Effects of the demethylating agent, 5-azacytidine, on expression of the kallikrein-kinin genes in carcinoma cells of the lung and pleura

Minireview: functional roles of tissue kallikrein, kinins, and kallikrein-related peptidases in lung cancer

Despite campaigns and improvements in detection and treatment, lung cancer continues to increase worldwide and represents a major public health problem. One approach to treating patients suffering from lung cancer is to target surface receptors overexpressed on tumor cells, such as GPCR-family kinin receptors, and proteases that control tumor progression, such as kallikrein-related peptidases (KLKs). These proteases have been visualized in recent years due to their contribution to the progression of cancers, such as prostate and ovarian cancer, facilitating the invasive and metastatic capacity of tumor cells in these tissues. In fact, KLK3 is the specific prostate antigen, the only tissue-specific biomarker used to diagnose this malignancy. In lung cancer to date, evidence indicates that KLK5, KLK6, KLK8, KLK11, and KLK14 are the major peptidases regulated and involved in its progression. The expression levels of KLKs in this neoplasm are modulated by the secretome of the different cell types present in the tumor microenvironment, the cancer subtype and the tumor stage, among others. Considering the multiple functions of kinin receptors and KLKs, this review highlights their roles, even considering the SARS-CoV-2 effects. Since lung cancer is often diagnosed in advanced stages, our efforts should focus on early diagnosis, validating for example specific KLKs, especially in high-risk populations such as smokers and people exposed to carcinogenic fumes, oil fields, and contaminated workplaces, unexplored fields to investigate. Furthermore, their modulation could be considered as a promising approach in lung cancer therapeutics.

Association between promoter methylation and gene expression of CGB3 and NOP56 in HPV-infected cervical cancer cells

Overexpression of the E7 gene of human papillomavirus (HPV) type 16 is one of the primary causes of cervical cancer. The E7 protein can bind with DNA methyltransferase I and induce methylation of tumor suppressor genes, such as cyclin-A1 (CCNA1), leading to suppression of their expression, and thus, cancer progression. In the present study, the confirmation of methylation-related expression of chorionic gonadotropin subunit 3 (CGB3) and nucleolar protein 56 (NOP56) genes in 5-Azacytidine (5'-aza)-treated HPV16-positive SiHa and HPV16-negative C33A cell lines was shown. Using methylation-specific-PCR and quantitative PCR, the results showed that CGB3 and NOP56 methylation significantly decreased as the 5'-aza concentration was increased, and this was inversely associated with their expression. Moreover, overexpression of E7 contributed to the augmentation of CGB3 and NOP56 methylation levels in C33A cells, resulting in a decrease in their expression. This study extends on previous observations of E7 HPV16 oncogenic function in terms of methylation-repressing expression in more genes, which may be wholly applied to gene therapy in cervical cancer prevention.

Serum KLKB1 as a Potential Prognostic Biomarker for Hepatocellular Carcinoma Based on Data-Independent Acquisition and Parallel Reaction Monitoring

Purpose

With the advancement of minimally invasive surgery and catheters for hepatocellular carcinoma (HCC), it is becoming more and more inconvenient to get tissues or the tissues gained are insufficient for testing. Screening of blood-derived markers is of great significance for prognosis assessment.

Patients and Methods

Data-independent acquisition (DIA) and parallel reaction monitoring (PRM) were implemented to identify valuable prognostic HCC biomarkers in 48 patients with different prognosis. The potential candidate biomarkers were examined in 205 HCC patients using enzyme-linked immunosorbent assay (ELISA) and then validated in The Cancer Genome Atlas (TCGA) HCC cohort.

Results

DIA screened 86 significantly differentially regulated proteins between patients with poor prognosis and those with good prognosis. Eight proteins from the DIA proteomic analyses were quantified by PRM, and six of them (KLKB1, IGFBP3, SHBG, SAA1, C7, and CD44) presented consistent expression trends between DIA and PRM. Then, the results of ELISA indicated that KLKB1 was abnormally expressed in HCC patients, and the serum level of KLKB1 also exhibited significant changes before and after treatment (P = 0.016). Patients with higher KLKB1 serum levels had significantly superior overall survival (P = 0.035) and progression-free survival (P = 0.027) than those with lower KLKB1 expression. In the TCGA-HCC cohort, Cox regression analysis suggested that KLKB1 was an independent prognostic factor for overall survival (P = 0.032) of HCC patients.

Conclusion

Aberrant expression of KLKB1 was strongly associated with the prognosis of HCC patients. KLKB1 may be used to evaluate the prognosis and guide the treatment for HCC.

Bioinformatics analysis of key biomarkers and potential molecular mechanisms in hepatocellular carcinoma induced by hepatitis B virus

BACKGROUND

Hepatocellular carcinoma (HCC) accounts for up to 90% of all primary hepatic malignancies; it is the sixth most common cancer and the second most common cause of cancer mortality worldwide. Numerous studies have shown that hepatitis B virus and its products, HBV integration, and mutation can induce HCC. However, the molecular mechanisms underpinning the regulation of HCC induced by HBV remain unclear.

METHODS

We downloaded 2 gene expression profiling datasets, of HBV and of HCC induced by HBV, from the gene expression omnibus (GEO) database. Differentially expressed genes (DEGs) between HCC and HBV were identified to explore any predisposing changes in gene expression associated with HCC. DEGs between HCC and adjacent healthy tissues were investigated to identify genes that may play a key role in HCC. Any overlapping genes among these DEGs were included in our bioinformatics analysis. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of overlapping genes were performed using the Metascape online database; the protein-protein interaction (PPI) network was analyzed using the STRING online database; and we obtained the hub genes of the PPI network using Cytoscape software. An overall survival (OS) analysis of hub genes was performed using km-plotter and the gene expression profiling interactive analysis (GEPIA) online database. The expression levels of hub genes were determined using the TCGA and GEPIA databases. Finally, the relationships between hub genes and tumors were analyzed using the comparative toxicogenomics database (CTD).

RESULTS

We identified 113 overlapping genes from the 2 datasets. Using functional and pathway analyses, we found that the overlapping genes were mainly related to the AMPK signaling pathway and cellular responses to cadmium ions. C8A, SPP2, KLKB1, PROZ, C6, FETUB, MBL2, HGFAC, C8B, and ANGPTL3 were identified as hub genes and C8A, SPP2, PROZ, C6, HGFAC, and C8B were found to be significant for survival.

CONCLUSION

The DEGs re-analyzed between HCC and hepatitis B enable a systematic understanding of the molecular mechanisms of HCC reliant on hepatitis B virus.

Prediction of potential drivers connecting different dysfunctional levels in lung adenocarcinoma via a protein-protein interaction network

Lung cancer is a serious disease that threatens an affected individual's life. Its pathogenesis has not yet to be fully described, thereby impeding the development of effective treatments and preventive measures. "Cancer driver" theory considers that tumor initiation can be associated with a number of specific mutations in genes called cancer driver genes. Four omics levels, namely, (1) methylation, (2) microRNA, (3) mutation, and (4) mRNA levels, are utilized to cluster cancer driver genes. In this study, the known dysfunctional genes of these four levels were used to identify novel driver genes of lung adenocarcinoma, a subtype of lung cancer. These genes could contribute to the initiation and progression of lung adenocarcinoma in at least two levels. First, random walk with restart algorithm was performed on a protein-protein interaction (PPI) network constructed with PPI information in STRING by using known dysfunctional genes as seed nodes for each level, thereby yielding four groups of possible genes. Second, these genes were further evaluated in a test strategy to exclude false positives and select the most important ones. Finally, after conducting an intersection operation in any two groups of genes, we obtained several inferred driver genes that contributed to the initiation of lung adenocarcinoma in at least two omics levels. Several genes from these groups could be confirmed according to recently published studies. The inferred genes reported in this study were also different from those described in a previous study, suggesting that they can be used as essential supplementary data for investigations on the initiation of lung adenocarcinoma. This article is part of a Special Issue entitled: Accelerating Precision Medicine through Genetic and Genomic Big Data Analysis edited by Yudong Cai & Tao Huang.

Analysis of DNA methylation and gene expression in radiation-resistant head and neck tumors

Resistance to radiation therapy constitutes a significant challenge in the treatment of head and neck squamous cell cancer (HNSCC). Alteration in DNA methylation is thought to play a role in this resistance. Here, we analyzed DNA methylation changes in a matched model of radiation resistance for HNSCC using the Illumina HumanMethylation450 BeadChip. Our results show that compared to radiation-sensitive cells (SCC-61), radiation-resistant cells (rSCC-61) had a significant increase in DNA methylation. After combining these results with microarray gene expression data, we identified 84 differentially methylated and expressed genes between these 2 cell lines. Ingenuity Pathway Analysis revealed ILK signaling, glucocorticoid receptor signaling, fatty acid α-oxidation, and cell cycle regulation as top canonical pathways associated with radiation resistance. Validation studies focused on CCND2, a protein involved in cell cycle regulation, which was identified as hypermethylated in the promoter region and downregulated in rSCC-61 relative to SCC-61 cells. Treatment of rSCC-61 and SCC-61 with the DNA hypomethylating agent 5-aza-2'deoxycitidine increased CCND2 levels only in rSCC-61 cells, while treatment with the control reagent cytosine arabinoside did not influence the expression of this gene. Further analysis of HNSCC data from The Cancer Genome Atlas found increased methylation in radiation-resistant tumors, consistent with the cell culture data. Our findings point to global DNA methylation status as a biomarker of radiation resistance in HNSCC, and suggest a need for targeted manipulation of DNA methylation to increase radiation response in HNSCC.

Novel kinin B₁ receptor splice variant and 5'UTR regulatory elements are responsible for cell specific B₁ receptor expression

The kinin B₁ receptor (B₁R) is rapidly upregulated after tissue trauma or inflammation and is involved in cancer and inflammatory diseases such as asthma. However, the role of the: promoter; a postulated alternative promoter; and spliced variants in airway epithelial and other lung cells are poorly understood.

We identified, in various lung cell lines and leucocytes, a novel, naturally occurring splice variant (SV) of human B₁R gene with a shorter 5′untranslated region. This novel SV is ≈35% less stable than the wild-type (WT) transcript in lung adenocarcinoma cells (H2126), but does not influence translation efficiency. Cell-specific differences in splice variant expression were observed post des[Arg10]-kallidin stimulation with delayed upregulation of SV compared to WT suggesting potentially different regulatory responses to inflammation. Although an alternative promoter was not identified in our cell-lines, several cell-specific regulatory elements within the postulated alternative promoter region (negative response element (NRE) −1020 to −766 bp in H2126; positive response element (PRE) −766 to −410 bp in 16HBE; −410 to +1 region acts as a PRE in H2126 and NRE in 16HBE cells) were found.

These findings reveal complex regulation of B₁R receptor expression in pulmonary cells which may allow future therapeutic manipulation in chronic pulmonary inflammation and cancer.

High-throughput screening of tumor metastatic-related differential glycoprotein in hepatocellular carcinoma by iTRAQ combines lectin-related techniques

Glycoproteomics is an important aspect in the research of cancer biomarker discovery. The objective of our study is to screen the profile of serum glycoproteins in hepatocellular carcinoma (HCC) patients and to discover differentially expressed glycoproteins in HCC with or without metastasis. We collected serum from HCC patients and divided them into two groups (non-metastatic HCC group and metastatic HCC group) according to 2002 UICC TNM staging system. Wheat germ agglutinin (WGA) lectin was used to enrich the serum glycoproteins by lectin affinity chromatography. The enriched glycoproteins were labeled with mass-balanced isobaric tags (iTRAQ) and analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Two differential glycoproteins were validated by Western blot and biochemical methods, respectively. Fifteen differential serum glycoproteins with WGA affinity were identified (p < 0.05). Among them, nine proteins were up-regulated (>1.5-folds) and six were down-regulated (<0.5-folds) in HCC patients with metastasis. Expression of alpha-1-antitrypsin (SERPINA1) and apolipoprotein A-I (APOA1) was validated by Western blot and biochemical methods, respectively (p < 0.05). Our study has obtained a set of HCC metastasis-associated glycoproteins which may serve as novel prognostic candidates and potential therapeutic targets for HCC metastasis. SERPINA1 might act as a potential glycoprotein biomarker of HCC metastasis.