Development and Validation of a Gene Signature Classifier for Consensus Molecular Subtyping of Colorectal Carcinoma in a CLIA-Certified Setting

Jeffrey S Morris; Rajyalakshmi Luthra; Yusha Liu; Dzifa Y Duose; Wonyul Lee; Neelima G Reddy; Justin Windham; Huiqin Chen; Zhimin Tong; Baili Zhang; Wei Wei; Manyam Ganiraju; Bradley M Broom; Hector A Alvarez; Alicia Mejia; Omkara Veeranki; Mark J Routbort; Van K Morris; Michael J Overman; David Menter; Riham Katkhuda; Ignacio I Wistuba; Jennifer S Davis; Scott Kopetz; Dipen M Maru

doi:10.1158/1078-0432.CCR-20-2403

Development and Validation of a Gene Signature Classifier for Consensus Molecular Subtyping of Colorectal Carcinoma in a CLIA-Certified Setting

Jeffrey S Morris, Rajyalakshmi Luthra, Yusha Liu, Dzifa Y Duose, Wonyul Lee, Neelima G Reddy, Justin Windham, Huiqin Chen, Zhimin Tong, Baili Zhang, Wei Wei, Manyam Ganiraju, Bradley M Broom, Hector A Alvarez, Alicia Mejia, Omkara Veeranki, Mark J Routbort, Van K Morris, Michael J Overman, David MenterRiham Katkhuda, Ignacio I Wistuba, Jennifer S Davis, Scott Kopetz, Dipen M Maru

Research output: Contribution to journal › Article › peer-review

18 Scopus citations

Abstract

PURPOSE: Consensus molecular subtyping (CMS) of colorectal cancer (CRC) has potential to reshape the CRC landscape. We developed and validated an assay that is applicable on formalin fixed paraffin embedded (FFPE) samples of CRC and implemented the assay in a CLIA-certified laboratory.

EXPERIMENTAL DESIGN: We performed an in silico experiment to build an optimal CMS classifier using a training set of 1329 samples from 12 studies and validation set of 1329 samples from 14 studies. We constructed assay based on Nanostring codesets for the top 472 genes, and performed analyses on paired flash frozen (FF)/FFPE samples from 175 CRCs to adapt the classifier to FFPE using a subset of genes found to be concordant between FF and FFPE, and tested the classifier`s reproducibility, repeatability, and validated in a CLIA-certified laboratory. We assessed prognostic significance of CMS in 345 patients pooled across 3 clinical trials.

RESULTS: The best classifier was Weighted Support Vector Machine with high accuracy across platforms and gene lists (>0.95), and the 472-gene model outperforming existing classifiers. We constructed subsets of 99 and 200 genes with high FF/FFPE concordance, and adapted FFPE-based classifier that had strong classification accuracy (>80%) relative to "gold standard" CMS. The classifier was reproducible to sample type, RNA quality, and demonstrated poor prognosis for CMS1-3 and good prognosis for CMS2 in metastatic CRC (p<0.001).

CONCLUSIONS: We developed and validated a CRC CMS assay that is ready for use in clinical trials, to assess prognosis in standard-of-care settings and explore as predictor of therapy response.

Original language	English (US)
Journal	Clinical cancer research : an official journal of the American Association for Cancer Research
DOIs	https://doi.org/10.1158/1078-0432.CCR-20-2403
State	E-pub ahead of print - Oct 27 2020

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10.1158/1078-0432.CCR-20-2403

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Morris, J. S., Luthra, R., Liu, Y., Duose, D. Y., Lee, W., Reddy, N. G., Windham, J., Chen, H., Tong, Z., Zhang, B., Wei, W., Ganiraju, M., Broom, B. M., Alvarez, H. A., Mejia, A., Veeranki, O., Routbort, M. J., Morris, V. K., Overman, M. J., ... Maru, D. M. (2020). Development and Validation of a Gene Signature Classifier for Consensus Molecular Subtyping of Colorectal Carcinoma in a CLIA-Certified Setting. Clinical cancer research : an official journal of the American Association for Cancer Research. Advance online publication. https://doi.org/10.1158/1078-0432.CCR-20-2403

Development and Validation of a Gene Signature Classifier for Consensus Molecular Subtyping of Colorectal Carcinoma in a CLIA-Certified Setting. / Morris, Jeffrey S; Luthra, Rajyalakshmi; Liu, Yusha et al.
In: Clinical cancer research : an official journal of the American Association for Cancer Research, 27.10.2020.

Research output: Contribution to journal › Article › peer-review

Morris, JS, Luthra, R, Liu, Y, Duose, DY, Lee, W, Reddy, NG, Windham, J, Chen, H , Tong, Z, Zhang, B, Wei, W, Ganiraju, M, Broom, BM, Alvarez, HA, Mejia, A, Veeranki, O, Routbort, MJ , Morris, VK , Overman, MJ , Menter, D, Katkhuda, R, Wistuba, II, Davis, JS, Kopetz, S & Maru, DM 2020, 'Development and Validation of a Gene Signature Classifier for Consensus Molecular Subtyping of Colorectal Carcinoma in a CLIA-Certified Setting', Clinical cancer research : an official journal of the American Association for Cancer Research. https://doi.org/10.1158/1078-0432.CCR-20-2403

@article{367fef8b6c3a4c8f8a0af5aa598f1486,

title = "Development and Validation of a Gene Signature Classifier for Consensus Molecular Subtyping of Colorectal Carcinoma in a CLIA-Certified Setting",

abstract = "PURPOSE: Consensus molecular subtyping (CMS) of colorectal cancer (CRC) has potential to reshape the CRC landscape. We developed and validated an assay that is applicable on formalin fixed paraffin embedded (FFPE) samples of CRC and implemented the assay in a CLIA-certified laboratory.EXPERIMENTAL DESIGN: We performed an in silico experiment to build an optimal CMS classifier using a training set of 1329 samples from 12 studies and validation set of 1329 samples from 14 studies. We constructed assay based on Nanostring codesets for the top 472 genes, and performed analyses on paired flash frozen (FF)/FFPE samples from 175 CRCs to adapt the classifier to FFPE using a subset of genes found to be concordant between FF and FFPE, and tested the classifier`s reproducibility, repeatability, and validated in a CLIA-certified laboratory. We assessed prognostic significance of CMS in 345 patients pooled across 3 clinical trials.RESULTS: The best classifier was Weighted Support Vector Machine with high accuracy across platforms and gene lists (>0.95), and the 472-gene model outperforming existing classifiers. We constructed subsets of 99 and 200 genes with high FF/FFPE concordance, and adapted FFPE-based classifier that had strong classification accuracy (>80%) relative to {"}gold standard{"} CMS. The classifier was reproducible to sample type, RNA quality, and demonstrated poor prognosis for CMS1-3 and good prognosis for CMS2 in metastatic CRC (p<0.001).CONCLUSIONS: We developed and validated a CRC CMS assay that is ready for use in clinical trials, to assess prognosis in standard-of-care settings and explore as predictor of therapy response.",

author = "Morris, {Jeffrey S} and Rajyalakshmi Luthra and Yusha Liu and Duose, {Dzifa Y} and Wonyul Lee and Reddy, {Neelima G} and Justin Windham and Huiqin Chen and Zhimin Tong and Baili Zhang and Wei Wei and Manyam Ganiraju and Broom, {Bradley M} and Alvarez, {Hector A} and Alicia Mejia and Omkara Veeranki and Routbort, {Mark J} and Morris, {Van K} and Overman, {Michael J} and David Menter and Riham Katkhuda and Wistuba, {Ignacio I} and Davis, {Jennifer S} and Scott Kopetz and Maru, {Dipen M}",

year = "2020",

month = oct,

day = "27",

doi = "10.1158/1078-0432.CCR-20-2403",

language = "English (US)",

journal = "Clinical cancer research : an official journal of the American Association for Cancer Research",

issn = "1078-0432",

publisher = "American Association for Cancer Research Inc.",

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TY - JOUR

T1 - Development and Validation of a Gene Signature Classifier for Consensus Molecular Subtyping of Colorectal Carcinoma in a CLIA-Certified Setting

AU - Morris, Jeffrey S

AU - Luthra, Rajyalakshmi

AU - Liu, Yusha

AU - Duose, Dzifa Y

AU - Lee, Wonyul

AU - Reddy, Neelima G

AU - Windham, Justin

AU - Chen, Huiqin

AU - Tong, Zhimin

AU - Zhang, Baili

AU - Wei, Wei

AU - Ganiraju, Manyam

AU - Broom, Bradley M

AU - Alvarez, Hector A

AU - Mejia, Alicia

AU - Veeranki, Omkara

AU - Routbort, Mark J

AU - Morris, Van K

AU - Overman, Michael J

AU - Menter, David

AU - Katkhuda, Riham

AU - Wistuba, Ignacio I

AU - Davis, Jennifer S

AU - Kopetz, Scott

AU - Maru, Dipen M

PY - 2020/10/27

Y1 - 2020/10/27

N2 - PURPOSE: Consensus molecular subtyping (CMS) of colorectal cancer (CRC) has potential to reshape the CRC landscape. We developed and validated an assay that is applicable on formalin fixed paraffin embedded (FFPE) samples of CRC and implemented the assay in a CLIA-certified laboratory.EXPERIMENTAL DESIGN: We performed an in silico experiment to build an optimal CMS classifier using a training set of 1329 samples from 12 studies and validation set of 1329 samples from 14 studies. We constructed assay based on Nanostring codesets for the top 472 genes, and performed analyses on paired flash frozen (FF)/FFPE samples from 175 CRCs to adapt the classifier to FFPE using a subset of genes found to be concordant between FF and FFPE, and tested the classifier`s reproducibility, repeatability, and validated in a CLIA-certified laboratory. We assessed prognostic significance of CMS in 345 patients pooled across 3 clinical trials.RESULTS: The best classifier was Weighted Support Vector Machine with high accuracy across platforms and gene lists (>0.95), and the 472-gene model outperforming existing classifiers. We constructed subsets of 99 and 200 genes with high FF/FFPE concordance, and adapted FFPE-based classifier that had strong classification accuracy (>80%) relative to "gold standard" CMS. The classifier was reproducible to sample type, RNA quality, and demonstrated poor prognosis for CMS1-3 and good prognosis for CMS2 in metastatic CRC (p<0.001).CONCLUSIONS: We developed and validated a CRC CMS assay that is ready for use in clinical trials, to assess prognosis in standard-of-care settings and explore as predictor of therapy response.

AB - PURPOSE: Consensus molecular subtyping (CMS) of colorectal cancer (CRC) has potential to reshape the CRC landscape. We developed and validated an assay that is applicable on formalin fixed paraffin embedded (FFPE) samples of CRC and implemented the assay in a CLIA-certified laboratory.EXPERIMENTAL DESIGN: We performed an in silico experiment to build an optimal CMS classifier using a training set of 1329 samples from 12 studies and validation set of 1329 samples from 14 studies. We constructed assay based on Nanostring codesets for the top 472 genes, and performed analyses on paired flash frozen (FF)/FFPE samples from 175 CRCs to adapt the classifier to FFPE using a subset of genes found to be concordant between FF and FFPE, and tested the classifier`s reproducibility, repeatability, and validated in a CLIA-certified laboratory. We assessed prognostic significance of CMS in 345 patients pooled across 3 clinical trials.RESULTS: The best classifier was Weighted Support Vector Machine with high accuracy across platforms and gene lists (>0.95), and the 472-gene model outperforming existing classifiers. We constructed subsets of 99 and 200 genes with high FF/FFPE concordance, and adapted FFPE-based classifier that had strong classification accuracy (>80%) relative to "gold standard" CMS. The classifier was reproducible to sample type, RNA quality, and demonstrated poor prognosis for CMS1-3 and good prognosis for CMS2 in metastatic CRC (p<0.001).CONCLUSIONS: We developed and validated a CRC CMS assay that is ready for use in clinical trials, to assess prognosis in standard-of-care settings and explore as predictor of therapy response.

U2 - 10.1158/1078-0432.CCR-20-2403

DO - 10.1158/1078-0432.CCR-20-2403

M3 - Article

C2 - 33109741

SN - 1078-0432

JO - Clinical cancer research : an official journal of the American Association for Cancer Research

JF - Clinical cancer research : an official journal of the American Association for Cancer Research

ER -

Development and Validation of a Gene Signature Classifier for Consensus Molecular Subtyping of Colorectal Carcinoma in a CLIA-Certified Setting

Abstract

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