Analysis of RNA expression of normal and cancer tissues reveals high correlation of COP9 gene expression with respiratory chain complex components

Analysis of Copy Number Variation of DNA Repair/Damage Response Genes in Tumor Tissues

Cells experience increased genome instability through the course of disease development including cancer initiation and progression. Point mutations, insertion/deletions, translocations, and amplifications of both coding and noncoding regions all contribute to cancer phenotypes. Copy number variation (CNV), i.e., changes of the number of copies of nuclear DNA, occurs in the genome of even normal somatic cells. Studies to understand the effects of CNV on tumor development, especially aspects concerning tumor aggressiveness and the influence on outcomes of therapeutic modalities, have been reignited by the breakthrough technologies of the molecular genomics. This section discusses the significance of analyzing CNVs that cause simultaneous increase/decrease of clusters of genes, using the expression profile of XRCC1 with its neighbor genes LIG1, PNKP, and POLD1 as an example. Methods for CNV assay at the individual gene level on formalin-fixed, paraffin-embedded (FFPE) tissues using the NanoString nCounter technology will then be described.

Panels of mRNAs and miRNAs for decoding molecular mechanisms of Renal Cell Carcinoma (RCC) subtypes utilizing Artificial Intelligence approaches

Renal Cell Carcinoma (RCC) encompasses three histological subtypes, including clear cell RCC (KIRC), papillary RCC (KIRP), and chromophobe RCC (KICH) each of which has different clinical courses, genetic/epigenetic drivers, and therapeutic responses. This study aimed to identify the significant mRNAs and microRNA panels involved in the pathogenesis of RCC subtypes. The mRNA and microRNA transcripts profile were obtained from The Cancer Genome Atlas (TCGA), which were included 611 ccRCC patients, 321 pRCC patients, and 89 chRCC patients for mRNA data and 616 patients in the ccRCC subtype, 326 patients in the pRCC subtype, and 91 patients in the chRCC for miRNA data, respectively. To identify mRNAs and miRNAs, feature selection based on filter and graph algorithms was applied. Then, a deep model was used to classify the subtypes of the RCC. Finally, an association rule mining algorithm was used to disclose features with significant roles to trigger molecular mechanisms to cause RCC subtypes. Panels of 77 mRNAs and 73 miRNAs could discriminate the KIRC, KIRP, and KICH subtypes from each other with 92% (F1-score ≥ 0.9, AUC ≥ 0.89) and 95% accuracy (F1-score ≥ 0.93, AUC ≥ 0.95), respectively. The Association Rule Mining analysis could identify miR-28 (repeat count = 2642) and CSN7A (repeat count = 5794) along with the miR-125a (repeat count = 2591) and NMD3 (repeat count = 2306) with the highest repeat counts, in the KIRC and KIRP rules, respectively. This study found new panels of mRNAs and miRNAs to distinguish among RCC subtypes, which were able to provide new insights into the underlying responsible mechanisms for the initiation and progression of KIRC and KIRP. The proposed mRNA and miRNA panels have a high potential to be as biomarkers of RCC subtypes and should be examined in future clinical studies.

COPS8 in cutaneous melanoma: an oncogene that accelerates the malignant development of tumor cells and predicts poor prognosis

This study aimed to investigate the roles of COP9 signalosome subunit 8 (COPS8) and its underlying mechanism in cutaneous melanoma. Bioinformatics tools were utilized to analyze the expression of COPS8 in cutaneous melanoma, while Kaplan-Meier analysis was employed to assess the correlation between COPS8 and patients' overall survival. The proliferation, migration, and invasion of cells were estimated by CCK8, colony formation, and Transwell assays. Western blot was used to check the expression of epithelial-mesenchymal transition (EMT)-related proteins. Results showed that COPS8 was up-regulated and predicted a poor clinical outcome for cutaneous melanoma patients. Knockdown of COPS8 inhibited cutaneous melanoma cell proliferation, migration and invasion, whereas overexpression of COPS8 resulted in the opposite outcomes. The up-regulation of E-cadherin and down-regulation of N-cadherin, vimentin, and snail were caused by silencing COPS8 while their expression showed contrary trends in cells with overexpressed COPS8. Collectively, COPS8 is up-regulated and promotes cutaneous melanoma progression via regulating EMT.

Glutaminase inhibition with telaglenastat (CB-839) improves treatment response in combination with ionizing radiation in head and neck squamous cell carcinoma models

The efficacy of ionizing radiation (IR) for head and neck cancer squamous cell carcinoma (HNSCC) is limited by poorly understood mechanisms of adaptive radioresistance. Elevated glutaminase gene expression is linked to significantly reduced survival (p < 0.03). The glutaminase inhibitor, telaglenastat (CB-839), has been tested in Phase I/II cancer trials and is well tolerated by patients. This study investigated if telaglenastat enhances the cellular response to IR in HNSCC models. Using three human HNSCC cell lines and two xenograft mouse models, we examined telaglenastat's effects on radiation sensitivity. IR and telaglenastat combinatorial treatment reduced cell survival (p ≤ 0.05), spheroid size (p ≤ 0.0001) and tumor growth in CAL-27 xenograft bearing mice relative to vehicle (p ≤ 0.01), telaglenastat (p ≤ 0.05) or IR (p ≤ 0.01) monotherapy. Telaglenastat significantly reduced the Oxygen Consumption Rate/Extracellular Acidification Rate ratio in CAL-27 and HN5 cells in the presence of glucose and glutamine (p ≤ 0.0001). Telaglenastat increased oxidative stress and DNA damage in irradiated CAL-27 cells. These data suggest that combination treatment with IR and telaglenastat leads to an enhanced anti-tumor response. This pre-clinical data, combined with the established safety of telaglenastat justifies further investigation for the combination in HNSCC patients.

CSN1 facilitates proliferation and migration of hepatocellular carcinoma cells by upregulating cyclin A2 expression

Constitutive photomorphogenesis 9 signalosome subunit 1 (CSN1) plays an important role in the ubiquitin-proteasome pathway and regulates various cellular processes, such as the cell cycle and DNA repair. The CSN complex consists of eight subunits (CSN1 to CSN8) and regulates the tumorigenesis of a variety of tumor types. However, the exact role of CSN1 in hepatocellular carcinoma (HCC) remains unclear. The present study evaluated the expression and biological effects of CSN1 in HCC tissue samples and cell lines. CSN1 was significantly overexpressed in HCC tissue and cell lines, compared with their normal counterparts. In patients with HCC, elevated CSN1 levels correlated with tumor size, tumor metastasis and tumor stage. Loss‑of‑function assays indicated that CSN1 knockdown inhibited the proliferation and migration HCC cells. In addition, CSN1 promoted the expression of cyclin A2 in a ubiquitination‑independent manner. Lastly, xenograft experiments indicated that CSN1 promoted HCC tumor growth in vivo. The present study suggested that CSN1 inhibition could represent a potential approach for the prevention of HCC progression and metastasis.

Evaluation of antioxidant network proteins as novel prognostic biomarkers for head and neck cancer patients

OBJECTIVES

Recurrence rates for head and neck squamous cell carcinoma (HNSCC) approach 50% at 5 years. Current staging fails to identify patients with a worse prognosis who might benefit from intensified treatment, which warrants improved prognostic biomarkers. The purpose of this retrospective case study is to identify potential prognostic biomarkers in patients with HNSCC including APE1 (DNA repair/redox gene regulator), NRF2 and PPARGC1A (redox gene regulators), SOD3 and DCN (antioxidant proteins).

MATERIALS AND METHODS

Differential protein expression between benign, carcinoma in situ (CIS), and invasive HNSCC tissue specimens from 77 patients was assessed using immunohistochemistry. Protein expression was analyzed with multivariate, pair-wise, and Kaplan-Meier survival analyses to identify potential prognostic biomarkers. Utilizing The Cancer Genome Atlas's transcriptome database, pair-wise and survival analysis was performed to identify potential prognostic biomarkers.

RESULTS

APE1, NRF2, PPARGC1A, SOD3, and DCN expression in HNSCC in relation to, lymph node invasion, and patient survival were examined. Elevated APE1 protein expression in CIS corresponded with reduced survival (p = 0.0243). Increased APE1 gene expression in stage T4a HNSCC was associated with reduced patient survival (p < 0.015). Increased PPARGC1A in invasive tumor correlated with reduced survival (p = 0.0281). Patients with lymph node invasion at diagnosis had significantly increased APE1 protein in the primary sites (p < 0.05). Patients with poorly differentiated invasive tumors had reduced PPARGC1A in CIS proximal to the invasive tumor and had elevated DCN and SOD3 in proximal benign tissue (p < 0.05).

CONCLUSIONS

The expression of APE1, DCN, and SOD3 is a potential prognostic signature that identifies patients with worsened survival.

Alternative Polyadenylation Modification Patterns Reveal Essential Posttranscription Regulatory Mechanisms of Tumorigenesis in Multiple Tumor Types

Among various risk factors for the initiation and progression of cancer, alternative polyadenylation (APA) is a remarkable endogenous contributor that directly triggers the malignant phenotype of cancer cells. APA affects biological processes at a transcriptional level in various ways. As such, APA can be involved in tumorigenesis through gene expression, protein subcellular localization, or transcription splicing pattern. The APA sites and status of different cancer types may have diverse modification patterns and regulatory mechanisms on transcripts. Potential APA sites were screened by applying several machine learning algorithms on a TCGA-APA dataset. First, a powerful feature selection method, minimum redundancy maximum relevancy, was applied on the dataset, resulting in a feature list. Then, the feature list was fed into the incremental feature selection, which incorporated the support vector machine as the classification algorithm, to extract key APA features and build a classifier. The classifier can classify cancer patients into cancer types with perfect performance. The key APA-modified genes had a potential prognosis ability because of their significant power in the survival analysis of TCGA pan-cancer data.

Efficiently Detecting Protein Complexes from Protein Interaction Networks via Alternating Direction Method of Multipliers

Protein complexes are crucial in improving our understanding of the mechanisms employed by proteins. Various computational algorithms have thus been proposed to detect protein complexes from protein interaction networks. However, given massive protein interactome data obtained by high-throughput technologies, existing algorithms, especially those with additionally consideration of biological information of proteins, either have low efficiency in performing their tasks or suffer from limited effectiveness. For addressing this issue, this work proposes to detect protein complexes from a protein interaction network with high efficiency and effectiveness. To do so, the original detection task is first formulated into an optimization problem according to the intuitive properties of protein complexes. After that, the framework of alternating direction method of multipliers is applied to decompose this optimization problem into several subtasks, which can be subsequently solved in a separate and parallel manner. An algorithm for implementing this solution is then developed. Experimental results on five large protein interaction networks demonstrated that compared to state-of-the-art protein complex detection algorithms, our algorithm outperformed them in terms of both effectiveness and efficiency. Moreover, as number of parallel processes increases, one can expect an even higher computational efficiency for the proposed algorithm with no compromise on effectiveness.

Long non-coding RNA KRT19P3 suppresses proliferation and metastasis through COPS7A-mediated NF-κB pathway in gastric cancer

Long non-coding RNAs (lncRNAs) have emerged as critical regulators in gastric cancer (GC). LncRNA expression microarray data indicate that KRT19P3 (Keratin 19 Pseudogene 3) is downregulated in GC samples. However, the expression pattern and molecular mechanism of KRT19P3 in GC have not been characterized. The present study confirmed the downregulation of KRT19P3 in GC tissues and cells. Decreased expression of KRT19P3 was correlated with larger tumor size, advanced TNM stage, Lauren's classification, positive lymph node metastasis, and poor prognosis. Enforced expression of KRT19P3 significantly inhibited cell proliferation, migration, and invasion in vitro, as well as tumorigenesis and metastasis in vivo. Conversely, KRT19P3 knockdown had opposite effects. Mechanistically, RNA pull-down and RNA immunoprecipitation assay revealed that KRT19P3 could directly bind COPS7A. KRT19P3 enhanced COPS7A protein stability in GC cells, and KRT19P3 suppressed GC cell proliferation and metastasis partly through regulation of COPS7A expression. COPS7A could promote deubiquitinylation of IκBα, which was executed by CSN-associated deubiquitinylase USP15, and then KRT19P3 inactivated nuclear factor kappa-B (NF-κB) signaling pathway in a COPS7A-dependent manner. For the first time, we revealed that KRT19P3 could suppress tumor growth and metastasis through COPS7A-mediated NF-κB pathway, which may serve as potential targets for treatment of GC in the future.

Genetic variants of genes in the NER pathway associated with risk of breast cancer: A large-scale analysis of 14 published GWAS datasets in the DRIVE study

A recent hypothesis-free pathway-level analysis of genome-wide association study (GWAS) datasets suggested that the overall genetic variation measured by single nucleotide polymorphisms (SNPs) in the nucleotide excision repair (NER) pathway genes was associated with breast cancer (BC) risk, but no detailed SNP information was provided. To substantiate this finding, we performed a larger meta-analysis of 14 previously published GWAS datasets in the Discovery, Biology and Risk of Inherited Variants in Breast Cancer (DRIVE) study with 53,107 subjects of European descent. Using a hypothesis-driven approach, we selected 138 candidate genes from the NER pathway using the "Molecular Signatures Database (MsigDB)" and "PathCards". All SNPs were imputed using IMPUTE2 with the 1000 Genomes Project Phase 3. Logistic regression was used to estimate BC risk, and pooled ORs for each SNP were obtained from the meta-analysis using the false discovery rate for multiple test correction. RegulomeDB, HaploReg, SNPinfo and expression quantitative trait loci (eQTL) analysis were used to assess the SNP functionality. We identified four independent SNPs associated with BC risk, BIVM-ERCC5 rs1323697_C (OR = 1.06, 95% CI = 1.03-1.10), GTF2H4 rs1264308_T (OR = 0.93, 95% CI = 0.89-0.97), COPS2 rs141308737_C deletion (OR = 1.06, 95% CI = 1.03-1.09) and ELL rs1469412_C (OR = 0.93, 95% CI = 0.90-0.96). Their combined genetic score was also associated with BC risk (OR = 1.12, 95% CI = 1.08-1.16, p_trend < 0.0001). The eQTL analysis revealed that BIVM-ERCC5 rs1323697 C and ELL rs1469412 C alleles were correlated with increased mRNA expression levels of their genes in 373 lymphoblastoid cell lines (p = 0.022 and 2.67 × 10^-22 , respectively). These SNPs might have roles in the BC etiology, likely through modulating their corresponding gene expression.

Dramatic dysbalancing of the Wnt pathway in breast cancers

Wnt signaling is important for breast development and remodeling during pregnancy and lactation. Epigenetic modifications change expression levels of components of the Wnt pathway, underlying oncogenic transformation. However, no clear Wnt component increasing expression universally across breast cancer (BC) or its most Wnt-dependent triple-negative BC (TNBC) subgroup has been identified, delaying development of targeted therapies. Here we perform network correlation analysis of expression of >100 Wnt pathway components in hundreds of healthy and cancerous breast tissues. Varying in expression levels among people, Wnt components remarkably coordinate their production; this coordination is dramatically decreased in BC. Clusters with coordinated gene expression exist within the healthy cohort, highlighting Wnt signaling subtypes. Different BC subgroups are identified, characterized by different remaining Wnt signaling signatures, providing the rational for patient stratification for personalizing the therapeutic applications. Key pairwise interactions within the Wnt pathway (some inherited and some established de novo) emerge as targets for future drug discovery against BC.