• Breast cancer
• Gene expression analysis
• L-arginine depletion
• Normalization
• Quantitative real-time PCR (qRT-PCR)
• Reference gene

• Humans
• Breast Neoplasms/genetics
• Breast Neoplasms/pathology
• Female
• Real-Time Polymerase Chain Reaction/methods
• Real-Time Polymerase Chain Reaction/standards
• Arginine/genetics
• Gene Expression Profiling/methods
• Gene Expression Profiling/standards
• Cell Line, Tumor
• Reference Standards
• Gene Expression Regulation, Neoplastic

• grant Joachim Herz Stiftung
• grant Georg and Jürgen Rickertsen foundation
• Universitätsklinikum Hamburg-Eppendorf (UKE) (5411)

• LZTFL1
• Wnt signaling
• adipogenesis
• caveolin
• cell surface protein
• cilia
• glucocorticoid receptor
• mesenchymal stem cells (MSCs)
• obesity
• peroxisome proliferator-activated receptor γ (PPARγ)

• Animals
• Mesenchymal Stem Cells/metabolism
• Mesenchymal Stem Cells/cytology
• Adipogenesis
• Mice
• Wnt Signaling Pathway
• Obesity/metabolism
• Obesity/pathology
• Obesity/genetics
• beta Catenin/metabolism
• beta Catenin/genetics
• PPAR gamma/metabolism
• PPAR gamma/genetics
• Mice, Knockout
• Transcription Factors/metabolism
• Transcription Factors/genetics

• HHSN261200800001C NCI NIH HHS
• HHSN261200800001E NCI NIH HHS

• CHD6
• MT: Bioinformatics
• chromatin remodeling
• epigenetics
• histone modifications
• housekeeping genes

• stem cells
• plant sciences

• Hematopoietic Stem Cells/metabolism
• Hematopoietic Stem Cells/cytology
• Cell Differentiation/genetics
• Cell Differentiation/physiology
• Gene Regulatory Networks/genetics
• Stochastic Processes
• Signal Transduction/genetics
• Signal Transduction/physiology
• Reactive Oxygen Species/metabolism
• Humans
• Models, Biological
• Animals
• Systems Biology/methods
• Transcription Factors/genetics
• Transcription Factors/metabolism

• RAB acknowledge the support from UNAM-DGAPA PAPIIT IN211721 “Patrones genéricos y sistémicos de la diferenciación y la proliferación en los nichos de células troncales: Raíz de Arabidopsis thaliana como sistema de estudio teórico-experimental”.

• R01 MH133123 NIMH NIH HHS
• R01 NS113104 NINDS NIH HHS
• R25 GM078441 NIGMS NIH HHS

• Experimental metastasis
• Gene expression
• Housekeeping genes
• RT-qPCR
• Radioisotopes

• Animals
• Genes, Essential
• Female
• Mice
• Gene Expression Regulation, Neoplastic
• Cell Line, Tumor
• Gene Expression Profiling/methods
• Mice, Inbred BALB C
• Neoplasm Metastasis
• Vascular Endothelial Growth Factor A/genetics
• Vascular Endothelial Growth Factor A/metabolism
• Humans
• Breast Neoplasms/genetics
• Breast Neoplasms/pathology
• Breast Neoplasms/metabolism

• RT-qPCR
• gene expression
• leukemia
• reference genes

• Mice
• Animals
• Humans
• Reverse Transcriptase Polymerase Chain Reaction
• Gene Expression Profiling
• Genes, Essential
• Glyceraldehyde-3-Phosphate Dehydrogenases/genetics
• Acute Disease
• Leukemia/genetics
• Gene Expression

• PPSUS Fundação Cearense de Apoio ao Desenvolvimento Científico e Tecnológico

• ECq
• amplification efficiency
• normalization
• real-time PCR
• run-to-run variation

• Swine
• Animals
• Porcine Reproductive and Respiratory Syndrome/diagnosis
• Porcine Reproductive and Respiratory Syndrome/prevention & control
• Real-Time Polymerase Chain Reaction/veterinary
• Antibodies, Viral
• Viral Vaccines
• Porcine respiratory and reproductive syndrome virus/genetics
• Vaccines, Attenuated
• Swine Diseases/diagnosis

• consejo nacional de ciencia y tecnología

• European quail
• RT-qPCR
• endogenous gene
• expression
• expression of stability

• Male
• Animals
• Female
• Gene Expression Profiling/methods
• Chickens/genetics
• Muscle, Skeletal/metabolism
• Software
• Real-Time Polymerase Chain Reaction
• Gene Expression/genetics

• Microtus ochrogaster
• dopamine receptor 1
• dopamine receptor 2
• motivation
• pair bond
• prairie vole
• social attachment
• social loss

• Humans
• Animals
• Male
• Female
• Dopamine/metabolism
• Grassland
• Limbic System/metabolism
• Nucleus Accumbens/metabolism
• Social Behavior
• Arvicolinae/genetics

• R01 MH133123 NIMH NIH HHS
• R01MH133123 NIMH NIH HHS
• National Institute of Mental Health

• EGFR
• Invasiveness
• Mitosis
• Radiotherapy
• Triple-negative breast cancer
• miR-218

• Humans
• MicroRNAs/genetics
• MicroRNAs/metabolism
• Triple Negative Breast Neoplasms/genetics
• Triple Negative Breast Neoplasms/radiotherapy
• Triple Negative Breast Neoplasms/metabolism
• Cell Line, Tumor
• ErbB Receptors/genetics
• ErbB Receptors/metabolism
• Cell Proliferation/genetics
• Cell Movement/genetics
• RNA, Messenger
• Gene Expression Regulation, Neoplastic

• EI211308 Innovative Medizinische Forschung (IMF) Münster
• Universitätsklinikum Münster (8918)

• KIT
• PRAME
• diagnostic tool
• gene expression
• melanoma
• nevi
• noninvasive

• Humans
• RNA
• COVID-19
• Skin Neoplasms/diagnosis
• Skin Neoplasms/genetics
• Skin Neoplasms/surgery
• Melanoma/diagnosis
• Melanoma/genetics
• Melanoma/pathology
• Nevus/diagnosis
• Nevus/genetics
• COVID-19 Testing
• Antigens, Neoplasm

• Raf/MEK/ERK
• glioma
• ketogenic microenvironment

• Humans
• Cell Proliferation
• Glioblastoma/drug therapy
• Glioblastoma/genetics
• Glioma/drug therapy
• Glioma/genetics
• Ketone Bodies
• Mitogen-Activated Protein Kinase Kinases
• Signal Transduction
• Tumor Microenvironment

• ADG
• Artificial rearing
• Feces
• IgG
• Lambs
• Microbiota
• Rumen

• NA Lallemand SAS
• NA Lallemand SAS
• NA Lallemand SAS
• NA Lallemand SAS

• EMT
• Gene expression quantification
• Internal control genes
• Katna1
• Percent relative range
• Rbm17

• Mice
• Rats
• Humans
• Animals
• Sodium Channels/metabolism
• Action Potentials/physiology
• Protein Isoforms/metabolism
• Myocytes, Cardiac/metabolism
• Fibroblast Growth Factors/genetics
• Fibroblast Growth Factors/metabolism

• P30 NS057105 NINDS NIH HHS
• R01 142520 NIH HHS
• R01 HL142520 NHLBI NIH HHS
• UL1 RR024992 NCRR NIH HHS
• R01 HL150637 NHLBI NIH HHS
• UL1 TR002345 NCATS NIH HHS
• National Heart, Lung, and Blood Institute
• National Institutes of Health
• National Center for Research Resources
• Institute for Clinical and Translational Sciences at Washington University
• Hope Center for Neurological Disorders

• ADSC
• Human adipose-derived stem cells
• Hypoxia
• RNAseq
• Reference genes
• qRT-PCR

Small heat shock proteins (sHSPs) are ubiquitous ATP-independent chaperones that contribute to the maintenance of proteome integrity and functionality. Recent evidence suggests that sHSPs are ubiquitously expressed in numerous types of tumors and have been proposed to be implicated in oncogenesis and malignant progression. Heat shock protein family B member 2 (HSPB2) is a member of the sHSPs, which is found to be expressed, among others, in human breast cancer cell lines and constitutes an inhibitor of apical caspase activation in the extrinsic apoptotic pathway. In this study, we investigated the potential prognostic significance of HSPB2 mRNA expression levels in breast cancer, which represents the most frequent malignancy in females and one of the three most common cancer types worldwide. To this end, malignant breast tumors along with paired non-cancerous breast tissue specimens were used. HSPB2 expression levels were quantified in these two cohorts using a sensitive and accurate SYBR green-based quantitative real-time polymerase chain reaction (q-RT-PCR). Extensive biostatistical analyses were performed including Kaplan–Meier and Cox regression survival analyses for the assessment of the results. The significant downregulation of HSPB2 gene expression was revealed in breast tumors compared to their adjacent non-cancerous breast tissues. Notably, high HSPB2 mRNA expression predicts poor disease-free survival and overall survival of breast cancer patients. Multivariate Cox regression analysis revealed that HSPB2 mRNA overexpression is a significant predictor of poor prognosis in breast cancer, independent of other clinicopathological factors. In conclusion, high HSPB2 mRNA expression levels are associated with breast cancer patients’ relapse and poor survival.

• Apoptosis
• Biomarkers, Tumor/genetics
• Breast Neoplasms/pathology
• Female
• HSP27 Heat-Shock Proteins/metabolism
• Heat-Shock Proteins, Small
• Humans
• Neoplasm Recurrence, Local/genetics
• RNA, Messenger/genetics

Concerns have been raised about the use of relative abundance data derived from next generation sequencing as a proxy for absolute abundances. For example, in the differential abundance setting, compositional effects in relative abundance data may give rise to spurious differences (false positives) when considered from the absolute perspective. In practice however, relative abundances are often transformed by renormalization strategies intended to compensate for these effects and the scope of the practical problem remains unclear. We used simulated data to explore the consistency of differential abundance calling on renormalized relative abundances versus absolute abundances and find that, while overall consistency is high, with a median sensitivity (true positive rates) of 0.91 and specificity (1—false positive rates) of 0.89, consistency can be much lower where there is widespread change in the abundance of features across conditions. We confirm these findings on a large number of real data sets drawn from 16S metabarcoding, expression array, bulk RNA-seq, and single-cell RNA-seq experiments, where data sets with the greatest change between experimental conditions are also those with the highest false positive rates. Finally, we evaluate the predictive utility of summary features of relative abundance data themselves. Estimates of sparsity and the prevalence of feature-level change in relative abundance data give reasonable predictions of discrepancy in differential abundance calling in simulated data and can provide useful bounds for worst-case outcomes in real data.

Molecular sequence counting is a near-ubituiqous method for taking “snapshots” of the state of biological systems at the molecular level and is applied to problems as diverse as profiling gene expression and characterizing bacterial community composition. However, concerns exist about the interpretation of these data, given they are relative counts. In particular some feature-level differences between samples may be technical, not biological, stemming from compositional effects. Here, we quantify the accuracy of estimates of sample-sample differences made from relative versus “absolute” molecular count data, using a comprehensive simulation strategy and published experimental data. We find the accuracy of difference estimation is high in at least 50% of simulated and real data sets but that low accuracy outcomes are far from rare. Further, we observe similar numbers of these low accuracy cases when using any of several popular methods for estimating differences in biological count data. Our results support the use of complementary reference measures of absolute abundance (like RNA spike-ins) for normalizing next-generation sequencing data. We briefly validate the use of these reference quantities and of stringent effect size thresholds as strategies for mitigating interpretational problems with relative count data.

• High-Throughput Nucleotide Sequencing
• RNA-Seq

• Human Frontier Science Program
• National Science Foundation
• North Carolina Biotechnology Center
• Duke Forge health data science center

As a powerful and attractive method for detecting gene expression, qRT-PCR has been broadly used in aquaculture research. Understanding the biology of taimen (Hucho taimen) has drawn increasing interest because of its ecological and economic value. Stable reference genes are required for the reliable quantification of gene expression, but such genes have not yet been optimized for taimen. In this study, the stability levels of 10 commonly used candidate reference genes were evaluated using geNorm, NormFinder, BestKeeper, and RefFinder. The expression levels of the 10 genes were detected using 240 samples from 48 experimental groups consisting of 40 individuals treated under four heat-stress conditions (18, 20, 22, and 24 °C) for 24 h and 26 °C for 4, 24, 48, and 72 h. Six tissues (blood, heart, brain, gill, skin, and liver) were collected from each individual. Ribosomal protein S29 (RPS29) and ribosomal protein L19 (RPL19) were the most stable genes among all of the samples, whereas 28S ribosomal RNA (28S rRNA), attachment region binding protein (ARBP), and 18S ribosomal RNA (18S rRNA) were the least stable. These results were verified by an expression analysis of taimen heat-stress genes (heat shock protein 60, hsp60, and heat shock protein 70, hsp70). In conclusion, RPS29 and RPL19 are the optimal reference genes for qRT-PCR analyses of taimen, irrespective of the tissue and experimental conditions. These results allow the reliable study of gene expression in taimen.

• GATA3
• NC9
• Transglutaminase variants
• breast cancer
• drug resistance

• Antibiotics, Antineoplastic/pharmacology
• Breast Neoplasms/drug therapy
• Breast Neoplasms/genetics
• Breast Neoplasms/pathology
• Cell Line, Tumor
• Disease Progression
• Doxorubicin/pharmacology
• Female
• GATA3 Transcription Factor/genetics
• Humans
• MCF-7 Cells
• Protein Glutamine gamma Glutamyltransferase 2/genetics
• Up-Regulation

We have investigated motility in breast cancer cell lines in association with the expression of Transglutaminase type 2 (TG2) as well as upon the administration of Doxorubicin (Dox), an active cytotoxic agent that is employed in chemotherapy. The exposure of MCF-7 cells to the drug increased TG2 levels, triggering epithelial–mesenchymal transition (EMT), thereby supporting cell motility. The effects of Dox on the movement of MCF-7 cells were counteracted by treatment with NC9, a TG2 inhibitor, which induced morphological changes and also reduced the migration of MDA-MB-231 cells exhibiting high levels of TG2. The physical association of TG2 with the cytoskeletal component vimentin appeared pivotal both in drug-treated MCF-7 and in MDA-MB-231 cells and seemed to be independent of the catalytic activity of TG2. NC9 altered the subcellular distribution of TG2 and, consequently, the co-localization of TG2 with vimentin. Furthermore, NC9 induced a nuclear accumulation of TG2 as a prelude to TG2-dependent gene expression modifications. Since enzyme activity can affect both motility and nuclear functions, targeting of this protein could represent a method to improve therapeutic interventions in breast tumors, particularly those to control progression and to limit drug resistance.

• EMT
• NC9
• breast cancer
• motility
• transglutaminase type 2

Breast cancer is the most common cancer among women worldwide. Its molecular receptor marker status and mutational subtypes complicate clinical therapies. Cold atmospheric plasma is a promising adjuvant therapy to selectively combat many cancers, including breast cancer, but not normal tissue; however, the underlying mechanisms remain unexplored. Here, four breast cancer cell lines with different marker status were treated with Canady Helios Cold Plasma™ (CHCP) at various dosages and their differential progress of apoptosis was monitored. Inhibition of cell proliferation, induction of apoptosis, and disruption of the cell cycle were observed. At least 16 histone mRNA types were oxidized and degraded immediately after CHCP treatment by 8-oxoguanine (8-oxoG) modification. The expression of DNA damage response genes was up-regulated 12 h post-treatment, indicating that 8-oxoG modification and degradation of histone mRNA during the early S phase of the cell cycle, rather than DNA damage, is the primary cause of cancer cell death induced by CHCP. Our report demonstrates for the first time that CHCP effectively induces cell death in breast cancer regardless of subtyping, through histone mRNA oxidation and degradation during the early S phase of the cell cycle.

• breast cancer
• cancer treatment
• cold atmospheric plasma
• histone gene
• oxidation of RNA

• Breast Neoplasms/drug therapy
• Breast Neoplasms/metabolism
• Breast Neoplasms/pathology
• Cell Death/drug effects
• Cell Line, Tumor
• Female
• Histones/metabolism
• Humans
• Neoplasm Proteins/metabolism
• Oxidation-Reduction/drug effects
• Plasma Gases/pharmacology
• RNA, Messenger/metabolism
• RNA, Neoplasm/metabolism

Reverse transcription quantitative real-time polymerase chain reaction is one of the important methods to investigate gene expression in cells and tissues. However, if the data cannot be normalized with appropriate reference genes, the results may be unreliable. In this study, we detected the expression of 15 reference genes in three pig cell lines. The results showed that SDHA and ALDOA were the most stable reference genes in 3D4/21 cells. TOP2B, TBP, and PPIA were the most stable reference genes in PK-15 cells. SDHA and ALDOA were the most stable reference genes in IPEC-J2 cells. In addition, each cell line only needs to use two reference genes to standardize the expression of target genes. Taken together, this study provides a reference for different pig cell lines to select reference genes and also provides a theoretical basis for the use of these cell lines in related functional researches.

• RT-PCR
• colon
• gene expression
• mRNA
• unchanged colon mucosa

Long non-coding RNAs are nucleotide molecules that regulate transcription in numerous cellular processes and are related to the occurrence of many diseases, including cancer. In this regard, we recently discovered a polyadenylated long non-coding RNA (named TG2-lncRNA) encoded within the first intron of the Transglutaminase type 2 gene (TGM2), which is related to tumour proliferation in human cancer cell lines. To better characterize this new biological player, we investigated the effects of its suppression in MCF-7 breast cancer cells, using siRNA treatment and RNA-sequencing. In this way, we found modifications in several networks associated to biological functions relevant for tumorigenesis (apoptosis, chronic inflammation, angiogenesis, immunomodulation, cell mobility, and epithelial–mesenchymal transition) that were originally attributed only to Transglutaminase type 2 protein but that could be regulated also by TG2-lncRNA. Moreover, our experiments strongly suggest the ability of TG2-lncRNA to directly interact with important transcription factors, such as RXRα and TP53, paving the way for several regulatory loops that can potentially influence the phenotypic behaviour of MCF-7 cells. These considerations imply the need to further investigate the relative relevance of the TG2 protein itself and/or other gene products as key regulators in the organization of breast cancer program.

• RNA-sequencing
• TGM2
• network
• non-coding RNA
• transglutaminase 2

Normalization of RNA-seq data aims at identifying biological expression differentiation between samples by removing the effects of unwanted confounding factors. Explicitly or implicitly, the justification of normalization requires a set of housekeeping genes. However, the existence of housekeeping genes common for a very large collection of samples, especially under a wide range of conditions, is questionable.

We propose to carry out pairwise normalization with respect to multiple references, selected from representative samples. Then the pairwise intermediates are integrated based on a linear model that adjusts the reference effects. Motivated by the notion of housekeeping genes and their statistical counterparts, we adopt the robust least trimmed squares regression in pairwise normalization. The proposed method (MUREN) is compared with other existing tools on some standard data sets. The goodness of normalization emphasizes on preserving possible asymmetric differentiation, whose biological significance is exemplified by a single cell data of cell cycle. MUREN is implemented as an R package. The code under license GPL-3 is available on the github platform: github.com/hippo-yf/MUREN and on the conda platform: anaconda.org/hippo-yf/r-muren.

MUREN performs the RNA-seq normalization using a two-step statistical regression induced from a general principle. We propose that the densities of pairwise differentiations are used to evaluate the goodness of normalization. MUREN adjusts the mode of differentiation toward zero while preserving the skewness due to biological asymmetric differentiation. Moreover, by robustly integrating pre-normalized counts with respect to multiple references, MUREN is immune to individual outlier samples.

The online version contains supplementary material available at 10.1186/s12859-021-04288-0.

• Asymmetrically regulated transcription profiles (ART)
• Mode
• Multi-reference
• Normalization
• RNA-seq
• Skewness

Mice with a loss of function mutation in Wdpcp were described previously to display severe birth defects in the developing heart, neural tube, and limb buds. Further characterization of the skeletal phenotype of Wdpcp null mice was limited by perinatal lethality.

We utilized Prx1-Cre mice to generate limb bud mesenchyme specific deletion of Wdpcp. These mice recapitulated the appendicular skeletal phenotype of the Wdpcp null mice including polydactyl and limb bud signaling defects. Examination of late stages of limb development demonstrated decreased size of cartilage anlagen, delayed calcification, and abnormal growth plates. Utilizing in vitro assays, we demonstrated that loss of Wdpcp in skeletal progenitors lead to loss of hedgehog signaling responsiveness and associated proliferative response. In vitro chondrogenesis assays showed this loss of hedgehog and proliferative response was associated with decreased expression of early chondrogenic marker N-Cadherin. E14.5 forelimbs demonstrated delayed ossification and expression of osteoblast markers Runx2 and Sp7. P0 growth plates demonstrated loss of hedgehog signaling markers and expansion of the hypertrophic zones of the growth plate. In vitro osteogenesis assays demonstrated decreased osteogenic differentiation of Wdpcp null mesenchymal progenitors in response to hedgehog stimulation.

These findings demonstrate how Wdpcp and associated regulation of the hedgehog signaling pathway plays an important role at multiple stages of skeletal development. Wdpcp is necessary for positive regulation of hedgehog signaling and associated proliferation is key to the initiation of chondrogenesis. At later stages, Wdpcp facilitates the robust hedgehog response necessary for chondrocyte hypertrophy and osteogenic differentiation.

The online version contains supplementary material available at 10.1186/s12861-021-00241-9.

• Chondrogenesis
• Differentiation
• Growth plate
• Hedgehog
• Limb bud
• Osteogenesis
• Proliferation
• Wdpcp

• Reference genes/ beta cells/ diabetes/ RNA-sequencing/ quantitative real-time pcr

• Genomics/methods
• Humans
• Insulin-Secreting Cells/metabolism
• Real-Time Polymerase Chain Reaction
• Reverse Transcriptase Polymerase Chain Reaction

• U01 DK127786 NIDDK NIH HHS

• CRISPR-Cas9 variant editing
• osteoblast and adipocyte metabolism
• pleiotropy of type 2 diabetes and bone mineral density
• regulatory genomics
• variant-to-function study

• Adenylyl Cyclases/genetics
• Adenylyl Cyclases/metabolism
• Adipocytes/cytology
• Adipocytes/metabolism
• Adult
• Bone Density/physiology
• Cell Differentiation
• Cells, Cultured
• Diabetes Mellitus, Type 2/genetics
• Diabetes Mellitus, Type 2/pathology
• Female
• Genetic Loci
• Genome-Wide Association Study
• Haplotypes
• Humans
• Lipid Peroxidation
• Male
• Middle Aged
• Osteoblasts/cytology
• Osteoblasts/metabolism
• Polymorphism, Single Nucleotide
• Risk Factors
• Stem Cells/cytology
• Stem Cells/metabolism
• Sterol Regulatory Element Binding Protein 1/genetics
• Sterol Regulatory Element Binding Protein 1/metabolism

• R24 DK092759 NIDDK NIH HHS
• 203141/Z/16/Z Wellcome Trust
• R01 AR072199 NIAMS NIH HHS
• R01 AR041398 NIAMS NIH HHS
• Wellcome Trust
• MC_U142661184 Medical Research Council

Determining which treatment to provide to men with prostate cancer (PCa) is a major challenge for clinicians. Currently, the clinical risk-stratification for PCa is based on clinico-pathological variables such as Gleason grade, stage and prostate specific antigen (PSA) levels. But transcriptomic data have the potential to enable the development of more precise approaches to predict evolution of the disease. However, high quality RNA sequencing (RNA-seq) datasets along with clinical data with long follow-up allowing discovery of biochemical recurrence (BCR) biomarkers are small and rare. In this study, we propose a machine learning approach that is robust to batch effect and enables the discovery of highly predictive signatures despite using small datasets. Gene expression data were extracted from three RNA-Seq datasets cumulating a total of 171 PCa patients. Data were re-analyzed using a unique pipeline to ensure uniformity. Using a machine learning approach, a total of 14 classifiers were tested with various parameters to identify the best model and gene signature to predict BCR. Using a random forest model, we have identified a signature composed of only three genes (JUN, HES4, PPDPF) predicting BCR with better accuracy [74.2%, balanced error rate (BER) = 27%] than the clinico-pathological variables (69.2%, BER = 32%) currently in use to predict PCa evolution. This score is in the range of the studies that predicted BCR in single-cohort with a higher number of patients. We showed that it is possible to merge and analyze different small and heterogeneous datasets altogether to obtain a better signature than if they were analyzed individually, thus reducing the need for very large cohorts. This study demonstrates the feasibility to regroup different small datasets in one larger to identify a predictive genomic signature that would benefit PCa patients.

• RNA-seq
• biochemical recurrence
• machine learning
• predictive signature
• prostate cancer
• random forest

• Prostate cancer
• biochemical recurrence
• immunotherapy
• leukocyte Ig-Like Receptors
• multi-omics analysis

• Disease Progression
• Humans
• Immunoglobulins
• Leukocytes
• Male
• Neoplasm Recurrence, Local
• Prostatic Neoplasms/genetics

• P50 CA211015 NCI NIH HHS

• Animals
• Coleoptera/genetics
• Coleoptera/growth & development
• Coleoptera/pathogenicity
• Crops, Agricultural/parasitology
• Female
• Gene Expression Profiling/standards
• Gene Expression Regulation, Developmental
• Insect Proteins/genetics
• Male
• Pesticides/pharmacology
• Photoperiod
• Real-Time Polymerase Chain Reaction/standards
• Reference Standards
• Temperature

• Natural Science Foundation of Anhui Province
• National Key Research and Development Program of China
• Anhui Academy of Recycling Economical and Technical Engineering, Chinese Academy of Sciences (CN)

Intracranial aneurysms (IAs) are dangerous because of their potential to rupture. We previously found significant RNA expression differences in circulating neutrophils between patients with and without unruptured IAs and trained machine learning models to predict presence of IA using 40 neutrophil transcriptomes. Here, we aim to develop a predictive model for unruptured IA using neutrophil transcriptomes from a larger population and more robust machine learning methods.

Neutrophil RNA extracted from the blood of 134 patients (55 with IA, 79 IA-free controls) was subjected to next-generation RNA sequencing. In a randomly-selected training cohort (n = 94), the Least Absolute Shrinkage and Selection Operator (LASSO) selected transcripts, from which we constructed prediction models via 4 well-established supervised machine-learning algorithms (K-Nearest Neighbors, Random Forest, and Support Vector Machines with Gaussian and cubic kernels). We tested the models in the remaining samples (n = 40) and assessed model performance by receiver-operating-characteristic (ROC) curves. Real-time quantitative polymerase chain reaction (RT-qPCR) of 9 IA-associated genes was used to verify gene expression in a subset of 49 neutrophil RNA samples. We also examined the potential influence of demographics and comorbidities on model prediction.

Feature selection using LASSO in the training cohort identified 37 IA-associated transcripts. Models trained using these transcripts had a maximum accuracy of 90% in the testing cohort. The testing performance across all methods had an average area under ROC curve (AUC) = 0.97, an improvement over our previous models. The Random Forest model performed best across both training and testing cohorts. RT-qPCR confirmed expression differences in 7 of 9 genes tested. Gene ontology and IPA network analyses performed on the 37 model genes reflected dysregulated inflammation, cell signaling, and apoptosis processes. In our data, demographics and comorbidities did not affect model performance.

We improved upon our previous IA prediction models based on circulating neutrophil transcriptomes by increasing sample size and by implementing LASSO and more robust machine learning methods. Future studies are needed to validate these models in larger cohorts and further investigate effect of covariates.

• Inflammation
• Intracranial aneurysm
• Machine learning
• Neutrophil
• Prediction model
• Transcriptomics

MCF-7 breast cancer cell line is undoubtedly amongst the most extensively studied patient-derived research models, providing pivotal results that have over the decades translated to constantly improving patient care. Many research groups, have previously identified suitable reference genes for qPCR normalization in MCF-7 cell line. However, over the course of identification of suitable reference genes, a comparative analysis comprising these genes together in a single study has not been reported. Furthermore, the expression dynamics of these reference genes within sub-clones cultured over multiple passages (p) has attracted limited attention from research groups. Therefore, we investigated the expression dynamics of 12 previously suggested reference genes within two sub-clones (culture A1 and A2) cultured identically over multiple passages. Additionally, the effect of nutrient stress on reference gene expression was examined to postulate an evidence-based recommendation of the least variable reference genes that could be employed in future gene expression studies.

The analysis revealed the presence of differential reference gene expression within the sub-clones of MCF-7. In culture A1, GAPDH-CCSER2 were identified as the least variable reference genes while for culture A2, GAPDH-RNA28S were identified. However, upon validation using genes of interest, both these pairs were found to be unsuitable control pairs. Normalization of AURKA and KRT19 with triplet pair GAPDH-CCSER2-PCBP1 yielded successful results. The triplet also proved its capability to handle variations arising from nutrient stress.

The variance in expression behavior amongst sub-clones highlights the potential need for exercising caution while selecting reference genes for MCF-7. GAPDH-CCSER2-PCBP1 triplet offers a reliable alternative to otherwise traditionally used internal controls for optimizing intra- and inter-assay gene expression differences. Furthermore, we suggest avoiding the use of ACTB, GAPDH and PGK1 as single internal controls.

• Breast cancer cell line
• Culture media
• Gene expression
• MCF-7
• Nutrient stress
• RT-qPCR
• Reference genes
• Sub-clones

• cancer testis antigen
• hepatocelluar cancer
• tumor immunotherapy

To evaluate the gene expression of peroxisome proliferator activated receptors gamma (PPARG) in colorectal tumors and to correlate this data with clinical variables of the patients.

We analyzed the gene expression of PPARG in 50 samples of colorectal tumors using real-time reverse transcription polymerase chain reaction, and 20 adjacent normal tissue samples as control. The results of these quantifications were correlated with the respective patients’ medical records’ clinical information.

PPARG expression was not different in the tumor tissue compared to the control tissue. Patients older than 60 years, histological type with mucinous differentiation, more advanced staging at the time of diagnosis, and patients who evolved with recurrence of the disease or death did not present higher PPARG expression.

Expression of PPARGD was not associated with worse prognosis.

• alligator weed flea beetle
• biomarker
• heat shock protein
• heat tolerance

• Acanthaceae
• Amaranthaceae
• Animals
• Coleoptera/genetics
• Heat-Shock Proteins/genetics
• Thermotolerance