Immunological subtyping of salivary gland cancer identifies histological origin-specific tumor immune microenvironment.

Gene expression analysis enhances proper cancer subtyping, a better understanding of the molecular characteristics of cancer, and strategies for precision medicine. However, salivary gland cancer (SGC) subtyping remains largely unexplored because of its rarity and diverse histopathological and immunological characteristics. This study aimed to determine whether the histological origin and immunological characteristics of SGC subtypes are intrinsic tumor immunity factors. We performed immune profiling of 94 RNA-seq of SGC tissues and found that the SGCs that originated from the excretory duct (ED), such as the salivary duct and mucoepidermoid carcinomas, exhibit higher immunity than those from the intercalated duct (ID), such as the adenoid cystic and myoepithelial carcinomas, based on the computationally predicted immune score (p < 0.001), immune cell enrichment in the tumor immune microenvironment (TIME) (p < 0.001), T-cell receptor diversity (p < 0.001), and expression of signal I (major histocompatibility complex, MHC, p < 0.001) and signal II (co-stimulatory, p < 0.001 and co-inhibitory, p < 0.001) genes. Further analysis revealed that tolerogenic dendritic cell-induced dysfunctional T-cell populations and T-cell exclusion in the TIME are the major immune evasive mechanisms of the ED-and ID-derived SGCs, respectively.

Characterizing intrinsic molecular features of the immune subtypes of salivary mucoepidermoid carcinoma.

INTRODUCTION: Characterizing the tumor microenvironment (TME) and immune landscape of cancer has been a promising step towards discovering new therapeutic biomarkers and guiding precision medicine; however, its application in mucoepidermoid carcinoma (MEC) has been sparse. Here, we conducted a comprehensive study to understand the properties of the TME and immune profiles of MEC. METHOD: 20 patients with MEC were collected from Yonsei Head and Neck Cancer Centre, Yonsei University, South Korea. Total RNA sequencing was conducted to determine gene expression profiles. Bioinformatic and immunoinformatic analyses were applied to characterize the TME and identify immunophenotypic subgroups, and to investigate the molecular features that explain the distinct phenotypes. RESULTS: The MEC samples were subdivided into two groups, immune hot and immune cold, based on the heterogenous immune cell-infiltration and activation level. The immune-hot subgroup exhibited a higher level of immune activity, including T cell infiltration, cytolytic score, IFN-γ, antigen-presenting machinery, and immune modulator genes. Further characterizing molecular features of two subgroups, downregulation of lipid metabolic regulators, including MLXIPL and FASN, and the migration of chemokines and leukocytes were observed, respectively. And, Group-specific expression of immune checkpoint molecules, such as TIGIT, PD-L2, and CTLA-4, was observed in the immune-hot group, which can be exploited as a potential immunotherapeutic biomarker. CONCLUSIONS: Immunophenotypically heterogeneous MEC subgroups analysis has shown distinctive molecular characteristics and provided potential treatment options. These findings yield new insights into TME of MEC and may help next step to study this uncharted cancer.

HLA-I-restricted CD8+ T cell immunity may accelerate tumorigenesis in conjunction with VHL inactivation.

CD8+ T cells recognize and kill tumor cells with HLA-I tumor antigens in early tumorigenesis, the efficiency of which differs according to antigen-recognition coverage, as shown in earlier tumor onset in HLA-I homozygosity. However, the universality of these associations remains unknown. Here, we assessed the tumor type and driver mutation specificity in the association between tumor onset age and HLA-I zygosity. Statistical analyses identified an unexpected negative relationship in tumors with VHL biallelic loss, wherein HLA-I heterozygosity was associated with earlier tumor onset, while all others showed either no or a positive association. Testing on an independent dataset reproduced the VHL-dependent acceleration of tumor onset in the HLA-I heterozygous group, confirming the association. Further speculation proposed VEGF-A-mediated T cell exhaustion under VHL inactivation as a potential mechanism. Our findings suggest that CD8+ T cell immunity in early tumor suppression can be conditional to the genetic status of tumors and may even lead to adverse consequences.

Ethyl Acetate Fractions of Papaver rhoeas L. and Papaver nudicaule L. Exert Antioxidant and Anti-Inflammatory Activities.

Abnormal inflammation and oxidative stress are involved in various diseases. Papaver rhoeas L. possesses various pharmacological activities, and a previously reported analysis of the anti-inflammatory effect of P. nudicaule ethanol extracts and alkaloid profiles of the plants suggest isoquinoline alkaloids as potential pharmacologically active compounds. Here, we investigated anti-inflammatory and antioxidant activities of ethyl acetate (EtOAc) fractions of P. nudicaule and P. rhoeas extracts in lipopolysaccharide (LPS)-stimulated RAW264.7 cells. EtOAc fractions of P. nudicaule and P. rhoeas compared to their ethanol extracts showed less toxicity but more inhibitory activity against LPS-induced nitric oxide production. Moreover, EtOAc fractions lowered the LPS-induced production of proinflammatory molecules and cytokines and inhibited LPS-activated STAT3 and NF-κB, and additionally showed significant free radical scavenging activity and decreased LPS-induced reactive oxygen species and oxidized glutathione. EtOAc fractions of P. nudicaule increased the expression of HO-1, GCLC, NQO-1, and Nrf2 in LPS-stimulated cells and that of P. rhoeas enhanced NQO-1. Furthermore, metabolomic and biochemometric analyses of ethanol extracts and EtOAc fractions indicated that EtOAc fractions of P. nudicaule and P. rhoeas have potent anti-inflammatory and antioxidant activities, further suggesting that alkaloids in EtOAc fractions are potent active molecules of tested plants.

Development of a program for in silico optimized selection of oligonucleotide-based molecular barcodes.

Short DNA oligonucleotides (~4 mer) have been used to index samples from different sources, such as in multiplex sequencing. Presently, longer oligonucleotides (8-12 mer) are being used as molecular barcodes with which to distinguish among raw DNA molecules in many high-tech sequence analyses, including low-frequent mutation detection, quantitative transcriptome analysis, and single-cell sequencing. Despite some advantages of using molecular barcodes with random sequences, such an approach, however, makes it impossible to know the exact sequences used in an experiment and can lead to inaccurate interpretation due to misclustering of barcodes arising from the occurrence of unexpected mutations in the barcodes. The present study introduces a tool developed for selecting an optimal barcode subset during molecular barcoding. The program considers five barcode factors: GC content, homopolymers, simple sequence repeats with repeated units of dinucleotides, Hamming distance, and complementarity between barcodes. To evaluate a selected barcode set, penalty scores for the factors are defined based on their distributions observed in random barcodes. The algorithm employed in the program comprises two steps: i) random generation of an initial set and ii) optimal barcode selection via iterative replacement. Users can execute the program by inputting barcode length and the number of barcodes to be generated. Furthermore, the program accepts a user's own values for other parameters, including penalty scores, for advanced use, allowing it to be applied in various conditions. In many test runs to obtain 100000 barcodes with lengths of 12 nucleotides, the program showed fast performance, efficient enough to generate optimal barcode sequences with merely the use of a desktop PC. We also showed that VFOS has comparable performance, flexibility in program running, consideration of simple sequence repeats, and fast computation time in comparison with other two tools (DNABarcodes and FreeBarcodes). Owing to the versatility and fast performance of the program, we expect that many researchers will opt to apply it for selecting optimal barcode sets during their experiments, including next-generation sequencing.