Expression profiling of archival tumors for long-term health studies

Levi Waldron, Shuji Ogino, Yujin Hoshida, Kaori Shima, Amy E McCart Reed, Peter T. Simpson, Yoshifumi Baba, Katsuhiko Nosho, Nicola Segata, Ana Cristina Vargas, Margaret C. Cummings, Sunil R. Lakhani, Gregory J. Kirkner, Edward Giovannucci, John Quackenbush, Todd R. Golub, Charles S. Fuchs, Giovanni Parmigiani, Curtis Huttenhower

Research output: Contribution to journalArticle

Abstract

Purpose: More than 20 million archival tissue samples are stored annually in the United States as formalin-fixed, paraffin-embedded (FFPE) blocks, but RNA degradation during fixation and storage has prevented their use for transcriptional profiling. New and highly sensitive assays for whole-transcriptome microarray analysis of FFPE tissues are now available, but resulting data include noise and variability for which previous expression array methods are inadequate. Experimental Design: We present the two largest whole-genome expression studies from FFPE tissues to date, comprising 1,003 colorectal cancer (CRC) and 168 breast cancer samples, combined with a metaanalysis of 14 new and published FFPE microarray datasets. We develop and validate quality control (QC) methods through technical replication, independent samples, comparison to results from fresh-frozen tissue, and recovery of expected associations between gene expression and protein abundance. Results: Archival tissues from large, multicenter studies showed a much wider range of transcriptional data quality relative to smaller or frozen tissue studies and required stringent QC for subsequent analysis. We developed novel methods for such QC of archival tissue expression profiles based on sample dynamic range and per-study median profile. This enabled validated identification of gene signatures of microsatellite instability and additional features of CRC, and improved recovery of associations between gene expression and protein abundance of MLH1, FASN, CDX2, MGMT, and SIRT1 in CRC tumors. Conclusions: These methods for large-scale QC of FFPE expression profiles enable study of the cancer transcriptome in relation to extensive clinicopathological information, tumor molecular biomarkers, and long-term lifestyle and outcome data.

Original languageEnglish (US)
Pages (from-to)6136-6146
Number of pages11
JournalClinical Cancer Research
Volume18
Issue number22
DOIs
StatePublished - Nov 15 2012
Externally publishedYes

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Paraffin
Formaldehyde
Health
Quality Control
Colorectal Neoplasms
Neoplasms
Breast Neoplasms
Gene Expression
Microsatellite Instability
RNA Stability
Gene Expression Profiling
Microarray Analysis
Tumor Biomarkers
Transcriptome
Multicenter Studies
Noise
Life Style
Proteins
Research Design
Genome

ASJC Scopus subject areas

  • Cancer Research
  • Oncology

Cite this

Waldron, L., Ogino, S., Hoshida, Y., Shima, K., Reed, A. E. M., Simpson, P. T., ... Huttenhower, C. (2012). Expression profiling of archival tumors for long-term health studies. Clinical Cancer Research, 18(22), 6136-6146. https://doi.org/10.1158/1078-0432.CCR-12-1915

Expression profiling of archival tumors for long-term health studies. / Waldron, Levi; Ogino, Shuji; Hoshida, Yujin; Shima, Kaori; Reed, Amy E McCart; Simpson, Peter T.; Baba, Yoshifumi; Nosho, Katsuhiko; Segata, Nicola; Vargas, Ana Cristina; Cummings, Margaret C.; Lakhani, Sunil R.; Kirkner, Gregory J.; Giovannucci, Edward; Quackenbush, John; Golub, Todd R.; Fuchs, Charles S.; Parmigiani, Giovanni; Huttenhower, Curtis.

In: Clinical Cancer Research, Vol. 18, No. 22, 15.11.2012, p. 6136-6146.

Research output: Contribution to journalArticle

Waldron, L, Ogino, S, Hoshida, Y, Shima, K, Reed, AEM, Simpson, PT, Baba, Y, Nosho, K, Segata, N, Vargas, AC, Cummings, MC, Lakhani, SR, Kirkner, GJ, Giovannucci, E, Quackenbush, J, Golub, TR, Fuchs, CS, Parmigiani, G & Huttenhower, C 2012, 'Expression profiling of archival tumors for long-term health studies', Clinical Cancer Research, vol. 18, no. 22, pp. 6136-6146. https://doi.org/10.1158/1078-0432.CCR-12-1915
Waldron L, Ogino S, Hoshida Y, Shima K, Reed AEM, Simpson PT et al. Expression profiling of archival tumors for long-term health studies. Clinical Cancer Research. 2012 Nov 15;18(22):6136-6146. https://doi.org/10.1158/1078-0432.CCR-12-1915
Waldron, Levi ; Ogino, Shuji ; Hoshida, Yujin ; Shima, Kaori ; Reed, Amy E McCart ; Simpson, Peter T. ; Baba, Yoshifumi ; Nosho, Katsuhiko ; Segata, Nicola ; Vargas, Ana Cristina ; Cummings, Margaret C. ; Lakhani, Sunil R. ; Kirkner, Gregory J. ; Giovannucci, Edward ; Quackenbush, John ; Golub, Todd R. ; Fuchs, Charles S. ; Parmigiani, Giovanni ; Huttenhower, Curtis. / Expression profiling of archival tumors for long-term health studies. In: Clinical Cancer Research. 2012 ; Vol. 18, No. 22. pp. 6136-6146.
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AU - Waldron, Levi

AU - Ogino, Shuji

AU - Hoshida, Yujin

AU - Shima, Kaori

AU - Reed, Amy E McCart

AU - Simpson, Peter T.

AU - Baba, Yoshifumi

AU - Nosho, Katsuhiko

AU - Segata, Nicola

AU - Vargas, Ana Cristina

AU - Cummings, Margaret C.

AU - Lakhani, Sunil R.

AU - Kirkner, Gregory J.

AU - Giovannucci, Edward

AU - Quackenbush, John

AU - Golub, Todd R.

AU - Fuchs, Charles S.

AU - Parmigiani, Giovanni

AU - Huttenhower, Curtis

PY - 2012/11/15

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N2 - Purpose: More than 20 million archival tissue samples are stored annually in the United States as formalin-fixed, paraffin-embedded (FFPE) blocks, but RNA degradation during fixation and storage has prevented their use for transcriptional profiling. New and highly sensitive assays for whole-transcriptome microarray analysis of FFPE tissues are now available, but resulting data include noise and variability for which previous expression array methods are inadequate. Experimental Design: We present the two largest whole-genome expression studies from FFPE tissues to date, comprising 1,003 colorectal cancer (CRC) and 168 breast cancer samples, combined with a metaanalysis of 14 new and published FFPE microarray datasets. We develop and validate quality control (QC) methods through technical replication, independent samples, comparison to results from fresh-frozen tissue, and recovery of expected associations between gene expression and protein abundance. Results: Archival tissues from large, multicenter studies showed a much wider range of transcriptional data quality relative to smaller or frozen tissue studies and required stringent QC for subsequent analysis. We developed novel methods for such QC of archival tissue expression profiles based on sample dynamic range and per-study median profile. This enabled validated identification of gene signatures of microsatellite instability and additional features of CRC, and improved recovery of associations between gene expression and protein abundance of MLH1, FASN, CDX2, MGMT, and SIRT1 in CRC tumors. Conclusions: These methods for large-scale QC of FFPE expression profiles enable study of the cancer transcriptome in relation to extensive clinicopathological information, tumor molecular biomarkers, and long-term lifestyle and outcome data.

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