scholarly journals Integrative analyses of the RNA modification machinery reveal tissue- and cancer-specific signatures

2019 ◽  
Author(s):  
Oguzhan Begik ◽  
Morghan C. Lucas ◽  
Huanle Liu ◽  
Jose Miguel Ramirez ◽  
John S. Mattick ◽  
...  
Keyword(s):  
Cancer Research ◽  
Expression Patterns ◽  
Rna Modification ◽  
Cancer Type ◽  
Evolutionary Analysis ◽  
Rna Modifications ◽  
Human Samples ◽  
Mammalian Tissues ◽  
Normal Human ◽  
Cancer Types

ABSTRACTBackgroundRNA modifications play central roles in cellular fate and differentiation. These features have placed the epitranscriptome in the forefront of developmental biology and cancer research. However, the machinery responsible for placing, removing and recognizing more than 170 RNA modifications remains largely uncharacterized and poorly annotated, and we currently lack integrative studies that identify which RNA modification–related proteins (RMPs) may be dysregulated in each cancer type.ResultsHere we have performed a comprehensive annotation and evolutionary analysis of human RMPs as well as an integrative analysis of their expression patterns across 32 tissues, 10 species and 13,358 paired tumor-normal human samples. Our analysis reveals an unanticipated heterogeneity of RMP expression patterns across mammalian tissues, with a vast proportion of duplicated enzymes displaying testis-specific expression, suggesting a key role for RNA modifications in sperm formation and possibly intergenerational inheritance. Moreover, through the analysis of paired tumor-normal human samples we uncover many RMPs that are dysregulated in various types of cancer, and whose expression levels are predictive of cancer progression. Surprisingly, we find that several commonly studied RNA modification enzymes such as METTL3 or FTO, are not significantly up-regulated in most cancer types, once the sample is properly scaled and normalized to the full dataset, whereas several less-characterized RMPs, such as LAGE3 and HENMT1, are dysregulated in many cancers.ConclusionsOur analyses reveal an unanticipated heterogeneity in the expression patterns of RMPs across mammalian tissues, and uncover a large proportion of dysregulated RMPs in multiple cancer types. We provide novel targets for future cancer research studies targeting the human epitranscriptome, as well as foundations to understand cell type-specific behaviours that are orchestrated by RNA modifications.

scholarly journals Repurposing RNA sequencing for discovery of RNA modifications in clinical cohorts

2021 ◽  
Vol 7 (32) ◽  
pp. eabd2605
Author(s):  
Kar-Tong Tan ◽  
Ling-Wen Ding ◽  
Chan-Shuo Wu ◽  
Daniel G. Tenen ◽  
Henry Yang
Keyword(s):  
Rna Sequencing ◽  
Cancer Progression ◽  
De Novo ◽  
Rna Modification ◽  
Rna Modifications ◽  
Multiple Cancer ◽  
Patients With Cancer ◽  
Statistical Framework ◽  
Cancer Types ◽  
Nucleotide Resolution

The study of RNA modifications in large clinical cohorts can reveal relationships between the epitranscriptome and human diseases, although this is especially challenging. We developed ModTect (https://github.com/ktan8/ModTect), a statistical framework to identify RNA modifications de novo by standard RNA-sequencing with deletion and mis-incorporation signals. We show that ModTect can identify both known (N1-methyladenosine) and previously unknown types of mRNA modifications (N2,N2-dimethylguanosine) at nucleotide-resolution. Applying ModTect to 11,371 patient samples and 934 cell lines across 33 cancer types, we show that the epitranscriptome was dysregulated in patients across multiple cancer types and was additionally associated with cancer progression and survival outcomes. Some types of RNA modification were also more disrupted than others in patients with cancer. Moreover, RNA modifications contribute to multiple types of RNA-DNA sequence differences, which unexpectedly escape detection by Sanger sequencing. ModTect can thus be used to discover associations between RNA modifications and clinical outcomes in patient cohorts.

scholarly journals m6A target microRNAs in serum for cancer detection

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Bo Zhang ◽  
Zhenmei Chen ◽  
Baorui Tao ◽  
Chenhe Yi ◽  
Zhifei Lin ◽  
...  
Keyword(s):  
Cancer Detection ◽  
External Validation ◽  
High Accuracy ◽  
Rna Modification ◽  
Support Vector ◽  
Cancer Type ◽  
Mass Detection ◽  
Serum Samples ◽  
Multiple Cancer ◽  
Cancer Types

AbstractRecent studies have revealed the significant dysregulation of m6A level in peripheral blood in several cancer types and its value in diagnosis. Nonetheless, a biomarker for accurate screening of multiple cancer types has not been established based on the perspective of m6A modification. In this study, we aimed to develop a serum diagnostic signature based on the m6A target miRNAs for the mass detection of cancer. A total of 14965 serum samples with 12 cancer types were included. Based on training cohort (n=7299), we developed the m6A-miRNAs signature using a support vector machine algorithm for cancer detection. The m6A-miRNAs signature showed high accuracy, and its area under the curve (AUC) in the training, internal validation and external validation cohort reached 0.979 (95%CI 0.976 - 0.982), 0.976 (95%CI 0.973 - 0.979) and 0.936 (95%CI 0.922 - 0.951), respectively. In the performance of distinguishing cancer types, the m6A-miRNAs signature showed superior sensitivity in each cancer type and presented a satisfactory AUC in identifying lung cancer, gastric cancer and hepatocellular carcinoma. Additionally, the diagnostic performance of m6A-miRNAs was not interfered by the gender, age and benign disease. In short, this study revealed the value of serum circulating m6A miRNAs in cancer detection and provided a new direction and strategy for the development of novel biomarkers with high accuracy, low cost and less invasiveness for mass cancer screening, such as RNA modification.

Integrating molecular profiling into cancer treatment decision making: Experience with over 35,000 cases.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. 11001-11001 ◽  
Author(s):  
Zoran Gatalica ◽  
Sherri Millis ◽  
Sting Chen ◽  
Gargi Dan Basu ◽  
Wenhsiang Wen ◽  
...  
Keyword(s):  
Targeted Therapy ◽  
Protein Expression ◽  
Kras Mutation ◽  
Expression Patterns ◽  
Soft Tissue Sarcomas ◽  
Molecular Profiling ◽  
Cancer Type ◽  
Rare Cancer ◽  
Her2 Amplification ◽  
Cancer Types

11001 Background: Molecular profiling of both common and rare cancer types provides for the identification of actionable targets for chemotherapy with many unexpected associations. Methods: Caris Life Sciences database of >35,000 profiled cancers was reviewed for well-established driver gene mutations and copy number alterations, and protein expression patterns that are relevant for selection of targeted therapy. Based on the published literature, these tumor characteristics were then associated with potential benefit or no benefit to the specific therapeutic agents. All relevant published studies were evaluated using the USPSTF grading scheme for study design and validity. Assay methodologies included sequencing (Sanger, pyrosequencing), PCR, FISH, CISH, and immunohistochemistry. Results: All common malignancies (10 most common cancer types in men and women) and 10 rare cancer types were well represented (minimum of 100 cases in each individual cancer type). Well established driver mutations and protein expression in common cancers were all identified with expected frequencies (e.g. HER2 amplification in breast, PIK3CA mutations in ER+ breast cancer, EGFR mutations in NSCLC, etc.). Importantly, unexpected new and potentially actionable targets were identified in common (e.g., 6.7% HER2 amplification in NSCLC, 1.6% KRAS mutation in prostatic adenocarcinoma) and rare cancers (e.g., 8.3% ALK alteration in soft tissue sarcomas, 10.5% c-MET and 26.4% EGFR gene amplification in melanomas, 16.3% KRAS mutation in cholangiocarcinomas, 10% AR expression in STS), as well in cancers of unknown primary site (approximately 4% of all tested cases). Conclusions: This review of the large referral cancer profiling database provided an unparalleled insight in the distribution of common and rare genetic and protein alterations with direct and potential treatment implications. Numerous targets were discovered that had a potential to be treated by the conventional chemotherapy as well as targeted therapy not usually considered for the cancer type. Comparison between an individual patient tumor profile and database for the matched cancer type provides additional level of support for targeted treatment choices.

scholarly journals Mutually Antagonistic Protein Pairs of Cancer

2021 ◽  
Author(s):  
Ertugrul Dalgic
Keyword(s):  
Differential Expression ◽  
Large Scale ◽  
Expression Patterns ◽  
The Other ◽  
Cancer Type ◽  
Mutual Inhibition ◽  
Extensive Analysis ◽  
Cancer Types ◽  
Specific Antagonist ◽  
Potential Cancer

Switch-like behavior of tumorigenesis could be governed by antagonistic gene and protein pairs with mutual inhibition. Unlike extensive analysis of gene expression, search for protein level antagonistic pairs has been limited. Here, potential cancer type specific antagonist protein pairs with mutual inhibition were obtained from large scale datasets. Cancer samples or cancer types were compared to retrieve potential protein pairs with contrasting differential expression patterns. Analysis of two different protein expression datasets showed that a few proteins participate in most of the mutually antagonistic relationships. Some proteins with highly antagonistic profile were identified, which could not be attained from a differential expression or a correlation based analysis. The antagonistic protein pairs are sparsely connected by molecular interactions. Glioma, melanoma, and cervical cancer, are more frequently associated with antagonistic proteins than most of the other cancer types. Integrative analysis of mutually antagonist protein pairs contributes to our understanding of systems level changes of cancer.

scholarly journals A Pan-Cancer Study of KMT2 Family as Therapeutic Targets in Cancer

2022 ◽  
Vol 2022 ◽  
pp. 1-10
Author(s):  
Jiamin Zhu ◽  
Zhili Liu ◽  
Xiao Liang ◽  
Lu Wang ◽  
Dan Wu ◽  
...  
Keyword(s):  
Overall Survival ◽  
Tumor Microenvironment ◽  
Patient Survival ◽  
Expression Patterns ◽  
Family Members ◽  
Cancer Type ◽  
Tumor Type ◽  
Histone Lysine ◽  
Cancer Types ◽  
Pan Cancer

Objective. Exome sequencing studies have shown that the histone-lysine N-methyltransferase 2 (KMT2) gene is one of the most commonly mutated genes in a range of human malignancies and is linked to some of the most common and deadly solid tumors. However, the connection between this gene family’s function and tumor type, immunological subtype, and molecular subtype dependency is still unknown. Methods. We examine the expression patterns of the histone-lysine N-methyltransferase 2 (KMT2) gene, as well as their relationship to patient survival. We also used a pan-cancer analysis to link their function to immunological subtypes, the tumor microenvironment, and treatment sensitivity. Results. Using the TCGA pan-cancer data, researchers looked at and examined KMT2 expression patterns and their links to patient survival and the tumor microenvironment in 33 cancer types. The expression of the KMT2 family changes significantly across and within cancer types, indicating significant inter- and intracancer heterogeneity. Patients’ overall survival was often linked to the expression of KMT2 family members. However, the direction of the link differed depending on the KMT2 isoform and cancer type studied. Notably, in all cancer types examined, nearly all KMT2 family members were substantially linked with overall survival in patients with renal clear cell carcinoma (KIRC). Furthermore, all KMT2 genes have a strong relationship with immune infiltrate subtypes, as well as varying degrees of stromal cell infiltration and tumor cell stemness. Finally, we discovered that higher expression of KMT2s, particularly KMT2F and KMT2G, was linked to greater chemotherapeutic sensitivity in several cell lines. Conclusions. The necessity to investigate each KMT2 member as a distinct entity inside each particular cancer type is highlighted by our comprehensive investigation of KMT2 gene expression and its relationship with immune infiltrates, tumor microenvironment, and cancer patient outcomes. Our research also confirmed the identification of KMT2 as a potential therapeutic target in cancer, but further laboratory testing is required.

scholarly journals Comprehensive analyses of m6A regulators and interactive coding and non-coding RNAs across 32 cancer types

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Sipeng Shen ◽  
Ruyang Zhang ◽  
Yue Jiang ◽  
Yi Li ◽  
Lijuan Lin ◽  
...  
Keyword(s):  
Wnt Signaling Pathway ◽  
Rna Modification ◽  
Cancer Type ◽  
Individual Level ◽  
Mutation Burden ◽  
Cancer Types ◽  
Unsupervised Approach ◽  
Single Cancer ◽  
Non Coding Rnas ◽  
Interactive Coding

AbstractN6-Methyladenosine (m6A) is an RNA modification that interacts with numerous coding and non-coding RNAs and plays important roles in the development of cancers. Nonetheless, the clinical impacts of m6A interactive genes on these cancers largely remain unclear since most studies focus only on a single cancer type. We comprehensively evaluated m6A modification patterns, including 23 m6A regulators and 83 interactive coding and non-coding RNAs among 9,804 pan-cancer samples. We used clustering analysis to identify m6A subtypes and constructed the m6A signature based on an unsupervised approach. We used the signatures to identify potential m6A modification targets across the genome. The prognostic value of one target was further validated in 3,444 samples from six external datasets. We developed three distinct m6A modification subtypes with different tumor microenvironment cell infiltration degrees: immunological, intermediate, and tumor proliferative. They were significantly associated with overall survival in 24 of 27 cancer types. Our constructed individual-level m6A signature was associated with survival, tumor mutation burden, and classical pathways. With the signature, we identified 114 novel genes as potential m6A targets. The gene shared most commonly between cancer types, BCL9L, is an oncogene and interacts with m6A patterns in the Wnt signaling pathway. In conclusion, m6A regulators and their interactive genes impact the outcome of various cancers. Evaluating the m6A subtype and the signature of individual tumors may inform the design of adjuvant treatments.

scholarly journals Integrated molecular characterisation of endometrioid ovarian carcinoma identifies opportunities for stratification

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Robert L. Hollis ◽  
Barbara Stanley ◽  
John P. Thomson ◽  
Michael Churchman ◽  
Ian Croy ◽  
...  
Keyword(s):  
High Risk ◽  
Ovarian Carcinoma ◽  
Expression Patterns ◽  
Parp Inhibitors ◽  
Receptor Expression ◽  
Cancer Type ◽  
Sequencing Data ◽  
Molecular Features ◽  
Endometrioid Ovarian Carcinoma ◽  
Molecular Landscape

AbstractEndometrioid ovarian carcinoma (EnOC) is an under-investigated ovarian cancer type. Recent studies have described disease subtypes defined by genomics and hormone receptor expression patterns; here, we determine the relationship between these subtyping layers to define the molecular landscape of EnOC with high granularity and identify therapeutic vulnerabilities in high-risk cases. Whole exome sequencing data were integrated with progesterone and oestrogen receptor (PR and ER) expression-defined subtypes in 90 EnOC cases following robust pathological assessment, revealing dominant clinical and molecular features in the resulting integrated subtypes. We demonstrate significant correlation between subtyping approaches: PR-high (PR + /ER + , PR + /ER−) cases were predominantly CTNNB1-mutant (73.2% vs 18.4%, P < 0.001), while PR-low (PR−/ER + , PR−/ER−) cases displayed higher TP53 mutation frequency (38.8% vs 7.3%, P = 0.001), greater genomic complexity (P = 0.007) and more frequent copy number alterations (P = 0.001). PR-high EnOC patients experience favourable disease-specific survival independent of clinicopathological and genomic features (HR = 0.16, 95% CI 0.04–0.71). TP53 mutation further delineates the outcome of patients with PR-low tumours (HR = 2.56, 95% CI 1.14–5.75). A simple, routinely applicable, classification algorithm utilising immunohistochemistry for PR and p53 recapitulated these subtypes and their survival profiles. The genomic profile of high-risk EnOC subtypes suggests that inhibitors of the MAPK and PI3K-AKT pathways, alongside PARP inhibitors, represent promising candidate agents for improving patient survival. Patients with PR-low TP53-mutant EnOC have the greatest unmet clinical need, while PR-high tumours—which are typically CTNNB1-mutant and TP53 wild-type—experience excellent survival and may represent candidates for trials investigating de-escalation of adjuvant chemotherapy to agents such as endocrine therapy.

scholarly journals Proportion of children with cancer that have an indication for genetic counseling and testing based on the cancer type irrespective of other features

2021 ◽  
Author(s):  
Thi Minh Kha Nguyen ◽  
Astrid Behnert ◽  
Torsten Pietsch ◽  
Christian Vokuhl ◽  
Christian Peter Kratz
Keyword(s):  
Childhood Cancer ◽  
Rhabdoid Tumor ◽  
Juvenile Myelomonocytic Leukemia ◽  
Cancer Type ◽  
Nerve Sheath Tumor ◽  
Children With Cancer ◽  
Pediatric Pathology ◽  
Cancer Trial ◽  
Cancer Predisposition Syndrome ◽  
Cancer Types

Abstract In children with cancer, specific clinical features such as physical anomalies, occurrence of cancer in young relatives, specific cancer histologies, and unique mutation/methylation signatures may indicate the presence of an underlying cancer predisposition syndrome (CPS). The proportion of children with a cancer type suggesting a CPS among all children with cancer is unknown. To determine the proportion of children with cancer types suggesting an underlying CPS among children with cancer. We evaluated the number of children with cancer types strongly associated with CPS diagnosed in Germany between 2007 and 2016. Data were obtained from various sources including two national pediatric pathology reference laboratories for brain and solid tumors, respectively, various childhood cancer trial offices as well as the German Childhood Cancer Registry. Among 21,127 children diagnosed with cancer between 2007 and 2016, 2554 (12.1%) had a cancer type strongly associated with a CPS. The most common diagnoses were myelodysplastic syndrome and juvenile myelomonocytic leukemia, retinoblastoma, malignant peripheral nerve sheath tumor, infantile myofibromatosis, medulloblastomaSHH, rhabdoid tumor as well as atypical teratoid/rhabdoid tumor. Based on cancer type only, 12.1% of all children with cancer have an indication for a genetic evaluation. Pediatric oncology patients require access to genetic counselling and testing.

scholarly journals Genome-wide identification and evolutionary analysis of RLKs involved in the response to aluminium stress in peanut

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xin Wang ◽  
Ming-Hua Wu ◽  
Dong Xiao ◽  
Ruo-Lan Huang ◽  
Jie Zhan ◽  
...  
Keyword(s):  
Stress Responses ◽  
Segmental Duplication ◽  
Tandem Duplication ◽  
Expression Patterns ◽  
Purifying Selection ◽  
Segmental Duplications ◽  
Evolutionary Analysis ◽  
Gene Pairs ◽  
Al Stress ◽  
Peanut Genome

Abstract Background As an important cash crop, the yield of peanut is influenced by soil acidification and pathogen infection. Receptor-like protein kinases play important roles in plant growth, development and stress responses. However, little is known about the number, location, structure, molecular phylogeny, and expression of RLKs in peanut, and no comprehensive analysis of RLKs in the Al stress response in peanuts have been reported. Results A total of 1311 AhRLKs were identified from the peanut genome. The AhLRR-RLKs and AhLecRLKs were further divided into 24 and 35 subfamilies, respectively. The AhRLKs were randomly distributed across all 20 chromosomes in the peanut. Among these AhRLKs, 9.53% and 61.78% originated from tandem duplications and segmental duplications, respectively. The ka/ks ratios of 96.97% (96/99) of tandem duplication gene pairs and 98.78% (646/654) of segmental duplication gene pairs were less than 1. Among the tested tandem duplication clusters, there were 28 gene conversion events. Moreover, all total of 90 Al-responsive AhRLKs were identified by mining transcriptome data, and they were divided into 7 groups. Most of the Al-responsive AhRLKs that clustered together had similar motifs and evolutionarily conserved structures. The gene expression patterns of these genes in different tissues were further analysed, and tissue-specifically expressed genes, including 14 root-specific Al-responsive AhRLKs were found. In addition, all 90 Al-responsive AhRLKs which were distributed unevenly in the subfamilies of AhRLKs, showed different expression patterns between the two peanut varieties (Al-sensitive and Al-tolerant) under Al stress. Conclusions In this study, we analysed the RLK gene family in the peanut genome. Segmental duplication events were the main driving force for AhRLK evolution, and most AhRLKs subject to purifying selection. A total of 90 genes were identified as Al-responsive AhRLKs, and the classification, conserved motifs, structures, tissue expression patterns and predicted functions of Al-responsive AhRLKs were further analysed and discussed, revealing their putative roles. This study provides a better understanding of the structures and functions of AhRLKs and Al-responsive AhRLKs.

scholarly journals BART Cancer: a web resource for transcriptional regulators in cancer genomes

NAR Cancer ◽  
2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Zachary V Thomas ◽  
Zhenjia Wang ◽  
Chongzhi Zang
Keyword(s):  
Gene Expression ◽  
Cancer Research ◽  
Computational Prediction ◽  
Transcriptional Regulators ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Regulation Of Transcription ◽  
Data Resource ◽  
Web Resource ◽  
Cancer Types

Abstract Dysregulation of gene expression plays an important role in cancer development. Identifying transcriptional regulators, including transcription factors and chromatin regulators, that drive the oncogenic gene expression program is a critical task in cancer research. Genomic profiles of active transcriptional regulators from primary cancer samples are limited in the public domain. Here we present BART Cancer (bartcancer.org), an interactive web resource database to display the putative transcriptional regulators that are responsible for differentially regulated genes in 15 different cancer types in The Cancer Genome Atlas (TCGA). BART Cancer integrates over 10000 gene expression profiling RNA-seq datasets from TCGA with over 7000 ChIP-seq datasets from the Cistrome Data Browser database and the Gene Expression Omnibus (GEO). BART Cancer uses Binding Analysis for Regulation of Transcription (BART) for predicting the transcriptional regulators from the differentially expressed genes in cancer samples compared to normal samples. BART Cancer also displays the activities of over 900 transcriptional regulators across cancer types, by integrating computational prediction results from BART and the Cistrome Cancer database. Focusing on transcriptional regulator activities in human cancers, BART Cancer can provide unique insights into epigenetics and transcriptional regulation in cancer, and is a useful data resource for genomics and cancer research communities.

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