PRRX1 Is a Novel Prognostic Biomarker and Facilitates Tumor Progression Through Epithelial–Mesenchymal Transition in Uveal Melanoma

Dihydroartemisinin inhibits melanoma migration and metastasis by affecting angiogenesis

Tumor angiogenesis is critical for tumor metastasis by providing oxygen, nutrients, and metastatic pathways. As a potential anti-angiogenic agent, Dihydroartemisinin (DHA) can effectively inhibit tumor metastasis. However, the mechanism how it regulates angiogenesis to affect tumor metastasis has not been fully clarified. To investigate the mechanisms of how DHA regulates melanoma progression. In this study, bioinformatics methods were used to analyze the correlation between angiogenesis and melanoma metastasis. Then, B16F10, A375, HUVECs and mouse metastasis models were adapted to clarify the inhibition of DHA in melanoma. GESA analysis revealed melanoma metastasis significantly positive correlated with angiogenesis. Meanwhile, DHA significantly decreased melanoma nodules and lung wet weight in metastatic tumor mice, and inhibited the expression of the angiogenic marker CD31 in vitro and in vivo. Similarly, DHA inhibited the expression of the angiogenic signal molecule VEGFR2 in A375 and B16F10 cells, and significantly suppressed the formation of their tubular structures. DHA-treated supernatants significantly inhibited the tubule-forming ability as well as lateral and longitudinal migration ability of HUVECs compared with untreated melanoma cell supernatants. Screening yielded the angiogenic pathways HIF-1α/VEGF, PI3K/ATK/mTOR associated with melanoma metastasis, and DHA may inhibit tumor metastasis by inhibiting these angiogenic pathways in melanoma cells to inhibit tumor metastasis. Further non-targeted metabolomics analysis revealed that DHA-treated model mice produced differential metabolites that were also associated with angiogenic pathways. DHA inhibits melanoma invasion and metastasis by mediating angiogenesis. These results have important implications for the potential use of DHA in treatment of melanoma.

Characterizing tumor biology and immune microenvironment in high-grade serous ovarian cancer via single-cell RNA sequencing: insights for targeted and personalized immunotherapy strategies

Background

High-grade serous ovarian cancer (HGSOC), the predominant subtype of epithelial ovarian cancer, is frequently diagnosed at an advanced stage due to its nonspecific early symptoms. Despite standard treatments, including cytoreductive surgery and platinum-based chemotherapy, significant improvements in survival have been limited. Understanding the molecular mechanisms, immune landscape, and drug sensitivity of HGSOC is crucial for developing more effective and personalized therapies. This study integrates insights from cancer immunology, molecular profiling, and drug sensitivity analysis to identify novel therapeutic targets and improve treatment outcomes. Utilizing single-cell RNA sequencing (scRNA-seq), the study systematically examines tumor heterogeneity and immune microenvironment, focusing on biomarkers influencing drug response and immune activity, aiming to enhance patient outcomes and quality of life.

Methods

scRNA-seq data was obtained from the GEO database in this study. Differential gene expression was analyzed using gene ontology and gene set enrichment methods. InferCNV identified malignant epithelial cells, while Monocle, Cytotrace, and Slingshot software inferred subtype differentiation trajectories. The CellChat software package predicted cellular communication between malignant cell subtypes and other cells, while pySCENIC analysis was utilized to identify transcription factor regulatory networks within malignant cell subtypes. Finally, the analysis results were validated through functional experiments, and a prognostic model was developed to assess prognosis, immune infiltration, and drug sensitivity across various risk groups.

Results

This study investigated the cellular heterogeneity of HGSOC using scRNA-seq, focusing on tumor cell subtypes and their interactions within the tumor microenvironment. We confirmed the key role of the C2 IGF2+ tumor cell subtype in HGSOC, which was significantly associated with poor prognosis and high levels of chromosomal copy number variations. This subtype was located at the terminal differentiation of the tumor, displaying a higher degree of malignancy and close association with stage IIIC tissue types. The C2 subtype was also associated with various metabolic pathways, such as glycolysis and riboflavin metabolism, as well as programmed cell death processes. The study highlighted the complex interactions between the C2 subtype and fibroblasts through the MK signaling pathway, which may be closely related to tumor-associated fibroblasts and tumor progression. Elevated expression of PRRX1 was significantly connected to the C2 subtype and may impact disease progression by modulating gene transcription. A prognostic model based on the C2 subtype demonstrated its association with adverse prognosis outcomes, emphasizing the importance of immune infiltration and drug sensitivity analysis in clinical intervention strategies.

Conclusion

This study integrates molecular oncology, immunotherapy, and drug sensitivity analysis to reveal the mechanisms driving HGSOC progression and treatment resistance. The C2 IGF2+ tumor subtype, linked to poor prognosis, offers a promising target for future therapies. Emphasizing immune infiltration and drug sensitivity, the research highlights personalized strategies to improve survival and quality of life for HGSOC patients.

PLEK2: a potential biomarker for metastasis and prognostic evaluation in uveal melanoma

Background

Uveal melanoma (UVM) is an aggressive tumor known for its high metastatic rate, making it necessary to delineate potential molecules that may promote the development of UVM. PLEK2 has been found to promote the progression and metastasis of some tumors, but its role in UVM has not yet been reported. Through this study, we hope to explore the effect of PLEK2 on the prognosis of UVM patients and to discover the potential functional role and intrinsic mechanism of PLEK2.

Methods

The GEO datasets GSE211763 and GSE149920 were analyzed using GEO2R to identify differentially expressed genes that may be associated with UVM progression and metastasis. A Protein-Protein Interaction Network (PPI) was constructed to identify key molecules. The correlation between PLEK2 expression and overall survival was evaluated via GEPIA2, and clinical characteristics of UVM patients were compared based on PLEK2 levels. PLEK2 expression in UVM cell lines was assessed using the CCLE database and confirmed by qPCR and western blot. A weighted correlation network analysis (WGCNA) was performed, followed by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Finally, a search for miRNAs potentially regulating PLEK2 expression was performed using TargetScan, miRWalk, and TarBase databases.

Results

Comparative analysis of the GEO datasets unveiled 79 commonly up-regulated genes and 238 commonly down-regulated genes. The PPI network identified 9 hub genes, with PLEK2 significantly linked to reduced overall survival. Clinical comparisons indicated significant differences in cancer status (p = 0.013) and tumor diameter (p = 0.039) between high and low PLEK2 expression groups. Elevated PLEK2 mRNA levels were confirmed in UVM cell lines compared to retinal pigment epithelial cells. PLEK2 was enriched in the calcium signaling pathway and associated with the Wnt/Ca2+ signaling pathway. A total of 21 miRNAs potentially regulating PLEK2 were predicted.

Conclusion

PLEK2 is upregulated in UVM and correlates with poor patient prognosis, likely influencing the calcium signaling pathway. PLEK2 represents a promising prognostic biomarker and therapeutic target for UVM.

Machine learning and single-cell RNA sequencing reveal relationship between intratumor CD8+ T cells and uveal melanoma metastasis

PURPOSE

Uveal melanoma (UM) is adults' most common primary intraocular malignant tumor. It has been observed that 40% of patients experience distant metastasis during subsequent treatment. While there exist multigene models developed using machine learning methods to assess metastasis and prognosis, the immune microenvironment's specific mechanisms influencing the tumor microenvironment have not been clarified. Single-cell transcriptome sequencing can accurately identify different types of cells in a tissue for precise analysis. This study aims to develop a model with fewer genes to evaluate metastasis risk in UM patients and provide a theoretical basis for UM immunotherapy.

METHODS

RNA-seq data and clinical information from 79 μm patients from TCGA were used to construct prognostic models. Mechanisms were probed using two single-cell datasets derived from the GEO database. After screening for metastasis-related genes, enrichment analysis was performed using GO and KEGG. Prognostic genes were screened using log-rank test and one-way Cox regression, and prognostic models were established using LASSO regression analysis and multifactor Cox regression analysis. The TCGA-UVM dataset was used as internal validation and dataset GSE22138 as external validation data. A time-dependent subject work characteristic curve (time-ROC) was established to assess the predictive ability of the model. Subsequently, dimensionality reduction, clustering, pseudo-temporal analysis and cellular communication analysis were performed on GSE138665 and GSE139829 to explore the underlying mechanisms involved. Cellular experiments were also used to validate the relevant findings.

RESULTS

Based on clinical characteristics and RNA-seq transcriptomic data from 79 samples in the TCGA-UVM cohort, 247 metastasis-related genes were identified. Survival models for three genes (SLC25A38, EDNRB, and LURAP1) were then constructed using lasso regression and multifactorial cox regression. Kaplan-Meier survival analysis showed that the high-risk group was associated with poorer overall survival (OS) and metastasis-free survival (MFS) in UM patients. Time-dependent ROC curves demonstrated high predictive performance in 6 m, 18 m, and 30 m prognostic models. Cell scratch assay showed that the 24 h and 48 h migration rates of cells with reduced expression of the three genes were significantly higher than those of the si-NC group. CD8 + T cells may play an important role in tumour metastasis as revealed by immune infiltration analysis. An increase in the percentage of cytotoxic CD8 + T cells in the metastatic high-risk group was found in the exploration of single-cell transcriptome data. The communication intensity of cytotoxic CD8 was significantly enhanced. It was also found that the CD8 + T cells in the two groups were in different states, although the number of CD8 + T cells in the high-risk group increased, they were mostly in the exhausted and undifferentiated state, while in the low-risk group, the CD8 + T cells were mostly in the functional state.

CONCLUSIONS

We developed a precise and stable 3-gene model to predict the metastatic risk and prognosis of patients. CD8 + T cells exhaustion in the tumor microenvironment play a crucial role in UM metastasis.

PRRX1 silencing is required for metastatic outgrowth in melanoma and is an independent prognostic of reduced survival in patients

Paired related homeobox 1 (PRRX1) is an inducer of epithelial-to-mesenchymal transition (EMT) in different types of cancer cells. We detected low PRRX1 expression in nevus but increased levels in primary human melanoma and cell lines carrying the BRAFV600E mutation. High expression of PRRX1 correlates with invasiveness and enrichment of genes belonging to the EMT programme. Conversely, we found that loss of PRRX1 in metastatic samples is an independent prognostic predictor of poor survival for melanoma patients. Here, we show that stable depletion of PRRX1 improves the growth of melanoma xenografts and increases the number of distant spontaneous metastases, compared to controls. We provide evidence that loss of PRRX1 counteracts the EMT phenotype, impairing the expression of other EMT-related transcription factors, causing dysregulation of the ERK and signal transducer and activator of transcription 3 (STAT3) signaling pathways, and abrogating the invasive and migratory properties of melanoma cells while triggering the up-regulation of proliferative/melanocytic genes and the expression of the neural-crest-like markers nerve growth factor receptor (NGFR; also known as neurotrophin receptor p75NTR) and neural cell adhesion molecule L1 (L1CAM). Overall, our results indicate that loss of PRRX1 triggers a switch in the invasive programme, and cells de-differentiate towards a neural crest stem cell (NCSC)-like phenotype that accounts for the metastatic aggressiveness.

Global transcriptomic network analysis of the crosstalk between microbiota and cancer-related cells in the oral-gut-lung axis

Background

The diagnosis and treatment of lung, colon, and gastric cancer through the histologic characteristics and genomic biomarkers have not had a strong impact on the mortality rates of the top three global causes of death by cancer.

Methods

Twenty-five transcriptomic analyses (10 lung cancer, 10 gastric cancer, and 5 colon cancer datasets) followed our own bioinformatic pipeline based on the utilization of specialized libraries from the R language and DAVID´s gene enrichment analyses to identify a regulatory metafirm network of transcription factors and target genes common in every type of cancer, with experimental evidence that supports its relationship with the unlocking of cell phenotypic plasticity for the acquisition of the hallmarks of cancer during the tumoral process. The network's regulatory functional and signaling pathways might depend on the constant crosstalk with the microbiome network established in the oral-gut-lung axis.

Results

The global transcriptomic network analysis highlighted the impact of transcription factors (SOX4, TCF3, TEAD4, ETV4, and FOXM1) that might be related to stem cell programming and cancer progression through the regulation of the expression of genes, such as cancer-cell membrane receptors, that interact with several microorganisms, including human T-cell leukemia virus 1 (HTLV-1), the human papilloma virus (HPV), the Epstein-Barr virus (EBV), and SARS-CoV-2. These interactions can trigger the MAPK, non-canonical WNT, and IFN signaling pathways, which regulate key transcription factor overexpression during the establishment and progression of lung, colon, and gastric cancer, respectively, along with the formation of the microbiome network.

Conclusion

The global transcriptomic network analysis highlights the important interaction between key transcription factors in lung, colon, and gastric cancer, which regulates the expression of cancer-cell membrane receptors for the interaction with the microbiome network during the tumorigenic process.

PRRX1-OLR1 axis supports CAFs-mediated lung cancer progression and immune suppression

OBJECTIVE

To investigate the mechanism by which cancer-associated fibroblasts (CAFs) affect the growth and immune evasion of lung cancer cells.

METHODS

Initially, datasets comparing CAFs with normal fibroblasts were downloaded from the GEO dataset GSE48397. Genes with the most significant differential expression were selected and validated using clinical data. Subsequently, CAFs were isolated, and the selected genes were knocked down in CAFs. Co-culture experiments were conducted with H1299 or A549 cells to analyze changes in lung cancer cell growth, migration, and immune evasion in vitro and in vivo. To further elucidate the upstream regulatory mechanism, relevant ChIP-seq data were downloaded from the GEO database, and the regulatory relationships were validated through ChIP-qPCR and luciferase reporter assays.

RESULTS

OLR1 was significantly overexpressed in CAFs and strongly correlated with adverse prognosis in lung cancer patients. Knockdown of OLR1 markedly inhibited CAFs' support for the growth and immune evasion of lung cancer cells in vitro and in vivo. ChIP-seq results demonstrated that PRRX1 can promote OLR1 expression by recruiting H3K27ac and H3K4me3, thereby activating CAFs. Knockdown of PRRX1 significantly inhibited CAFs' function, while further overexpression of OLR1 restored CAFs' support for lung cancer cell growth, migration, and immune evasion.

CONCLUSION

PRRX1 promotes OLR1 expression by recruiting H3K27ac and H3K4me3, activating CAFs, and thereby promoting the growth, migration, and immune evasion of lung cancer cells.

LncRNA KIFAP3-5:1 inhibits epithelial-mesenchymal transition of renal tubular cell through PRRX1 in diabetic nephropathy

Long noncoding RNAs play an important role in several pathogenic processes in diabetic nephropathy, but the relationship with epithelial-mesenchymal transition in DN is unclear. Herein, we found that KIFAP3-5:1 expression was significantly down-regulated in DN plasma samples, db/db mouse kidney tissues and high glucose treated renal tubular epithelial cells compared to normal healthy samples and untreated cells. Overexpression of KIFAP3-5:1 improved renal fibrosis in db/db mice and rescued epithelial-mesenchymal transition of high glucose cultured renal tubular epithelial cells. The silence of KIFAP3-5:1 will exacerbate the progression of EMT. Mechanistically, KIFAP3-5:1 was confirmed to directly target to the -488 to -609 element of the PRRX1 promoter and negatively modulate PRRX1 mRNA and protein expressions. Furthermore, rescue assays demonstrated that the knockdown of PRRX1 counteracted the KIFAP3-5:1 low expression-mediated effects on EMT in hRPTECs cultured under high glucose. The plasma KIFAP3-5:1 of DN patients is highly correlated with the severity of renal dysfunction and plays an important role in the prediction model of DN diseases. These findings suggested that KIFAP3-5:1 plays a critical role in regulation of renal EMT and fibrosis through suppress PRRX1, and highlight the clinical potential of KIFAP3-5:1 to assist in the diagnosis of diabetic nephropathy.

Suppression of malignant melanoma by knocking down growth differentiation factor-15 via inhibiting PTEN/PI3K/AKT signaling pathway

Background: Melanoma is a highly malignant tumor, and it is characterized by high mortality. Growth differentiation factor 15 (GDF15) and PTEN/PI3K/AKT signaling pathway have been proved to be related with regulation of tumors. If GDF15 could regulate melanoma through targeting PTEN/PI3K/AKT signaling pathway remain unclear. Methods: EdU staining, wound healing, Transwell assay, and flow cytometry were performed to measure cell proliferation, migration, invasion, and apoptosis. GEPIA and TCGA data bases were applied to analyze the relationship between GDF15 and prognosis. Results: We found that high expression of GDF15 suggested lower survival of melanoma patients, and is positively linked with advanced stage through analysis with GEPIA and TCGA data bases. Knockdown of GDF15 greatly inhibited the migration, invasion and proliferation ability of both M14 and M21 cells, but promoted cell apoptosis. However, the influence of GDF15 on M14 and M21 cells were reversed by 740Y-P, the activator of PTEN/PI3K/AKT signaling pathway. In addition, 740Y-P significantly reversed the influence of sh-GDF15 on the epithelial-mesenchymal transition (EMT) related proteins expression in M14 and M21 cell lines. Significant higher expression of GDF15 in melanoma was observed. In addition, the inhibition of PTEN/PI3K/AKT signaling pathway by knocking down GDF15 was observed in both M14 and M21 cell lines. sh-GDF15 greatly decreased the resistance of M14 and M21 to chemotherapy drugs, docetaxel and doxorubicin. Conclusions: GDF15 regulated the cell proliferation, apoptosis, migration, invasion, and EMT process of M14 and M21 cell lines through targeting PTEN/PI3K/AKT signaling pathway. This research provides a novel prevention and treatment strategy for melanoma.

BAP1 mutations inhibit the NF-κB signaling pathway to induce an immunosuppressive microenvironment in uveal melanoma

BACKGROUND

Tumor immune microenvironment regulates the growth and metastasis of uveal melanoma (UM). This study aims to reveal the possible molecular mechanism of BRCA1-associated protein 1 (BAP1) mutations in affecting the tumor immune microenvironment in UM through mediating the nuclear factor-κB (NF-κB) signaling pathway.

METHODS

TCGA and cBioPortal databases jointly analyzed the genes with high mutation frequency in UM samples. Following survival analysis of UM patients, UM samples with BAP1 mutations were subjected to immune cell infiltration analysis. The signaling pathways associated with the mutated genes were screened by GSEA. Subsequently, the differential BAP1 expression was analyzed in the selected UM cell lines with wild type (WT) or mutant type (MUT) BAP1.

RESULTS

Bioinformatics analysis identified 12 genes mutated in the UM samples, while only BAP1 mutations were related to the prognosis of UM patients. UM patients with BAP1 mutations had higher immune cell infiltration. BAP1 mutations inhibited the NF-κB signaling pathway, suppressing the cytokine secretion and antigen presentation by macrophages. Rescue experiments confirmed that overexpressed NF-κB could reverse the effect of BAP1 mutations on the immunosuppressive microenvironment, thus suppressing the malignant phenotypes of UM cells.

CONCLUSION

BAP1 mutations may inhibit the NF-κB signaling pathway, repressing the cytokine secretion and antigen presentation by macrophages, which induces the immunosuppressive microenvironment, enhances the malignant phenotypes of UM cells and ultimately promotes the growth and metastasis of UM.

Integrated single-cell and transcriptome sequencing analyses develops a metastasis-based risk score system for prognosis and immunotherapy response in uveal melanoma

Background: Uveal melanoma (UM) is the most frequent ocular neoplasm with a strong metastatic ability. The prognostic value of metastasis-associated genes (MAGs) of UM remains unclear. It is urgent to develop a prognostic score system according to the MAGs of UM. Methods: Unsupervised clustering was used to identify MAGs-based molecular subtypes. Cox methods were utilized to generate a prognostic score system. The prognostic ability of the score system was detected by plotting ROC and survival curves. The immune activity and underlying function were depicted by CIBERSORT GSEA algorithms. Results: Gene cluster analysis determined two MAGs-based subclusters in UM, which were remarkably different in clinical outcomes. A risk score system containing six MAGs (COL11A1, AREG, TIMP3, ADAM12, PRRX1 and GAS1) was set up. We employed ssGSEA to compare immune activity and immunocyte infiltration between the two risk groups. Notch, JAK/STAT and mTOR pathways were greatly enriched in the high-risk group. Furthermore, we observed that knockdown of AREG could inhibit UM proliferation and metastasis by in vitro assays. Conclusion: The MAGs-based subtype and score system in UM can enhance prognosis assessment, and the core system provides valuable reference for clinical decision-making.

The identification of N6-methyladenosine-related miRNAs predictive of hepatocellular carcinoma prognosis and immunotherapy efficacy

BACKGROUND

Hepatocellular carcinoma (HCC) has a high degree of malignancy and poor prognosis. N6-methyladenosine (m6A) modifications and microRNAs (miRNAs) play pivotal roles in tumorigenesis and development. However, the role of m6A-related miRNAs in HCC has not been clarified yet. This study aimed to identify the role of m6A-miRNAs in HCC prognosis through bioinformatics analysis.

METHODS

The clinicopathological information and RNA sequencing data of 369 HCC tumor tissues and 49 tumor-adjacent tissues were downloaded from the TCGA database. A total of 23 m6A regulators were extracted to evaluated the m6A-related miRNAs using Pearson's correlation analysis. Then, we selected prognosis-related m6A-miRNAs using a univariate Cox regression model and used the consensus cluster analysis to explore the characteristics of the m6A-miRNAs. The coefficient of the least absolute shrinkage and selection operator (LASSO) Cox regression was applied to construct a prognostic risk score model. The receiver operated characteristic (ROC) analysis was applied to evaluate the prognostic value of the signature. The biological functions of targeted genes were predicted by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Then, to validate the potential predictive value for prognosis, the miRNA expression profiles from the GSE76903 and GSE6857 were used. Single sample Gene Set Enrichment Analysis (ssGSEA) and Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) were applied to assess the immune microenvironment of HCC. Additionally, a meta-analysis was used to verify the prognostic value of the m6A-microRNAs. RT-PCR was applied to validated the expression of miRNAs in HCC tissues. Cell viability, transwell assay and RNA m6A dot blot assays of HCC cells was applied to access the function of miR-17-5p.

RESULTS

The expression of 48 m6A-related miRNAs was identified and 17 prognostic m6A-miRNAs was discovered. The expression profile of those 17 miRNAs was divided into three clusters, and these clusters were associated with the tumor microenvironment (TME) and prognosis. The nine m6A-related miRNA signature was associated with the prognosis of HCC, the AUC of the ROC was 0.771(TCGA dataset), 0.788(GSE76903) and 0.646(GSE6857). The TME and the expression of immune checkpoint molecules were associated with the risk score. The meta-analysis also validated the prognostic value of the m6A-related miRNAs (miR182-5p (HR:1.58, 95%CI:1.04-2.40) and miR-17-5p (HR:1.58, 95%CI: 1.04-2.40)). The expression of miR-17-5p was upregulated in HCC tissues and miR-17-5p showed an oncogenic role in HCC cells.

CONCLUSION

The clinical innovation is the use of m6A-miRNAs as biomarkers for predicting prognosis regarding immunotherapy response in HCC patients.

Role of Epithelial-to-Mesenchymal Transition for the Generation of Circulating Tumors Cells and Cancer Cell Dissemination

Tumor-related death is primarily caused by metastasis; consequently, understanding, preventing, and treating metastasis is essential to improving clinical outcomes. Metastasis is mainly governed by the dissemination of tumor cells in the systemic circulation: so-called circulating tumor cells (CTCs). CTCs typically arise from epithelial tumor cells that undergo epithelial-to-mesenchymal transition (EMT), resulting in the loss of cell-cell adhesions and polarity, and the reorganization of the cytoskeleton. Various oncogenic factors can induce EMT, among them the transforming growth factor (TGF)-β, as well as Wnt and Notch signaling pathways. This entails the activation of numerous transcription factors, including ZEB, TWIST, and Snail proteins, acting as transcriptional repressors of epithelial markers, such as E-cadherin and inducers of mesenchymal markers such as vimentin. These genetic and phenotypic changes ultimately facilitate cancer cell migration. However, to successfully form distant metastases, CTCs must primarily withstand the hostile environment of circulation. This includes adaption to shear stress, avoiding being trapped by coagulation and surviving attacks of the immune system. Several applications of CTCs, from cancer diagnosis and screening to monitoring and even guided therapy, seek their way into clinical practice. This review describes the process leading to tumor metastasis, from the generation of CTCs in primary tumors to their dissemination into distant organs, as well as the importance of subtyping CTCs to improve personalized and targeted cancer therapy.

Dysregulation of B7 family and its association with tumor microenvironment in uveal melanoma

Background

Uveal melanoma (UVM) is the most common primary intraocular malignancy in adults with a poor prognosis. B7 family is an important modulator of the immune response. However, its dysregulation and underlying molecular mechanism in UVM still remains unclear.

Methods

Data were derived from TCGA and GEO databases. The prognosis was analyzed by Kaplan-Meier curve. The ESTIMATE algorithm, CIBERSORT algorithm, and TIMER database were used to demonstrate the correlation between B7 family and tumor immune microenvironment in UVM. Single-cell RNA sequencing was used to detect the expression levels of the B7 family in different cell types of UVM. UVM was classified into different types by consistent clustering. Enrichment analysis revealed downstream signaling pathways of the B7 family. The interaction between different cell types was visualized by cell chat.

Results

The expression level of B7 family in UVM was significantly dysregulated and negatively correlated with methylation level. The expression of B7 family was associated with prognosis and immune infiltration, and B7 family plays an important role in the tumor microenvironment (TME). B7 family members were highly expressed in monocytes/macrophages of UVM compared with other cell types. Immune response and visual perception were the main functions affected by B7 family. The result of cell chat showed that the interaction between photoreceptor cells and immune-related cells was mainly generated by HLA-C-CD8A. CABP4, KCNJ10 and RORB had the strongest correlation with HLA-C-CD8A, and their high expression was significantly correlated with poor prognosis. CABP4 and RORB were specifically expressed in photoreceptor cells.

Conclusions

Dysregulation of the B7 family in UVM is associated with poor prognosis and affects the tumor immune microenvironment. CABP4 and RORB can serve as potential therapeutic targets for UVM, which can be regulated by the B7 family to affect the visual perception and immune response function of the eye, thus influencing the prognosis of UVM.

Identification of Three Genes Associated with Metastasis in Melanoma and Construction of a Predictive Model: A Multiracial Identification

The aim of this study was to identify hub genes associated with metastasis and prognosis in melanoma. Weighted gene coexpression network analysis (WGCNA) was performed to screen and identify hub genes. ROC and K-M analyses were used to verify the hub genes in the internal and external data sets. The risk score model and nomogram model were constructed based on the IHC result. Through WGCNA, the three hub genes, SNRPD2, SNRPD3, and EIF4A3, were identified. In the external data set, the hub genes identified were associated with the worse prognosis (TCGA, SNRPD2, $P\le 0.02$ ; SNRPD3, $P=0.12$ ; EIF4A3, $P=0.11$ ; GSE65904, SNRPD2, $P=0.04$ ; SNRPD3, $P=0.10$ ; EIF4A3, $P<0.01$ ; GSE19234, SNRPD2, $P<0.01$ ; SNRPD3, $P<0.01$ ; EIF4A3, $P<0.01$ ). In the GSE8401, we found that the hub genes were highly expressed in the metastasis compared with the nonmetastasis group (SNRPD2, $988.5\pm 47.83$ vs. $738.4\pm 35.35$ , $P<0.01$ ; SNRPD3, $502.7\pm 25.7$ vs. $416.4\pm 23.88$ , $P=0.02$ ; EIF4A3, $567.6\pm 19.56$ vs. $495.2\pm 21.1$ , $P=0.01$ ). Moreover, the hub genes were identified by the IHC in our data set. The result was similar with the external data set. The hub genes could predict the metastasis and prognosis in the Chinese MM patients. Finally, the GSEA and Pearson analysis demonstrated that the SNRPD2 was associated with the immunotherapy. The three hub genes were identified and validated in MM patients in external and internal data sets. The risk factor model was constructed and verified as a powerful model to predict metastasis and prognosis in MM patients.