THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

Cells release into the extracellular environment diverse types of membrane vesicles of endosomal and plasma membrane origin called exosomes and microvesicles, respectively. These extracellular vesicles (EVs) represent an important mode of intercellular communication by serving as vehicles for transfer between cells of membrane and cytosolic proteins, lipids, and RNA. Deficiencies in our knowledge of the molecular mechanisms for EV formation and lack of methods to interfere with the packaging of cargo or with vesicle release, however, still hamper identification of their physiological relevance in vivo. In this review, we focus on the characterization of EVs and on currently proposed mechanisms for their formation, targeting, and function.

https://rupress.org/jcb/article-pdf/200/4/373/1262520/jcb_201211138.pdf

Extracellular vesicles: exosomes, microvesicles, and friends.

In the 1980s, exosomes were described as vesicles of endosomal origin secreted from reticulocytes. Interest increased around these extracellular vesicles, as they appeared to participate in several cellular processes. Exosomes bear proteins, lipids, and RNAs, mediating intercellular communication between different cell types in the body, and thus affecting normal and pathological conditions. Only recently, scientists acknowledged the difficulty of separating exosomes from other types of extracellular vesicles, which precludes a clear attribution of a particular function to the different types of secreted vesicles. To shed light into this complex but expanding field of science, this review focuses on the definition of exosomes and other secreted extracellular vesicles. Their biogenesis, their secretion, and their subsequent fate are discussed, as their functions rely on these important processes.

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Biogenesis, Secretion, and Intercellular Interactions of Exosomes and Other Extracellular Vesicles

In the past decade, extracellular vesicles (EVs) have been recognized as potent vehicles of intercellular communication, both in prokaryotes and eukaryotes. This is due to their capacity to transfer proteins, lipids and nucleic acids, thereby influencing various physiological and pathological functions of both recipient and parent cells. While intensive investigation has targeted the role of EVs in different pathological processes, for example, in cancer and autoimmune diseases, the EV-mediated maintenance of homeostasis and the regulation of physiological functions have remained less explored. Here, we provide a comprehensive overview of the current understanding of the physiological roles of EVs, which has been written by crowd-sourcing, drawing on the unique EV expertise of academia-based scientists, clinicians and industry based in 27 European countries, the United States and Australia. This review is intended to be of relevance to both researchers already working on EV biology and to newcomers who will encounter this universal cell biological system. Therefore, here we address the molecular contents and functions of EVs in various tissues and body fluids from cell systems to organs. We also review the physiological mechanisms of EVs in bacteria, lower eukaryotes and plants to highlight the functional uniformity of this emerging communication system.

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Biological properties of extracellular vesicles and their physiological functions

Biogenesis, Secretion, and Intercellular Interactions of Exosomes and Other


 Tumor ulceration in cutaneous melanoma represents one of the top prognostic indicators for clinical outcome, associated with reduced progression free and overall survival. Despite this influence, the underlying biology driving tumor ulceration remains largely unexplored. One of the potential mediators of ulceration are microRNAs (miRNAs). These short, non-coding RNAs are frequently dysregulated in cancer and can impact tumor biology via mediation of gene expression. Distinct miRNA expression patterns have been identified in melanoma that can function as predictive biomarkers of disease progression and metastasis. However, the presence of a unique miRNA profile in ulcerated melanoma has not yet been assessed.
 miRNA and mRNA expression was assessed in 35 ulcerated and non-ulcerated cutaneous melanomas using the NanoString Human miRNA and Tumor Signaling 360 mRNA assays and validated in an independent cohort. Linear models and moderated t-tests were used to detect differential expression between ulcerated and non-ulcerated tumors. Pathway enrichment and functional annotations were determined using public databases. Pearson correlations were employed to predict miRNA-mRNA binding pairs. Differentially expressed mRNAs were identified as miRNA targets using Ingenuity Pathway Analysis.
 Comparison between groups revealed significant upregulation of 13 miRNAs in ulcerated relative to non-ulcerated tumors (p <0.03). 4 of these miRNAs were also significantly upregulated in the validation cohort (miR-363-3p, miR-196b-5p, miR-135b-5p and miR-223-3p, p <0.02). Conversely, 11 miRNAs were significantly downregulated in ulcerated relative to non-ulcerated tumors (p <0.05), of which, miR-376c-5p was also significantly downregulated in the validation cohort (p=0.009). 21 mRNAs were differentially expressed in ulcerated relative to non-ulcerated tumors, with 3 being significant in the validation cohort as well (FPR, IL-11, and ADM, p <0.05). 9 of these 21 mRNAs were then identified as predicted targets of multiple differentially expressed miRNAs in ulcerated tumors. 2 of the differentially expressed mRNAs had an inverse correlation in expression with regulatory miRNAs in our tumor samples (SOCS3 and miR-218-5p, and IL7R and miR-376c-5p). Each of the mRNAs significantly upregulated in both the original and validation cohorts have been previously associated with angiogenesis, migration or pro-metastatic cell survival in the context of cancer and pathway analysis identified significant enrichment for “granulocyte adhesion and diapedesis” (p=0.02) in ulcerated tumors.
 This study demonstrates that a unique subset of miRNAs and mRNAs are differentially expressed in ulcerated melanoma when compared to non-ulcerated. These findings also provide novel insight regarding how increased angiogenesis and metastasis may contribute to melanoma tumor ulceration.
 Citation Format: Emily Schwarz, Mallory J. DiVincenzo, Casey Ren, Zoe Barricklow, Maribelle Moufawad, Lianbo Yu, Paolo Fadda, Colin Angell, Sara Zelinskas, Steven Sun, John H. Howard, Catherine Chung, Craig Slingluff, Alejandro A. Gru, Kari Kendra, William E. Carson. Expression patterns of microRNAs and associated target genes in ulcerated primary cutaneous melanoma. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3764.

Abstract 3764: Expression patterns of microRNAs and associated target genes in ulcerated primary cutaneous melanoma

MOTIVATION
CRISPR-based genetic perturbation screen is a powerful tool to probe gene function. However, experimental noises, especially for the lowly expressed genes, need to be accounted for to maintain proper control of false positive rate.


METHOD
We develop a statistical method, named CRISPR screen with Expression Data Analysis (CEDA), to integrate gene expression profiles and CRISPR screen data for identifying essential genes. CEDA stratifies genes based on expression level and adopts a three-component mixture model for the log-fold change of single-guide RNAs (sgRNAs). Empirical Bayesian prior and Expectation-Maximization algorithm are used for parameter estimation and false discovery rate inference.


RESULTS
Taking advantage of gene expression data, CEDA identifies essential genes with higher expression. Compared to existing methods, CEDA shows comparable reliability but higher sensitivity in detecting essential genes with moderate sgRNA fold change. Therefore, using the same CRISPR data, CEDA generates an additional hit gene list.


SUPPLEMENTARY INFORMATION
Supplementary data are available at Bioinformatics online.

CEDA: integrating gene expression data with CRISPR-pooled screen data identifies essential genes with higher expression

Human T-cell leukemia virus type 1 (HTLV-1) is the infectious cause of adult T-cell leukemia/lymphoma (ATL), an extremely aggressive and fatal malignancy of CD4+ T-cells. Due to the chemotherapy-resistance of ATL and the absence of long-term therapy regimens currently available for ATL patients, there is an urgent need to characterize novel therapeutic targets against this disease. Protein arginine methyltransferase 5 (PRMT5) is a type II PRMT enzyme that is directly involved in the pathogenesis of multiple different lymphomas through the transcriptional regulation of relevant oncogenes. Recently, our group identified that PRMT5 is overexpressed in HTLV-1-transformed T-cell lines, during the HTLV-1-mediated T-cell immortalization process, and in ATL patient samples. The objective of this study was to determine the importance of PRMT5 on HTLV-1 infected cell viability, T-cell transformation, and ultimately disease induction. Inhibition of PRMT5 enzymatic activity with a commercially available small molecule inhibitor (EPZ015666) resulted in selective in vitro toxicity of actively proliferating and transformed T-cells. EPZ015666-treatment resulted in a dose-dependent increase in apoptosis in HTLV-1-transformed and ATL-derived cell lines compared to uninfected Jurkat T-cells. Using a co-culture model of infection and immortalization, we found that EPZ015666 is capable of blocking HTLV-1-mediated T-cell immortalization in vitro, indicating that PRMT5 enzymatic activity is essential for the HTLV-1 T-cell transformation process. Administration of EPZ015666 in both NSG xenograft and HTLV-1-infected humanized immune system (HIS) mice significantly improved survival outcomes. The cumulative findings of this study demonstrate that the epigenetic regulator PRMT5 is critical for the survival, transformation, and pathogenesis of HTLV-1, illustrating the value of this cellular enzyme as a potential therapeutic target for the treatment of ATL.

/pdf/the-prmt5-inhibitor-epz015666-is-effective-against-htlv-1-26yn8sgo.pdf

The PRMT5 inhibitor EPZ015666 is effective against HTLV-1-transformed T-cell lines in vitro and in vivo

Motivation The rapid growth in the number and application of high-throughput “omics” technologies has created a need for better methods to integrate multiomics data sets. Much progress has been made in developing unsupervised methods, but supervised methods have lagged behind. Results We develop a novel algorithm, plasma, to train and validate models to predict time-to-event outcomes from multiomics data sets. The model is built on using two layers of the existing partial least squares algorithm to first select components that covary with the outcome in order to construct a joint Cox proportional hazards model. We apply plasma to the lung squamous cell carcinoma (LUSC) data from The Cancer Genome Atlas (TCGA). Our model successfully separates an independent test data set into high risk and low risk patients (p = 0.0132). The performance of the joint multiomics model is superior to that of the individual omics data sets. It is also superior to the performance of an approach that uses an unsupervised method (Multi Omics Factor Analysis; MOFA) to find factors that might work as predictors. Many of the factors that contribute strongly to the plasma model can be justified from the biological literature. Availability and Implementation The plasma R package can be obtained from The Comprehensive R Archive Network (CRAN) at https://cran.r-project.org/web/packages/plasma/index.html. The latest version of the package can be obtained from R-Forge at https://r-forge.r-project.org/R/?group_id=174. Source code and data for the analysis presented here can be obtained from GitLab, at https://gitlab.com/krcoombes/plasma. Contact Email: kcoombes@augusta.edu Supplementary Information Supplementary material is available from Bioinformatics online.

/pdf/plasma-partial-least-squares-for-multiomics-analysis-1ul2himo.pdf

plasma: Partial LeAst Squares for Multiomics Analysis

http://www.bloodjournal.org/content/bloodjournal/early/2015/04/01/blood-2014-12-618470.full.pdf

Lianbo Yu

Papers

Abstract 3764: Expression patterns of microRNAs and associated target genes in ulcerated primary cutaneous melanoma

CEDA: integrating gene expression data with CRISPR-pooled screen data identifies essential genes with higher expression

The PRMT5 inhibitor EPZ015666 is effective against HTLV-1-transformed T-cell lines in vitro and in vivo

plasma: Partial LeAst Squares for Multiomics Analysis

Authors and affiliations