CoChat
Sign Up
Cited by 64Cancer Genomics and DiagnosticsGenomics and Chromatin DynamicsChromatin Remodeling and Cancer

Discovery of regulatory noncoding variants in individual cancer genomes by using cis-X

Open access
Liu, Yu, Li, Chunliang, Shen, Shuhong, Chen, Xiaolong, Szlachta, Karol, Edmonson, Michael N., Shao, Ying, Ma, Xiaotu +14 more·2020·Nature Genetics
DOI 10.1038/s41588-020-0659-5PMC PMC7679232
Open this paper in CoChat — free account

Abstract

We developed cis-X, a computational method for discovering regulatory noncoding variants in cancer by integrating whole-genome and transcriptome sequencing data from a single cancer sample. cis-X first finds aberrantly cis-activated genes that exhibit allele-specific expression accompanied by an elevated outlier expression. It then searches for causal noncoding variants that may introduce aberrant transcription factor binding motifs or enhancer hijacking by structural variations. Analysis of 13 T-lineage acute lymphoblastic leukemias identified a recurrent intronic variant predicted to cis-activate the TAL1 oncogene, a finding validated in vivo by chromatin immunoprecipitation sequencing of a patient-derived xenograft. Candidate oncogenes include the prolactin receptor PRLR activated by a focal deletion that removes a CTCF-insulated neighborhood boundary. cis-X may be applied to pediatric and adult solid tumors that are aneuploid and heterogeneous. In contrast to existing approaches, which require large sample cohorts, cis-X enables the discovery of regulatory noncoding variants in individual cancer genomes.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/s41588-020-0659-5

Cites

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Three groups of gain-of-function mutations affecting TAL1 in T-ALL-a cluster of 5′ neo-enhancer mutations upstream of TAL1 TSS, an intronic SNV and a 3′ neo-enhancer-converge on a common mechanism of upregulation of the TAL1 oncogene.

    “We evaluated three groups of gain-of-function mutations affecting the TAL1 gene in T cell acute lymphoblastic leukaemia (T-ALL): a cluster of 5′ neo-enhancer mutations upstream of the TAL1 TSS6,33, an intronic single-nucleotide variant (SNV)34 and a 3′ neo-enhancer35.”

    From Advancing regulatory variant effect prediction with AlphaGenome (2026) · cites this paper as [34]

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

No citation lists for this paper

No citation lists for this paper yet — checked again daily.

References 69 · Cited by 64

Research works printed but not linked: 62

  1. [1]Encode Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57– 74 (2012). 22955616 PMC3439153
  2. [3]Khurana E Role of non-coding sequence variants in cancer. Nat Rev Genet 17, 93– 108 (2016). 26781813
  3. [7]Zhang J Deregulation of DUX4 and ERG in acute lymphoblastic leukemia. Nat Genet 48, 1481– 1489 (2016). 27776115 PMC5144107
  4. [8]Zhang X Identification of focally amplified lineage-specific super-enhancers in human epithelial cancers. Nat Genet 48, 176– 82 (2016). 26656844 PMC4857881
  5. [10]Huang FW Highly recurrent TERT promoter mutations in human melanoma. Science 339, 957– 9 (2013). 23348506 PMC4423787
  6. [11]Horn S TERT promoter mutations in familial and sporadic melanoma. Science 339, 959– 61 (2013). 23348503
  7. [12]Rheinbay E Analyses of non-coding somatic drivers in 2,658 cancer whole genomes. Nature 578, 102– 111 (2020). 32025015 PMC7054214
  8. [14]Fredriksson NJ, Ny L, Nilsson JA & Larsson E Systematic analysis of noncoding somatic mutations and gene expression alterations across 14 tumor types. Nat Genet 46, 1258– 63 (2014). 25383969
  9. [16]Melton C, Reuter JA, Spacek DV & Snyder M Recurrent somatic mutations in regulatory regions of human cancer genomes. Nat Genet 47, 710– 6 (2015). 26053494 PMC4485503
  10. [17]Kim K Chromatin structure-based prediction of recurrent noncoding mutations in cancer. Nat Genet 48, 1321– 1326 (2016). 27723759
  11. [18]Ma X Pan-cancer genome and transcriptome analyses of 1,699 paediatric leukaemias and solid tumours. Nature 555, 371– 376 (2018). 29489755 PMC5854542
  12. [19]Dixon JR Topological domains in mammalian genomes identified by analysis of chromatin interactions. Nature 485, 376– 80 (2012). 22495300 PMC3356448
  13. [20]Belver L & Ferrando A The genetics and mechanisms of T cell acute lymphoblastic leukaemia. Nat Rev Cancer 16, 494– 507 (2016). 27451956
  14. [21]Liu Y The genomic landscape of pediatric and young adult T-lineage acute lymphoblastic leukemia. Nat Genet 49, 1211– 1218 (2017). 28671688 PMC5535770
  15. [22]Li Z APOBEC signature mutation generates an oncogenic enhancer that drives LMO1 expression in T-ALL. Leukemia (2017). PMC5629363 28260788
  16. [23]Hu S Whole-genome noncoding sequence analysis in T-cell acute lymphoblastic leukemia identifies oncogene enhancer mutations. Blood 129, 3264– 3268 (2017). 28408461 PMC5472902
  17. [24]Abraham BJ Small genomic insertions form enhancers that misregulate oncogenes. Nat Commun 8, 14385 (2017). 28181482 PMC5309821
  18. [25]Rahman S Activation of the LMO2 oncogene through a somatically acquired neomorphic promoter in T-cell acute lymphoblastic leukemia. Blood (2017). PMC5472898 28270453
  19. [26]Mayba O MBASED: allele-specific expression detection in cancer tissues and cell lines. Genome Biol 15, 405 (2014). 25315065 PMC4165366
  20. [27]Pawlikowska I The most informative spacing test effectively discovers biologically relevant outliers or multiple modes in expression. Bioinformatics 30, 1400– 8 (2014). 24458951 PMC4068004
  21. [28]Simonis M High-resolution identification of balanced and complex chromosomal rearrangements by 4C technology. Nat Methods 6, 837– 42 (2009). 19820713
  22. [29]Weintraub AS YY1 Is a Structural Regulator of Enhancer-Promoter Loops. Cell 171, 1573– 1588 e28 (2017). 29224777 PMC5785279
  23. [30]Ali S & Ali S Prolactin receptor regulates Stat5 tyrosine phosphorylation and nuclear translocation by two separate pathways. J Biol Chem 273, 7709– 16 (1998). 9516478
  24. [31]Goffin V Prolactin receptor targeting in breast and prostate cancers: New insights into an old challenge. Pharmacol Ther 179, 111– 126 (2017). 28549597
  25. [32]Pugh TJ The genetic landscape of high-risk neuroblastoma. Nat Genet 45, 279– 84 (2013). 23334666 PMC3682833
  26. [33]Peifer M Telomerase activation by genomic rearrangements in high-risk neuroblastoma. Nature 526, 700– 4 (2015). 26466568 PMC4881306
  27. [34]Valentijn LJ TERT rearrangements are frequent in neuroblastoma and identify aggressive tumors. Nat Genet 47, 1411– 4 (2015). 26523776
  28. [35]Davis CF The somatic genomic landscape of chromophobe renal cell carcinoma. Cancer Cell 26, 319– 330 (2014). 25155756 PMC4160352
  29. [36]Zhang Y High-coverage whole-genome analysis of 1220 cancers reveals hundreds of genes deregulated by rearrangement-mediated cis-regulatory alterations. Nat Commun 11, 736 (2020). 32024823 PMC7002524
  30. [37]Akbani R Genomic Classification of Cutaneous Melanoma. Cell 161, 1681– 1696 (2015). 26091043 PMC4580370
  31. [38]Strub T SIRT6 haploinsufficiency induces BRAF. Nat Commun 9, 3440 (2018). 30143629 PMC6109055
  32. [39]Zhou B INO80 governs superenhancer-mediated oncogenic transcription and tumor growth in melanoma. Genes Dev 30, 1440– 53 (2016). 27340176 PMC4926866
  33. [40]Fontanals-Cirera B Harnessing BET Inhibitor Sensitivity Reveals AMIGO2 as a Melanoma Survival Gene. Mol Cell 68, 731– 744.e9 (2017). 29149598 PMC5993436
  34. [41]Kaufman CK A zebrafish melanoma model reveals emergence of neural crest identity during melanoma initiation. Science 351, aad2197 (2016). 26823433 PMC4868069
  35. [42]Lin AW & Lowe SW Oncogenic ras activates the ARF-p53 pathway to suppress epithelial cell transformation. Proc Natl Acad Sci U S A 98, 5025– 30 (2001). 11309506 PMC33157
  36. [44]Zhang Y A cis-element within the ARF locus mediates repression of p16 (INK4A) expression via long-range chromatin interactions. Proc Natl Acad Sci U S A (2019). PMC6936709 31818950
  37. [45]Zhang B & Peng Z Defective folding of mutant p16(INK4) proteins encoded by tumor-derived alleles. J Biol Chem 271, 28734– 7 (1996). 8910511
  38. [46]Walker GJ, Gabrielli BG, Castellano M & Hayward NK Functional reassessment of P16 variants using a transfection-based assay. Int J Cancer 82, 305– 12 (1999). 10389768
  39. [47]Yu M & Ren B The Three-Dimensional Organization of Mammalian Genomes. Annu Rev Cell Dev Biol 33, 265– 289 (2017). 28783961 PMC5837811
  40. [48]Monk M & Holding C Human embryonic genes re-expressed in cancer cells. Oncogene 20, 8085– 91 (2001). 11781821
  41. [49]Roadmap Epigenomics Consortium. Integrative analysis of 111 reference human epigenomes. Nature 518, 317– 30 (2015). 25693563 PMC4530010
  42. [50]Hidalgo M Patient-derived xenograft models: an emerging platform for translational cancer research. Cancer Discov 4, 998– 1013 (2014). 25185190 PMC4167608
  43. [51]Forbes SA COSMIC: somatic cancer genetics at high-resolution. Nucleic Acids Res 45, D777– d783 (2017). 27899578 PMC5210583
  44. [52]Grant CE, Bailey TL & Noble WS FIMO: scanning for occurrences of a given motif. Bioinformatics 27, 1017– 8 (2011). 21330290 PMC3065696
  45. [53]Kulakovskiy IV HOCOMOCO: expansion and enhancement of the collection of transcription factor binding sites models. Nucleic Acids Res 44, D116– 25 (2016). 26586801 PMC4702883
  46. [54]Rao SS A 3D map of the human genome at kilobase resolution reveals principles of chromatin looping. Cell 159, 1665– 80 (2014). 25497547 PMC5635824
  47. [55]Li H & Durbin R Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25, 1754– 60 (2009). 19451168 PMC2705234
  48. [56]Edmonson MN Bambino: a variant detector and alignment viewer for next-generation sequencing data in the SAM/BAM format. Bioinformatics 27, 865– 6 (2011). 21278191 PMC3051333
  49. [57]Chen X CONSERTING: integrating copy-number analysis with structural-variation detection. Nat Methods 12, 527– 30 (2015). 25938371 PMC4591043
  50. [58]Wang J CREST maps somatic structural variation in cancer genomes with base-pair resolution. Nat Methods 8, 652– 4 (2011). 21666668 PMC3527068
  51. [59]MacDonald JR, Ziman R, Yuen RK, Feuk L & Scherer SW The Database of Genomic Variants: a curated collection of structural variation in the human genome. Nucleic Acids Res 42, D986– 92 (2014). 24174537 PMC3965079
  52. [60]Geoffroy V AnnotSV: an integrated tool for structural variations annotation. Bioinformatics 34, 3572– 3574 (2018). 29669011
  53. [61]Parker M C11orf95-RELA fusions drive oncogenic NF-kappaB signalling in ependymoma. Nature 506, 451– 5 (2014). 24553141 PMC4050669
  54. [62]Anders S, Pyl PT & Huber W HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31, 166– 9 (2015). 25260700 PMC4287950
  55. [63]Zhang XL Integrative epigenomic analysis reveals unique epigenetic signatures involved in unipotency of mouse female germline stem cells. Genome Biol 17, 162 (2016). 27465593 PMC4963954
  56. [64]Kharchenko PV, Tolstorukov MY & Park PJ Design and analysis of ChIP-seq experiments for DNA-binding proteins. Nat Biotechnol 26, 1351– 9 (2008). 19029915 PMC2597701
  57. [65]Zhang Y Model-based analysis of ChIP-Seq (MACS). Genome Biol 9, R137 (2008). 18798982 PMC2592715
  58. [66]Cheng Y Principles of regulatory information conservation between mouse and human. Nature 515, 371– 375 (2014). 25409826 PMC4343047
  59. [67]Cancer Genome Atlas N Genomic Classification of Cutaneous Melanoma. Cell 161, 1681– 96 (2015). 26091043 PMC4580370
  60. [68]Quinlan AR & Hall IM BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841– 2 (2010). 20110278 PMC2832824
  61. [69]Strub T SIRT6 haploinsufficiency induces BRAF(V600E) melanoma cell resistance to MAPK inhibitors via IGF signalling. Nat Commun 9, 3440 (2018). 30143629 PMC6109055
  62. [70]Fontanals-Cirera B Harnessing BET Inhibitor Sensitivity Reveals AMIGO2 as a Melanoma Survival Gene. Mol Cell 68, 731– 744 e9 (2017). 29149598 PMC5993436

Authors
Liu, Y., Li, C., Shen, S., Chen, X., Szlachta, K., Edmonson, M. N., Shao, Y., Ma, X., Hyle, J., Wright, S., Ju, B., Rusch, M. C., Liu, Y., Li, B., Macias, M., Tian, L., Easton, J., Qian, M., Yang, J. J., Hu, S., Look, A. T., & Zhang, J.
Affiliations
  • St. Jude Children's Research Hospital (US)
  • Shanghai Jiao Tong University (CN)
  • Soochow University (CN)
  • Boston Children's Hospital (US)
Corresponding author
  • Liu, Yu
  • Zhang, Jinghui
ORCID
Venue
Nature Genetics
Publisher
Springer Science and Business Media LLC
Published
2020-07-06
Volume
52
Issue
8
Pages
811-818
ISSN
  • 1061-4036 (ISSN-L)
  • 1546-1718
DOI
10.1038/s41588-020-0659-5
PMC
PMC7679232
OpenAlex
W3038447707
Cited by
64
References
69
Citations by year
2026: 4 · 2025: 7 · 2024: 9 · 2023: 7 · 2022: 14 · 2021: 19 · 2020: 4
FWCI
3.77
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Genetics (publishedVersion)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
Funders
National Cancer Institute (R35CA210064, R01CA216391, P30CA021765)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
Keywords
cis-activation, allele-specific expression, enhancer hijacking, structural variants, T-cell acute lymphoblastic leukemia, TAL1, intronic variants, focal deletions, patient-derived xenografts, ChIP-seq
MeSH terms
Adolescent, Alleles, Child, Child, Preschool, Chromatin, Enhancer Elements, Genetic, Female, Humans, Male, Oncogenes, Transcription, Genetic, Genetic Variation, Gene Expression Regulation, Neoplastic, RNA, Untranslated, Precursor Cell Lymphoblastic Leukemia-Lymphoma

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review