Insertions and Deletions Target Lineage-Defining Genes in Human Cancers

Imieliński, Marcin; Guo, Guangwu; Meyerson, Matthew

doi:10.1016/j.cell.2016.12.025

Cited by 110 publications

(127 citation statements)

References 81 publications

Supporting

Mentioning

113

Contrasting

Unclassified

Order By: Relevance

“…2a, Supplementary Note Fig. 38 ), which were reported to frequently occur in highly expressed lineage-specific genes in cancer 12 , consistent with experimental data of transcription-replication collisions 34 .…”

Section: [C>t]n and T[c>t]n Variant Counts Decline Steadily As Gene Esupporting

confidence: 85%

“…A similar change of the mutation spectrum was observed in Liver-HCC and other cancer types, reflected by the diverging activity of TS07-N[T>C]N and TS08-A[T>C]W. The activity of TS08 is most prominent in highly transcribed genes, indicative of transcription-associated mutagenesis 12,18 . TensorSignatures unifies the overarching mutational spectrum of this process and sheds light on its genomic determinants.…”

Section: Discussionmentioning

confidence: 55%

“…Mutational signature analysis via computational pattern recognition draws its strength from detecting recurrent patterns of mutations across catalogues of cancer genomes. As many mutational processes also generate characteristic multi nucleotide variants (MNVs) 10,11 , insertion and deletions (indels) [12][13][14] , and structural variants (SVs) 6,[15][16][17] it appears valuable to jointly deconvolve broader mutational catalogues to further understand the multifaceted nature of mutagenesis.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Learning mutational signatures and their multidimensional genomic properties with TensorSignatures

Vöhringer

Gerstung

2019

Preprint

View full text Add to dashboard Cite

Key findings• Simultaneous inference of mutational signatures across mutation types and genomic features refines signature spectra and defines their genomic determinants • Two distinct mutational signatures of UV exposure found in active and quiescent chromatin, which may be attributed to differential activity of nucleotide excision repair • Transcription-associated mutagenesis manifesting as A[T>C] mutations is found in a range of cancer types • APOBEC mutagenesis produces two signatures reflecting highly clustered, double strand break repair initiated and lowly clustered replication-driven mutagenesis, respectively • Somatic hypermutation produces a strongly clustered, TSS-associated signature in lymphoid cancers, which is distinct from a weakly clustered TLS signature found in multiple tumour types. AbstractMutational signature analysis is an essential part of the cancer genome analysis toolkit. Conventionally, mutational signature analysis extracts patterns of different mutation types across many cancer genomes. Here we present TensorSignatures, an algorithm to learn mutational signatures jointly across all variant categories and their genomic context. The analysis of 2,778 cancer genomes of the PCAWG consortium shows that practically all signatures operate dynamically in response to various genomic and epigenomic states. The analysis pins differential spectra of UV mutagenesis found in active and inactive chromatin to global genome nucleotide excision repair. TensorSignatures accurately characterises transcription-associated mutagenesis, which is detected in 7 different cancer types. The analysis also unmasks replication and double strand break repair driven APOBEC mutagenesis, which manifests with differential numbers and length of mutation clusters indicating a differential processivity of the two triggers. As a fourth example, TensorSignatures detects a signature of somatic hypermutation generating highly clustered variants around the transcription start sites of active genes in lymphoid leukaemia, distinct from a more general and less clustered signature of Polη-driven TLS found in a broad range of cancer types. Directional effectsMutation rates may differ between template and coding strand, because RNA polymerase II recruits transcription coupled nucleotide excision repair (TC-NER) upon lesion recognition

show abstract

Section: [C>t]n and T[c>t]n Variant Counts Decline Steadily As Gene Esupporting

confidence: 85%

Section: Discussionmentioning

confidence: 55%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Learning mutational signatures and their multidimensional genomic properties with TensorSignatures

Vöhringer

Gerstung

2019

Preprint

View full text Add to dashboard Cite

show abstract

“…The understanding of GC pathogenesis involves many mutations and amplifications of tumor suppressor genes and oncogenes [11-13]. However, the mechanism of GC development remains largely unknown.…”

Section: Discussionmentioning

confidence: 99%

C/D-Box Snord105b Promotes Tumorigenesis in Gastric Cancer via ALDOA/C-Myc Pathway

Zhang¹,

Zhao²,

Wu³

et al. 2018

Cell Physiol Biochem

View full text Add to dashboard Cite

Background/Aims: Small nucleolar RNAs (snoRNAs) play an important role in carcinogenesis. In this study, we identified a C/D box snoRNA, snord105b, and further investigated the function and mechanism of the snord105b in gastric cancer (GC). Methods: The expression level of snord105b in GC tissures, sera and cell lines were detected by qRT-PCR. Cell viability was assessed using MTS assay. Transwell and wound healing assay were performed to evaluate migration and invasion, and protein expression was examined by western blotting. ChIRP and MS analysis was used to seek for the special binding protein of snord105b. Results: The snord105b was upregulated and associated with tumor size, differentiation, and pathological stage in GC. Snord105b affected proliferation, migration and invasion in multiple GC cell lines. The oncoqenic activity of snord105b was also confirmed with in vivo data. Mechanistically, snord105b specifically bound to ALDOA and affected C-myc, which plays a key role in carcinogenesis and tumor development. Conclusion: Snord105b appears to be a novel oncogene and is clinically and functionally involved in the development of GC. Targeting snord105b and its pathway may provide new biomarkers or potential treatments for patients with GC.

show abstract

“…Emerging techniques and models of progenitors and mutational processes to link cell lineage to clonal evolution include induced pluripotent stem cells and CRISPR/Cas9 editing to map the evolution of myeloid neoplasia, and cell-fate dynamics, reprogramming, and lineage-specific regulation of progenitor cells, potentially at the single-cell level, to identify and target cancers for early destruction. 60–62 Data from these new models suggest that some premalignant lesions progress to cancer via fundamental epigenetic or transcriptional reprogramming to a progenitor-like state required for driver mutations to induce tumorigenesis. 63 For example, recent studies in BRAF Val600Glu and p53-null zebrafish suggest that initiation of malignant transformation within a so-called cancerised field requires fundamental epigenetic reprogramming of these premalignant cells into an embryonic state via transcription factor-mediated reactivation of genes typically expressed only in neural crest progenitor cells.…”

Section: Preventionmentioning

confidence: 99%

Future cancer research priorities in the USA: a Lancet Oncology Commission

Jaffee

Dang

Agus

et al. 2017

The Lancet Oncology

171

123

View full text Add to dashboard Cite

We are in the midst of a technological revolution that is providing new insights into human biology and cancer. In this era of big data, we are amassing large amounts of information that is transforming how we approach cancer treatment and prevention. Enactment of the Cancer Moonshot within the 21st Century Cures Act in the USA arrived at a propitious moment in the advancement of knowledge, providing nearly US$2 billion of funding for cancer research and precision medicine. In 2016, the Blue Ribbon Panel (BRP) set out a roadmap of recommendations designed to exploit new advances in cancer diagnosis, prevention, and treatment. Those recommendations provided a high-level view of how to accelerate the conversion of new scientific discoveries into effective treatments and prevention for cancer. The US National Cancer Institute is already implementing some of those recommendations. As experts in the priority areas identified by the BRP, we bolster those recommendations to implement this important scientific roadmap. In this Commission, we examine the BRP recommendations in greater detail and expand the discussion to include additional priority areas, including surgical oncology, radiation oncology, imaging, health systems and health disparities, regulation and financing, population science, and oncopolicy. We prioritise areas of research in the USA that we believe would accelerate efforts to benefit patients with cancer. Finally, we hope the recommendations in this report will facilitate new international collaborations to further enhance global efforts in cancer control.

show abstract

Insertions and Deletions Target Lineage-Defining Genes in Human Cancers

Cited by 110 publications

References 81 publications

Learning mutational signatures and their multidimensional genomic properties with TensorSignatures

Learning mutational signatures and their multidimensional genomic properties with TensorSignatures

C/D-Box Snord105b Promotes Tumorigenesis in Gastric Cancer via ALDOA/C-Myc Pathway

Future cancer research priorities in the USA: a Lancet Oncology Commission

Contact Info

Product

Resources

About