Clinicopathological significance and underlying molecular mechanism of downregulation of basonuclin 1 expression in ovarian carcinoma

Identification of ZIC2 as a Potential Biomarker Linked with the Clinical Progression and Immune Infiltration of Oral Cancer: A Multicenter Study

Aim

To investigate the specific expression profile, clinicopathological significance and mechanism of Zic family member 2 (ZIC2) in oral cancer were unclear. Patients and Methods. We explored the expression pattern and clinicopathological significance of ZIC2 in oral cancer through performing in-house tissue microarray and integrated analysis global RNA-seq and microarrays containing large samples. The molecular basis of ZIC2 in oral cancer was further investigated in the aspects of transcription network and immune correlations. We also performed in vitro experiments and calculated drug sensitivity of oral cancer with different ZIC2 expression levels in response to hundreds of compounds.

Results

All data unanimously proved the significant overexpression of ZIC2 in oral cancer. The upregulation of ZIC2 was remarkably associated with the malignant clinical progression of oral cancer. ZIC2 was predicted to be targeted by miRNAs such as miR-3140, miR-4999, and miR-1322. The infiltration level of CD8+ T and central memory cells was positively related to the overexpression of ZIC2. Oral cancer patients with higher ZIC2 expression showed higher drug sensitivity to two compounds including AZD8186 and ERK_2240.

Conclusions

We demonstrated the upregulation of ZIC2 in oral cancer and its promoting effect on the clinical advancement of oral cancer. The potential clinical value of ZIC2 in oral cancer deserves attention.

KLF17 is an important regulatory component of the transcriptomic response of Atlantic salmon macrophages to Piscirickettsia salmonis infection

Piscirickettsia salmonis is the most important health problem facing Chilean Aquaculture. Previous reports suggest that P. salmonis can survive in salmonid macrophages by interfering with the host immune response. However, the relevant aspects of the molecular pathogenesis of P. salmonis have been poorly characterized. In this work, we evaluated the transcriptomic changes in macrophage-like cell line SHK-1 infected with P. salmonis at 24- and 48-hours post-infection (hpi) and generated network models of the macrophage response to the infection using co-expression analysis and regulatory transcription factor-target gene information. Transcriptomic analysis showed that 635 genes were differentially expressed after 24- and/or 48-hpi. The pattern of expression of these genes was analyzed by weighted co-expression network analysis (WGCNA), which classified genes into 4 modules of expression, comprising early responses to the bacterium. Induced genes included genes involved in metabolism and cell differentiation, intracellular transportation, and cytoskeleton reorganization, while repressed genes included genes involved in extracellular matrix organization and RNA metabolism. To understand how these expression changes are orchestrated and to pinpoint relevant transcription factors (TFs) controlling the response, we established a curated database of TF-target gene regulatory interactions in Salmo salar, SalSaDB. Using this resource, together with co-expression module data, we generated infection context-specific networks that were analyzed to determine highly connected TF nodes. We found that the most connected TF of the 24- and 48-hpi response networks is KLF17, an ortholog of the KLF4 TF involved in the polarization of macrophages to an M2-phenotype in mammals. Interestingly, while KLF17 is induced by P. salmonis infection, other TFs, such as NOTCH3 and NFATC1, whose orthologs in mammals are related to M1-like macrophages, are repressed. In sum, our results suggest the induction of early regulatory events associated with an M2-like phenotype of macrophages that drives effectors related to the lysosome, RNA metabolism, cytoskeleton organization, and extracellular matrix remodeling. Moreover, the M1-like response seems delayed in generating an effective response, suggesting a polarization towards M2-like macrophages that allows the survival of P. salmonis. This work also contributes to SalSaDB, a curated database of TF-target gene interactions that is freely available for the Atlantic salmon community.

A cohesin-associated gene score may predict immune checkpoint blockade in hepatocellular carcinoma

Stromal antigen 1 (STAG1), a component of cohesion, is overexpressed in various cancers, but it is unclear whether it has a role in the transcriptional regulation of hepatocellular carcinoma (HCC). To test this hypothesis, here, we screened global HCC datasets and performed multiscale embedded gene co-expression network analysis to identify the potential functional modules of differentially expressed STAG1 co-expressed genes. The putative transcriptional targets of STAG1 were identified using chromatin immunoprecipitation followed by high-throughput DNA sequencing. The cohesin-associated gene score (CAGS) was quantified using the The Cancer Genome Atlas HCC cohort and single-sample gene set enrichment analysis. Distinct cohesin-associated gene patterns were identified by calculating the euclidean distance of each patient. We assessed the potential ability of the CAGS in predicting immune checkpoint blockade (ICB) treatment response using IMvigor210 and GSE78220 cohorts. STAG1 was upregulated in 3313 HCC tissue samples compared with 2692 normal liver tissue samples (standard mean difference = 0.54). A total of three cohesin-associated gene patterns were identified, where cluster 2 had a high TP53 mutated rate and a poor survival outcome. Low CAGS predicted a significant survival advantage but presaged poor immunotherapy response. Differentially expressed STAG1 co-expression genes were enriched in the mitotic cell cycle, lymphocyte activation, and blood vessel development. PDS5A and PDGFRA were predicted as the downstream transcriptional targets of STAG1. In summary, STAG1 is significantly upregulated in global HCC tissue samples and may participate in blood vessel development and the mitotic cell cycle. A cohesin-associated gene scoring system may have potential to predict the ICB response.

Upregulation of CCNB2 and Its Perspective Mechanisms in Cerebral Ischemic Stroke and All Subtypes of Lung Cancer: A Comprehensive Study

Cyclin B2 (CCNB2) belongs to type B cell cycle family protein, which is located on chromosome 15q22, and it binds to cyclin-dependent kinases (CDKs) to regulate their activities. In this study, 103 high-throughput datasets related to all subtypes of lung cancer (LC) and cerebral ischemic stroke (CIS) with the data of CCNB2 expression were collected. The analysis of standard mean deviation (SMD) and summary receiver operating characteristic (SROC) reflecting expression status demonstrated significant up-regulation of CCNB2 in LC and CIS (Lung adenocarcinoma: SMD = 1.40, 95%CI [0.98–1.83], SROC = 0.92, 95%CI [0.89–0.94]. Lung squamous cell carcinoma: SMD = 2.56, 95%CI [1.64–3.48]. SROC = 0.97, 95%CI [0.95–0.98]. Lung small cell carcinoma: SMD = 3.01, 95%CI [2.01–4.01]. SROC = 0.98, 95%CI [0.97–0.99]. CIS: SMD = 0.29, 95%CI [0.05–0.53], SROC = 0.68, 95%CI [0.63–0.71]). Simultaneously, protein-protein interaction (PPI) analysis indicated that CCNB2 is the hub molecule of crossed high-expressed genes in CIS and LC. Through Multiscale embedded gene co-expression network analysis (MEGENA), a gene module of CIS including 76 genes was obtained and function enrichment analysis of the CCNB2 module genes implied that CCNB2 may participate in the processes in the formation of CIS and tissue damage caused by CIS, such as “cell cycle,” “protein kinase activity,” and “glycosphingolipid biosynthesis.” Afterward, via single-cell RNA-seq analysis, CCNB2 was found up-regulated on GABAergic neurons in brain organoids as well as T cells expressing proliferative molecules in LUAD. Concurrently, the expression of CCNB2 distributed similarly to TOP2A as a module marker of cell proliferation in cell cluster. These findings can help in the field of the pathogenesis of LC-related CIS and neuron repair after CIS damage.

Downregulated Dual-Specificity Protein Phosphatase 1 in Ovarian Carcinoma: A Comprehensive Study With Multiple Methods

Introduction: We aimed to explore the abnormal expression of dual-specificity protein phosphatase 1 (DUSP1) and its latent molecular mechanisms in ovarian carcinoma (OVCA).

Materials and Methods: Two clinical cohorts collected from two different hospitals were used to evaluate the expression of DUSP1 protein in OVCA tissues. RNA-sequencing and microarray datasets were utilised to verify DUSP1 expression at mRNA levels in both OVCA tissues and in the peripheral blood of OVCA patients. Furthermore, an integrated calculation was performed to pool the standard mean difference (SMD) from each cohort in order to comprehensively assess the expression of DUSP1 in OVCA. Furthermore, we examined the relationship among DUSP1, tumour microenvironment (TME), and chemotherapy resistance in OVCA. Moreover, we used pathway enrichment analysis to explore the underlying mechanisms of DUSP1 in OVCA.

Results: A pooled SMD of −1.19 (95% CI [−2.00, −0.38], p = 0.004) with 1,240 samples revealed that DUSP1 was downregulated in OVCA at both mRNA and protein levels. The area under the receiver operating characteristic curve of 0.9235 indicated the downregulated DUSP1 in peripheral blood may have a non-invasive diagnostic value in OVCA. Through six algorithms, we identified that DUSP1 may related to tumour-infiltrating T cells and cancer associated fibroblasts (CAFs) in OVCA. Pathway enrichment demonstrated that DUSP1 might participate in the mitogen-activated protein kinase (MAPK) signalling pathway. Furthermore, DUSP1 may have relations with chemotherapy resistance, and a favourable combining affinity was observed in the paclitaxel-DUSP1 docking model.

Conclusion: DUSP1 was downregulated in OVCA, and this decreasing trend may affect the infiltration of CAFs. Finally, DUSP1 may have a targeting relation with paclitaxel and participate in MAPK signaling pathways.

Downregulation of the Coiled-Coil Domain Containing 80 and Its Perspective Mechanisms in Ovarian Carcinoma: A Comprehensive Study

INTRODUCTION

We aimed to explore the downregulation of the coiled-coil domain containing 80 (CCDC80) and its underlying molecular mechanisms in ovarian carcinoma (OVCA). Materials/Methods. Immunohistochemical staining was performed to confirm the expression status of CCDC80 protein. Combining the data from in-house tissue microarrays and high-throughput datasets, we identified the expression level of CCDC80 in OVCA. We utilized cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm and single-sample gene set enrichment analysis (ssGSEA) to explore the relationship between CCDC80 and the tumor microenvironment (TME) landscape in OVCA. Pathway enrichment, function annotation, and transcription factor (TFs) exploration were conducted to study the latent molecular mechanisms. Moreover, the cell line data in the Genomics of Drug Sensitivity in Cancer (GDSC) database was used to discover the relationship between CCDC80 and drug sensitivity.

RESULTS

An integrated standard mean difference (SMD) of -0.919 (95% CI: -1.515-0.324, P = 0.002) identified the downregulation of CCDC80 in OVCA based on 1048 samples, and the sROC (AUC = 0.76) showed a moderate discriminatory ability of CCDC80 in OVCA. The fraction of infiltrating naive B cells showed significant differences between the high- and low-CCDC80 expression groups. Also, CCDC80-related genes are enriched in the Ras signaling pathway and metabolic of lipid. Nuclear receptor subfamily three group C member 1 (NR3C1) may be an upstream TF of CCDC80, and CCDC80 may be related to the sensitivity of mitocycin C and nilotinib.

CONCLUSION

CCDC80 was downregulated in OVCA and may play a role as a tumor suppressor in OVCA.