Somatic gene mutation signatures predict cancer type and prognosis in multiple cancers with pan-cancer 1000 gene panel

A comparison analysis of the somatic mutations in early-onset gastric cancer and traditional gastric cancer

BACKGROUND

Early onset gastric cancer (EOGC) has been on the rise in recent years and differs slightly in pathology from traditional gastric cancer (TGC). Somatic mutations have an essential role in the development of gastric cancer. We aimed to investigate these two types of gastric cancers at the level of somatic mutations and to further understanding of gastric cancer development.

METHODS

Somatic mutation, copy number variation (CNV), and clinical information were obtained from TCGA and UCSC Xena. Samples were divided into EOGC (< 50 years old, N = 28) and TGC (≥ 50 years old, N = 395) groups based on age. R packages "maftools" and "sigminer" were used to identify mutation signatures, while CNV information was processed using GISTIC2.0.

RESULTS

CDH1(21 %, P = 0.030) and ARID1A (28 %, P = 0.014) were more common in EOGC and TGC, respectively. The mutation frequency of ARID1A increased with age, while the opposite was true for CDH1. Sex, Lauren classifications, tumor mutation burden levels, mutation status of TP53, MUC6, NIPBL, KRAS, and copy number variation of the WOOX can affect the activity of the mutant signature.

CONCLUSIONS

Early-onset gastric cancer and traditional gastric cancer have distinct somatic mutation signatures, each with its own relatively specific high-frequency mutated genes, and the gene's mutation frequency correlates with age. Several clinical factors and genetic status affect the activity of some mutational features in gastric cancer in both groups.

Melatonin suppresses Akt/mTOR/S6K activity, induces cell apoptosis, and synergistically inhibits cell growth with sunitinib in renal carcinoma cells via reversing Warburg effect

BACKGROUND

Metabolic alteration drives renal cell carcinoma (RCC) development, while the impact of melatonin (MLT), a neurohormone secreted during darkness, on RCC cell growth and underlying mechanisms remains unclear.

METHODS

We detected concentration of metabolites through metabolomic analyses using UPLC-MS/MS, and the oxygen consumption rate was determined using the Seahorse Extracellular Flux analyzer.

RESULTS

We observed that MLT effectively inhibited RCC cell growth both in vitro and in vivo. Additionally, MLT increased ROS levels, suppressed antioxidant enzyme activity, and induced apoptosis. Furthermore, MLT treatment upregulated key TCA cycle metabolites while reducing aerobic glycolysis products, leading to higher oxygen consumption rate, ATP production, and membrane potential. Moreover, MLT treatment suppressed phosphorylation of Akt, mTOR, and p70 S6 Kinase as well as the expression of HIF-1α/VEGFA in RCC cells; these effects were reversed by NAC (ROS inhibitors). Conversely, MLT synergistically inhibited cell growth with sunitinib and counteracted the Warburg effect induced by sunitinib in RCC cells.

CONCLUSIONS

In conclusion, our results indicate that MLT treatment reverses the Warburg effect and promotes intracellular ROS production, which leads to the suppression of Akt/mTOR/S6K signaling pathway, induction of cell apoptosis, and synergistically inhibition of cell growth with sunitinib in RCC cells. Overall, this study provides new insights into the mechanisms underlying anti-tumor effect of MLT in RCC cells, and suggests that MLT might be a promising therapeutic for RCC.

Bioinformatic analyzes and validation of cystathionine gamma-lyase as a prognostic biomarker and related to immune infiltrates in hepatocellular carcinoma

Background

The role of cystathionine γ-lyase (CTH) in the prognosis and immune invasion of hepatocellular carcinoma (HCC) remains poorly understood.

Methods

In this study, the clinical data of patients with HCC were analyzed, and the expression level of CTH was compared between HCC and normal tissues using the R package and various databases.

Results

We found that CTH expression was significantly decreased in HCC compared with normal tissues, and its expression was associated with various clinicopathological factors, including tumor stage, gender, tumor status, residual tumor, histologic stage, race, alpha-fetoprotein (AFP), albumin, drinking, and smoking. Our results suggest that CTH might be a protective factor for the survival of patients with HCC. Further functional analysis revealed that high CTH expression was enriched in the Reactome signaling by interleukins and the Reactome neutrophil degranulation. Moreover, CTH expression was closely correlated with a variety of immune cells, including a negative correlation with the CD56 (bright) NK cells and follicular helper T cell (TFH), while a positive correlation with Th17 cells and central memory T cell (Tcm). High expression of CTH in immune cells predicted a better prognosis of HCC. Our findings further indicated Pyridoxal phosphate, l-cysteine, Carboxymethylthio-3-(3-chlorophenyl)-1,2,4-oxadiazol, 2-[(3-Hydroxy-2-Methyl-5-Phosphonooxymethyl-Pyridin-4-Ylmethyl)-Imino]-5-phosphono-pent-3-enoic acid and L-2-amino-3-butynoic acid as potential target candidate medications for HCC treatment based on CTH.

Conclusion

Our study suggests that CTH can serve as a biomarker to predict the prognosis and immune infiltration of HCC.

Identification of Differentially Expressed Genes Related to the Lipid Metabolism of Esophageal Squamous Cell Carcinoma by Integrated Bioinformatics Analysis

Purpose: In recent years, lipid metabolism has been reprogrammed to meet the energy and substrate needs of tumorigenesis and development and is a potential new target for cancer treatment. However, the regulatory mechanism of lipid metabolism in esophageal squamous cell carcinoma is not well understood. Methods: We first downloaded the esophageal squamous cell carcinoma (ESCC) gene dataset in the GEO and TCGA databases and analyzed the central differentially expressed genes (DEGs) of ESCC through bioinformatics. Afterwards, the GSEA method was used to analyze the lipid metabolism-related pathway of the central gene in the pathological process of ESCC, and it was determined that the central gene OIP5 was significantly related to the fatty acid metabolism pathway. Our heatmap also revealed that the enrichment of the ACSL family in ESCC tissues was more pronounced than in normal tissues. We hypothesized that OIP5 can regulate the fatty acid metabolism process in ESCC cells and affect the tumorigenic ability of ESCC. Further statistical analysis and experiment were conducted to determine the lipid metabolism-related gene, OIP5′s, expression pattern and clinical significance in ESCC, analyze the effect of OIP5 expression on fatty acid metabolism-related enzymes in ESCC, revealing the specific mechanism of OIP5 that promotes ESCC development. Conclusions: Our study established a correlation between OIP5 expression and clinicopathological factors (tumor size, T stage, N stage, and clinical grade) in esophageal squamous cell carcinoma (p < 0.05). We have also experimentally demonstrated that OIP5 regulates ESCC fatty acid metabolism by influencing the expression of the key enzyme ACSL1 in lipid metabolism.

Identification of mutational signature for lung adenocarcinoma prognosis and immunotherapy prediction

There is no robust genomic signature to predict the prognosis of patients with early-stage lung adenocarcinoma (LUAD). It was known that clonal heterogeneity was closely associated to tumour progression and prognosis prediction. Herein, using stage I patients from The Cancer Genome Atlas, we identified the clonal/subclonal events of each gene and preselected a set of genes with prognosis-specific mutation patterns based on a robust published transcriptomic prognostic signature. Subsequently, we constructed a mutational prognostic signature (MPS), whose prognostic performance was independently validated in two datasets of stage I samples. The predicted high-risk patients had significantly higher immune cell infiltration, along with higher expression of cytotoxic and immune checkpoint genes, and an integrated dataset with 88 samples confirmed that high-risk patients could benefit from immunotherapy. The developed MPS can identify the high-risk patients with stage I LUAD and improve individualised treatment planning of high-risk patients who might benefit from immunotherapy. KEY MESSAGES: We creatively developed a prognostic signature (57-MPS) based on clonal diversity. The high-risk samples displayed an underlying immunosuppressive mechanism. 57-MPS improved the predictive performance of PD-L1 for immunotherapy.

Prognostic Significance of Cuproptosis-Related Gene Signatures in Breast Cancer Based on Transcriptomic Data Analysis

Breast cancer (BRCA) remains a serious threat to women's health, with the rapidly increasing morbidity and mortality being possibly due to a lack of a sophisticated classification system. To date, no reliable biomarker is available to predict prognosis. Cuproptosis has been recently identified as a new form of programmed cell death, characterized by the accumulation of copper in cells. However, little is known about the role of cuproptosis in breast cancer. In this study, a cuproptosis-related genes (CRGs) risk model was constructed, based on transcriptomic data with corresponding clinical information relating to breast cancer obtained from both the TCGA and GEO databases, to assess the prognosis of breast cancer by comprehensive bioinformatics analyses. The CRGs risk model was constructed and validated based on the expression of four genes (NLRP3, LIPT1, PDHA1 and DLST). BRCA patients were then divided into two subtypes according to the CRGs risk model. Furthermore, our analyses revealed that the application of this risk model was significantly associated with clinical outcome, immune infiltrates and tumor mutation burden (TMB) in breast cancer patients. Additionally, a new clinical nomogram model based on risk score was established and showed great performance in overall survival (OS) prediction, confirming the potential clinical significance of the CRGs risk model. Collectively, our findings revealed that the CRGs risk model can be a useful tool to stratify subtypes and that the cuproptosis-related signature plays an important role in predicting prognosis in BRCA patients.

Targeting Strategies for Aberrant Lipid Metabolism Reprogramming and the Immune Microenvironment in Esophageal Cancer: A Review

Esophageal cancer is of high importance to occurrence, development, and treatment resistance. As evidenced by recent studies, pathways (e.g., Wnt/β-catenin, AMPK, and Hippo) are critical to the proliferation, differentiation, and self-renewal of esophageal cancer. In addition, the above pathways play a certain role in regulating esophageal cancer and act as potential therapeutic targets. Over the past few years, the function of lipid metabolism in controlling tumor cells and immune cells has aroused extensive attention. It has been reported that there are intricate interactions between lipid metabolism reprogramming between immune and esophageal cancer cells, whereas molecular mechanisms should be studied in depth. Immune cells have been commonly recognized as a vital player in the esophageal cancer microenvironment, having complex crosstalk with cancer cells. It is increasingly evidenced that the function of immune cells in the tumor microenvironment (TME) is significantly correlated with abnormal lipid metabolism. In this review, the latest findings in lipid metabolism reprogramming in TME are summarized, and the above findings are linked to esophageal cancer progression. Aberrant lipid metabolism and associated signaling pathways are likely to serve as a novel strategy to treat esophageal cancer through lipid metabolism reprogramming.

Heat shock factor 2-binding protein promotes tumor progression via activation of MAPK signaling pathway in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is a malignant tumor that causes a serious public health burden. The biological functions and potential mechanism of heat shock factor 2-binding protein (HSF2BP) in LUAD have not been studied. This study aimed to explore the HSF2BP expression pattern and its potential biological function in LUAD. The transcriptome data and relevant clinical data of LUAD were downloaded from The Cancer Genome Atlas (TCGA) database. The mRNA levels and prognosis of HSF2BP were determined using TCGA datasets. The protein and mRNA expression levels of HSF2BP were identified by conducting western blot analysis and quantitative real-time polymerase chain reaction in tissues and cells, respectively. To determine whether HSF2BP affected the biological function of LUAD cell lines, a series of functional experiments were performed in vitro and in vivo. In addition, gene set enrichment analysis was applied to determine the pathways that HSF2BP regulated, which was further confirmed by western blotting, and the high expression of HSF2BP was observed in LUAD, which was correlated with the unfavorable prognosis in LUAD patients. Clinical correlation analysis revealed that tumor stage was positively correlated with high HSF2BP expression. Furthermore, HSF2BP could serve as an independent risk factor for overall survival. In vitro, HSF2BP knockdown suppressed the proliferation and migration of A549 and H1299 cells. We observed the same results in vivo experiments. Mechanistically, the HSF2BP regulates the mitogen-activated protein kinase signaling pathway to perform its biological function. The HSF2BP plays a role in the development of LUAD and could be a useful anticancer target for the treatment of LUAD.

Integration of Tumor Heterogeneity for Recurrence Prediction in Patients with Esophageal Squamous Cell Cancer

Simple Summary

This manuscript reports a deep sequencing study comprehensively analyzing the clinical impact of mutations considering the abundance of mutations. We built an eight-gene mutation predictor considering intratumoral heterogeneity to predict post-surgery recurrence in ESCC patients. Unlike previous studies that simply treated mutations as binary variables (mutant and wild type), we quantified mutations by the fraction of cancer cells carrying the mutations, and our results showed that the cancer cell fraction of mutations was more informative than the mutation status of genes in recurrence prediction. The predictor was further validated as a powerful recurrence indicator in our validation set and the TCGA-ESCC cohort. With the popularization of targeted deep sequencing in clinical work, our study will help clinicians make accurate predictions of recurrence for patients and will provide a new perspective in the clinical transformation of genomic findings.

Abstract

Esophageal squamous cell carcinoma (ESCC) is one of the deadliest malignancies in China. The prognostic value of mutations, especially those in minor tumor clones, has not been systematically investigated. We conducted targeted deep sequencing to analyze the mutation status and the cancer cell fraction (CCF) of mutations in 201 ESCC patients. Our analysis showed that the prognostic effect of mutations was relevant to the CCF, and it should be considered in prognosis prediction. EP300 was a promising biomarker for overall survival, impairing prognosis in a CCF dose-dependent manner. We constructed a CCF-based predictor using a smooth clipped absolute deviation Cox model in the training set of 143 patients. The 3-year disease-free survival rates were 6.3% (95% CI: 1.6–23.9%), 29.8% (20.9–42.6%) and 70.5% (56.6–87.7%) in high-, intermediate- and low-risk patients, respectively, in the training set. The prognostic accuracy was verified in a validation set of 58 patients and the TCGA-ESCC cohort. The eight-gene model predicted prognosis independent of clinicopathological factors and the combination of our model and pathological staging markedly improved the prognostic accuracy of pathological staging alone. Our study describes a novel recurrence predictor for ESCC patients and provides a new perspective for the clinical translation of genomic findings.

Elevated Stratifin promotes cisplatin-based chemotherapy failure and poor prognosis in non-small cell lung cancer

Drug resistance is a key factor in the treatment failure of clinical non-small cell lung cancer (NSCLC) patients after adjuvant chemotherapy. Here, our results provide the first evidence that eukaryotic translation initiation factor 2b subunit delta (EIF2B4)-Stratifin (SFN) fusion and increased SFN expression are associated with chemotherapy tolerance and activation of the phosphatidylinositol 3 kinase/v-akt murine thymoma viral oncogene (PI3K/Akt) signaling pathway in NSCLC patients, suggesting that SFN might have potential prognostic value as a tumor biomarker for the prognosis of patients with NSCLC.

Identification of a Genome Instability-Associated LncRNA Signature for Prognosis Prediction in Colon Cancer

Long non-coding RNAs (lncRNAs) were reported to have the potential in maintaining genome instability, but the identification of lncRNAs related to genome instability and their prognostic value have not been largely explored in colon cancer. In this study, we obtained 155 genome instability-associated lncRNAs based on somatic mutation profiles in colon cancer from The Cancer Genome Atlas (TCGA) database. Functional enrichment analysis revealed the possible roles of genes co-expressed with those lncRNAs involved in some cancer, genome instability and immune related biological processes. Combined with overall survival data, a seven-lncRNA signature was established for prognosis prediction. According to the risk score calculated by this signature, high-risk patients characterized by high somatic mutation count, high microsatellite instability, significantly poorer clinical outcomes and specific tumor immune infiltration status compared with low-risk patients. The lncRNA signature was validated to be an independent prognostic indicator with good predictive performance in TCGA cohort. Furthermore, the prognostic value of the ZNF503-AS1 in lncRNA signature was confirmed in another independent dataset from Gene Expression Omnibus database. In summary, the genome instability-associated lncRNA signature in this study could be a promising tool for effectively predicting survival outcomes in colon cancer.

Construction of a Myc-associated ceRNA network reveals a prognostic signature in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) remains an extremely lethal disease worldwide. High-throughput methods have revealed global transcriptome dysregulation; however, a comprehensive investigation of the complexity and behavioral characteristics of the competing endogenous RNA (ceRNA) network in HCC is lacking. In this study, we extracted the transcriptome (RNA) sequencing data of 371 HCC patients from The Cancer Genome Atlas platform. With the comparison of the high Myc expression (Myc^high) tumor and low Myc expression (Myc^low) tumor groups in HCC, we identified 1,125 differentially expressed (DE) mRNAs, 589 long non-coding RNAs (lncRNAs), and 93 microRNAs (miRNAs). DE RNAs predicted the interactions necessary to construct an associated Myc ceRNA network, including 19 DE lncRNAs, 5 miRNAs, and 72 mRNAs. We identified a significant signature (long intergenic non-protein-coding [LINC] RNA 2691 [LINC02691] and LINC02499) that effectively predicted overall survival and had protective effects. The target genes of microRNA (miR)-212-3p predicted to intersect with DE mRNAs included SEC14-like protein 2 (SEC14L2) and solute carrier family 6 member 1 (SLC6A1), which were strongly correlated with survival and prognosis. With the use of the lncRNA-miRNA-mRNA axis, we constructed a ceRNA network containing four lncRNAs (LINC02691, LINC02499, LINC01354, and NAV2 antisense RNA 4), one miRNA (miR-212-3p), and two mRNAs (SEC14L2 and SLC6A1). Overall, we successfully constructed a mutually regulated ceRNA network and identified potential precision-targeted therapies and prognostic biomarkers.

Characteristics of Pan-Cancer Patients With Ultrahigh Tumor Mutation Burden

Background

Tumor mutation burden has been proven to be a good predictor for the efficacy of immunotherapy, especially in patients with hypermutation. However, most research focused on the analysis of hypermutation in individual tumors, and there is a lack of integrated research on the hypermutation across different cancers. This study aimed to characterize hypermutated patients to distinguish between these patients and non-hypermutated patients.

Methods

A total of 5,980 tumor samples involving 23 types of solid tumors from the in-house database were included in the study. Based on the cutoff value of tumor mutation burden (TMB), all samples were divided into hypermutated or non-hypermutated groups. Microsatellite instability status, PD-L1 expression and other mutation-related indicators were analyzed.

Results

Among the 5,980 tumor samples, 1,164 were selected as samples with hypermutation. Compared with the non-hypermutated group, a significant increase in the mutation rates of DNA mismatch repair genes and polymerase genes was detected in the hypermutated group, and there was an overlap between high TMB and high microsatellite instability or high PD-L1. In addition, we found that EGFR, KRAS and PIK3CA had a high frequency of both single nucleotide variation and copy number variation mutations. These identified mutant genes were enriched in the oncogenic signaling pathway and the DNA damage repair pathway. At the same time, the somatic cell characteristics and distribution of the two groups were significantly different.

Conclusions

This study identified genetic and phenotypic characteristics of hypermutated tumors and demonstrated that DNA damage repair is critically involved in hypermutation.

MicroRNA-497-5p Is Downregulated in Hepatocellular Carcinoma and Associated with Tumorigenesis and Poor Prognosis in Patients

Background

MicroRNAs (miRNAs) have been demonstrated to exhibit important regulatory roles in multiple malignancies, including hepatocellular carcinoma (HCC). hsa-miR-497-5p was reported to involve in cancer progression and poor prognosis in many kinds of tumors. However, the expression and its clinical significance of hsa-miR-497-5p in HCC remain unclear.

Methods

In the present study, we investigated the expression of hsa-miR-497-5p in HCC and analyzed the correction of clinical features with prognosis. The expression levels of hsa-miR-497-5p and potential target genes were analyzed in HCC and adjacent noncancerous tissues using The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) datasets. Real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to analyze hsa-miR-497-5p levels in 328 HCC tissues and 30 paired adjacent noncancer tissues. Overall survival (OS) and progression-free survival (PFS) of patients with HCC were assessed using the Kaplan-Meier method and the log-rank test.

Results

The hsa-miR-497-5p expression levels were decreased, and its target genes ACTG1, CSNK1D, PPP1CC, and BIRC5 were upregulated in HCC tissues compared with normal tissues. Lower levels of hsa-miR-497-5p expression and higher levels of the four target genes were significantly associated with higher tumor diameter. Moreover, patients with lower hsa-miR-497-5p expression and higher target genes levels had shorter OS.

Conclusion

The expression levels of hsa-miR-497-5p may play an important regulatory role in HCC and are closely correlated with HCC progression and poor prognosis in patients. The hsa-miR-497-5p may be a specific therapeutic target for the treatment of HCC.

Visualization and Analysis in the Field of Pan-Cancer Studies and Its Application in Breast Cancer Treatment

Although all cancers are molecularly distinct, many share common driver mutations. Pan-cancer analysis, utilizes next-generation sequencing (NGS), pan-cancer model systems, and pan-cancer projects such as The Cancer Genome Atlas (TCGA), to assess frequently mutated genes and other genomic abnormalities that are common among many cancer types, regardless of the tumor origin, providing new directions for tumor biology research. However, there is currently no study that has objectively analyzed the results of pan-cancer studies on cancer biology. For this study, 999 articles on pan-cancer published from 2006 to 2020 were obtained from the Scopus database, and bibliometric methods were used to analyze citations, international cooperation, co-authorship and keyword co-occurrence clusters. Furthermore, we also focused on and summarized the application of pan-cancer in breast cancer. Our result shows that the pan-cancer studies were first published in 2006 and entered a period of rapid development after 2013. So far, 86 countries have carried out international cooperation in sharing research. Researchers form the United States and Canada have published the most articles and have made the most extensive contribution to this field, respectively. Through author keyword analysis of the 999 articles, TCGA, biomarkers, NGS, immunotherapy, DNA methylation, prognosis, and several other keywords appear frequently, and these terms are hot spots in pan-cancer studies. There are four subtypes of breast cancer (luminalA, luminalB, HER2, and basal-like) according to pan-cancer analysis of breast cancer. Meanwhile, it was found that breast cancer has genetic similarity to pan-gynecological cancers, such as ovarian cancer, which indicates related etiology and possibly similar treatments. Collectively, with the emergence of new detection methods, new cancer databases, and the involvement of more researchers, pan-cancer analyses will play a greater role in cancer biology research.

Identification of Iron Metabolism-Related Gene Signatures for Predicting the Prognosis of Patients With Sarcomas

Iron is one of the essential trace elements in the human body. An increasing amount of evidence indicates that the imbalance of iron metabolism is related to the occurrence and development of cancer. Here, we obtained the gene expression and clinical data of sarcoma patients from TCGA and the GEO database. The prognostic value of iron metabolism-related genes (IMRGs) in patients with sarcoma and the relationship between these genes and the immune microenvironment were studied by comprehensive bioinformatics analyses. Two signatures based on IMRGs were generated for the overall survival (OS) and disease-free survival (DFS) of sarcoma patients. At 3, 5, and 7 years, the areas under the curve (AUCs) of the OS signature were 0.708, 0.713, and 0.688, respectively. The AUCs of the DFS signature at 3, 5, and 7 years were 0.717, 0.689, and 0.702, respectively. Kaplan–Meier survival analysis indicated that the prognosis of high-risk patients was worse than that of low-risk patients. In addition, immunological analysis showed that there were different patterns of immune cell infiltration among patients in different clusters. Finally, we constructed two nomograms that can be used to predict the OS and DFS of sarcoma patients. The C-index was 0.766 (95% CI: 0.697–0.835) and 0.763 (95% CI: 0.706–0.820) for the OS and DFS nomograms, respectively. Both the ROC curves and the calibration plots showed that the two nomograms have good predictive performance. In summary, we constructed two IMRG-based prognostic models that can effectively predict the OS and DFS of sarcoma patients.

Long Noncoding RNA OIP5-AS1 Promotes the Progression of Liver Hepatocellular Carcinoma via Regulating the hsa-miR-26a-3p/EPHA2 Axis

Numerous studies have suggested that dysregulated long noncoding RNAs (lncRNAs) contributed to the development and progression of many cancers. lncRNA OIP5 antisense RNA 1 (OIP5-AS1) has been reported to be increased in several cancers. However, the roles of OIP5-AS1 in liver hepatocellular carcinoma (LIHC) remain to be investigated. In this study, we demonstrated that OIP5-AS1 was upregulated in LIHC tissue specimens and its overexpression was associated with the poor survival of patients with LIHC. Furthermore, loss-of function experiments indicated that OIP5-AS1 promoted cell proliferation and inhibited cell apoptosis both in vitro and in vivo. Moreover, binding sites between OIP5-AS1 and hsa-miR-26a-3p as well as between hsa-miR-26a-3p and EPHA2 were confirmed by luciferase assays. Finally, a rescue assay was performed to prove the effect of the OIP5-AS1/hsa-miR-26a-3p/EPHA2 axis on LIHC cell biological behaviors. Based on all of the above findings, our results suggested that OIP5-AS1 promoted LIHC cell proliferation and invasion via regulating the hsa-miR-26a-3p/EPHA2 axis.

Survival prediction model for non-small cell lung cancer based on somatic mutations

BACKGROUND

The 5-year survival rate of non-small cell lung cancer (NSCLC) is only 15%. Screening some combined gene mutations could predict the survival of NSCLC patients and also provide new ideas for the diagnosis and treatment of NSCLC. The present study aimed to identify signature mutations for survival prediction of NSCLC.

METHODS

Clinical and gene mutation information for 949 NSCLC patients was downloaded from TCGA. High frequency mutation and common mutation genes were analyzed based on 1000 cancer related genes. The LASSO-COX model was used to screen gene mutation points and analyze their survival, and then a survival prediction model was established. Fifty NSCLC patients were collected and 1000 targeted genes were enriched by targeted next generation sequencing. The results were used to verify the combination of common mutation genes and the function of the survival model, and then to clarify their clinical significance.

RESULTS

Ten variables were screened out after LASSO-COX analysis, including age, tumor stage, EGFR c.[2,573 T>G], PIK3CA c.[1624G>A], TP53 c.[375G>T], TP53 c.[527G>T], TP53 c.[733G>T], TP53 c.[734G>T], TP53 c.[743G>T], NFE2L2 c.[100C>G]. Except for TP53 c.[743G>T] and NFE2L2 c.[100C>G], the residual six hot spot mutations of EGFR, PIK3CA and TP53 could be regarded as a signature mutations for forecasting the survival time of NSCLC.

CONCLUSIONS

The combination of six hot spot mutations of EGFR, PIK3CA and TP53 is expected to be used for predicting the survival time of NSCLC.

Diagnostic model of combined ceRNA and DNA methylation related genes in esophageal carcinoma

Esophageal cancer is a common malignant tumor in the world, and the aim of this study was to screen key genes related to the development of esophageal cancer using a variety of bioinformatics analysis tools and analyze their biological functions. The data of esophageal squamous cell carcinoma from the Gene Expression Omnibus (GEO) were selected as the research object, processed and analyzed to screen differentially expressed microRNAs (miRNAs) and differential methylation genes. The competing endogenous RNAs (ceRNAs) interaction network of differentially expressed genes was constructed by bioinformatics tools DAVID, String, and Cytoscape. Biofunctional enrichment analysis was performed using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). The expression of the screened genes and the survival of the patients were verified. By analyzing GSE59973 and GSE114110, we found three down-regulated and nine up-regulated miRNAs. The gene expression matrix of GSE120356 was calculated by Pearson correlation coefficient, and the 11696 pairs of ceRNA relation were determined. In the ceRNA network, 643 lncRNAs and 147 mRNAs showed methylation difference. Functional enrichment analysis showed that these differentially expressed genes were mainly concentrated in the FoxO signaling pathway and were involved in the corresponding cascade of calcineurin. By analyzing the clinical data in The Cancer Genome Atlas (TCGA) database, it was found that four lncRNAs had an important impact on the survival and prognosis of esophageal carcinoma patients. QRT-PCR was also conducted to identify the expression of the key lncRNAs (RNF217-AS1, HCP5, ZFPM2-AS1 and HCG22) in ESCC samples. The selected key genes can provide theoretical guidance for further research on the molecular mechanism of esophageal carcinoma and the screening of molecular markers.