As we grow and develop, our cells divide. With every cell division, the three billion “letters” of DNA that make up our genetic instructions have to be copied. However, we know that the copying process is not always perfect. Mistakes occasionally occur, and sometimes they can’t be repaired. This process gives rise to cells that do not behave as they should – sometimes they die, sometimes they never divide again, and sometimes, if that mutation or “spelling mistake” in the genetic instructions happens in a gene that controls cell division, then the cells grow in an uncontrolled way. This is how cancer develops.
What cancer researchers haven’t been able to do until now is to find all of the mutations present in a given tumour.
In 1986 the Nobel Laureate, Renato Dulbecco suggested that cancer biologists would never fully understand cancer, until the entire DNA sequence the genome of cancer cells could be obtained. Within the last two years, next generation sequencing technologies have brought this within reach. We can now obtain the same amount of genome sequence in a week from a single computer that took a year and a room full of computers, eight years ago.
Aims and Relevance
Next-generation DNA sequencing technology means that researchers can now study the complete genome of an individual patient’s cancer tumour much faster. They can study which mutations make cells resistant to drug therapy, and are learning which drugs are the most effective for that patient’s cancer. This advances the development of personalized medicine for cancer patients.
We are currently focusing on learning more about the mutations present in distinct subtypes of breast cancer and on building a comprehensive genomic map of breast cancer based on 2,000 cancers. We are focusing on sequencing the genomes of triple negative breast cancers, which are particularly aggressive, and for which there are far fewer treatment options than for other breast cancers.
Named for what it isn’t, triple negative breast cancer is currently defined by three missing cancer-causing proteins (the estrogen receptor, progesterone receptor and ERBB2 receptor), compared to other breast cancer subtypes. Triple negative breast cancer is currently treated as if it’s a single disease and accounts for 16% of all breast cancer diagnoses and approximately 25% of breast cancer deaths.
Our work has shown that this form of cancer is not one distinct single entity, but rather an extremely complex and evolved tumour with an unprecedented range of mutations. We have shown that triple negative breast cancer is not just one uniform subtype of breast cancer; it’s actually extremely complex, with each cancer at a different stage in the evolutionary process at the time of diagnosis, which helps to explain why patient responses to treatment differ greatly. Operating with the complexity of a mini ecosystem, triple negative breast cancers’ evolution before diagnosis may explain its ability to evade current therapies, earning it the distinction as the deadliest form of breast cancer.
In approximately 20% of cases studied, the tumours revealed groupings of genetic mutations that already have potential clinical treatment options in the pipeline. This leads researchers and clinicians toward a future where patients’ tumours could be sequenced as a means to better direct targeted therapies. Pinpointing the exact cellular mutations involved is an important first step in understanding why patients respond differently to treatment. More effective treatments come from being able to identify and target the genetic factors that play a role in the cancer’s growth.
We are also sequencing the DNA of tumours from patients enrolled in clinical trials, to learn whether mutations can be found that predict sensitivity or resistance to drugs.
Recent related papers from the Aparicio and Shah Laboratories
- Ha G, Roth A, Lai D, Bashashati A, Ding J, Goya R, Giuliany R, Rosner J, Oloumi A, Shumansky K, Chin SF, Turashvili G, Hirst M, Caldas C, Marra MA, Aparicio S, Shah SP. Integrative analysis of genome-wide loss of heterozygosity and mono-allelic expression at nucleotide resolution reveals disrupted pathways in triple negative breast cancer. Genome Res. 2012: doi:10.1101/gr.137570.112
- Nik-Zainal S, Alexandrov LB, Wedge DC, Van Loo P, Greenman CD, Raine K, Jones D, Hinton J, Marshall J, Stebbings LA, Menzies A, Martin S, Leung K, Chen L, Leroy C, Ramakrishna M, Rance R, Lau KW, Mudie LJ, Varela I, McBride DJ, Bignell GR, Cooke SL, Shlien A, Gamble J, Whitmore I, Maddison M, Tarpey PS, Davies HR, Papaemmanuil E, Stephens PJ, McLaren S, Butler AP, Teague JW, Jönsson G, Garber JE, Silver D, Miron P, Fatima A, Boyault S, Langerød A, Tutt A, Martens JW, Aparicio SA, Borg A, Salomon AV, Thomas G, Børresen-Dale AL, Richardson AL, Neuberger MS, Futreal PA, Campbell PJ, Stratton MR; the Breast Cancer Working Group of the International Cancer Genome Consortium. Mutational Processes Molding the Genomes of 21 Breast Cancers. Cell 2012: doi 10.1016/j.cell.2012.04.024
- Nik-Zainal S, Van Loo P, Wedge DC, Alexandrov LB, Greenman CD, Lau KW, Raine K, Jones D, Marshall J, Ramakrishna M, Shlien A, Cooke SL, Hinton J, Menzies A, Stebbings LA, Leroy C, Jia M, Rance R, Mudie LJ, Gamble SJ, Stephens PJ, McLaren S, Tarpey PS, Papaemmanuil E, Davies HR, Varela I, McBride DJ, Bignell GR, Leung K, Butler AP, Teague JW, Martin S, Jönsson G, Mariani O, Boyault S, Miron P, Fatima A, Langerød A, Aparicio SA, Tutt A, Sieuwerts AM, Borg A, Thomas G, Salomon AV, Richardson AL, Børresen-Dale AL, Futreal PA, Stratton MR, Campbell PJ; Breast Cancer Working Group of the International Cancer Genome Consortium. The Life History of 21 Breast Cancers. Cell 2012: doi 10.1016/j.cell.2012.04.023
- Shah SP, Roth A, Goya R, Oloumi A, Ha G, Zhao Y, Turashvili G, Ding J, Tse K, Haffari G, Bashashati A, Prentice L, Khattra J, Burleigh A, Yap D, Bernard V, McPherson A, Shumansky K, Crisan A, Giuliany R, Heravi-Moussavi A, Rosner J, Lai D, Birol I, Varhol R, Tam A, Dhalla N, Zeng T, Ma K, Chan S, Griffith M, Moradian A, Cheng G, Morin GB, Watson P, Gelmon K, Chia S, Chin SF, Curtis C, Rueda O, Pharoah PD, Damaraju S, Mackey J, Hoon K, Harkins T, Tadigotla V, Sigaroudinia M, Gascard P, Tlsty T, Costello JF, Meyer IM, Eaves CJ, Wasserman WW, Jones S, Huntsman D, Hirst M, Caldas C, Marra MA, Aparicio S. The clonal and mutational evolution spectrum of primary triple negative breast cancers. Nature 2012, doi:10.1038/nature10933
- Roth A, Morin R, Ding J, Crisan A, Ha G, Giuliany R, Bashashati A, Hirst M, Turashvili G, Oloumi A, Marra MA, Aparicio S, Shah SP. JointSNVMix : A Probabilistic Model For Accurate Detection Of Somatic Mutations In Normal/Tumour Paired Next Generation Sequencing Data. Bioinformatics 2012: 28(7):907-13
- Ding J, Bashashati A, Roth A, Oloumi A, Tse K, Zeng T, Haffari G, Hirst M, Marra MA, Condon A, Aparicio S, Shah SP. Feature-based classifiers for somatic mutation detection in tumour-normal paired sequencing data. Bioinformatics 2012: 28(2):167-75.
- McPherson A, Hormozdiari F, Zayed A, Giuliany R, Ha G, Sun MG, Griffith M, Heravi Moussavi A, Senz J, Melnyk N, Pacheco M, Marra MA, Hirst M, Nielsen TO, Sahinalp SC, Huntsman D, Shah SP. deFuse: An Algorithm for Gene Fusion Discovery in Tumor RNA-Seq Data.PLoS Comput Biol. 2011: 7(5):e1001138.
- McPherson A, Wu C, Hajirasouliha I, Hormozdiari F, Hach F, Lapuk A, Volik S, Shah S, Collins C, Sahinalp SC. Comrad: detection of expressed rearrangements by integrated analysis of RNA-Seq and low coverage genome sequence data. Bioinformatics 2011: 27(11):1481-8.
- Holland D, Burleigh A, Git A, Goldgraben MA, Perez-Mancera PA, Chin SF, Hurtado A, Bruna A, Ali R, Greenwood W, Dunning MJ, Samarajiwa S, Menon S, Rueda OM, Lynch AG, McKinney S, Ellis IO, Eaves CJ, Carroll JS, Curtis C, Aparicio S, Caldas C. ZNF703 is a common Luminal B breast cancer oncogene that differentially regulates luminal and basal progenitors in human mammary epithelium. EMBO Mol Med 2011 3:1–14
- Goya R, Sun MG, Morin RD, Leung G, Ha G, Wiegand KC, Senz J, Crisan A, Marra MA, Hirst M, Huntsman D, Murphy KP, Aparicio S, Shah SP. SNVMix: predicting single nucleotide variants from next generation sequencing of tumors. Bioinformatics 2010 26:730-6
- International Cancer Genome Consortium. International network of cancer genome projects. Nature 2010: 464:993-8.
- Shah SP, Morin RD, Khattra J, Prentice L, Pugh T, Burleigh A, Delaney A, Gelmon K, Guliany R, Senz J, Steidl C, Holt RA, Jones S, Sun M, Leung G, Moore R, Severson T, Taylor GA, Teschendorff AE, Tse K, Turashvili G, Varhol R, Warren RL, Watson P, Zhao Y, Caldas C, Huntsman D, Hirst M, Marra MA, Aparicio S. Mutational evolution in a lobular breast tumour profiled at single nucleotide resolution. Nature 2009: 461: 809-813