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Towards quantitative and multiplexed in vivo functional cancer genomics

A Correction to this article was published on 16 October 2018

This article has been updated

Abstract

Large-scale sequencing of human tumours has uncovered a vast array of genomic alterations. Genetically engineered mouse models recapitulate many features of human cancer and have been instrumental in assigning biological meaning to specific cancer-associated alterations. However, their time, cost and labour-intensive nature limits their broad utility; thus, the functional importance of the majority of genomic aberrations in cancer remains unknown. Recent advances have accelerated the functional interrogation of cancer-associated alterations within in vivo models. Specifically, the past few years have seen the emergence of CRISPR–Cas9-based strategies to rapidly generate increasingly complex somatic alterations and the development of multiplexed and quantitative approaches to ascertain gene function in vivo.

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Fig. 1: Diversity and complexity of somatic mutations in human cancer genomes.
Fig. 2: Autochthonous mouse models of cancer recapitulate complex and multifaceted genetic and microenvironmental inputs that affect tumorigenesis.
Fig. 3: Strategies to model somatic cancer-associated alterations in mice.
Fig. 4: Increasing the throughput and quantitative nature of functional genomics in vivo through multiplexed approaches.
Fig. 5: Integration of genome engineering with DNA barcoding enables barcode sequencing-based quantitative analysis of tumour suppression and oncogenicity.
Fig. 6: Generating combinatorial alterations in vivo.
Fig. 7: The next frontier: accurately reconstructing and characterizing all aspects of carcinogenesis.

Change history

  • 16 October 2018

    The originally published article failed to acknowledge the equal first authorship contribution of I. P. Winters and C. W. Murray. The article has now been corrected online. The editors apologize for this error.

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Acknowledgements

The authors thank the vibrant and innovative genome editing, cancer genetics and cancer modelling communities for their commitment to data sharing and collaboration. The authors apologize to those authors whose important work they could not highlight owing to space limitations. The authors thank D. Feldser and all members of the Winslow laboratory for helpful comments. I.P.W. and C.W.M. were supported by the US National Science Foundation Graduate Research Fellowship Program. I.P.W was additionally supported by US National Institutes of Health (NIH) grants F31-CA210627 and T32-HG000044. C.W.M. was additionally supported by an Anne T. and Robert M. Bass Stanford Graduate Fellowship. M.M.W. was supported by NIH grants R01-CA175336 and R01-CA207133. The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the various funding bodies or Stanford University.

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Nature Reviews Genetics thanks R. Rad and the other, anonymous reviewer(s) for their contribution to the peer review of this work.

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I.P.W. and C.W.M. contributed equally to all aspects of this manuscript. M.M.W. reviewed and/or edited the manuscript before submission.

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Correspondence to Monte M. Winslow.

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Competing interests

Stanford University has filed a patent on related work on which I.P.W. and M.M.W. are co- inventors. I.P.W. and M.M.W. are co-founders of and hold equity in D2G Oncology, Inc. The authors declare no additional competing interests.

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Glossary

Autochthonous mouse models of cancer

Mouse models in which tumours are initiated de novo from somatic cells and progress within the native in vivo environment.

Organoids

3D cultures of a tissue that recapitulate biological features of a specific organ in a more experimentally tractable in vitro setting.

Allografts

Transplants of cells from a donor mouse into a recipient mouse.

Xenografts

Transplants of cells or bulk tissue from one species into a different species; typically refers to the transplant of human cells or tissue into an immunodeficient mouse.

Driver mutations

Mutations that confer a selective advantage to the cell in which they occur and are therefore causally implicated in tumorigenesis.

Proto-oncogenes

Genes with a normal cellular function that promote tumorigenesis when altered.

Tumour suppressor genes

Genes for which the normal function is to restrain or inhibit tumorigenesis and the loss of which promotes tumorigenesis.

Somatic cancer alterations

Genetic changes in a cancer cell relative to the constitutional genome.

Substitutions

Mutations resulting from the replacement of one nucleotide for another.

Insertion and deletions

(Indels). Mutations resulting from an insertion or deletion of one or more — typically <1,000 — nucleotides.

Structural alterations

Alterations that affect the linear architecture or content of the genome, typically spanning a region of DNA at least 1 kb in length.

Silent

A mutation within a coding region that does not change the amino acid sequence of the encoded protein. It is also used to refer to mutations that have no detectable impact on cellular phenotypes.

Missense

A single-nucleotide substitution in a coding region that results in an amino acid substitution in the encoded protein.

Nonsense

A single-nucleotide substitution in a coding region that introduces a stop codon, creating a truncated protein.

Frameshift

An insertion or deletion in a coding region that alters the triplicate open reading frame of the encoded gene, therefore altering the downstream amino acid sequence of the encoded protein.

Copy number variants

Alterations in which there is a gain or loss of genomic material spanning ≥1 kb.

Translocations

Alterations in which genomic material is transferred from one chromosome to another (non-reciprocal) or exchanged between two chromosomes (reciprocal).

Inversions

Structural alterations in which the orientation of a chromosomal region is inverted.

Oncogenic fusion proteins

The products of the in-frame juxtaposition of two distinct coding sequences as a consequence of a structural alteration, such as a translocation or inversion.

Aneuploidy

An abnormal number of chromosomes in a cell, generally not including multiples of chromosomal complements.

Polyploidy

The presence of more than two complete sets of chromosomes in a cell.

Passenger mutations

Mutations that have no functional effect on the selective fitness of the neoplastic cell in which they occur.

Non-synonymous

A single-nucleotide substitution within a coding region that changes an amino acid in the encoded protein.

Hotspot

A term to describe a localized genomic region that frequently incurs mutations in cancer.

Transgenic mice

Mouse models in which an exogenous genetic element is stably engineered into the mouse germ line.

Single guide RNA

(sgRNA). A synthetic chimeric RNA that encodes a desired CRISPR RNA (crRNA) and the trans-activating CRISPR RNA (tracrRNA) of the CRISPR type II system to direct mammalian genome editing.

Germline alleles

Genetic alterations that are heritable.

Synonymous mutations

Single-nucleotide substitutions within a coding region that do not change the amino acid sequence of the encoded protein.

Chromothripsis

A pattern of extensive chromosomal rearrangements and copy number variants typically confined to one or several chromosomes; thought to result from the random repair of a catastrophic chromosome-shattering event.

Chromoplexy

Large chains of structural alterations that affect multiple chromosomes of the cancer genome; most commonly observed in prostate cancer genomes.

Kataegis

A pattern of localized hypermutation that typically coincides with chromothripsis.

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Winters, I.P., Murray, C.W. & Winslow, M.M. Towards quantitative and multiplexed in vivo functional cancer genomics. Nat Rev Genet 19, 741–755 (2018). https://doi.org/10.1038/s41576-018-0053-7

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