miR‑32‑5p suppresses the proliferation and migration of pancreatic adenocarcinoma cells by targeting TLDC1

LncRNA FEZF1-AS1 facilitates cisplatin resistance in non-small cell lung cancer through modulating the miR-32-5p-glutaminase axis

Non-small cell lung cancer (NSCLC) is one of the prevalent malignancies. Cisplatin (CDDP) is a conventional chemotherapeutic agent against NSCLC. However, inherent and acquired chemoresistance limited the effectiveness of cisplatin in treatment of NSCLC. This study aimed to investigate the roles and underlying mechanisms of lncRNA-FEZF1-AS1 in mediating cisplatin sensitivity in NSCLC. We found that FEZF1-AS1 levels were significantly higher in lung cancer patients and cell lines. Blocking FEZF1-AS1 sensitized lung cancer cells to cisplatin. Additionally, both glutamine metabolism and FEZF1-AS1 were significantly elevated in cisplatin resistant NSCLC cell lines, A549/CDDP R and SK-MES-1 CDDP/R. Analysis using bioinformatics, RNA pull-down assay and luciferase assay demonstrated that FEZF1-AS1 sponged miR-32-5p, which acted as a tumor suppressor in NSCLC. Glutaminase (GLS), a key enzyme in the glutamine metabolism, was predicted and validated as the direct target of miR-32-5p in NSCLC cells. Inhibiting glutamine metabolism or reducing glutamine supply effectively resensitized cisplatin-resistant cells. Furthermore, restoring miR-32-5p in FEZF1-AS1-overexpressing cisplatin resistant cells successfully overcame FEZF1-AS1-mediated cisplatin resistance by targeting GLS. These findings were further supported by in vivo xenograft mice experiments. This study uncovered the roles and molecular mechanisms of lncRNA FEZF1-AS1 in mediating cisplatin resistance in NSCLC, specifically through modulating the miR-32-5p-GLS axis, providing support for the development of new therapeutic approaches against chemoresistant lung cancer.

Can DNA Methylation Profiling Classify Histologic Subtypes and Grades in Soft Tissue Sarcoma?

BACKGROUND

A clear classification of the subtype and grade of soft tissue sarcoma is important for predicting prognosis and establishing treatment strategies. However, the rarity and heterogeneity of these tumors often make diagnosis difficult. In addition, it remains challenging to predict the response to chemotherapy and prognosis. Thus, we need a new method to help diagnose soft tissue sarcomas and determine treatment strategies in conjunction with traditional methods. Genetic alterations can be found in some subtypes of soft tissue sarcoma, but many other types show dysregulated gene expression attributed to epigenetic changes, such as DNA methylation status. However, research on DNA methylation profiles in soft tissue sarcoma is still insufficient to provide information to assist in diagnosis and therapeutic decisions.

QUESTIONS/PURPOSES

(1) Do DNA methylation profiles differ between normal tissue and soft tissue sarcoma? (2) Do DNA methylation profiles vary between different histologic subtypes of soft tissue sarcoma? (3) Do DNA methylation profiles differ based on tumor grade?

METHODS

Between January 2019 and December 2022, we treated 85 patients for soft tissue sarcomas. We considered patients whose specimens were approved for pilot research by the Human Biobank of St. Vincent's Hospital, The Catholic University of Korea, as potentially eligible. Based on this, 41% (35 patients) were eligible; 1% (one patient) was excluded because of gender mismatch between clinical and genetic data after controlling for data quality. Finally, 39 specimens (34 soft tissue sarcomas and five normal samples) were included from 34 patients who had clinical data. All tissue samples were collected intraoperatively. The five normal tissue samples were from muscle tissues. There were 20 female patients and 14 male patients, with a median age of 58 years (range 19 to 82 years). Genomic DNA was extracted from frozen tissue, and DNA methylation profiles were obtained. Genomic annotation of DNA methylation sites and hierarchical cluster analysis were performed to interpret results from DNA methylation profiling. A t-test was used to analyze different methylation probes. Benjamini-Hochberg-adjusted p value calculations were used to account for bias resulting from evaluating thousands of methylation sites.

RESULTS

The most common histologic subtypes were liposarcoma (n = 10) and leiomyosarcoma (n = 9). The tumor grade was Fédération Nationale des Centres de Lutte Contre Le Cancer Grades 1, 2, and 3 in 3, 15, and 16 patients, respectively. DNA methylation profiling demonstrated differences between soft tissue sarcoma and normal tissue as 21,188 cytosine-phosphate-guanine sites. Despite the small number of samples, 72 of these sites showed an adjusted p value of < 0.000001, suggesting a low probability of statistical errors. Among the 72 sites, 70 exhibited a hypermethylation pattern in soft tissue sarcoma, with only two sites showing a hypomethylation pattern. Thirty of 34 soft tissue sarcomas were distinguished from normal samples using hierarchical cluster analysis. There was a different methylation pattern between leiomyosarcoma and liposarcoma at 7445 sites. Using the data, hierarchical clustering analysis showed that liposarcoma was distinguished from leiomyosarcoma. When we used the same approach and included other subtypes with three or more samples, only leiomyosarcoma and myxofibrosarcoma were separated from the other subtypes, while liposarcoma and alveolar soft-part sarcoma were mixed with the others. When comparing DNA methylation profiles between low-grade (Grade 1) and high-grade (Grades 2 and 3) soft tissue sarcomas, a difference in methylation pattern was observed at 144 cytosine-phosphate-guanine sites. Among these, 132 cytosine-phosphate-guanine sites exhibited hypermethylation in the high-grade group compared with the low-grade group. Hierarchical clustering analysis showed a division into two groups, with most high-grade sarcomas (28 of 31) separated from the low-grade group and few (3 out of 31) clustered together with the low-grade group. However, three high-grade soft tissue sarcomas were grouped with the Grade 1 cluster, and all of these sarcomas were Grade 2. When comparing Grades 1 and 2 to Grade 3, Grade 3 tumors were separated from Grades 1 and 2.

CONCLUSION

We observed a different DNA methylation pattern between soft tissue sarcomas and normal tissues. Liposarcoma was distinguished from leiomyosarcoma using methylation profiling. High-grade soft tissue sarcoma samples showed a hypermethylation pattern compared with low-grade ones. Our findings indicate the need for research using methylation profiling to better understand the diverse biological characteristics of soft tissue sarcoma. Such research should include studies with sufficient samples and a variety of subtypes, as well as analyses of the expression and function of related genes. Additionally, efforts to link this research with clinical data related to treatment and prognosis are necessary.

LEVEL OF EVIDENCE

Level III, diagnostic study.

[Plasma miRNA expression in patients with genetically confirmed multiple endocrine neoplasia type 1 syndrome and its phenocopies]

BACKGROUND

MEN-1 is a rare autosomal dominant disease caused by mutations in MEN1 gene encoding the menin protein. This syndrome is characterized by the occurrence of parathyroid tumors, gastroenteropancreatic neuroendocrine tumors, pituitary adenomas, as well as other endocrine and non-endocrine tumors. If a patient with the MEN-1 phenotype carry no mutations in the MEN1 gene, the condition considers a phenocopy of syndrome (phMEN1). The possible cause of this changes could be changes in epigenetic regulation, particularly in microRNA expression that might affect menin signaling pathways.

AIM

to identify differently expressed circulating miRNAs in plasma in patients with genetically confirmed MEN-1 syndrome, its phenocopies and healthy controls.

MATERIALS AND METHODS

single-center, case-control study was conducted. We assessed plasma microRNA expression in patients with genetically confirmed MEN-1 (gMEN1), phMEN1 and healthy controls. Morning plasma samples were collected from fasting patients and stored at -80°C. Total RNA isolation was performed using miRNeasy Mini Kit with QIAcube. The libraries were prepared by the QIAseq miRNA Library Kit following the manufacturer. Circulating miRNA sequencing was done on Illumina NextSeq 500 (Illumina). Subsequent data processing was performed using the DESeq2 bioinformatics algorithm.

RESULTS

we enrolled 21 consecutive patients with gMEN1 and 11 patients with phMEN1, along with 12 gender matched controls. Median age of gMEN1 was 38,0 [34,0; 41,0]; in phMEN1 - 59,0 [51,0; 60,0]; control - 59,5 [51,5; 62,5]. The gMEN1 group differed in age (p<0.01) but not gender (р=0.739) or BMI (р=0.116) compared to phMEN1 and controls group, the last two groups did not differ by these parameters (p>0.05). 25 microRNA were differently expressed in groups gMEN1 and phMEN1 (21 upregulated microRNAs, 4 - downregulated). Comparison of samples from the phMEN-1 group and relatively healthy controls revealed 10 differently expressed microRNAs: 5 - upregulated; 5 - downregulated. In the gMEN-1 and control groups, 26 differently expressed microRNAs were found: 24 - upregulated; 2 - downregulated. The miRNAs most differing in expression among the groups were selected for further validation by RT-qPCR (in the groups of gMEN1 vs phMEN1 - miR-3613-5p, miR-335-5p, miR-32-5p, miR-425-3p, miR-25-5p, miR-576-5p, miR-215-5p, miR-30a-3p, miR-141-3p, miR-760, miR-501-3p; gMEN1 vs control - miR-1976, miR-144-5p miR-532-3p, miR-375; as well as in phMEN1 vs control - miR-944, miR-191-5p, miR-98-5p).

CONCLUSION

In a pilot study, we detected microRNAs that may be expressed differently between patients with gMEN-1 and phMEN-1. The results need to be validated using different measurement method with larger sample size.

TLDc Domain-Containing Genes in Autism Spectrum Disorder: New Players in the Oxidative Stress Response

Oxidative stress (OS) plays a key role in autism spectrum disorder (ASD), a neurodevelopmental disorder characterized by deficits in social communication, restricted interests, and repetitive behaviors. Recent evidence suggests that the TLDc [Tre2/Bub2/Cdc16 (TBC), lysin motif (LysM), domain catalytic] domain is a highly conserved motif present in proteins that are important players in the OS response and in neuroprotection. Human proteins sharing the TLDc domain include OXR1, TLDC1, NCOA7, TBC1D24, and C20ORF118. This study was aimed at understanding whether TLDc domain-containing mRNAs together with specific microRNAs (200b-3p and 32-5p) and long noncoding RNAs (TUG1), known to target TLDc proteins, contributed to regulate the OS response in ASD. Data showed a significant increase in the levels of OXR1 and TLDC1 mRNAs in peripheral blood mononuclear cells (PBMCs) of ASD children compared to their neurotypically developing (NTD) counterparts, along with an increase in TUG1 mRNA expression levels, suggesting its possible role in the regulation of TLDc proteins. A positive correlation between the expression of some TLDc mRNAs and the Childhood Autism Rating Scale (CARS) global score as well as inflammatory gene expression was found. In conclusion, our data suggest a novel biological pathway in the OS response of ASD subjects that deserves further exploration.

Genome, Metabolism, or Immunity: Which Is the Primary Decider of Pancreatic Cancer Fate through Non-Apoptotic Cell Death?

Pancreatic ductal adenocarcinoma (PDAC) is a solid tumor characterized by poor prognosis and resistance to treatment. Resistance to apoptosis, a cell death process, and anti-apoptotic mechanisms, are some of the hallmarks of cancer. Exploring non-apoptotic cell death mechanisms provides an opportunity to overcome apoptosis resistance in PDAC. Several recent studies evaluated ferroptosis, necroptosis, and pyroptosis as the non-apoptotic cell death processes in PDAC that play a crucial role in the prognosis and treatment of this disease. Ferroptosis, necroptosis, and pyroptosis play a crucial role in PDAC development via several signaling pathways, gene expression, and immunity regulation. This review summarizes the current understanding of how ferroptosis, necroptosis, and pyroptosis interact with signaling pathways, the genome, the immune system, the metabolism, and other factors in the prognosis and treatment of PDAC.

Long non-coding RNA SNHG17 contributes to the progression of pancreatic adenocarcinoma by modulating miR-32-5p/EZH2/STAT3 signaling

BACKGROUND

Adenocarcinoma of the pancreas (PAAD) is one of the most malignant tumors in the gastrointestinal tract. Long-chain noncoding RNAs (lncRNAs) are non-coding RNAs that are expressed in a variety of cancers. The purpose of this study is to study the expression, biology functions, and molecular mechanism of lncRNA SNHG17 in PAAD.

METHODS

In this study, qRT-PCR was used to measure the relative expression of SNHG17 and miR-32-5p in PAAD. In order to investigate the effect of SNHG17 and miR-32-5p on the proliferation, migration and invasion of PAAD cells, we performed a variety of tests including CCK-8, colony formation, scratch and transwell assays. Furthermore, SNHG17 and miR-32-5p interactions were confirmed by a luciferase reporter gene test.

RESULTS

Our results indicate that the expression of SNHG17 in PAAD is elevated, and in vitro studies have shown that SNHG17 enhances the proliferation of PAAD cells, Mechanistically, it has been shown that SNHG17 can direct target miR-32-5p in PAAD cells, thus promoting the proliferation of PAAD cells, migration, and invasion. Furthermore, SNHG17 has been found to activate EZH2/STAT3 signaling pathway through miR-32-5p in PAAD cells.

CONCLUSION

Our results show that SNHG17 plays a key role in the progression of PAAD by activating STAT3 signaling via regulation of miR-32-5p and EZH2.Identifying these new regulatory pathways may shed light on the underlying mechanism of PAAD and offer a potential therapeutic target for this fatal disease.

Overexpression of miR-32 in Chinese hamster ovary cells increases production of Fc-fusion protein

The demand for industrial genetically modified host cells were increased with the growth of the biopharmaceutical market. Numerous studies on improving host cell productivity have shown that altering host cell growth and viability through genetic engineering can increase recombinant protein production. During the last decades, it was demonstrated that overexpression or downregulation of some microRNAs in Chinese Hamster Ovary (CHO) cells as the host cell in biopharmaceutical manufacturing, can improve their productivity. The selection of microRNA targets has been based on their previously identified role in human cancers. MicroRNA-32 (miR-32), which is conserved between humans and hamsters (Crisetulus griseus), was shown to play a role in the regulation of cell proliferation and apoptosis in some human cancers. In this study, we investigated the effect of miR-32 overexpression on the productivity of CHO-VEGF-trap cells. Our results indicated that stable overexpression of miR-32 could dramatically increase the productivity of CHO cells by 1.8-fold. It also significantly increases cell viability, batch culture longevity, and cell growth. To achieve these results, following the construction of a single clone producing an Fc-fusion protein, we transfected cells with a pLexJRed-miR-32 plasmid to stably produce the microRNA and evaluate the impact of mir-32 overexpression on cell productivity, growth and viability in compare with scrambled control. Our findings highlight the application of miRNAs as engineering tools and indicated that miR-32 could be a target for engineering CHO cells to increase cell productivity.

DSCR9/miR-21-5p axis inhibits pancreatic cancer proliferation and resistance to gemcitabine via BTG2 signaling

The outcome of pancreatic adenocarcinoma (PAAD) patients is poor, given resistance to gemcitabine. Long noncoding RNA (lncRNA) has been implicated in the carcinogenesis of pancreatic cancer; however, its function and mechanism in PAAD resistance to gemcitabine (GEM) are yet unknown. Herein, we demonstrate that lncRNA DSCR9 is significantly reduced in PAAD in vitro and in vivo. CCK-8, BrdU and flow cytometry assays show that overexpression of DSCR9 markedly suppresses pancreatic cancer cell proliferation and invasion, and promotes apoptosis under gemcitabine treatment. BTG2 acts as a tumor suppressor by reducing the proliferation and invasion of pancreatic cancer cells and increasing gemcitabine-induced apoptosis. Immunofluorescence (IF) staining combined with fluorescence in situ hybridization (FISH) of pancreatic cancer tissues shows that DSCR9 and BTG2 are both increased in pancreatic cancer tissues. Luciferase assay shows that miR-21-5p simultaneously binds to DSCR9 and 3'UTR of BTG2; DSCR9 relieves miR-21-5p-induced inhibition of BTG2 by competing with BTG2 for miR-21-5p binding. Overexpression of miR-21-5p enhances the invasiveness of pancreatic cancer cells by promoting cancer cell proliferation and invasion and attenuating gemcitabine-induced apoptosis. Overexpression of miR-21-5p attenuates the effect of DSCR9 overexpression on BTG2 expression and invasiveness of pancreatic cancer cells. Finally, miR-21-5p expression is increased, while BTG2 expression is decreased in pancreatic cancer tissues. miR-21-5p is negatively correlated with DSCR9 and BTG2. In conclusion, the DSCR9/miR-21-5p/BTG2 axis modulates pancreatic cancer proliferation, invasion, and gemcitabine resistance.

Endometrial Carcinoma: Molecular Cytogenetics and Transcriptomic Profile

Endometrial carcinomas (ECs) are histologically classified as endometrioid and nonendometrioid tumors, with each subgroup displaying different molecular profiles and clinical outcomes. Considerable biological and clinical heterogeneity exists within this scheme, however, reflecting its imperfection. We aimed to gather additional data that might help clarify the tumors’ pathogenesis and contribute toward a more meaningful classification scheme. In total, 33 ECs were examined for the presence of chromosomal aberrations, genomic imbalances, pathogenic variants, microsatellite instability, and expression profiles at both gene and miRNA levels. Chromosome 1 was the most frequently rearranged chromosome, showing a gain of all or part of the long arm. Pathogenic variants were found for PTEN (53%), PDGFRA (37%), PIK3CA (34%), and KIT (31%). High microsatellite instability was identified in 15 ECs. Comparing tumors and controls, we identified 23 differentially expressed genes of known importance in carcinogenesis, 15 genes involved in innate and adaptative immune responses, and altered expression of 7 miRNAs. miR-32-5p was the most upregulated. Our series showed a high degree of heterogeneity. Tumors were well-separated from controls, but there was no clear-cut separation between endometrioid and nonendometrioid ECs. Whether this means that the current phenotypic classification is of little relevance or if one still has not detected which genomic parameters to enter into correlation analyses remains unknown.

Comprehensive Analysis of Necroptosis in Pancreatic Cancer for Appealing its Implications in Prognosis, Immunotherapy, and Chemotherapy Responses

Objective: Necroptosis represents a new target for cancer immunotherapy and is considered a form of cell death that overcomes apoptosis resistance and enhances tumor immunogenicity. Herein, we aimed to determine necroptosis subtypes and investigate the roles of necroptosis in pancreatic cancer therapy. Methods: Based on the expression of prognostic necroptosis genes in pancreatic cancer samples from TCGA and ICGC cohorts, a consensus clustering approach was implemented for robustly identifying necroptosis subtypes. Immunogenic features were evaluated according to immune cell infiltrations, immune checkpoints, HLA molecules, and cancer-immunity cycle. The sensitivity to chemotherapy agents was estimated using the pRRophetic package. A necroptosis-relevant risk model was developed with a multivariate Cox regression analysis. Results: Five necroptosis subtypes were determined for pancreatic cancer (C1∼C5) with diverse prognosis, immunogenic features, and chemosensitivity. In particular, C4 and C5 presented favorable prognosis and weakened immunogenicity; C2 had high immunogenicity; C1 had undesirable prognosis and high genetic mutations. C5 was the most sensitive to known chemotherapy agents (cisplatin, gemcitabine, docetaxel, and paclitaxel), while C4 displayed resistance to aforementioned agents. The necroptosis-relevant risk model could accurately predict prognosis, immunogenicity, and chemosensitivity. Conclusion: Our findings provided a conceptual framework for comprehending necroptosis in pancreatic cancer biology. Future work is required for evaluating its relevance in the design of combined therapeutic regimens and guiding the best choice for immuno- and chemotherapy.