Search

Mesothelioma (MESO) is an infrequent tumor derived from mesothelial cells of pleura, peritoneum, pericardium, and tunica vaginalis testis. Despite advancement in technologies and better understanding of tumor progression mechanism, the prognosis of MESO remains poor. The role of alternative splicing events (ASEs) in the oncogenesis, tumor metastasis and drug resistance has been widely discussed in multiple cancers. But the prognosis and potential therapeutic value of ASEs in MESO were not clearly studied by now. We constructed a prognostic model using RNA sequencing data and matched ASE data of MESO patients obtained from the TCGA and TCGASpliceSeq database. A total of 3,993 ASEs were identified associated with overall survival using Cox regression analysis. Eight of them were finally figured out to institute the model by lasso regression analysis. The risk score of the model can predict the prognosis independently. Among the identified 390 splicing factors (SF), HSPA1A and DDX3Y was significantly associated with 43 OS‐SEs. Among these OS‐SEs, SNX5‐58744‐AT (p = 0.048) and SNX5‐58745‐AT (p = 0.048) were significantly associated with bone metastasis. Co‐expression analysis of signal pathways and SNX5‐58744‐AT, SNX5‐58745‐AT was also depicted using GSVA. Finally, we proposed that splicing factor (SF) HSPA1A could regulate SNX5‐58744‐AT (R = −0.414) and SNX5‐58745‐AT (R = 0.414) through the pathway “Class I MHC mediated antigen processing and presentation” (R = 0.400). In this way, tumorigenesis and bone metastasis of MESO were controlled., Despite advancement in technologies and better understanding of tumor progression mechanism, the prognosis of Mesothelioma (MESO) remains poor. Alternative splicing events (ASEs) are widely reported in the tumorigenesis, metastasis and drug resistance of multiple cancers. Based on the results of this study, we proposed that splicing factor (SF) HSPA1A could regulate SNX5‐58744‐AT (R = ‐0.414) and SNX5‐58745‐AT through “Class I MHC mediated antigen processing and presentation” pathway and subsequently impact tumorigenesis and bone metastasis of MESO. more...

Background Soft tissue sarcomas (STS) has a high rate of early metastasis. In this study, we aimed to uncover the potential metastasis mechanisms and related signaling pathways in STS with differentially expressed genes and tumor-infiltrating cells. Methods RNA-sequencing (RNA-seq) of 261 STS samples downloaded from the Cancer Genome Atlas (TCGA) database were used to identify metastasis-related differentially expressed immune genes and transcription factors (TFs), whose relationship was constructed by Pearson correlation analysis. Metastasis-related prediction model was established based on the most significant immune genes. CIBERSORT algorithm was performed to identify significant immune cells co-expressed with key immune genes. The GSVA and GSEA were performed to identify prognosis-related KEGG pathways. Ultimately, we used the Pearson correlation analysis to explore the relationship among immune genes, immune cells, and KEGG pathways. Additionally, key genes and regulatory mechanisms were validated by single-cell RNA sequencing and ChIP sequencing data. Results A total of 204 immune genes and 12 TFs, were identified. The prediction model achieved a satisfactory effectiveness in distant metastasis with the Area Under Curve (AUC) of 0.808. LTB was significantly correlated with PAX5 (P Conclusions We hypothesized that down-regulated LTB (immune gene) modulated by PAX5 (TF) in STSs may have the capability of inducing cancer cell metastasis in patients with STS. more...

STUDY DESIGN A retrospective data analysis was performed. OBJECTIVE The aim of this study is to explore the significant prognostic factors and propose new nomograms to facilitate clinical decision-making. SUMMARY OF BACKGROUND DATA Chordoma is a rare bone tumor. The clinical features and optimal therapeutic strategies are still uncertain. METHODS Chordoma patients treated in four medical centers of mainland China before January 2015 were included. The predictors for local relapse-free survival (LRFS) and overall survival (OS) were identified by the Lasso regression and Cox proportional hazards regression model. Then the nomograms were developed. Their discrimination, calibration, and accuracy were evaluated by the C-index, calibration curve, and receiver operating characteristic curve (ROC), respectively. RESULTS A total of 341 patients were identified and full prognostic variable data were available for 276 patients. A total of 179 patients (64.9%) experienced recurrence and 122 patients (44.2%) died of all causes with a median follow-up time of 57.5 (range, 1-325) months. We identified recurrence-relevant factors of tumor size, tumor location, histology subtype and resection method, and death-relevant factors of tumor size, tumor location, resection method, complication, and postoperative recurrence. The constructed LRFS and OS nomograms showed good calibration and discriminative ability (C index 0.79 and 0.76, respectively). The ROCs suggested decent prediction ability with the 5-year area under curve (AUC) value of 0.868 and 0.786, respectively. CONCLUSION Based on the multicenter case series of chordoma with a relative long follow-up, we proposed two nomograms to predict the prognosis on the basis of recurrence- and death-relevant factors. These findings could be referenced in the clinical decision-making process and provide additional prognostic information for risk stratification. LEVEL OF EVIDENCE 4. more...

Peroxisome proliferator-activated receptors (PPARs) are members of nuclear transcription factors. The functions of the PPAR family (PPARA, PPARD, and PPARG) and their coactivators (PPARGC1A and PPARGC1B) in maintenance of lipid and glucose homeostasis have been unveiled. However, the roles of PPARs in cancer development remain elusive. In this work, we made use of 11,057 samples across 33 TCGA tumor types to analyze the relationship between PPAR transcriptional expression and tumorigenesis as well as drug sensitivity. We performed multidimensional analyses on PPARA, PPARG, PPARD, PPARGC1A, and PPARGC1B, including differential expression analysis in pan-cancer, immune subtype analysis, clinical analysis, tumor purity analysis, stemness correlation analysis, and drug responses. PPARs and their coactivators expressed differently in different types of cancers, in different immune subtypes. This analysis reveals various expression patterns of the PPAR family at a level of pan-cancer and provides new clues for the therapeutic strategies of cancer. more...

Some studies suggested the prognosis value of immune gene in lower grade glioma (LGG). Recurrence in LGG is a tough clinical problem for many LGG patients. Therefore, prognosis biomarker is required. Multivariate prognosis Cox model was constructed and then calculated the risk score. And differential expressed transcription factors (TFs) and differential expressed immune genes (DEIGs) were co‐analysed. Besides, significant immune cells/pathways were identified by single sample gene set enrichment analysis (ssGSEA). Moreover, gene set variation analysis (GSVA) and univariate Cox regression were applied to filter prognostic signalling pathways. Additionally, significant DEIG and immune cells/pathways, and significant DEIG and pathways were co‐analysed. Further, differential enriched pathways were identified by GSEA. In sum, a scientific hypothesis for recurrence LGG including TF, immune gene and immune cell/pathway was established. In our study, a total of 536 primary LGG samples, 2,498 immune genes and 318 TFs were acquired. Based on edgeR method, 2,164 DEGs, 2,498 DEIGs and 31 differentials expressed TFs were identified. A total of 106 DEIGs were integrated into multivariate prognostic model. Additionally, the AUC of the ROC curve was 0.860, and P value of Kaplan‐Meier curve more...

Background Maternal vitamin D deficiency has been a worldwide concern in recent years. However the epidemiological data of vitamin D deficiency among large group of Chinese pregnant women is limited. This study is to evaluate the prevalence of vitamin D deficiency among pregnant women in Shanghai, China and to analyze the association of vitamin D status with some pregnancy outcomes (gestational diabetes and low birth weight). Methods A total of 34,417 pregnant women in Shanghai were included in this study from January 2014 to December 2017, and the serum 25-hydroxyvitamin D [25(OH)D] concentrations were measured at 16th week of gestation by electrochemiluminescence assay. Seventy five grams of glucose was used to conduct oral glucose tolerance test during 24-28th week of gestational in all enrolled persons and the birth weight of newborns was recorded. Results The median serum 25(OH) D concentration in the pregnant women during 4 years was 42.87 nmol/L (32.88–51.90 nmol/L). 9.9% of the population were severe vitamin D deficient [25(OH)D Conclusion Pregnant women in Shanghai were generally deficient in vitamin D status and the level of vitamin D was related to season and age. No evidence showed vitamin D deficiency in pregnant women contributes to the rate of gestational diabetes or low birth weight of newborns in this study. These results suggest that most of the pregnant women may need vitamin D supplementation to achieve adequate vitamin D level. more...

Aβ plaques of Alzheimer's disease (AD) are believed to precede cognitive deficits or clinical manifestation by decades. However, validated biomarkers for early diagnosis of the AD disease are still not available. In this present study, we combined MRI-based neuroimages and histological assessment of the glial response and altered cytokines, neurogenesis during the early course of Aβ deposits in TgAPP/PS1 mice to find potential early biomarkers for AD. We found that microglia and astrocytes were initially activated and clustered around Aβ plaques at the age of 6 months and significantly increased with age from 6-12 months of age. Confocal microscope analysis revealed that microglia not astrocytes began to phagocytose Aβ in 6-month-old TgAPP/PS1 mice, evidenced by the intracellular Aβ in Iba1 positive microglia not in GFAP positive astrocytes. In parallel with these observations, we found that mainly clustered microglia significantly upregulated the production of proinflammatory factors including TNF-α, iNOS and IL-1β, and anti-inflammatory cytokines including IL-4, TGF-β and extracellular protecting matrix YM-1 and enzyme arginase 1 (Arg1) at 6-12 months of age. Interestingly, reactive astrocyte did not express these cytokines and YM-1 and Arg1. These results may suggest that microglia rather than astrocytes play crucial roles in clearing Aβ and neuroinflammation in early stage of AD. In addition, the number of neural stem cells labeled by BrdU and immature neurons labeled by doublecortin was significantly decreased in 3-month-old TgAPP/PS1 mice ahead of Aβ deposits. Finally, DTI conforms that reduced fractional anisotropy (FA) in dentate gyrus of hippocampus and rs-MRI shows an increased connectivity in the networks of somatosensory cortex-caudoputamen and insula in TgAPP/PS1 mice at 6 months. These findings provide a clue to early biomarkers for diagnosis of the AD disease. more...

BACKGROUND Osteosarcoma is one of the most common bone tumors, with strong local aggressiveness and early metastasis. The aim of this study was to describe the epidemiological data and evaluate the prognostic factors for overall survival (OS) and cause-specific survival (CSS) in patients with non-metastatic osteosarcoma. MATERIAL AND METHODS Patients histologically diagnosed with non-metastatic osteosarcoma between 2005 and 2014 were selected from the Surveillance, Epidemiology, and End Results (SEER) database. Survival analysis, machine learning, and Lasso regression were used to identify the prognostic factors for OS and CSS, and the accuracy of the nomograms was tested and compared with the American Joint Committee on Cancer (AJCC) staging systems. RESULTS The entire cohort comprised 1000 patients with non-metastatic osteosarcoma. The multivariable analysis suggested that age, tumor size, grade, and American Joint Committee on Cancer (AJCC) T staging were independent prognostic factors for OS and CSS. Additionally, the nomograms based on these results could better predict probability of OS (Internal validation C-index, 0.7095) and CSS (0.7100) compared with the sixth (OS: 0.613; CSS: 0.628) and seventh edition AJCC staging systems (0.602, 0.613). CONCLUSIONS Relatively young age and low histopathological grade were favorable factors for both OS and CSS. Nomograms based on multivariable models worked well in predicting the probability of death for patients with non-metastatic osteosarcoma. more...

Background The coronavirus disease 2019 (COVID-19) has induced a worldwide epidemiological event with a high infectivity and mortality. However, the predicting biomarkers and their potential mechanism in the progression of COVID-19 are not well known. Objective The aim of this study is to identify the candidate predictors of COVID-19 and investigate their underlying mechanism. Methods The retrospective study was conducted to identify the potential laboratory indicators with prognostic values of COVID-19 disease. Then, the prognostic nomogram was constructed to predict the overall survival of COVID-19 patients. Additionally, the scRNA-seq data of BALF and PBMCs from COVID-19 patients were downloaded to investigate the underlying mechanism of the most important prognostic indicators in lungs and peripherals, respectively. Results In total, 304 hospitalized adult COVID-19 patients in Wuhan Jinyintan Hospital were included in the retrospective study. CEA was the only laboratory indicator with significant difference in the univariate (P Conclusion This study identifies the prognostic roles of CEA in COVID-19 patients and implies the potential roles of CEACAM8-CEACAM6 in the progression of COVID-19 by regulating the cell–cell communication of developing neutrophils and type II pneumocyte. more...

Uterine carcinosarcoma (UCS) is a malignant tumor with a high tendency to invasion and metastasis. However, the underlying invasion and metastasis mechanisms of UCS remain poorly understood. Genetic alteration and tumor-infiltrating immune cells play important roles in tumorigenesis, progression, and metastasis. To better understand the underlying mechanisms of UCS, we screened tumor-infiltrating immune cells by applying CIBERSORT algorithm and constructed nomograms to predict the prognosis of UCS patients based on metastasis-specific tumor-infiltrating immune cells and genes, and demonstrated their utility by the high AUC values. Combining gene co-expression and experimental validation results, we propose a potential mechanism of AK8, MPZ, and mast cells activated might play important parts in UCS metastasis. more...

BackgroundBone is the most common metastatic site of Breast invasive carcinoma (BRCA). In this study, the bone metastasis-specific regulation network of BRCA was constructed based on prognostic stemness-related signatures (PSRSs), their upstream transcription factors (TFs) and downstream pathways.MethodsClinical information and RNA-seq data of 1,080 primary BRCA samples (1,048 samples without bone metastasis and 32 samples with bone metastasis) were downloaded from The Cancer Genome Atlas (TCGA). The edgeR method was performed to identify differential expressed genes (DEGs). Next, mRNA stemness index (mRNAsi) was calculated by one-class logistic regression (OCLR). To analyze DEGs by classification, similar genes were integrated into the same module by weighted gene co-expression network analysis (WGCNA). Then, univariate and multivariate Cox proportional hazard regression were applied to find the PSRSs. Furthermore, PSRSs, 318 TFs obtained from Cistrome database and 50 hallmark pathways quantified by GSVA were integrated into co-expression analysis. Significant co-expression patterns were used to construct the bone metastasis-specific regulation network. Finally, spatial single-cell RNA-seq and chromatin immunoprecipitation sequence (ChIP-seq) data and multi-omics databases were applied to validate the key scientific hypothesis in the regulation network. Additionally, Connectivity Map (CMap) was utilized to select the potential inhibitors of bone metastasis-specific regulation network in BRCA.ResultsBased on edgeR and WGCNA method, 43 PSRSs were identified. In the bone metastasis-specific regulation network, MAF positively regulated CD248 (R = 0.435, P < 0.001), and hallmark apical junction was the potential pathway of CD248 (R = 0.353, P < 0.001). This regulatory pattern was supported by spatial single-cell RNA sequence, ChIP-seq data and multi-omics online databases. Additionally, alexidine was identified as the possible inhibitor for bone metastasis of BRCA by CMap analysis.ConclusionPSRSs played important roles in bone metastasis of BRCA, and the prognostic model based on PSRSs showed good performance. Especially, we proposed that CD248 was the most significant PSRS, which was positively regulated by MAF, influenced bone metastasis via apical junction pathway. And this axis might be inhibited by alexidine, which providing a potential treatment strategy for bone metastasis of BRCA. more...

Background: Breast cancer (BRCA) ranks among the top most common female malignancies and was regarded as incurable when combined with bone and distant metastasis. Alternative splicing events (ASEs) together with splicing factors (SFs) were considered responsible for the development and progression of tumors. Methods: Datasets including RNA sequencing and ASEs of BRCA samples were achieved from TCGA and TCGASpliceSeq databases. Then, a survival model was built including 15 overall-survival-associated splicing events (OS-SEs) by Cox regression and Lasso regression. The co-expressed SFs of each bone-and-distant-metastasis-related OS-SE were discovered by Pearson correlation analysis. Additionaly, Gene Set Variation Analysis (GSVA) was performed to identify the downstream mechanisms of the key OS-SEs. Finally, the results were validated in different online platforms. Results: A reliable survival model was established (the area under ROC = 0.856) and CIRBP was found co-expressed with FAM110B ( R = 0.320 , P < 0.001 ) associated with the fatty acid metabolism pathway. Conclusions: Aberrant SF, CIRBP, regulated a specific ASE, exon skip (ES) of FAM110B, during which the fatty acid metabolism pathway played an essential part in tumorigenesis and prognosis of BRCA. more...

BackgroundColon adenocarcinoma (COAD) is a malignant and lethal tumor in digestive system and distance metastasis lead to poor prognosis. The metastasis-specific ceRNAs (competitive endogenous RNAs) and tumor-infiltrating immune cells might associate with tumor prognosis and distance metastasis. Nonetheless, few studies have concentrated on ceRNAs and Immune cells in COAD.MethodsThe gene expression profile and clinical information of COAD were downloaded from TCGA and divided into two groups: primary tumors with or without distance metastasis. We applied comprehensive bioinformatics methods to analyze differential expression genes (DEGs) related to metastasis and establish the ceRNA networks. The Cox analysis and Lasso regression were utilized to screen the pivotal genes and prevent overfitting. Based on them, the prognosis prediction nomograms were established. The cell type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm was then applied to screen significant tumor immune-infiltrating cells associated with COAD metastasis and established another prognosis prediction model. Ultimately, co-expression analysis was applied to explore the relationship between key genes in ceRNA networks and significant immune cells. Multiple databases and preliminary clinical specimen validation were used to test the expressions of key biomarkers at the cellular and tissue levels.ResultsWe explored 1 significantly differentially expressed lncRNA, 1 significantly differentially expressed miRNA, 8 survival-related immune-infiltrating cells, 5 immune cells associated with distance metastasis. Besides, 3 pairs of important biomarkers associated with COAD metastasis were also identified: T cells follicular helper and hsa-miR-125b-5p (R = −0.200, P < 0.001), Macrophages M0 and hsa-miR-125b-5p (R = 0.170, P < 0.001) and Macrophages M0 and FAS (R = −0.370, P < 0.001). Multidimensional validation and preliminary clinical specimen validation also supported the results.ConclusionIn this research, we found some significant ceRNAs (FAS and hsa-miR-125b-5p) and tumor-infiltrating immune cells (T cells follicular helper and Macrophages M0) might related to distance metastasis and prognosis of COAD. The nomograms could assist scientific and medical researchers in clinical management. more...

As the most common neoplasm in digestive system, hepatocellular carcinoma (HCC) is one of the most important leading cause of cancer deaths worldwide. Its high-frequency metastasis and relapse rate lead to the poor survival of HCC patients. However, the mechanism of HCC metastasis is still unclear. Alternative splicing events (ASEs) have a great effect in cancer development, progression and metastasis. We downloaded RNA sequencing and seven types of ASEs data of HCC samples, in order to explore the mechanism of ASEs underlying tumorigenesis and metastasis of HCC. The data were taken from the The Cancer Genome Atlas (TCGA) and TCGASpliceSeq databases. Univariate Cox regression analysis was used to determine a total of 3197 overall survival-related ASEs (OS-SEs). And based on five OS-SEs screened by Lasso regression, we constructed a prediction model with the Area Under Curve of 0.765. With a good reliability of the model, the risk score was also proved to be an independent predictor. Among identified 390 candidate SFs, Y-box protein 3 (YBX3) was significantly correlated with OS and metastasis. Among 177 ASEs, ATP-binding cassette subfamily A member 6 (ABCA6)-43162-AT and PLIN5-46808-AT were identified both associated with OS, bone metastasis and co-expressed with SFs. Then we identified primary bile acid biosynthesis as survival-related (KEGG) pathway by Gene Set Variation Analysis (GSVA) and univariate regression analysis, which was correlated with ABCA6-43162-AT and PLIN5-46808-AT. Finally, we proposed that ABCA6-43162-AT and PLIN5-46808-AT may contribute to HCC poor prognosis and metastasis under the regulation of aberrant YBX3 through the pathway of primary bile acid biosynthesis. more...

Purpose: To construct and analyze tumor-infiltrating immune cell and ceRNA (competitive endogenous RNA) networks in metastatic adrenal cortical carcinoma (ACC). Methods: A ceRNA network was established to identify the ceRNAs involved in metastasis of ACC based on 92 samples from TCGA, including 18 cases of metastasis and 74 cases of non-metastatic primary tumors. And the algorithm “cell type identification by estimating relative subsets of RNA transcripts (CIBERSORT)” was used to quantify the proportion of immune cells in ACC. In addition, predictive nomograms based on the types of important immune cells or ceRNAs were constructed to predict ACC prognosis. Moreover, we evaluated the relationships between metastatic ACC-specific immune cells and ceRNA networks to identify the potential immune gene characteristics. Results: Ten prognostic biomarkers were identified as key members of the ceRNA network and three tumor-infiltrating immune cells were identified by CIBERSORT algorithm. Some important co-expression patterns between immune cells and ceRNAs network indicate significant correlation between Macrophages M0 and hsa-miR-130b-3p (P < 0.001), Macrophages M0 and H2AFX (P = 0.003). Conclusions: The present study inferred that the metastasis-related ceRNAs of H2AFX, hsa-miR-130b-3p and Macrophages M0 might play important roles in ACC metastasis. more...

Background Spinal cord injury (SCI) is one of the most devastating diseases with a high incidence rate around the world. SCI-related neuropathic pain (NeP) is a common complication, whereas its pathomechanism is still unclear. The purpose of this study is to identify key genes and cellular components for SCI-related NeP by an integrated transcriptome bioinformatics analysis. Methods The gene expression profile of 25 peripheral blood samples from chronic phase SCI patients (E-GEOD-69901) and 337 normal peripheral blood samples were downloaded from ArrayExpress and Genotype-Tissue Expression Portal (GTEx), respectively. A total of 3,368 normal peripheral blood mononuclear cells (PBMC) were download from Sequence Read Archive (SRA713577). Non-parametric tests were used to evaluate the association between all of differential expression genes (DEGs) and SCI-related NeP. CellPhoneDB algorithm was performed to identify the ligand-receptor interactions and their cellular localization among single PBMCs. Transcription factor (TF) enrichment analysis and Gene Set Variation Analysis (GSVA) were used to identify the potential upstream regulatory TFs and downstream signaling pathways, respectively. Co-expression analysis among significantly enriched TFs, key cellular communication genes and differentially expressed signaling pathways were performed to identify key genes and cellular components for SCI-related NeP. Results A total of 2,314 genes were identified as DEGs between the experimental and the control group. Five proteins (ADRB2, LGALS9, PECAM1, HAVCR2, LRP1) were identified in the overlap of proteins in the significant ligand-receptor interactions of PBMCs and protein-protein interaction (PPI) network based on the DEGs. Only HAVCR2 was significantly associated with NeP (P = 0.005). Besides, the co-expression analysis revealed that TF YY1 had significantly co-expression pattern with cellular communication receptor HAVCR2 (R = -0.54, P < 0.001) in NK cells while HAVCR2 was also co-expressed with mTOR signaling pathway (R = 0.57, P < 0.001). The results of RT-qPCR and external dataset validation supported the signaling axis with the most significant co-expression patterns. Conclusion In peripheral blood of chronic SCI, HAVCR2 might act as a key receptor on the surface of NK cells and interact with ligand LGALS9 secreted by CD14+ monocytes, inhibiting NK cells through mTOR signaling pathway and ultimately predicting the occurrence of SCI-related NeP. This hypothetical signaling axis may provide prognostic biomarkers and therapeutic targets for SCI-related NeP. more...

Purpose: The purpose of this study was to construct a multi-center cross-sectional study to predict self-regulated learning (SRL) levels of Chinese medical undergraduates. Methods: We selected medical undergraduates by random sampling from five universities in mainland China. The classical regression methods (Logistic regression and Lasso regression) and machine learning model were combined to identify the most significant predictors of SRL levels. Nomograms were built based on multivariable models. The accuracy, discrimination and generalization of our nomograms were evaluated by the receiver operating characteristic curves (ROC) and the calibration curves and a high quality external validation. Results: There were 2052 medical undergraduates from five universities in mainland China initially. The nomograms constructed based on the non-overfitting multivariable models were verified by internal validation (C-index: learning motivation: 0.736; learning strategy: 0.744) and external validation (C-index: learning motivation: 0.986; learning strategy: 1.000), showing decent prediction accuracy, discrimination and generalization. Conclusions: Comprehensive nomograms constructed in this study were useful and convenient tools to evaluate the SRL levels of undergraduate medical students in China. more...

BackgroundAlternative splicing (AS) modifies 92-94% human genes, abnormal splicing events might relate to tumor development and invasion. Glioblastoma Multiforme (GBM) is a fatal, invasive, and malignant tumor in nervous system. The recurrence and development leads to poor prognosis. However, few studies have focused on AS in GBM.MethodsRNA-seq and Alternative splicing events (ASEs) data of GBM samples were downloaded from The Cancer Genome Atlas (TCGA) and TCGASpliceSeq databases, respectively. Firstly, the Cox regression analysis was utilized to identify the overall survival splicing events (OS-SEs). Secondly, a multivariable model was applied to access the prognostic value of risk score. Then, we constructed a co-expressed network between splicing factors (SFs) and overall survival alternative splicing events (OS-SEs). Additionally, to explore the relationship between the potential prognostic signaling pathways and OS-SEs, we constructed a network between these pathways and OS-SEs. Ultimately, to better explain the results, validations from multi-dimension platforms were applied.ResultsIn the first step, 1,062 OS-SEs were selected by Cox regression. Then, 11 OS-SEs were integrated in a multivariate model by Lasso regression. The area under the curve (AUC) of receiver operator characteristic (ROC) curve was 0.861. In addition, the risk score generated from the multivariate model was confirmed to be an independent prognostic factor (P < 0.001). What's more, in the network of SFs and ASEs, CELF5 significantly regulated GSG1L|35696|AP and GSG1L|35698|AP (P < 0.001, R = 0.511 and = -0.492). Additionally, GSG1L|35696|AP (P = 0.006) and GSG1L|35698|AP (P = 0.007) showed a significant relationship with cancer status. Eventually, KEGG pathways related to prognosis of GBM were selected by GSVA. The primary bile acid synthesis (P < 0.001, R = 0.420) was the significant pathway co-expressed with Germ Cell-Specific Gene 1-Like Protein (GSG1L).ConclusionsBased on the comprehensive bioinformatics analysis, we proposed that aberrant splicing factor CUGBP Elav-like family member 5 (CELF5) significantly, positively and negatively, regulated ASE of GSG1L, and the primary bile acid synthesis pathway might play an important role in tumorigenesis and prognosis of GBM. more...

Background: Kidney renal clear cell carcinoma (KIRC) is the malignancy originated from the renal epithelium, with a high rate of distant metastasis. Aberrant alternative splicing (AS) of pre-mRNA are widely reported to be involved in the tumorigenesis and metastasis of multiple cancers. The aim of this study is to explore the mechanism of alternative splicing events (ASEs) underlying tumorigenesis and metastasis of KIRC. Methods: RNA-seq of 537 KIRC samples downloaded from the TCGA database and ASEs data from the TCGASpliceSeq database were used to identify ASEs in patients with KIRC. The univariate and Lasso regression analysis were used to screen the most significant overall survival-related ASEs (OS-SEs). Based on those, the OS-SEs model was proposed. The interaction network of OS-SEs and splicing factors (SFs) with absolute value of correlation coefficient value >0.750 was constructed by Pearson correlation analysis. The OS-SEs significantly related to distant metastasis and clinical stage were identified by non-parametric test, and those were also integrated into co-expression analysis with prognosis-related Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways identified by Gene Set Variation Analysis (GSVA). ASEs with significance were selected for multiple online database validation. Results: A total of prognostic 6,081 overall survival-related ASEs (OS-SEs) were identified by univariate Cox regression analysis and a prediction model was constructed based on 5 OS-SEs screened by Lasso regression with the Area Under Curve of 0.788. Its risk score was also illustrated to be an independent predictor, which the good reliability of the model. Among 390 identified candidate SFs, DExD-Box Helicase 39B (DDX39B) was significantly correlated with OS and metastasis. After external database validation, Retained Intron of Ras Homolog Family Member T2 (RHOT2) and T-Cell Immune Regulator 1 (TCIRG1) were identified. In the co-expression analysis, overlapped co-expression signal pathways for RHOT2 and TCIRG1 were sphingolipid metabolism and N-glycan biosynthesis. Conclusions: Based on the results of comprehensive bioinformatic analysis, we proposed that aberrant DDX39B regulated RHOT2-32938-RI and TCIRG1-17288-RI might be associated with the tumorigenesis, metastasis, and poor prognosis of KIRC via sphingolipid metabolism or N-glycan biosynthesis pathway. more...

Background/Aims: As a malignant and melanocytic tumor, cutaneous melanoma is the devastating skin tumor with high rates of recurrence and metastasis. Bone is the common metastatic location, and bone metastasis may result in pathologic fracture, neurologic damage, and severe bone pain. Although metastatic melanoma was reported to get benefits from immunotherapy, molecular mechanisms and immune microenviroment underlying the melanoma bone metastasis and prognostic factors are still unknown.Methods: Gene expression profiling of 112 samples, including 104 primary melanomas and 8 bone metastatic melanomas from The Cancer Genome Atlas database, was assayed to construct a ceRNA network associated with bone metastases. Besides, we detected the fraction of 22 immune cell types in melanoma via the algorithm of “cell type identification by estimating relative subsets of RNA transcripts (CIBERSORT).” Based on the significant ceRNAs or immune cells, we constructed nomograms to predict the prognosis of patients with melanoma. Ultimately, correlation analysis was implemented to discover the relationship between the significant ceRNA and immune cells to reveal the potential signaling pathways.Results: We constructed a ceRNA network based on the interaction among 8 pairs of long noncoding RNA–microRNA and 15 pairs of microRNA–mRNA. CIBERSORT and ceRNA integration analysis discovered that AL118506.1 has both significant prognostic value (P = 0.002) and high correlation with T follicular helper cells (P = 0.033). Meanwhile, T cells CD8 and macrophages M2 were negatively correlated (P < 0.001). Moreover, we constructed two satisfactory nomograms (area under curve of 3-year survival: 0.899; 5-year survival: 0.885; and concordance index: 0.780) with significant ceRNAs or immune cells, to predict the prognosis of patients.Conclusions: In this study, we suggest that bone metastasis in melanoma might be related to AL118506.1 and its role in regulating thrombospondin 2 and T follicular helper cells. Two nomograms were constructed to predict the prognosis of patients with melanoma and demonstrated their value in improving the personalized management. more...

BACKGROUND Malignant giant cell tumor of bone (MGCTB) is a rare histological type of malignant tumor that has a high tendency for local relapse and distant metastasis and ultimately leads to a poor prognosis. The purpose of this study was to describe the epidemiological features, identify the prognostic factors, and construct nomograms for patients with MGCTB. MATERIAL AND METHODS Patients with MGCTB that was histologically diagnosed between 1973 and 2014 were selected from the Surveillance, Epidemiology, and End Results (SEER) database as a training set. Survival analysis, Lasso regression, and random forests were used to identify the prognostic variables and establish the nomograms for patients with MGCTB, while an external cohort of 37 patients from our own institution and an external cohort of 163 patients from the SEER database in 2016 were used to validate the generalization performance of the nomograms. RESULTS In total, univariate and multivariable analysis indicated that age, International Classification of Diseases for Oncology, historical stage, primary site, surgery information, radiotherapy, and chemotherapy were independent prognostic variables for overall survival or cause-specific survival. Nomograms based on the multivariable models were built to predict survival, and we achieved a higher C-index in subsequent multidimensional validation. CONCLUSIONS Age, historical stage, and chemotherapy were independent prognostic variables for overall survival and cause-specific survival of MGCTB patients, and radiotherapy and primary site were independent prognostic variables for overall survival. Nomograms based on significant clinicopathological features and clinical experience can be effective in predicting the probability of survival for MGCTB patients. more...

Malignant peripheral nerve sheath tumor (MPNST) is extremely rare in soft tissue sarcoma, with a high rate of recurrence and metastasis. Due to its rarity, the epidemiological features and prognostic factors are still uncertain. Moreover, nomograms for patients with MPNST have not been constructed and validated until now. Patients diagnosed with MPNST between 1973 and 2014 were selected from the Surveillance, Epidemiology, and End Results (SEER) database. Survival analysis, machine learning and Lasso regression were used to identify the prognostic factors for overall survival (OS) and cause-specific survival (CSS). Significant prognostic factors were integrated to construct nomograms and then the nomograms were validated externally with a separate cohort from our own institution. A total of 689 patients were included in the training set and 42 patients in the validation set. Multivariate analysis suggested that age, histology, historic stage and chemotherapy were independent prognostic factors for OS and primary site, surgery, historic stage and chemotherapy for CSS. The nomograms based on multivariate models were developed and validated for predicting 3- and 5-year OS and CSS, with a C-index of 0.686 and 0.707, respectively. In the external validation set, the C-index was 0.700 for OS and 0.722 for CSS. ICD-O-3 histology, historic stage and chemotherapy were independent prognostic factors for OS and primary site, surgery, historic stage and chemotherapy for CSS. The constructed nomograms could provide individual prediction for MPNST patients and assist oncologists in making accurate survival evaluation. more...

Objectives: Chordoma is a rare bone malignancy that affects the spine and skull base. Treatment dilemma leads to a high rate of local relapse and distant metastases. Molecular targeted therapy (MTT) is an option for advanced chordoma, but its therapeutic efficacy and safety have not been investigated systematically. Therefore, a systematic review was conducted on studies reporting MTT regimens for chordoma. Methods: Clinical trials, case series and case reports on chordoma MTT were identified using MEDLINE, Cochrane library and EMBASE, and systematically reviewed. Data on clinical outcomes, such as median overall survival, progression-free survival, response rate and adverse events (AEs) were extracted and analyzed. Results: Thirty-three eligible studies were selected for the systematic review, which indicated that imatinib and erlotinib were the most frequently used molecular targeted inhibitors (MTIs) for chordoma. For PDGFR-positive and/or EGFR-positive chordoma, clinical benefits were achieved with acceptable AEs. Monotherapy is preferred as the first-line of treatment, and combined drug therapy as the second-line treatment. In addition, the brachyury vaccine has shown promising results. Conclusions: The selection of MTIs for patients with advanced or relapsed chordoma should be based on gene mutation screening and immunohistochemistry (IHC). Monotherapy of TKIs is recommended as the first-line management, and combination therapy (two TKIs or TKI plus mTOR inhibitor) may be the choice for drug-resistant chordoma. Brachyury vaccine is a promising therapeutic strategy and requires more clinical trials to evaluate its safety and efficacy. more...

Background: Mesothelioma is a rare and aggressive tumor. Bone metastasis often occurs in the later stages of this disease along with poor quality of life. Thus, it is important to explore the tumorigenesis and bone metastasis mechanism of invasive mesothelioma. For this purpose, we established two nomograms based on tumor-infiltrating immune cells and ceRNA networks to describe the molecular immunity and the clinical prediction of mesothelioma patients with bone metastasis. Method: The expression profiles of mRNAs, lncRNAs, and miRNAs of 87 primary mesotheliomas were obtained from the TCGA database; there were four patients with bone metastasis and 83 patients without. We constructed a ceRNAs network based on the differentially expressed RNAs between mesothelioma and bone metastasis. CIBERSORT was used to distinguish 22 immune cell types from the tumor transcriptomes. Kaplan–Meier survival analysis and the Cox proportional hazards model were used to evaluate the prognostic value of each factor. Prognosis-associated immune cells and ceRNAs were applied to establish prediction nomograms. The receiver operating characteristic curves (ROC) and calibration curves were utilized to assess the discrimination and accuracy of the nomogram. Results: Differential analysis revealed that 20 lncRNAs, 15 miRNAs, and 230 mRNAs were significantly different in mesothelioma samples vs. bone metastasis samples. We constructed the ceRNA network to include 10 protein-coding mRNAs, 8 lncRNAs, and 10 miRNAs. Nine of 28 ceRNAs were found to be significant in the Kaplan–Meier analysis. Out of the 22 cell types, the fraction of dendritic cells resting (P = 0.018) was significantly different between the bone metastasis group and the non-bone metastasis group. The ROC and the calibration curves, based on ceRNA networks and tumor-infiltrating immune cells, respectively, suggested acceptable accuracy (AUC of 3-year survival: 0.827, AUC of 5-year survival: 0.840; AUC of 3-year survival: 0.730; AUC of 5-year survival: 0.753). Notably, based on the co-expression patterns between ceRNAs and Immune cells, we found that the hsa-miR-582-5p, CASP9, dendritic cells resting, ANIX2, T cells CD8, and T cells CD4 memory resting might be associated with the mesothelioma bone metastasis. Conclusion: Based on ceRNA networks and patterns of immune infiltration, our study provided a valid bioinformatics basis in order to explore the molecular mechanism and predict the possibility of mesothelioma bone metastasis. more...