Application of NanoString technologies in companion diagnostic development

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.

Considering Context-Specific microRNAs in Ischemic Stroke with Three "W": Where, When, and What

MicroRNAs are short non-coding RNA molecules that function as critical regulators of various biological processes through negative regulation of gene expression post-transcriptionally. Recent studies have indicated that microRNAs are potential biomarkers for ischemic stroke. In this review, we first illustrate the pathogenesis of ischemic stroke and demonstrate the biogenesis and transportation of microRNAs from cells. We then discuss several promising microRNA biomarkers in ischemic stroke in a context-specific manner from three dimensions: biofluids selection for microRNA extraction (Where), the timing of sample collection after ischemic stroke onset (When), and the clinical application of the differential-expressed microRNAs during stroke pathophysiology (What). We show that microRNAs have the utilities in ischemic stroke diagnosis, risk stratification, subtype classification, prognosis prediction, and treatment response monitoring. However, there are also obstacles in microRNA biomarker research, and this review will discuss the possible ways to improve microRNA biomarkers. Overall, microRNAs have the potential to assist clinical treatment, and developing microRNA panels for clinical application is worthwhile.

Remodeling of the gastric environment in Helicobacter pylori-induced atrophic gastritis

Helicobacter pylori colonization of the human stomach is a strong risk factor for gastric cancer. To investigate H. pylori-induced gastric molecular alterations, we used a Mongolian gerbil model of gastric carcinogenesis. Histologic evaluation revealed varying levels of atrophic gastritis (a premalignant condition characterized by parietal and chief cell loss) in H. pylori-infected animals, and transcriptional profiling revealed a loss of markers for these cell types. We then assessed the spatial distribution and relative abundance of proteins in the gastric tissues using imaging mass spectrometry and liquid chromatography with tandem mass spectrometry. We detected striking differences in the protein content of corpus and antrum tissues. Four hundred ninety-two proteins were preferentially localized to the corpus in uninfected animals. The abundance of 91 of these proteins was reduced in H. pylori-infected corpus tissues exhibiting atrophic gastritis compared with infected corpus tissues exhibiting non-atrophic gastritis or uninfected corpus tissues; these included numerous proteins with metabolic functions. Fifty proteins localized to the corpus in uninfected animals were diffusely delocalized throughout the stomach in infected tissues with atrophic gastritis; these included numerous proteins with roles in protein processing. The corresponding alterations were not detected in animals infected with a H. pylori ∆cagT mutant (lacking Cag type IV secretion system activity). These results indicate that H. pylori can cause loss of proteins normally localized to the gastric corpus as well as diffuse delocalization of corpus-specific proteins, resulting in marked changes in the normal gastric molecular partitioning into distinct corpus and antrum regions.IMPORTANCEA normal stomach is organized into distinct regions known as the corpus and antrum, which have different functions, cell types, and gland architectures. Previous studies have primarily used histologic methods to differentiate these regions and detect H. pylori-induced alterations leading to stomach cancer. In this study, we investigated H. pylori-induced gastric molecular alterations in a Mongolian gerbil model of carcinogenesis. We report the detection of numerous proteins that are preferentially localized to the gastric corpus but not the antrum in a normal stomach. We show that stomachs with H. pylori-induced atrophic gastritis (a precancerous condition characterized by the loss of specialized cell types) exhibit marked changes in the abundance and localization of proteins normally localized to the gastric corpus. These results provide new insights into H. pylori-induced gastric molecular alterations that are associated with the development of stomach cancer.

Distinct neuroinflammatory signatures exist across genetic and sporadic amyotrophic lateral sclerosis cohorts

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by progressive loss of upper and lower motor neurons. ALS is on a pathogenetic disease spectrum with frontotemporal dementia, referred to as ALS-frontotemporal spectrum disorder (ALS-FTSD). For mutations associated with ALS-FTSD, such as the C9orf72 hexanucleotide repeat expansion, the molecular factors associated with heterogeneity along this spectrum require further characterization. Here, using a targeted NanoString molecular barcoding approach, we interrogate neuroinflammatory dysregulation and heterogeneity at the level of gene expression in post-mortem motor cortex tissue from a cohort of clinically heterogeneous C9-ALS-FTSD cases. We identified 20 dysregulated genes in C9-ALS-FTSD, with enrichment of microglial and inflammatory response gene sets. Two genes with significant correlations to available clinical metrics were selected for validation: FKBP5, a correlate of cognitive function, and brain-derived neurotrophic factor (BDNF), a correlate of disease duration. FKBP5 and its signalling partner, NF-κB, appeared to have a cell type-specific staining distribution, with activated (i.e. nuclear) NF-κB immunoreactivity in C9-ALS-FTSD. Expression of BDNF, a correlate of disease duration, was confirmed to be higher in individuals with long compared to short disease duration using BaseScope™ in situ hybridization. Our analyses also revealed two distinct neuroinflammatory panel signatures (NPS), NPS1 and NPS2, delineated by the direction of expression of proinflammatory, axonal transport and synaptic signalling pathways. We compared NPS between C9-ALS-FTSD cases and those from sporadic ALS and SOD1-ALS cohorts and identified NPS1 and NPS2 across all cohorts. Moreover, a subset of NPS was also able to separate publicly available RNA sequencing data from independent C9-ALS and sporadic ALS cohorts into two inflammatory subgroups. Importantly, NPS subgroups did not clearly segregate with available demographic, genetic, clinical or pathological features, highlighting the value of molecular stratification in clinical trials for inflammatory subgroup identification. Our findings thus underscore the importance of tailoring therapeutic approaches based on distinct molecular signatures that exist between and within ALS-FTSD cohorts.

From Chaos to Opportunity: Decoding Cancer Heterogeneity for Enhanced Treatment Strategies

Cancer manifests as a multifaceted disease, characterized by aberrant cellular proliferation, survival, migration, and invasion. Tumors exhibit variances across diverse dimensions, encompassing genetic, epigenetic, and transcriptional realms. This heterogeneity poses significant challenges in prognosis and treatment, affording tumors advantages through an increased propensity to accumulate mutations linked to immune system evasion and drug resistance. In this review, we offer insights into tumor heterogeneity as a crucial characteristic of cancer, exploring the difficulties associated with measuring and quantifying such heterogeneity from clinical and biological perspectives. By emphasizing the critical nature of understanding tumor heterogeneity, this work contributes to raising awareness about the importance of developing effective cancer therapies that target this distinct and elusive trait of cancer.

Derivation and validation of risk prediction for posttraumatic stress symptoms following trauma exposure

BACKGROUND

Posttraumatic stress symptoms (PTSS) are common following traumatic stress exposure (TSE). Identification of individuals with PTSS risk in the early aftermath of TSE is important to enable targeted administration of preventive interventions. In this study, we used baseline survey data from two prospective cohort studies to identify the most influential predictors of substantial PTSS.

METHODS

Self-identifying black and white American women and men (n = 1546) presenting to one of 16 emergency departments (EDs) within 24 h of motor vehicle collision (MVC) TSE were enrolled. Individuals with substantial PTSS (⩾33, Impact of Events Scale - Revised) 6 months after MVC were identified via follow-up questionnaire. Sociodemographic, pain, general health, event, and psychological/cognitive characteristics were collected in the ED and used in prediction modeling. Ensemble learning methods and Monte Carlo cross-validation were used for feature selection and to determine prediction accuracy. External validation was performed on a hold-out sample (30% of total sample).

RESULTS

Twenty-five percent (n = 394) of individuals reported PTSS 6 months following MVC. Regularized linear regression was the top performing learning method. The top 30 factors together showed good reliability in predicting PTSS in the external sample (Area under the curve = 0.79 ± 0.002). Top predictors included acute pain severity, recovery expectations, socioeconomic status, self-reported race, and psychological symptoms.

CONCLUSIONS

These analyses add to a growing literature indicating that influential predictors of PTSS can be identified and risk for future PTSS estimated from characteristics easily available/assessable at the time of ED presentation following TSE.

Enhanced Multiplexing Technology for Proteomics

The identification of thousands of proteins and their relative levels of expression has furthered understanding of biological processes and disease and stimulated new systems biology hypotheses. Quantitative proteomics workflows that rely on analytical assays such as mass spectrometry have facilitated high-throughput measurements of proteins partially due to multiplexing. Multiplexing allows proteome differences across multiple samples to be measured simultaneously, resulting in more accurate quantitation, increased statistical robustness, reduced analysis times, and lower experimental costs. The number of samples that can be multiplexed has evolved from as few as two to more than 50, with studies involving more than 10 samples being denoted as enhanced multiplexing or hyperplexing. In this review, we give an update on emerging multiplexing proteomics techniques and highlight advantages and limitations for enhanced multiplexing strategies.

A novel, stain-free, natural auto-fluorescent signal, Sig M, identified from cytometric and transcriptomic analysis of infectivity of Cryptosporidium hominis and Cryptosporidium parvum

Cryptosporidiosis is a worldwide diarrheal disease caused by the protozoan Cryptosporidium. The primary symptom is diarrhea, but patients may exhibit different symptoms based on the species of the Cryptosporidium parasite they are infected with. Furthermore, some genotypes within species are more transmissible and apparently virulent than others. The mechanisms underpinning these differences are not understood, and an effective in vitro system for Cryptosporidium culture would help advance our understanding of these differences. Using COLO-680N cells, we employed flow cytometry and microscopy along with the C. parvum-specific antibody Sporo-Glo™ to characterize infected cells 48 h following an infection with C. parvum or C. hominis. The Cryptosporidium parvum-infected cells showed higher levels of signal using Sporo-Glo™ than C. hominis-infected cells, which was likely because Sporo-Glo™ was generated against C. parvum. We found a subset of cells from infected cultures that expressed a novel, dose-dependent auto-fluorescent signal that was detectable across a range of wavelengths. The population of cells that expressed this signal increased proportionately to the multiplicity of infection. The spectral cytometry results confirmed that the signature of this subset of host cells closely matched that of oocysts present in the infectious ecosystem, pointing to a parasitic origin. Present in both C. parvum and C. hominis cultures, we named this Sig M, and due to its distinct profile in cells from both infections, it could be a better marker for assessing Cryptosporidium infection in COLO-680N cells than Sporo-Glo™. We also noted Sig M's impact on Sporo-Glo™ detection as Sporo-Glo™ uses fluoroscein-isothiocynate, which is detected where Sig M also fluoresces. Lastly, we used NanoString nCounter^® analysis to investigate the transcriptomic landscape for the two Cryptosporidium species, assessing the gene expression of 144 host and parasite genes. Despite the host gene expression being at high levels, the levels of putative intracellular Cryptosporidium gene expression were low, with no significant difference from controls, which could be, in part, explained by the abundance of uninfected cells present as determined by both Sporo-Glo™ and Sig M analyses. This study shows for the first time that a natural auto-fluorescent signal, Sig M, linked to Cryptosporidium infection can be detected in infected host cells without any fluorescent labeling strategies and that the COLO-680N cell line and spectral cytometry could be useful tools to advance the understanding of Cryptosporidium infectivity.

Association Between Serum MicroRNAs and Abdominal Aortic Aneurysm Diagnosis and Growth

OBJECTIVE

This study aimed to examine the association between serum microRNAs (miRNAs) and diagnosis and growth of abdominal aortic aneurysm (AAA), and to test their diagnostic and prognostic value.

METHODS

The expression levels of 800 miRNA tags were assessed in 108 patients with AAA, 12 age and sex matched healthy controls (HCs), and 12 patients with peripheral artery disease (PAD) using NanoString technology. Findings were assessed in an independent sample of 66 patients with AAA and 29 age and sex matched HCs by reverse transcriptase polymerase chain reaction. AAA growth was assessed by a median of three (interquartile range [IQR] 2, 3) repeat ultrasound scans over a median follow up of 1.1 (IQR 1.0, 2.0) years. The association between the miRNA and AAA diagnosis and growth was examined by regression and linear mixed effects analyses. The diagnostic and prognostic potential of the miRNAs were examined using area under the receiver operator characteristic curve (AUC), net re-classification index (NRI), and Cox hazard analyses.

RESULTS

In comparison with HCs, a model combining clinical risk factors, let-7b-5p and miR-548n had an AUC of 98.0% (95% confidence interval [CI] 95.6 - 100.0; p = .003) for diagnosing AAA, which was a significant improvement over clinical risk factors alone (NRI 1.74; 95% CI 1.61 - 1.87; p < .001). Compared with PAD, a model combining clinical risk factors and miR-548n had an AUC of 99.6% (95% CI 98.9 - 100.0, p = .037) for diagnosing AAA, which was a significant improvement over clinical risk factors alone (NRI 1.79, 95% CI 1.68 - 1.91; p < .001). In the longitudinal cohort, none of the miRNAs were able to predict the likelihood of reaching surgical threshold diameter better than clinical risk factors alone.

CONCLUSION

Serum let-7b-5p and miR548n significantly improved the ability to diagnose AAA. None of the miRNAs had independent prognosis value in predicting AAA growth.

Lantern-shaped flexible RNA origami for Smad4 mRNA delivery and growth suppression of colorectal cancer

mRNA delivery has shown high application value in the treatment of various diseases, but its effective delivery is still a major challenge at present. Herein, we propose a lantern-shaped flexible RNA origami for mRNA delivery. The origami is composed of a target mRNA scaffold and only two customized RGD-modified circular RNA staples, which can compress the mRNA into nanoscale and facilitate its endocytosis by cells. In parallel, the flexible structure of the lantern-shaped origami allows large regions of the mRNA to be exposed and translated, exhibiting a good balance between endocytosis and translation efficiency. The application of lantern-shaped flexible RNA origami in the context of the tumor suppressor gene, Smad4 in colorectal cancer models demonstrates promising potential for accurate manipulation of protein levels in in vitro and in vivo settings. This flexible origami strategy provides a competitive delivery method for mRNA-based therapies.

Application of the NanoString nCounter System as an Alternative Method to Investigate Molecular Mechanisms Involved in Host Plant Responses to Plasmodiophora brassicae

Clubroot, caused by the soilborne pathogen Plasmodiophora brassicae, is an important disease of canola (Brassica napus) and other crucifers. The recent application of RNA sequencing (RNA-seq) technologies to study P. brassicae−host interactions has generated large amounts of gene expression data, improving knowledge of the molecular mechanisms of pathogenesis and host resistance. Quantitative PCR (qPCR) analysis has been widely applied to examine the expression of a limited number of genes and to validate the results of RNA-seq studies, but may not be ideal for analyzing larger suites of target genes or increased sample numbers. Moreover, the need for intermediate steps such as cDNA synthesis may introduce variability that could affect the accuracy of the data generated by qPCR. Here, we report the validation of gene expression data from a previous RNA-seq study of clubroot using the NanoString nCounter System, which achieves efficient gene expression quantification in a fast and simple manner. We first confirm the robustness of the NanoString system by comparing the results with those generated by qPCR and RNA-seq and then discuss the importance of some candidate genes for resistance or susceptibility to P. brassicae in the host. The results show that the expression of genes measured using NanoString have a high correlation with the values obtained using the other two technologies, with R > 0.90 and p < 0.01, and the same expression patterns for most genes. The three methods (qPCR, RNA-seq, and NanoString) were also compared in terms of laboratory procedures, time, and cost. We propose that the NanoString nCounter System is a robust, sensitive, highly reproducible, and simple technology for gene expression analysis. NanoString could become a common alternative to qPCR to validate RNA-seq data or to create panels of genes for use as markers of resistance/susceptibility when plants are challenged with different P. brassicae pathotypes.

Study on the use of Nanostring nCounter to analyze RNA extracted from formalin-fixed-paraffin-embedded and fresh frozen bladder cancer tissues

Formalin-fixed paraffin-embedded (FFPE) tissue is the most common source of archived material for genomic medicine. However, FFPE tissue is suboptimal for high-throughput analyses, such as RNA sequencing, because the quality of nucleic acids in FFPE tissues is low. We compared RNA-seq with the nCounter system to evaluate use of FFPE tissue for genomic medicine. Twelve fresh frozen bladder cancer samples were analyzed by both RNA sequencing and nCounter, and matched FFPE samples, by nCounter. Gene-expression values obtained by these two platforms were compared by calculating Pearson correlation coefficients for each sample (across the set of matched genes) and for each matched gene (across the set of samples). For each sample, gene-expression levels measured by RNA sequencing highly correlated with those measured by nCounter (all Pearson's R > 0.8, P < 0.0001), as seen by hierarchical clustering. RNA sequencing results for fresh frozen tissues positively correlated with nCounter results for FFPE tissues (R ranged from 0.675 to 0.873, all P < 0.0001). Correlation and hierarchical-clustering analyses of nCounter data from the two specimens demonstrated a strong positive correlation between each group (R ranged from 0.779 to 0.977, all P < 0.0001). Our findings suggest that the nCounter system is useful for assaying archived-FFPE samples and that the gene-expression signatures obtained from FFPE samples represent those from fresh frozen tissues.

The role of CPT1A as a biomarker of breast cancer progression: a bioinformatic approach

Breast cancer is the commonest malignancy of women and with its incidence on the rise, the need to identify new targets for treatment is imperative. There is a growing interest in the role of lipid metabolism in cancer. Carnitine palmitoyl-transferase-1 (CPT-1); the rate limiting step in fatty acid oxidation, has been shown to be overexpressed in a range of tumours. There are three isoforms of CPT-1; A, B and C. It is CPT-1A that has been shown to be the predominant isoform which is overexpressed in breast cancer. We performed a bioinformatic analysis using readily available online platforms to establish the prognostic and predictive effects related to CPT-1A expression. These include the KM plotter, the Human Protein Atlas, the cBioPortal, the G2O, the MethSurvand the ROC plotter. A Network analysis was performed using the Oncomine platform and signalling pathways constituting the cancer hallmarks, including immune regulation as utilised by NanoString. The epigenetic pathways were obtained from the EpiFactor website. Spearman correlations (r) to determine the relationship between CPT-1A and the immune response were obtained using the TISIDB portal. Overexpression of CPT-1A largely confers a worse prognosis and CPT-1A progressively recruits a range of pathways as breast cancer progresses. CPT-1A's interactions with cancer pathways is far wider than previously realised and includes associations with epigenetic regulation and immune evasion pathways, as well as wild-type moderate to high penetrant genes involved in hereditary breast cancer. Although CPT-1A genomic alterations are detected in 9% of breast carcinomas, both the alteration and the metagene associated with it, confers a poor prognosis. CPT-1A expression can be utilised as a biomarker of disease progression and as a potential therapeutic target.

NOTCH1 mutation associates with impaired immune response and decreased relapse-free survival in patients with resected T1-2N0 laryngeal cancer

Background

Patients with early-stage laryngeal cancer, even stage T1-2N0, are at considerable risk of recurrence and death. The genetic and immunologic characteristics of recurrent laryngeal cancer remain unclear.

Methods

A total of 52 T1-2N0 laryngeal cancer patients were enrolled. Of these, 42 tissue samples were performed by targeted DNA sequencing, and 21 cases were performed by NanoString immuno-oncology targeted RNA sequencing to identify the distinct molecular bases and immunologic features associated with relapse in patients with early laryngeal cancer, respectively.

Results

To the best to our knowledge, we present for the first time an overview of the genomic mutation spectrum of early-stage laryngeal cancers. A total of 469 genomic alterations were detected in 211 distinct cancer-relevant genes, and the genes found to be mutated in more than five patients (>10%) included tumor protein p53 (TP53, 78.5%), FAT atypical cadherin 1 (FAT1, 26%), LDL receptor related protein 1B (LRP1B, 19%), cyclin dependent kinase inhibitor 2A (CDKN2A, 17%), tet methylcytosine dioxygenase 2 (TET2, 17%), notch receptor 1 (NOTCH1, 12%) and neuregulin 1 (NRG1, 12%). Recurrent laryngeal cancer demonstrated a higher tumor mutation burden (TMB), as well as higher LRP1B mutation and NOTCH1 mutation rates. Univariate and multivariate analyses revealed that high TMB (TMB-H) and NOTCH1 mutation are independent genetic factors that are significantly associated with shorter relapse-free survival (RFS). Simultaneously, the results of the transcriptome analysis presented recurrent tumors with NOTCH1 mutation displayed upregulation of the cell cycle pathway, along with decreased B cells score, T cells score, immune signature score and tumor-infiltrating lymphocytes (TILs) score. The Cancer Genome Atlas (TCGA)-laryngeal cancer dataset also revealed weakened immune response and impaired adhesion functions in NOTCH1-mutant patients.

Conclusions

Genomic instability and impaired immune response are key features of the immunosurveillance escape and recurrence of early laryngeal cancer after surgery. These findings revealed immunophenotypic attenuation in recurrent tumors and provided valuable information for improving the management of these high-risk patients. Due to the small number of patients in this study, these differences need to be further validated in a larger cohort.

Chimeric RNAs Discovered by RNA Sequencing and Their Roles in Cancer and Rare Genetic Diseases

Chimeric RNAs are transcripts that are generated by gene fusion and intergenic splicing events, thus comprising nucleotide sequences from different parental genes. In the past, Northern blot analysis and RT-PCR were used to detect chimeric RNAs. However, they are low-throughput and can be time-consuming, labor-intensive, and cost-prohibitive. With the development of RNA-seq and transcriptome analyses over the past decade, the number of chimeric RNAs in cancer as well as in rare inherited diseases has dramatically increased. Chimeric RNAs may be potential diagnostic biomarkers when they are specifically expressed in cancerous cells and/or tissues. Some chimeric RNAs can also play a role in cell proliferation and cancer development, acting as tools for cancer prognosis, and revealing new insights into the cell origin of tumors. Due to their abilities to characterize a whole transcriptome with a high sequencing depth and intergenically identify spliced chimeric RNAs produced with the absence of chromosomal rearrangement, RNA sequencing has not only enhanced our ability to diagnose genetic diseases, but also provided us with a deeper understanding of these diseases. Here, we reviewed the mechanisms of chimeric RNA formation and the utility of RNA sequencing for discovering chimeric RNAs in several types of cancer and rare inherited diseases. We also discussed the diagnostic, prognostic, and therapeutic values of chimeric RNAs.

A Clinically Applicable Gene Expression based Score predicts Resistance to Induction Treatment in Acute Myeloid Leukemia

Prediction of induction failure in AML is possible using cytogenetic data and a gene expression–based classifier.

Integration of PS29MRC in the clinical routine or trials may be facilitated by gene expression analysis with the NanoString platform.

Prediction of resistant disease at initial diagnosis of acute myeloid leukemia (AML) can be achieved with high accuracy using cytogenetic data and 29 gene expression markers (Predictive Score 29 Medical Research Council; PS29MRC). Our aim was to establish PS29MRC as a clinically usable assay by using the widely implemented NanoString platform and further validate the classifier in a more recently treated patient cohort. Analyses were performed on 351 patients with newly diagnosed AML intensively treated within the German AML Cooperative Group registry. As a continuous variable, PS29MRC performed best in predicting induction failure in comparison with previously published risk models. The classifier was strongly associated with overall survival. We were able to establish a previously defined cutoff that allows classifier dichotomization (PS29MRCdic). PS29MRCdic significantly identified induction failure with 59% sensitivity, 77% specificity, and 72% overall accuracy (odds ratio, 4.81; P = 4.15 × 10⁻¹⁰). PS29MRCdic was able to improve the European Leukemia Network 2017 (ELN-2017) risk classification within every category. The median overall survival with high PS29MRCdic was 1.8 years compared with 4.3 years for low-risk patients. In multivariate analysis including ELN-2017 and clinical and genetic markers, only age and PS29MRCdic were independent predictors of refractory disease. In patients aged ≥60 years, only PS29MRCdic remained as a significant variable. In summary, we confirmed PS29MRC as a valuable classifier to identify high-risk patients with AML. Risk classification can still be refined beyond ELN-2017, and predictive classifiers might facilitate clinical trials focusing on these high-risk patients with AML.

Multi-omics reveals clinically relevant proliferative drive associated with mTOR-MYC-OXPHOS activity in chronic lymphocytic leukemia

Chronic Lymphocytic Leukemia (CLL) has a complex pattern of driver mutations and much of its clinical diversity remains unexplained. We devised a method for simultaneous subgroup discovery across multiple data types and applied it to genomic, transcriptomic, DNA methylation and ex-vivo drug response data from 217 Chronic Lymphocytic Leukemia (CLL) cases. We uncovered a biological axis of heterogeneity strongly associated with clinical behavior and orthogonal to the known biomarkers. We validated its presence and clinical relevance in four independent cohorts (n=547 patients). We find that this axis captures the proliferative drive (PD) of CLL cells, as it associates with lymphocyte doubling rate, global hypomethylation, accumulation of driver aberrations and response to pro-proliferative stimuli. CLL-PD was linked to the activation of mTOR-MYC-oxidative phosphorylation (OXPHOS) through transcriptomic, proteomic and single cell resolution analysis. CLL-PD is a key determinant of disease outcome in CLL. Our multi-table integration approach may be applicable to other tumors whose inter-individual differences are currently unexplained.

Investigation of Neuropathology after Nerve Release in Chronic Constriction Injury of Rat Sciatic Nerve

Peripheral compressive neuropathy causes significant neuropathic pain, muscle weakness and prolong neuroinflammation. Surgical decompression remains the gold standard of treatment but the outcome is suboptimal with a high recurrence rate. From mechanical compression to chemical propagation of the local inflammatory signals, little is known about the distinct neuropathologic patterns and the genetic signatures after nerve decompression. In this study, controllable mechanical constriction forces over rat sciatic nerve induces irreversible sensorimotor dysfunction with sustained local neuroinflammation, even 4 weeks after nerve release. Significant gene upregulations are found in the dorsal root ganglia, regarding inflammatory, proapoptotic and neuropathic pain signals. Genetic profiling of neuroinflammation at the local injured nerve reveals persistent upregulation of multiple genes involving oxysterol metabolism, neuronal apoptosis, and proliferation after nerve release. Further validation of the independent roles of each signal pathway will contribute to molecular therapies for compressive neuropathy in the future.

Comprehensive and Computable Molecular Diagnostic Panel (C2Dx) From Small Volume Specimens for Precision Oncology: Molecular Subtyping of Non-Small Cell Lung Cancer From Fine Needle Aspirates

The Comprehensive, Computable NanoString Diagnostic gene panel (C2Dx) is a promising solution to address the need for a molecular pathological research and diagnostic tool for precision oncology utilizing small volume tumor specimens. We translate subtyping-related gene expression patterns of Non-Small Cell Lung Cancer (NSCLC) derived from public transcriptomic data which establish a highly robust and accurate subtyping system. The C2Dx demonstrates supreme performance on the NanoString platform using microgram-level FNA samples and has excellent portability to frozen tissues and RNA-Seq transcriptomic data. This workflow shows great potential for research and the clinical practice of cancer molecular diagnosis.

Using proteomic and transcriptomic data to assess activation of intracellular molecular pathways

Analysis of molecular pathway activation is the recent instrument that helps to quantize activities of various intracellular signaling, structural, DNA synthesis and repair, and biochemical processes. This may have a deep impact in fundamental research, bioindustry, and medicine. Unlike gene ontology analyses and numerous qualitative methods that can establish whether a pathway is affected in principle, the quantitative approach has the advantage of exactly measuring the extent of a pathway up/downregulation. This results in emergence of a new generation of molecular biomarkers-pathway activation levels, which reflect concentration changes of all measurable pathway components. The input data can be the high-throughput proteomic or transcriptomic profiles, and the output numbers take both positive and negative values and positively reflect overall pathway activation. Due to their nature, the pathway activation levels are more robust biomarkers compared to the individual gene products/protein levels. Here, we review the current knowledge of the quantitative gene expression interrogation methods and their applications for the molecular pathway quantization. We consider enclosed bioinformatic algorithms and their applications for solving real-world problems. Besides a plethora of applications in basic life sciences, the quantitative pathway analysis can improve molecular design and clinical investigations in pharmaceutical industry, can help finding new active biotechnological components and can significantly contribute to the progressive evolution of personalized medicine. In addition to the theoretical principles and concepts, we also propose publicly available software for the use of large-scale protein/RNA expression data to assess the human pathway activation levels.

microRNA regulation related to the protective effects of environmental enrichment against cocaine-seeking behavior

BACKGROUND

MicroRNAs (miRNAs) are "master post-transcriptional regulators" of gene expression. Here we investigate miRNAs involved in the incentive motivation for cocaine elicited by exposure to cocaine-associated cues.

METHODS

We conducted NanoString nCounter analyses of microRNA expression in the nucleus accumbens shell of male rats that had been tested for cue reactivity in a previous study. These rats had been trained to self-administer cocaine while living in isolate housing, then during a subsequent 21-day forced abstinence period they either stayed under isolate housing or switched to environmental enrichment (EE), as this EE intervention is known to decrease cocaine seeking. This allowed us to create groups of "high" and "low" cocaine seekers using a median split of cocaine-seeking behavior.

RESULTS

Differential expression analysis across high- and low-seekers identified 33 microRNAs that were differentially expressed in the nucleus accumbens shell. Predicted mRNA targets of these microRNAs are implicated in synaptic plasticity, neuronal signaling, and neuroinflammation signaling, and many are known addiction-related genes. Of the 33 differentially-expressed microRNAs, 8 were specifically downregulated in the low-seeking group and another set of 8 had expression levels that were significantly correlated with cocaine-seeking behavior.

CONCLUSION

These findings not only confirm the involvement of previously identified microRNAs (e.g., miR-212, miR-495) but also reveal novel microRNAs (e.g., miR-3557, miR-377) that alter, or are altered by, processes associated with cocaine-seeking behavior. Further research examining the mechanisms involved in these microRNA changes and their effects on signaling may reveal novel therapeutic targets for attenuating drug craving.

Micro-RNA: The darkhorse of cancer

The discovery of micro RNAs (miRNA) in cancer has opened up new vistas for researchers in recent years. Micro RNAs area set of small, endogenous, highly conserved, non-coding RNAs that control the expression of about 30% genes at post-transcriptional levels. Typically, microRNAs impede the translation and stability of messenger RNAs (mRNA), control genes associated with cellular processes namely inflammation, cell cycle regulation, stress response, differentiation, apoptosis, and migration. Compelling findings revealed that miRNA mutations or disruption correspond to diverse human cancers and suggest that miRNAs can function as tumor suppressors or oncogenes. Here we summarize the literature on these master regulators in clinical settings from last three decades as both abrupt cancer therapeutics and as an approach to sensitize tumors to chemotherapy. This review highlights (I) the prevailing perception of miRNA genomics, biogenesis, as well as function; (II) the significant advancements in regulatory mechanisms in the expression of carcinogenic genes; and (III) explains, how miRNA is utilized as a diagnostic and prognostic biomarker for the disease stage indicating survival as well as therapeutic targets in cancer.

Low MGMT digital expression is associated with a better outcome of IDH1 wildtype glioblastomas treated with temozolomide

INTRODUCTION

Glioblastoma (GBM) is the deadliest primary brain tumor. The standard treatment consists of surgery, radiotherapy, and temozolomide (TMZ). TMZ response is heterogeneous, and MGMT promoter (MGMTp) methylation has been the major predictive biomarker. We aimed to describe the clinical and molecular data of GBMs treated with TMZ, compare MGMT methylation with MGMT expression, and further associate with patient's outcome.

METHODS

We evaluate 112 FFPE adult GBM cases. IDH1 and ATRX expression was analyzed by immunohistochemistry, hotspot TERT promoter (TERTp) mutations were evaluated by Sanger or pyrosequencing, and MGMTp methylation was assessed by pyrosequencing and MGMT mRNA expression using the nCounter® Vantage 3D™ DNA damage and repair panel.

RESULTS

Of the 112 GBMs, 96 were IDH1^WT, and 16 were IDH1^MUT. Positive ATRX expression was found in 91.6% (88/96) of IDH^WT and 43.7% (7/16) of IDH^MUT. TERTp mutations were detected in 70.4% (50/71) of IDH^WT. MGMTp methylation was found in 55.5% (35/63) of IDH^WT and 84.6% (11/13) of IDH^MUT, and as expected, MGMTp methylation was significantly associated with a better response to TMZ. MGMT expression was inversely correlated with MGMTp methylation levels (- 0.506, p < 0.0001), and MGMT low expression were significantly associated with better patient survival. It was also observed that integrating MGMTp methylation and expression, significantly improved the prognostication value.

CONCLUSIONS

MGMT mRNA levels evaluated by digital expression were associated with the outcome of TMZ-treated GBM patients. The combination of MGMT methylation and mRNA expression may provide a more accurate prediction of TMZ response in GBM patients.

Transcriptomic Analysis of Age-Associated Periventricular Lesions Reveals Dysregulation of the Immune Response

White matter lesions (WML) are a common feature of the ageing brain associated with cognitive impairment. The gene expression profiles of periventricular lesions (PVL, n = 7) and radiologically-normal-appearing (control) periventricular white matter cases (n = 11) obtained from the Cognitive Function and Ageing Study (CFAS) neuropathology cohort were interrogated using microarray analysis and NanoString to identify novel mechanisms potentially underlying their formation. Histological characterisation of control white matter cases identified a subgroup (n = 4) which contained high levels of MHC-II immunoreactive microglia, and were classified as “pre-lesional.” Microarray analysis identified 2256 significantly differentially-expressed genes (p ≤ 0.05, FC ≥ 1.2) in PVL compared to non-lesional control white matter (1378 upregulated and 878 downregulated); 2649 significantly differentially-expressed genes in “pre-lesional” cases compared to PVL (1390 upregulated and 1259 downregulated); and 2398 significantly differentially-expressed genes in “pre-lesional” versus non-lesional control cases (1527 upregulated and 871 downregulated). Whilst histological evaluation of a single marker (MHC-II) implicates immune-activated microglia in lesion pathology, transcriptomic analysis indicates significant downregulation of a number of activated microglial markers and suggests established PVL are part of a continuous spectrum of white matter injury. The gene expression profile of “pre-lesional” periventricular white matter suggests upregulation of several signalling pathways may be a neuroprotective response to prevent the pathogenesis of PVL.

NanoString in the screening of genetic abnormalities associated with thyroid cancer

In the setting of cancer pathology, molecular characterization of tumors providing diagnostic and predictive information is acquiring more and more relevance. Moreover, the advent of innovative technologies continuously improves the knowledge of the molecular landscape of tumors and strengthens the links between clinics, tumor pathology and molecular features. In the clinical management of patients with thyroid nodules and thyroid tumors, the aid of molecular testing is encouraged but still not strongly recommended by current guidelines. Also for this reason this field of study is attracting much interest. The nCounter system is a relatively new technology based on a direct hybridization of fluorescent probes to specific nucleic acid targets, followed by digital measurement of signals; the reaction is highly multiplexable and results are robust and reproducible. This review reports and discusses the available data related to the application of this specific technique to thyroid nodules and thyroid tumors samples. The available data indicate that nCounter system represents a solid approach for the research of relevant diagnostic and prognostic biomarkers in thyroid pathology.

Age-Dependent Assessment of Genes Involved in Cellular Senescence, Telomere, and Mitochondrial Pathways in Human Lung Tissue of Smokers, COPD, and IPF: Associations With SARS-CoV-2 COVID-19 ACE2-TMPRSS2-Furin-DPP4 Axis

BACKGROUND

Aging is one of the key contributing factors for chronic obstructive pulmonary diseases (COPD) and other chronic inflammatory lung diseases. Here, we determined how aging contributes to the altered gene expression related to mitochondrial function, cellular senescence, and telomeric length processes that play an important role in the progression of COPD and idiopathic pulmonary fibrosis (IPF).

METHODS

Total RNA from the human lung tissues of non-smokers, smokers, and patients with COPD and IPF were processed and analyzed using a Nanostring platform based on their ages (younger: <55 years and older: >55 years).

RESULTS

Several genes were differentially expressed in younger and older smokers, and patients with COPD and IPF compared to non-smokers which were part of the mitochondrial biogenesis/function (HSPD1, FEN1, COX18, COX10, UCP2 & 3), cellular senescence (PCNA, PTEN, KLOTHO, CDKN1C, TNKS2, NFATC1 & 2, GADD45A), and telomere replication/maintenance (PARP1, SIRT6, NBN, TERT, RAD17, SLX4, HAT1) target genes. Interestingly, NOX4 and TNKS2 were increased in the young IPF as compared to the young COPD patients. Genes in the mitochondrial dynamics and quality control mechanisms like FIS1 and RHOT2 were decreased in young IPF compared to their age matched COPD subjects. ERCC1 and GADD45B were higher in young COPD as compared to IPF. Aging plays an important role in various infectious diseases including the SARS-CoV-2 infection. Lung immunoblot analysis of smokers, COPD and IPF subjects revealed increased abundance of proteases and receptor/spike protein like TMPRSS2, furin, and DPP4 in association with a slight increase in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) receptor ACE2 levels.

CONCLUSIONS

Overall, these findings suggest that altered transcription of target genes that regulate mitochondrial function, cellular senescence, and telomere attrition in the pathobiology of lung aging in COPD and IPF is associated with alterations in SARS-CoV-2 ACE2-TMPRSS2-Furin-DPP4 axis as pharmacological targets for COVID-19.

Literature review and methodological considerations for understanding circulating risk biomarkers following trauma exposure

Exposure to traumatic events is common. While many individuals recover following trauma exposure, a substantial subset develop adverse posttraumatic neuropsychiatric sequelae (APNS) such as posttraumatic stress, major depression, and regional or widespread chronic musculoskeletal pain. APNS cause substantial burden to the individual and to society, causing functional impairment and physical disability, risk for suicide, lost workdays, and increased health care costs. Contemporary treatment is limited by an inability to identify individuals at high risk of APNS in the immediate aftermath of trauma, and an inability to identify optimal treatments for individual patients. Our purpose is to provide a comprehensive review describing candidate blood-based biomarkers that may help to identify those at high risk of APNS and/or guide individual intervention decision-making. Such blood-based biomarkers include circulating biological factors such as hormones, proteins, immune molecules, neuropeptides, neurotransmitters, mRNA, and noncoding RNA expression signatures, while we do not review genetic and epigenetic biomarkers due to other recent reviews of this topic. The current state of the literature on circulating risk biomarkers of APNS is summarized, and key considerations and challenges for their discovery and translation are discussed. We also describe the AURORA study, a specific example of current scientific efforts to identify such circulating risk biomarkers and the largest study to date focused on identifying risk and prognostic factors in the aftermath of trauma exposure.

Circulating Tumour DNAs and Non-Coding RNAs as Liquid Biopsies for the Management of Colorectal Cancer Patients

Circulating tumour DNAs and non-coding RNAs present in body fluids have been under investigation as tools for cancer diagnosis, disease monitoring, and prognosis for many years. These so-called liquid biopsies offer the opportunity to obtain information about the molecular make-up of a cancer in a minimal invasive way and offer the possibility to implement theranostics for precision oncology. Furthermore, liquid biopsies could overcome the limitations of tissue biopsies in capturing the complexity of tumour heterogeneity within the primary cancer and among different metastatic sites. Liquid biopsies may also be implemented to detect early tumour formation or to monitor cancer relapse of response to therapy with greater sensitivity compared with the currently available protein-based blood biomarkers. Most colorectal cancers are often diagnosed at late stages and have a high mortality rate. Hence, biomolecules as nucleic acids present in liquid biopsies might have prognostic potential and could serve as predictive biomarkers for chemotherapeutic regimens. This review will focus on the role of circulating tumour DNAs and non-coding RNAs as diagnostic, prognostic, and predictive biomarkers in the context of colorectal cancer.

Age-dependent assessment of genes involved in cellular senescence, telomere and mitochondrial pathways in human lung tissue of smokers, COPD and IPF: Associations with SARS-CoV-2 COVID-19 ACE2-TMPRSS2-Furin-DPP4 axis

Aging is one of the key contributing factors for chronic obstructive pulmonary diseases (COPD) and other chronic inflammatory lung diseases. Cigarette smoke is a major etiological risk factor that has been shown to alter cellular processes involving mitochondrial function, cellular senescence and telomeric length. Here we determined how aging contribute to the alteration in the gene expression of above mentioned cellular processes that play an important role in the progression of COPD and IPF. We hypothesized that aging may differentially alter the expression of mitochondrial, cellular senescence and telomere genes in smokers and patients with COPD and IPF compared to non-smokers. Total RNA from human lung tissues from non-smokers, smokers, and patients with COPD and IPF were processed and analyzed based on their ages (younger: <55 yrs and older: >55 yrs). NanoString nCounter panel was used to analyze the gene expression profiles using a custom designed codeset containing 112 genes including 6 housekeeping controls (mitochondrial biogenesis and function, cellular senescence, telomere replication and maintenance). mRNA counts were normalized, log2 transformed for differential expression analysis using linear models in the limma package (R/Bioconductor). Data from non-smokers, smokers and patients with COPD and IPF were analyzed based on the age groups (pairwise comparisons between younger vs. older groups). Several genes were differentially expressed in younger and older smokers, and patients with COPD and IPF compared to non-smokers which were part of the mitochondrial biogenesis/function (HSPD1, FEN1, COX18, COX10, UCP2 & 3), cellular senescence (PCNA, PTEN, KLOTHO, CDKN1C, TNKS2, NFATC1 & 2, GADD45A) and telomere replication/maintenance (PARP1, SIRT6, NBN, TERT, RAD17, SLX4, HAT1) target genes. Interestingly, NOX4 and TNKS2 were increased in the young IPF as compared to the young COPD patients. Genes in the mitochondrial dynamics and other quality control mechanisms like FIS1 and RHOT2 were decreased in young IPF compared to their age matched COPD subjects. ERCC1 (Excision Repair Cross-Complementation Group 1) and GADD45B were higher in young COPD as compared to IPF. Aging plays an important role in various infectious diseases. Elderly patients with chronic lung disease and smokers were found to have high incidence and mortality rates in the current pandemic of SARS-CoV-2 infection. Immunoblot analysis in the lung homogenates of smokers, COPD and IPF subjects revealed increased protein abundance of important proteases and spike proteins like TMPRSS2, furin and DPP4 in association with a slight increase in SARS-CoV-2 receptor ACE2 levels. This may further strengthen the observation that smokers, COPD and IPF subjects are more prone to COVID-19 infection. Overall, these findings suggest that altered transcription of target genes that regulate mitochondrial function, cellular senescence, and telomere attrition add to the pathobiology of lung aging in COPD and IPF and other smoking-related chronic lung disease in associated with alterations in SARS-CoV-2 ACE2-TMPRSS2-Furin-DPP4 axis for COVID-19 infection.

Age-dependent assessment of genes involved in cellular senescence, telomere and mitochondrial pathways in human lung tissue of smokers, COPD and IPF: Associations with SARS-CoV-2 COVID-19 ACE2-TMPRSS2-Furin-DPP4 axis

Aging is one of the key contributing factors for chronic obstructive pulmonary diseases (COPD) and other chronic inflammatory lung diseases. Cigarette smoke is a major etiological risk factor that has been shown to alter cellular processes involving mitochondrial function, cellular senescence and telomeric length. Here we determined how aging contribute to the alteration in the gene expression of above mentioned cellular processes that play an important role in the progression of COPD and IPF. We hypothesized that aging may differentially alter the expression of mitochondrial, cellular senescence and telomere genes in smokers and patients with COPD and IPF compared to non-smokers. Total RNA from human lung tissues from non-smokers, smokers, and patients with COPD and IPF were processed and analyzed based on their ages (younger: <55 yrs and older: >55 yrs). NanoString nCounter panel was used to analyze the gene expression profiles using a custom designed codeset containing 112 genes including 6 housekeeping controls (mitochondrial biogenesis and function, cellular senescence, telomere replication and maintenance). mRNA counts were normalized, log2 transformed for differential expression analysis using linear models in the limma package (R/Bioconductor). Data from non-smokers, smokers and patients with COPD and IPF were analyzed based on the age groups (pairwise comparisons between younger vs. older groups). Several genes were differentially expressed in younger and older smokers, and patients with COPD and IPF compared to non-smokers which were part of the mitochondrial biogenesis/function (HSPD1, FEN1, COX18, COX10, UCP2 & 3), cellular senescence (PCNA, PTEN, KLOTHO, CDKN1C, TNKS2, NFATC1 & 2, GADD45A) and telomere replication/maintenance (PARP1, SIRT6, NBN, TERT, RAD17, SLX4, HAT1) target genes. Interestingly, NOX4 and TNKS2 were increased in the young IPF as compared to the young COPD patients. Genes in the mitochondrial dynamics and other quality control mechanisms like FIS1 and RHOT2 were decreased in young IPF compared to their age matched COPD subjects. ERCC1 (Excision Repair Cross-Complementation Group 1) and GADD45B were higher in young COPD as compared to IPF. Aging plays an important role in various infectious diseases. Elderly patients with chronic lung disease and smokers were found to have high incidence and mortality rates in the current pandemic of SARS-CoV-2 infection. Immunoblot analysis in the lung homogenates of smokers, COPD and IPF subjects revealed increased protein abundance of important proteases and spike proteins like TMPRSS2, furin and DPP4 in association with a slight increase in SARS-CoV-2 receptor ACE2 levels. This may further strengthen the observation that smokers, COPD and IPF subjects are more prone to COVID-19 infection. Overall, these findings suggest that altered transcription of target genes that regulate mitochondrial function, cellular senescence, and telomere attrition add to the pathobiology of lung aging in COPD and IPF and other smoking-related chronic lung disease in associated with alterations in SARS-CoV-2 ACE2-TMPRSS2-Furin-DPP4 axis for COVID-19 infection.

Application of NanoString technologies in angioimmunoblastic T cell lymphoma

BACKGROUND

Angioimmunoblastic T-cell lymphoma (AITL) is an aggressive disease. Most cancer diagnoses are determined by anatomical histology. Therefore, many samples are stored in FFPE blocks for H&E staining. However, RNAs extracted from the FFPE block have a high level of fragmentation, making it difficult to perform accurate DEG analysis using RNA sequencing.

OBJECTIVE

To overcome fragmented RNA's drawback in NGS application, we applied the NanoString nCounter^® technique of hybridization method that can be used for DEG analysis without PCR amplification.

METHODS

We characterized the gene expression profiling of AITLs though transcriptome analysis based on the nCounter^® PanCancer IO 360™ Panel and NanoString platform. To perform the analysis of differential expression gene (DEG) profiles in AITLs, we compared the NanoString data from eight AITL patients with a healthy control donor.

RESULTS

Ninety-one genes were up-regulated and six genes were down-regulated in AITLs compared to control. The Gene Ontology (GO) analysis of 97-DEGs revealed that they were closely related to cytokine, MAPK cascade, leukocyte differentiation, and immune response, suggesting that this affect the immune system. In addition, KEGG analysis revealed that AITL DEGs were found to be highly involved in cytokine-cytokine receptor interaction and PI3K-Akt signaling pathway.

CONCLUSION

We believe that comprehensive multiplex studies, along with NanoString analysis, may be helpful to understand the molecular mechanisms of AITL, including mutations, gene expression, and protein expression studies.

Single-molecule analysis of nucleic acid biomarkers - A review

Nucleic acids are important biomarkers for disease detection, monitoring, and treatment. Advances in technologies for nucleic acid analysis have enabled discovery and clinical implementation of nucleic acid biomarkers. However, challenges remain with technologies for nucleic acid analysis, thereby limiting the use of nucleic acid biomarkers in certain contexts. Here, we review single-molecule technologies for nucleic acid analysis that can be used to overcome these challenges. We first discuss the various types of nucleic acid biomarkers important for clinical applications and conventional technologies for nucleic acid analysis. We then discuss technologies for single-molecule in vitro and in situ analysis of nucleic acid biomarkers. Finally, we discuss other ultra-sensitive techniques for nucleic acid biomarker detection.