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Article ; Online: Expression-based subtypes define pathologic response to neoadjuvant immune-checkpoint inhibitors in muscle-invasive bladder cancer

A. Gordon Robertson / Khyati Meghani / Lauren Folgosa Cooley / Kimberly A. McLaughlin / Leigh Ann Fall / Yanni Yu / Mauro A. A. Castro / Clarice S. Groeneveld / Aurélien de Reyniès / Vadim I. Nazarov / Vasily O. Tsvetkov / Bonnie Choy / Daniele Raggi / Laura Marandino / Francesco Montorsi / Thomas Powles / Andrea Necchi / Joshua J. Meeks

Nature Communications, Vol 14, Iss 1, Pp 1-

2023 Volume 19

Abstract: Abstract Checkpoint immunotherapy (CPI) has increased survival for some patients with advanced-stage bladder cancer (BCa). However, most patients do not respond. Here, we characterized the tumor and immune microenvironment in pre- and post-treatment ... ...

Abstract	Abstract Checkpoint immunotherapy (CPI) has increased survival for some patients with advanced-stage bladder cancer (BCa). However, most patients do not respond. Here, we characterized the tumor and immune microenvironment in pre- and post-treatment tumors from the PURE01 neoadjuvant pembrolizumab immunotherapy trial, using a consolidative approach that combined transcriptional and genetic profiling with digital spatial profiling. We identify five distinctive genetic and transcriptomic programs and validate these in an independent neoadjuvant CPI trial to identify the features of response or resistance to CPI. By modeling the regulatory network, we identify the histone demethylase KDM5B as a repressor of tumor immune signaling pathways in one resistant subtype (S1, Luminal-excluded) and demonstrate that inhibition of KDM5B enhances immunogenicity in FGFR3-mutated BCa cells. Our study identifies signatures associated with response to CPI that can be used to molecularly stratify patients and suggests therapeutic alternatives for subtypes with poor response to neoadjuvant immunotherapy.
Keywords	Science ; Q
Subject code	616
Language	English
Publishing date	2023-04-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Identification of Post-Transcriptional Modulators of Breast Cancer Transcription Factor Activity Using MINDy.

Thomas M Campbell / Mauro A A Castro / Bruce A J Ponder / Kerstin B Meyer

PLoS ONE, Vol 11, Iss 12, p e

2016 Volume 0168770

Abstract: We have recently identified transcription factors (TFs) that are key drivers of breast cancer risk. To better understand the pathways or sub-networks in which these TFs mediate their function we sought to identify upstream modulators of their activity. ... ...

Abstract	We have recently identified transcription factors (TFs) that are key drivers of breast cancer risk. To better understand the pathways or sub-networks in which these TFs mediate their function we sought to identify upstream modulators of their activity. We applied the MINDy (Modulator Inference by Network Dynamics) algorithm to four TFs (ESR1, FOXA1, GATA3 and SPDEF) that are key drivers of estrogen receptor-positive (ER+) breast cancer risk, as well as cancer progression. Our computational analysis identified over 500 potential modulators. We assayed 189 of these and identified 55 genes with functional characteristics that were consistent with a role as TF modulators. In the future, the identified modulators may be tested as potential therapeutic targets, able to alter the activity of TFs that are critical in the development of breast cancer.
Keywords	Medicine ; R ; Science ; Q
Language	English
Publishing date	2016-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Novel lncRNAs Co-Expression Networks Identifies LINC00504 with Oncogenic Role in Luminal A Breast Cancer Cells

Carolina Mathias / Clarice S. Groeneveld / Sheyla Trefflich / Erika P. Zambalde / Rubens S. Lima / Cícero A. Urban / Karin B. Prado / Enilze M. S. F. Ribeiro / Mauro A. A. Castro / Daniela F. Gradia / Jaqueline C. de Oliveira

International Journal of Molecular Sciences, Vol 22, Iss 5, p

2021 Volume 2420

Abstract: Long non-coding RNAs (lncRNAs) are functional transcripts with more than 200 nucleotides. These molecules exhibit great regulatory capacity and may act at different levels of gene expression regulation. Despite this regulatory versatility, the biology of ...

Abstract	Long non-coding RNAs (lncRNAs) are functional transcripts with more than 200 nucleotides. These molecules exhibit great regulatory capacity and may act at different levels of gene expression regulation. Despite this regulatory versatility, the biology of these molecules is still poorly understood. Computational approaches are being increasingly used to elucidate biological mechanisms in which these lncRNAs may be involved. Co-expression networks can serve as great allies in elucidating the possible regulatory contexts in which these molecules are involved. Herein, we propose the use of the pipeline deposited in the RTN package to build lncRNAs co-expression networks using TCGA breast cancer (BC) cohort data. Worldwide, BC is the most common cancer in women and has great molecular heterogeneity. We identified an enriched co-expression network for the validation of relevant cell processes in the context of BC, including LINC00504. This lncRNA has increased expression in luminal subtype A samples, and is associated with prognosis in basal-like subtype. Silencing this lncRNA in luminal A cell lines resulted in decreased cell viability and colony formation. These results highlight the relevance of the proposed method for the identification of lncRNAs in specific biological contexts.
Keywords	LINC00504 ; breast cancer ; co-expression ; lncRNA ; luminal A ; Biology (General) ; QH301-705.5 ; Chemistry ; QD1-999
Subject code	570
Language	English
Publishing date	2021-02-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Correction

Ricardo M Ferreira / José Luiz Rybarczyk-Filho / Rodrigo J S Dalmolin / Mauro A A Castro / José C F Moreira / Leonardo G Brunnet / Rita M C de Almeida

PLoS ONE, Vol 10, Iss 3, p e

preferential duplication of intermodular hub genes: an evolutionary signature in eukaryotes genome networks.

2015 Volume 0118425

Keywords	Medicine ; R ; Science ; Q
Language	English
Publishing date	2015-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: O Processamento de uma Ontologia sobre a Integração de Dados de Vias de Interação Molecular Envolvidas em Câncer

Heleno Carmo Borges Cabral / Giovani Rubert Librelotto / Éder M. Simão / Marialva Sinigaglia / Mauro A. A. Castro / José C. M. Mombach

Revista Brasileira de Computação Aplicada, Vol 3, Iss 1, Pp 82-

2011 Volume 91

Abstract: The study on the interactions of molecular pathways linked to cancer requires the centralization of biological data, because the information is spread over several public systems of storage. Ontocancro ontology aims to provide research data relevant to ... ...

Abstract	The study on the interactions of molecular pathways linked to cancer requires the centralization of biological data, because the information is spread over several public systems of storage. Ontocancro ontology aims to provide research data relevant to their study through a Web interface that provides a direct search and consistent, ensuring uniformity of information.
Keywords	Bioinformática ; Câncer ; Ontologias ; Electronic computers. Computer science ; QA75.5-76.95
Language	English
Publishing date	2011-04-01T00:00:00Z
Publisher	Universidade de Passo Fundo (UPF)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: FOXA1 repression drives lineage plasticity and immune heterogeneity in bladder cancers with squamous differentiation

Joshua I. Warrick / Wenhuo Hu / Hironobu Yamashita / Vonn Walter / Lauren Shuman / Jenna M. Craig / Lan L. Gellert / Mauro A. A. Castro / A. Gordon Robertson / Fengshen Kuo / Irina Ostrovnaya / Judy Sarungbam / Ying-bei Chen / Anuradha Gopalan / Sahussapont J. Sirintrapun / Samson W. Fine / Satish K. Tickoo / Kwanghee Kim / Jasmine Thomas /

Nagar Karan / Sizhi Paul Gao / Timothy N. Clinton / Andrew T. Lenis / Timothy A. Chan / Zhiyu Chen / Manisha Rao / Travis J. Hollman / Yanyun Li / Nicholas D. Socci / Shweta Chavan / Agnes Viale / Neeman Mohibullah / Bernard H. Bochner / Eugene J. Pietzak / Min Yuen Teo / Gopa Iyer / Jonathan E. Rosenberg / Dean F. Bajorin / Matthew Kaag / Suzanne B. Merrill / Monika Joshi / Rosalyn Adam / John A. Taylor / Peter E. Clark / Jay D. Raman / Victor E. Reuter / Yu Chen / Samuel A. Funt / David B. Solit / David J. DeGraff

Nature Communications, Vol 13, Iss 1, Pp 1-

2022 Volume 17

Abstract: Bladder cancer can often exhibit genomic and morphological heterogeneity. Here, the authors use genomics analysis to show lineage plasticity of bladder cancers with squamous differentiation, and identify key transcription factors related to this ... ...

Abstract	Bladder cancer can often exhibit genomic and morphological heterogeneity. Here, the authors use genomics analysis to show lineage plasticity of bladder cancers with squamous differentiation, and identify key transcription factors related to this morphological and immune heterogeneity.
Keywords	Science ; Q
Language	English
Publishing date	2022-11-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Preferential duplication of intermodular hub genes

Ricardo M Ferreira / José Luiz Rybarczyk-Filho / Rodrigo J S Dalmolin / Mauro A A Castro / José C F Moreira / Leonardo G Brunnet / Rita M C de Almeida

PLoS ONE, Vol 8, Iss 2, p e

an evolutionary signature in eukaryotes genome networks.

2013 Volume 56579

Abstract: Whole genome protein-protein association networks are not random and their topological properties stem from genome evolution mechanisms. In fact, more connected, but less clustered proteins are related to genes that, in general, present more paralogs as ... ...

Abstract	Whole genome protein-protein association networks are not random and their topological properties stem from genome evolution mechanisms. In fact, more connected, but less clustered proteins are related to genes that, in general, present more paralogs as compared to other genes, indicating frequent previous gene duplication episodes. On the other hand, genes related to conserved biological functions present few or no paralogs and yield proteins that are highly connected and clustered. These general network characteristics must have an evolutionary explanation. Considering data from STRING database, we present here experimental evidence that, more than not being scale free, protein degree distributions of organisms present an increased probability for high degree nodes. Furthermore, based on this experimental evidence, we propose a simulation model for genome evolution, where genes in a network are either acquired de novo using a preferential attachment rule, or duplicated with a probability that linearly grows with gene degree and decreases with its clustering coefficient. For the first time a model yields results that simultaneously describe different topological distributions. Also, this model correctly predicts that, to produce protein-protein association networks with number of links and number of nodes in the observed range for Eukaryotes, it is necessary 90% of gene duplication and 10% of de novo gene acquisition. This scenario implies a universal mechanism for genome evolution.
Keywords	Medicine ; R ; Science ; Q
Subject code	612
Language	English
Publishing date	2013-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Whole-genome characterization of lung adenocarcinomas lacking alterations in the RTK/RAS/RAF pathway

Jian Carrot-Zhang / Xiaotong Yao / Siddhartha Devarakonda / Aditya Deshpande / Jeffrey S. Damrauer / Tiago Chedraoui Silva / Christopher K. Wong / Hyo Young Choi / Ina Felau / A. Gordon Robertson / Mauro A.A. Castro / Lisui Bao / Esther Rheinbay / Eric Minwei Liu / Tuan Trieu / David Haan / Christina Yau / Toshinori Hinoue / Yuexin Liu /

Ofer Shapira / Kiran Kumar / Karen L. Mungall / Hailei Zhang / Jake June-Koo Lee / Ashton Berger / Galen F. Gao / Binyamin Zhitomirsky / Wen-Wei Liang / Meng Zhou / Sitapriya Moorthi / Alice H. Berger / Eric A. Collisson / Michael C. Zody / Li Ding / Andrew D. Cherniack / Gad Getz / Olivier Elemento / Christopher C. Benz / Josh Stuart / J.C. Zenklusen / Rameen Beroukhim / Jason C. Chang / Joshua D. Campbell / D. Neil Hayes / Lixing Yang / Peter W. Laird / John N. Weinstein / David J. Kwiatkowski / Ming S. Tsao / William D. Travis

Cell Reports, Vol 34, Iss 8, Pp 108784- (2021)

2021

Keywords	Biology (General) ; QH301-705.5
Language	English
Publishing date	2021-02-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Long non-coding RNAs identify a subset of luminal muscle-invasive bladder cancer patients with favorable prognosis

Joep J. de Jong / Yang Liu / A. Gordon Robertson / Roland Seiler / Clarice S. Groeneveld / Michiel S. van der Heijden / Jonathan L. Wright / James Douglas / Marc Dall’Era / Simon J. Crabb / Bas W. G. van Rhijn / Kim E. M. van Kessel / Elai Davicioni / Mauro A. A. Castro / Yair Lotan / Ellen C. Zwarthoff / Peter C. Black / Joost L. Boormans / Ewan A. Gibb

Genome Medicine, Vol 11, Iss 1, Pp 1-

2019 Volume 13

Abstract: 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 ... ...

Abstract	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.
Keywords	Gene expression analysis ; Long non-coding RNA ; Molecular subtypes ; Muscle-invasive bladder cancer ; Medicine ; R ; Genetics ; QH426-470
Subject code	610 ; 616
Language	English
Publishing date	2019-10-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Comprehensive Molecular Characterization of Muscle-Invasive Bladder Cancer

Robertson, A. Gordon / Akinyemi I. Ojesina / Andrew D. Cherniack / Benilton de Sa Carvalho / Bogdan A. Czerniak / Caleb Choo / Catherine J. Wu / Chandra Sekhar Pedamallu / David J. Kwiatkowski / David J. McConkey / Dmitry A. Gordenin / Donna E. Hansel / Ewan A. Gibb / Francisco Sanchez-Vega / Gad Getz / Gordon B. Mills / Guangwu Guo / Hikmat Al-Ahmadie / Jaegil Kim /

Cell. 2017 Oct. 19, v. 171

2017

Abstract: We report a comprehensive analysis of 412 muscle-invasive bladder cancers characterized by multiple TCGA analytical platforms. Fifty-eight genes were significantly mutated, and the overall mutational load was associated with APOBEC-signature mutagenesis. ...

Abstract	We report a comprehensive analysis of 412 muscle-invasive bladder cancers characterized by multiple TCGA analytical platforms. Fifty-eight genes were significantly mutated, and the overall mutational load was associated with APOBEC-signature mutagenesis. Clustering by mutation signature identified a high-mutation subset with 75% 5-year survival. mRNA expression clustering refined prior clustering analyses and identified a poor-survival “neuronal” subtype in which the majority of tumors lacked small cell or neuroendocrine histology. Clustering by mRNA, long non-coding RNA (lncRNA), and miRNA expression converged to identify subsets with differential epithelial-mesenchymal transition status, carcinoma in situ scores, histologic features, and survival. Our analyses identified 5 expression subtypes that may stratify response to different treatments.
Keywords	carcinoma ; gene expression ; genes ; histology ; messenger RNA ; microRNA ; mutagenesis ; non-coding RNA ; urinary bladder neoplasms
Language	English
Dates of publication	2017-1019
Size	p. 540-556.e25.
Publishing place	Elsevier Inc.
Document type	Article
ZDB-ID	187009-9
ISSN	1097-4172 ; 0092-8674
ISSN (online)	1097-4172
ISSN	0092-8674
DOI	10.1016/j.cell.2017.09.007
Database	NAL-Catalogue (AGRICOLA)

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