Correlations between RNA and protein expression profiles in 23 human cell lines

SNCA and TPPP transcripts increase in oligodendroglial cytoplasmic inclusions in multiple system atrophy

Multiple system atrophy (MSA) is characterized by glial cytoplasmic inclusions (GCIs) containing aggregated α-synuclein (α-syn) in oligodendrocytes. The origin of α-syn accumulation in GCIs is unclear, in particular whether abnormal α-syn aggregates result from the abnormal elevation of endogenous α-syn expression in MSA or ingested from the neuronal source. Tubulin polymerization promoting protein (TPPP) has been reported to play a crucial role in developing GCI pathology. Here, the total cell body, nucleus, and cytoplasmic area density of SNCA and TPPP transcripts in neurons and oligodendrocytes with and without various α-syn pathologies in the pontine base in autopsy cases of MSA (n = 4) and controls (n = 2) were evaluated using RNAscope with immunofluorescence. Single-nucleus RNA-sequencing data for TPPP was evaluated using control frontal cortex (n = 3). SNCA and TPPP transcripts were present in the nucleus and cytoplasm of oligodendrocytes in both controls and diseased, with higher area density in GCIs and glial nuclear inclusions in MSA. Area densities of SNCA and TPPP transcripts were lower in neurons showing cytoplasmic inclusions in MSA. Indeed, TPPP transcripts were unexpectedly found in neurons, while the anti-TPPP antibody failed to detect immunoreactivity. Single-nucleus RNA-sequencing revealed significant TPPP transcript expression predominantly in oligodendrocytes, but also in excitatory and inhibitory neurons. This study addressed the unclear origin of accumulated α-syn in GCIs, proposing that the elevation of SNCA transcripts may supply templates for misfolded α-syn. In addition, the parallel behavior of TPPP and SNCA transcripts in GCI development highlights their potential synergistic contribution to inclusion formation. In conclusion, this study advances our understanding of MSA pathogenesis, offers insights into the dynamics of SNCA and TPPP transcripts in inclusion formation, and proposes regulating their transcripts for future molecular therapy to MSA.

Implementation of a High-Accuracy Targeted Gene Expression Panel for Clinical Care

This study describes the validation of a clinical RNA expression panel with evaluation of concordance between gene copy gain by a next-generation sequencing (NGS) assay and high gene expression by an RNA expression panel. The RNA Salah Targeted Expression Panel (RNA STEP) was designed with input from oncologists to include 204 genes with utility for clinical trial prescreening and therapy selection. RNA STEP was validated with the nanoString platform using remnant formalin-fixed, paraffin-embedded-derived RNA from 102 patients previously tested with a validated clinical NGS panel. The repeatability, reproducibility, and concordance of RNA STEP results with NGS results were evaluated. RNA STEP demonstrated high repeatability and reproducibility, with excellent correlation (r > 0.97, P < 0.0001) for all comparisons. Comparison of RNA STEP high gene expression (log2 ratio ≥ 2) versus NGS DNA-based gene copy number gain (copies ≥ 5) for 38 mutually covered genes revealed an accuracy of 93.0% with a positive percentage agreement of 69.4% and negative percentage agreement of 93.8%. Moderate correlation was observed between platforms (r = 0.53, P < 0.0001). Concordance between high gene expression and gene copy number gain varied by specific gene, and some genes had higher accuracy between assays. Clinical implementation of RNA STEP provides gene expression data complementary to NGS and offers a tool for prescreening patients for clinical trials.

Gastric digestion of the sweet-tasting plant protein thaumatin releases bitter peptides that reduce H. pylori induced pro-inflammatory IL-17A release via the TAS2R16 bitter taste receptor

About half of the world's population is infected with the bacterium Helicobacter pylori. For colonization, the bacterium neutralizes the low gastric pH and recruits immune cells to the stomach. The immune cells secrete cytokines, i.e., the pro-inflammatory IL-17A, which directly or indirectly damage surface epithelial cells. Since (I) dietary proteins are known to be digested into bitter tasting peptides in the gastric lumen, and (II) bitter tasting compounds have been demonstrated to reduce the release of pro-inflammatory cytokines through functional involvement of bitter taste receptors (TAS2Rs), we hypothesized that the sweet-tasting plant protein thaumatin would be cleaved into anti-inflammatory bitter peptides during gastric digestion. Using immortalized human parietal cells (HGT-1 cells), we demonstrated a bitter taste receptor TAS2R16-dependent reduction of a H. pylori-evoked IL-17A release by up to 89.7 ± 21.9% (p ≤ 0.01). Functional involvement of TAS2R16 was demonstrated by the study of specific antagonists and siRNA knock-down experiments.

Comprehensive analysis of the endothelin system in the kidneys of mice, rats, and humans

The intrarenal endothelin (ET) system is an established moderator of kidney physiology and mechanistic contributor to the pathophysiology and progression of chronic kidney disease in humans and rodents. The aim of the present study was to characterize ET system by combining single cell RNA sequencing (scRNA-seq) data with immunolocalization in human and rodent kidneys of both sexes. Using publicly available scRNA-seq data, we assessed sex and kidney disease status (human), age and sex (rats), and diurnal expression (mice) on the kidney ET system expression. In normal human biopsies of both sexes and in rodent kidney samples, the endothelin-converting enzyme-1 (ECE1) and ET-1 were prominent in the glomeruli and endothelium. These data agreed with the scRNA-seq data from these three species, with ECE1/Ece1 mRNA enriched in the endothelium. However, the EDN1/Edn1 gene (encodes ET-1) was rarely detected, even though it was immunolocalized within the kidneys, and plasma and urinary ET-1 excretion are easily measured. Within each species, there were some sex-specific differences. For example, in kidney biopsies from living donors, men had a greater glomerular endothelial cell endothelin receptor B (Ednrb) compared with women. In mice, females had greater kidney endothelial cell Ednrb than male mice. As commercially available antibodies did not work in all species, and RNA expression did not always correlate with protein levels, multiple approaches should be considered to maintain required rigor and reproducibility of the pre- and clinical studies evaluating the intrarenal ET system.

Proteome-wide association study using cis and trans variants and applied to blood cell and lipid-related traits in the Women's Health Initiative study

In most Proteome-Wide Association Studies (PWAS), variants near the protein-coding gene (±1 Mb), also known as cis single nucleotide polymorphisms (SNPs), are used to predict protein levels, which are then tested for association with phenotypes. However, proteins can be regulated through variants outside of the cis region. An intermediate GWAS step to identify protein quantitative trait loci (pQTL) allows for the inclusion of trans SNPs outside the cis region in protein-level prediction models. Here, we assess the prediction of 540 proteins in 1002 individuals from the Women's Health Initiative (WHI), split equally into a GWAS set, an elastic net training set, and a testing set. We compared the testing r2 between measured and predicted protein levels using this proposed approach, to the testing r2 using only cis SNPs. The two methods usually resulted in similar testing r2, but some proteins showed a significant increase in testing r2 with our method. For example, for cartilage acidic protein 1, the testing r2 increased from 0.101 to 0.351. We also demonstrate reproducible findings for predicted protein association with lipid and blood cell traits in WHI participants without proteomics data and in UK Biobank utilizing our PWAS weights.

ZCCHC17 knockdown phenocopies Alzheimer's disease-related loss of synaptic proteins and hyperexcitability

ZCCHC17 is a master regulator of synaptic gene expression and has recently been shown to play a role in splicing of neuronal mRNA. We previously showed that ZCCHC17 protein declines in Alzheimer's disease (AD) brain tissue before there is significant gliosis and neuronal loss, that ZCCHC17 loss partially replicates observed splicing abnormalities in AD brain tissue, and that maintenance of ZCCHC17 levels is predicted to support cognitive resilience in AD. Here, we assessed the functional consequences of reduced ZCCHC17 expression in primary cortical neuronal cultures using siRNA knockdown. Consistent with its previously identified role in synaptic gene expression, loss of ZCCHC17 led to loss of synaptic protein expression. Patch recording of neurons shows that ZCCHC17 loss significantly disrupted the excitation/inhibition balance of neurotransmission, and favored excitatory-dominant synaptic activity as measured by an increase in spontaneous excitatory post synaptic currents and action potential firing rate, and a decrease in spontaneous inhibitory post synaptic currents. These findings are consistent with the hyperexcitable phenotype seen in AD animal models and in patients. We are the first to assess the functional consequences of ZCCHC17 knockdown in neurons and conclude that ZCCHC17 loss partially phenocopies AD-related loss of synaptic proteins and hyperexcitability.

Identification of novel biomarkers to distinguish clear cell and non-clear cell renal cell carcinoma using bioinformatics and machine learning

Renal cell carcinoma (RCC), accounting for 90% of all kidney cancer, is categorized into clear cell RCC (ccRCC) and non-clear cell RCC (non-ccRCC) for treatment based on the current NCCN Guidelines. Thus, the classification will be associated with therapeutic implications. This study aims to identify novel biomarkers to differentiate ccRCC from non-ccRCC using bioinformatics and machine learning. The gene expression profiles of ccRCC and non-ccRCC subtypes (including papillary RCC (pRCC) and chromophobe RCC (chRCC)), were obtained from TCGA. Differential expression genes (DEGs) were identified, and specific DEGs for ccRCC and non-ccRCC were explored using a Venn diagram. Gene Ontology and pathway enrichment analysis were performed using DAVID. The top ten expressed genes in ccRCC were then selected for machine learning analysis. Feature selection was operated to identify a minimum highly effective gene set for constructing a predictive model. The expression of best-performing gene set was validated on tissue samples from RCC patients using immunohistochemistry techniques. Subsequently, machine learning models for diagnosing RCC were developed using H-scores. There were 910, 415, and 835 genes significantly specific for DEGs in ccRCC, pRCC, and chRCC, respectively. Specific DEGs in ccRCC enriched in PD-1 signaling, immune system, and cytokine signaling in the immune system, whereas TCA cycle and respiratory, signaling by insulin receptor, and metabolism were enriched in chRCC. Feature selection based on Decision Tree Classifier revealed that the model with two genes, including NDUFA4L2 and DAT, had an accuracy of 98.89%. Supervised classification models based on H-score of NDUFA4L2, and DAT revealed that Decision Tree models showed the best performance with 82% accuracy and 0.9 AUC. NDUFA4L2 expression was associated with lymphovascular invasion, pathologic stage and pT stage in ccRCC. Using integrated bioinformatics and machine learning analysis, NDUFA4L2 and DAT were identified as novel biomarkers to differential diagnosis ccRCC from non-ccRCC.

Multi-omics profiling reveals dysregulated ribosome biogenesis and impaired cell proliferation following knockout of CDR2L

BACKGROUND

Cerebellar degeneration-related (CDR) proteins are associated with paraneoplastic cerebellar degeneration (PCD) - a rare, neurodegenerative disease caused by tumour-induced autoimmunity against neural antigens resulting in degeneration of Purkinje neurons in the cerebellum. The pathogenesis of PCD is unknown, in large part due to our limited understanding of the functions of CDR proteins. To this end, we performed an extensive, multi-omics analysis of CDR-knockout cells focusing on the CDR2L protein, to gain a deeper understanding of the properties of the CDR proteins in ovarian cancer.

METHODS

Ovarian cancer cell lines lacking either CDR1, CDR2, or CDR2L were analysed using RNA sequencing and mass spectrometry-based proteomics to assess changes to the transcriptome, proteome and secretome in the absence of these proteins.

RESULTS

For each knockout cell line, we identified sets of differentially expressed genes and proteins. CDR2L-knockout cells displayed a distinct expression profile compared to CDR1- and CDR2-knockout cells. Knockout of CDR2L caused dysregulation of genes involved in ribosome biogenesis, protein translation, and cell cycle progression, ultimately causing impaired cell proliferation in vitro. Several of these genes showed a concurrent upregulation at the transcript level and downregulation at the protein level.

CONCLUSIONS

Our study provides the first integrative multi-omics analysis of the impact of knockout of the CDR genes, providing both new insights into the biological properties of the CDR proteins in ovarian cancer, and a valuable resource for future investigations into the CDR proteins.

Discrepant Phenotyping of Monocytes Based on CX3CR1 and CCR2 Using Fluorescent Reporters and Antibodies

Monocytes, as well as downstream macrophages and dendritic cells, are essential players in the immune system, fulfilling key roles in homeostasis as well as in inflammatory conditions. Conventionally, driven by studies on reporter models, mouse monocytes are categorized into a classical and a non-classical subset based on their inversely correlated surface expression of Ly6C/CCR2 and CX3CR1. Here, we aimed to challenge this concept by antibody staining and reporter mouse models. Therefore, we took advantage of Cx3cr1GFP and Ccr2RFP reporter mice, in which the respective gene was replaced by a fluorescent reporter protein gene. We analyzed the expression of CX3CR1 and CCR2 by flow cytometry using several validated fluorochrome-coupled antibodies and compared them with the reporter gene signal in these reporter mouse strains. Although we were able to validate the specificity of the fluorochrome-coupled flow cytometry antibodies, mouse Ly6Chigh classical and Ly6Clow non-classical monocytes showed no differences in CX3CR1 expression levels in the peripheral blood and spleen when stained with these antibodies. On the contrary, in Cx3cr1GFP reporter mice, we were able to reproduce the inverse correlation of the CX3CR1 reporter gene signal and Ly6C surface expression. Furthermore, differential CCR2 surface expression correlating with the expression of Ly6C was observed by antibody staining, but not in Ccr2RFP reporter mice. In conclusion, our data suggest that phenotyping strategies for mouse monocyte subsets should be carefully selected. In accordance with the literature, the suitability of CX3CR1 antibody staining is limited, whereas for CCR2, caution should be applied when using reporter mice.

Multiomics analysis identifies oxidative phosphorylation as a cancer vulnerability arising from myristoylation inhibition

BACKGROUND

In humans, two ubiquitously expressed N-myristoyltransferases, NMT1 and NMT2, catalyze myristate transfer to proteins to facilitate membrane targeting and signaling. We investigated the expression of NMTs in numerous cancers and found that NMT2 levels are dysregulated by epigenetic suppression, particularly so in hematologic malignancies. This suggests that pharmacological inhibition of the remaining NMT1 could allow for the selective killing of these cells, sparing normal cells with both NMTs.

METHODS AND RESULTS

Transcriptomic analysis of 1200 NMT inhibitor (NMTI)-treated cancer cell lines revealed that NMTI sensitivity relates not only to NMT2 loss or NMT1 dependency, but also correlates with a myristoylation inhibition sensitivity signature comprising 54 genes (MISS-54) enriched in hematologic cancers as well as testis, brain, lung, ovary, and colon cancers. Because non-myristoylated proteins are degraded by a glycine-specific N-degron, differential proteomics revealed the major impact of abrogating NMT1 genetically using CRISPR/Cas9 in cancer cells was surprisingly to reduce mitochondrial respiratory complex I proteins rather than cell signaling proteins, some of which were also reduced, albeit to a lesser extent. Cancer cell treatments with the first-in-class NMTI PCLX-001 (zelenirstat), which is undergoing human phase 1/2a trials in advanced lymphoma and solid tumors, recapitulated these effects. The most downregulated myristoylated mitochondrial protein was NDUFAF4, a complex I assembly factor. Knockout of NDUFAF4 or in vitro cell treatment with zelenirstat resulted in loss of complex I, oxidative phosphorylation and respiration, which impacted metabolomes.

CONCLUSIONS

Targeting of both, oxidative phosphorylation and cell signaling partly explains the lethal effects of zelenirstat in select cancer types. While the prognostic value of the sensitivity score MISS-54 remains to be validated in patients, our findings continue to warrant the clinical development of zelenirstat as cancer treatment.

Transcriptomic and Proteomic Spatial Profiling of Pediatric and Adult Diffuse Midline Glioma H3 K27-Altered, Reveals Region Specific Differences and Limited Overlap between mRNA and Protein

Diffuse midline glioma, H3 K27 -altered (DMG-Alt) are highly aggressive malignancies of the central nervous system (CNS) that primarily affect the pediatric population. Large scale spatial transcriptomic studies have implicated that tumor microenvironmental landscape plays an important role in determining the phenotypic differences in tumor presentation and clinical course, however, data connecting overall transcriptomic changes to the protein level is lacking. The NanoString GeoMx™ Digital Spatial Profiler platform was used to determine the spatial transcriptomic and proteomic landscape in a cohort of both pediatric and adult H3 K27 -altered DMG biopsy samples. Three fluorescently labeled antibodies targeting immune cells (CD45), epithelial cells (PanCK), tumor cells ( H3 K27M ) and a nucleic acid stain (SYTO-13) were used to establish regions of interest (ROI) for genomic and proteomic analysis. We found genetic alterations within the tumor which can be delineated across patient age and spatial location. We show that the H3 K27M mutation itself has a profound impact on tumor cells transcriptomics and interestingly we found limited fidelity between overall transcriptome and proteome. Our data also validate the previously described OPC like precursor signature at the proteomic level and reveal a special shift in the signature based on the local TME composition.

Sample-Wise and Gene-Wise Comparisons Confirm a Greater Similarity of RNA and Protein Expression Data at the Level of Molecular Pathways and Suggest an Approach for the Data Quality Check in High-Throughput Expression Databases

Identification of genes and molecular pathways with congruent profiles in the proteomic and transcriptomic datasets may result in the discovery of promising transcriptomic biomarkers that would be more relevant to phenotypic changes. In this study, we conducted comparative analysis of 943 paired RNA and proteomic profiles obtained for the same samples of seven human cancer types from The Cancer Genome Atlas (TCGA) and NCI Clinical Proteomic Tumor Analysis Consortium (CPTAC) [two major open human cancer proteomic and transcriptomic databases] that included 15,112 protein-coding genes and 1611 molecular pathways. Overall, our findings demonstrated statistically significant improvement of the congruence between RNA and proteomic profiles when performing analysis at the level of molecular pathways rather than at the level of individual gene products. Transition to the molecular pathway level of data analysis increased the correlation to 0.19-0.57 (Pearson) and 0.14-057 (Spearman), or 2-3-fold for some cancer types. Evaluating the gain of the correlation upon transition to the data analysis the pathway level can be used to refine the omics data by identifying outliers that can be excluded from the comparison of RNA and proteomic profiles. We suggest using sample- and gene-wise correlations for individual genes and molecular pathways as a measure of quality of RNA/protein paired molecular data. We also provide a database of human genes, molecular pathways, and samples related to the correlation between RNA and protein products to facilitate an exploration of new cancer transcriptomic biomarkers and molecular mechanisms at different levels of human gene expression.

A topographical atlas of α-synuclein dosage and cell type-specific expression in adult mouse brain and peripheral organs

Parkinson's disease (PD) is the second most common neurodegenerative disease worldwide and presents pathologically with Lewy pathology and dopaminergic neurodegeneration. Lewy pathology contains aggregated α-synuclein (αSyn), a protein encoded by the SNCA gene which is also mutated or duplicated in a subset of familial PD cases. Due to its predominant presynaptic localization, immunostaining for the protein results in a diffuse reactivity pattern, providing little insight into the types of cells expressing αSyn. As a result, insight into αSyn expression-driven cellular vulnerability has been difficult to ascertain. Using a combination of knock-in mice that target αSyn to the nucleus (SncaNLS) and in situ hybridization of Snca in wild-type mice, we systematically mapped the topography and cell types expressing αSyn in the mouse brain, spinal cord, retina, and gut. We find a high degree of correlation between αSyn protein and RNA levels and further identify cell types with low and high αSyn content. We also find high αSyn expression in neurons, particularly those involved in PD, and to a lower extent in non-neuronal cell types, notably those of oligodendrocyte lineage, which are relevant to multiple system atrophy pathogenesis. Surprisingly, we also found that αSyn is relatively absent from select neuron types, e.g., ChAT-positive motor neurons, whereas enteric neurons universally express some degree of αSyn. Together, this integrated atlas provides insight into the cellular topography of αSyn, and provides a quantitative map to test hypotheses about the role of αSyn in network vulnerability, and thus serves investigations into PD pathogenesis and other α-synucleinopathies.

Claudin-2 upregulation enhances intestinal permeability, immune activation, dysbiosis, and mortality in sepsis

Intestinal epithelial expression of the tight junction protein claudin-2, which forms paracellular cation and water channels, is precisely regulated during development and in disease. Here, we show that small intestinal epithelial claudin-2 expression is selectively upregulated in septic patients. Similar changes occurred in septic mice, where claudin-2 upregulation coincided with increased flux across the paracellular pore pathway. In order to define the significance of these changes, sepsis was induced in claudin-2 knockout (KO) and wild-type (WT) mice. Sepsis-induced increases in pore pathway permeability were prevented by claudin-2 KO. Moreover, claudin-2 deletion reduced interleukin-17 production and T cell activation and limited intestinal damage. These effects were associated with reduced numbers of neutrophils, macrophages, dendritic cells, and bacteria within the peritoneal fluid of septic claudin-2 KO mice. Most strikingly, claudin-2 deletion dramatically enhanced survival in sepsis. Finally, the microbial changes induced by sepsis were less pathogenic in claudin-2 KO mice as survival of healthy WT mice injected with cecal slurry collected from WT mice 24 h after sepsis was far worse than that of healthy WT mice injected with cecal slurry collected from claudin-2 KO mice 24 h after sepsis. Claudin-2 upregulation and increased pore pathway permeability are, therefore, key intermediates that contribute to development of dysbiosis, intestinal damage, inflammation, ineffective pathogen control, and increased mortality in sepsis. The striking impact of claudin-2 deletion on progression of the lethal cascade activated during sepsis suggests that claudin-2 may be an attractive therapeutic target in septic patients.

Molecular Behavior of α-Synuclein Is Associated with Membrane Transport, Lipid Metabolism, and Ubiquitin-Proteasome Pathways in Lewy Body Disease

Lewy body diseases (LBDs) feature α-synuclein (α-syn)-containing Lewy bodies, with misfolded α-syn potentially propagating as seeds. Using a seeding amplification assay, we previously reported distinct α-syn seeding in LBD cases based on the area under seeding curves. This study revealed that LBD cases showing different α-syn seeding kinetics have distinct proteomics profiles, emphasizing disruptions in mitochondria and lipid metabolism in high-seeder cases. Though the mechanisms underlying LBD development are intricate, the factors influencing α-syn seeding activity remain elusive. To address this and complement our previous findings, we conducted targeted transcriptome analyses in the substantia nigra using the nanoString nCounter assay together with histopathological evaluations in high (n = 4) and low (n = 3) nigral α-syn seeders. Neuropathological findings (particularly the substantia nigra) were consistent between these groups and were characterized by neocortical LBD associated with Alzheimer's disease neuropathologic change. Among the 1811 genes assessed, we identified the top 20 upregulated and downregulated genes and pathways in α-syn high seeders compared with low seeders. Notably, alterations were observed in genes and pathways related to transmembrane transporters, lipid metabolism, and the ubiquitin-proteasome system in the high α-syn seeders. In conclusion, our findings suggest that the molecular behavior of α-syn is the driving force in the neurodegenerative process affecting the substantia nigra through these identified pathways. These insights highlight their potential as therapeutic targets for attenuating LBD progression.

Proteomics-based clustering of lung adenocarcinoma identifies three subtypes with significantly different clinical and molecular features

BACKGROUND

Lung adenocarcinoma (LUAD) is a predominant subtype of lung cancer. Although molecular classification of LUAD has been widely explored, proteomics-based subtyping of LUAD remains scarce.

METHODS

We proposed a subtyping method for LUAD based on the expression profiles of 500 proteins with the largest expression variability across LUAD. Furthermore, we comprehensively compared molecular and clinical features among the LUAD subtypes.

RESULTS

Consensus clustering identified three subtypes of LUAD, namely MtE, DrE, and StE. We demonstrated this subtyping method to be reproducible by analyzing two independent LUAD cohorts. MtE was characterized by high enrichment of metabolic pathways, high EGFR mutation rate, low stemness, proliferation, invasion, metastasis and inflammation signatures, favorable prognosis; DrE was characterized by high enrichment of DNA repair pathways, high TP53 mutation rate, and high levels of genomic instability, stemness, proliferation, and intratumor heterogeneity (ITH); and StE was characterized by high enrichment of stroma-related pathways, high KRAS mutation rate, and low levels of genomic instability.

CONCLUSIONS

The proteomics-based clustering analysis identified three LUAD subtypes with significantly different molecular and clinical properties. The novel subtyping method offers new perspectives on the cancer biology and holds promise in improving the clinical management of LUAD.

In-Depth Proteomic Map of Innate Lymphoid Cells from Healthy Human Skin and Blood

Innate lymphoid cells (ILCs) are essential players in the skin-associated immune system, nevertheless little is known about their proteomes and proteomic diversity. In this study, we describe about 6,600 proteins constitutively expressed by ILC2s and ILC3s from healthy human skin and blood using state-of-the-art proteomics. Although the vast majority of proteins was expressed by both ILC subsets and in both compartments, the skin ILC2s and ILC3s were more distinct than their counterparts in blood. Only skin ILC3s expressed uniquely detected proteins. Our in-depth proteomic dataset allowed us to define the cluster of differentiation marker profiles of the ILC subsets, explore distribution and abundance of proteins known to have immunological functions, as well as identify subset-specific proteins that have not previously been implicated in ILC biology. Taken together, our analyses substantially expand understanding of the protein expression signatures of ILC subsets. Going forward, these proteomic datasets will serve as valuable resources for future studies of ILC biology.

Multiscale protein networks systematically identify aberrant protein interactions and oncogenic regulators in seven cancer types

Global proteomic data generated by advanced mass spectrometry (MS) technologies can help bridge the gap between genome/transcriptome and functions and hold great potential in elucidating unbiased functional models of pro-tumorigenic pathways. To this end, we collected the high-throughput, whole-genome MS data and conducted integrative proteomic network analyses of 687 cases across 7 cancer types including breast carcinoma (115 tumor samples; 10,438 genes), clear cell renal carcinoma (100 tumor samples; 9,910 genes), colorectal cancer (91 tumor samples; 7,362 genes), hepatocellular carcinoma (101 tumor samples; 6,478 genes), lung adenocarcinoma (104 tumor samples; 10,967 genes), stomach adenocarcinoma (80 tumor samples; 9,268 genes), and uterine corpus endometrial carcinoma UCEC (96 tumor samples; 10,768 genes). Through the protein co-expression network analysis, we identified co-expressed protein modules enriched for differentially expressed proteins in tumor as disease-associated pathways. Comparison with the respective transcriptome network models revealed proteome-specific cancer subnetworks associated with heme metabolism, DNA repair, spliceosome, oxidative phosphorylation and several oncogenic signaling pathways. Cross-cancer comparison identified highly preserved protein modules showing robust pan-cancer interactions and identified endoplasmic reticulum-associated degradation (ERAD) and N-acetyltransferase activity as the central functional axes. We further utilized these network models to predict pan-cancer protein regulators of disease-associated pathways. The top predicted pan-cancer regulators including RSL1D1, DDX21 and SMC2, were experimentally validated in lung, colon, breast cancer and fetal kidney cells. In summary, this study has developed interpretable network models of cancer proteomes, showcasing their potential in unveiling novel oncogenic regulators, elucidating underlying mechanisms, and identifying new therapeutic targets.

Impact of Rehydration Following Systemic Dehydration on Vocal Fold Gene Expression

OBJECTIVE

Biological data on the beneficial effects of vocal fold rehydration are lacking. This study aimed to examine the effects of acute systemic dehydration on vocal fold gene expression and determine whether rehydration would reverse these changes.

METHODS

Male New Zealand White rabbits (N = 24, n = 8/group) provided the animal model. Systemic dehydration was induced by 5 days of water volume restriction. Rehydration was provided by ad-lib water for 3 days following dehydration. Euhydrated rabbits were used as the control group. Vocal fold tissue was dissected. Seventeen genes were selected based on physiological function and role in supporting vocal fold structure, oxidative stress, hemodynamics, and extracellular matrix turnover. Relative gene expression was assessed by RT-qPCR.

RESULTS

Rehydration following systemic dehydration can modulate gene expression, with expression patterns suggesting that rehydration reverses dehydration-induced changes in over half of the tested genes. CLIC5 (chloride intracellular channel 5) and EFEMP1 (EGF containing fibulin extracellular matrix protein 1) genes were significantly upregulated in the dehydration group compared with the euhydrated control. A1BG (alpha-1B-glycoprotein) and IL1RAP (interleukin 1 receptor accessory protein) were downregulated by rehydration compared with the dehydration group.

CONCLUSION

This study provides molecular evidence for a transcriptional response to rehydration following acute systemic dehydration in the vocal folds. These data are the first to study gene expression following realistic dehydration and rehydration paradigms and provide biological data to support clinical recommendations to increase water intake after acute dehydration.

LEVEL OF EVIDENCE

NA Laryngoscope, 133:3499-3505, 2023.

Neuronal SNCA transcription during Lewy body formation

Misfolded α-synuclein (α-syn) is believed to contribute to neurodegeneration in Lewy body disease (LBD) based on considerable evidence including a gene-dosage effect observed in relation to point mutations and multiplication of SNCA in familial Parkinson's disease. A contradictory concept proposes early loss of the physiological α-syn as the major driver of neurodegeneration. There is a paucity of data on SNCA transcripts in various α-syn immunoreactive cytopathologies. Here, the total cell body, nuclear, and cytoplasmic area density of SNCA transcripts in neurons without and with various α-syn immunoreactive cytopathologies in the substantia nigra and amygdala in autopsy cases of LBD (n = 5) were evaluated using RNAscope combined with immunofluorescence for disease-associated α-syn. Single-nucleus RNA sequencing was performed to elucidate cell-type specific SNCA expression in non-diseased frontal cortex (n = 3). SNCA transcripts were observed in the neuronal nucleus and cytoplasm in neurons without α-syn, those containing punctate α-syn immunoreactivity, irregular-shaped compact inclusion, and brainstem-type and cortical-type LBs. However, SNCA transcripts were only rarely found in the α-syn immunoreactive LB areas. The total cell body SNCA transcript area densities in neurons with punctate α-syn immunoreactivity were preserved but were significantly reduced in neurons with compact α-syn inclusions both in the substantia nigra and amygdala. This reduction was also observed in the cytoplasm but not in the nucleus. Only single SNCA transcripts were detected in astrocytes with or without disease-associated α-syn immunoreactivity in the amygdala. Single-nucleus RNA sequencing revealed that excitatory and inhibitory neurons, oligodendrocyte progenitor cells, oligodendrocytes, and homeostatic microglia expressed SNCA transcripts, while expression was largely absent in astrocytes and microglia. The preserved cellular SNCA expression in the more abundant non-Lewy body type α-syn cytopathologies might provide a pool for local protein production that can aggregate and serve as a seed for misfolded α-syn. Successful segregation of disease-associated α-syn is associated with the exhaustion of SNCA production in the terminal cytopathology, the Lewy body. Our observations inform therapy development focusing on targeting SNCA transcription in LBD.

Adjustment of p-value expression to ontology using machine learning for genetic prediction, prioritization, interaction, and its validation in glomerular disease

The results of gene expression analysis based on p-value can be extracted and sorted by their absolute statistical significance and then applied to multiple similarity scores of their gene ontology (GO) terms to promote the combination and adjustment of these scores as essential predictive tasks for understanding biological/clinical pathways. The latter allows the possibility to assess whether certain aspects of gene function may be associated with other varieties of genes, to evaluate regulation, and to link them into networks that prioritize candidate genes for classification by applying machine learning techniques. We then detect significant genetic interactions based on our algorithm to validate the results. Finally, based on specifically selected tissues according to their normalized gene expression and frequencies of occurrence from their different biological and clinical inputs, a reported classification of genes under the subject category has validated the abstract (glomerular diseases) as a case study.

Integrative analysis identifies two molecular and clinical subsets in Luminal B breast cancer

Comprehensive multiplatform analysis of Luminal B breast cancer (LBBC) specimens identifies two molecularly distinct, clinically relevant subtypes: Cluster A associated with cell cycle and metabolic signaling and Cluster B with predominant epithelial mesenchymal transition (EMT) and immune response pathways. Whole-exome sequencing identified significantly mutated genes including TP53, PIK3CA, ERBB2, and GATA3 with recurrent somatic mutations. Alterations in DNA methylation or transcriptomic regulation in genes (FN1, ESR1, CCND1, and YAP1) result in tumor microenvironment reprogramming. Integrated analysis revealed enriched biological pathways and unexplored druggable targets (cancer-testis antigens, metabolic enzymes, kinases, and transcription regulators). A systematic comparison between mRNA and protein displayed emerging expression patterns of key therapeutic targets (CD274, YAP1, AKT1, and CDH1). A potential ceRNA network was developed with a significantly different prognosis between the two subtypes. This integrated analysis reveals a complex molecular landscape of LBBC and provides the utility of targets and signaling pathways for precision medicine.

Deep spatial-omics analysis of Head & Neck carcinomas provides alternative therapeutic targets and rationale for treatment failure

Immune checkpoint inhibitor (ICI) therapy has had limited success (<30%) in treating metastatic recurrent Head and Neck Oropharyngeal Squamous Cell Carcinomas (OPSCCs). We postulate that spatial determinants in the tumor play a critical role in cancer therapy outcomes. Here, we describe the case of a male patient diagnosed with p16+ OPSCC and extensive lung metastatic disease who failed Nivolumab and Pembrolizumab/Lenvatinib therapies. Using advanced integrative spatial proteogenomic analysis on the patient's recurrent OPSCC tumors we demonstrate that: (i) unbiased tissue clustering based on spatial transcriptomics (ST) successfully detected tumor cells and enabled the investigation of phenotypic traits such as proliferation or drug-resistance genes in the tumor's leading-edge and core; (ii) spatial proteomic imagining used in conjunction with ST (SpiCi, Spatial Proteomics inferred Cell identification) can resolve the profiling of tumor infiltrating immune cells, (iii) ST data allows for the discovery and ranking of clinically relevant alternative medicines based on their interaction with their matching ligand-receptor. Importantly, when the spatial profiles of ICI pre- and post-failure OPSCC tumors were compared, they exhibited highly similar PD-1/PD-L1low and VEGFAhigh expression, suggesting that these new tumors were not the product of ICI resistance but rather of Lenvatinib dose reduction due to complications. Our work establishes a path for incorporating spatial-omics in clinical settings to facilitate treatment personalization.

Single-Cell Spatial MIST for Versatile, Scalable Detection of Protein Markers

High-multiplex detection of protein biomarkers across tissue regions has been an attractive spatial biology approach due to significant advantages over traditional immunohistochemistry (IHC) methods. Different from most methods, spatial multiplex in situ tagging (MIST) transfers the spatial protein expression information to an ultrahigh-density, large-scale MIST array. This technique has been optimized to reach single-cell resolution by adoption of smaller array units and 30% 8-arm PEG polymer as transfer medium. Tissue cell nuclei stained with lamin B have been clearly visualized on the MIST arrays and are colocalized with detection of nine mouse brain markers. Pseudocells defined at 10 μm in size have been used to fully profile tissue regions including cells and the intercellular space. We showcased the versatility of our technology by successfully detecting 20 marker proteins in kidney samples with the addition of five minutes atop the duration of standard immunohistochemistry protocols. Spatial MIST is amenable to iterative staining and detection on the same tissue samples. When 25 proteins were co-detected on 1 mouse brain section for each round and 5 rounds were executed, an ultrahigh multiplexity of 125 proteins was obtained for each pseudocell. With its unique abilities, this single-cell spatial MIST technology has the potential to become an important method in advanced diagnosis of complex diseases.

Untangling Alzheimer's disease with spatial multi-omics: a brief review

Alzheimer's disease (AD) is the most common form of neurological dementia, specified by extracellular β-amyloid plaque deposition, neurofibrillary tangles, and cognitive impairment. AD-associated pathologies like cerebral amyloid angiopathy (CAA) are also affiliated with cognitive impairment and have overlapping molecular drivers, including amyloid buildup. Discerning the complexity of these neurological disorders remains a significant challenge, and the spatiomolecular relationships between pathogenic features of AD and AD-associated pathologies remain poorly understood. This review highlights recent developments in spatial omics, including profiling and molecular imaging methods, and how they are applied to AD. These emerging technologies aim to characterize the relationship between how specific cell types and tissue features are organized in combination with mapping molecular distributions to provide a systems biology view of the tissue microenvironment around these neuropathologies. As spatial omics methods achieve greater resolution and improved molecular coverage, they are enabling deeper characterization of the molecular drivers of AD, leading to new possibilities for the prediction, diagnosis, and mitigation of this debilitating disease.

Synthetic Adrenocorticotropic Peptides Modulate the Expression Pattern of Immune Genes in Rat Brain following the Early Post-Stroke Period

Ischemic stroke is an acute local decrease in cerebral blood flow due to a thrombus or embolus. Of particular importance is the study of the genetic systems that determine the mechanisms underlying the formation and maintenance of a therapeutic window (a time interval of up to 6 h after a stroke) when effective treatment can be provided. Here, we used a transient middle cerebral artery occlusion (tMCAO) model in rats to study two synthetic derivatives of adrenocorticotropic hormone (ACTH). The first was ACTH(4-7)PGP, which is known as Semax. It is actively used as a neuroprotective drug. The second was the ACTH(6-9)PGP peptide, which is elucidated as a prospective agent only. Using RNA-Seq analysis, we revealed hundreds of ischemia-related differentially expressed genes (DEGs), as well as 131 and 322 DEGs related to the first and second peptide at 4.5 h after tMCAO, respectively, in dorsolateral areas of the frontal cortex of rats. Furthermore, we showed that both Semax and ACTH(6-9)PGP can partially prevent changes in the immune- and neurosignaling-related gene expression profiles disturbed by the action of ischemia at 4.5 h after tMCAO. However, their different actions with regard to predominantly immune-related genes were also revealed. This study gives insight into how the transcriptome depends on the variation in the structure of the related peptides, and it is valuable from the standpoint of the development of measures for early post-stroke therapy.

GDF15 Promotes the Osteogenic Cell Fate of Periodontal Ligament Fibroblasts, thus Affecting Their Mechanobiological Response

Periodontal ligament fibroblasts (PdLFs) exert important functions in oral tissue and bone remodeling following mechanical forces, which are specifically applied during orthodontic tooth movement (OTM). Located between the teeth and the alveolar bone, mechanical stress activates the mechanomodulatory functions of PdLFs including regulating local inflammation and activating further bone-remodeling cells. Previous studies suggested growth differentiation factor 15 (GDF15) as an important pro-inflammatory regulator during the PdLF mechanoresponse. GDF15 exerts its effects through both intracrine signaling and receptor binding, possibly even in an autocrine manner. The extent to which PdLFs are susceptible to extracellular GDF15 has not yet been investigated. Thus, our study aims to examine the influence of GDF15 exposure on the cellular properties of PdLFs and their mechanoresponse, which seems particularly relevant regarding disease- and aging-associated elevated GDF15 serum levels. Therefore, in addition to investigating potential GDF15 receptors, we analyzed its impact on the proliferation, survival, senescence, and differentiation of human PdLFs, demonstrating a pro-osteogenic effect upon long-term stimulation. Furthermore, we observed altered force-related inflammation and impaired osteoclast differentiation. Overall, our data suggest a major impact of extracellular GDF15 on PdLF differentiation and their mechanoresponse.

Integrating Genetics, Transcriptomics, and Proteomics in Lung Tissue to Investigate Chronic Obstructive Pulmonary Disease

The integration of transcriptomic and proteomic data from lung tissue with chronic obstructive pulmonary disease (COPD)-associated genetic variants could provide insight into the biological mechanisms of COPD. Here, we assessed associations between lung transcriptomics and proteomics with COPD in 98 subjects from the Lung Tissue Research Consortium. Low correlations between transcriptomics and proteomics were generally observed, but higher correlations were found for COPD-associated proteins. We integrated COPD risk SNPs or SNPs near COPD-associated proteins with lung transcripts and proteins to identify regulatory cis-quantitative trait loci (QTLs). Significant expression QTLs (eQTLs) and protein QTLs (pQTLs) were found regulating multiple COPD-associated biomarkers. We investigated mediated associations from significant pQTLs through transcripts to protein levels of COPD-associated proteins. We also attempted to identify colocalized effects between COPD genome-wide association studies and eQTL and pQTL signals. Evidence was found for colocalization between COPD genome-wide association study signals and a pQTL for RHOB and an eQTL for DSP. We applied weighted gene co-expression network analysis to find consensus COPD-associated network modules. Two network modules generated by consensus weighted gene co-expression network analysis were associated with COPD with a false discovery rate lower than 0.05. One network module is related to the catenin complex, and the other module is related to plasma membrane components. In summary, multiple cis-acting determinants of transcripts and proteins associated with COPD were identified. Colocalization analysis, mediation analysis, and correlation-based network analysis of multiple omics data may identify key genes and proteins that work together to influence COPD pathogenesis.

Relationships between neurotransmitter receptor densities and expression levels of their corresponding genes in the human hippocampus

Neurotransmitter receptors are key molecules in signal transmission, their alterations are associated with brain dysfunction. Relationships between receptors and their corresponding genes are poorly understood, especially in humans. We combined in vitro receptor autoradiography and RNA sequencing to quantify, in the same tissue samples (7 subjects), the densities of 14 receptors and expression levels of their corresponding 43 genes in the Cornu Ammonis (CA) and dentate gyrus (DG) of human hippocampus. Significant differences in receptor densities between both structures were found only for metabotropic receptors, whereas significant differences in RNA expression levels mostly pertained ionotropic receptors. Receptor fingerprints of CA and DG differ in shapes but have similar sizes; the opposite holds true for their "RNA fingerprints", which represent the expression levels of multiple genes in a single area. In addition, the correlation coefficients between receptor densities and corresponding gene expression levels vary widely and the mean correlation strength was weak-to-moderate. Our results suggest that receptor densities are not only controlled by corresponding RNA expression levels, but also by multiple regionally specific post-translational factors.

Prokineticin 1 is a novel factor regulating porcine corpus luteum function

Prokineticin 1 (PROK1) is a pleiotropic factor secreted by endocrine glands; however, its role has not been studied in the corpus luteum (CL) during pregnancy in any species. The present study aimed to investigate the contribution of PROK1 in regulating processes related to porcine CL function and regression: steroidogenesis, luteal cell apoptosis and viability, and angiogenesis. The luteal expression of PROK1 was greater on Days 12 and 14 of pregnancy compared to Day 9. PROK1 protein expression during pregnancy increased gradually and peaked on Day 14, when it was also significantly higher than that on Day 14 of the estrous cycle. Prokineticin receptor 1 (PROKR1) mRNA abundance increased on Days 12 and 14 of pregnancy, whereas PROKR2 elevated on Day 14 of the estrous cycle. PROK1, acting via PROKR1, stimulated the expression of genes involved in progesterone synthesis, as well as progesterone secretion by luteal tissue. PROK1-PROKR1 signaling reduced apoptosis and increased the viability of luteal cells. PROK1 acting through PROKR1 stimulated angiogenesis by increasing capillary-like structure formation by luteal endothelial cells and elevating angiogenin gene expression and VEGFA secretion by luteal tissue. Our results indicate that PROK1 regulates processes vital for maintaining luteal function during early pregnancy and the mid-luteal phase.

ALDOC- and ENO2- driven glucose metabolism sustains 3D tumor spheroids growth regardless of nutrient environmental conditions: a multi-omics analysis

BACKGROUND

Metastases are the major cause of cancer-related morbidity and mortality. By the time cancer cells detach from their primary site to eventually spread to distant sites, they need to acquire the ability to survive in non-adherent conditions and to proliferate within a new microenvironment in spite of stressing conditions that may severely constrain the metastatic process. In this study, we gained insight into the molecular mechanisms allowing cancer cells to survive and proliferate in an anchorage-independent manner, regardless of both tumor-intrinsic variables and nutrient culture conditions.

METHODS

3D spheroids derived from lung adenocarcinoma (LUAD) and breast cancer cells were cultured in either nutrient-rich or -restricted culture conditions. A multi-omics approach, including transcriptomics, proteomics, and metabolomics, was used to explore the molecular changes underlying the transition from 2 to 3D cultures. Small interfering RNA-mediated loss of function assays were used to validate the role of the identified differentially expressed genes and proteins in H460 and HCC827 LUAD as well as in MCF7 and T47D breast cancer cell lines.

RESULTS

We found that the transition from 2 to 3D cultures of H460 and MCF7 cells is associated with significant changes in the expression of genes and proteins involved in metabolic reprogramming. In particular, we observed that 3D tumor spheroid growth implies the overexpression of ALDOC and ENO2 glycolytic enzymes concomitant with the enhanced consumption of glucose and fructose and the enhanced production of lactate. Transfection with siRNA against both ALDOC and ENO2 determined a significant reduction in lactate production, viability and size of 3D tumor spheroids produced by H460, HCC827, MCF7, and T47D cell lines.

CONCLUSIONS

Our results show that anchorage-independent survival and growth of cancer cells are supported by changes in genes and proteins that drive glucose metabolism towards an enhanced lactate production. Notably, this finding is valid for all lung and breast cancer cell lines we have analyzed in different nutrient environmental conditions. broader Validation of this mechanism in other cancer cells of different origin will be necessary to broaden the role of ALDOC and ENO2 to other tumor types. Future in vivo studies will be necessary to assess the role of ALDOC and ENO2 in cancer metastasis.

Quantifying tumor specificity using Bayesian probabilistic modeling for drug target discovery and prioritization

In diseases such as cancer, the design of new therapeutic strategies requires extensive, costly, and unfortunately sometimes deadly testing to reveal life threatening "off target" effects. A crucial first step in predicting toxicity are analyses of normal RNA and protein tissue expression, which are now possible using comprehensive molecular tissue atlases. However, no standardized approaches exist for target prioritization, which instead rely on ad-hoc thresholds and manual inspection. Such issues are compounded, given that genomic and proteomic data detection sensitivity and accuracy are often problematic. Thus, quantifiable probabilistic scores for tumor specificity that address these challenges could enable the creation of new predictive models for combinatorial drug design and correlative analyses. Here, we propose a Bayesian Tumor Specificity (BayesTS) score that can naturally account for multiple independent forms of molecular evidence derving from both RNA-Seq and protein expression while preserving the uncertainty of the inference. We applied BayesTS to 24,905 human protein-coding genes across 3,644 normal samples (GTEx and TCGA) spanning 63 tissues. These analyses demonstrate the ability of BayesTS to accurately incorporate protein, RNA and tissue distribution evidence, while effectively capturing the uncertainty of these inferences. This approach prioritized well-established drug targets, while deemphasizing those which were later found to induce toxicity. BayesTS allows for the adjustment of tissue importance weights for tissues of interest, such as reproductive and physiologically dispensable tissues (e.g., tonsil, appendix), enabling clinically translatable prioritizations. Our results show that BayesTS can facilitate novel drug target discovery and can be easily generalized to unconventional molecular targets, such as splicing neoantigens. We provide the code and inferred tumor specificity predictions as a database available online (https://github.com/frankligy/BayesTS). We envision that the widespread adoption of BayesTS will facilitate improved target prioritization for oncology drug development, ultimately leading to the discovery of more effective and safer drugs.

PPARβ/δ Ligands Regulate Oxidative Status and Inflammatory Response in Inflamed Corpus Luteum-An In Vitro Study

Inflammation in the female reproductive system causes serious health problems including infertility. The aim of this study was to determine the in vitro effects of peroxisome proliferator-activated receptor-beta/delta (PPARβ/δ) ligands on the transcriptomic profile of the lipopolysaccharide (LPS)-stimulated pig corpus luteum (CL) in the mid-luteal phase of the estrous cycle using RNA-seq technology. The CL slices were incubated in the presence of LPS or in combination with LPS and the PPARβ/δ agonist-GW0724 (1 μmol/L or 10 μmol/L) or the antagonist-GSK3787 (25 μmol/L). We identified 117 differentially expressed genes after treatment with LPS; 102 and 97 differentially expressed genes after treatment, respectively, with the PPARβ/δ agonist at a concentration of 1 μmol/L or 10 μmol/L, as well as 88 after the treatment with the PPARβ/δ antagonist. In addition, biochemical analyses of oxidative status were performed (total antioxidant capacity and activity of peroxidase, catalase, superoxide dismutase, and glutathione S-transferase). This study revealed that PPARβ/δ agonists regulate genes involved in the inflammatory response in a dose-dependent manner. The results indicate that the lower dose of GW0724 showed an anti-inflammatory character, while the higher dose seems to be pro-inflammatory. We propose that GW0724 should be considered for further research to alleviate chronic inflammation (at the lower dose) or to support the natural immune response against pathogens (at the higher dose) in the inflamed corpus luteum.

Dynamical modeling reveals RNA decay mediates the effect of matrix stiffness on aged muscle stem cell fate

Loss of muscle stem cell (MuSC) self-renewal with aging reflects a combination of influences from the intracellular (e.g., post-transcriptional modifications) and extracellular (e.g., matrix stiffness) environment. Whereas conventional single cell analyses have revealed valuable insights into factors contributing to impaired self-renewal with age, most are limited by static measurements that fail to capture nonlinear dynamics. Using bioengineered matrices mimicking the stiffness of young and old muscle, we showed that while young MuSCs were unaffected by aged matrices, old MuSCs were phenotypically rejuvenated by young matrices. Dynamical modeling of RNA velocity vector fields in silico revealed that soft matrices promoted a self-renewing state in old MuSCs by attenuating RNA decay. Vector field perturbations demonstrated that the effects of matrix stiffness on MuSC self-renewal could be circumvented by fine-tuning the expression of the RNA decay machinery. These results demonstrate that post-transcriptional dynamics dictate the negative effect of aged matrices on MuSC self-renewal.

Expression and regulation of visfatin/NAMPT in the porcine corpus luteum during the estrous cycle and early pregnancy

Visfatin/NAMPT creates a hormonal link between energy metabolism and female reproduction. A recent study documented visfatin expression in the ovary and its action on follicular cells; however, the expression of visfatin in luteal cells is still unknown. The aim of this study, therefore, was to investigate the transcript and protein expression of visfatin as well as its immunolocalization in the corpus luteum (CL) and to examine the involvement of extracellular signal-regulated kinases (ERK1/2) in the regulation of visfatin level in response to LH, insulin, progesterone (P₄), prostaglandin E₂ (PGE₂) and F_2α (PGF_2α). Corpora lutea were harvested from gilts on days 2-3, 10-12 and 14-16 of the estrous cycle and on days 10-11, 12-13, 15-16 and 27-28 of pregnancy. The current study demonstrated that visfatin expression depends on hormonal status related to the phase of the estrous cycle or early pregnancy. Visfatin was immunolocalized to the cytoplasm of small and large luteal cells. Moreover, visfatin protein abundance was increased by P₄, and decreased by both prostaglandins, while LH and insulin have modulatory effects, depending on the phase of the cycle. Interestingly, LH, P₄ and PGE₂ effects were abolished in response to the inhibition of ERK1/2 kinase. Thus, this study demonstrated that expression of visfatin in the porcine CL is determined by the endocrine status related to the estrous cycle and early pregnancy and by the action of LH, insulin, P₄ and prostaglandins via activation of the ERK1/2 pathway.

Advancing personalized medicine for tuberculosis through the application of immune profiling

While early and precise diagnosis is the key to eliminating tuberculosis (TB), conventional methods using culture conversion or sputum smear microscopy have failed to meet demand. This is especially true in high-epidemic developing countries and during pandemic-associated social restrictions. Suboptimal biomarkers have restricted the improvement of TB management and eradication strategies. Therefore, the research and development of new affordable and accessible methods are required. Following the emergence of many high-throughput quantification TB studies, immunomics has the advantages of directly targeting responsive immune molecules and significantly simplifying workloads. In particular, immune profiling has been demonstrated to be a versatile tool that potentially unlocks many options for application in TB management. Herein, we review the current approaches for TB control with regard to the potentials and limitations of immunomics. Multiple directions are also proposed to hopefully unleash immunomics' potential in TB research, not least in revealing representative immune biomarkers to correctly diagnose TB. The immune profiles of patients can be valuable covariates for model-informed precision dosing-based treatment monitoring, prediction of outcome, and the optimal dose prediction of anti-TB drugs.

Peroxisome proliferator-activated receptor γ coactivator 1-α overexpression improves angiogenic signalling potential of skeletal muscle-derived extracellular vesicles

NEW FINDINGS

What is the central question of this study? Skeletal muscle extracellular vesicles likely act as pro-angiogenic signalling factors: does overexpression of peroxisome proliferator-activated receptor γ coactivator 1-α (PGC-1α) alter skeletal muscle myotube extracellular vesicle release, contents and angiogenic potential? What is the main finding and its importance? Overexpression of PGC-1α results in secretion of extracellular vesicles that elevate measures of angiogenesis and protect against acute oxidative stress in vitro. Skeletal muscle with high levels of PGC-1α expression, commonly associated with exercise induced angiogenesis and high basal capillarization, may secrete extracellular vesicles that support capillary growth and maintenance.

ABSTRACT

Skeletal muscle capillarization is proportional to muscle fibre mitochondrial content and oxidative capacity. Skeletal muscle cells secrete many factors that regulate neighbouring capillary endothelial cells (ECs), including extracellular vesicles (SkM-EVs). Peroxisome proliferator-activated receptor γ coactivator 1-α (PGC-1α) regulates mitochondrial biogenesis and the oxidative phenotype in skeletal muscle. Skeletal muscle PGC-1α also regulates secretion of multiple angiogenic factors, but it is unknown whether PGC-1α regulates SkM-EV release, contents and angiogenic signalling potential. PGC-1α was overexpressed via adenovirus in primary human myotubes. EVs were collected from PGC-1α-overexpressing myotubes (PGC-EVs) as well as from green fluorescent protein-overexpressing myotubes (GFP-EVs), and from untreated myotubes. EV release and select mRNA contents were measured from EVs. Additionally, ECs were treated with EVs to measure angiogenic potential of EVs in normal conditions and following an oxidative stress challenge. PGC-1α overexpression did not impact EV release but did elevate EV content of mRNAs for several antioxidant proteins (nuclear factor erythroid 2-related factor 2, superoxide dismutase 2, glutathione peroxidase). PGC-EV treatment of cultured human umbilical vein endothelial cells (HUVECs) increased their proliferation (+36.6%), tube formation (length: +28.1%; number: +25.7%) and cellular viability (+52.9%), and reduced reactive oxygen species levels (-41%) compared to GFP-EVs. Additionally, PGC-EV treatment protected against tube formation impairments and induction of cellular senescence following acute oxidative stress. Overexpression of PGC-1α in human myotubes increases the angiogenic potential of SkM-EVs. These angiogenic benefits coincided with increased anti-oxidative capacity of recipient HUVECs. High PGC-1α expression in skeletal muscle may prompt the release of SkM-EVs that support vascular redox homeostasis and angiogenesis.

Characterization of proteome-size scaling by integrative omics reveals mechanisms of proliferation control in cancer

Almost all living cells maintain size uniformity through successive divisions. Proteins that over and underscale with size can act as rheostats, which regulate cell cycle progression. Using a multiomic strategy, we leveraged the heterogeneity of melanoma cell lines to identify peptides, transcripts, and phosphorylation events that differentially scale with cell size. Subscaling proteins are enriched in regulators of the DNA damage response and cell cycle progression, whereas super-scaling proteins included regulators of the cytoskeleton, extracellular matrix, and inflammatory response. Mathematical modeling suggested that decoupling growth and proliferative signaling may facilitate cell cycle entry over senescence in large cells when mitogenic signaling is decreased. Regression analysis reveals that up-regulation of TP53 or CDKN1A/p21CIP1 is characteristic of proliferative cancer cells with senescent-like sizes/proteomes. This study provides one of the first demonstrations of size-scaling phenomena in cancer and how morphology influences the chemistry of the cell.

Comparing the Biology of Young versus Old Age Estrogen-Receptor-Positive Breast Cancer through Gene and Protein Expression Analyses

Background: Breast cancer developed at a young age (≤45 years) is hypothesized to have unique biology; however, findings in this field are controversial. Methods: We compared the whole transcriptomic profile of young vs. old-age breast cancer using DNA microarray. RNA was extracted from 13 fresh estrogen receptor (ER)-positive primary breast cancer tissues of untreated patients (7 = young age ≤45 years and 6 = old age ≥55 years). In silico validation for the differentially expressed genes (DEGs) by young-age patients was conducted using The Cancer Genome Atlas (TCGA) database. Next, we analyzed the protein expression encoded by two of the significantly down-regulated genes by young-age patients, Glycine N-acyltransferase-like 1 (GLYATL-1) and Ran-binding protein 3 like (RANBP3L), using immunohistochemical analysis in an independent cohort of 56 and 74 ER-positive pre-therapeutic primary breast cancer tissues, respectively. Results: 12 genes were significantly differentially expressed by young-age breast cancers (fold change >2 or <2- with FDR p-value < 0.05). TCGA data confirmed the differential expression of six genes. Protein expression analysis of GLYATL-1 and RANBP3L did not show heterogeneous expression between young and old-age breast cancer tissues. Loss of expression of GLYATL-1 was significantly (p-value 0.005) associated with positive lymph node status. Higher expression of RANBP3L was significantly associated with breast cancers with lower histopathological grades (p-value 0.038). Conclusions: At the transcriptomic level, breast cancer developed in young and old age patients seems homogenous. The variation in the transcriptomic profiles can be attributed to the other clinicopathological characteristics rather than the age of the patient.

Using chemical and biological data to predict drug toxicity

Various sources of information can be used to better understand and predict compound activity and safety-related endpoints, including biological data such as gene expression and cell morphology. In this review, we first introduce types of chemical, in vitro and in vivo information that can be used to describe compounds and adverse effects. We then explore how compound descriptors based on chemical structure or biological perturbation response can be used to predict safety-related endpoints, and how especially biological data can help us to better understand adverse effects mechanistically. Overall, the described applications demonstrate how large-scale biological information presents new opportunities to anticipate and understand the biological effects of compounds, and how this can support predictive toxicology and drug discovery projects.

Hypergraph geometry reflects higher-order dynamics in protein interaction networks

Protein interactions form a complex dynamic molecular system that shapes cell phenotype and function; in this regard, network analysis is a powerful tool for studying the dynamics of cellular processes. Current models of protein interaction networks are limited in that the standard graph model can only represent pairwise relationships. Higher-order interactions are well-characterized in biology, including protein complex formation and feedback or feedforward loops. These higher-order relationships are better represented by a hypergraph as a generalized network model. Here, we present an approach to analyzing dynamic gene expression data using a hypergraph model and quantify network heterogeneity via Forman-Ricci curvature. We observe, on a global level, increased network curvature in pluripotent stem cells and cancer cells. Further, we use local curvature to conduct pathway analysis in a melanoma dataset, finding increased curvature in several oncogenic pathways and decreased curvature in tumor suppressor pathways. We compare this approach to a graph-based model and a differential gene expression approach.

Chlorotoxin and Lung Cancer: A Targeting Perspective for Drug Delivery

In the generational evolution of nano-based drug delivery carriers, active targeting has been a major milestone for improved and selective drug accumulation in tissues and cell types beyond the existing passive targeting capabilities. Among the various active targeting moieties, chlorotoxin, a peptide extracted from scorpions, demonstrated promising tumor cell accumulation and selection. With lung cancer being among the leading diagnoses of cancer-related deaths in both men and women, novel therapeutic methodologies utilizing nanotechnology for drug delivery emerged. Given chlorotoxin's promising biological activity, we explore its potential against lung cancer and its utilization for active targeting against this cancer's tumor cells. Our analysis indicates that despite the extensive chlorotoxin's research against glioblastoma, lung cancer research with the molecule has been limited, despite some promising early results.

Discovery of pathway-independent protein signatures associated with clinical outcome in human cancer cohorts

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.

In silico investigations identified Butyl Xanalterate to competently target CK2α (CSNK2A1) for therapy of chronic lymphocytic leukemia

Chronic lymphocytic leukemia (CLL) is an incurable malignancy of B-cells. In this study, bioinformatics analyses were conducted to identify possible pathogenic roles of CK2α, which is a protein encoded by CSNK2A1, in the progression and aggressiveness of CLL. Furthermore, various computational tools were used to search for a competent inhibitor of CK2α from fungal metabolites that could be proposed for CLL therapy. In CLL patients, high-expression of CSNK2A1 was associated with early need for therapy (n = 130, p < 0.0001) and short overall survival (OS; n = 107, p = 0.005). Consistently, bioinformatics analyses showed CSNK2A1 to associate with/play roles in CLL proliferation and survival-dependent pathways. Furthermore, PPI network analysis identified interaction partners of CK2α (PPI enrichment p value = 1 × 10^-16) that associated with early need for therapy (n = 130, p < 0.003) and have been known to heavily impact on the progression of CLL. These findings constructed a rational for targeting CK2α for CLL therapy. Consequently, computational analyses reported 35 fungal metabolites out of 5820 (filtered from 19,967 metabolites) to have lower binding energy (ΔG: - 10.9 to - 11.7 kcal/mol) and better binding affinity (Kd: 9.77 × 10⁷ M^-1 to 3.77 × 10⁸ M^-1) compared with the native ligand (ΔG: - 10.8, Kd: 8.3 × 10⁷ M-^-1). Furthermore, molecular dynamics simulation study established that Butyl Xanalterate-CK2α complex continuously remained stable throughout the simulation time (100 ns). Moreover, Butyl Xanalterate interacted with most of the catalytic residues, where complex was stabilized by more than 65% hydrogen bond interactions, and a significant hydrophobic interaction with residue Phe113. Here, high-expression of CSNK2A1 was implicated in the progression and poor prognosis of CLL, making it a potential therapeutic target in the disease. Butyl Xanalterate showed stable and strong interactions with CK2α, thus we propose it as a competitive inhibitor of CK2α for CLL therapy.

BET inhibition induces vulnerability to MCL1 targeting through upregulation of fatty acid synthesis pathway in breast cancer

Therapeutic options for treatment of basal-like breast cancers remain limited. Here, we demonstrate that bromodomain and extra-terminal (BET) inhibition induces an adaptive response leading to MCL1 protein-driven evasion of apoptosis in breast cancer cells. Consequently, co-targeting MCL1 and BET is highly synergistic in breast cancer models. The mechanism of adaptive response to BET inhibition involves the upregulation of lipid synthesis enzymes including the rate-limiting stearoyl-coenzyme A (CoA) desaturase. Changes in lipid synthesis pathway are associated with increases in cell motility and membrane fluidity as well as re-localization and activation of HER2/EGFR. In turn, the HER2/EGFR signaling results in the accumulation of and vulnerability to the inhibition of MCL1. Drug response and genomics analyses reveal that MCL1 copy-number alterations are associated with effective BET and MCL1 co-targeting. The high frequency of MCL1 chromosomal amplifications (>30%) in basal-like breast cancers suggests that BET and MCL1 co-targeting may have therapeutic utility in this aggressive subtype of breast cancer.

Evaluation of Potential Inflammatory Markers for Cystic Echinococcosis: P-selectin and Resistin

OBJECTIVE

Cystic echinococcosis (CE) is one of the most common zoonotic diseases worldwide. Diagnosis of CE is predominantly based on imaging techniques and serological tests are used in cases of non-characteristic imaging findings as diagnostic reference. However, serological test results cannot be completely reliable as they are affected by multi-factors. P-selectin and resistin are inflammatory markers that are altered during the acute stages of infection. In this purpose, inflammatory markers as P-selectin and resistin have been investigated for a potential diagnostic reference for CE diagnosis.

METHODS

A total of 60 patients who were diagnosed with CE and twenty-five healthy individuals were included in this study. Blood samples were obtained from all participants. Obtained sera were evaluated using the P-selectin and resistin ELISA kits for protein levels. Additionally, the relative expression of SELP (P-selectin) and RETN (resistin) genes were determined using the comparative CT (ΔΔCT) method between groups as CE patients with active and inactive cysts, CE patients and healthy controls.

RESULTS

SELP (13.9-fold change, p<0.05) and RETN (8.1-fold change, p<0.05) were differentially expressed in CE patients compared in the control group. Whereas resistin protein levels were significantly higher in CE patients than the healthy controls (p<0.001), the difference in P-selectin protein levels was not significant (p>0.05). There was no difference between active and inactive CE patients in terms of P-selectin and resistin in gene and protein levels (p>0.05).

CONCLUSION

Although there was no difference between the active and inactive CE patients, the good differentiation between the healthy controls and the CE patients suggested that resistin is a potential inflammatory diagnostic reference.

KRAS Promoter Methylation Status and miR-18a-3p and miR-143 Expression in Patients With Wild-type KRAS Gene in Colorectal Cancer

BACKGROUND/AIM

Although some mutations of KRAS proto-oncogene, GTPase (KRAS) have been associated with the prognosis and therapeutic management of colorectal cancer (CRC), the epigenetic mechanisms (DNA methylation and microRNA expression) that regulate wild-type KRAS expression in patients with CRC are poorly known. The aim of this study was to establish whether there is a relationship between the expression of the wild-type KRAS gene, the methylation status of its distal promoter, and miR-143 and miR-18a-3p levels in samples of sporadic CRC.

PATIENTS AND METHODS

A total of 51 cases of sporadic CRC with wild-type KRAS were analyzed. The expression levels of KRAS mRNA, miR-18a-3p, miR-143, and KRAS protein, as well as methylation in the distal promoter of the KRAS gene were evaluated.

RESULTS

In the analyzed cases, KRAS mRNA expression was detected in 51.1%; wild-type KRAS protein was found in the membrane in 31.4% and in the cytoplasm in 98% of cases. An inverse relationship of marginal significance was observed between miR-18a-3p and KRAS protein expression in the cytoplasm (odds ratio=0.14, 95% confidence interval=0.012-1.092; p=0.08). The methylation status of the distal promoter of KRAS at four CpG islands was analyzed in 30 cases (58.8%): partial methylation of the four CpG islands evaluated was observed in two cases (6.7%). In these cases, KRAS protein expression was not evidenced at the membrane level; miR-18a-3p expression was not detected either but high expression of miR-143 was observed.

CONCLUSION

No association was found between the expression levels of KRAS mRNA, miR-18a-3p, miR-143 and methylation status. Methylation status was detected with low frequency, thus being the first report of methylation in wild-type KRAS.

Bioinformatics study of expression from genomes of epidemiologically related MRSA CC398 isolates from human and wild animal samples

One of the most important livestock-associated methicillin-resistant Staphylococcus aureus (LA-MRSA) genetic lineages is the clonal complex (CC) 398, which can cause typical S. aureus-associated infections in people. In this work, whole-genome sequencing, RNA-sequencing, and gel-based comparative proteomics were applied to study the genetic characteristics of three MRSA CC398 isolates recovered from humans (strains C5621 and C9017), and from an animal (strain OR418). Of the three strains, C9017 presented the broadest resistance genotype, including resistance to fluroquinolone, clindamycin, tiamulin, macrolide and aminoglycoside antimicrobial classes. The scn, sak, and chp genes of the immune evasion cluster system were solely detected in OR418. Pangenome analysis showed a total of 288 strain-specific genes, most of which are hypothetical or phage-related proteins. OR418 had the most pronounced genetic differences. RNAIII (δ-hemolysin) gene was clearly the most expressed gene in OR418 and C5621, but it was not detected in C9017. Significant differences in the proteome profiles were found between strains. For example, the immunoglobulin-binding protein Sbi was more abundant in OR418. Considering that Sbi is a multifunctional immune evasion factor in S. aureus, the results point to OR418 strain having high zoonotic potential. Overall, multiomics biomarker signatures can assume an important role to advance precision medicine in the years to come. SIGNIFICANCE: MRSA is one of the most representative drug-resistant pathogens and its dissemination is increasing due to MRSA capability of establishing new reservoirs. LA-MRSA is considered an emerging problem worldwide and CC398 is one of the most important genetic lineages. In this study, three MRSA CC398 isolates recovered from humans and from a wild animal were analyzed through whole-genome sequencing, RNA-sequencing, and gel-based comparative proteomics in order to gather systems-wide omics data and better understand the genetic characteristics of this lineage to identify distinctive markers and genomic features of relevance to public health. The scn, sak, and chp genes of the immune evasion cluster system were solely detected in OR418. Pangenome analysis showed a total of 288 strain-specific genes, most of which are hypothetical or phage-related proteins. OR418 had the most pronounced genetic differences. RNAIII (δ-hemolysin) gene was clearly the most expressed gene in OR418 and C5621, but it was not detected in C9017. Significant differences in the proteome profiles were found between strains.