scholarly journals Functional annotation of noncoding mutations in cancer

2021 ◽  
Vol 4 (9) ◽  
pp. e201900523
Author(s):  
Husen M Umer ◽  
Karolina Smolinska ◽  
Jan Komorowski ◽  
Claes Wadelius
Keyword(s):  
Cancer Progression ◽  
Somatic Mutations ◽  
Regulatory Elements ◽  
Downstream Effects ◽  
Enhancer Binding Protein ◽  
Whole Genomes ◽  
Cancer Genomes ◽  
Regulatory Mutations ◽  
Significant Enrichment ◽  
Cancer Types

In a cancer genome, the noncoding sequence contains the vast majority of somatic mutations. While very few are expected to be cancer drivers, those affecting regulatory elements have the potential to have downstream effects on gene regulation that may contribute to cancer progression. To prioritize regulatory mutations, we screened somatic mutations in the Pan-Cancer Analysis of Whole Genomes cohort of 2,515 cancer genomes on individual bases to assess their potential regulatory roles in their respective cancer types. We found a highly significant enrichment of regulatory mutations associated with the deamination signature overlapping a CpG site in the CCAAT/Enhancer Binding Protein β recognition sites in many cancer types. Overall, 5,749 mutated regulatory elements were identified in 1,844 tumor samples from 39 cohorts containing 11,962 candidate regulatory mutations. Our analysis indicated 20 or more regulatory mutations in 5.5% of the samples, and an overall average of six per tumor. Several recurrent elements were identified, and major cancer-related pathways were significantly enriched for genes nearby the mutated regulatory elements. Our results provide a detailed view of the role of regulatory elements in cancer genomes.

scholarly journals Predicting pathogenic non-coding SVs disrupting the 3D genome in 1646 whole cancer genomes using multiple instance learning

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Marleen M. Nieboer ◽  
Luan Nguyen ◽  
Jeroen de Ridder
Keyword(s):  
Multiple Instance Learning ◽  
Cancer Diagnostics ◽  
Common Mechanism ◽  
Open Chromatin ◽  
Driver Genes ◽  
3D Genome ◽  
Whole Genomes ◽  
Cancer Genomes ◽  
Cancer Types ◽  
The Impact

AbstractOver the past years, large consortia have been established to fuel the sequencing of whole genomes of many cancer patients. Despite the increased abundance in tools to study the impact of SNVs, non-coding SVs have been largely ignored in these data. Here, we introduce svMIL2, an improved version of our Multiple Instance Learning-based method to study the effect of somatic non-coding SVs disrupting boundaries of TADs and CTCF loops in 1646 cancer genomes. We demonstrate that svMIL2 predicts pathogenic non-coding SVs with an average AUC of 0.86 across 12 cancer types, and identifies non-coding SVs affecting well-known driver genes. The disruption of active (super) enhancers in open chromatin regions appears to be a common mechanism by which non-coding SVs exert their pathogenicity. Finally, our results reveal that the contribution of pathogenic non-coding SVs as opposed to driver SNVs may highly vary between cancers, with notably high numbers of genes being disrupted by pathogenic non-coding SVs in ovarian and pancreatic cancer. Taken together, our machine learning method offers a potent way to prioritize putatively pathogenic non-coding SVs and leverage non-coding SVs to identify driver genes. Moreover, our analysis of 1646 cancer genomes demonstrates the importance of including non-coding SVs in cancer diagnostics.

scholarly journals Cancer Is Associated with Alterations in the Three-Dimensional Organization of the Genome

Cancers ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 1886 ◽  
Author(s):  
Lifei Li ◽  
Nicolai K. H. Barth ◽  
Christian Pilarsky ◽  
Leila Taher
Keyword(s):  
Human Genome ◽  
Cancer Patients ◽  
Cancer Progression ◽  
Gene Expression Regulation ◽  
Cox Regression ◽  
Three Dimensional ◽  
Regulatory Elements ◽  
Cox Regression Analysis ◽  
Regulatory Mutations ◽  
Coding Variants

The human genome is organized into topologically associating domains (TADs), which represent contiguous regions with a higher frequency of intra-interactions as opposed to inter-interactions. TADs contribute to gene expression regulation by restricting the interactions between their regulatory elements, and TAD disruption has been associated with cancer. Here, we provide a proof of principle that mutations within TADs can be used to predict the survival of cancer patients. Specifically, we constructed a set of 1467 consensus TADs representing the three-dimensional organization of the human genome and used Cox regression analysis to identify a total of 35 prognostic TADs in different cancer types. Interestingly, only 46% of the 35 prognostic TADs comprised genes with known clinical relevance. Moreover, in the vast majority of such cases, the prognostic value of the TAD was not directly related to the presence/absence of mutations in the gene(s), emphasizing the importance of regulatory mutations. In addition, we found that 34% of the prognostic TADs show strong structural perturbations in the cancer genome, consistent with the widespread, global epigenetic dysregulation often observed in cancer patients. In summary, this study elucidates the mechanisms through which non-coding variants may influence cancer progression and opens new avenues for personalized medicine.

scholarly journals Comprehensive analysis of clustered mutations in cancer reveals recurrent APOBEC3 mutagenesis of ecDNA

2021 ◽  
Author(s):  
Erik N Bergstrom ◽  
Jens-Christian Luebeck ◽  
Mia Petljak ◽  
Vineet Bafna ◽  
Paul S. Mischel ◽  
...  
Keyword(s):  
Somatic Mutations ◽  
Human Cancer ◽  
Cancer Genes ◽  
Base Substitutions ◽  
Cancer Genomes ◽  
Cancer Types ◽  
Mutational Processes ◽  
Comprehensive Characterization

Clustered somatic mutations are common in cancer genomes with prior analyses revealing several types of clustered single-base substitutions, including doublet- and multi-base substitutions, diffuse hypermutation termed omikli, and longer strand-coordinated events termed kataegis. Here, we provide a comprehensive characterization of clustered substitutions and clustered small insertions and deletions (indels) across 2,583 whole-genome sequenced cancers from 30 cancer types. While only 3.7% of substitutions and 0.9% of indels were found to be clustered, they contributed 8.4% and 6.9% of substitution and indel drivers, respectively. Multiple distinct mutational processes gave rise to clustered indels including signatures enriched in tobacco smokers and homologous-recombination deficient cancers. Doublet-base substitutions were caused by at least 12 mutational processes, while the majority of multi-base substitutions were generated by either tobacco smoking or exposure to ultraviolet light. Omikli events, previously attributed to the activity of APOBEC3 deaminases, accounted for a large proportion of clustered substitutions. However, only 16.2% of omikli matched APOBEC3 patterns with experimental validation confirming additional mutational processes giving rise to omikli. Kataegis was generated by multiple mutational processes with 76.1% of all kataegic events exhibiting AID/APOBEC3-associated mutational patterns. Co-occurrence of APOBEC3 kataegis and extrachromosomal-DNA (ecDNA) was observed in 31% of samples with ecDNA. Multiple distinct APOBEC3 kataegic events were observed on most mutated ecDNA. ecDNA containing known cancer genes exhibited both positive selection and kataegic hypermutation. Our results reveal the diversity of clustered mutational processes in human cancer and the role of APOBEC3 in recurrently mutating and fueling the evolution of ecDNA.

scholarly journals A catalog of cis-regulatory mutations in 12 major cancer types

2019 ◽  
Author(s):  
Zhongshan Cheng ◽  
Michael Vermeulen ◽  
Micheal Rollins-Green ◽  
Brian DeVeale ◽  
Tomas Babak
Keyword(s):  
Gene Expression ◽  
Binding Sites ◽  
Molecular Mechanisms ◽  
Somatic Mutations ◽  
Gene Expression Regulation ◽  
Patient Survival ◽  
Chromatin Accessibility ◽  
Regulatory Mutations ◽  
Cancer Types ◽  
Affect Gene Expression

AbstractDespite the recent availability of complete genome sequences of tumors from thousands of patients, isolating disease-causing (driver) non-coding mutations from the plethora of somatic variants is notoriously challenging, and only a handful of validated examples exist. By integrating whole-genome sequencing, gene expression, chromatin accessibility, and genetic data from TCGA, we identified 301 non-coding somatic mutations that affect gene expression in cis. These mutations cluster into 36 hotspot regions with diverse molecular mechanisms of gene expression regulation. We further show that these mutations have hallmark features of noncoding drivers; namely, that they confer a positive selection on growth, functionally disrupt transcription factor binding sites, and contribute to disease progression reflected in decreased overall patient survival.

scholarly journals Mutational likeliness and entropy help to identify driver mutations and their functional role in cancer

2018 ◽  
Author(s):  
Giorgio Mattiuz ◽  
Salvatore Di Giorgio ◽  
Lorenzo Tofani ◽  
Antonio Frandi ◽  
Francesco Donati ◽  
...  
Keyword(s):  
Cancer Progression ◽  
Somatic Mutations ◽  
Driver Mutations ◽  
Cancer Evolution ◽  
Loss Of Function ◽  
Driver Genes ◽  
Cancer Driver ◽  
Cancer Genomes ◽  
Passenger Mutations ◽  
Mutational Processes

AbstractAlterations in cancer genomes originate from mutational processes taking place throughout oncogenesis and cancer progression. We show that likeliness and entropy are two properties of somatic mutations crucial in cancer evolution, as cancer-driver mutations stand out, with respect to both of these properties, as being distinct from the bulk of passenger mutations. Our analysis can identify novel cancer driver genes and differentiate between gain and loss of function mutations.

scholarly journals Structure and Regulation of the Salivary Gland Secretion Protein Gene Sgs-1 of Drosophila melanogaster

Genetics ◽  
1999 ◽  
Vol 153 (2) ◽  
pp. 753-762
Author(s):  
Günther E Roth ◽  
Sigrid Wattler ◽  
Hartmut Bornschein ◽  
Michael Lehmann ◽  
Günter Korge
Keyword(s):  
Drosophila Melanogaster ◽  
Tandem Repeats ◽  
Transcriptional Start Site ◽  
Regulatory Elements ◽  
Coding Region ◽  
Band Shift ◽  
Salivary Gland Secretion ◽  
Enhancer Binding Protein ◽  
Factor Secretion ◽  
Third Instar Larvae

Abstract The Drosophila melanogaster gene Sgs-1 belongs to the secretion protein genes, which are coordinately expressed in salivary glands of third instar larvae. Earlier analysis had implied that Sgs-1 is located at the 25B2-3 puff. We cloned Sgs-1 from a YAC covering 25B2-3. Despite using a variety of vectors and Escherichia coli strains, subcloning from the YAC led to deletions within the Sgs-1 coding region. Analysis of clonable and unclonable sequences revealed that Sgs-1 mainly consists of 48-bp tandem repeats encoding a threonine-rich protein. The Sgs-1 inserts from single λ clones are heterogeneous in length, indicating that repeats are eliminated. By analyzing the expression of Sgs-1/lacZ fusions in transgenic flies, cis-regulatory elements of Sgs-1 were mapped to lie within 1 kb upstream of the transcriptional start site. Band shift assays revealed binding sites for the transcription factor fork head (FKH) and the factor secretion enhancer binding protein 3 (SEBP3) at positions that are functionally relevant. FKH and SEBP3 have been shown previously to be involved in the regulation of Sgs-3 and Sgs-4. Comparison of the levels of steady state RNA and of the transcription rates for Sgs-1 and Sgs-1/lacZ reporter genes indicates that Sgs-1 RNA is 100-fold more stable than Sgs-1/lacZ RNA. This has implications for the model of how Sgs transcripts accumulate in late third instar larvae.

scholarly journals Circulating Cell-Free DNA in Liquid Biopsies as Potential Biomarker for Bladder Cancer: A Review

Cancers ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1448
Author(s):  
Raquel Herranz ◽  
Julia Oto ◽  
Emma Plana ◽  
Álvaro Fernández-Pardo ◽  
Fernando Cana ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Cancer Progression ◽  
Specific Treatment ◽  
Predictive Biomarkers ◽  
Liquid Biopsies ◽  
Cell Free Dna ◽  
Specific Patient ◽  
Free Dna ◽  
Potential Biomarker ◽  
Cancer Types

Bladder cancer (BC) is among the most frequent cancer types in the world and is the most lethal urological malignancy. Presently, diagnostic and follow-up methods for BC are expensive and invasive. Thus, the identification of novel predictive biomarkers for diagnosis, progression, and prognosis of BC is of paramount importance. To date, several studies have evidenced that cell-free DNA (cfDNA) found in liquid biopsies such as blood and urine may play a role in the particular scenario of urologic tumors, and its analysis may improve BC diagnosis report about cancer progression or even evaluate the effectiveness of a specific treatment or anticipate whether a treatment would be useful for a specific patient depending on the tumor characteristics. In the present review, we have summarized the up-to-date studies evaluating the value of cfDNA as potential diagnostic, prognostic, or monitoring biomarker for BC in several biofluids.

scholarly journals Transporter associated with antigen processing 1 (TAP1) expression and prognostic analysis in breast, lung, liver, and ovarian cancer

2021 ◽  
Author(s):  
Anika Tabassum ◽  
Md. Nazmus Samdani ◽  
Tarak Chandra Dhali ◽  
Rahat Alam ◽  
Foysal Ahammad ◽  
...  
Keyword(s):  
Expression Pattern ◽  
Cancer Progression ◽  
Antigen Processing ◽  
Human Cancer ◽  
Analytical Data ◽  
Significant Negative Correlation ◽  
Cancer Tissue ◽  
Human Cancer Cell Lines ◽  
Prognostic Analysis ◽  
Cancer Types

Abstract Transporter associated with antigen processing 1 (TAP1) is a transporter protein that represent tumor antigen in the MHC I or HLA complex. Any defect in the TAP1 gene resulting in inadequate tumor tracking. TAP1 influences multidrug resistance (MDR) in human cancer cell lines and hinders the treatment during chemotherapeutic. The association of TAP1 in cancer progression remains mostly unknown and further study of the gene in relation with cancer need to conduct. Thus, the study has designed to analyze the association between the TAP1 with cancer by computationally. The expression pattern of the gene has determined by using ONCOMINE, GENT2, and GEPIA2 online platforms. The protein level of TAP1 was examined by the help of Human Protein Atlas. Samples with different clinical outcomes were investigated to evaluate the expression and promoter methylation in cancer vs. normal tissues by using UALCAN server. The copy number alteration, mutation frequency, and expression level of the gene in different cancer were analyzed by using cBioPortal server. The PrognoScan and KM plotter platforms were used to perform the survival analysis and represented graphically. Additionally, pathway and gene ontology (GO) features correlated to the TAP1 gene were analyzed and presented by bar charts. After arranging the data in a single panel like correlating expression to prognosis, mutational and alterations characteristic, and pathways analysis, we observed some interesting insights that emphasized the importance of the gene in cancer progression. The study found the relationship between the TAP1 expression pattern and prognosis in different cancer tissues and shows how TAP1 affects the clinical characteristics. The analytical data presented in the study is vital to learn about the effect of TAP1 in tumor tissue, where previously studies showing contradicting expression of TAP1 in cancer tissue. The analyzed data can also be utilized further to evade the threats against chemotherapy. Overall, the study provided a new aspect to consider the role of TAP1 gene in cancer progression and survival status. Key messages • This study demonstrated, for the first time, a correlation between the TAP1 gene and tumor progression. • An upregulation of TAP1 mRNA was demonstrated in various cancer types. • This study reported a significant negative correlation for TAP1 gene expression and the survival rate in different cancer types.

scholarly journals miR-205 in Breast Cancer: State of the Art

2020 ◽  
Vol 22 (1) ◽  
pp. 27
Author(s):  
Ilaria Plantamura ◽  
Alessandra Cataldo ◽  
Giulia Cosentino ◽  
Marilena V. Iorio
Keyword(s):  
Breast Cancer ◽  
Cancer Progression ◽  
Normal Breast ◽  
Response To Therapy ◽  
Aberrant Expression ◽  
Open Questions ◽  
Tumor Tissues ◽  
Breast Physiology ◽  
Cancer Types

Despite its controversial roles in different cancer types, miR-205 has been mainly described as an oncosuppressive microRNA (miRNA), with some contrasting results, in breast cancer. The role of miR-205 in the occurrence or progression of breast cancer has been extensively studied since the first evidence of its aberrant expression in tumor tissues versus normal counterparts. To date, it is known that the expression of miR-205 in the different subtypes of breast cancer is decreasing from the less aggressive subtype, estrogen receptor/progesterone receptor positive breast cancer, to the more aggressive, triple negative breast cancer, influencing metastasis capability, response to therapy and patient survival. In this review, we summarize the most important discoveries that have highlighted the functional role of this miRNA in breast cancer initiation and progression, in stemness maintenance, in the tumor microenvironment, its potential role as a biomarker and its relevance in normal breast physiology—the still open questions. Finally, emerging evidence reveals the role of some lncRNAs in breast cancer progression as sponges of miR-205. Here, we also reviewed the studies in this field.

scholarly journals Role of the NUDT Enzymes in Breast Cancer

2021 ◽  
Vol 22 (5) ◽  
pp. 2267
Author(s):  
Roni H. G. Wright ◽  
Miguel Beato
Keyword(s):  
Breast Cancer ◽  
Signaling Pathways ◽  
Cancer Progression ◽  
Breast Cancers ◽  
Metastatic Colonization ◽  
Hormone Receptor Positive ◽  
Aggressive Cancer ◽  
Cancer Types ◽  
Metastatic Process

Despite global research efforts, breast cancer remains the leading cause of cancer death in women worldwide. The majority of these deaths are due to metastasis occurring years after the initial treatment of the primary tumor and occurs at a higher frequency in hormone receptor-positive (Estrogen and Progesterone; HR+) breast cancers. We have previously described the role of NUDT5 (Nudix-linked to moiety X-5) in HR+ breast cancer progression, specifically with regards to the growth of breast cancer stem cells (BCSCs). BCSCs are known to be the initiators of epithelial-to-mesenchyme transition (EMT), metastatic colonization, and growth. Therefore, a greater understanding of the proteins and signaling pathways involved in the metastatic process may open the door for therapeutic opportunities. In this review, we discuss the role of NUDT5 and other members of the NUDT family of enzymes in breast and other cancer types. We highlight the use of global omics data based on our recent phosphoproteomic analysis of progestin signaling pathways in breast cancer cells and how this experimental approach provides insight into novel crosstalk mechanisms for stratification and drug discovery projects aiming to treat patients with aggressive cancer.

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