Identification of differentially expressed metastatic genes and their signatures to predict the overall survival of uveal melanoma patients by bioinformatics analysis

Machine-learning and scRNA-Seq-based diagnostic and prognostic models illustrating survival and therapy response of lung adenocarcinoma

Lung cancer is a major cause accounting for cancer-related mortalities, with lung adenocarcinoma (LUAD) being the most prevalent subtype. Given the high clinical and cellular heterogeneities of LUAD, accurate diagnosis and prognosis are crucial to avoid overdiagnosis and overtreatment. Taking full advantage of scRNA-Seq data to resolve the tumor heterogeneities, we explored the overall landscape of LUAD microenvironment. Utilizing the stage-specific tumor cell markers, we have developed highly accurate diagnostic and prognostic models with elevated sensitivity and specificity. The diagnostic model, developed through random forest algorithms with a thirteen-gene signature, achieved an accuracy of 96.4% and an AUC of 0.993. These metrics were further demonstrated by benchmarking with available models and scoring systems in independent cohorts. Concurrently, the prognostic model, formulated via Cox regression with a six-gene signature, effectively predicted overall survival, with elevated risk scores associated with increased fractions of cancer-associated fibroblasts, and higher likelihood of immune escape and T-cell exclusion. Subsequently, two nomograms were developed to predict survival and drug responses, facilitating their integration into clinical practice. Overall, this study underscores the potential of our models for efficient, rapid, and cost-effective diagnosis and prognosis of LUAD, adaptable to multiple expression profiling platforms and quantification methods.

RNA-seq analysis identifies transcriptomic profiles associated with anal cancer recurrence among people living with HIV

BACKGROUND

Chemoradiation therapy (CRT) is the standard of care for squamous cell carcinoma of the anus (SCCA), the most common type of anal cancer. However, approximately one fourth of patients still relapse after CRT.

METHODS

We used RNA-sequencing technology to characterize coding and non-coding transcripts in tumor tissues from CRT-treated SCCA patients and compare them between 9 non-recurrent and 3 recurrent cases. RNA was extracted from FFPE tissues. Library preparations for RNA-sequencing were created using SMARTer Stranded Total RNA-Seq Kit. All libraries were pooled and sequenced on a NovaSeq 6000. Function and pathway enrichment analysis was performed with Metascape and enrichment of gene ontology (GO) was performed with Gene Set Enrichment Analysis (GSEA).

RESULTS

There were 449 differentially expressed genes (DEGs) observed (390 mRNA, 12 miRNA, 17 lincRNA and 18 snRNA) between the two groups. We identified a core of upregulated genes (IL4, CD40LG, ICAM2, HLA-I (HLA-A, HLA-C) and HLA-II (HLA-DQA1, HLA-DRB5) in the non-recurrent SCCA tissue enriching to the gene ontology term 'allograft rejection', which suggests a CD4+ T cell driven immune response. Conversely, in the recurrent tissues, keratin (KRT1, 10, 12, 20) and hedgehog signaling pathway (PTCH2) genes involved in 'Epidermis Development,', were significantly upregulated. We identified miR-4316, that inhibit tumor proliferation and migration by repressing vascular endothelial growth factors, as being upregulated in non-recurrent SCCA. On the contrary, lncRNA-SOX21-AS1, implicated in the progression of many other cancers, was also found to be more common in our recurrent compared to non-recurrent SCCA.

Our study identified key host factors which may drive the recurrence of SCCA and warrants further studies to understand the mechanism and evaluate their potential use in personalized treatment.Key MessageOur study used RNA sequencing (RNA-seq) to identify pivotal factors in coding and non-coding transcripts which differentiate between patients at risk for recurrent anal cancer after treatment. There were 449 differentially expressed genes (390 mRNA, 12 miRNA, 17 lincRNA and 18 snRNA) between 9 non-recurrent and 3 recurrent squamous cell carcinoma of anus (SCCA) tissues. The enrichment of genes related to allograft rejection was observed in the non-recurrent SCCA tissues, while the enrichment of genes related to epidermis development was positively linked with recurrent SCCA tissues.

Validation of an Ultraviolet Light Response Gene Signature for Predicting Prognosis in Patients with Uveal Melanoma

Uveal melanoma (UVM) is a highly aggressive ocular cancer with limited therapeutic options and poor prognosis particularly for patients with liver metastasis. As such, the identification of new prognostic biomarkers is critical for developing effective treatment strategies. In this study, we aimed to investigate the potential of an ultraviolet light response gene signature to predict the prognosis of UVM patients. Our approach involved the development of a prognostic model based on genes associated with the cellular response to UV light. By employing this model, we generated risk scores to stratify patients into high- and low-risk groups. Furthermore, we conducted differential expression analysis between these two groups and explored the estimation of immune infiltration. To validate our findings, we applied our methodology to an independent UVM cohort. Through our study, we introduced a novel survival prediction tool and shed light on the underlying cellular processes within UVM tumors, emphasizing the involvement of immune subsets in tumor progression.

Tumor subtypes and signature model construction based on chromatin regulators for better prediction of prognosis in uveal melanoma

Background: Uveal Melanoma (UM) is the most prevalent primary intraocular malignancy in adults. This study assessed the importance of chromatin regulators (CRs) in UM and developed a model to predict UM prognosis. Methods: Gene expression data and clinical information for UM were obtained from public databases. Samples were typed according to the gene expression of CRs associated with UM prognosis. The prognostic key genes were further screened by the protein interaction network, and the risk model was to predict UM prognosis using the least absolute shrinkage and selection operator (LASSO) regression analysis and performed a test of the risk mode. In addition, we performed gene set variation analysis, tumor microenvironment, and tumor immune analysis between subtypes and risk groups to explore the mechanisms influencing the development of UM. Results: We constructed a signature model consisting of three CRs (RUVBL1, SIRT3, and SMARCD3), which was shown to be accurate, and valid for predicting prognostic outcomes in UM. Higher immune cell infiltration in poor prognostic subtypes and risk groups. The Tumor immune analysis and Tumor Immune Dysfunction and Exclusion (TIDE) score provided a basis for clinical immunotherapy in UM. Conclusion: The risk model has prognostic value for UM survival and provides new insights into the treatment of UM.

Deep learning classification of uveal melanoma based on histopathological images and identification of a novel indicator for prognosis of patients

BACKGROUND

Deep learning has been extensively used in digital histopathology. The purpose of this study was to test deep learning (DL) algorithms for predicting the vital status of whole-slide image (WSI) of uveal melanoma (UM).

METHODS

We developed a deep learning model (Google-net) to predict the vital status of UM patients from histopathological images in TCGA-UVM cohort and validated it in an internal cohort. The histopathological DL features extracted from the model and then were applied to classify UM patients into two subtypes. The differences between two subtypes in clinical outcomes, tumor mutation, and microenvironment, and probability of drug therapeutic response were investigated further.

RESULTS

We observed that the developed DL model can achieve a high accuracy of >  = 90% for patches and WSIs prediction. Using 14 histopathological DL features, we successfully classified UM patients into Cluster1 and Cluster2 subtypes. Compared to Cluster2, patients in the Cluster1 subtype have a poor survival outcome, increased expression levels of immune-checkpoint genes, higher immune-infiltration of CD8 + T cell and CD4 + T cells, and more sensitivity to anti-PD-1 therapy. Besides, we established and verified prognostic histopathological DL-signature and gene-signature which outperformed the traditional clinical features. Finally, a well-performed nomogram combining the DL-signature and gene-signature was constructed to predict the mortality of UM patients.

CONCLUSIONS

Our findings suggest that DL model can accurately predict vital status in UM patents just using histopathological images. We found out two subgroups based on histopathological DL features, which may in favor of immunotherapy and chemotherapy. Finally, a well-performing nomogram that combines DL-signature and gene-signature was constructed to give a more straightforward and reliable prognosis for UM patients in treatment and management.

MicroRNA as a Diagnostic Tool, Therapeutic Target and Potential Biomarker in Cutaneous Malignant Melanoma Detection—Narrative Review

Melanoma is the most serious type of skin cancer, causing a large majority of deaths but accounting for only ~1% of all skin cancer cases. The worldwide incidence of malignant melanoma is increasing, causing a serious socio-economic problem. Melanoma is diagnosed mainly in young and middle-aged people, which distinguishes it from other solid tumors detected mainly in mature people. The early detection of cutaneous malignant melanoma (CMM) remains a priority and it is a key factor limiting mortality. Doctors and scientists around the world want to improve the quality of diagnosis and treatment, and are constantly looking for new, promising opportunities, including the use of microRNAs (miRNAs), to fight melanoma cancer. This article reviews miRNA as a potential biomarker and diagnostics tool as a therapeutic drugs in CMM treatment. We also present a review of the current clinical trials being carried out worldwide, in which miRNAs are a target for melanoma treatment.

Advances in the role of SWI/SNF complexes in tumours

Cancer development is a complex process involving both genetic and epigenetic changes. The SWI/SNF (switch/sucrose non-fermentable) chromatin remodelling complex, one of the most studied ATP-dependent complexes, plays an important role in coordinating chromatin structural stability, gene expression and post-translational modifications. The SWI/SNF complex can be classified into BAF, PBAF and GBAF according to their constituent subunits. Cancer genome sequencing studies have shown a high incidence of mutations in genes encoding subunits of the SWI/SNF chromatin remodelling complex, with abnormalities in one or more of these genes present in nearly 25% of all cancers, which indicating that stabilizing normal expression of genes encoding subunits in the SWI/SNF complex may prevent tumorigenesis. In this paper, we will review the relationship between the SWI/SNF complex and some clinical tumours and its mechanism of action. The aim is to provide a theoretical basis to guide the diagnosis and treatment of tumours caused by mutations or inactivation of one or more genes encoding subunits of the SWI/SNF complex in the clinical setting.

The Cancer/Testis Antigen CT45A1 Promotes Transcription of Oncogenic Sulfatase-2 Gene in Breast Cancer Cells and Is Sensible Targets for Cancer Therapy

PURPOSE

Invasive breast carcinomas (BRCAs) are highly lethal. The molecular mechanisms underlying progression of invasive BRCAs are unclear, and effective therapies are highly desired. The cancer-testis antigen CT45A1 promotes overexpression of pro-metastatic sulfatase-2 (SULF2) and breast cancer metastasis to the lungs, but its mechanisms are largely unknown. In this study, we aimed to elucidate the mechanism of CT45A1-induced SULF2 overexpression and provide evidence for targeting CT45A1 and SULF2 for breast cancer therapy.

METHODS

The effect of CT45A1 on SULF2 expression was assessed using reverse transcription polymerase chain reaction and western blot. The mechanism of CT45A1-induced SULF2 gene transcription was studied using protein-DNA binding assay and a luciferase activity reporter system. The interaction between CT45A1 and SP1 proteins was assessed using immunoprecipitation and western blot. Additionally, the suppression of breast cancer cell motility by SP1 and SULF2 inhibitors was measured using cell migration and invasion assays.

RESULTS

CT45A1 and SULF2 are aberrantly overexpressed in patients with BRCA; importantly, overexpression of CT45A1 is closely associated with poor prognosis. Mechanistically, gene promoter demethylation results in overexpression of both CT45A1 and SULF2. CT45A1 binds directly to the core sequence GCCCCC in the promoter region of SULF2 gene and activates the promoter. Additionally, CT45A1 interacts with the oncogenic master transcription factor SP1 to drive SULF2 gene transcription. Interestingly, SP1 and SULF2 inhibitors suppress breast cancer cell migration, invasion, and tumorigenicity.

CONCLUSION

Overexpression of CT45A1 is associated with poor prognosis in patients with BRCA. CT45A1 promotes SULF2 overexpression by activating the promoter and interacting with SP1. Additionally, SP1 and SULF2 inhibitors suppress breast cancer cell migration, invasion, and tumorigenesis. Our findings provide new insight into the mechanisms of breast cancer metastasis and highlight CT45A1 and SULF2 as sensible targets for developing novel therapeutics against metastatic breast cancer.

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 5 microRNA biomarkers associated with the prognosis of uveal melanoma

To uncover the role of microRNAs in the occurrence and development of uveal melanoma (UM), we used R language packages in this study to analyze the correlations between the expression of microRNA isoforms, their target genes, and the clinical data for UM patients retrieved from The Cancer Genome Atlas (TCGA). We used Weighted Correlation Network Analysis (WGCNA) to divide the expression profiles of different microRNAs into 10 modules, among which blue and yellow modules were associated with UM survival. Hsa-miR-513a-5p, miR-506-3p, miR-508-3p, miR-140-3p, and miR-103a-2-5p were further identified as the top 5 node microRNAs based on the risk scores in both modules using least absolute shrinkage and selection operator (LASSO) Cox regression analysis. After combining these 5 microRNAs into an integrated risk signature, the prognostic performance of the risk signature was evaluated by area under the receiver operating characteristic (AUROC) curve, and their association with UM clinical characteristics was further analyzed using multiple Cox regression. Our results showed that this risk signature was sensitivity and specificity, and could serve as an independent prognostic factor. In addition, Spearman correlation analysis showed that expression of almost all target mRNAs were significantly positively or negatively correlated with the associated microRNAs. The gene ontology (GO), pathways, and disease enrichment analyses also showed that these 5 microRNAs were closely related to the incidence and progression of tumor, indicating their potential for predicting the outcome of UM.

MiR-520a-5p/PPP5C regulation pattern is identified as the key to gemcitabine resistance in pancreatic cancer

Objective

To explore the effects of the expression level of miR-520-5p/PPP5C in pancreatic cancer cells and exosomes on cell viability, angiogenesis, autophagy, which involved in the mechanism of gemcitabine resistance in pancreatic cancer.

Methods

APSC-1 cell line was treated with gemcitabine, after which its exosomes were extracted for NTA assay. Subsequently, the drug resistance of APSC-1 cells was assayed using CCK8, as well as the activity of HUVEC cells treated with exosomes from each group of APSC-1 cells after drug resistance treatment as well as overexpression treatment. Five groups of HUVEC cells treated with exosomes were subjected to in vitro tubule formation assay. levels of PPP5C in each group of ASPC-1 cells and their exosomes, levels of overexpressed PPP5C, and related exosomal proteins were examined by WB. mRNA expression levels of PPP5C and levels of miR-520a were examined by qPCR The relationship between miR-520a-5p and PPP5C was investigated. After that, the autophagy of PPP5C was detected. Finally, it was analyzed by TCGA database for survival prognosis analysis.

Results

APSC-1 cells had an IC50 value of 227.1 μM for gemcitabine, elevated PPP5C expression, drug resistance, and enhanced HUVEC cell activity; exosomes CD9, CD63, and CD81 were significantly expressed in all groups; meanwhile, enhanced PPP5C expression not only promoted in vitro tubule formation but also increased autophagy levels; meanwhile, its relationship with miR-520-5p and There was a targeted inhibitory relationship between its level and miR-520-5p and PPP5C, and its elevated level also led to a decrease in the survival level of patients over 3-5 years.

Conclusion

PPP5C has a prognostic role in pancreatic cancer by promoting the value-added and invasion of pancreatic cancer cells, and a targeted inhibitory relationship between miR-520-5p and PPP5C was found.

idenMD-NRF: a ranking framework for miRNA-disease association identification

Identifying miRNA-disease associations is an important task for revealing pathogenic mechanism of complicated diseases. Different computational methods have been proposed. Although these methods obtained encouraging performance for detecting missing associations between known miRNAs and diseases, how to accurately predict associated diseases for new miRNAs is still a difficult task. In this regard, a ranking framework named idenMD-NRF is proposed for miRNA-disease association identification. idenMD-NRF treats the miRNA-disease association identification as an information retrieval task. Given a novel query miRNA, idenMD-NRF employs Learning to Rank algorithm to rank associated diseases based on high-level association features and various predictors. The experimental results on two independent test datasets indicate that idenMD-NRF is superior to other compared predictors. A user-friendly web server of idenMD-NRF predictor is freely available at http://bliulab.net/idenMD-NRF/.

Proteomics analysis: inhibiting the expression of P62 protein by chloroquine combined with dacarbazine can reduce the malignant progression of uveal melanoma

Background

Although uveal melanoma (UM) at the early stage is controllable to some extent, it inevitably ultimately leads to death due to its metastasis. At present, the difficulty is that there is no way to effectively tackle the metastasis. It is hypothesized that these will be treated by target molecules, but the recognized target molecule has not yet been found. In this study, the target molecule was explored through proteomics.

Methods

Transgenic enhanced green fluorescent protein (EGFP) inbred nude mice, which spontaneously display a tumor microenvironment (TME), were used as model animal carriers. The UM cell line 92.1 was inoculated into the brain ventricle stimulating metastatic growth of UM, and a graft re-cultured Next, the UM cell line 92.1-A was obtained through monoclonal amplification, and a differential proteomics database, between 92.1 and ectopic 92.1-A, was established. Finally, bioinformatics methodologies were adopted to optimize key regulatory proteins, and in vivo and in vitro functional verification and targeted drug screening were performed.

Results

Cells and tissues displaying green fluorescence in animal models were determined as TME characteristics provided by hosts. The data of various biological phenotypes detected proved that 92.1-A were more malignant than 92.1. Besides this malignancy, the key protein p62 (SQSTM1), selected from 5267 quantifiable differential proteomics databases, was a multifunctional autophagy linker protein, and its expression could be suppressed by chloroquine and dacarbazine. Inhibition of p62 could reduce the malignancy degree of 92.1-A.

Conclusions

As the carriers of human UM orthotopic and ectopic xenotransplantation, transgenic EGFP inbred nude mice clearly display the characteristics of TME. In addition, the p62 protein optimized by the proteomics is the key protein that increases the malignancy of 92.1 cells, which therefore provides a basis for further exploration of target molecule therapy for refractory metastatic UM.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09499-z.

A Novel Four Genes of Prognostic Signature for Uveal Melanoma

Autophagy and immunity play critical roles in various cancers, but the prognostic impact of autophagy and immunity for uveal melanoma (UM) remains lacking. Therefore, the RNA sequencing of data in the TCGA-UVM dataset was downloaded from UCSC Xena database. The prognostic autophagy- and immunity-related genes (AIRGs) were selected via univariate Cox regression. Next, we applied LASSO method to construct four genes of signature in the TCGA-UVM and verified in another two GEO datasets (GSE84976 and GSE22138). This signature intimately associated with overall survival (OS) time and metastasis-free survival (MFS) time of UM, which could be considered as a prognostic indicator. Besides, by applying risk assessment, the patients of UM can be divided into two subgroups (high/low risk) with different survival time, distinct clinical outcomes, and immune microenvironments. Gene set enrichment analysis (GSEA) manifested that cancer hallmark epithelial-mesenchymal transition and KRAS pathways were positively activated in the high-risk group. Moreover, the high-risk group could be more sensitive to chemotherapies than the low-risk group. Thus, our finding suggested that the four genes of signature closely linked with UM risk and survival can afford more accurate survival prediction and potential therapeutic targets for clinical application.

Identification of the Tumor Immune Microenvironment and Therapeutic Biomarkers by a Novel Molecular Subtype Based on Aging-Related Genes in Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the most prevalent malignant tumors with poor prognosis. Increasing evidence has revealed that immune cells and checkpoints in the tumor microenvironment (TME) and aging are associated with the prognosis of HCC. However, the association between aging and the tumor immune microenvironment (TIME) in HCC is still unclear.

Methods

RNA expression profiles and clinical data concerning HCC were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Based on differentially expressed aging-related genes (DEAGs), unsupervised clustering was used to identify a novel molecular subtype in HCC. The features of immune cell infiltration and checkpoints were further explored through CIBERSORTx. Enrichment analysis and both univariate and multivariate Cox analyses were conducted to construct a 3-gene model for predicting prognosis and chemosensitivity. Finally, the mRNA and protein expression levels of the 3 genes were verified in HCC and other cancers through database searches and experiments.

Results

Eleven differentially expressed AGs (GHR, APOC3, FOXM1, PON1, TOP2A, FEN1, HELLS, BUB1B, PPARGC1A, PRKDC, and H2AFX) correlated with the prognosis of HCC were used to divide HCC into two subtypes in which the prognosis was different. In cluster 2, which had a poorer prognosis, the infiltration of naive B cells and monocytes was lower in the TCGA and GEO cohorts, while the infiltration of M0 macrophages was higher. In addition, the TCGA cohort indicated that the microenvironment of cluster 2 had more immunosuppression through immune checkpoints. Enrichment analysis suggested that the MYC and E2F targets were positively associated with cluster 2 in the TCGA and GEO cohorts. Additionally, 3 genes (HMGCS2, SLC22A1, and G6PD) were screened to construct the prognostic model through univariate/multivariate Cox analysis. Then, the model was validated through the TCGA validation set and GEO dataset (GSE54236). Cox analysis indicated that the risk score was an independent prognostic factor and that patients in the high-risk group were sensitive to multiple targeted drugs (sorafenib, gemcitabine, rapamycin, etc.). Finally, significantly differential expression of the 3 genes was detected across cancers.

Conclusion

We systematically described the immune differences in the TME between the molecular subtypes based on AGs and constructed a novel three-gene signature to predict prognosis and chemosensitivity in patients with HCC.

SWI/SNF Chromatin Remodeling Enzymes in Melanoma

Melanoma is an aggressive malignancy that arises from the transformation of melanocytes on the skin, mucosal membranes, and uvea of the eye. SWI/SNF chromatin remodeling enzymes are multi-subunit complexes that play important roles in the development of the melanocyte lineage and in the response to ultraviolet radiation, a key environmental risk factor for developing cutaneous melanoma. Exome sequencing has revealed frequent loss of function mutations in genes encoding SWI/SNF subunits in melanoma. However, some SWI/SNF subunits have also been demonstrated to have pro-tumorigenic roles in melanoma and to affect sensitivity to therapeutics. This review summarizes studies that have implicated SWI/SNF components in melanomagenesis and have evaluated how SWI/SNF subunits modulate the response to current therapeutics.

Profiling and Integrated Analysis of Differentially Expressed MicroRNAs as Novel Biomarkers of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a heterogeneous disease that has multiple etiologies. It is the most common primary liver cancer, the sixth highest cause of cancer incidences, and the fourth highest cause of cancer-related deaths. The discovery of new biomarkers for the early detection, treatment, and prognosis of HCC would therefore be extremely useful. This study investigated differentially expressed ribonucleic acid (RNA) profiles by constructing a genome-wide profile of clinical samples. Differential expression analysis identified 1,280 differentially expressed messenger RNAs (dif-mRNAs), 99 differentially expressed microRNAs (dif-miRNAs), 181 differentially expressed long non-coding RNAs (dif-lncRNAs), and 31 differentially expressed circular RNAs (dif-circRNAs). Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) path analysis were then conducted on these differentially expressed RNAs, revealing that they were clearly related to cell division, foreign body metabolism, and ribosome assembly. A competing endogenous RNA (ceRNA) network was then constructed based on the regulatory dif-miRNA-dif-mRNA and dif-miRNA-dif-lncRNA relationships. These results were also verified using HCC data from the Cancer Genome Atlas (TCGA); seven dif-miRNAs were verified in clinical samples by real-time quantitative polymerase chain reaction (RT-qPCR). Kaplan-Meier survival analysis revealed that the expression levels of Hsa-miR-1269a, Hsa-miR-421, and Hsa-miR-190b were correlated with overall survival. (P <0.05). Survival analysis of clinical samples showed that hsa-mir-1269a, hsa-mir-421 were associated with prognosis (p<0.05).This study revealed the general expression characteristics of specific differentially expressed miRNAs using a ceRNA network constructed from HCC samples. Hsa-mir-1269a, hsa-mir-421 may be promising candidates.

Identification of Prognostic alternative splicing signatures and their clinical significance in uveal melanoma

As a posttranscriptional regulatory mechanism, alternative splicing (AS) has the potential to generate a large amount of protein diversity from limited genes. The purpose of our study was to assess the usefulness of prognostic splicing events as novel diagnostic and therapeutic signatures for uveal melanoma (UM). The datasets, clinical traits and AS data of UM were obtained from The Cancer Genome Atlas (TCGA) database and TCGA SpliceSeq database. Using bioinformatics analysis, we identified 1047 AS events as candidate AS events closely related to prognosis from 920 parent genes. The gene enrichment analysis indicated that these genes were mainly enriched in cellular components (CC) including cytosol, nucleoplasm, cytoplasm and ribosome, and in molecular functions (MF), including protein binding and poly(A) RNA binding. Furthermore, we selected all survival-associated splicing events to generate prognostic signatures, which included 4 exon skip (ES) events (DNASE1L1-90581-ES, NUDT1-78611-ES, BIN1-55198-ES, SEPN1-1195-ES) and 1 alternate promoter (AP) event (DPYSL2-83132-AP). The AS prognostic model was confirmed as independent overall survival (OS)-related factors (p = 0.014). A total of 17 splicing factors (SFs) involved in the regulation of AS were identified as related to the OS of UM patients. Our pooled data highlighted the usefulness and importance of AS biomarkers, which provided a potential strategy for the diagnosis and treatment of UM.

Abnormal Expression of Mitochondrial Ribosomal Proteins and Their Encoding Genes with Cell Apoptosis and Diseases

Mammalian mitochondrial ribosomes translate 13 proteins encoded by mitochondrial genes, all of which play roles in the mitochondrial respiratory chain. After a long period of reconstruction, mitochondrial ribosomes are the most protein-rich ribosomes. Mitochondrial ribosomal proteins (MRPs) are encoded by nuclear genes, synthesized in the cytoplasm and then, transported to the mitochondria to be assembled into mitochondrial ribosomes. MRPs not only play a role in mitochondrial oxidative phosphorylation (OXPHOS). Moreover, they participate in the regulation of cell state as apoptosis inducing factors. Abnormal expressions of MRPs will lead to mitochondrial metabolism disorder, cell dysfunction, etc. Many researches have demonstrated the abnormal expression of MRPs in various tumors. This paper reviews the basic structure of mitochondrial ribosome, focuses on the structure and function of MRPs, and their relationships with cell apoptosis and diseases. It provides a reference for the study of the function of MRPs and the disease diagnosis and treatment.

The Role of Non-Coding RNAs in Uveal Melanoma

Simple Summary

The development of uveal melanoma is a multifactorial and multi-step process, in which abnormal gene expression plays a key role. Recently, several studies have highlighted the role of non-coding RNAs in the progression of uveal melanoma by affecting different signaling pathways. As important agents in the regulation of genes, non-coding RNAs have enormous potential to open up therapeutic pathways, predict response to treatment, and anticipate patient outcome for uveal melanoma. This review aims to provide a comprehensive view of what we know about ncRNAs in uveal melanoma currently.

Abstract

Uveal melanoma (UM) is the most common primary intraocular tumor in adulthood. Approximately 50% of patients develop metastatic disease, which typically affects the liver and is usually fatal within one year. This type of cancer is heterogeneous in nature and is divided into two broad groups of tumors according to their susceptibility to develop metastasis. In the last decade, chromosomal abnormalities and the aberrant expression of several signaling pathways and oncogenes in uveal melanomas have been described. Recently, importance has been given to the association of the mentioned deregulation with the expression of non-coding RNAs (ncRNAs). Here, we review the different classes of ncRNAs—such as long non-coding RNAs (lncRNAs) and microRNAs (miRNAs)—and their contribution to the development of UM. Special attention is given to miRNAs and their regulatory role in physiopathology and their potential as biomarkers. As important agents in gene regulation, ncRNAs have a huge potential for opening up therapeutic pathways, predicting response to treatment, and anticipating patient outcome for UM.