Christopher Maher, PhD

Associate Professor
Internal Medicine
Medical Oncology

Cancer Biology Program
Computational and Systems Biology Program
Molecular Genetics and Genomics Program
Human and Statistical Genetics Program

  • 314-286-2856

  • 740 Southwest Tower



  • non-coding RNAs, lncRNAs, cancer genomics, transcriptome, bioinformatics, computational biology, solid tumor malignancies

  • Translational Cancer Genomics; Noncoding RNAs

Research Abstract:

Our lab is currently integrating genomics, bioinformatics, and molecular biology approaches to characterize RNA species, elucidate their function, and assessing their clinical applicability.

1. Understanding the role of long non-coding RNAs in lung cancer
In our recently published study in Genome Biology (PMID:25116943) we leveraged three large publicly available data collections comprising ~550 lung cancer patients that enable us to detect 111 lung cancer associated lncRNAs, which we refer to as LCALs. We experimentally validated a subset of LCALs in cell lines and an independent tissue cohort as well as confirming their full-length transcripts. A meta-analysis across human cancers revealed that most LCALs that have lung cancer specific expression and therefore may represent putative biomarkers. However, a few LCALs are altered in multiple solid tumors suggesting they may have a common oncogenic role. Furthermore, we have found that the expression of multiple LCALs is associated with poor overall survival in a cohort of 409 stage I/II lung cancer patients suggesting their clinical potential. Lastly, to demonstrate that LCALs may contribute to lung tumorigenesis we silenced and over expressed the most commonly up-regulated lncRNA across lung subtypes, LCAL1, highlighting its role in regulating cellular proliferation. Overall, transcriptomic analysis highlights the lncRNA landscape that may contribute to lung cancer and lays the framework for future studies exploring their mechanism in lung tumorigenesis and potential use as biomarkers. Our lab is currently addressing the challenge of understanding how lncRNAs function using high-throughput assays (i.e., RIP-Seq) within subsets of lung cancer patients with the intent of identifying novel therapeutic strategies.

2. Understanding the biological and clinical significant of Prostate Cancer Associated Transcripts (PCATs)
Each year, over 180,000 men are diagnosed with prostate cancer in the United States, and over 29,000 will die from this disease. To date prostate cancer research has primarily focused on the deregulation of protein-coding genes to identify oncogenes and tumor suppressors as potential diagnostic and therapeutic targets. We leveraged the unbiased approach of transcriptome sequencing to identify over 1,800 unannotated lncRNAs, with 121 found to be involved in prostate tumorigenesis, referred to as prostate cancer associated transcripts (PCATs). Although originally regarded as transcriptional noise, several well-described examples indicate that lncRNAs may be master regulators in cancer biology, typically facilitating epigenetic gene repression through chromatin-modifying complexes. However, of the thousands of lncRNAs discovered to date, only a few have been functionally characterized in human cancers. Interestingly, PCAT-1 was found to have mutually exclusive expression with EZH2, a core PRC2 protein and prostate cancer biomarker. Subsequent in vitro and in vivo studies demonstrated that PCAT-1 regulates cellular proliferation through an unknown mechanism. Through RNA immunoprecipitation we found that PCAT-1 associates with PRC2, which in turn can bind to the PCAT-1 promoter. Taken together, these results suggest that PCAT-1 biology may exhibit two distinct modalities: one in which PRC2 represses PCAT-1 and a second in which active PCAT-1 promotes cell proliferation. Building upon this, our lab is currently focusing on understanding how additional PCATs promote to prostate cancer and placing them in clinical context (as part of the projects described in the `Prostate Cancer Genomics` section).

3. Understanding the contribution of long non-coding RNAs to metastasis
As part of a Team Science Award we are exploring the differences in the genome, transcriptome, and epigenome between primary and metastatic colorectal cancer with the intent of revealing novel pathways critical for tumor metastases, identify potential diagnostic/prognostic markers, and unmask new targets for therapeutic intervention. Interestingly, a gene set enrichment analysis of the differentially expressed protein-coding genes from our patient cohort revealed an enrichment of Polycomb Repressive Complex 2 (PRC2) target genes during the progression of mCRC. Consistent with earlier reports, our subsequent preliminary studies demonstrate that ~20% of the known lncRNAs associate with the PRC2, which represses the transcription of pro-differentiation and anti-proliferative genes leading to poorly differentiated and aggressive human tumors. Therefore, we are optimizing novel techniques to systematically identify how lncRNAs interact with PRC2 to modulate chromatin states.

4. Role of lncRNAs in aromatase inhibitor resistance
Estrogen-receptor-positive breast cancer exhibits highly variable prognoses, histological growth patterns and treatment outcomes. The observation that estrogen receptor positive breast cancer growth is stimulated by estrogen led to clinical trials utilizing anti-estrogen therapies prior to surgery. To date multiple clinical trials have focused on aromatase inhibitors, a form of anti-estrogen therapy that blocks the enzyme aromatase from synthesizing estrogen. Despite the successes of using neoadjuvant hormone therapy, only a subset of patients will respond to treatment. Therefore, our lab is focusing on understanding the role of lncRNAs in therapy sensitivity.

Selected Publications:

For full list of publications:

Quigley DA, Dang HX, Zhao SG, Lloyd P, Aggarwal R, Alumkal JJ, Foye A, Kothari V, Perry MD, Bailey AM, Playdle D, Barnard TJ, Zhang L, Zhang J, Youngren JF, Cieslik MP, Parolia A, Beer TM, Thomas G, Chi KN, Gleave M, Lack NA, Zoubeidi A, Reiter RE, Rettig MB, Witte O, Ryan CJ, Fong L, Kim W, Friedlander T, Chou J, Li H, Das R, Li H, Moussavi-Baygi R, Goodarzi H, Gilbert LA, Lara PN Jr, Evans CP, Goldstein TC, Stuart JM, Tomlins SA, Spratt DE, Cheetham RK, Cheng DT, Farh K, Gehring JS, Hakenberg J, Liao A, Febbo PG, Shon J, Sickler B, Batzoglou S, Knudsen KE, He HH, Huang J, Wyatt AW, Dehm SM, Ashworth A, Chinnaiyan AM*, Maher CA*, Small EJ*, Feng FY*. Genomic Hallmarks and Structural Variation in Metastatic Prostate Cancer. Cell. 2018 Jul 26;174(3):758-769.e9. doi: 10.1016/j.cell.2018.06.039. Epub 2018 Jul 19. PubMed PMID: 30033370. (* co-senior authors).

Zhang J, Gao T, Maher CA. INTEGRATE-Vis: a tool for comprehensive gene fusion visualization. Sci Rep. 2017 Dec 19;7(1):17808. doi: 10.1038/s41598-017-18257-2. PubMed PMID: 29259323; PubMed Central PMCID: PMC5736641.

Dang HX, White BS, Foltz SM, Miller CA, Luo J, Fields RC, Maher CA. ClonEvol: clonal ordering and visualization in cancer sequencing. Ann Oncol. 2017 Sep 11. doi: 10.1093/annonc/mdx517. [Epub ahead of print] PubMed PMID: 28950321.

Zhang J, Mardis ER, Maher CA. INTEGRATE-neo: a pipeline for personalized gene fusion neoantigen discovery. Bioinformatics. 2017 Feb 15;33(4):555-557. doi: 10.1093/bioinformatics/btw674. PubMed PMID: 27797777; PubMed Central PMCID: PMC5408800.

White NM, Zhao SG, Zhang J, Rozycki EB, Dang HX, McFadden SD, Eteleeb AM, Alshalalfa M, Vergara IA, Erho N, Arbeit JM, Karnes RJ, Den RB, Davicioni E, Maher CA. Multi-institutional Analysis Shows that Low PCAT-14 Expression Associates with Poor Outcomes in Prostate Cancer. Eur Urol. 2017 Feb;71(2):257-266. doi: 10.1016/j.eururo.2016.07.012. Epub 2016 Jul 22. PubMed PMID: 27460352.

Zhang J, White NM, Schmidt HK, Fulton RS, Tomlinson C, Warren WC, Wilson RK, Maher CA. INTEGRATE: gene fusion discovery using whole genome and transcriptome data. Genome Res. 2016 Jan;26(1):108-18. doi: 10.1101/gr.186114.114. Epub 2015 Nov 10. PubMed PMID: 26556708; PubMed Central PMCID: PMC4691743.

Dang HX, Maher CA. Clonotyping for precision oncology. Drug Discov Today. 2015 Dec;20(12):1464-9. doi: 10.1016/j.drudis.2015.10.010. Epub 2015 Oct 19. Review. PubMed PMID: 26494143.

Cabanski CR, White NM, Dang HX, Silva-Fisher JM, Rauck CE, Cicka D, Maher CA. Pan-cancer transcriptome analysis reveals long noncoding RNAs with conserved function. RNA Biol. 2015;12(6):628-42. doi: 10.1080/15476286.2015.1038012. PubMed PMID: 25864709; PubMed Central PMCID: PMC4615893.

White NM, Cabanski CR, Silva-Fisher JM, Dang HX, Govindan R, Maher CA. Transcriptome sequencing reveals altered long intergenic non-coding RNAs in lung cancer. Genome Biol. 2014 Aug 13;15(8):429. doi: 10.1186/s13059-014-0429-8. PubMed PMID: 25116943; PubMed Central PMCID: PMC4156652.

Cabanski CR, Magrini V, Griffith M, Griffith OL, McGrath S, Zhang J, Walker J, Ly A, Demeter R, Fulton RS, Pong WW, Gutmann DH, Govindan R, Mardis ER, Maher CA. cDNA hybrid capture improves transcriptome analysis on low-input and archived samples. J Mol Diagn. 2014 Jul;16(4):440-51. doi: 10.1016/j.jmoldx.2014.03.004. Epub 2014 May 9. PubMed PMID: 24814956; PubMed Central PMCID: PMC4078367.

Natrajan R, Wilkerson PM, Marchi C, Piscuoglio S, Ng CK, Wai P, Lambros MB, Samartzis EP, Dedes KJ, Frankum J, Bajrami I, Kopec A, Mackay A, A`hern R, Fenwick K, Kozarewa I, Hakas J, Mitsopoulos C, Hardisson D, Lord CJ, Kumar-Sinha C, Ashworth A, Weigelt B, Sapino A, Chinnaiyan AM, Maher CA, Reis-Filho JS. Characterization of the genomic features and expressed fusion genes in micropapillary carcinomas of the breast. J Pathol. 2014 Apr;232(5):553-65. doi:
10.1002/path.4325. Epub 2014 Feb 5. PubMed PMID: 24395524; PubMed Central PMCID: PMC4013428.

White NM, Feng FY, Maher CA. Recurrent rearrangements in prostate cancer: causes and therapeutic potential. Curr Drug Targets. 2013 Apr;14(4):450-9. Review. PubMed PMID: 23410129; PubMed Central PMCID:PMC3733264.

Maher CA, Wilson RK. Chromothripsis and human disease: piecing together the shattering process. Cell. 2012 Jan 20;148(1-2):29-32. doi:10.1016/j.cell.2012.01.006. Review. PubMed PMID: 22265399; PubMed Central PMCID:

Iyer MK, Chinnaiyan AM, Maher CA. ChimeraScan: A tool for identifying chimeric transcription in sequencing data. Bioinformatics. 2011 Oct 15;27(20):2903-4. Epub 2011 Aug 11.

Prensner J, Iyer MK, Balbin OA, Dhanasekaran M, Iyer HK, Brenner JC, Grasso C, Cao Q, Kominsky H, Cao X, Siddiqui J, Wei JT, Palanisamy N, Robinson D, Maher CA, and Chinnaiyan AM. Transcriptome Sequencing Reveals Non-coding RNAs Associated with Prostate Cancer Progression. Nature Biotechnology 2011 Jul 31;29(8):742-9.

Sam LT, Lipson D, Raz, T, Cao X, Thompson J, Milos PM, Robinson D, Chinnaiyan AM, Kumar-Sinha C, Maher CA. A comparison of single molecule and amplification based sequencing of cancer transcriptomes. PLoS ONE 2011 6(3): e17305.

Palanisamy N, Ateeq B, Kalyana-Sundaram S, Pflueger D, Ramnarayanan K, Shankar S, Han B, Cao Q, Cao X, Suleman K, Kumar-Sinha C, Dhanasekaran SM, Chen Y, Esgueva R, Banerjee S, LaFargue CJ, Demichelis F, Moeller P, Bismar TA, Kuefer R, Tomlins SA, Varambally S, Rubin MA, Maher CA and Chinnaiyan AM. Rearrangements of the RAF Kinase Pathway in Prostate Cancer. Nature Medicine 2010 16(7):793-8.

Maher CA, Palanisamy N, Brenner JC, Cao X, Kalyana-Sundaram S, Luo S, Khrebtukova I, Barrette T, Quist C, Yu J, Lonigro R, Schroth G, Kumar-Sinha C and Chinnaiyan A. Chimera transcript discovery using paired-end transcriptome sequencing. Proceedings of the National Academy of Sciences 2009106(30):12353-8.

Maher CA, Kumar-Sinha C, Cao X, Kalyana-Sundaram S, Han B, Jing X, Sam L, Barrette T, Palanisamy N, Chinnaiyan AM. Transcriptome sequencing to detect gene
fusions in cancer. Nature. 2009 Mar5;458(7234):97-101. doi: 10.1038/nature07638. Epub 2009 Jan 11. PubMed PMID: 19136943; PubMed Central PMCID: PMC2725402.

Last Updated: 10/11/2021 1:30:58 PM

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