The Goode laboratory combines bioinformatics, genomics, molecular evolution and population genetics to study the evolutionary forces governing the formation of tumours and their responses to therapy, with an emphasis on the roles of genomic instability and transcriptional plasticity as drivers of drug resistance in cancer. Our work centres mainly on prostate cancer and brain cancer, though our approaches are applicable to a range of solid tumours. Evolutionary genomics is the use of genome-scale analysis to investigate how natural selection has shaped genetic and phenotypic diversity between and within species. As cancer results from strong selection for particular cellular phenotypes, evolutionary genomics has great potential to unlock the secrets of this disease. We use evolutionary genomics to study all stages of tumour evolution, through in-depth analysis of large genome and RNA sequencing data sets from cancer patients and laboratory models of cancer, along with computational and statistical modelling. Our research involves assessing genetic, transcriptomic and phenotypic changes in individual tumours over time, as well as the impact impacts of mutation, selection and drift at the population and species level on the incidence and manifestation of cancer. We are particularly interested in the processes that generate genetic and transcriptional diversity within tumour and how these are shaped by external selective pressures.

Evolutionary genomics is the use of genome-scale analysis to investigate how natural selection has shaped genetic and phenotypic diversity between and within species. As cancer results from strong selection for particular cellular phenotypes, evolutionary genomics has great potential to unlock the secrets of this disease.

We use evolutionary genomics to study all stages of tumour evolution, through in-depth analysis of large genome and RNA sequencing data sets from cancer patients and laboratory models of cancer as well as computational and statistical modeling.

Our research involves assessing genetic, epigenetic and phenotypic changes in individual tumours over time, as well as the impact impacts of mutation, selection and drift at the population and species level on the incidence and manifestation of cancer. We’re particularly interested are the tradeoffs related to elevated genomic instability typical of tumours, which can be both advantageous and deleterious, depending on external and intracellular conditions.

Group Leader, Junior Faculty

Head of the Evolutionary Cancer Genomics group at Peter Mac

Research projects

Understanding common hallmarks of cancer through evolutionary network analysis

Tumour cells share many properties with single-celled organisms, suggesting the evolutionary age of a gene is related to its role in cancer. Our recent analysis of data from TCGA showed genes originating in unicellular or multicellular species exhibited different expression patterns (Trigos et al, PNAS, 2017). Furthermore, transcriptional networks formed during the emergence of multicellularity to control more primitive processes (e.g., cell replication, glycolysis) are frequently disrupted in cancer. We are now evaluating the biological and therapeutic implications of these signatures, particularly as they relate to the progression from low-grade glioma to glioblastoma (two types of brain cancer).

Evolution of castration-resistant prostate cancer

Many prostate tumours develop resistance to androgen blockade, a common first-line therapy for prostate cancer. Patients with castration-resistance prostate cancer (CRPC) have poor long-term survival prospects and few effective options for subsequent treatment. We combine genomics, clinical and experimental data to undercover how genetic instability and transcriptional plasticity drive emergence of CRPC. We have recently begun to apply single-cell genomics approaches to patient-derived xenograft models to explore intratumoral heterogeneity in CRPC in depth and uncover new therapeutic vulnerabilities that can be used to devise better treatments for CRPC.

Computational models of tumour evolution

Many of the factors influencing a tumour’s response to therapy are established very early on in its development, but such events are difficult to observe directly. My group has designed a sophisticated computational simulation models to reconstruct all stages of tumour evolution. One major goal is to investigate the role of genetic instability in tumour development and response to therapy, with the goal of testing and identifying novel drug dosing strategies. Model predictions are validated using genetic and clinical data from large patient cohorts

Spatial analysis of the tumour microenvironment

The growth of tumours is strongly influenced by the composition and activities of the cells in the microenvironment surrounding the tumour. Several emerging technologies are allowing scientists to conduct high-resolution spatial profiling the tumour microenvironment. We are developing analytical tools to annotate and analyse these important new data sets.

Identification of polygenic risk factors for heritable cancers

Cancer with a strong family history and/or early age of onset are driven by inherited genetic risk factors, yet most cases cannot be explained by known cancer risk genes. Iwe are investigating how the damaging effects of multiple genetic variants within the same person’s genome may combine to jointly risk cancer risk. These polygenic risk studies are being conducted in sarcoma and familial breast cancer cohorts, with Prof. Ian Campbell’s Cancer Genetics group at the Peter Mac and Prof. David Thomas at the Garvan Institute of Medical Research in Sydney, respectively.

People

Dr. Shivakumar Keerthikumar, Post-doctoral Fellow
Dr. Anna Trigos, Post-doctoral Fellow
Andrew Bakshi, PhD Student
Rosalia Quezada Urban, PhD Student
Alex Casar, PhD Student
Felicia Bongiovanni, Masters Student
Tarun Tikkoo, Masters Student
Will Walters, Masters Student
Jack Cooper, MDRP Student
Goode Lab

Key publications

Cipponi A, Goode DL, Bedo J, McCabe MJ, Pajic M, Croucher DR, Rajal AG, Junankar SR, Saunders DN, Lobachevsky P, Papenfuss AT, Nessem D, Nobis M, Warren SC, Timpson P, Cowley M, Vargas AC, Qiu MR, Generali DG, Keerthikumar S, Nguyen U, Corcoran NM, Long GV, Blay JY,Thomas DM. MTOR signalling orchestrates stress-induced mutagenesis, facilitating adaptive evolution in cancer. Science. 2020 Jun 5;368(6495):1127-1131. doi: 10.1126/science.aau8768.

Trigos AS, Pearson RB, Papenfuss AT, Goode DL. Somatic mutations in early metazoan genes disrupt regulatory links between unicellular and multicellular genes in cancer. Elife. 2019 Feb 26;8. pii: e40947. doi: 10.7554/eLife.40947.

Trigos AS, Pearson RB, Papenfuss AT, Goode DL. Altered interactions between unicellular and multicellular genes drive hallmarks of transformation in a diverse range of solid tumors. Proc Natl Acad Sci U S A. 2017 Jun 13;114(24):6406-6411. doi: 10.1073/pnas.1617743114.

Lawrence MG, Obinata D, Sandhu S, Selth LA, Wong SQ, Porter LH, Lister N, Pook D, Pezaro CJ, Goode DL, Rebello RJ, Clark AK, Papargiris M, Van Gramberg J, Hanson AR, Banks P, Wang H, Niranjan B, Keerthikumar S, Hedwards S, Huglo A, Yang R, Henzler C, Li Y, Lopez-Campos F, Castro E, Toivanen R, Azad A, Bolton D, Goad J, Grummet J, Harewood L, Kourambas J, Lawrentschuk N, Moon D, Murphy DG, Sengupta S, Snow R, Thorne H, Mitchell C, Pedersen J, Clouston D, Norden S, Ryan A, Dehm SM, Tilley WD, Pearson RB, Hannan RD, Frydenberg M, Furic L, Taylor RA, Risbridger GP. Patient-derived Models of Abiraterone- and Enzalutamide-resistant Prostate Cancer Reveal Sensitivity to Ribosome-directed Therapy. Eur Urol. 2018 Nov;74(5):562-572. doi: 10.1016/j.eururo.2018.06.020.

Bell CC, Fennell KA, Chan YC, Rambow F, Yeung MM, Vassiliadis D, Lara L, Yeh P, Martelotto LG, Rogiers A, Kremer BE, Barbash O, Mohammad HP, Johanson TM, Burr ML, Dhar A, Karpinich N, Tian L, Tyler DS, MacPherson L, Shi J, Pinnawala N, Yew Fong C, Papenfuss AT, Grimmond SM, Dawson SJ, Allan RS, Kruger RG, Vakoc CR, Goode DL, Naik SH, Gilan O, Lam EYN, Marine JC, Prinjha RK, Dawson MA. Targeting enhancer switching overcomes non-genetic drug resistance in acute myeloid leukaemia. Nat Commun. 2019 Jun 20;10(1):2723. doi: 10.1038/s41467-019-10652-9.

Trigos AS, Pearson RB, Papenfuss AT, Goode DL. How the evolution of multicellularity set the stage for cancer. Br J Cancer. 2018 Jan;118(2):145-152. doi: 10.1038/bjc.2017.398.

Li N, Rowley SM, Goode DL, Amarasinghe KC, McInerny S, Devereux L; LifePool Investigators, Wong-Brown MW, Lupat R, Lee JEA, Hughes S, Thompson ER, Zethoven M, Li J, Trainer AH, Gorringe KL, Scott RJ, James PA, Campbell IG. Mutations in RECQL are not associated with breast cancer risk in an Australian population. Nat Genet. 2018 Oct;50(10):1346-1348.

Ballinger ML, Goode DL, Ray-Coquard I, James PA, Mitchell G, Niedermayr E, Puri A, Schiffman JD, Dite GS, Cipponi A, Maki RG, Brohl AS, Myklebost O, Stratford EW, Lorenz S, Ahn SM, Ahn JH, Kim JE, Shanley S, Beshay V, Randall RL, Judson I, Seddon B, Campbell IG, Young MA, Sarin R, Blay JY, O'Donoghue SI, Thomas DM; International Sarcoma Kindred Study. Monogenic and polygenic determinants of sarcoma risk: an international genetic study. Lancet Oncol. 2016 Sep;17(9):1261-71. doi: 10.1016/S1470-2045(16)30147-4.

Research programs

Positions available

Students interested in potential Honours, Masters and PhD project should contact Dr. Goode directly.