Long non-coding RNAs identify a subset of luminal muscle-invasive bladder cancer patients with favorable prognosis
Long non-coding RNAs identify a subset of luminal muscle-invasive bladder cancer patients with favorable prognosis
BACKGROUND: Muscle-invasive bladder cancer (MIBC) is a heterogeneous disease, and gene expression profiling has identified several molecular subtypes with distinct biological and clinicopathological characteristics. While MIBC subtyping has primarily been based on messenger RNA (mRNA), long non-coding RNAs (lncRNAs) may provide additional resolution.
METHODS: LncRNA expression was quantified from microarray data of a MIBC cohort treated with neoadjuvant chemotherapy (NAC) and radical cystectomy (RC) (n = 223). Unsupervised consensus clustering of highly variant lncRNAs identified a four-cluster solution, which was characterized using a panel of MIBC biomarkers, regulon activity profiles, gene signatures, and survival analysis. The four-cluster solution was confirmed in The Cancer Genome Atlas (TCGA) cohort (n = 405). A single-sample genomic classifier (GC) was trained using ridge-penalized logistic regression and validated in two independent cohorts (n = 255 and n = 94).
RESULTS: NAC and TCGA cohorts both contained an lncRNA cluster (LC3) with favorable prognosis that was enriched with tumors of the luminal-papillary (LP) subtype. In both cohorts, patients with LP tumors in LC3 (LPL-C3) were younger and had organ-confined, node-negative disease. The LPL-C3 tumors had enhanced FGFR3, SHH, and wild-type p53 pathway activity. In the TCGA cohort, LPL-C3 tumors were enriched for FGFR3 mutations and depleted for TP53 and RB1 mutations. A GC trained to identify these LPL-C3 patients showed robust performance in two validation cohorts.
CONCLUSIONS: Using lncRNA expression profiles, we identified a biologically distinct subgroup of luminal-papillary MIBC with a favorable prognosis. These data suggest that lncRNAs provide additional information for higher-resolution subtyping, potentially improving precision patient management.
1-13
de Jong, Joep J.
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Liu, Yang
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Robertson, A. Gordon
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Seiler, Roland
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Groeneveld, Clarice S.
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van der Heijden, Michiel S.
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Wright, Jonathan L.
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Douglas, James
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Dall'Era, Marc
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Crabb, Simon J.
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van Rhijn, Bas W.G.
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van Kessel, Kim E.M.
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Davicioni, Elai
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Castro, Mauro A.A.
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Lotan, Yair
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Zwarthoff, Ellen C.
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Black, Peter C.
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Boormans, Joost L.
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Gibb, Ewan A.
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17 October 2019
de Jong, Joep J.
c8631e1b-fd90-421d-89db-37ef1cc2fba3
Liu, Yang
1aef6807-3d74-48fa-bcef-cc69beb91dc9
Robertson, A. Gordon
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Seiler, Roland
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Groeneveld, Clarice S.
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van der Heijden, Michiel S.
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Wright, Jonathan L.
2b5a4f14-69ae-4a14-b073-399cd499e1ca
Douglas, James
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Dall'Era, Marc
5236d9b8-175e-4fe0-abea-f24bc77030c5
Crabb, Simon J.
bcd1b566-7677-4f81-8429-3ab0e85f8373
van Rhijn, Bas W.G.
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van Kessel, Kim E.M.
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Davicioni, Elai
8d0ac603-abf4-4d0e-894e-975a2edb318b
Castro, Mauro A.A.
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Lotan, Yair
31675425-4fe7-429a-9292-eb2bd19dad5a
Zwarthoff, Ellen C.
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Black, Peter C.
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Boormans, Joost L.
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Gibb, Ewan A.
0f360aa2-3f90-4f79-9746-00ed593e521e
de Jong, Joep J., Liu, Yang, Robertson, A. Gordon, Seiler, Roland, Groeneveld, Clarice S., van der Heijden, Michiel S., Wright, Jonathan L., Douglas, James, Dall'Era, Marc, Crabb, Simon J., van Rhijn, Bas W.G., van Kessel, Kim E.M., Davicioni, Elai, Castro, Mauro A.A., Lotan, Yair, Zwarthoff, Ellen C., Black, Peter C., Boormans, Joost L. and Gibb, Ewan A.
(2019)
Long non-coding RNAs identify a subset of luminal muscle-invasive bladder cancer patients with favorable prognosis.
Genome Medicine, 11 (1), .
(doi:10.1186/s13073-019-0669-z).
Abstract
BACKGROUND: Muscle-invasive bladder cancer (MIBC) is a heterogeneous disease, and gene expression profiling has identified several molecular subtypes with distinct biological and clinicopathological characteristics. While MIBC subtyping has primarily been based on messenger RNA (mRNA), long non-coding RNAs (lncRNAs) may provide additional resolution.
METHODS: LncRNA expression was quantified from microarray data of a MIBC cohort treated with neoadjuvant chemotherapy (NAC) and radical cystectomy (RC) (n = 223). Unsupervised consensus clustering of highly variant lncRNAs identified a four-cluster solution, which was characterized using a panel of MIBC biomarkers, regulon activity profiles, gene signatures, and survival analysis. The four-cluster solution was confirmed in The Cancer Genome Atlas (TCGA) cohort (n = 405). A single-sample genomic classifier (GC) was trained using ridge-penalized logistic regression and validated in two independent cohorts (n = 255 and n = 94).
RESULTS: NAC and TCGA cohorts both contained an lncRNA cluster (LC3) with favorable prognosis that was enriched with tumors of the luminal-papillary (LP) subtype. In both cohorts, patients with LP tumors in LC3 (LPL-C3) were younger and had organ-confined, node-negative disease. The LPL-C3 tumors had enhanced FGFR3, SHH, and wild-type p53 pathway activity. In the TCGA cohort, LPL-C3 tumors were enriched for FGFR3 mutations and depleted for TP53 and RB1 mutations. A GC trained to identify these LPL-C3 patients showed robust performance in two validation cohorts.
CONCLUSIONS: Using lncRNA expression profiles, we identified a biologically distinct subgroup of luminal-papillary MIBC with a favorable prognosis. These data suggest that lncRNAs provide additional information for higher-resolution subtyping, potentially improving precision patient management.
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s13073-019-0669-z
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Accepted/In Press date: 29 August 2019
Published date: 17 October 2019
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Local EPrints ID: 437348
URI: http://eprints.soton.ac.uk/id/eprint/437348
ISSN: 1756-994X
PURE UUID: 2515c083-72e7-4aa2-aaa2-113fa44fbe2a
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Date deposited: 24 Jan 2020 17:31
Last modified: 17 Mar 2024 02:57
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Contributors
Author:
Joep J. de Jong
Author:
Yang Liu
Author:
A. Gordon Robertson
Author:
Roland Seiler
Author:
Clarice S. Groeneveld
Author:
Michiel S. van der Heijden
Author:
Jonathan L. Wright
Author:
James Douglas
Author:
Marc Dall'Era
Author:
Bas W.G. van Rhijn
Author:
Kim E.M. van Kessel
Author:
Elai Davicioni
Author:
Mauro A.A. Castro
Author:
Yair Lotan
Author:
Ellen C. Zwarthoff
Author:
Peter C. Black
Author:
Joost L. Boormans
Author:
Ewan A. Gibb
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