Abstract
Background
In order to correctly decode phenotypic information from RNA-sequencing (RNA-seq) data, careful selection of the RNA-seq quantification measure is critical for inter-sample ...comparisons and for downstream analyses, such as differential gene expression between two or more conditions. Several methods have been proposed and continue to be used. However, a consensus has not been reached regarding the best gene expression quantification method for RNA-seq data analysis.
Methods
In the present study, we used replicate samples from each of 20 patient-derived xenograft (PDX) models spanning 15 tumor types, for a total of 61 human tumor xenograft samples available through the NCI patient-derived model repository (PDMR). We compared the reproducibility across replicate samples based on TPM (transcripts per million), FPKM (fragments per kilobase of transcript per million fragments mapped), and normalized counts using coefficient of variation, intraclass correlation coefficient, and cluster analysis.
Results
Our results revealed that hierarchical clustering on normalized count data tended to group replicate samples from the same PDX model together more accurately than TPM and FPKM data. Furthermore, normalized count data were observed to have the lowest median coefficient of variation (CV), and highest intraclass correlation (ICC) values across all replicate samples from the same model and for the same gene across all PDX models compared to TPM and FPKM data.
Conclusion
We provided compelling evidence for a preferred quantification measure to conduct downstream analyses of PDX RNA-seq data. To our knowledge, this is the first comparative study of RNA-seq data quantification measures conducted on PDX models, which are known to be inherently more variable than cell line models. Our findings are consistent with what others have shown for human tumors and cell lines and add further support to the thesis that normalized counts are the best choice for the analysis of RNA-seq data across samples.
To facilitate functional investigation of the role of NADPH oxidase 1 (NOX1) and associated reactive oxygen species in cancer cell signaling, we report herein the development and characterization of ...a novel mouse monoclonal antibody that specifically recognizes the C-terminal region of the NOX1 protein. The antibody was validated in stable NOX1 overexpression and knockout systems, and demonstrates wide applicability for Western blot analysis, confocal microscopy, flow cytometry, and immunohistochemistry. We employed our NOX1 antibody to characterize NOX1 expression in a panel of 30 human colorectal cancer cell lines, and correlated protein expression with NOX1 mRNA expression and superoxide production in a subset of these cells. Although a significant correlation between oncogenic RAS status and NOX1 mRNA levels could not be demonstrated in colon cancer cell lines, RAS mutational status did correlate with NOX1 expression in human colon cancer surgical specimens. Immunohistochemical analysis of a comprehensive set of tissue microarrays comprising over 1,200 formalin-fixed, paraffin-embedded tissue cores from human epithelial tumors and inflammatory disease confirmed that NOX1 is overexpressed in human colon and small intestinal adenocarcinomas, as well as adenomatous polyps, compared to adjacent, uninvolved intestinal mucosae. In contradistinction to prior studies, we did not find evidence of NOX1 overexpression at the protein level in tumors versus histologically normal tissues in prostate, lung, ovarian, or breast carcinomas. This study constitutes the most comprehensive histopathological characterization of NOX1 to date in cellular models of colon cancer and in normal and malignant human tissues using a thoroughly evaluated monoclonal antibody. It also further establishes NOX1 as a clinically relevant therapeutic target in colorectal and small intestinal cancer.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The significance of the phenotypic plasticity afforded by epithelial-mesenchymal transition (EMT) for cancer progression and drug resistance remains to be fully elucidated in the clinic. We evaluated ...epithelial-mesenchymal phenotypic characteristics across a range of tumor histologies using a validated, high-resolution digital microscopic immunofluorescence assay (IFA) that incorporates β-catenin detection and cellular morphology to delineate carcinoma cells from stromal fibroblasts and that quantitates the individual and colocalized expression of the epithelial marker E-cadherin (E) and the mesenchymal marker vimentin (V) at subcellular resolution ("EMT-IFA"). We report the discovery of β-catenin
cancer cells that coexpress E-cadherin and vimentin in core-needle biopsies from patients with various advanced metastatic carcinomas, wherein these cells are transitioning between strongly epithelial and strongly mesenchymal-like phenotypes. Treatment of carcinoma models with anticancer drugs that differ in their mechanism of action (the tyrosine kinase inhibitor pazopanib in MKN45 gastric carcinoma xenografts and the combination of tubulin-targeting agent paclitaxel with the BCR-ABL inhibitor nilotinib in MDA-MB-468 breast cancer xenografts) caused changes in the tumor epithelial-mesenchymal character. Moreover, the appearance of partial EMT or mesenchymal-like carcinoma cells in MDA-MB-468 tumors treated with the paclitaxel-nilotinib combination resulted in upregulation of cancer stem cell (CSC) markers and susceptibility to FAK inhibitor. A metastatic prostate cancer patient treated with the PARP inhibitor talazoparib exhibited similar CSC marker upregulation. Therefore, the phenotypic plasticity conferred on carcinoma cells by EMT allows for rapid adaptation to cytotoxic or molecularly targeted therapy and could create a form of acquired drug resistance that is transient in nature. SIGNIFICANCE: Despite the role of EMT in metastasis and drug resistance, no standardized assessment of EMT phenotypic heterogeneity in human carcinomas exists; the EMT-IFA allows for clinical monitoring of tumor adaptation to therapy.
Proteomic data provide a direct readout of protein function, thus constituting an information-rich resource for prognostic and predictive modeling. However, protein array data may not fully capture ...pathway activity due to the limited number of molecules and incomplete pathway coverage compared to other high-throughput technologies. For the present study, our aim was to improve clinical outcome prediction compared to published pathway-dependent prognostic signatures for The Cancer Genome Atlas (TCGA) cohorts using the least absolute shrinkage and selection operator (LASSO). RPPA data is particularly well-suited to the LASSO due to the relatively low number of predictors compared to larger genomic data matrices. Our approach selected predictors regardless of their pathway membership and optimally combined their RPPA measurements into a weighted risk score. Performance was assessed and compared to that of the published signatures using two unbiased approaches: 1) 10 iterations of threefold cross-validation for unbiased estimation of hazard ratio and difference in 5-year survival (by Kaplan-Meier method) between predictor-defined high and low risk groups; and 2) a permutation test to evaluate the statistical significance of the cross-validated log-rank statistic. Here, we demonstrate strong stratification of 445 renal clear cell carcinoma tumors from The Cancer Genome Atlas (TCGA) into high and low risk groups using LASSO regression on RPPA data. Median cross-validated difference in 5-year overall survival was 32.8%, compared to 25.2% using a published receptor tyrosine kinase (RTK) prognostic signature (median hazard ratios of 3.3 and 2.4, respectively). Applicability and performance of our approach was demonstrated in three additional TCGA cohorts: ovarian serous cystadenocarcinoma (OVCA), sarcoma (SARC), and cutaneous melanoma (SKCM). The data-driven LASSO-based approach is versatile and well-suited for discovery of new protein/disease associations.
Functional conservation is known to constrain protein evolution. Nevertheless, the long-term divergence patterns of proteins maintaining the same molecular function and the possible limits of this ...divergence have not been explored in detail. We investigate these fundamental questions by characterizing the divergence between ancient protein orthologs with conserved molecular function. Our results demonstrate that the decline of sequence and structural similarities between such orthologs significantly slows down after ~1-2 billion years of independent evolution. As a result, the sequence and structural similarities between ancient orthologs have not substantially decreased for the past billion years. The effective divergence limit (>25% sequence identity) is not primarily due to protein sites universally conserved in all linages. Instead, less than four amino acid types are accepted, on average, per site across orthologous protein sequences. Our analysis also reveals different divergence patterns for protein sites with experimentally determined small and large fitness effects of mutations.
This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).
The cellular microenvironment plays a critical role in cancer initiation and progression. Exposure to oxidative stress, specifically hydrogen peroxide (H2O2), has been linked to aberrant cellular ...signaling through which the development of cancer may be promoted. Three members of the NADPH oxidase family (NOX4, DUOX1 and DUOX2) explicitly generate this non-radical oxidant in a wide range of tissues, often in support of the inflammatory response. This review summarizes the contributions of each H2O2-producing NOX to the invasive behaviors of tumors and/or the epithelial-mesenchymal transition (EMT) in cancer that plays an essential role in metastasis. Tissue localization in tumorigenesis is also highlighted, with patient-derived TCGA microarray data profiled across 31 cancer cohorts to provide a comprehensive guide to the relevance of NOX4/DUOX1/DUOX2 in cancer studies.
•Intracellular hydrogen peroxide can promote oxidative stress leading to invasive cellular characteristics.•NADPH oxidase enzymes NOX4, DUOX1 and DUOX2 are prominent sources of hydrogen peroxide linked to cancer and metastasis.•Intracellular ROS production from the NOX4 enzyme is critical to promoting invadopodia formation.•Substantial DUOX1 promoter methylation evokes expression loss, impacting lung cancer cell migration and EMT status.•Hydrogen peroxide, produced by DUOX2, contributes to chemoresistance-induced EMT in colon cancer cells.
: The intracellular effects and overall efficacies of anticancer therapies can vary significantly by tumor type. To identify patterns of drug-induced gene modulation that occur in different cancer ...cell types, we measured gene-expression changes across the NCI-60 cell line panel after exposure to 15 anticancer agents. The results were integrated into a combined database and set of interactive analysis tools, designated the NCI Transcriptional Pharmacodynamics Workbench (NCI TPW), that allows exploration of gene-expression modulation by molecular pathway, drug target, and association with drug sensitivity. We identified common transcriptional responses across agents and cell types and uncovered gene-expression changes associated with drug sensitivity. We also demonstrated the value of this tool for investigating clinically relevant molecular hypotheses and identifying candidate biomarkers of drug activity. The NCI TPW, publicly available at https://tpwb.nci.nih.gov, provides a comprehensive resource to facilitate understanding of tumor cell characteristics that define sensitivity to commonly used anticancer drugs. SIGNIFICANCE: The NCI Transcriptional Pharmacodynamics Workbench represents the most extensive compilation to date of directly measured longitudinal transcriptional responses to anticancer agents across a thoroughly characterized ensemble of cancer cell lines.
Dual oxidase 2 (DUOX2) generates H
O
that plays a critical role in both host defense and chronic inflammation. Previously, we demonstrated that the proinflammatory mediators IFN-γ and LPS enhance ...expression of DUOX2 and its maturation factor DUOXA2 through STAT1- and NF-κB‒mediated signaling in human pancreatic cancer cells. Using a panel of colon and pancreatic cancer cell lines, we now report the induction of DUOX2/DUOXA2 mRNA and protein expression by the T
2 cytokine IL-4. IL-4 activated STAT6 signaling that, when silenced, significantly decreased induction of DUOX2. Furthermore, the T
17 cytokine IL-17A combined synergistically with IL-4 to increase DUOX2 expression in both colon and pancreatic cancer cells mediated, at least in part, by signaling through NF-κB. The upregulation of DUOX2 was associated with a significant increase in the production of extracellular H
O
and DNA damage-as indicated by the accumulation of 8-oxo-dG and γH2AX-which was suppressed by the NADPH oxidase inhibitor diphenylene iodonium and a DUOX2-specific small interfering RNA. The clinical relevance of these experiments is suggested by immunohistochemical, microarray, and quantitative RT-PCR studies of human colon and pancreatic tumors demonstrating significantly higher DUOX2, IL-4R, and IL-17RA expression in tumors than in adjacent normal tissues; in pancreatic adenocarcinoma, increased DUOX2 expression is adversely associated with overall patient survival. These data suggest a functional association between DUOX2-mediated H
O
production and induced DNA damage in gastrointestinal malignancies.
Abstract Background With poor prognosis and high mortality, pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies. Standard of care therapies for PDAC have included ...gemcitabine for the past three decades, although resistance often develops within weeks of chemotherapy initiation through an array of possible mechanisms. Methods We reanalyzed publicly available RNA-seq gene expression profiles of 28 PDAC patient-derived xenograft (PDX) models before and after a 21-day gemcitabine treatment using our validated analysis pipeline to identify molecular markers of intrinsic and acquired resistance. Results Using normalized RNA-seq quantification measurements, we first identified oxidative phosphorylation and interferon alpha pathways as the two most enriched cancer hallmark gene sets in the baseline gene expression profile associated with intrinsic gemcitabine resistance and sensitivity, respectively. Furthermore, we discovered strong correlations between drug-induced expression changes in glycolysis and oxidative phosphorylation genes and response to gemcitabine, which suggests that these pathways may be associated with acquired gemcitabine resistance mechanisms. Thus, we developed prediction models using baseline gene expression profiles in those pathways and validated them in another dataset of 12 PDAC models from Novartis. We also developed prediction models based on drug-induced expression changes in genes from the Molecular Signatures Database (MSigDB)’s curated 50 cancer hallmark gene sets. Finally, pathogenic TP53 mutations correlated with treatment resistance. Conclusion Our results demonstrate that concurrent upregulation of both glycolysis and oxidative phosphorylation pathways occurs in vivo in PDAC PDXs following gemcitabine treatment and that pathogenic TP53 status had association with gemcitabine resistance in these models. Our findings may elucidate the molecular basis for gemcitabine resistance and provide insights for effective drug combination in PDAC chemotherapy.
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