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Concordance of deregulated mechanisms unveiled in underpowered experiments: PTBP1 knockdown case study

ABSTRACT: Background: Genome-wide transcriptome profiling generated by microarray and RNA-Seq often provides deregulated genes or pathways applicable only to larger cohort. On the other hand, individualized interpretation of transcriptomes is increasely pursued to improve diagnosis, prognosis, and patient treatment processes. Yet, robust and accurate methods based on a single paired-sample remain an unmet challenge. Methods: “N-of-1-pathways” translates gene expression data profiles into mechanism-level profiles on single pairs of samples (one p-value per geneset). It relies on three principles: i) statistical universe is a single paired sample, which serves as its own control; ii) statistics can be derived from multiple gene expression measures that share common biological mechanisms assimilated to genesets; iii) semantic similarity metric takes into account inter-mechanisms’ relationships to better assess commonality and differences, within and cross study-samples (e.g. patients, cell-lines, tissues, etc.), which helps the interpretation of the underpinning biology. Results: In the context of underpowered experiments, N-of-1-pathways predictions perform better or comparable to those of GSEA and Differentially Expressed Genes enrichment (DEG enrichment), within- and cross-datasets. N-of-1-pathways uncovered concordant PTBP1-dependent mechanisms across datasets (Odds-Ratios≥13, p-values≤1×10-5), such as RNA splicing and cell cycle. In addition, it unveils tissue-specific mechanisms of alternatively transcribed PTBP1-dependent genesets. Furthermore, we demonstrate that GSEA and DEG Enrichment preclude accurate analysis on single paired samples. Conclusions: N-of-1-pathways enables robust and biologically relevant mechanism-level classifiers with small cohorts and one single paired samples that surpasses conventional methods. Further, it identifies unique sample/ patient mechanisms, a requirement for precision medicine.

ORGANISM(S): Homo sapiens

PROVIDER: GSE52493 | GEO | 2013/11/20

SECONDARY ACCESSION(S): PRJNA229102

REPOSITORIES: GEO

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Project description:Background: Genome-wide transcriptome profiling generated by microarray and RNA-Seq often provides deregulated genes or pathways applicable only to larger cohort. On the other hand, individualized interpretation of transcriptomes is increasely pursued to improve diagnosis, prognosis, and patient treatment processes. Yet, robust and accurate methods based on a single paired-sample remain an unmet challenge. Methods: M-bM-^@M-^\N-of-1-pathwaysM-bM-^@M-^] translates gene expression data profiles into mechanism-level profiles on single pairs of samples (one p-value per geneset). It relies on three principles: i) statistical universe is a single paired sample, which serves as its own control; ii) statistics can be derived from multiple gene expression measures that share common biological mechanisms assimilated to genesets; iii) semantic similarity metric takes into account inter-mechanismsM-bM-^@M-^Y relationships to better assess commonality and differences, within and cross study-samples (e.g. patients, cell-lines, tissues, etc.), which helps the interpretation of the underpinning biology. Results: In the context of underpowered experiments, N-of-1-pathways predictions perform better or comparable to those of GSEA and Differentially Expressed Genes enrichment (DEG enrichment), within- and cross-datasets. N-of-1-pathways uncovered concordant PTBP1-dependent mechanisms across datasets (Odds-RatiosM-bM-^IM-%13, p-valuesM-bM-^IM-$1M-CM-^W10-5), such as RNA splicing and cell cycle. In addition, it unveils tissue-specific mechanisms of alternatively transcribed PTBP1-dependent genesets. Furthermore, we demonstrate that GSEA and DEG Enrichment preclude accurate analysis on single paired samples. Conclusions: N-of-1-pathways enables robust and biologically relevant mechanism-level classifiers with small cohorts and one single paired samples that surpasses conventional methods. Further, it identifies unique sample/ patient mechanisms, a requirement for precision medicine. Cell lines, culture conditions: The epithelial human breast cancer cell line MDA-MB231 (ER-/ PR-/ HER2-) were obtained from the American Type Culture Collection (Manassas, VA). The epithelial human ovarian tumor cell line A2780 was received as a generous gift from Dr. Thomas C. Hamilton (Fox Chase Cancer Center, Philadelphia, PA) Cancer Center, Philadelphia, PA). Cells were grown in DMEM supplemented with 10% fetal bovine serum (FBS), 2mM L-glutamine in a humid environment at 37M-BM-0C, with 5% CO2. Both cell lines were free of Mycoplasma species and were maintained for no longer than 10 weeks in culture after recovery from frozen stocks. Mycoplasma levels were checked periodically using the MycoAlertM-BM-. Mycoplasma Detection Kit (Lonza Inc., Allendale, NJ). The authenticity of cell lines was assessed by the ATCC carrying out short tandem repeat (STR) analysis (Verified STR Profiling Service, ATCCM-BM-. 135-XV). Additionally, we compared A2780 to the original STR profile collected by the European Collection of Cell Culture (Catalogue number 93112519). Doxycycline-inducible knockdown of PTBP1 regulated by small hairpin RNA (shRNA): In order to analyze the effect of PTBP1 depletion, two consecutive viral transductions were performed in both MDA-MB231 and A2780 cell lines. Cells were plated on 24-well plate (10-20M-CM-^W104 cells/well), maintained in culture for 16 hours, and then medium containing LV-tTR/KRAB-Red lentiviral particles was added. Following 16 h of incubation, cells were transduced a second time by LV-THM/PTBshRNA or LV-THM/LUCshRNA lentiviral particles. Clones expressing both red and green fluorescent protein (dsRED and GFP respectively) were selected and expanded. Following 16 h of incubation, cells were washed and split in two subcultures, one without doxycycline (PTBP1/-DOX; Control in Figure 1) and the other with Doxycycline (DOX) at a final concentration of 1 M-NM-<g/ml (PTBP1/+DOX; PTBP1-KD in Figure 1). Doxycycline was prepared according to the manufacturerM-bM-^@M-^Ys recommendations (Sigma-Aldrich, St. Louis, MO). Five days later, cells were analyzed by fluorescence microscopy, and PTBP1 gene expression was assessed using PCR and Western Blotting (data not shown). The cells that were transduced by LV-LUCshRNA express PTBP1 regardless of the presence of DOX (LUCshRNA/+DOX). Constructs and lentivirus preparation were performed as previously described in literature [He X et al., Knockdown of polypyrimidine tract-binding protein suppresses ovarian tumor cell growth and invasiveness in vitro, Oncogene 2007, 26(34):4961-4968]. Microarray Analysis: For each of the cell lines, MDA-MB231 and A2780, total RNAs were extracted from four biological replicates of PTBP1-depleted cells, PTBP1-KD (4M-CM-^W PTBP1/+DOX) and eight biological replicates control cells (4M-CM-^W PTBP1/-DOX and 4M-CM-^W LUCshRNA/+DOX) by Direct-zol RNA kit (Zymo Research, Irvine, CA). All paired samples consist of PTBP1-depleted cells (PTBP1-KD) and matched control cells. Qualities of RNA were assessed based on the RNA quality indicator (RQI M-bM-^IM-% 8) using Experion Automated Electrophoresis System (Bio-Rad, Hercules, CA). Gene expression microarray measurements were performed using the GeneChip PrimeView Human Gene Expression Array that contains 49,395 probes and measures 36,000 transcripts and variants per sample. Labeling and hybridization were performed following Affymetrix protocols. The raw data were normalized according to the Robust Multiple-array Average (RMA) technique, using Affymetrix Power Tools (APT). biological replicate: Ovarian_LucsH_DOX_1, Ovarian_LucsH_DOX_2, Ovarian_LucsH_DOX_3, Ovarian_LucsH_DOX_4 biological replicate: Ovarian_PTBsh1_NODOX_1, Ovarian_PTBsh1_NODOX_2, Ovarian_PTBsh1_NODOX_3, Ovarian_PTBsh1_NODOX_4 biological replicate: Ovarian_PTBsh1_DOX_1, Ovarian_PTBsh1_DOX_2, Ovarian_PTBsh1_DOX_3, Ovarian_PTBsh1_DOX_4 biological replicate: Breast_LucsH_DOX_1, Breast_LucsH_DOX_2, Breast_LucsH_DOX_3, Breast_LucsH_DOX_4 biological replicate: Breast_PTBsh1_NODOX_1, Breast_PTBsh1_NODOX_2, Breast_PTBsh1_NODOX_3, Breast_PTBsh1_NODOX_4 biological replicate: Breast_PTBsh1_DOX_1, Breast_PTBsh1_DOX_2, Breast_PTBsh1_DOX_3, Breast_PTBsh1_DOX_4

Project description:Background: Understanding individual patient host-response to viruses is key to designing optimal personalized therapy. Indeed, a subjectM-bM-^@M-^Ys epigenetic, transcriptomic and proteomic profiles dynamically respond to environmental challenges according to their intrinsic specific genetics. Unsurprisingly, in vivo human experimentation to understand individualized dynamic response of the transcriptome to viruses are rarely studied because of the obviously limitations stemming from ethical considerations of the clinical risk. In this rhinovirus study, we first establish that ex vivo human cells response to virus can serve as proxy for otherwise controversial in vivo human experimentation of viral infection. We further demonstrate that the N-of-1-pathways framework, that we previously validated for single patient M-bM-^@M-^Xomics analyses in cancer, can be utilized to understand individualized ex vivo response to viral stress and inform clinicians involved in personalized therapeutics. Method: N-of-1-pathways, validated retrospectively in whole tumors and experimentally in cancer cell lines, is a framework designed for identifying deregulated pathways at the single patient level between two M-bM-^@M-^Xomics profiles. It computes a significance score for a list of given genesets, using the M-bM-^@M-^Xomics profiles of a mere two samples as input (e.g. normal/tumoral, pre/post-treatment). We hypothesized that its usage could be extended to virus exposed cells. Additionally, we developed the Similarity Venn Diagram, an efficient and deceptively simple method for comparing results expressed in an ontology organized as a directed acyclic graph. We extracted the peripheral blood of four human subjects, with and without an ex vivo infection to rhinovirus. Their deregulated pathways were compared to those of 9 human subjects prior and after intranasal inoculation M-bM-^@M-^\in vivoM-bM-^@M-^] with rhinovirus. Results: We compared the N-of-1-pathways results using two established cohort-level methodologies: GSEA and enrichment of differentially expressed genes. Results are significantly and biologically similar between in vivo and ex vivo studies, both at the genes and enriched pathways levels. ROC curves demonstrate that deregulated pathways identified by N-of-1-pathways in cells each single subject infected ex vivo recapitulate the biologically relevant pathways observed in vivo in a whole cohort. Conclusion: In the context of less than five published transcriptomes of human viral infections in vivo and one ex vivo, the latter can be supplemented by 2-sample analyses yielding increased insight in individualized response without clinical risks. PBMCs incubated with viruses: The live PBMCs had been isolated from blood samples collected from four human subjects under a protocol approved by The University of Arizona Internal Review Board. Whole blood was obtained from donors and placed in heparin tubes that were centrifuged according to standard protocols to obtain PBMCs, then each aliquoted in two paired samples. Each sample of the pair was subsequently exposed to and incubated with either (i) Human Rhinovirus serotype 16 obtained from the American Type Culture Collection (RV; ATCCM-BM-. VR-283; ex vivo infected sample), or to (ii) sterile medium (control ex vivo non-infected sample) and incubated at 35M-BM-0C. This protocol resulted in 4 ex vivo infected + 4 ex vivo controls = 8 paired samples. RNA was extracted from these samples, amplified, tagged and hybridized on Affymetrix Human Gene 1.0 ST microarrays according to standard operating procedures. Dataset and preprocessing: Robust Multiple-array Average (RMA) normalization was applied on each patient data independently (2 paired samples at a time, to avoid bias in the single-patient experiments) using Affymetrix Power Tools (APT)

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Concordance of deregulated mechanisms unveiled in underpowered experiments: PTBP1 knockdown case study

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