CEMIP as a prognostic biomarker for cancers: a meta- and bioinformatic analysis

OBJECTIVE

Cell migration-inducing and hyaluronan-binding protein (CEMIP) is overexpressed in several cancers and is related to prognosis in cancer patients. Here, we conducted a meta-analysis to explore the prognostic effects of CEMIP in cancer patients.

METHODS

Relevant published studies were systematically searched in four databases. The role of CEMIP was evaluated using pooled hazard ratios (HRs), odd ratios (ORs), and 95% confidence intervals (95% CIs). The Cancer Genome Atlas (TCGA) was used to investigate the prognostic value of CEMIP in various cancers.

RESULTS

11 literatures with 1355 patients were included in this meta-analysis. The results showed that overexpression of CEMIP was significantly associated with poor OS (HR = 3.03; 95% CI: 2.00-4.59; p < 0.001), DFS (HR = 3.38; 95% CI: 2.41-4.74; p < 0.001). Elevated CEMIP expression is associated with advanced clinical stage, lymph node metastasis, and poor histological grade. In addition, TCGA datasets were used to verify that CEMIP was found highly expressed in multiple cancers and was associated with poorer survival.

CONCLUSION

The results demonstrated that CEMIP could be a novel prognostic biomarker for cancer patients. However, because the included studies mainly focused on Asian populations, further research is needed to verify its applicability.

Prognostic significance of long non-coding RNA five prime to XIST in various cancers

BACKGROUND

To observe the clinicopathological and prognostic value of long non-coding RNA five prime to X inactive specific transcript (lncFTX) in multiple tumors.

METHODS

Eligible studies for lncFTX were identified by searching PubMed, Embase, Web of Science and Cochrane Library databases from inception to December 01, 2020. Stata 12.0 software was used to calculate the odds ratio (OR)/hazard ratio (HR) and 95% confidence interval (95% CI). We used The Cancer Genome Atlas (TCGA) dataset to further investigate the differential expression and prognostic value of lncFTX.

RESULTS

We included 11 studies involving a total of 1633 patients. The results showed that the expression of lncFTX was positively associated with advanced TNM stage (III-IV versus I-II) (OR = 2.30, 95% CI: 1.74-3.03, P < 0.05), lymph nodes metastasis (OR = 3.01, 95% CI: 2.00-4.52, P < 0.05), distant metastasis (OR = 3.68, 95% CI: 2.13-6.34, P < 0.05), and cancer mortality (HR = 1.83, 95% CI: 1.20-2.81, P < 0.05). However, the expression of lncFTX was not associated with tumor differentiation (poor differentiation versus well or moderate differentiation) and vessel invasion of cancer. Subgroup analysis showed that the higher lncFTX expression was associated with shorter overall survival in cancer patients, regardless of the sample size and cancer type. No publication bias was found, and the sensitivity analysis results suggested that the main findings were robust. Elevated expression and prognostic significance of FTX were confirmed using TCGA dataset.

CONCLUSIONS

This study found that the expression of lncFTX was positively associated with advanced tumor node metastasis (TNM) stage, lymph nodes, distant metastasis and, cancer mortality, suggesting that lncFTX might be a potential prognostic biomarker for tumors.

Establishment and validation of immune microenvironmental gene signatures for predicting prognosis in patients with head and neck squamous cell carcinoma

Tumor cells influencing the microenvironment are essential for restrained immunity in head and neck squamous cell carcinoma (HNSCC). There has been considerable progress in the research on monoclonal antibodies for antigen-specific immunotherapy that overcome immunosuppressive checkpoint receptor/ligand signaling in patients with HNSCC. However, alteration of immunogenicity and formation of neoantigens that lead to dysregulation and immunosuppression in the HNSCC microenvironment is not well-defined. The aim of this study was to quantify the Immune, Stromal, and ESTIMATE scores based on the gene matrix of patients with HNSCC reported in The Cancer Genome Atlas (TCGA). We examined the association of the Immune, Stromal, and ESTIMATE scores with the pathologic characteristics of patients with HNSCC, using weighted gene co-expression network (WGCNA) and protein-protein interaction (PPI) analyses, and selected 17 hub gene signatures from the key gene module that was mostly correlated to immunocyte infiltration. Gene functional enrichment showed that this key gene module was closely related to the regulation of immune cell activation and its relevant pathways. In the prognostic analysis, high expression of CD3E, SASH3, CD2, SIRPG, UBASH3A, IKZF1, SPN, IL10RA, SLA, and CD3G was significantly associated with a good prognosis. Consequently, these prognosis-related genes were validated via analysis of mRNA expression in tumor-infiltrating lymphocytes (TILs) and matched peripheral blood lymphocytes (PBLs) in ten patients with HNSCC, and the expression of these genes was significantly higher in TILs compared to that in PBLs. These findings provide a novel understanding of the tumor immune targets for improved therapeutic regimes in patients with HNSCC.

The relationship between the expression of Ki-67 and the prognosis of osteosarcoma

Background

A number of studies have linked positive Ki-67 expression with the prognosis of osteosarcoma (OS) patients. However, the results have been conflicting. To address this controversy, we conducted an analysis using a meta-analysis and a TCGA dataset to estimate the value of Ki-67 expression in the prognosis of OS.

Methods

A comprehensive search for relevant papers was conducted using NCBI PubMed, Embase, Springer, ISI Web of Knowledge, the Cochrane Library, and CNKI regardless of the publication year. The associations between Ki-67 expression and the clinical features and main prognostic outcomes of OS were measured. The TCGA dataset was also analyzed. The pooled odds ratio (OR) and its 95% confidential intervals (CIs) were utilized for statistical analysis.

Results

Overall, a total of 12 studies with 500 cases were included, and the results indicated that the expression of Ki-67 was significantly associated with Enneking stage (OR = 6.88, 95% CI: 2.92–16.22, p < 0.05), distant metastasis (OR = 3.04, 95% CI: 1.51–6.12, p < 0.05) and overall survival (OR = 8.82, 95% CI: 4.68–16.65, p < 0.05) in OS patients. Additionally, we observed no significant heterogeneity among all retrieved studies. Associations between Ki-67 expression and overall survival and disease-free survival of sarcoma were confirmed using the TCGA and Kaplan-Meier plotter datasets.

Conclusion

The present study strongly suggests that positive Ki-67 expression was associated with Enneking stage, distant metastasis, and overall survival of OS, and it may be used as a potential biomarker to predict prognosis and guide clinical therapy for OS.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-07880-y.

High expression of the TEFM gene predicts poor prognosis in hepatocellular carcinoma

BACKGROUND

Mitochondrial transcription elongation factor (TEFM) is an essential molecule that regulates the replication-transcription switch of mitochondrial DNA. TEFM modulates both transcription elongation and RNA processing in mitochondria. The purpose of the present study was to determine the association of TEFM with tumor progression and prognosis in hepatocellular carcinoma (HCC) patients.

METHODS

The different protein expression level of TEFM among HCC cell lines was detected by Western blotting. The gene expression profiling interactive analysis (GEPIA) was used to dynamically analyze the mRNA expression of TEFM gene in different stages of HCC. The protein and mRNA expression levels of TEFM were detected by immunohistochemistry, Western blotting and qRT-PCR. The mRNA-SeqV2 expression of TEFM and clinical information of HCC patients were downloaded from the TCGA database by using R3.6.3 software. Next, the relationships between the expression level of TEFM and clinicopathological characteristics and the prognostic value of TEFM were analyzed. A Cox regression model was used for multivariate analysis of the factors that affected the prognosis of HCC. Finally, the association between the expression levels of TEFM and other mitochondrial regulatory genes and HCC biomarker genes was analyzed by GEPIA.

RESULTS

TEFM is upregulated in HCC cell lines compared to noncancerous liver cell line. TEFM protein and mRNA expression levels in HCC tissues were significantly upregulated compared with those in noncancerous liver tissues. In addition, the mRNA expression level of TEFM was significantly correlated with sex, serum AFP level, and vascular invasion (P<0.05). Further analysis showed that high expression level of TEFM was unfavorable in terms of the prognosis of patients with HCC. Cox multivariate regression analysis showed that patient age, vascular invasion, and TEFM expression were independent factors affecting the prognosis of HCC patients (P<0.05). The expression level of the TEFM gene was significantly positively correlated with the expression of multiple mitochondrial regulatory genes and biomarker genes of HCC (P<0.01, R>0).

CONCLUSIONS

Our findings reveal that TEFM may play an important role in the progression of HCC. More importantly, the elevated expression of TEFM may potentially predict poor overall survival (OS) and disease-free survival (DFS) in patients with HCC.

Potential dual functional roles of the Y-linked RBMY in hepatocarcinogenesis

Hepatocellular carcinoma (HCC) is a highly heterogeneous liver cancer with significant male biases in incidence, disease progression, and outcomes. Previous studies have suggested that genes on the Y chromosome could be expressed and exert various male‐specific functions in the oncogenic processes. In particular, the RNA‐binding motif on the Y chromosome (RBMY) gene is frequently activated in HCC and postulated to promote hepatic oncogenesis in patients and animal models. In the present study, immunohistochemical analyses of HCC specimens and data mining of The Cancer Genome Atlas (TCGA) database revealed that high‐level RBMY expression is associated with poor prognosis and survival of the patients, suggesting that RBMY could possess oncogenic properties in HCC. To examine the immediate effect(s) of the RBMY overexpression in liver cancer cells, cell proliferation was analyzed on HuH‐7 and HepG2 cells. The results unexpectedly showed that RBMY overexpression inhibited cell proliferation in both cell lines as its immediate effect, which led to vast cell death in HuH‐7 cells. Transcriptome analysis showed that genes involved in various cell proliferative pathways, such as the RAS/RAF/MAP and PIP3/AKT signaling pathways, were downregulated by RBMY overexpression in HuH‐7 cells. Furthermore, in vivo analyses in a mouse liver cancer model using hydrodynamic tail vein injection of constitutively active AKT and RAS oncogenes showed that RBMY abolished HCC development. These findings support the notion that Y‐linked RBMY could serve dual tumor‐suppressing and tumor‐promoting functions, depending on the spatiotemporal and magnitude of its expression during oncogenic processes, thereby contributing to sexual dimorphisms in liver cancer.

Low microRNA-139 expression associates with poor prognosis in patients with tumors: A meta-analysis

BACKGROUND

microRNA-139 (miR-139) is dysregulated in various types of tumors and plays a key role in carcinogenesis. miR-139 may be used as a diagnostic and prognostic biomarker of cancers. However, the data from the literature are not consistent. The present study aimed to verify the prognostic and diagnostic values of miR-139 in solid tumors.

DATA SOURCES

PubMed, Web of Science and Embase databases were searched and publications from January 2011 to August 2017 were included. We used Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) database to further validate this meta-analysis.

RESULTS

Eight individual studies from seven articles were included. Pooled analyses showed that low miR-139 expression was related to worse overall survival (OS) [hazard ratio (HR) = 2.27; 95% confidence intervals (CI): 1.74-2.95; P < 0.001] in solid tumors, including hepatocellular carcinoma (HCC) and glioblastoma multiforme (GBM), consisting with the results of TCGA. However, our results of CRC showed that low miR-139 expression was associated with poor OS which was contradictory with the results in TCGA database and need larger samples to validate the phenomenon; whereas for CRC patients, high miR-139 expression predicted poor RFS, which was in good accordance with TCGA results. The results of 27 microarrays from GEO database showed that miR-139 expression levels were lower in tumor tissues compared to adjacent non-tumor tissues or healthy tissues. Decreased miR-139 expression was also significantly correlated with poor differentiation grade (OR = 3.57; 95% CI: 1.44-8.85; P = 0.006). However, the combined data indicated that no associations between miR-139 expression and the following parameters such as age (pooled OR = 1.50; 95% CI: 0.69-3.24; P = 0.304), gender (pooled OR = 0.92; 95% CI: 0.56-1.51; P = 0.738), tumor size (pooled OR = 1.51; 95% CI: 0.69-3.31; P = 0.298), late tumor-node-metastasis stage (pooled OR = 1.63; 95% CI: 0.99-2.68; P = 0.057) and lymph-node-metastasis (pooled OR = 0.66; 95% CI: 0.34-1.28; P = 0.222).

CONCLUSIONS

Low miR-139 expression was related to poor prognosis in HCC and GBM, which could be regarded as a potential prognostic biomarker. However, its precise functional role in CRC still need to be further investigated through larger samples and multicenter studies.

A high expression of MTERF3 correlates with tumor progression and predicts poor outcomes in patients with brain glioma

Mitochondrial transcription termination factor 3 (MTERF3) is a negative regulator of mitochondrial transcription. MTERF3 is overexpressed in liver cancer, pancreatic cancer, lung cancer, and breast cancer. However, whether MTERF3 is up-regulated in brain glioma is still unclear. The aim of this study was to investigate the expression and clinicopathological significance of MTERF3 in brain glioma and to analyze its potential prognostic value in brain glioma. Immunohistochemistry, Western blot, and a semi-quantitative RT-PCR were performed to analyze the protein and mRNA expression levels of MTERF3 in 28 human brain glioma tissues and 10 noncancerous brain tissues. The expression data of MTERF3 and its clinical information in brain glioma were downloaded from the TCGA dataset using R 2.15.3 software. The relationship between the expression of MTERF3 and its clinicopathological characteristics and its prognostic value was analyzed. A Cox regression model was used for a multivariate analysis of the factors affecting the prognosis of brain glioma. The immunohistochemistry results showed that the MTERF3 protein is located in the cytoplasm, and the positive expression rate of the MTERF3 protein in brain glioma tissues is 64.29%. We found that the positive expression rate of the MTERF3 protein in high-grade glioma tissues (81.25%) is higher than it is in low-grade glioma tissues (41.67%). The expression levels of the MTERF3 mRNA and protein in brain glioma tissues are significantly higher than they are in the noncancerous brain tissues. Moreover, the expression of MTERF3 is significantly correlated with age, tumor type, and pathological classification (P<0.05). A Kaplan-Meier analysis showed that a high expression level of MTERF3 mRNA indicated a poor prognosis (log rank P<0.01). Furthermore, a multivariate Cox regression analysis showed that age and tumor type were independent prognostic factors for brain glioma patients. A GEPIA analysis suggested that the expression levels of MTERF3 are positively correlated with the TFAM, TFB1M, TFB2M, MTERF1, MTERF2, TEFM, and MFN1 genes, but negatively correlated with the PINK1 gene. The expression level of MTERF3 had no correlation with the MTERF4 gene. In conclusion, these data indicate that the expression of MTERF3 in glioma tissue samples can be used as a prognostic factor for patients with glioma and that a high MTERF3 expression correlates with a poor prognosis in glioma patients.

The Y-linked proto-oncogene TSPY contributes to poor prognosis of the male hepatocellular carcinoma patients by promoting the pro-oncogenic and suppressing the anti-oncogenic gene expression

Background

Liver cancer is one of the major causes of cancer death worldwide, with significantly higher incidence and mortality among the male patients. Although sex hormones and their receptors could contribute to such sex differences, the story is incomplete. Genes on the male-specific region of the Y chromosome could play a role(s) in this cancer. TSPY is the putative gene for the gonadoblastoma locus on the Y chromosome (GBY) that is ectopically expressed in a subset of male hepatocellular carcinomas (HCCs). Although various studies showed that TSPY expression is associated with poor prognosis in the patients and its overexpression promotes cell proliferation of various cancer cell lines, it remains unclear how TSPY contributes to the clinical outcomes of the HCC patients. Identifying the downstream genes and pathways of TSPY actions would provide novel insights on its contribution(s) to male predominance in this deadly cancer.

Results

To determine the effects of TSPY on HCC, a TSPY transgene was introduced to the HCC cell line, HuH-7, and studied with RNA-Seq transcriptome analysis. The results showed that TSPY upregulates various genes associated with cell-cycle and cell-viability, and suppresses cell-death related genes. To correlate the experimental observations with those of clinical specimens, transcriptomes of male HCCs with high TSPY expression were analyzed with reference to those with silent TSPY expression from the Cancer Genome Atlas (TCGA). The comparative analysis identified 49 genes, which showed parallel expression patterns between HuH-7 cells overexpressing TSPY and clinical specimens with high TSPY expression. Among these 49 genes, 16 likely downstream genes could be associated with survival rates in HCC patients. The major upregulated targets were cell-cycle related genes and growth factor receptor genes, including CDC25B and HMMR, whose expression levels are negatively correlated with the patient survival rates. In contrast, PPARGC1A, SLC25A25 and SOCS2 were downregulated with TSPY expression, and possess favorable prognoses for HCC patients.

Conclusion

We demonstrate that TSPY could exacerbate the oncogenesis of HCC by differentially upregulate the expression of pro-oncogenic genes and downregulate those of anti-oncogenic genes in male HCC patients, thereby contributing to the male predominance in this deadly cancer.

Electronic supplementary material

The online version of this article (10.1186/s13578-019-0287-x) contains supplementary material, which is available to authorized users.

Prognostic values of GMPS, PR, CD40, and p21 in ovarian cancer

Early detection and prediction of prognosis and treatment responses are all the keys in improving survival of ovarian cancer patients. This study profiled an ovarian cancer progression model to identify prognostic biomarkers for ovarian cancer patients. Mouse ovarian surface epithelial cells (MOSECs) can undergo spontaneous malignant transformation in vitro cell culture. These were used as a model of ovarian cancer progression for alterations in gene expression and signaling detected using the Illumina HiSeq2000 Next-Generation Sequencing platform and bioinformatical analyses. The differential expression of four selected genes was identified using the gene expression profiling interaction analysis (http://gepia.cancer-pku.cn/) and then associated with survival in ovarian cancer patients using the Cancer Genome Atlas dataset and the online Kaplan–Meier Plotter (http://www.kmplot.com) data. The data showed 263 aberrantly expressed genes, including 182 up-regulated and 81 down-regulated genes between the early and late stages of tumor progression in MOSECs. The bioinformatic data revealed four genes (i.e., guanosine 5′-monophosphate synthase (GMPS), progesterone receptor (PR), CD40, and p21 (cyclin-dependent kinase inhibitor 1A)) to play an important role in ovarian cancer progression. Furthermore, the Cancer Genome Atlas dataset validated the differential expression of these four genes, which were associated with prognosis in ovarian cancer patients. In conclusion, this study profiled differentially expressed genes using the ovarian cancer progression model and identified four (i.e., GMPS, PR, CD40, and p21) as prognostic markers for ovarian cancer patients. Future studies of prospective patients could further verify the clinical usefulness of this four-gene signature.

CDH1, DLEC1 and SFRP5 methylation panel as a prognostic marker for advanced epithelial ovarian cancer

AIM

To investigate the CDH1, DLEC1 and SFRP5 gene methylation panel for advanced epithelial ovarian carcinoma (EOC).

MATERIALS & METHODS

One hundred and seventy-seven advanced EOC specimens were evaluated by methylation-specific PCR. We also used The Cancer Genome Atlas dataset to evaluate the panel.

RESULTS

The presence of two or more methylated genes was significant in recurrence (hazard ratio [HR]: 1.91 [1.33-2.76]; p = 0.002) and death (HR: 1.96 [1.26-3.06]; p = 0.006) in our cohort. In The Cancer Genome Atlas dataset, the presence of two or three methylated genes was significant in death (HR: 1.59 [1.15-2.18]; p = 0.0047) and close to the significance level in recurrence (HR: 1.37 [0.99-1.88]; p = 0.058).

CONCLUSION

The CDH1, DLEC1 and SFRP5 methylation panel is a potential prognostic biomarker for advanced EOC.

Expression of programmed cell death protein 1 (PD-1) and indoleamine 2,3-dioxygenase (IDO) in the tumor microenvironment and in tumor-draining lymph nodes of breast cancer

Programmed cell death protein 1 (PD-1) and indoleamine 2,3-dioxygenase (IDO) are both immunosuppressive proteins. Here, we investigated the relationship between PD-1 and IDO in the tumor microenvironment (TME) and in tumor-draining lymph nodes (TDLNs) in breast cancer patients. First, the protein and mRNA expression levels of PD-1 and IDO in 20 frozen tissues were examined using Western blotting and real-time polymerase chain reaction. Second, 151 paraffin-embedded breast samples and 52 lymph node samples were analyzed by immunohistochemistry. Third, correlation and survival data for PD-1 and IDO in 963 breast tumor patients were mined using the cBio Cancer Genomics Portal. We found that the protein expression level of IDO was significantly increased in frozen tumor tissues (P = .005). From paraffin-embedded samples in the TME, PD-1⁺ cells were only located in the stroma, while IDO was expressed in myoepithelial, stromal, and tumor cells. PD-1 and stromal IDO in the TME showed increased expression in tumors (P< .001 and P < .001, respectively). In TDLNs, PD-1⁺ cells were primarily located in the germinal centers (GCs), and IDO⁺ cells were primarily located in the paracortex. Normal lymph nodes expressed PD-1 and IDO at the same level as non-metastatic and metastatic lymph nodes (P = .151 and P = .812, respectively). According to cBioPortal, the correlation analysis showed that IDO and PD-1 had high correlation coefficients (r = 0.83). These findings suggest that there is a positive correlation between the expression of PD-1 and IDO and that blocking both PD-1 and IDO pathways may represent an attractive therapeutic strategy in breast cancer treatment.

MicroRNA based Pan-Cancer Diagnosis and Treatment Recommendation

BACKGROUND

The current state-of-the-art in cancer diagnosis and treatment is not ideal; diagnostic tests are accurate but invasive, and treatments are "one-size fits-all" instead of being personalized. Recently, miRNA's have garnered significant attention as cancer biomarkers, owing to their ease of access (circulating miRNA in the blood) and stability. There have been many studies showing the effectiveness of miRNA data in diagnosing specific cancer types, but few studies explore the role of miRNA in predicting treatment outcome.

METHODS

Here we go a step further, using tissue miRNA and clinical data across 21 cancers from the 'The Cancer Genome Atlas' (TCGA) database. We use machine learning techniques to create an accurate pan-cancer diagnosis system, and a prediction model for treatment outcomes. Finally, using these models, we create a web-based tool that diagnoses cancer and recommends the best treatment options.

RESULTS

We achieved 97.2% accuracy for classification using a support vector machine classifier with radial basis. The accuracies improved to 99.9-100% when climbing up the embryonic tree and classifying cancers at different stages. We define the accuracy as the ratio of the total number of instances correctly classified to the total instances. The classifier also performed well, achieving greater than 80% sensitivity for many cancer types on independent validation datasets. Many miRNAs selected by our feature selection algorithm had strong previous associations to various cancers and tumor progression. Then, using miRNA, clinical and treatment data and encoding it in a machine-learning readable format, we built a prognosis predictor model to predict the outcome of treatment with 85% accuracy. We used this model to create a tool that recommends personalized treatment regimens. Both the diagnosis and prognosis model, incorporating semi-supervised learning techniques to improve their accuracies with repeated use, were uploaded online for easy access.

CONCLUSION

Our research is a step towards the final goal of diagnosing cancer and predicting treatment recommendations using non-invasive blood tests.

LPRP: A Gene-Gene Interaction Network Construction Algorithm and Its Application in Breast Cancer Data Analysis

The importance of the construction of gene-gene interaction (GGI) network to better understand breast cancer has previously been highlighted. In this study, we propose a novel GGI network construction method called linear and probabilistic relations prediction (LPRP) and used it for gaining system level insight into breast cancer mechanisms. We construct separate genome-wide GGI networks for tumor and normal breast samples, respectively, by applying LPRP on their gene expression datasets profiled by The Cancer Genome Atlas. According to our analysis, a large loss of gene interactions in the tumor GGI network was observed (7436; 88.7 % reduction), which also contained fewer functional genes (4757; 32 % reduction) than the normal network. Tumor GGI network was characterized by a bigger network diameter and a longer characteristic path length but a smaller clustering coefficient and much sparse network connections. In addition, many known cancer pathways, especially immune response pathways, are enriched by genes in the tumor GGI network. Furthermore, potential cancer genes are filtered in this study, which may act as drugs targeting genes. These findings will allow for a better understanding of breast cancer mechanisms.