translocations, such as the t(14;18)/IGH-BCL2 in follicular lymphomas and the t(11;14)/CCND1-IGH in mantle cell lymphomas and that the events leading to the t(14;18)/IGH-MALT1 might take place during an initial DH-to-JH or a later VH-to-DJH joining.

Abstract 393: Predicting DNA accessibility in the pan-cancer tumor genome using RNA-Seq, WGS, and deep learning

2017 ◽  
Author(s):  
Kamil Wnuk ◽  
Jeremi Sudol ◽  
Shahrooz Rabizadeh ◽  
Patrick Soon-Shiong ◽  
Christopher Szeto ◽  
...  
Keyword(s):  
Deep Learning ◽  
Rna Seq ◽  
Dna Accessibility ◽  
Cancer Tumor ◽  
Tumor Genome ◽  
Pan Cancer

Tumor inflammatory signature as a biomarker of response to immunotherapy in lung cancer.

2020 ◽  
Vol 38 (5_suppl) ◽  
pp. 47-47
Author(s):  
Sarabjot Pabla ◽  
Erik Van Roey ◽  
Jeffrey M. Conroy ◽  
Sean Glenn ◽  
Yirong Wang ◽  
...  
Keyword(s):  
Cell Activation ◽  
B Cell Activation ◽  
Rna Seq ◽  
Immune Genes ◽  
Tumor Microenvironments ◽  
Inflammatory Score ◽  
Cancer Tumor ◽  
Tumor Inflammation ◽  
Inflammation Group ◽  
Pan Cancer

47 Background: Tumor Inflammation signatures (TIS) comprising multiple immune genes have been shown to enrich for response to ICI. To study this immune phenotype in a large cohort of clinically evaluated patients, we studied gene expression data for a stable pan-cancer tumor inflammation profile and clinical response to ICI. Methods: 1323 FFPE tumors from 35 histologies were tested by RNA-seq, PD-L1 IHC and DNA-seq for TMB. Unsupervised analysis of the RNA-seq data revealed a cluster of 160 genes which separated inflamed from non-inflamed tumor microenvironments (TME). A TIS, algorithmically defined as the mean mRNA expression of the 160 genes was developed with each tumor assigned into a weak, moderate or strong inflammation group. PD-L1 IHC was performed using DAKO 22C3 antibody and considered positive if TPS ≥1%. TMB > 10 mut/Mb was considered high. The TIS, PD-L1 and TMB were independently applied to 110 NSCLC cases for association with ORR to ICIs by RECIST criterion. Results: Unsupervised clustering identified 3 inflammation clusters in the 1323 samples; inflamed (n = 439; 33.2%), borderline (n = 467; 35.3%) and non-inflamed (n = 417; 31.5%). 160 genes are over-represented by T & B-cell activation, IFNg, chemokine, cytokine and interleukin pathways. The TIS algorithm results in an inflammatory score that leads to 3 distinct groups of strong (n = 384; 29.0%), moderate (n = 354; 26.8%) and weak (n = 585; 44.2%) inflammation. Strongly inflamed tumors are over-represented by PD-L1+ tumors (240/384) whereas weakly inflamed tumors are significantly under-represented by PD-L1+ tumors (369/585; p = 1.02e-14). Strongly inflamed tumors presented with improved ORR to ICI in NSCLC (36.6%; 16/44; p = 0.051). Similar results were observed for overall survival for strongly inflamed tumors (median = 16 months; p = 0.0012) vs. weakly inflamed tumors (median = 8 months). ORR for PD-L1+ 33.96% (p = 0.026) and TMB high 21.43% (p = 0.83) were observed. Conclusions: Concurrent measurement of multiple markers led to a comprehensive, stable TIS that predicts host immune response. A strongly inflamed TIS was associated with higher ORR versus single biomarker PD-L1 and TMB in NSCLC.

scholarly journals Characterization of Frond and Flower Development and Identification of FT and FD Genes From Duckweed Lemna aequinoctialis Nd

2021 ◽  
Vol 12 ◽  
Author(s):  
Akiko Yoshida ◽  
Ken-ichiro Taoka ◽  
Aoi Hosaka ◽  
Keisuke Tanaka ◽  
Hisato Kobayashi ◽  
...  
Keyword(s):  
Flower Development ◽  
De Novo ◽  
Wide Distribution ◽  
Proximal Region ◽  
Flower Formation ◽  
Rna Seq ◽  
Flowering Locus T ◽  
Protein Protein Interaction ◽  
Transcriptional Complex

Duckweeds (Araceae: Lemnoideae) are aquatic monocotyledonous plants that are characterized by their small size, rapid growth, and wide distribution. Developmental processes regulating the formation of their small leaf-like structures, called fronds, and tiny flowers are not well characterized. In many plant species, flowering is promoted by the florigen activation complex, whose major components are florigen FLOWERING LOCUS T (FT) protein and transcription factor FD protein. How this complex is regulated at the molecular level during duckweed flowering is also not well understood. In this study, we characterized the course of developmental changes during frond development and flower formation in Lemna aequinoctialis Nd, a short-day plant. Detailed observations of frond and flower development revealed that cell proliferation in the early stages of frond development is active as can be seen in the separate regions corresponding to two budding pouches in the proximal region of the mother frond. L. aequinoctialis produces two stamens of different lengths with the longer stamen growing more rapidly. Using high-throughput RNA sequencing (RNA-seq) and de novo assembly of transcripts from plants induced to flower, we identified the L. aequinoctialis FT and FD genes, whose products in other angiosperms form a transcriptional complex to promote flowering. We characterized the protein-protein interaction of duckweed FT and FD in yeast and examined the functions of the two gene products by overexpression in Arabidopsis. We found that L. aequinoctialis FTL1 promotes flowering, whereas FTL2 suppresses flowering.

scholarly journals Molecular characterization of OsCURT1A from upland rice in response to osmotic stress

2019 ◽  
pp. 1343-1352 ◽  
Author(s):  
Bernadette Toni ◽  
Nurulhikma Md Isa ◽  
Cheng Seng Tan ◽  
Ismanizan Ismail ◽  
Zamri Zainal
Keyword(s):  
Upland Rice ◽  
Crop Improvement ◽  
In Silico Analysis ◽  
Mutant Line ◽  
Potential Candidate ◽  
Rna Seq ◽  
Coding Region ◽  
Heterologous System ◽  
Silico Analysis

CURT1 proteins in Arabidopsis thaliana have been reported to be important for inducing grana curvature. Currently, we have identified transcript encoding CURT1A from Oryza sativa cv. indica through RNA-seq analysis and characterised using heterologous system in Arabidopsis. The OsCURT1A gene shares 80% of its amino acid sequence with Arabidopsis AtCURT1A. Phylogenetic analysis revealed that the OsCURT1A is also closely related to the CURT1 proteins in other choloroplast- conatining organisms. In silico analysis of OsCURT1A promoter shows that several cis-elements related to stress are present in the 5' upstream from the coding region. Under normal conditions, there were no notable changes in the phenotype and chlorophyll a;b ratio between three Arabidopsis genotypes, which were overexpressed (35S::OsCURT1A), T-DNA insertional mutant line (atcurt1a), and Wild type (Col-0). However, overexpression of OsCURT1A under salinity condition demonstrate high chlorophyll a:b compared to Col-0, whereas, the lack of atcurt1a gene in the mutant line showed reduced chlorophyll a:b ratio. These results indicate that the OsCURT1A might have a function as salt-stress related gene, which may indirectly regulate the chlorophyll a:b ratio. Therefore, OsCURT1A can be used as a potential candidate for salinity stress tolerance in crop improvement.

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