Literature DB >> 29339835

Obtaining high quality transcriptome data from formalin-fixed, paraffin-embedded diagnostic prostate tumor specimens.

Chol-Hee Jung1, Ee Ming Wong2,3, Liesel M FitzGerald4,5, JiHoon E Joo2,3, Jodee A Gould6, Vivien Vasic6, Julie K Bassett4, Neil O'Callaghan2, Tim Nottle7, John Pedersen7, Graham G Giles4,8, Melissa C Southey9,10,11.   

Abstract

Prognostic genomic biomarkers that can be measured at diagnosis to aid choice of treatment options are unavailable for most common cancers. This is due in part to the poor quality and quantity of available diagnostic specimens for discovery research and to limitations in genomic technologies. Recent technical advances now enable high-density molecular analyses using suboptimal biological specimens. Here we describe the optimization of a transcriptome-specific protocol for use with formalin-fixed, paraffin-embedded (FFPE) diagnostic prostate cancer (PrCa) specimens. We applied the Ion AmpliSeq Transcriptome Human Gene Expression Kit (AmpliSeq Kit) to RNA samples extracted from 36 tumor-enriched and 16 adjacent normal tissues (ADJNT) from 37 FFPE PrCa specimens over a series of eight pilot studies, incorporating protocol modifications from Pilots 2 to 5. Data quality were measured by (1) the total number of mapped reads; (2) the percentage of reads that mapped to AmpliSeq target regions (OnTarget%); (3) the percentage of genes on the AmpliSeq panel with a read count ≥10 (TargetsDetected%); and (4) comparing the gene read-count distribution of the prostate tissue samples with the median gene read-count distribution of cell line-derived RNA samples. Modifications incorporated into Pilot study 5 provided gene expression data equivalent to cell line-derived RNA samples. These modifications included the use of freshly cut slides for macrodissection; increased tissue section thickness (8 µm); RNA extraction using the RecoverAll Total Nucleic Acid Isolation Kit for FFPE (ThermoFisher); 18 target amplification cycles; and processing six samples per Ion PI chip. This protocol will facilitate the discovery of prognostic biomarkers for cancer by allowing researchers to exploit previously underutilized diagnostic FFPE specimens.

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Year:  2018        PMID: 29339835     DOI: 10.1038/s41374-017-0001-8

Source DB:  PubMed          Journal:  Lab Invest        ISSN: 0023-6837            Impact factor:   5.662


  26 in total

Review 1.  Aberrant DNA methylation impacts gene expression and prognosis in breast cancer subtypes.

Authors:  Balázs Győrffy; Giulia Bottai; Thomas Fleischer; Gyöngyi Munkácsy; Jan Budczies; Laura Paladini; Anne-Lise Børresen-Dale; Vessela N Kristensen; Libero Santarpia
Journal:  Int J Cancer       Date:  2015-07-30       Impact factor: 7.396

Review 2.  Ki67, PCNA, and MCM proteins: Markers of proliferation in the diagnosis of breast cancer.

Authors:  Miroslava Juríková; Ľudovít Danihel; Štefan Polák; Ivan Varga
Journal:  Acta Histochem       Date:  2016-05-28       Impact factor: 2.479

3.  mRNA expression signature of Gleason grade predicts lethal prostate cancer.

Authors:  Kathryn L Penney; Jennifer A Sinnott; Katja Fall; Yudi Pawitan; Yujin Hoshida; Peter Kraft; Jennifer R Stark; Michelangelo Fiorentino; Sven Perner; Stephen Finn; Stefano Calza; Richard Flavin; Matthew L Freedman; Sunita Setlur; Howard D Sesso; Swen-Olof Andersson; Neil Martin; Philip W Kantoff; Jan-Erik Johansson; Hans-Olov Adami; Mark A Rubin; Massimo Loda; Todd R Golub; Ove Andrén; Meir J Stampfer; Lorelei A Mucci
Journal:  J Clin Oncol       Date:  2011-05-02       Impact factor: 44.544

4.  Prognostic Utility of a New mRNA Expression Signature of Gleason Score.

Authors:  Jennifer A Sinnott; Sam F Peisch; Svitlana Tyekucheva; Travis Gerke; Rosina Lis; Jennifer R Rider; Michelangelo Fiorentino; Meir J Stampfer; Lorelei A Mucci; Massimo Loda; Kathryn L Penney
Journal:  Clin Cancer Res       Date:  2016-09-23       Impact factor: 12.531

5.  Prospective multicentre evaluation of PCA3 and TMPRSS2-ERG gene fusions as diagnostic and prognostic urinary biomarkers for prostate cancer.

Authors:  Gisele H J M Leyten; Daphne Hessels; Sander A Jannink; Frank P Smit; Hans de Jong; Erik B Cornel; Theo M de Reijke; Henk Vergunst; Paul Kil; Ben C Knipscheer; Inge M van Oort; Peter F A Mulders; Christina A Hulsbergen-van de Kaa; Jack A Schalken
Journal:  Eur Urol       Date:  2012-11-15       Impact factor: 20.096

6.  Validation of a cell-cycle progression gene panel to improve risk stratification in a contemporary prostatectomy cohort.

Authors:  Matthew R Cooperberg; Jeffry P Simko; Janet E Cowan; Julia E Reid; Azita Djalilvand; Satish Bhatnagar; Alexander Gutin; Jerry S Lanchbury; Gregory P Swanson; Steven Stone; Peter R Carroll
Journal:  J Clin Oncol       Date:  2013-03-04       Impact factor: 44.544

7.  Large-scale evaluation of SLC18A2 in prostate cancer reveals diagnostic and prognostic biomarker potential at three molecular levels.

Authors:  Christa Haldrup; Anne-Sofie Lynnerup; Tine Maj Storebjerg; Søren Vang; Peter Wild; Tapio Visakorpi; Christian Arsov; Wolfgang A Schulz; Johan Lindberg; Henrik Grönberg; Lars Egevad; Michael Borre; Torben Falck Ørntoft; Søren Høyer; Karina Dalsgaard Sørensen
Journal:  Mol Oncol       Date:  2016-02-09       Impact factor: 7.449

8.  Prognostic value of a cell cycle progression signature for prostate cancer death in a conservatively managed needle biopsy cohort.

Authors:  J Cuzick; D M Berney; G Fisher; D Mesher; H Møller; J E Reid; M Perry; J Park; A Younus; A Gutin; C S Foster; P Scardino; J S Lanchbury; S Stone
Journal:  Br J Cancer       Date:  2012-02-23       Impact factor: 7.640

Review 9.  Prostate cancer biomarkers: Are we hitting the mark?

Authors:  Shannon McGrath; Daniel Christidis; Marlon Perera; Sung Kyu Hong; Todd Manning; Ian Vela; Nathan Lawrentschuk
Journal:  Prostate Int       Date:  2016-07-29

10.  Testing breast cancer serum biomarkers for early detection and prognosis in pre-diagnosis samples.

Authors:  Anna Kazarian; Oleg Blyuss; Gergana Metodieva; Aleksandra Gentry-Maharaj; Andy Ryan; Elena M Kiseleva; Olga M Prytomanova; Ian J Jacobs; Martin Widschwendter; Usha Menon; John F Timms
Journal:  Br J Cancer       Date:  2017-01-12       Impact factor: 7.640

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  5 in total

1.  Optimization of RNA extraction from laser captured microdissected glomeruli from formalin-fixed paraffin-embedded mouse kidney samples for Nanostring analysis.

Authors:  Abigail Hay; Jean-Martin Lapointe; Arthur Lewis; Carol Moreno Quinn; Elena Miranda
Journal:  Histol Histopathol       Date:  2019-06-11       Impact factor: 2.303

2.  A comparative analysis of RNA sequencing methods with ribosome RNA depletion for degraded and low-input total RNA from formalin-fixed and paraffin-embedded samples.

Authors:  Xiaojing Lin; Lihong Qiu; Xue Song; Junyan Hou; Weizhi Chen; Jun Zhao
Journal:  BMC Genomics       Date:  2019-11-08       Impact factor: 3.969

3.  The insertion and dysregulation of transposable elements in osteosarcoma and their association with patient event-free survival.

Authors:  Chao Wang; Chun Liang
Journal:  Sci Rep       Date:  2022-01-10       Impact factor: 4.996

4.  Non-invasive human skin transcriptome analysis using mRNA in skin surface lipids.

Authors:  Takayoshi Inoue; Tetsuya Kuwano; Yuya Uehara; Michiko Yano; Naoki Oya; Naoto Takada; Shodai Tanaka; Yui Ueda; Akira Hachiya; Yoshito Takahashi; Noriyasu Ota; Takatoshi Murase
Journal:  Commun Biol       Date:  2022-03-09

5.  Fecal Host Transcriptomics for Non-Invasive Human Mucosal Immune Profiling: Proof of Concept in Clostridium Difficile Infection.

Authors:  Bert K Lopansri; Daniel T Leung; Robert Schlaberg; Amanda Barrett; Kornelia Edes; Michael Graves; Litty Paul; Jenna Rychert
Journal:  Pathog Immun       Date:  2018-09-12
  5 in total

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