Publications by authors named "John N Weinstein"

182 Publications

Compound NSC84167 selectively targets NRF2-activated pancreatic cancer by inhibiting asparagine synthesis pathway.

Cell Death Dis 2021 07 10;12(7):693. Epub 2021 Jul 10.

Department of Gastrointestinal Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, 33612, USA.

Nuclear factor erythroid 2-related factor 2 (NRF2) is aberrantly activated in about 93% of pancreatic cancers. Activated NRF2 regulates multiple downstream molecules involved in cancer cell metabolic reprogramming, translational control, and treatment resistance; however, targeting NRF2 for pancreatic cancer therapy remains largely unexplored. In this study, we used the online computational tool CellMiner to explore the NCI-60 drug databases for compounds with anticancer activities correlating most closely with the mRNA expression of NQO1, a marker for NRF2 pathway activity. Among the >100,000 compounds analyzed, NSC84167, termed herein as NRF2 synthetic lethality compound-01 (NSLC01), was one of the top hits (r = 0.71, P < 0.001) and selected for functional characterization. NSLC01 selectively inhibited the viabilities of four out of seven conventional pancreatic cancer cell lines and induced dramatic apoptosis in the cells with high NRF2 activation. The selective anticancer activity of NSLC01 was further validated with a panel of nine low-passage pancreatic patient-derived cell lines, and a significant reverse correlation between log(IC) of NSLC01 and NQO1 expression was confirmed (r = -0.5563, P = 0.024). Notably, screening of a panel of nine patient-derived xenografts (PDXs) revealed six PDXs with high NQO1/NRF2 activation, and NSLC01 dramatically inhibited the viabilities and induced apoptosis in ex vivo cultures of PDX tumors. Consistent with the ex vivo results, NSLC01 inhibited the tumor growth of two NRF2-activated PDX models in vivo (P < 0.01, n = 7-8) but had no effects on the NRF2-low counterpart. To characterize the mechanism of action, we employed a metabolomic isotope tracer assay that demonstrated that NSLC01-mediated inhibition of de novo synthesis of multiple amino acids, including asparagine and methionine. Importantly, we further found that NSLC01 suppresses the eEF2K/eEF2 translation elongation cascade and protein translation of asparagine synthetase. In summary, this study identified a novel compound that selectively targets protein translation and induces synthetic lethal effects in NRF2-activated pancreatic cancers.
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http://dx.doi.org/10.1038/s41419-021-03970-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8272721PMC
July 2021

Whole-genome characterization of lung adenocarcinomas lacking the RTK/RAS/RAF pathway.

Cell Rep 2021 02;34(5):108707

Fred Hutchinson Cancer Research Center, Seattle, WA, USA.

RTK/RAS/RAF pathway alterations (RPAs) are a hallmark of lung adenocarcinoma (LUAD). In this study, we use whole-genome sequencing (WGS) of 85 cases found to be RPA(-) by previous studies from The Cancer Genome Atlas (TCGA) to characterize the minority of LUADs lacking apparent alterations in this pathway. We show that WGS analysis uncovers RPA(+) in 28 (33%) of the 85 samples. Among the remaining 57 cases, we observe focal deletions targeting the promoter or transcription start site of STK11 (n = 7) or KEAP1 (n = 3), and promoter mutations associated with the increased expression of ILF2 (n = 6). We also identify complex structural variations associated with high-level copy number amplifications. Moreover, an enrichment of focal deletions is found in TP53 mutant cases. Our results indicate that RPA(-) cases demonstrate tumor suppressor deletions and genome instability, but lack unique or recurrent genetic lesions compensating for the lack of RPAs. Larger WGS studies of RPA(-) cases are required to understand this important LUAD subset.
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http://dx.doi.org/10.1016/j.celrep.2021.108707DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8009291PMC
February 2021

A user guide for the online exploration and visualization of PCAWG data.

Nat Commun 2020 07 7;11(1):3400. Epub 2020 Jul 7.

European Molecular Biology Laboratory, 69117, Heidelberg, Germany.

The Pan-Cancer Analysis of Whole Genomes (PCAWG) project generated a vast amount of whole-genome cancer sequencing resource data. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumor types, we provide a user's guide to the five publicly available online data exploration and visualization tools introduced in the PCAWG marker paper. These tools are ICGC Data Portal, UCSC Xena, Chromothripsis Explorer, Expression Atlas, and PCAWG-Scout. We detail use cases and analyses for each tool, show how they incorporate outside resources from the larger genomics ecosystem, and demonstrate how the tools can be used together to understand the biology of cancers more deeply. Together, the tools enable researchers to query the complex genomic PCAWG data dynamically and integrate external information, enabling and enhancing interpretation.
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http://dx.doi.org/10.1038/s41467-020-16785-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7340791PMC
July 2020

Assessment of Luminal and Basal Phenotypes in Bladder Cancer.

Sci Rep 2020 06 16;10(1):9743. Epub 2020 Jun 16.

Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.

Genomic profiling studies have demonstrated that bladder cancer can be divided into two molecular subtypes referred to as luminal and basal with distinct clinical behaviors and sensitivities to frontline chemotherapy. We analyzed the mRNA expressions of signature luminal and basal genes in bladder cancer tumor samples from publicly available and MD Anderson Cancer Center cohorts. We developed a quantitative classifier referred to as basal to luminal transition (BLT) score which identified the molecular subtypes of bladder cancer with 80-94% sensitivity and 83-93% specificity. In order to facilitate molecular subtyping of bladder cancer in primary care centers, we analyzed the protein expressions of signature luminal (GATA3) and basal (KRT5/6) markers by immunohistochemistry, which identified molecular subtypes in over 80% of the cases. In conclusion, we provide a tool for assessment of molecular subtypes of bladder cancer in routine clinical practice.
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http://dx.doi.org/10.1038/s41598-020-66747-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7298008PMC
June 2020

Urothelial-to-Neural Plasticity Drives Progression to Small Cell Bladder Cancer.

iScience 2020 Jun 27;23(6):101201. Epub 2020 May 27.

Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. Electronic address:

We report a comprehensive molecular analysis of 34 cases of small cell carcinoma (SCC) and 84 cases of conventional urothelial carcinoma (UC), with The Cancer Genome Atlas cohort of 408 conventional UC bladder cancers used as the reference. SCCs showed mutational landscapes characterized by nearly uniform inactivation of TP53 and were dominated by Sanger mutation signature 3 associated with loss of BRCA1/2 function. SCCs were characterized by downregulation of luminal and basal markers and were referred to as double-negative. Transcriptome analyses indicated that SCCs displayed lineage plasticity driven by a urothelial-to-neural phenotypic switch with a dysregulated epithelial-to-mesenchymal transition network. SCCs were depleted of immune cells, and expressed high levels of the immune checkpoint receptor, adenosine receptor A2A (ADORA2A), which is a potent inhibitor of immune infiltration. Our observations have important implications for the prognostication and development of more effective therapies for this lethal bladder cancer variant.
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http://dx.doi.org/10.1016/j.isci.2020.101201DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7286965PMC
June 2020

Mechanism of Catalysis by l-Asparaginase.

Biochemistry 2020 05 11;59(20):1927-1945. Epub 2020 May 11.

Macromolecular Crystallography Laboratory, Center for Cancer Research, National Cancer Institute, Frederick, Maryland 21702, United States.

Two bacterial type II l-asparaginases, from and , have played a critical role for more than 40 years as therapeutic agents against juvenile leukemias and lymphomas. Despite a long history of successful pharmacological applications and the apparent simplicity of the catalytic reaction, controversies still exist regarding major steps of the mechanism. In this report, we provide a detailed description of the reaction catalyzed by type II l-asparaginase (EcAII). Our model was developed on the basis of new structural and biochemical experiments combined with previously published data. The proposed mechanism is supported by quantum chemistry calculations based on density functional theory. We provide strong evidence that EcAII catalyzes the reaction according to the double-displacement (ping-pong) mechanism, with formation of a covalent intermediate. Several steps of catalysis by EcAII are unique when compared to reactions catalyzed by other known hydrolytic enzymes. Here, the reaction is initiated by a weak nucleophile, threonine, without direct assistance of a general base, although a distant general base is identified. Furthermore, tetrahedral intermediates formed during the catalytic process are stabilized by a never previously described motif. Although the scheme of the catalytic mechanism was developed only on the basis of data obtained from EcAII and its variants, this novel mechanism of enzymatic hydrolysis could potentially apply to most (and possibly all) l-asparaginases.
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http://dx.doi.org/10.1021/acs.biochem.0c00116DOI Listing
May 2020

Interactive Clustered Heat Map Builder: An easy web-based tool for creating sophisticated clustered heat maps.

F1000Res 2019 14;8. Epub 2019 Oct 14.

Department of Bioinformatics and Computational Biology, University of Texas MD Anderson Cancer Center, Houston, TX, USA.

Clustered heat maps are the most frequently used graphics for visualization and interpretation of genome-scale molecular profiling data in biology.  Construction of a heat map generally requires the assistance of a biostatistician or bioinformatics analyst capable of working in R or a similar programming language to transform the study data, perform hierarchical clustering, and generate the heat map.  Our web-based Interactive Heat Map Builder can be used by investigators with no bioinformatics experience to generate high-caliber, publication quality maps.  Preparation of the data and construction of a heat map is rarely a simple linear process.  Our tool allows a user to move back and forth iteratively through the various stages of map generation to try different options and approaches.  Finally, the heat map the builder creates is available in several forms, including an interactive Next-Generation Clustered Heat Map that can be explored dynamically to investigate the results more fully.
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http://dx.doi.org/10.12688/f1000research.20590.2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7111501PMC
June 2020

Comprehensive molecular characterization of mitochondrial genomes in human cancers.

Nat Genet 2020 03 5;52(3):342-352. Epub 2020 Feb 5.

Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.

Mitochondria are essential cellular organelles that play critical roles in cancer. Here, as part of the International Cancer Genome Consortium/The Cancer Genome Atlas Pan-Cancer Analysis of Whole Genomes Consortium, which aggregated whole-genome sequencing data from 2,658 cancers across 38 tumor types, we performed a multidimensional, integrated characterization of mitochondrial genomes and related RNA sequencing data. Our analysis presents the most definitive mutational landscape of mitochondrial genomes and identifies several hypermutated cases. Truncating mutations are markedly enriched in kidney, colorectal and thyroid cancers, suggesting oncogenic effects with the activation of signaling pathways. We find frequent somatic nuclear transfers of mitochondrial DNA, some of which disrupt therapeutic target genes. Mitochondrial copy number varies greatly within and across cancers and correlates with clinical variables. Co-expression analysis highlights the function of mitochondrial genes in oxidative phosphorylation, DNA repair and the cell cycle, and shows their connections with clinically actionable genes. Our study lays a foundation for translating mitochondrial biology into clinical applications.
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http://dx.doi.org/10.1038/s41588-019-0557-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7058535PMC
March 2020

Integrated Analysis of TP53 Gene and Pathway Alterations in The Cancer Genome Atlas.

Cell Rep 2019 07;28(5):1370-1384.e5

Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA.

The TP53 tumor suppressor gene is frequently mutated in human cancers. An analysis of five data platforms in 10,225 patient samples from 32 cancers reported by The Cancer Genome Atlas (TCGA) enables comprehensive assessment of p53 pathway involvement in these cancers. More than 91% of TP53-mutant cancers exhibit second allele loss by mutation, chromosomal deletion, or copy-neutral loss of heterozygosity. TP53 mutations are associated with enhanced chromosomal instability, including increased amplification of oncogenes and deep deletion of tumor suppressor genes. Tumors with TP53 mutations differ from their non-mutated counterparts in RNA, miRNA, and protein expression patterns, with mutant TP53 tumors displaying enhanced expression of cell cycle progression genes and proteins. A mutant TP53 RNA expression signature shows significant correlation with reduced survival in 11 cancer types. Thus, TP53 mutation has profound effects on tumor cell genomic structure, expression, and clinical outlook.
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http://dx.doi.org/10.1016/j.celrep.2019.07.001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7546539PMC
July 2019

Glutaminase Activity of L-Asparaginase Contributes to Durable Preclinical Activity against Acute Lymphoblastic Leukemia.

Mol Cancer Ther 2019 09 17;18(9):1587-1592. Epub 2019 Jun 17.

Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas.

We and others have reported that the anticancer activity of L-asparaginase (ASNase) against asparagine synthetase (ASNS)-positive cell types requires ASNase glutaminase activity, whereas anticancer activity against ASNS-negative cell types does not. Here, we attempted to disentangle the relationship between asparagine metabolism, glutamine metabolism, and downstream pathways that modulate cell viability by testing the hypothesis that ASNase anticancer activity is based on asparagine depletion rather than glutamine depletion per se. We tested ASNase wild-type (ASNase) and its glutaminase-deficient Q59L mutant (ASNase) and found that ASNase glutaminase activity contributed to durable anticancer activity against xenografts of the ASNS-negative Sup-B15 leukemia cell line in NOD/SCID gamma mice, whereas asparaginase activity alone yielded a mere growth delay. Our findings suggest that ASNase glutaminase activity is necessary for durable, single-agent anticancer activity , even against ASNS-negative cancer types.
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http://dx.doi.org/10.1158/1535-7163.MCT-18-1329DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6726508PMC
September 2019

ZC3H12A Expression in Different Stages of Colorectal Cancer.

Oncoscience 2019 Mar 2;6(3-4):301-311. Epub 2019 Apr 2.

Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.

Identification of CRC patients with early-stage disease provides the opportunity for curative local resection. However, robust markers for stage I tumor prediction are yet to be developed. We analyzed RNA-sequencing data of 221 CRC samples using the TCGA dataset to identify novel biomarkers for stage I CRC. We next validated the TCGA finding in an independent GEO cohort of 290 CRC patients and in a third cohort of 110 CRC tumors and matched normal samples. We further performed correlative analysis of ZC3H12A gene expression with clinicopathologic features and disease-free survival. Expression correlation of ZC3H12A with the chemokine ligands was evaluated via Student's t-test. In the TCGA cohort, stage I CRC patients had significantly higher ZC3H12A mRNA expression as compared with the other three stages combined and with the other individual stages in a pairwise manner (P<0.001 for all comparisons). The significant association of ZC3H12A gene expression with stages was further validated in the GEO cohort and in the additional third cohort. In support of these findings, we further found that patients with lower ZC3H12A expression had more aggressive tumor features and shorter disease-free survival. Biologically, ZC3H12A expression was significantly correlated with expression of three chemokine ligands (CXCL1, CXCL2 and CXCL3), suggesting that immune response dysregulation likely contributes to CRC development. Our results demonstrate ZC3H12A's potential role in identification of CRC patients with early-stage disease.
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http://dx.doi.org/10.18632/oncoscience.480DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6508193PMC
March 2019

Dysregulation of EMT Drives the Progression to Clinically Aggressive Sarcomatoid Bladder Cancer.

Cell Rep 2019 05;27(6):1781-1793.e4

Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. Electronic address:

Sarcomatoid urothelial bladder cancer (SARC) displays a high propensity for distant metastasis and is associated with short survival. We report a comprehensive genomic analysis of 28 cases of SARC and 84 cases of conventional urothelial carcinoma (UC), with the TCGA cohort of 408 muscle-invasive bladder cancers serving as the reference. SARCs show a distinct mutational landscape, with enrichment of TP53, RB1, and PIK3CA mutations. They are related to the basal molecular subtype of conventional UCs and could be divided into epithelial-basal and more clinically aggressive mesenchymal subsets on the basis of TP63 and its target gene expression levels. Other analyses reveal that SARCs are driven by downregulation of homotypic adherence genes and dysregulation of the EMT network, and nearly half exhibit a heavily infiltrated immune phenotype. Our observations have important implications for prognostication and the development of more effective therapies for this highly lethal variant of bladder cancer.
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http://dx.doi.org/10.1016/j.celrep.2019.04.048DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6546434PMC
May 2019

Integrated transcriptomic-genomic tool Texomer profiles cancer tissues.

Nat Methods 2019 05 15;16(5):401-404. Epub 2019 Apr 15.

Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.

Profiling of both the genome and the transcriptome promises a comprehensive, functional readout of a tissue sample, yet analytical approaches are required to translate the increased data dimensionality, heterogeneity and complexity into patient benefits. We developed a statistical approach called Texomer ( https://github.com/KChen-lab/Texomer ) that performs allele-specific, tumor-deconvoluted transcriptome-exome integration of autologous bulk whole-exome and transcriptome sequencing data. Texomer results in substantially improved accuracy in sample categorization and functional variant prioritization.
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http://dx.doi.org/10.1038/s41592-019-0388-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7337246PMC
May 2019

Response envelope analysis for quantitative evaluation of drug combinations.

Bioinformatics 2019 10;35(19):3761-3770

Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.

Motivation: The concept of synergy between two agents, over a century old, is important to the fields of biology, chemistry, pharmacology and medicine. A key step in drug combination analysis is the selection of an additivity model to identify combination effects including synergy, additivity and antagonism. Existing methods for identifying and interpreting those combination effects have limitations.

Results: We present here a computational framework, termed response envelope analysis (REA), that makes use of 3D response surfaces formed by generalized Loewe Additivity and Bliss Independence models of interaction to evaluate drug combination effects. Because the two models imply two extreme limits of drug interaction (mutually exclusive and mutually non-exclusive), a response envelope defined by them provides a quantitatively stringent additivity model for identifying combination effects without knowing the inhibition mechanism. As a demonstration, we apply REA to representative published data from large screens of anticancer and antibiotic combinations. We show that REA is more accurate than existing methods and provides more consistent results in the context of cross-experiment evaluation.

Availability And Implementation: The open-source software package associated with REA is available at: https://github.com/4dsoftware/rea.

Supplementary Information: Supplementary data are available at Bioinformatics online.
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http://dx.doi.org/10.1093/bioinformatics/btz091DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7963081PMC
October 2019

Whole-Organ Genomic Characterization of Mucosal Field Effects Initiating Bladder Carcinogenesis.

Cell Rep 2019 02;26(8):2241-2256.e4

Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. Electronic address:

We used whole-organ mapping to study the locoregional molecular changes in a human bladder containing multifocal cancer. Widespread DNA methylation changes were identified in the entire mucosa, representing the initial field effect. The field effect was associated with subclonal low-allele frequency mutations and a small number of DNA copy alterations. A founder mutation in the RNA splicing gene, ACIN1, was identified in normal mucosa and expanded clonally with an additional 21 mutations in progression to carcinoma. The patterns of mutations and copy number changes in carcinoma in situ and foci of carcinoma were almost identical, confirming their clonal origins. The pathways affected by the DNA copy alterations and mutations, including the Kras pathway, were preceded by the field changes in DNA methylation, suggesting that they reinforced mechanisms that had already been initiated by methylation. The results demonstrate that DNA methylation can serve as the initiator of bladder carcinogenesis.
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http://dx.doi.org/10.1016/j.celrep.2019.01.095DOI Listing
February 2019

ElemCor: accurate data analysis and enrichment calculation for high-resolution LC-MS stable isotope labeling experiments.

BMC Bioinformatics 2019 Feb 19;20(1):89. Epub 2019 Feb 19.

Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.

Background: The investigation of intracellular metabolism is the mainstay in the biotechnology and physiology settings. Intracellular metabolic rates are commonly evaluated using labeling pattern of the identified metabolites obtained from stable isotope labeling experiments. The labeling pattern or mass distribution vector describes the fractional abundances of all isotopologs with different masses as a result of isotopic labeling, which are typically resolved using mass spectrometry. Because naturally occurring isotopes and isotopic impurity also contribute to measured signals, the measured patterns must be corrected to obtain the labeling patterns. Since contaminant isotopologs with the same nominal mass can be resolved using modern mass spectrometers with high mass resolution, the correction process should be resolution dependent.

Results: Here we present a software tool, ElemCor, to perform correction of such data in a resolution-dependent manner. The tool is based on mass difference theory (MDT) and information from unlabeled samples (ULS) to account for resolution effects. MDT is a mathematical theory and only requires chemical formulae to perform correction. ULS is semi-empirical and requires additional measurement of isotopologs from unlabeled samples. We validate both methods and show their improvement in accuracy and comprehensiveness over existing methods using simulated data and experimental data from Saccharomyces cerevisiae. The tool is available at https://github.com/4dsoftware/elemcor .

Conclusions: We present a software tool based on two methods, MDT and ULS, to correct LC-MS data from isotopic labeling experiments for natural abundance and isotopic impurity. We recommend MDT for low-mass compounds for cost efficiency in experiments, and ULS for high-mass compounds with relatively large spectral inaccuracy that can be tracked by unlabeled standards.
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http://dx.doi.org/10.1186/s12859-019-2669-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6381631PMC
February 2019

Assessment of l-Asparaginase Pharmacodynamics in Mouse Models of Cancer.

Metabolites 2019 Jan 9;9(1). Epub 2019 Jan 9.

Department of Bioinformatics and Computational Biology and The Proteomics and Metabolomics Core Facility, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.

l-asparaginase (ASNase) is a metabolism-targeted anti-neoplastic agent used to treat acute lymphoblastic leukemia (ALL). ASNase's anticancer activity results from the enzymatic depletion of asparagine (Asn) and glutamine (Gln), which are converted to aspartic acid (Asp) and glutamic acid (Glu), respectively, in the blood. Unfortunately, accurate assessment of the in vivo pharmacodynamics (PD) of ASNase is challenging because of the following reasons: (i) ASNase is resilient to deactivation; (ii) ASNase catalytic efficiency is very high; and (iii) the PD markers Asn and Gln are depleted ex vivo in blood samples containing ASNase. To address those issues and facilitate longitudinal studies in individual mice for ASNase PD studies, we present here a new LC-MS/MS bioanalytical method that incorporates rapid quenching of ASNase for measurement of Asn, Asp, Gln, and Glu in just 10 µL of whole blood, with limits of detection (s:n ≥ 10:1) estimated to be 2.3, 3.5, 0.8, and 0.5 µM, respectively. We tested the suitability of the method in a 5-day, longitudinal PD study in mice and found the method to be simple to perform with sufficient accuracy and precision for whole blood measurements. Overall, the method increases the density of data that can be acquired from a single animal and will facilitate optimization of novel ASNase treatment regimens and/or the development of new ASNase variants with desired kinetic properties.
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http://dx.doi.org/10.3390/metabo9010010DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6359345PMC
January 2019

Global analysis of tRNA and translation factor expression reveals a dynamic landscape of translational regulation in human cancers.

Commun Biol 2018 21;1:234. Epub 2018 Dec 21.

1Department of Biochemistry and Molecular Biology, McGovern Medical School at The University of Texas Health Science Center at Houston, Houston, TX 77030 USA.

The protein translational system, including transfer RNAs (tRNAs) and several categories of enzymes, plays a key role in regulating cell proliferation. Translation dysregulation also contributes to cancer development, though relatively little is known about the changes that occur to the translational system in cancer. Here, we present global analyses of tRNAs and three categories of enzymes involved in translational regulation in ~10,000 cancer patients across 31 cancer types from The Cancer Genome Atlas. By analyzing the expression levels of tRNAs at the gene, codon, and amino acid levels, we identified unequal alterations in tRNA expression, likely due to the uneven distribution of tRNAs decoding different codons. We find that overexpression of tRNAs recognizing codons with a low observed-over-expected ratio may overcome the translational bottleneck in tumorigenesis. We further observed overall overexpression and amplification of tRNA modification enzymes, aminoacyl-tRNA synthetases, and translation factors, which may play synergistic roles with overexpression of tRNAs to activate the translational systems across multiple cancer types.
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http://dx.doi.org/10.1038/s42003-018-0239-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6303286PMC
December 2018

A Pan-Cancer Analysis Reveals High-Frequency Genetic Alterations in Mediators of Signaling by the TGF-β Superfamily.

Cell Syst 2018 10 26;7(4):422-437.e7. Epub 2018 Sep 26.

Memorial Sloan Kettering Cancer Center, Computational & Systems Biology Program, New York, NY 10065, USA.

We present an integromic analysis of gene alterations that modulate transforming growth factor β (TGF-β)-Smad-mediated signaling in 9,125 tumor samples across 33 cancer types in The Cancer Genome Atlas (TCGA). Focusing on genes that encode mediators and regulators of TGF-β signaling, we found at least one genomic alteration (mutation, homozygous deletion, or amplification) in 39% of samples, with highest frequencies in gastrointestinal cancers. We identified mutation hotspots in genes that encode TGF-β ligands (BMP5), receptors (TGFBR2, AVCR2A, and BMPR2), and Smads (SMAD2 and SMAD4). Alterations in the TGF-β superfamily correlated positively with expression of metastasis-associated genes and with decreased survival. Correlation analyses showed the contributions of mutation, amplification, deletion, DNA methylation, and miRNA expression to transcriptional activity of TGF-β signaling in each cancer type. This study provides a broad molecular perspective relevant for future functional and therapeutic studies of the diverse cancer pathways mediated by the TGF-β superfamily.
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http://dx.doi.org/10.1016/j.cels.2018.08.010DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6370347PMC
October 2018

Clinical significance of FBXO17 gene expression in high-grade glioma.

BMC Cancer 2018 Jul 31;18(1):773. Epub 2018 Jul 31.

Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.

Background: High-grade gliomas (HGGs) exhibit marked heterogeneity in clinical behavior. The purpose of this study was to identify a novel biomarker that predicts patient outcome, which is helpful in HGG patient management.

Methods: We analyzed gene expression profiles of 833 HGG cases, representing the largest patient population ever reported. Using the data set from the Cancer Genome Atlas (TCGA) and random partitioning approach, we performed Cox proportional hazards model analysis to identify novel prognostic mRNAs in HGG. The predictive capability was further assessed via multivariate analysis and validated in 4 additional data sets. The Kaplan-Meier method was used to evaluate survival difference between dichotomic groups of patients. Correlation of gene expression and DNA methylation was evaluated via Student's t-test.

Results: Patients with elevated FBXO17 expression had a significantly shorter overall survival (OS) (P = 0.0011). After adjustment by IDH1 mutation, sex, and patient age, FBXO17 gene expression was significantly associated with OS (HR = 1.29, 95% CI =1.04-1.59, P = 0.018). In addition, FBXO17 expression can significantly distinguish patients by OS not only among patients who received temozolomide chemotherapy (HR 1.35, 95% CI =1.12-1.64, P = 0.002) but also among those who did not (HR = 1.48, 95% CI =1.20-1.82, P < 0.0001). The significant association of FBXO17 gene expression with OS was further validated in four external data sets. We further found that FBXO17 endogenous expression is significantly contributable from its promoter methylation.

Conclusion: Epigenetically modulated FBXO17 has a potential as a stratification factor for clinical decision-making in HGG.
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http://dx.doi.org/10.1186/s12885-018-4680-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6069786PMC
July 2018

SoS Notebook: an interactive multi-language data analysis environment.

Bioinformatics 2018 11;34(21):3768-3770

Department of Bioinformatics and Computational Biology, The University of Texas, MD Anderson Cancer Center, Houston, TX, USA.

Motivation: Complex bioinformatic data analysis workflows involving multiple scripts in different languages can be difficult to consolidate, share and reproduce. An environment that streamlines the entire processes of data collection, analysis, visualization and reporting of such multi-language analyses is currently lacking.

Results: We developed Script of Scripts (SoS) Notebook, a web-based notebook environment that allows the use of multiple scripting language in a single notebook, with data flowing freely within and across languages. SoS Notebook enables researchers to perform sophisticated bioinformatic analysis using the most suitable tools for different parts of the workflow, without the limitations of a particular language or complications of cross-language communications.

Availability And Implementation: SoS Notebook is hosted at http://vatlab.github.io/SoS/ and is distributed under a BSD license.
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http://dx.doi.org/10.1093/bioinformatics/bty405DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6198852PMC
November 2018

Predicting high-risk endometrioid carcinomas using proteins.

Oncotarget 2018 Apr 13;9(28):19704-19715. Epub 2018 Apr 13.

Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.

Background: The lethality of endometrioid endometrial cancer (EEC) is primarily attributable to advanced-stage diseases. We sought to develop a biomarker model that predicts EEC surgical stage at the time of clinical diagnosis.

Results: PSES was significantly correlated with surgical stage in the TCGA cohort ( < 0.0001) and in the validation cohort ( = 0.0003). Even among grade 1 or 2 tumors, PSES was significantly higher in advanced than in early stage tumors in both the TCGA ( = 0.005) and MD Anderson Cancer Center (MDACC) ( = 0.006) cohorts. Patients with positive PSES score had significantly shorter progression-free survival than those with negative PSES in the TCGA (hazard ratio [HR], 2.033; 95% CI, 1.031 to 3.809; = 0.04) and validation (HR, 3.306; 95% CI, 1.836 to 9.436; = 0.0007) cohorts. The ErbB signaling pathway was most significantly enriched in the PSES proteins and downregulated in advanced stage tumors.

Methods: Using reverse-phase protein array expression profiles of 170 antibodies for 210 EEC cases from TCGA, we constructed a Protein Scoring of EEC Staging (PSES) scheme comprising 6 proteins (3 of them phosphorylated) for surgical stage prediction. We validated and evaluated its diagnostic potential in an independent cohort of 184 EEC cases obtained at MDACC using receiver operating characteristic curve analyses. Kaplan-Meier survival analysis was used to examine the association of PSES score with patient outcome, and Ingenuity pathway analysis was used to identify relevant signaling pathways. Two-sided statistical tests were used.

Conclusions: PSES may provide clinically useful prediction of high-risk tumors and offer new insights into tumor biology in EEC.
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http://dx.doi.org/10.18632/oncotarget.24803DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5929419PMC
April 2018

The Immune Landscape of Cancer.

Immunity 2018 04 5;48(4):812-830.e14. Epub 2018 Apr 5.

Department of Systems Biology and Department of Electrical Engineering, Columbia University, New York, NY 10027, USA.

We performed an extensive immunogenomic analysis of more than 10,000 tumors comprising 33 diverse cancer types by utilizing data compiled by TCGA. Across cancer types, we identified six immune subtypes-wound healing, IFN-γ dominant, inflammatory, lymphocyte depleted, immunologically quiet, and TGF-β dominant-characterized by differences in macrophage or lymphocyte signatures, Th1:Th2 cell ratio, extent of intratumoral heterogeneity, aneuploidy, extent of neoantigen load, overall cell proliferation, expression of immunomodulatory genes, and prognosis. Specific driver mutations correlated with lower (CTNNB1, NRAS, or IDH1) or higher (BRAF, TP53, or CASP8) leukocyte levels across all cancers. Multiple control modalities of the intracellular and extracellular networks (transcription, microRNAs, copy number, and epigenetic processes) were involved in tumor-immune cell interactions, both across and within immune subtypes. Our immunogenomics pipeline to characterize these heterogeneous tumors and the resulting data are intended to serve as a resource for future targeted studies to further advance the field.
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http://dx.doi.org/10.1016/j.immuni.2018.03.023DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5982584PMC
April 2018
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