Integrated analysis of pseudogene RP11-564D11.3 expression and its potential roles in hepatocellular carcinoma

UHRF1P contributes to IL-17A-mediated systemic lupus erythematosus via UHRF1-MAP4K3 axis

Inflammatory T cells contribute to the pathogenesis of autoimmune diseases such as systemic lupus erythematosus (SLE). Analysis of the T-cell transcriptomics data of two independent SLE patient cohorts by three machine learning models revealed the pseudogene UHRF1P as a novel SLE biomarker. The pseudogene-encoded UHRF1P protein was overexpressed in peripheral blood T cells of SLE patients. The UHRF1P protein lacks the amino-terminus of its parental UHRF1 protein, resulting in missing the proteasome-binding ubiquitin-like (Ubl) domain of UHRF1. T-cell-specific UHRF1P transgenic mice manifested the induction of IL-17A and autoimmune inflammation. Mechanistically, UHFR1P prevented UHRF1-induced Lys48-linked ubiquitination and degradation of MAP4K3 (GLK), which is a kinase known to induce IL-17A. Consistently, IL-17A induction and autoimmune phenotypes of UHRF1P transgenic mice were obliterated by MAP4K3 knockout. Collectively, UHRF1P overexpression in T cells inhibits the E3 ligase function of its parental UHRF1 and induces autoimmune diseases.

A prognostic exosome-related long non-coding RNAs risk model related to the immune microenvironment and therapeutic responses for patients with liver hepatocellular carcinoma

Background

Liver hepatocellular carcinoma (LIHC) is the third largest cause of cancer mortality. Exosomes are vital regulators in the development of cancer. However, the mechanisms regarding the association of exosome-related long non-coding RNAs (lncRNAs) in LIHC are not clear.

Methods

LIHC RNA sequences and exosome-associated genes were collected according to The Cancer Genome Atlas (TCGA), Hepatocellular Carcinoma Cell DataBase (HCCDB) and ExoBCD databases, and exosome-related lncRNAs with prognostic differential expression were screened as candidate lncRNAs using Spearman's method and univariate Cox regression analysis. Candidate lncRNAs were then used to construct a prognostic model and mRNA-lncRNA co-expression network. Differentially expressed genes (DEGs) in low- and high-risk groups were identified and enrichment analysis was performed for up- and down-regulated DEGs, respectively. The expression of immune checkpoint-related genes, immune escape potential and microsatellite instability among different risk groups were further analyzed. Quantitative real-time polymerase chain reaction (qRT-PCR) and transwell assay were applied for detecting gene expression levels and invasion and migration ability.

Results

Based on 17 prognostical exosome-associated lncRNAs, four hub lncRNAs (BACE1_AS, DSTNP2, PLGLA, and SNHG3) were selected for constructing a prognostic model, which was demonstrated to be an independent prognostic variable for LIHC. High risk score was indicative of poorer overall survival, lower anti-tumor immune cells, higher genomic instability, higher immune escape potential, and less benefit for immunotherapy. The qRT-PCR test verified the expression level of the lncRNAs in LIHC cells, and the inhibitory effect of BACE1_AS on immune checkpoint genes levels. BACE1_AS silence also depressed the ability of migration and invasion of LIHC cells.

Conclusion

The Risk model constructed by exosome-associated lncRNAs could well predict immunotherapy response and prognostic outcomes for LIHC patients. We comprehensively reveal the clinical features of prognostical exosome-related lncRNAs and their potential ability to predict immunotherapeutic response of patients with LIHC and their prognosis.

The hsa-miR-3613-5p, a potential oncogene correlated with diagnostic and prognostic merits in kidney renal clear cell carcinoma

MicroRNA-3613 (hsa-miR-3613-5p), a biomarker with a dual role as an oncogenic or tumor suppressor, is associated with different types of cancer. This study aimed to determine the correlation between the hsa-miR-3613-5p gene expression and Kidney renal clear cell carcinoma (KIRC). Utilizing several bioinformatics tools, we examined the expression level and clinicopathological value of hsa-miR-3613-5p in patients with KIRC compared to normal tissues. Other bioinformatic measures, including survival analysis, diagnostic merit of hsa-miR-3613-5p, downstream target prediction, potential upstream lncRNAs, network construction, and functional enrichment analysis of hsa-miR-3613-5p, were performed. We observed that overexpression of hsa-miR-3613-5p in KIRC tissues had valuable diagnostic merit and was significantly correlated with the poor overall survival of KIRC patients. We also realized a correlation between abnormal expression of hsa-miR-3613-5p and several clinical parameters such as pathological stage, race, age, and histological grades in patients with KIRC. Moreover, we constructed the most potential regulatory network of hsa-miR-3613-5p in KIRC with 17 different axes, including four pseudogenes, two lncRNAs, and three mRNAs. Besides, we uncovered six variants in the mature form of hsa-miR-3613-5p. Finally, pathway enrichment analysis demonstrated that the top-ranked pathways for hsa-miR-3613-5p are cell cycle, cell adhesion molecules (CAMs), and hepatocellular carcinoma pathways. The present report suggests that the higher expression of hsa-miR-3613-5p is associated with the progression of KIRC. Therefore, it may be considered a valuable indicator for the early detection, risk stratification, and targeted treatment of patients with KIRC.

Two rare copy number variants involving loss of NPHP1, MALL, and MTLN genes contribute to nephronophthisis-induced nephropathy progression in a family: A case report

Nephronophthisis (NPHP) is a common pediatric cystic kidney disease, accounting for approximately 10% of end-stage renal failure cases in children. NPHP is primarily diagnosed through the identification of indel mutations and copy number variants (CNVs), and patients carrying NPHP1 mutations usually progress to renal failure at a mean age of 13 years old. However, the association between CNVs containing NPHP1 variations and the progression of NPHP-induced disease remains unclear. Here, we report three NPHP patients in a family. The proband had developed stage 4 chronic kidney disease (CKD) at 9 years old, and her younger brother and older sister had developed renal failure at 8 and 10 years old, respectively. A genetic diagnosis showed that they carried two rare CNVs, including homozygous loss of NPHP1, MALL, ACTR1AP1, MTLN, and LOC100507334. Heterozygous deletions mainly consisted of non-coding RNA genes on both sides of the CNVs. The proband was in stage 4 of CKD while her brother had progressed to renal failure, probably due to more extensive heterozygous deletion of a 67.115 kbp fragment, which included LIMS3-LOC440895, LOC440895, GPAA1P1, ZBTB45P1, and LINC0112 genes. This report demonstrates that larger CNV deletions, including homozygous NPHP1, MALL, and MTLN mutations and heterozygous deletions, presumably accelerate disease progression. Therefore, early genetic diagnosis plays a crucial role in the intervention and prognosis of these patients.

Pseudogene PLGLA exerts anti-tumor effects on hepatocellular carcinoma through modulating miR-324-3p/GLYATL1 axis

BACKGROUND

Pseudogenes are dysfunctional copies of protein-coding genes that showed critical regulatory roles during carcinogenesis. Plasminogen like A (PLGLA) is a transcribed unprocessed pseudogene and biasedly expressed in liver. But its function has not been studied in hepatocellular carcinoma (HCC).

AIMS

We aimed to explore the role of PLGLA in HCC.

METHODS

The expression of PLGLA and its association with pathological features in HCC patients was analyzed using The Cancer Genome Atlas (TCGA) datasets. Quantitative reverse transcription PCR (qRT-PCR) was used to validate PLGLA level in HCC tissue samples and cell lines. Gain-of-function experiments in vitro and in vivo were employed to assess the impact of PLGLA on HCC cell proliferation, migration and invasion. Luciferase reporter assay and RNA pull-down assay were conducted to confirm the interaction among PLGLA, miR-324-3p and GLYATL1.

RESULTS

PLGLA expression was significantly downregulated in HCC tissues and cell lines. Furthermore, low PLGLA expression was positively associated with tumor progression and poor prognosis. PLGLA restoration markedly suppressed cell proliferation, migration and invasion. Mechanistically, PLGLA could competitively bind to miR-324-3p and acted as a competitive endogenous RNA (ceRNA) to enhance GLYATL1 expression.

CONCLUSIONS

Our results established a novel tumor suppressive role of PLGLA in HCC pathogenesis and highlighted its potential as a therapeutic target for HCC treatment.

Ovarian Cancer Risk Scores Based on Immune-Related Pseudogenes to Predict Overall Survival and Guide Immunotherapy and Chemotherapy

Background

Ovarian cancer (OC) is the top of the aggressive malignancies in females with a poor survival rate. However, the roles of immune-related pseudogenes (irPseus) in the immune infiltration of OC and the impact on overall survival (OS) have not been adequately studied. Therefore, this study aims to identify a novel model constructed by irPseus to predict OS in OC and to determine its significance in immunotherapy and chemotherapy.

Methods

In this study, with the use of The Cancer Genome Atlas (TCGA) combined with Genotype-Tissue Expression (GTEx), 55 differentially expressed irPseus (DEirPseus) were identified. Then, we constructed 10 irPseus pairs with the help of univariate, Lasso, and multivariate Cox regression analysis. The prognostic performance of the model was determined and measured by the Kaplan-Meier curve, a time-dependent receiver operating characteristic (ROC) curve.

Results

After dividing OC subjects into high- and low-risk subgroups via the cut-off point, it was revealed that subjects in the high-risk group had a shorter OS. The multivariate Cox regression performed between the model and multiple clinicopathological variables revealed that the model could effectively and independently predict the prognosis of OC. The prognostic model characterized infiltration by various kinds of immune cells and demonstrated the immunotherapy response of subjects with cytotoxic lymphocyte antigen 4 (CTLA4), anti-programmed death-1 (PD-1), and anti-PD-ligand 1 (PD-L1) therapy. A high risk score was related to a higher inhibitory concentration (IC₅₀) for etoposide (P=0.0099) and mitomycin C (P=0.0013).

Conclusion

It was the first study to identify a novel signature developed by DEirPseus pairs and verify the role in predicting OS, immune infiltrates, immunotherapy, and chemosensitivity. The irPseus are vital factors predicting the prognosis of OC and could act as a novel potential treatment target.

LncRNA EBLN3P promotes the progression of osteosarcoma through modifying the miR-224-5p/Rab10 signaling axis

The treatment of patients with advanced-stage osteosarcoma represents a major challenge, with very few treatments currently approved. Although accumulating evidence has demonstrated the importance of lncRNAs in osteosarcoma, the current knowledge on the functional roles and molecular mechanisms of lncRNA endogenous born avirus-like nucleoprotein (EBLN3P) is limited. At present, the expressions of EBLN3P and miR-224-5p in osteosarcoma tissues were quantified by reverse transcription-quantitative PCR assay, and the expression of Ras-related protein 10 (Rab10) in osteosarcoma tissues was quantified by immunohistochemistry and western-blotting. The bioinformatics prediction software ENCORI was used to predict the putative binding sites of EBLN3P, Rab10 and miR-224-5p. The regulatory role of EBLN3P or miR-224-5p on cell proliferation, migration and invasion ability were verified by Cell Counting Kit-8, wound healing and Transwell assays, respectively. The interaction among EBLN3P, miR-224-5p and Rab10 were testified by luciferase. The increased expression of EBLN3P and Rab10 and decreased expression of miR-224-5p were observed in osteosarcoma tissues and cell lines. Besides, the overexpression of EBLN3P or knockdown of miR-224-5p were revealed to promote the proliferation, migration and invasion of osteosarcoma cells. Bioinformatics analysis and luciferase assay revealed that EBLN3P could directly interacted with miR-224-5p to attenuate miR-224-5p binding to the Rab10 3'-untranslated region. Furthermore, the mechanistic investigations revealed activation of the miR-224-5p/Rab10 regulatory loop by knockdown of miR-372-3p or overexpression of Rab10, thereby confirming the in vitro role of EBLN3P in promoting osteosarcoma cell proliferation, migration and invasion. To the best of our knowledge, the present study is the first to demonstrate that EBLN3P may act as a competitive endogenous RNA to modulate Rab10 expression by competitive sponging to miR-224-5p, leading to the regulation of osteosarcoma progression, which indicates a possible new approach to osteosarcoma diagnosis and treatment.

Development and validation of a novel pseudogene pair-based prognostic signature for prediction of overall survival in patients with hepatocellular carcinoma

BACKGROUND

There is growing evidence that pseudogenes may serve as prognostic biomarkers in several cancers. The present study was designed to develop and validate an accurate and robust pseudogene pairs-based signature for the prognosis of hepatocellular carcinoma (HCC).

METHODS

RNA-sequencing data from 374 HCC patients with clinical follow-up information were obtained from the Cancer Genome Atlas (TCGA) database and used in this study. Survival-related pseudogene pairs were identified, and a signature model was constructed by Cox regression analysis (univariate and least absolute shrinkage and selection operator). All individuals were classified into high- and low-risk groups based on the optimal cutoff. Subgroups analysis of the novel signature was conducted and validated in an independent cohort. Pearson correlation analyses were carried out between the included pseudogenes and the protein-coding genes based on their expression levels. Enrichment analysis was performed to predict the possible role of the pseudogenes identified in the signature.

RESULTS

A 19-pseudogene pair signature, which included 21 pseudogenes, was established. Patients in high-risk group demonstrated an increased the risk of adverse prognosis in the TCGA cohort and the external cohort (all P < 0.001). The novel pseudogene signature was independent of other conventional clinical variables used for survival prediction in HCC patients in the two cohorts revealed by the multivariate Cox regression analysis (all P < 0.001). Subgroup analysis further demonstrated the diagnostic value of the signature across different stages, grades, sexes, and age groups. The C-index of the prognostic signature was 0.761, which was not only higher than that of several previous risk models but was also much higher than that of a single age, sex, grade, and stage risk model. Furthermore, functional analysis revealed that the potential biological mechanisms mediated by these pseudogenes are primarily involved in cytokine receptor activity, T cell receptor signaling, chemokine signaling, NF-κB signaling, PD-L1 expression, and the PD-1 checkpoint pathway in cancer.

CONCLUSION

The novel proposed and validated pseudogene pair-based signature may serve as a valuable independent prognostic predictor for predicting survival of patients with HCC.

Pseudogene-Derived lncRNAs and Their miRNA Sponging Mechanism in Human Cancer

Pseudogenes, abundant in the human genome, are traditionally considered as non-functional “junk genes.” However, recent studies have revealed that pseudogenes act as key regulators at DNA, RNA or protein level in diverse human disorders (including cancer), among which pseudogene-derived long non-coding RNA (lncRNA) transcripts are extensively investigated and has been reported to be frequently dysregulated in various types of human cancer. Growing evidence demonstrates that pseudogene-derived lncRNAs play important roles in cancer initiation and progression by serving as competing endogenous RNAs (ceRNAs) through competitively binding to shared microRNAs (miRNAs), thus affecting both their cognate genes and unrelated genes. Herein, we retrospect those current findings about expression, functions and potential ceRNA mechanisms of pseudogene-derived lncRNAs in human cancer, which may provide us with some crucial clues in developing potential targets for cancer therapy in the future.

Application of Machine Learning in Developing a Novelty Five-Pseudogene Signature to Predict Prognosis of Head and Neck Squamous Cell Carcinoma: A New Aspect of "Junk Genes" in Biomedical Practice

Head and neck squamous cell carcinoma (HNSCC) is the sixth malignancy, which is characterized by poor prognosis or high mortality because of the lack of predicting markers. Aberrant cancer pseudogenes have been found predictive for prognosis. We aim to identify a pseudogene-based prognosis signature for HNSCC by machine learning. RNA-seq data were downloaded from The Cancer Genome Atlas, and 700 differentially-expressed pseudogenes were identified. The survival-related pseudogenes were screened through COX-regression analysis, which includes univariate regression, least absolute shrinkage and selection operator regression, and multivariate regression, and a five-pseudogene signature was constructed. The value of prediction for the signature was validated in multiple subgroups in terms of survival. Gene set enrichment analysis (GSEA) and coexpression analysis were used to determine the underlying biological functions. Seven hundred dysregulated pseudogenes were identified, and the five-pseudogene signature can distinguish the low-risk and high-risk patients for both training and testing sets and predicted prognosis with high sensitivity and specificity. Furthermore, the signature was applicable to patients of different genders, ages, stages, and grades. Coexpression analysis revealed that the five-pseudogene is associated with immune system. GSEA showed cancer-related biological process and pathways the five-pseudogene involved in. The five-pseudogene signature is not only a novel marker for prognosis but also a promising signature for monitoring therapeutic schedule. Therefore, our findings may have potential clinical significance.

Comprehensive analysis of pseudogene HSPB1P1 and its potential roles in hepatocellular carcinoma

The incidence and mortality rate of hepatocellular carcinoma (HCC) nowadays is still at high levels. The regulatory roles of pseudogene in cancers have been gradually recognized in recent years. However, comprehensive investigation of abnormally expressed pseudogene and related mechanisms in HCC remains lacking. GSE124535 dataset was used to identify differentially expressed pseudogenes in HCC tissues compared with normal tissues. Prognostic value of these differentially expressed pseudogenes was analyzed at GEPIA. StarBase used to analyze microRNAs (miRNAs) can bind with pseudogene, while the targets for these miRNAs were analyzed at miRTarBase. Protein-protein interaction (PPI) network was then established for miRNA targets, after that hub genes were selected. Expression correlation of pseudogene and hub genes was analyzed at StarBase. In total, 16 upregulated and 17 downregulated pseudogenes were identified. Pseudogene HSPB1P1 was identified abnormally expressed in 20 types of human cancers and could be used as an indicator for poorer overall survival of patients with HCC. Functional analyses showed that HSPB1P1 was strongly correlated with signaling pathways related to cancer progression. Further studied revealed that HSPB1P1 could direct regulate the EZH2 expression in HCC. In summary, our study indicated that HSPB1P1 was a predictor for poorer overall survival of patients with HCC and may be potential therapeutic target against HCC.

Re-recognition of pseudogenes: From molecular to clinical applications

Pseudogenes were initially regarded as "nonfunctional" genomic elements that did not have protein-coding abilities due to several endogenous inactivating mutations. Although pseudogenes are widely expressed in prokaryotes and eukaryotes, for decades, they have been largely ignored and classified as gene "junk" or "relics". With the widespread availability of high-throughput sequencing analysis, especially omics technologies, knowledge concerning pseudogenes has substantially increased. Pseudogenes are evolutionarily conserved and derive primarily from a mutation or retrotransposon, conferring the pseudogene with a "gene repository" role to store and expand genetic information. In contrast to previous notions, pseudogenes have a variety of functions at the DNA, RNA and protein levels for broadly participating in gene regulation to influence the development and progression of certain diseases, especially cancer. Indeed, some pseudogenes have been proven to encode proteins, strongly contradicting their "trash" identification, and have been confirmed to have tissue-specific and disease subtype-specific expression, indicating their own value in disease diagnosis. Moreover, pseudogenes have been correlated with the life expectancy of patients and exhibit great potential for future use in disease treatment, suggesting that they are promising biomarkers and therapeutic targets for clinical applications. In this review, we summarize the natural properties, functions, disease involvement and clinical value of pseudogenes. Although our knowledge of pseudogenes remains nascent, this field deserves more attention and deeper exploration.

Generation of a Transcriptional Radiation Exposure Signature in Human Blood Using Long-Read Nanopore Sequencing

In the event of a large-scale event leading to acute ionizing radiation exposure, high-throughput methods would be required to assess individual dose estimates for triage purposes. Blood-based gene expression is a broad source of biomarkers of radiation exposure which have great potential for providing rapid dose estimates for a large population. Time is a crucial component in radiological emergencies and the shipment of blood samples to relevant laboratories presents a concern. In this study, we performed nanopore sequencing analysis to determine if the technology can be used to detect radiation-inducible genes in human peripheral blood mononuclear cells (PBMCs). The technology offers not only long-read sequencing but also a portable device which can overcome issues involving sample shipment, and provide faster results. For this goal, blood from nine healthy volunteers was 2 Gy ex vivo X irradiated. After PBMC isolation, irradiated samples were incubated along with the controls for 24 h at 37°C. RNA was extracted, poly(A)+ enriched and reverse-transcribed before sequencing. The data generated was analyzed using a Snakemake pipeline modified to handle paired samples. The sequencing analysis identified a radiation signature consisting of 46 differentially expressed genes (DEGs) which included 41 protein-coding genes, a long non-coding RNA and four pseudogenes, five of which have been identified as radiation-responsive transcripts for the first time. The genes in which transcriptional expression is most significantly modified after radiation exposure were APOBEC3H and FDXR, presenting a 25- and 28-fold change on average, respectively. These levels of transcriptional response were comparable to results we obtained by quantitative polymerase chain reaction (qPCR) analysis. In vivo exposure analyses showed a transcriptional radioresponse at 24 h postirradiation for both genes together with a strong dose-dependent response in blood irradiated ex vivo. Finally, extrapolating from the data we obtained, the minimum sequencing time required to detect an irradiated sample using APOBEC3H transcripts would be less than 3 min for a total of 50,000 reads. Future improvements, in sample processing and bioinformatic pipeline for specific radiation-responsive transcript identification, will allow the provision of a portable, rapid, real-time biodosimetry platform based on this new sequencing technology. In summary, our data show that nanopore sequencing can identify radiation-responsive genes and can also be used for identification of new transcripts.

A disparate role of RP11-424C20.2/UHRF1 axis through control of tumor immune escape in liver hepatocellular carcinoma and thymoma

The immune system is critical in modulating cancer progression. Pseudogenes are a special type of long non-coding RNAs that regulate different tumorigenic processes. However, the potential roles of pseudogenes in tumor-immune interaction remain largely unclear. Here, we reported that pseudogene RP11-424C20.2 and its parental gene UHRF1 were frequently up-regulated and positively correlated in liver hepatocellular carcinoma (LIHC) and thymoma (THYM), but associated with distinct clinical outcomes. We further found that RP11-424C20.2 may act as a competing endogenous RNA (ceRNA) to increase UHRF1 expression through sponging miR-378a-3p. Functional enrichment analysis showed a strong association of UHRF1 with immune-related biological processes. We also observed that UHRF1 expression significantly correlated with immune infiltration, and different types of tumor-infiltrating immune cells displayed different impacts on clinical outcomes. Furthermore, UHRF1 expression in LIHC and THYM showed an opposite correlation with biomarkers from monocyte, dendritic cell, Th1 and T cell exhaustion. Mechanism investigations revealed that RP11-424C20.2/UHRF1 axis regulated immune escape of LIHC and THYM at least partly through IFN-γ-mediated CLTA-4 and PD-L1 pathway. These findings demonstrate a disparate role of RP11-424C20.2/UHRF1 axis in LIHC and THYM via regulating immune infiltrates, and also indicate a therapeutic value for UHRF1 inhibitors in combination with anti-PD-L1/CLTA-4 blockade.

Overexpressed pseudogenes, DUXAP8 and DUXAP9, promote growth of renal cell carcinoma and serve as unfavorable prognostic biomarkers

BACKGROUND

Growing studies have reported that pseudogenes play key roles in multiple human cancers. However, expression and roles of pseudogenes in renal cell carcinoma remains absent.

RESULTS

31 upregulated and 16 downregulated pseudogenes were screened. Higher expression of DUXAP8 and DUXAP9 indicated poorer prognosis of kidney cancer. 33 and 5 miRNAs were predicted to potentially binding to DUXAP8 and DUXAP9, respectively. miR-29c-3p was identified as the most potential binding miRNAs of DUXAP8 and DUXAP9 based on expression, survival and correlation analyses. 254 target genes of miR-29c-3p were forecast. 47 hub genes with node degree >= 10 were identified. Subsequent analysis for the top 10 hub genes demonstrated that COL1A1 and COL1A2 may be two functional targets of DUXAP8 and DUXAP9. Expression of DUXAP8, DUXAP9, COL1A1 and COL1A2 were significantly increased in cancer samples compared to normal controls while miR-29c-3p expression was decreased. Luciferase reporter assay revealed that miR-29c-3p could directly bind to DUXAP8, DUXAP9, COL1A1 and COL1A2. Functional experiments showed that DUXAP8 and DUXAP9 enhanced but miR-29c-3p weakened growth of renal cell carcinoma.

CONCLUSIONS

In conclusion, upregulated DUXAP8 and DUXAP9 promote growth of renal cell carcinoma and serve as two promising prognostic biomarkers.

METHODS

Dysregulated pseudogenes were obtained by dreamBase and GEPIA. The binding miRNAs of pseudogene and targets of miRNA were predicted using starBase and miRNet. Kaplan-Meier plotter was utilized to perform survival analysis, and Enrichr database was introduced to conduct functional enrichment analysis. Hub genes were identified through STRING and Cytoscape. qRT-PCR, luciferase reporter assay, cell counting assay and colony formation assay were performed to validate in silico analytic results.

A Four-Pseudogene Classifier Identified by Machine Learning Serves as a Novel Prognostic Marker for Survival of Osteosarcoma

Osteosarcoma is a common malignancy with high mortality and poor prognosis due to lack of predictive markers. Increasing evidence has demonstrated that pseudogenes, a type of non-coding gene, play an important role in tumorigenesis. The aim of this study was to identify a prognostic pseudogene signature of osteosarcoma by machine learning. A sample of 94 osteosarcoma patients’ RNA-Seq data with clinical follow-up information was involved in the study. The survival-related pseudogenes were screened and related signature model was constructed by cox-regression analysis (univariate, lasso, and multivariate). The predictive value of the signature was further validated in different subgroups. The putative biological functions were determined by co-expression analysis. In total, 125 survival-related pseudogenes were identified and a four-pseudogene (RPL11-551L14.1, HR: 0.65 (95% CI: 0.44–0.95); RPL7AP28, HR: 0.32 (95% CI: 0.14–0.76); RP4-706A16.3, HR: 1.89 (95% CI: 1.35–2.65); RP11-326A19.5, HR: 0.52(95% CI: 0.37–0.74)) signature effectively distinguished the high- and low-risk patients, and predicted prognosis with high sensitivity and specificity (AUC: 0.878). Furthermore, the signature was applicable to patients of different genders, ages, and metastatic status. Co-expression analysis revealed the four pseudogenes are involved in regulating malignant phenotype, immune, and DNA/RNA editing. This four-pseudogene signature is not only a promising predictor of prognosis and survival, but also a potential marker for monitoring therapeutic schedule. Therefore, our findings may have potential clinical significance.

High Expression of Pseudogene PTTG3P Indicates a Poor Prognosis in Human Breast Cancer

Pseudogenes play pivotal roles in tumorigenesis. Previous studies have suggested that pituitary tumor-transforming 3, pseudogene (PTTG3P), serves as an oncogene in human cancers. However, its expression pattern, biological function, and underlying mechanism in breast cancer remain unknown. In this study, we demonstrated an elevated expression of PTTG3P in breast cancer and discovered that PTTG3P expression correlated negatively with estrogen receptor (ER) and progesterone receptor (PR) status, but linked positively to basal-like status, triple-negative breast cancer status, Nottingham prognostic index (NPI), and Scarff-Bloom-Richardson grade. High expression of PTTG3P was also found to be associated with a poor prognosis of breast cancer. To explore the potential mechanisms of PTTG3P, a PTTG3P-microRNA (miRNA)-mRNA regulatory network was established. Co-expressed genes of PTTG3P were also obtained. Enrichment analysis for these co-expressed genes revealed that they were significantly enriched in mitotic nuclear division and cell cycle. Subsequent research on mechanism of PTTG3P indicated that its expression correlated positively with PTTG1 expression. However, no significant expression correlation between PTTG3P and PTTG2 was observed. Taken together, our findings suggest that increased expression of pseudogene PTTG3P may be used as a promising prognostic biomarker and novel therapeutic target for breast cancer.