Novel candidate biomarkers of origin recognition complex 1, 5 and 6 for survival surveillance in patients with hepatocellular carcinoma

Subset-based method for cross-tissue transcriptome-wide association studies improves power and interpretability

Integrating results from genome-wide association studies (GWASs) and studies of molecular phenotypes such as gene expressions can improve our understanding of the biological functions of trait-associated variants and can help prioritize candidate genes for downstream analysis. Using reference expression quantitative trait locus (eQTL) studies, several methods have been proposed to identify gene-trait associations, primarily based on gene expression imputation. To increase the statistical power by leveraging substantial eQTL sharing across tissues, meta-analysis methods aggregating such gene-based test results across multiple tissues or contexts have been developed as well. However, most existing meta-analysis methods have limited power to identify associations when the gene has weaker associations in only a few tissues and cannot identify the subset of tissues in which the gene is "activated." For this, we developed a cross-tissue subset-based transcriptome-wide association study (CSTWAS) meta-analysis method that improves power under such scenarios and can extract the set of potentially associated tissues. To improve applicability, CSTWAS uses only GWAS summary statistics and pre-computed correlation matrices to identify a subset of tissues that have the maximal evidence of gene-trait association. Through numerical simulations, we found that CSTWAS can maintain a well-calibrated type-I error rate, improves power especially when there is a small number of associated tissues for a gene-trait association, and identifies an accurate associated tissue set. By analyzing GWAS summary statistics of three complex traits and diseases, we demonstrate that CSTWAS could identify biological meaningful signals while providing an interpretation of disease etiology by extracting a set of potentially associated tissues.

ORC6 acts as an effective prognostic predictor for non‑small cell lung cancer and is closely associated with tumor progression

Origin recognition complexes (ORCs) are vital in the control of DNA replication and the progression of the cell cycle, however the precise function and mechanism of ORC6 in non-small cell lung cancer (NSCLC) is still not well understood. The present study used bioinformatics methods to assess the predictive significance of ORC6 expression in NSCLC. Moreover, the expression of ORC6 was further evaluated using reverse transcription-quantitative PCR and western blotting, and its functional significance in lung cancer was assessed via knockdown experiments using small interfering RNA. A significant association was demonstrated between the expression of ORC6 and the clinical features of NSCLC. In particular, elevated levels of ORC6 were significantly strongly correlated with an unfavorable prognosis. Multivariate analysis demonstrated that increased ORC6 expression independently contributed to the risk of overall survival (HR 1.304; P=0.015) in individuals diagnosed with NSCLC. Analysis of Kaplan-Meier plots demonstrated that ORC6 expression served as a valuable indicator for diagnosing and predicting the prognosis of NSCLC. Moreover, in vitro studies demonstrated that modified ORC6 expression had a significant impact on the proliferation, migration and metastasis of NSCLC cells. NSCLC cell lines (H1299 and mH1650) exhibited markedly higher ORC6 expression than normal lung cell lines. The results of the present study indicated a strong association between the expression of ORC6 and the clinicopathological characteristics of NSCLC, which suggested its potential as a reliable biomarker for predicting NSCLC. Furthermore, ORC6 may have important therapeutic implications in the management of NSCLC.

Clinical relevance of ORCs in predicting prognosis and immunotherapy outcomes: A pan-cancer analysis

BACKGROUND

The origin recognition complex (ORC) consists of six subunits and mediates DNA replication by binding to its origin. Recent studies show that ORCs are closely related to various biological processes in tumors. However, a comprehensive study of ORCs in pan-cancer has not been conducted.

RESULTS

A systematic evaluation of the expression, mutation, and prognostic significance of ORCs was conducted across cancer types using data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. The single-sample Gene Set Enrichment Analysis (ssGSEA) was performed using R package "Gene Set Variation Analysis (GSVA)" to evaluate ORC score. ORC score was significantly elevated in most cancers and linked with an inferior prognosis. It was positively related to the G2/M checkpoint and DNA repair pathways. An elevated ORC score also correlated with tumor mutation burden (TMB)/ microsatellite instability (MSI). A prognosis analysis suggested that high ORC scores were associated with heightened immunotherapeutic sensitivity.

CONCLUSIONS

Our research elucidates the genomic changes associated with and clinical relevance of ORCs in cancer and provides unique insights for future investigation of ORCs in immunotherapy.

The important role of miR-1-3p in cancers

Cancer is a malignant tumor that seriously threatens human life and health. At present, the main treatment methods include surgical resection, chemotherapy, radiotherapy, and immunotherapy. However, the mechanism of tumor occurrence and development is complex, and it produces resistance to some traditional treatment methods, leading to treatment failure and a high mortality rate for patients. Therefore, exploring the molecular mechanisms of tumor occurrence, development, and drug resistance is a very important task. MiRNAs are a type of non-coding small RNA that regulate a series of biological effects by binding to the 3'-UTR of the target mRNA, degrading the mRNA, or inhibiting its translation. MiR-1-3p is an important member of them, which is abnormally expressed in various tumors and closely related to the occurrence and development of tumors. This article introduces miR-1-3p from multiple aspects, including its production and regulation, role in tumor occurrence and development, clinical significance, role in drug resistance, and approaches for targeting miR-1-3p. Intended to provide readers with a comprehensive understanding of the important role of miR-1-3p in tumors.

Multi-omics analysis reveals the involvement of origin recognition complex subunit 6 in tumor immune regulation and malignant progression

Background

Origin recognition complex 6 (ORC6) is one of the six highly conserved subunit proteins required for DNA replication and is essential for maintaining genome stability during cell division. Recent research shows that ORC6 regulates the advancement of multiple cancers; however, it remains unclear what regulatory impact it has on the tumor immune microenvironment.

Methods

Unpaired Wilcoxon rank sum and signed rank tests were used to analyze the differences in the expression of ORC6 in normal tissues and corresponding tumor tissues. Multiple online databases have evaluated the genetic alterations, protein expression and localization, and clinical relevance of ORC6. To evaluate the potential prognostic impact and diagnostic significance of ORC6 expression, we carried out log-rank, univariate Cox regression, and receiver operating characteristic curve analysis. The ICGC-LIRI-JP cohort, CGGA-301 cohort, CGGA-325 cohort, CGGA-693 cohort, and GSE13041 cohort were used for external validation of the study findings. The associations between ORC6 expression and immune cell infiltration, immune checkpoint expression, and immunotherapy cohorts was further analyzed. To explore the functional and signaling pathways related to ORC6 expression, gene set enrichment analysis was performed. To clarify the expression and function of ORC6 in hepatocellular carcinoma (LIHC) and glioma, we conducted in vitro experiments.

Results

Expression of ORC6 is upregulated in the majority of cancer types and is associated with poor patient prognosis, notably in cases of LIHC and gliomas. In addition, ORC6 may be involved in multiple signaling pathways related to cancer progression and immune regulation. High expression of ORC6 correlates with an immunosuppressive state in the tumor microenvironment. The results of further immunotherapy cohort analysis suggested that patients in the ORC6 high-expression group benefited from immunotherapy. Inhibiting ORC6 expression suppressed the proliferative and migratory abilities of LIHC and glioma cells.

Conclusion

High expression of ORC6 may be used as a biomarker to predict the poor prognosis of most tumor patients. The high expression of ORC6 may be involved in the regulation of the tumor immunosuppressive environment, and it is expected to become a molecular target for inhibiting tumor progression.

Systemic analysis of the DNA replication regulator origin recognition complex in lung adenocarcinomas identifies prognostic and expression significance

BACKGROUND

DNA replication alteration is a hallmark of patients with lung adenocarcinoma (LUAD) and is frequently observed in LUAD progression. Origin recognition complex (ORC) 1, ORC2, ORC3, ORC4, ORC5, and ORC6 form a replication-initiator complex to mediate DNA replication, which plays a key role in carcinogenesis, while their roles in LUAD remain poorly understood.

METHODS

The mRNA and protein expression of ORCs was confirmed by the GEPIA, HPA, CPTAC, and TCGA databases. The protein-protein interaction network was analyzed by the GeneMANIA database. Functional enrichment was confirmed by the Metascape database. The effects of ORCs on immune infiltration were validated by the TIMER database. The prognostic significance of ORCs in LUAD was confirmed by the KM-plot and GENT2 databases. DNA alteration and protein structure were determined in the cBioProtal and PDB databases. Moreover, the protein expression and prognostic value of ORCs were confirmed in our LUAD data sets by immunohistochemistry (IHC) staining.

RESULTS

ORC mRNA and protein were significantly increased in patients with LUAD compared with corresponding normal tissue samples. The results of IHC staining analysis were similar result to those of the above bioinformatics analysis. Furthermore, ORC1 and ORC6 had significant prognostic values for LUAD patients. Furthermore, the ORC cooperatively promoted LUAD development by driving DNA replication, cellular senescence, and metabolic processes.

CONCLUSION

The ORC, especially ORC1/6, has important prognostic and expression significance for LUAD patients.

Bioinformatics Analysis of RNA-seq Data Reveals Genes Related to Cancer Stem Cells in Colorectal Cancerogenesis

Cancer stem cells (CSC) play one of the crucial roles in the pathogenesis of various cancers, including colorectal cancer (CRC). Although great efforts have been made regarding our understanding of the cancerogenesis of CRC, CSC involvement in CRC development is still poorly understood. Using bioinformatics and RNA-seq data of normal mucosa, colorectal adenoma, and carcinoma (n = 106) from GEO and TCGA, we identified candidate CSC genes and analyzed pathway enrichment analysis (PEI) and protein–protein interaction analysis (PPI). Identified CSC-related genes were validated using qPCR and tissue samples from 47 patients with adenoma, adenoma with early carcinoma, and carcinoma without and with lymph node metastasis and were compared to normal mucosa. Six CSC-related genes were identified: ANLN, CDK1, ECT2, PDGFD, TNC, and TNXB. ANLN, CDK1, ECT2, and TNC were differentially expressed between adenoma and adenoma with early carcinoma. TNC was differentially expressed in CRC without lymph node metastases whereas ANLN, CDK1, and PDGFD were differentially expressed in CRC with lymph node metastases compared to normal mucosa. ANLN and PDGFD were differentially expressed between carcinoma without and with lymph node metastasis. Our study identified and validated CSC-related genes that might be involved in early stages of CRC development (ANLN, CDK1, ECT2, TNC) and in development of metastasis (ANLN, PDGFD).

Origin recognition complex 1 regulates phospholipase Cδ1 to inhibit cell proliferation, migration and epithelial-mesenchymal transition in lung adenocarcinoma

As a common pulmonary malignant disease, lung adenocarcinoma exhibits high mortality and morbidity rate. Phospholipase Cδ1 (PLCD1), an enzyme involved in the homeostasis of energy metabolism, is downregulated in lung adenocarcinoma. According to GEPIA, origin recognition complex 1 (ORC1) is a highly expressed gene in lung adenocarcinoma and is negatively associated with PLCD1. To the best of our knowledge, the present study was the first to investigate the role of ORC1 in regulating PLCD1 in lung adenocarcinoma. According to TCGA database, low expression of PLCD1 was correlated with the low overall survival rate of patients suffering from lung adenocarcinoma. The protein and mRNA expression levels of PLCD1 and ORC1 were detected in A549 cells by western blot analysis and reverse transcription-quantitative PCR, respectively. Cell proliferation, invasion and migration were analyzed by MTT, colony formation, Transwell and wound healing assay. Immunofluorescence staining was adopted to estimate the content of Ki67 and western blot was applied for the evaluation of PLCD1, MMP2, MMP9, E-cadherin, N-cadherin, vimentin, Snail and ORC. The binding interaction between ORC1 and PLCD1 was analyzed using chromatin immunoprecipitation and luciferase reporter enzyme gene assays. The results indicated that PLCD1 was lowly expressed in lung adenocarcinoma cells in comparison with that in 16HBE. When PLCD1 was overexpressed in cancer cells, cell proliferation, invasion and migration were significantly inhibited. However, in the presence of both ORC1 and PLCD1 overexpression, the suppressive effects of PLCD1 overexpression alone on cell proliferation, invasion, migration and EMT were attenuated. In conclusion, ORC1 was indicated to inhibit PLCD1, thus regulating the proliferation, migration and EMT processes of lung adenocarcinoma cells, which suggested that ORC1 might be a target for the treatment of lung adenocarcinoma.

Identification of Recurrent Chromosome Breaks Underlying Structural Rearrangements in Mammary Cancer Cell Lines

Cancer genomes are characterized by the accumulation of small-scale somatic mutations as well as large-scale chromosomal deletions, amplifications, and complex structural rearrangements. This characteristic is at least partially dependent on the ability of cancer cells to undergo recurrent chromosome breakage. In order to address the extent to which chromosomal structural rearrangement breakpoints correlate with recurrent DNA double-strand breaks (DSBs), we simultaneously mapped chromosome structural variation breakpoints (using whole-genome DNA-seq) and spontaneous DSB formation (using Break-seq) in the estrogen receptor (ER)-positive breast cancer cell line MCF-7 and a non-cancer control breast epithelium cell line MCF-10A. We identified concurrent DSBs and structural variation breakpoints almost exclusively in the pericentromeric region of chromosome 16q in MCF-7 cells. We fine-tuned the identification of copy number variation breakpoints on 16q. In addition, we detected recurrent DSBs that occurred in both MCF-7 and MCF-10A. We propose a model for DSB-driven chromosome rearrangements that lead to the translocation of 16q, likely with 10q, and the eventual 16q loss that does not involve the pericentromere of 16q. We present evidence from RNA-seq data that select genes, including SHCBP1, ORC6, and MYLK3, which are immediately downstream from the 16q pericentromere, show heightened expression in MCF-7 cell line compared to the control. Data published by The Cancer Genome Atlas show that all three genes have increased expression in breast tumor samples. We found that SHCBP1 and ORC6 are both strong poor prognosis and treatment outcome markers in the ER-positive breast cancer cohort. We suggest that these genes are potential oncogenes for breast cancer progression. The search for tumor suppressor loss that accompanies the 16q loss ought to be augmented by the identification of potential oncogenes that gained expression during chromosomal rearrangements.

Identification of immune infiltration-related genes as prognostic indicators for hepatocellular carcinoma

Hepatocellular carcinoma (HCC) has a high degree of malignancy and a poor prognosis. Immune infiltration-related genes have shown good predictive value in the prognosis of many solid tumours. In this study, we established and verified prognostic biomarkers consisting of immune infiltration-related genes in HCC. Gene expression data and clinical data were downloaded from The Cancer Genome Atlas (TCGA) database. Differential gene expression analysis, univariate Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) regression algorithm were used to screen prognostic immune infiltration-related genes and to construct a risk scoring model. Kaplan-Meier (KM) survival plots and receiver operating characteristic (ROC) curve analysis were used to evaluate the prognostic performance of the risk scoring model in the TCGA-HCC cohort. In addition, a nomogram model with a risk score was established, and its predictive performance was verified by ROC analysis and calibration plot analysis in the TCGA-HCC cohort. Gene set enrichment analysis (GSEA) identified pathways and biological processes that may be enriched in the high-risk group. Finally, immune infiltration analysis was used to explore the characteristics of the tumour microenvironment related to the risk score. We identified 17 immune infiltration-related genes with prognostic value and constructed a risk scoring model. ROC analysis showed that the risk scoring model can accurately predict the 1-year, 3-year, and 5-year overall survival (OS) of HCC patients in the TCGA-HCC cohort. KM analysis showed that the OS of the high-risk group was significantly lower than that of the low-risk group (P < 0.001). The nomogram model effectively predicted the OS of HCC patients in the TCGA-HCC cohort. GSEA indicated that the immune infiltration-related genes may be involved in biological processes such as amino acid and lipid metabolism, matrisome and small molecule transportation, immune system regulation, and hepatitis virus infection. Immune infiltration analysis showed that the level of immune cell infiltration in the high-risk group was low, and the risk score was negatively correlated with infiltrating immune cells. Our prognostic model based on immune infiltration-related genes in HCC could help the prognostic assessment of HCC patients and provide potential targets for HCC inhibition.

Expression and Clinical Significance of Origin Recognition Complex Subunit 6 in Breast Cancer – A Comprehensive Bioinformatics Analysis

Objective

We aimed to investigate the expression, diagnostic and prognostic values, and potential molecular mechanisms of the origin recognition complex (ORC) in breast cancer (BC).

Methods

Kaplan–Meier estimation was used to assess the prognostic value of ORC genes, and Oncomine, TCGA, GEO and ULCAN databases were used to analyze their expression in BC. Wilcoxon rank-sum tests were used to evaluate the relationship between ORC gene expression levels and BC clinicopathological features. Receiver operating characteristic (ROC) curves were used to assess the diagnostic value of ORC genes in BC. Survival analysis was performed using Kaplan–Meier estimation and Cox regression. A nomogram was constructed to predict 1-, 3-, and 5-year survival probabilities in BC. Gene set enrichment analysis (GSEA) and immune infiltration were used to investigate potential molecular mechanisms of the ORC.

Results

ORC1L and ORC6L were highly expressed in BC compared with healthy tissue, while ORC5L expression patterns were inconsistent; no significant differences in ORC2L, ORC3L or ORC4L expression were observed between BC and healthy tissues. ORC1L and ORC6L expression levels were significantly correlated with age, tumor (T) stage and molecular subtype; ORC5L expression was significantly correlated with age and number of nearby lymph nodes with cancer (N stage). ORC6L expression had the highest diagnostic value in BC and was an independent prognostic factor for poor overall survival (OS). ORC6L may be involved in cell cycle progression and may regulate cancer signaling pathways, including NF-κB, P53, and WNT, in BC. ORC6L expression was also associated with immune infiltration.

Conclusion

ORC1L and ORC6L are highly expressed in BC; ORC6L has a high diagnostic value and is an independent prognostic factor for poor OS. ORC6L may be involved in the initiation and progression of BC by regulating cell cycle progression, promoting cancer signaling pathway activation, and influencing tumor immune cell infiltration.

A New Strategy for the Rapid Identification and Validation of the Direct Targets of Aconitine-Induced Cardiotoxicity

Background

The interaction of small molecules with direct targets constitutes the molecular initiation events of drug efficacy and toxicity. Aconitine, an active compound of the Aconitum species, has various pharmacological effects but is strongly toxic to the heart. The direct targets of aconitine-induced cardiotoxicity remain unclear.

Methods

We predicted the toxic targets of aconitine based on network pharmacology and followed a novel proteomic approach based on the "drug affinity responsive target stability" technology combined with LC-MS/MS to identify the direct targets of aconitine. The identified targets were analysed from the perspective of multilevel and multidimensional bioinformatics through a network integration method. The binding sites were investigated via molecular docking to explore the toxicity mechanism and predict the direct targets of aconitine. Finally, atomic force microscopy (AFM) imaging was performed to verify the affinity of aconitine to the direct targets.

Results

PTGS2, predicted by network pharmacology as a toxic target, encodes cyclooxygenase 2 (COX-2), which is closely related to myocardial injury. Furthermore, cytosolic phospholipase A2 (cPLA2) is the upstream signal protein of PTGS2, and it is a key enzyme in the metabolism of arachidonic acid during an inflammatory response. We determined cPLA2 as a direct target, and AFM imaging verified that aconitine could bind to cPLA2 well; thus, aconitine may cause the expression of PTGS2/COX-2 and release inflammatory factors, thereby promoting myocardial injury and dysfunction.

Conclusion

We developed a complete set of methods to predict and verify the direct targets of aconitine, and cPLA2 was identified as one. Overall, the novel strategy provides new insights into the discovery of direct targets and the molecular mechanism of toxic components that are found in traditional Chinese medicine.

Transcription factor E2F4 is an indicator of poor prognosis and is related to immune infiltration in hepatocellular carcinoma

Background: Recent studies have shown that the transcription factor E2F4 is involved in the progression of various tumors, but its expression and influence on immune cell infiltration and biological functions are largely unknown in hepatocellular carcinoma (HCC).

Methods: The Cancer Genome Atlas (TCGA) database, the Tumor Immune Estimation Resource (TIMER) and related online tools as well as a tissue microarray (TMA) were used for analyses in our study.

Results: E2F4 expression was elevated in HCC tumor tissue compared with adjacent normal tissue at both the mRNA and protein levels. Overexpression of E2F4 was markedly related to a poor prognosis in HCC patients. In addition, positively and negatively correlated significant genes of E2F4 were identified in HCC. Pathway enrichment analyses revealed that the top 100 positively correlated significant genes of E2F4 were closely related to nuclear splicing and degradation-related pathways. Furthermore, nine hub genes correlated with E2F4 expression were validated based on a protein-protein interaction (PPI) network. It was also demonstrated that E2F4 expression was negatively correlated to immune purity and positively correlated to immune cell infiltration.

Conclusion: E2F4 could serve as a novel biomarker for HCC diagnosis and prognosis prediction.