The disease burden of Oral Squamous Cell Carcinoma (OSCC) is rising day-by-day and is expected to rise 62 % through 2035. The chewing of tobacco, areca nut, and betel leaf, poor oral hygiene, and chronic infection are common risk factors of OSCC, but genetic and epigenetic factors also contribute equally. MicroRNAs (miRNAs) are comprised of small, non-coding endogenous RNA that regulate a plethora of biological activities by targeting messenger RNA through degradation or inhibition. Single Nucleotide Polymorphisms (SNPs) in miRNA genes can regulate the development and progression of OSCC. The present study aimed to determine the association between SNPs in miRNA genes (miRSNPs) with the risk of OSCC. A case-control study involving 225 histo-pathologically confirmed OSCC cases and 225 healthy controls was conducted, where 25 miRSNPs were analyzed by iPLEX MassArray analysis. A SNP rs12220909 in MIR4293 showed a highly protective effect (CC vs GG, OR = 0.0431, 95%CI = 0.005-0.323, p = 3e-6). Whereas three SNPs, namely, rs4705342 in MIR143 (CC vs TT, OR = 2.25, 95%CI = 2.00-2.53, p = 0.0008), rs531564 in MIR124 (CC vs GG, OR = 24.18, 95%CI = 3.22-181.37, p = 3e-6), and rs3746444 in MIR499 (AA vs GG, OR = 2.01, 95%CI = 1.32-3.05, p = 0.001) were significantly associated with a higher risk of OSCC. Additionally, NanoString-based nCounter miRNA expression profiling revealed that miR-499a (Log2FC = -1.07), and miR-143 (Log2FC = -1.56) were aberrantly expressed in OSCC tissue. Taken together, the above miSNPs may contribute to the high incidence of OSCC in central India. However, further studies with large cohorts and ethnic stratification are required to validate our findings.

Archive tissues are the most available source of human tissues useful for molecular analysis in translational research. The main issues for those specimens are the modification and degradation of biomolecules, namely proteins, DNA, and RNA. In the last decade, several high-throughput analytical methods have been applied to archive tissues. Although histological tissues are fixed in neutral-buffered formalin nowadays, in the recent past, Bouin\'s solution was also used in tissue processing. The present study aims to investigate the feasibility of nCounter Nanostring hybridization in quantifying mRNA in highly degraded samples, such as Bouin\'s fixed and paraffin-embedded (BFPE) tissues, in comparison to the standard formalin-fixed and paraffin-embedded (FFPE) tissues as a source of RNA. A total of 16 paraffin-embedded tissue blocks from eight patients were analyzed (8 were FFPE and 8 were BEPE). Nanostring technology was applied to 300 ng of each RNA sample, whereas 360 ng of the same templates were retrotranscribed and submitted to qPCR and ddPCR. Our results show that the Nanostring technology outperforms the reference methods (ddPCR and qPCR) in detecting target mRNA in FFPE and BFPE samples. However, even Nanostring technology does not escape the limitation imposed by the degradation of the RNA templates, which could lead to misleading conclusions on the gene expression level.

NanoString nCounter is a medium-throughput technology used in mRNA and miRNA differential expression studies. It offers several advantages, including the absence of an amplification step and the ability to analyze low-grade samples. Despite its considerable strengths, the popularity of the nCounter platform in experimental research stabilized in 2022 and 2023, and this trend may continue in the upcoming years. Such stagnation could potentially be attributed to the absence of a standardized analytical pipeline or the indication of optimal processing methods for nCounter data analysis. To standardize the description of the nCounter data analysis workflow, we divided it into five distinct steps: data pre-processing, quality control, background correction, normalization and differential expression analysis. Next, we evaluated eleven R packages dedicated to nCounter data processing to point out functionalities belonging to these steps and provide comments on their applications in studies of mRNA and miRNA samples.

Colorectal cancer (CRC) is one of the most prevalent cancers and the second leading cause of cancer deaths in developed countries. Early CRC may have no symptoms and symptoms usually appear with more advanced diseases. Regular screening can identify people who are at increased risk of CRC in order to offer earlier treatment. A cost-effective non-invasive platform for the screening and monitoring of CRC patients allows early detection and appropriate treatment of the disease, and the timely application of adjuvant therapy after surgical operation is needed. In this study, a cohort of 71 plasma samples that include 48 colonoscopy- and histopathology-confirmed CRC patients with TNM stages I to IV were recruited between 2017 and 2019. Plasma mRNA profiling was performed in CRC patients using NanoString nCounter. Normalized data were analyzed using a Mann-Whitney U test to determine statistically significant differences between samples from CRC patients and healthy subjects. A multiple-group comparison of clinical phenotypes was performed using the Kruskal-Wallis H test for statistically significant differences between multiple groups. Among the 27 selected circulating mRNA markers, all of them were found to be overexpressed (gene expression fold change > 2) in the plasma of patients from two or more CRC stages. In conclusion, NanoString-based targeted plasma CRC-associated mRNAs circulating the marker panel that can significantly distinguish CRC patients from a healthy population were developed for the non-invasive diagnosis of CRC using peripheral blood samples.

Regulatory B cells (Bregs) suppress antitumor immunity by producing anti-inflammatory cytokines such as transforming growth factor β (TGF-β) and interleukin-10 (IL-10) and promoting tumor growth. It is unknown whether diffuse large B-cell lymphoma (DLBCL), a common subtype of B-cell malignancy, exhibits characteristics similar to those of Bregs. This study aimed to clarify the features of DLBCLs carrying Breg markers. In 123 DLBCL cases, we evaluated TGF-β and IL-10 expression in tumor biopsy samples using immunohistochemical staining and retrospectively analyzed their clinicopathological characteristics. Fifteen cases (12.2 %) classified as Breg-type DLBCL were positive for both TGF-β and IL-10. Breg-type DLBCL is mainly classified as having activated B cell-like cells of origin. Breg-type DLBCL cases showed significantly worse progression-free survival and overall survival (OS) than other DLBCL cases (P = 0.0016 and P = 0.042, respectively). In multivariate analysis, Breg-type DLBCL significantly affected OS (hazard ratio, 3.13; 95 % confidence interval 1.15-8.55; P = 0.025). Gene expression analysis showed that the expression of follicular dendritic cell-associated genes (FCER2, PIK3CD, FOXO1) was downregulated in Breg-type DLBCLs compared to other DLBCLs. These results suggest that the double expression of Breg markers, TGF-β and IL-10, in tumor cells indicates a poor prognosis in DLBCL patients. Further studies evaluating genomic abnormalities could confirm the characteristics of Breg-type DLBCL.

Protein glycosylation is an essential post-translational modification in all domains of life. Its impairment in humans can result in severe diseases named congenital disorders of glycosylation (CDGs). Most of the glycosyltransferases (GTs) responsible for proper glycosylation are polytopic membrane proteins that represent challenging targets in proteomics. We established a multiple reaction monitoring (MRM) assay to comprehensively quantify GTs involved in the processes of N-glycosylation and O- and C-mannosylation in the endoplasmic reticulum. High robustness was achieved by using an enriched membrane protein fraction of isotopically labeled HEK 293T cells as an internal protein standard. The analysis of primary skin fibroblasts from eight CDG type I patients with impaired ALG1, ALG2, and ALG11 genes, respectively, revealed a substantial reduction in the corresponding protein levels. The abundance of the other GTs, however, remained unchanged at the transcript and protein levels, indicating that there is no fail-safe mechanism for the early steps of glycosylation in the endoplasmic reticulum. The established MRM assay was shared with the scientific community via the commonly used open source Skyline software environment, including Skyline Batch for automated data analysis. We demonstrate that another research group could easily reproduce all analysis steps, even while using different LC-MS hardware.

Dermatomyositis (DM), antisynthetase syndrome (AS), immune-mediated necrotizing myopathy (IMNM), and inclusion body myositis (IBM) are four major types of idiopathic inflammatory myopathy (IIM). Muscle biopsies from each type of IIM have unique transcriptomic profiles. MicroRNAs (miRNAs) target messenger RNAs (mRNAs), thereby regulating their expression and modulating transcriptomic profiles. In this study, 18 DM, 12 IMNM, 6 AS, 6 IBM, and 6 histologically normal muscle biopsies underwent miRNA profiling using the NanoString nCounter system. Eleven miRNAs were exclusively differentially expressed in DM compared to controls, seven miRNAs were only differentially expressed in AS, and nine miRNAs were specifically upregulated in IBM. No differentially expressed miRNAs were identified in IMNM. We also analyzed miRNA-mRNA associations to identify putative targets of differentially expressed miRNAs. In DM and AS, these were predominantly related to inflammation and cell cycle progression. Moreover, our analysis showed an association between miR-30a-3p, miR-30e-3p, and miR-199b-5p downregulation in DM and the upregulation of target genes induced by type I interferon. In conclusion, we show that muscle biopsies from DM, AS, and IBM patients have unique miRNA signatures and that these miRNAs might play a role in regulating the expression of genes known to be involved in IIM pathogenesis.

BACKGROUND: Meibomian gland dysfunction (MGD) is one of the most common conditions in ophthalmic practice and the most frequent cause of evaporative dry eye disease (DED). However, the immune mechanisms leading to this pathology are not fully understood and the diagnostic tests available are limited. Here, we used the nCounter technology to analyze immune gene expression in DED-MGD that can be used for developing diagnostic signatures for DED.
METHODS: Conjunctival cell samples were obtained by aspiration from patients with DED-MGD (n = 27) and asymptomatic controls (n = 22). RNA was purified, converted to cDNA, preamplified and analyzed using the Gene Expression Human Immune V2 panel (NanoString), which includes 579 target and 15 housekeeping genes. A machine learning (ML) algorithm was applied to design a signature associated with DED-MGD.
RESULTS: Forty-five immune genes were found upregulated in DED-MGD vs. controls, involved in eight signaling pathways, IFN I/II, MHC class I/II, immunometabolism, B cell receptor, T Cell receptor, and T helper-17 (Th-17) differentiation. Additionally, statistically significant correlations were found between 31 genes and clinical characteristics of the disease such as lid margin or tear osmolarity (Pearson\'s r < 0.05). ML analysis using a recursive feature elimination (RFE) algorithm selected a 4-gene mRNA signature that discriminated DED-MGD from control samples with an area under the ROC curve (AUC ROC) of 0.86 and an accuracy of 77.5%.
CONCLUSIONS: Multiplexed mRNA analysis of conjunctival cells can be used to analyze immune gene expression patterns in patients with DED-MGD and to generate diagnostic signatures.

UNASSIGNED: Glioblastoma (GBM), isocitrate dehydrogenase (IDH) wild-type (IDH wt), and grade 4 astrocytomas, IDH mutant (IDH mut), are the most common and aggressive primary malignant brain tumors in adults. A better understanding of the tumor immune microenvironment may provide new biomarkers and therapeutic opportunities.
UNASSIGNED: We aimed to evaluate the expression profile of 730 immuno-oncology-related genes in patients with IDH wt GBM and IDH mut tumors and identify prognostic biomarkers and a gene signature associated with patient survival.
UNASSIGNED: RNA was isolated from formalin-fixed, paraffin-embedded sections of 99 tumor specimens from patients treated with standard therapy. Gene expression profile was assessed using the Pan-Cancer Immune Profiling Panel (Nanostring Technologies, Inc., Seattle, WA, USA). Data analysis was performed using nSolverSoftware and validated in The Cancer Genome Atlas. In addition, we developed a prognostic signature using the cox regression algorithm (Least Absolute Shrinkage and Selection Operator).
UNASSIGNED: We found 88 upregulated genes, high immunological functions, and a high macrophage score in IDH wt GBM compared to IDH mut tumors. Regarding IDH wt GBM, we found 24 upregulated genes in short-term survivors (STS) and overexpression of CD274 (programmed death-ligand 1, PD-L1). Immune pathways, CD45, cytotoxic, and macrophage scores were upregulated in STS. Two different prognostic groups were found based on the 12-gene signature (CXCL14, PSEN2, TNFRSF13C, IL13RA1, MAP2K1, TNFSF14, THY1, CTSL, ITGAE, CHUK, CD207, and IFITM1).
UNASSIGNED: The elevated expression of immune-oncology-related genes was associated with worse outcome in IDH wt GBM patients. Increased immune functions, CD45, cytotoxic cells, and macrophage scores were associated with a more aggressive phenotype and may provide promising possibilities for therapy. Moreover, a 12 gene-based signature could predict patients\' prognosis.

The gene expression analysis of formalin-fixed paraffin-embedded (FFPE) tissues is often hampered by poor RNA quality, which results from the oxidation, cross-linking and other chemical modifications induced by the inclusion in paraffin. Yet, FFPE samples are a valuable source for molecular studies and can provide great insights into disease progression and prognosis. With the advancement of genomic technologies, new methods have been established that offer reliable and accurate gene expression workflows on samples of poor quality. NanoString is a probe-based technology that allows the direct counting of the mRNA transcripts and can be applied to degraded samples. Here, we have tested 2 RNA extraction methods for FFPE samples, and we have performed a titration experiment to evaluate the impact of RNA degradation and RNA input on the gene expression profiles assessed using the NanoString IO360 panel. We have selected FFPE samples of different DV200 values and assessed them on the nCounter platform with 2 different amounts of input RNA. This study concludes that the nCounter is a robust and reliable platform to assess the gene expression of RNA samples with DV200 > 30%; its robustness and ease of use could be of particular benefit to clinical settings.