The Laboratory for Advanced Genome Analysis (LAGA) occupies 3,600 square feet of laboratories and offices and houses state-of-the-art equipment. LAGA specializes in the acquisition, processing, statistical analysis, integration, and visualization of next-generation sequencing (NGS) and microarray data to enable and advance basic and translational research.
LAGA offers economically priced services based on a cost-recovery, not-for-profit model. The facility provides researchers with the highest quality results; manages research projects from experimental design to interpretation of data; and supports the researchers’ grant applications and publications.
Click here for a poster presentation (2020) describing specific examples of LAGA research expertise (3.4 MB PDF; opens in new window).
From 2011 to 2017, LAGA has produced >20 peer-reviewed publications on the characterization of the neuroendocrine phenotype in prostate cancer (1-3), cancer heterogeneity (4), characterization patient-derived xenografts for better in vitro models (5-7), integrative analysis of genomic and transcriptomic data for the discovery of patient’s prostate cancer (8), development of new methods for the detection of structural variants (9), ultra-sensitive detection of single nucleotide variants and indels in circulating tumour DNA (10), RNA editing (11), detection of fusions (12) and alternative splicing (13,14), analysis of clonality (15,16), pathway and subnetwork (17), identification of clinical variants (18-20), identification of a gene expression signature (21) and drivers for therapeutic targeting (17,22).
- From sequence to molecular pathology, and a mechanism driving the neuroendocrine phenotype in prostate cancer. Lapuk AV et al. (2012). J Pathol. 227(3):286-97. PMID: 22553170.
- Identification of DEK as a potential therapeutic target for neuroendocrine prostate cancer. Lin D et al. (2015) Oncotarget. Jan 30;6(3):1806-20. PMID: 25544761.
- The Placental Gene PEG10 Promotes Progression of Neuroendocrine Prostate. Akamatsu S et al. (2015) Cancer. Cell Report. 2015 Aug 11;12(6):922-36. PMID: 26235627.
- The inter-tumor transcriptome heterogeneity of high-risk primary prostate cancer Wyatt A et al (2014). Genome Biology 2014 Aug 26;15(8):426. PMID: 25155515.
- Lessons from patient-derived xenografts for better in vitro modeling of human cancer. Choi SY et al. (2014) Adv Drug Deliv Rev. Dec 15;79-80:222-37. PMID: 2530533
- Next generation patient-derived prostate cancer xenograft models. Lin D et al. (2014) Asian J Androl. May-Jun;16(3):407-12. PMID: 24589467
- High fidelity patient-derived xenografts for accelerating prostate cancer discovery and drug development. Lin D et al. (2014) Cancer Res. Feb 15;74(4):1272-83. PMID: 24356420
- Integrated genome and transcriptome sequencing identifies a novel form of hybrid and aggressive prostate cancer. Wu C, Wyatt AW et al. (2012). J Pathol. 2012 May;227(1):53-61. PMID: 22294438
- Nfuse: Discovery of complex genomic rearrangements in cancer using high-throughput sequencing. McPherson A et al. (2012). Genome Research. 22: 2250-2261. PMID: 22745232
- SiNVICT: Ultra-Sensitive Detection of Single Nucleotide Variants and Indels in Circulating Tumour DNA. Can Kockan et al. (2017) Bioinformatics Jan 1;33(1):26-34. PMID: 27531099
- Systematic identification and characterization of RNA editing in prostate tumors. Mo F. et al. (2014). PLoS One. Jul 18;9(7):e101431. PMID: 25036877
- Poly-gene fusion transcripts and chromothripsis in prostate cancer. Wu C et al. (2012) Genes Chromosomes Cancer. Dec;51(12):1144-53. PMID: 22927308.
- ORMAN: optimal resolution of ambiguous RNA-Seq multimappings in the presence of novel isoforms. Dao P et al. (2014) Bioinformatics. Mar 1;30(5):644-51. PMID: 24130305.
- The role of mRNA splicing in prostate cancer. Lapuk AV et al., (2014) Asian Journal of Andrology. 2014 July-Aug; 16(4):515-21. PMID: 24830689.
- Clonality inference in multiple tumor samples using phylogeny. Malikic S et al. (2015) Bioinformatics. May 1;31(9):1349-56. PMID: 25568283.
- Clonality Inference from Single Tumor Samples Using Low-Coverage Sequence Data. Donmez Net al. (2017) J Comput Biol. Jun;24(6):515-523. PMID: 28056180
- HIT'nDRIVE: patient-specific multi-driver gene prioritization for precision oncology. Shrestha R et al. (2017) Genome Res. Sep;27(9):1573-1588. PMID: 28768687
- Next generation sequencing of prostate cancer from a patient identifies a deficiency of methylthioadenosine phosphorylase, an exploitable tumor target. Collins CC et al. (2012): Mol Cancer Ther 11(3): 775-83. PMID: 22252602
- Androgen receptor gene aberrations in circulating cell-free DNA: biomarkers of therapeutic resistance and response in castration-resistant prostate cancer. Azad AA et al., (2015). Clinical Cancer Research. 21:2315-24. PMID: 25712683
- Genomic alterations in cell-free DNA and enzalutamide resistance in castration-resistant prostate cancer. Wyatt AW et al., (2016) JAMA Oncol. Dec 1;2(12):1598-1606. PMID: 27148695
- Stromal Gene Expression is Predictive for Metastatic Primary Prostate Cancer. Mo F. Eur Urol. 2017 Mar 19. doi: 10.1016/j.eururo.2017.02.038. [Epub ahead of print] PMID: 28330676
- A meta-analysis approach for characterizing pan-cancer mechanisms of drug sensitivity in cell lines. Wang K et al (2014). PLosOne 2014 july 18;9(7):e103050. PMID: 25036042.
Last updated: September 17, 2020