Combined analysis and validation for DNA methylation and gene expression profiles associated with prostate cancer

Integrated analysis of single-cell RNA-seq and bulk RNA-seq to unravel the molecular mechanisms underlying the immune microenvironment in the development of intestinal-type gastric cancer

Intestinal-type gastric cancer (IGC) is the most frequent type of gastric cancer in high-incidence populations. The early stages of IGC growth successively include nonatrophic gastritis (NAG), chronic atrophic gastritis (CAG) and intestinal metaplasia (IM). However, the mechanisms of IGC development through these stages remain unclear. For this study, single-cell RNA-seq data related to IGC were downloaded from the GEO database, and immune cells of the tumor microenvironment (TME) were annotated using R software. Changes in the proportion of immune cells and altered cell-to-cell interactions were explored at different disease stages using R software, with a focus on plasma cells. Additionally, IGC samples from the TCGA database were used for immune cell infiltration analysis, and a Cox proportional risk regression model was constructed to identify possible prognostic genes. The results indicated that for precancerous lesions, interactions between immune cells were mainly dominated by chemokines to stimulate the infiltration and activation of immune cells. In tumors, intercellular movement of upregulated molecules and amplified signals were associated with the tumor necrosis factor family and immunosuppression to escape immune surveillance and promote tumor growth. Regarding prognostic analysis, IGLC3, IGLV1-44, IGKV1-16, IGHV3-21, IGLV1-51, and IGLV3-19 were found to be novel biomarkers for IGC. Our analysis of the IGC single-cell atlas together with bulk transcriptome data contributes to understanding TME heterogeneity at the molecular level during IGC development and provides insights for elucidating the mechanism of IGC and discovering novel targets for precise therapy.

Enzalutamide and olaparib synergistically suppress castration-resistant prostate cancer progression by promoting apoptosis through inhibiting nonhomologous end joining pathway

Recent studies revealed the relationship among homologous recombination repair (HRR), androgen receptor (AR), and poly(adenosine diphosphate-ribose) polymerase (PARP); however, the synergy between anti-androgen enzalutamide (ENZ) and PARP inhibitor olaparib (OLA) remains unclear. Here, we showed that the synergistic effect of ENZ and OLA significantly reduced proliferation and induced apoptosis in AR-positive prostate cancer cell lines. Next-generation sequencing followed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses revealed the significant effects of ENZ plus OLA on nonhomologous end joining (NHEJ) and apoptosis pathways. ENZ combined with OLA synergistically inhibited the NHEJ pathway by repressing DNA-dependent protein kinase catalytic subunit (DNA-PKcs) and X-ray repair cross complementing 4 (XRCC4). Moreover, our data showed that ENZ could enhance the response of prostate cancer cells to the combination therapy by reversing the anti-apoptotic effect of OLA through the downregulation of anti-apoptotic gene insulin-like growth factor 1 receptor ( IGF1R ) and the upregulation of pro-apoptotic gene death-associated protein kinase 1 ( DAPK1 ). Collectively, our results suggested that ENZ combined with OLA can promote prostate cancer cell apoptosis by multiple pathways other than inducing HRR defects, providing evidence for the combined use of ENZ and OLA in prostate cancer regardless of HRR gene mutation status.

Identification of prognostic and diagnostic signatures for cancer and acute myocardial infarction: multi-omics approaches for deciphering heterogeneity to enhance patient management

Patients diagnosed with cancer face an increased risk of cardiovascular events in the short term, while those experiencing acute myocardial infarction (AMI) have a higher incidence of cancer. Given limitations in clinical resources, identifying shared biomarkers offers a cost-effective approach to risk assessment by minimizing the need for multiple tests and screenings. Hence, it is crucial to identify common biomarkers for both cancer survival and AMI prediction. Our study suggests that monocyte-derived biomarkers, specifically WEE1, PYHIN1, SEC61A2, and HAL, hold potential as predictors for cancer prognosis and AMI. We employed a novel formula to analyze mRNA levels in clinical samples from patients with AMI and cancer, resulting in the development of a new risk score based on expression profiles. By categorizing patients into high-risk and low-risk groups based on the median risk score, we observed significantly poorer overall survival among high-risk patients in cancer cohorts using Kaplan-Meier analysis. Furthermore, calibration curves, decision curve analysis (DCA), and clinical impact curve analyses provided additional evidence supporting the robust diagnostic capacity of the risk score for AMI. Noteworthy is the shared activation of the Notch Signaling pathway, which may shed light on common high-risk factors underlying both AMI and cancer. Additionally, we validated the differential expression of these genes in cell lines and clinical samples, respectively, reinforcing their potential as meaningful biomarkers. In conclusion, our study demonstrates the promise of mRNA levels as biomarkers and emphasizes the significance of further research for validation and refinement.

DNA methylation biomarkers for noninvasive detection of triple-negative breast cancer using liquid biopsy

Noninvasive detection of aberrant DNA methylation could provide invaluable biomarkers for earlier detection of triple-negative breast cancer (TNBC) which could help clinicians with easier and more efficient treatment options. We evaluated genome-wide DNA methylation data derived from TNBC and normal breast tissues, peripheral blood of TNBC cases and controls and reference samples of sorted blood and mammary cells. Differentially methylated regions (DMRs) between TNBC and normal breast tissues were stringently selected, verified and externally validated. A machine-learning algorithm was applied to select the top DMRs, which then were evaluated on plasma-derived circulating cell-free DNA (cfDNA) samples of TNBC patients and healthy controls. We identified 23 DMRs accounting for the methylation profile of blood cells and reference mammary cells and then selected six top DMRs for cfDNA analysis. We quantified un-/methylated copies of these DMRs by droplet digital PCR analysis in a plasma test set from TNBC patients and healthy controls and confirmed our findings obtained on tissues. Differential cfDNA methylation was confirmed in an independent validation set of plasma samples. A methylation score combining signatures of the top three DMRs overlapping with the SPAG6, LINC10606 and TBCD/ZNF750 genes had the best capability to discriminate TNBC patients from controls (AUC = 0.78 in the test set and AUC = 0.74 in validation set). Our findings demonstrate the usefulness of cfDNA-based methylation signatures as noninvasive liquid biopsy markers for the diagnosis of TNBC.

Utility of atherosclerosis-associated serum antibodies against colony-stimulating factor 2 in predicting the onset of acute ischemic stroke and prognosis of colorectal cancer

Introduction

Autoantibodies against inflammatory cytokines may be used for the prevention of atherosclerosis. Preclinical studies consider colony-stimulating factor 2 (CSF2) as an essential cytokine with a causal relationship to atherosclerosis and cancer. We examined the serum anti-CSF2 antibody levels in patients with atherosclerosis or solid cancer.

Methods

We measured the serum anti-CSF2 antibody levels via amplified luminescent proximity homogeneous assay-linked immunosorbent assay based on the recognition of recombinant glutathione S-transferase-fused CSF2 protein or a CSF2-derived peptide as the antigen.

Results

The serum anti-CSF2 antibody (s-CSF2-Ab) levels were significantly higher in patients with acute ischemic stroke (AIS), acute myocardial infarction (AMI), diabetes mellitus (DM), and chronic kidney disease (CKD) compared with healthy donors (HDs). In addition, the s-CSF2-Ab levels were associated with intima-media thickness and hypertension. The analyzes of samples obtained from a Japan Public Health Center-based prospective study suggested the utility of s-CSF2-Ab as a risk factor for AIS. Furthermore, the s-CSF2-Ab levels were higher in patients with esophageal, colorectal, gastric, and lung cancer than in HDs but not in those with mammary cancer. In addition, the s-CSF2-Ab levels were associated with unfavorable postoperative prognosis in colorectal cancer (CRC). In CRC, the s-CSF2-Ab levels were more closely associated with poor prognosis in patients with p53-Ab-negative CRC despite the lack of significant association of the anti-p53 antibody (p53-Ab) levels with the overall survival.

Conclusion

S-CSF2-Ab was useful for the diagnosis of atherosclerosis-related AIS, AMI, DM, and CKD and could discriminate poor prognosis, especially in p53-Ab-negative CRC.

Endocrine Disrupting Chemicals Influence Hub Genes Associated with Aggressive Prostate Cancer

Prostate cancer (PCa) is one of the most frequently diagnosed cancers among men in the world. Its prevention has been limited because of an incomplete understanding of how environmental exposures to chemicals contribute to the molecular pathogenesis of aggressive PCa. Environmental exposures to endocrine-disrupting chemicals (EDCs) may mimic hormones involved in PCa development. This research aims to identify EDCs associated with PCa hub genes and/or transcription factors (TF) of these hub genes in addition to their protein-protein interaction (PPI) network. We are expanding upon the scope of our previous work, using six PCa microarray datasets, namely, GSE46602, GSE38241, GSE69223, GSE32571, GSE55945, and GSE26126, from the NCBI/GEO, to select differentially expressed genes based on |log2FC| (fold change) ≥ 1 and an adjusted p-value < 0.05. An integrated bioinformatics analysis was used for enrichment analysis (using DAVID.6.8, GO, KEGG, STRING, MCODE, CytoHubba, and GeneMANIA). Next, we validated the association of these PCa hub genes in RNA-seq PCa cases and controls from TCGA. The influence of environmental chemical exposures, including EDCs, was extrapolated using the chemical toxicogenomic database (CTD). A total of 369 overlapping DEGs were identified associated with biological processes, such as cancer pathways, cell division, response to estradiol, peptide hormone processing, and the p53 signaling pathway. Enrichment analysis revealed five up-regulated (NCAPG, MKI67, TPX2, CCNA2, CCNB1) and seven down-regulated (CDK1, CCNB2, AURKA, UBE2C, BUB1B, CENPF, RRM2) hub gene expressions. Expression levels of these hub genes were significant in PCa tissues with high Gleason scores ≥ 7. These identified hub genes influenced disease-free survival and overall survival of patients 60-80 years of age. The CTD studies showed 17 recognized EDCs that affect TFs (NFY, CETS1P54, OLF1, SRF, COMP1) that are known to bind to our PCa hub genes, namely, NCAPG, MKI67, CCNA2, CDK1, UBE2C, and CENPF. These validated differentially expressed hub genes can be potentially developed as molecular biomarkers with a systems perspective for risk assessment of a wide-ranging list of EDCs that may play overlapping and important role(s) in the prognosis of aggressive PCa.

LncRNA HOTAIRM1 Involved in Nano NiO-Induced Pulmonary Fibrosis via Regulating PRKCB DNA Methylation-Mediated JNK/c-Jun Pathway

Nickel oxide nanoparticles (Nano NiO) lead to pulmonary fibrosis, and the mechanisms are associated with epigenetics. This study aimed to clarify the regulatory relationship among long noncoding RNA HOXA transcript antisense RNA myeloid-specific 1 (HOTAIRM1), DNA methylation and expression of protein kinase C beta (PRKCB), and JNK/c-Jun pathway in Nano NiO-induced pulmonary fibrosis. Therefore, we constructed the rat pulmonary fibrosis model by intratracheal instillation of Nano NiO twice a week for 9 weeks and established the collagen deposition model by treating BEAS-2B cells with Nano NiO for 24 h. Here, the DNA methylation pattern was analyzed by whole-genome bisulfite sequencing in rat fibrotic lung tissues. Then, we integrated mRNA transcriptome data and found 93 DNA methylation genes with transcriptional significance. Meanwhile, the data showed that Nano NiO caused the down-regulation of lncRNA HOTAIRM1, the hypomethylation, and up-regulation of PRKCB2, JNK/c-Jun pathway activation, and collagen deposition (the up-regulated Col-I and α-SMA) both in vivo and in vitro. DNMTs inhibitor 5-AZDC attenuated Nano NiO-induced PRKCB2 expression, JNK/c-Jun pathway activation, and collagen deposition, but overexpression of PRKCB2 aggravated the changes mentioned indicators in Nano NiO-induced BEAS-2B cells. Furthermore, JNK/c-Jun pathway inhibitor (SP600125) alleviated Nano NiO-induced excessive collagen formation. Additionally, overexpression of HOTAIRM1 restrained the PRKCB hypomethylation, the activation of JNK/c-Jun pathway, and collagen formation induced by Nano NiO in BEAS-2B cells. In conclusion, these findings demonstrated that HOTAIRM1 could arrest Nano NiO-induced pulmonary fibrosis by suppressing the PRKCB DNA methylation-mediated JNK/c-Jun pathway.

Combinatorial approaches of nanotherapeutics for inflammatory pathway targeted therapy of prostate cancer

Prostate cancer (PC) is the most prevalent male urogenital cancer worldwide. PC patients presenting an advanced or metastatic cancer succumb to the disease, even after therapeutic interventions including radiotherapy, surgery, androgen deprivation therapy (ADT), and chemotherapy. One of the hallmarks of PC is evading immune surveillance and chronic inflammation, which is a major challenge towards designing effective therapeutic formulations against PC. Chronic inflammation in PC is often characterized by tumor microenvironment alterations, epithelial-mesenchymal transition and extracellular matrix modifications. The inflammatory events are modulated by reactive nitrogen and oxygen species, inflammatory cytokines and chemokines. Major signaling pathways in PC includes androgen receptor, PI3K and NF-κB pathways and targeting these inter-linked pathways poses a major therapeutic challenge. Notably, many conventional treatments are clinically unsuccessful, due to lack of targetability and poor bioavailability of the therapeutics, untoward toxicity and multidrug resistance. The past decade witnessed an advancement of nanotechnology as an excellent therapeutic paradigm for PC therapy. Modern nanovectorization strategies such as stimuli-responsive and active PC targeting carriers offer controlled release patterns and superior anti-cancer effects. The current review initially describes the classification, inflammatory triggers and major inflammatory pathways of PC, various PC treatment strategies and their limitations. Subsequently, recent advancement in combinatorial nanotherapeutic approaches, which target PC inflammatory pathways, and the mechanism of action are discussed. Besides, the current clinical status and prospects of PC homing nanovectorization, and major challenges to be addressed towards the advancement PC therapy are also addressed.

Identification of a novel cellular senescence-related signature for the prediction of prognosis and immunotherapy response in colon cancer

The study was conducted to construct a cellular senescence-related risk score signature to predict prognosis and immunotherapy response in colon cancer. Colon cancer data were acquired from the Gene Expression Omnibus and The Cancer Genome Atlas databases. And cellular senescence-related genes were obtained from the CellAge database. The colon cancer data were classified into different clusters based on cellular senescence-related gene expression. Next, prognostic differential genes among clusters were identified with survival analysis. A cellular senescence-related risk score signature was developed by performing the LASSO regression analysis. Finally, PCA analysis, t-SNE analysis, Kaplan-Meier survival analysis, ROC analysis, univariate Cox regression analysis, multivariate Cox regression analysis, C-index analysis, meta-analysis, immune infiltration analysis, and IPS score analysis were used to evaluate the significance of the risk signature for predicting prognosis and immunotherapy response in colon cancer. The colon cancer data were classified into three clusters. The patients in cluster A and cluster B had longer survival. A cellular senescence-related risk score signature was developed. Patients in the low-risk score group showed a better prognosis. The risk score signature could predict colon cancer patients’ prognosis independently of other clinical characteristics. The risk score signature predicted the prognosis of colon cancer patients more accurately than other signatures. Patients in the low-risk score group showed a better response to immunotherapy. The opposite was true for the high-risk score group. In conclusion, the cellular senescence-related risk score signature could be used for the prediction of prognosis and immunotherapy response in colon cancer.

C1QTNF6 regulated by miR-29a-3p promotes proliferation and migration in stage I lung adenocarcinoma

OBJECTIVE

C1QTNF6 has been implicated as an essential component in multiple cellular and molecular preliminary event, including inflammation, glucose metabolism, endothelial cell modulation and carcinogenesis. However, the biological process and potential mechanism of C1QTNF6 in lung adenocarcinoma (LUAD) are indefinite and remain to be elucidated. Therefore, we investigated the interaction among the traits of C1QTNF6 and LUAD pathologic process.

METHODS

RT-qPCR and western blot were conducted to determine the expression levels of C1QTNF6. RNA interference and overexpression of C1QTNF6 were constructed to identify the biological function of C1QTNF6 in cellular proliferative, migratory and invasive potentials in vitro. Dual-luciferase reporter assay was applied to identify the possible interaction between C1QTNF6 and miR-29a-3p. Moreover, RNA sequencing analysis of C1QTNF6 knockdown was performed to identify the potential regulatory pathways.

RESULTS

C1QTNF6 was upregulated in stage I LUAD tissues compared with adjacent non-cancerous tissues. Concurrently, C1QTNF6 knockdown could remarkably inhibit cell proliferation, migratory and invasive abilities, while overexpression of C1QTNF6 presented opposite results. Additionally, miR-29a-3p may serve as an upstream regulator of C1QTNF6 and reduce the expression of C1QTNF6. Subsequent experiments showed that miR-29a-3p could decrease the cell mobility and proliferation positive cell rates, as well as reduce the migratory and invasive possibilities in LUAD cells via downregulating C1QTNF6. Moreover, RNA sequencing analysis demonstrated that the cytokine-cytokine receptor interaction pathway may participate in the process of C1QTNF6 regulating tumor progression.

CONCLUSION

Our study first demonstrated that downregulation of C1QTNF6 could inhibit tumorigenesis and progression in LUAD cells negatively regulated by miR-29a-3p. These consequences could reinforce our awareness and understanding of the underlying mechanism and provide a promising therapeutic target for LUAD.

Environmental Phenol and Paraben Exposure Risks and Their Potential Influence on the Gene Expression Involved in the Prognosis of Prostate Cancer

Prostate cancer (PCa) is one of the leading malignant tumors in US men. The lack of understanding of the molecular pathology on the risk of food supply chain exposures of environmental phenol (EP) and paraben (PB) chemicals limits the prevention, diagnosis, and treatment options. This research aims to utilize a risk assessment approach to demonstrate the association of EP and PB exposures detected in the urine samples along with PCa in US men (NHANES data 2005−2015). Further, we employ integrated bioinformatics to examine how EP and PB exposure influences the molecular pathways associated with the progression of PCa. The odds ratio, multiple regression model, and Pearson coefficients were used to evaluate goodness-of-fit analyses. The results demonstrated associations of EPs, PBs, and their metabolites, qualitative and quantitative variables, with PCa. The genes responsive to EP and PB exposures were identified using the Comparative Toxicogenomic Database (CTD). DAVID.6.8, GO, and KEGG enrichment analyses were used to delineate their roles in prostate carcinogenesis. The plug-in CytoHubba and MCODE completed identification of the hub genes in Cytoscape software for their roles in the PCa prognosis. It was then validated by using the UALCAN database by evaluating the expression levels and predictive values of the identified hub genes in prostate cancer prognosis using TCGA data. We demonstrate a significant association of higher levels of EPs and PBs in the urine samples, categorical and numerical confounders, with self-reported PCa cases. The higher expression levels of the hub genes (BUB1B, TOP2A, UBE2C, RRM2, and CENPF) in the aggressive stages (Gleason score > 8) of PCa tissues indicate their potential role(s) in the carcinogenic pathways. Our results present an innovative approach to extrapolate and validate hub genes responsive to the EPs and PBs, which may contribute to the severity of the disease prognosis, especially in the older population of US men.

Identification of Epigenetically Modified Hub Genes and Altered Pathways Associated With Retinoblastoma

Retinoblastoma (Rb) is the most common childhood malignancy initiated by biallelic mutation in RB1 gene and driven by various epigenetic events including DNA methylation and microRNA dysregulation. Hence, understanding the key genes that are critically modulated by epigenetic modifications in RB1 -/- cells is very important to identify prominent biomarkers and therapeutic targets of Rb. In this study, we for the first time have integrated various Rb microarray NCBI-GEO datasets including DNA Methylation (GSE57362), miRNA (GSE7072) and mRNA (GSE110811) to comprehensively investigate the epigenetic consequences of RB loss in retinoblastoma tumors and identify genes with the potential to serve as early diagnostic markers and therapeutic targets for Rb. Interestingly, the GEO2R and co-expression network analysis have identified three genes namely E2F3, ESR1, and UNC5D that are significantly deregulated by modified DNA methylation, mRNA and microRNA expression in Rb tumors. Due to their recognition in all epigenetic, transcriptomic, and miRNA datasets, we have termed these genes as "common genes". The results of our integrative bioinformatics analysis were validated in vitro by studying the gene and protein expression of these common genes in Y79, WERI-Rb-1, Rb cell lines and non-tumorigenic retinal pigment epithelial cell line (hTERT-RPE). The expression of E2F3 and UNC5D were up-regulated and that of ESR1 was down-regulated in Rb tumor cells when compared to that in non-tumorigenic hTERT-RPE cells. More importantly, UNC5D, a potent tumor suppressor gene in most cancers is significantly up-regulated in Y79 and Weri Rb1 cells, which, in turn, questions its anti-cancer properties. Together, our study shows that E2F3, ESR1, and UNC5D may be crucially involved in Rb tumorigenesis and possess the potential to act as early diagnostic biomarkers and therapeutic targets of Rb.

EGR1 and KLF4 as Diagnostic Markers for Abdominal Aortic Aneurysm and Associated With Immune Infiltration

Background

Formation and rupture of abdominal aortic aneurysm (AAA) is fatal, and the pathological processes and molecular mechanisms underlying its formation and development are unclear. Perivascular adipose tissue (PVAT) has attracted extensive attention as a newly defined secretory organ, and we aim to explore the potential association between PVAT and AAA.

Methods

We analyzed gene expression and clinical data of 30 PVAT around AAA and 30 PVAT around normal abdominal aorta (NAA). The diagnostic markers and immune cell infiltration of PVAT were further investigated by WGCNA, CIBERSORT, PPI, and multiple machine learning algorisms (including LASSO, RF, and SVM). Subsequently, eight-week-old C57BL/6 male mice (n = 10) were used to construct AAA models, and aorta samples were collected for molecular validation. Meanwhile, fifty-five peripheral venous blood samples from patients (AAA vs. normal: 40:15) in our hospital were used as an inhouse cohort to validate the diagnostic markers by qRT-PCR. The diagnostic efficacy of biomarkers was assessed by receiver operating characteristic (ROC) curve, area under the ROC (AUC), and concordance index (C-index).

Results

A total of 75 genes in the Grey60 module were identified by WGCNA. To select the genes most associated with PVAT in the grey60 module, three algorithms (including LASSO, RF, and SVM) and PPI were applied. EGR1 and KLF4 were identified as diagnostic markers of PVAT, with high accurate AUCs of 0.916, 0.926, and 0.948 (combined two markers). Additionally, the two biomarkers also displayed accurate diagnostic efficacy in the mice and inhouse cohorts, with AUCs and C-indexes all >0.8. Compared with the NAA group, PVAT around AAA was more abundant in multiple immune cell infiltration. Ultimately, the immune-related analysis revealed that EGR1 and KLF4 were associated with mast cells, T cells, and plasma cells.

Conclusion

EGR1 and KLF4 were diagnostic markers of PVAT around AAA and associated with multiple immune cells.

Detection of hypermethylated BCAT1 and IKZF1 DNA in blood and tissues of colorectal, breast and prostate cancer patients

BACKGROUND: Detection of circulating cell-free DNA (ccfDNA) methylated in BCAT1 and IKZF1 is a sensitive for detection of colorectal cancer (CRC), but it is not known if these biomarkers are present in other common adenocarcinomas. OBJECTIVE: Compare methylation levels of BCAT1 and IKZF1 in tissue and plasma from breast, prostate, and colorectal cancer patients. METHODS: Blood was collected from 290 CRC, 32 breast and 101 prostate cancer patients, and 606 cancer-free controls. Tumor and matched normal tissues were collected at surgery: 26 breast, 9 prostate and 15 CRC. DNA methylation in BCAT1 and IKZF1 was measured in blood and tissues. RESULTS: Either biomarker was detected in blood from 175/290 (60.3%) of CRC patients. The detection rate was higher than that measured in controls (48/606 (8.1%), OR = 18.2, 95%CI: 11.1–29.0). The test positivity rates in breast and prostate cancer patients were 9.4% (3/32) and 6.9% (7/101), respectively, and not significantly different to that measured in gender-matched controls (8.0% (33/382) females (OR = 0.84, 95%CI: 0.23–3.1) and 7.6% (26/318) males (OR = 0.86, 95%CI: 0.65–2.1). In tumor and non-neoplastic tissues, 93.5% (14/15) of CRC tumors were methylated in BCAT1 and/or IKZF1 (p< 0.004). Only 11.5% (3/26) and 44.4% (4/9) (p= 0.083) of breast and prostate tumors were hypermethylated in these two genes. CONCLUSIONS: Detection of circulating DNA methylated in BCAT1 and IKZF1 is sensitive and specific for CRC but not breast or prostate cancer.

Functions and roles of IFIX, a member of the human HIN-200 family, in human diseases

Pyrin and hematopoietic expression, interferon-inducible nature, and nuclear localization (HIN) domain family member 1 (PYHIN1), also known as IFIX, belongs to the family of pyrin proteins. This family includes structurally and functionally related mouse (e.g., p202, p203, and p204 proteins) and human (e.g., the interferon-inducible protein 16, absent in melanoma 2 protein, myeloid cell nuclear differentiation antigen, and pyrin and HIN domain family 1 or IFIX) proteins. The IFIX protein belongs to the HIN-200 family of interferon-inducible proteins that have a 200-amino acid signature motif at their C-termini. The increased expression of pyrin proteins in most cell types inhibits cell cycle control and modulates cell survival. Consistent with this role for pyrin proteins, IFIX is a potential antiviral DNA sensor that is essential for immune responses, the detection of viral DNA in the nucleus and cytoplasm, and the binding of foreign DNA via its HIN domain in a sequence non-specific manner. By promoting the ubiquitination and subsequent degradation of MDM2, IFIX acts as a tumor suppressor, thereby leading to p53/TP53 stabilization, HDAC1 regulation via the ubiquitin-proteasome pathway, and tumor-cell-specific silencing of the maspin gene. These data demonstrate that the potential molecular mechanism(s) underlying the action of the IFIX protein might be associated with the development of human diseases, such as viral infections, malignant tumors, and autoimmune diseases. This review summarizes the current insights into IFIX functions and how its regulation affects the outcomes of various human diseases.

PYHIN1 correlates with CD8+ T cells infiltration and confers good patient survival in oral cancer

Background/purpose

Immunotherapy has become a research hotspot and is used for head and neck cancer treatment. This research aims to explore the prognostic value of PYHIN1 in oral cancer and the relationship between PYHIN1 and cancer immunity.

Materials and methods

The expression of PYHIN1 in clinical specimens was evaluated by bioinformatics analyses and immunohistochemistry.

Results

Gene ontology term enrichment analyses and gene set enrichment analyses showed the involvement of PYHIN1 in the modulation of adaptive immunity-associated signaling according to The Cancer Genome Atlas database and Gene Expression Omnibus dataset. Interestingly, the correlation analyses in The Cancer Genome Atlas database revealed a positive correlation between PYHIN1 expression and activated CD8+ T cells infiltration and a negative correlation between PYHIN1 expression and tumor purity. Moreover, activated CD8+ T cells infiltration predicted good patient survival and was negatively correlated with tumor purity. Importantly, PYHIN1 expression was negatively correlated with the pathological stage and was positively associated with a good prognosis in patients with oral cancer. The data obtained from the Gene Expression Omnibus dataset and immunohistochemistry confirmed the positive association between PYHIN1 and CD8+ T cells infiltration in oral cancer tissues.

Conclusion

We conclude that PYHIN1 is an indicator of cancer immunity, and is an independent prognostic factor that may be an alternative target for oral cancer treatment.

Identification of Signature Genes in the PD-1 Relative Gastric Cancer Using a Combined Analysis of Gene Expression and Methylation Data

BACKGROUND

The morbidity and mortality rates for gastric cancer (GC) rank second among all cancers, indicating the serious threat it poses to human health, as well as human life. This study aims to identify the pathways and genes as well as investigate the molecular mechanisms of tumor-related genes in gastric cancer (GC).

METHOD

We compared differentially expressed genes (DEGs) and differentially methylated genes (DMGs) in gastric cancer and normal tissue samples using The Cancer Genome Atlas (TCGA) data. The Kyoto Encyclopedia of Gene and Genome (KEGG) and the Gene Ontology (GO) enrichment analysis' pathway annotations were conducted on DMGs and DEGs using a clusterProfiler R package to identify the important functions, as well as the biological processes and pathways involved. The intersection of the two was chosen and defined as differentially methylated and expressed genes (DMEGs). For DMEGs, we used the principal component analysis (PCA) to differentiate gastric cancer from adjacent samples. The linear discriminant analysis method was applied to categorize the samples using DMEGs methylation data and DMEGs expression profiles data and was validated using the leave-one-out cross-validation (LOOCV) method. We plotted the ROC curve for the classification and calculated the AUC (area under the ROC curve) value for a more intuitive view of the classification effect. We also used the NetworkAnalyst 3.0 tool to analyze DMEGs, using DrugBank to acquire information on protein-drug interactions and generate a network map of gene-drug interactions.

RESULTS

We identified a total of 971 DMGs in 188 PD-1 negative and 187 PD-1 positive gastric cancer samples obtained from TCGA. The KEGG and GO enrichment analysis showed the involvement of the regulation of ion transmembrane transport, collagen-containing extracellular matrix, cell-cell junction, and peptidase regulator activity. We simultaneously obtained 1,189 DEGs, out of which 986 were downregulated, while 203 were upregulated in tumors. The enriched analysis of the GO's and KEGG's pathways indicated that the most significant pathways included an intestinal immune network for IgA production, Staphylococcus aureus infection, cytokine-cytokine receptor interaction, and viral protein interaction with cytokine and cytokine receptor, which have previously been linked with gastric cancer. The compound DB01830 can bind well to the active site of the LCK protein and shows good stability, thus making it a potential inhibitor of the LCK protein. To observe the relationship between DMEGs' expression and prognosis, we observed 10 genes, among which were TRIM29, TSPAN8, EOMES, PPP1R16B, SELL, PCED1B, IYD, JPH1, CEACAM5, and RP11-44K6.2. Their high expressions were related to high risks. Besides, those genes were validated in different internal and external validation sets.

CONCLUSION

These results may provide potential molecular biological therapy for PD-1 negative gastric cancer.

Reduced DAPK1 Expression Promotes Stem Cell-Like Characteristics of Prostate Cancer Cells by Activating ZEB1 via Hippo/YAP Signaling Pathway

Prostate cancer (PCa) is a malignant tumor that originates in the male genitourinary system. Downregulation of death-associated protein kinase 1 (DAPK1) is closely related to PCa. Little is known about the functional role of DAPK1 in regulating cancer stem cell (CSC)-like characteristics of PCa cells, and we have conducted research on this topic. Compared with tumor-adjacent normal tissues, DAPK1 was severely downregulated in tumor tissues of PCa patients. DAPK1 expression was also reduced in PCa cell lines with respect to that in normal prostate cells. Moreover, we sorted PCa-CSCs (PCa-CD133⁺ cells) from PCa cells. PCa-CD133⁺ cells also exhibited a reduced DAPK1 level and elevated levels of stem cell markers (CD44, OCT4, and SOX2). DAPK1 knockdown promoted sphere formation and enhanced the proportions of PCa-CD133⁺/PCa-CD133^- cells. Inhibition of DAPK1 also accelerated migration and invasion of PCa-CD133⁺ cells. In addition, DAPK1 interacted with zinc finger E-box-binding homeobox-1 (ZEB1) and repressed ZEB1 expression in PCa-CD133⁺ cells. DAPK1 suppressed Hippo/YAP signaling pathway by interacting with ZEB1. Finally, we generated a tumor xenograft model to verify the effect of PCa-CD133⁺ cells following DAPK1 overexpression on tumor growth of PCa. DAPK1 overexpression inhibited tumor growth of PCa and repressed the expression of ZEB1, YAP, and TAZ in the tumor tissues of PCa mice. In conclusion, reduced DAPK1 expression promoted stem cell-like characteristics of PCa cells through activating ZEB1 via Hippo/YAP signaling pathway. Taken together, this work sheds lights on the potential of DAPK1 as a target for PCa therapeutics from bench to clinic.

Using Tumor-Infiltrating Immune Cells and a ceRNA Network Model to Construct a Prognostic Analysis Model of Thyroid Carcinoma

Thyroid carcinoma is a solid malignant tumor that has had a fast-growing incidence in recent years. Our research used thyroid carcinoma gene expression profiling from TCGA (The Cancer Genome Atlas) database to identify differentially expressed ceRNAs. Using the gene expression profiling from 502 carcinoma thyroid tissues and 58 normal thyroid tissues from the TCGA database, we established the thyroid carcinoma-specific competitive endogenous RNA (ceRNA) network and found nine overall survival (OS)-associated genes (PRDM1, TGFBR3, E2F1, FGF1, ADAM12, ALPL, RET, AL928654.2, AC128688.2). We quantified the proportions of immune cells using the algorithm “CIBERSORT”, found three OS-associated immune cells (memory B cells, M0 macrophages, and activated dendritic cells), and established a thyroid carcinoma-specific immune cell network based on that. The good reliabilities AUC (area under the curve) of 10-year survival (0.955, 0.944, respectively) were accessed from the nomograms of genes and immune cells. Subsequently, by conducting co-expression analyses, we found a potential regulation network among ceRNAs and immune cells. Besides, we found that ALPL (alkaline phosphatase) and hsa-miR-204-5p were significantly correlated and that ALPL was related to activated dendritic cells. We took advantage of multi-dimensional databases to verify our discovery. Besides, immunohistochemistry (IHC) assays were conducted to detect the expression of a dendritic cell marker (CD11c) and ALPL in thyroid carcinoma (TC) and paracancerous tissues. In summary, our study found a potential mechanism in which hsa-miR-204-5p regulated ALPL in activated dendritic cells, which may allow them to play a critical role in thyroid carcinoma. These findings provide potential prognostic biomarkers and therapeutic targets for thyroid carcinoma.

Variables Associated with Detection of Methylated BCAT1 or IKZF1 in Blood from Patients Without Colonoscopically Evident Colorectal Cancer

BACKGROUND

DNA methylated in BCAT1 and IKZF1 are promising circulating tumor DNA (ctDNA) biomarkers for colorectal cancer detection. This study tested for variables that might be associated with their detection in patients without colonoscopically evident colorectal cancer so-called false positives.

METHODS

A retrospective review of demographic and clinical variables was conducted on patients who were assayed for these biomarkers prior to a colonoscopy for any indication. Potential relationships between detection of these biomarkers and patient variables in patients without colorectal cancer were identified by logistic regression. An age- and sex-matched case-control study was undertaken to identify additional associations.

RESULTS

A total of 196 of 1,593 patients undergoing colonoscopy were positive for BCAT1 and/or IKZF1 methylation; 70 (35.7%) had confirmed diagnosis of colorectal cancer. Of the 126 false positives, biomarker levels were significantly lower than in those with colorectal cancer (P < 0.05), with the total cell-free circulating DNA concentration associated with biomarker detection (OR, 1.16; 95% CI, 1.10-1.22), and 83 (65.9%) of the non-colorectal cancer cases positive for methylated BCAT1 only. Age ≥70 years was the only demographic variable associated with biomarker detection (OR, 4.31; 95% CI, 1.50-12.41). No significant associations were seen with medications or comorbidities (P > 0.05). Four cases without colonoscopically evident colorectal cancer but with biomarker levels above the median for patients with colorectal cancer were diagnosed with metastatic adenocarcinoma within 1 year.

CONCLUSIONS

False-positive results were most commonly associated with detection of methylated BCAT1 only, as well as age ≥70 years.

IMPACT

In the absence of colonoscopically evident colorectal cancer, a high level of circulating methylated DNA warrants investigations for cancers at other sites.

circRNA circ_102049 Implicates in Pancreatic Ductal Adenocarcinoma Progression through Activating CD80 by Targeting miR-455-3p

Emerging evidence has shown that circular RNAs (circRNAs) and DNA methylation play important roles in the causation and progression of cancers. However, the roles of circRNAs and abnormal methylation genes in the tumorigenesis of pancreatic ductal adenocarcinoma (PDAC) are still largely unknown. Expression profiles of circRNA, gene methylation, and mRNA were downloaded from the GEO database, and differentially expressed genes were obtained via GEO2R, and a ceRNA network was constructed based on circRNA-miRNA pairs and miRNA-mRNA pairs. Inflammation-associated genes were collected from the GeneCards database. Then, functional enrichment analysis and protein-protein interaction (PPI) networks of inflammation-associated methylated expressed genes were investigated using Metascape and STRING databases, respectively, and visualized in Cytoscape. Hub genes of PPI networks were identified using the NetworkAnalyzer plugin. Also, we analyzed the methylation, protein expression levels, and prognostic value of hub genes in PDAC patients through the UALCAN, Human Protein Atlas (HPA), and Kaplan-Meier plotter databases, respectively. The circRNA_102049/miR-455-3p/CD80 axis was identified by the ceRNA network and hub genes. In vitro and in vivo experiments were performed to evaluate the functions of circRNA_102049. The regulatory mechanisms of circRNA_102049 and miR-455-3p were explored by RT-PCR, western blot, and dual-luciferase assays. In the present study, twelve hub genes (STAT1, CCND1, KRAS, CD80, ICAM1, ESR1, RAF1, RPS6KA2, KDM6B, TNRC6A, FOSB, and DNM1) were determined from the PPI networks. Additionally, the circRNA_102049 was upregulated in PDAC cell lines. Functionally, the knockdown of circRNA_102049 by siRNAs inhibited cell growth, inflammatory factors, and migratory and invasive potential and promoted cell apoptosis. Mechanistically, circRNA_102049 functioned as a sponge of miR-455-3p and partially reversed the effect of miR-455-3p and consequently upregulated CD80 expression. Our findings showed that circRNA_102049 and methylated hub genes play an important role in the proliferation, apoptosis, migration, invasion, and inflammatory response of PDAC, which might be selected as a promising prognostic marker and therapeutic target for PDAC.

Gene expression analysis of human prostate cell lines with and without tumor metastasis suppressor CD82

BACKGROUND

Tetraspanin CD82 is a tumor metastasis suppressor that is known to down regulate in various metastatic cancers. However, the exact mechanism by which CD82 prevents cancer metastasis is unclear. This study aims to identify genes that are regulated by CD82 in human prostate cell lines.

METHODS

We used whole human genome microarray to obtain gene expression profiles in a normal prostate epithelial cell line that expressed CD82 (PrEC-31) and a metastatic prostate cell line that does not express CD82 (PC3). Then, siRNA silencing was used to knock down CD82 expression in PrEC-31 while CD82 was re-expressed in PC3 to acquire differentially-expressed genes in the respective cell line.

RESULTS

Differentially-expressed genes with a P < 0.05 were identified in 3 data sets: PrEC-31 (+CD82) vs PrEC-31(-CD82), PC3-57 (+CD82) vs. PC3-5 V (-CD82), and PC3-29 (+CD82) vs. PC3-5 V (-CD82). Top 25 gene lists did not show overlap within the data sets, except (CALB1) the calcium binding protein calbindin 1 which was significantly up-regulated (2.8 log fold change) in PrEC-31 and PC3-29 cells that expressed CD82. Other most significantly up-regulated genes included serine peptidase inhibitor kazal type 1 (SPINK1) and polypeptide N-acetyl galactosaminyl transferase 14 (GALNT14) and most down-regulated genes included C-X-C motif chemokine ligand 14 (CXCL14), urotensin 2 (UTS2D), and fibroblast growth factor 13 (FGF13). Pathways related with cell proliferation and angiogenesis, migration and invasion, cell death, cell cycle, signal transduction, and metabolism were highly enriched in cells that lack CD82 expression. Expression of two mutually inclusive genes in top 100 gene lists of all data sets, runt-related transcription factor (RUNX3) and trefoil factor 3 (TFF3), could be validated with qRT-PCR.

CONCLUSION

Identification of genes and pathways regulated by CD82 in this study may provide additional insights into the role that CD82 plays in prostate tumor progression and metastasis, as well as identify potential targets for therapeutic intervention.

A Three Protein-Coding Gene Prognostic Model Predicts Overall Survival in Bladder Cancer Patients

Bladder cancer (BLCA) is the most common urinary tract tumor and is the 11th most malignant cancer worldwide. With the development of in-depth multisystem sequencing, an increasing number of prognostic molecular markers have been identified. In this study, we focused on the role of protein-coding gene methylation in the prognosis of BLCA. We downloaded BLCA clinical and methylation data from The Cancer Genome Atlas (TCGA) database and used this information to identify differentially methylated genes and construct a survival model using lasso regression. We assessed 365 cases, with complete information regarding survival status, survival time longer than 30 days, age, gender, and tumor characteristics (grade, stage, T, M, N), in our study. We identified 353 differentially methylated genes, including 50 hypomethylated genes and 303 hypermethylated genes. After annotation, a total of 227 genes were differentially expressed. Of these, 165 were protein-coding genes. Three genes (zinc finger protein 382 (ZNF382), galanin receptor 1 (GALR1), and structural maintenance of chromosomes flexible hinge domain containing 1 (SMCHD1)) were selected for the final risk model. Patients with higher-risk scores represent poorer survival than patients with lower-risk scores in the training set (HR = 2.37, 95% CI 1.43-3.94, p = 0.001), in the testing group (HR = 1.85, 95% CI 1.16-2.94, p = 0.01), and in the total cohort (HR = 2.06, 95% CI 1.46-2.90, p < 0.001). Further univariate and multivariate analyses using the Cox regression method were conducted in these three groups, respectively. All the results indicated that risk score was an independent risk factor for BLCA. Our study screened the different methylation protein-coding genes in the BLCA tissues and constructed a robust risk model for predicting the outcome of BLCA patients. Moreover, these three genes may function in the mechanism of development and progression of BLCA, which should be fully clarified in the future.

Concomitant DNA methylation and transcriptome signatures define epidermal responses to acute solar UV radiation

The simultaneous analysis of different regulatory levels of biological phenomena by means of multi-omics data integration has proven an invaluable tool in modern precision medicine, yet many processes ultimately paving the way towards disease manifestation remain elusive and have not been studied in this regard. Here we investigated the early molecular events following repetitive UV irradiation of in vivo healthy human skin in depth on transcriptomic and epigenetic level. Our results provide first hints towards an immediate acquisition of epigenetic memories related to aging and cancer and demonstrate significantly correlated epigenetic and transcriptomic responses to irradiation stress. The data allowed the precise prediction of inter-individual UV sensitivity, and molecular subtyping on the integrated post-irradiation multi-omics data established the existence of three latent molecular phototypes. Importantly, further analysis suggested a form of melanin-independent DNA damage protection in subjects with higher innate UV resilience. This work establishes a high-resolution molecular landscape of the acute epidermal UV response and demonstrates the potential of integrative analyses to untangle complex and heterogeneous biological responses.

PYCR1 knockdown inhibits the proliferation, migration, and invasion by affecting JAK/STAT signaling pathway in lung adenocarcinoma

Lung adenocarcinoma (LUAD), as a form of non-small cell lung cancer (NSCLC), is the most frequently diagnosed lung cancer worldwide. To date, a few biomarkers have been reported to provide valuable information in guiding LUAD treatment. The aim of our study was to explore the functional role of pyrroline-5-carboxylate reductase 1 (PYCR1) in LUAD. Based on Oncomine database, we found that PYCR1 was highly expressed in LUAD tissues. We also confirmed an abnormal increase of PYCR1 expression in LUAD cell lines and patients' tissues. Through Kaplan-Meier plotter database, we further studied the prognostic values of PYCR1. The outcomes indicated that overexpressed PYCR1 associated with poor prognosis among LUAD patients. To further study the function of PYCR1 in LUAD, cell counting kit-8, colony-forming, scratch wound healing, and Transwell assays were conducted. The results suggested that knockdown of PYCR1 curbed cell proliferation, migration, and invasion in LUAD cell lines. Subsequently, we identified 50 top genes positively and negatively correlated with PYCR1 in LUAD, and conducted biological pathway enrichment analysis of these genes. Among those enriched pathways, we selected JAK/STAT signaling pathway for further analysis. The results of Western blot assays revealed that PYCR1 knockdown significantly increased the expression of Bcl-2 and c-Myc, and the phosphorylation level of JAK2 and STAT3. Taken together, this study unearthed that PYCR1 knockdown could inhibit tumor growth and affect the JAK/STAT signaling pathway in LUAD. This study may contribute to a better understanding of PYCR1 in LUAD and provide a potential biomarker for cancer prognosis.

Comprehensive analysis of DNA methylation and gene expression profiles in cholangiocarcinoma

BACKGROUND

The incidence of cholangiocarcinoma (CCA) has risen in recent years, and it has become a significant health burden worldwide. However, the mechanisms underlying tumorigenesis and progression of this disease remain largely unknown. An increasing number of studies have demonstrated crucial biological functions of epigenetic modifications, especially DNA methylation, in CCA. The present study aimed to identify and analyze methylation-regulated differentially expressed genes (MeDEGs) involved in CCA tumorigenesis and progression by bioinformatics analysis.

METHODS

The gene expression profiling dataset (GSE119336) and gene methylation profiling dataset (GSE38860) were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and differentially methylated genes (DMGs) were identified using the limma packages of R and GEO2R, respectively. The MeDEGs were obtained by overlapping the DEGs and DMGs. Functional enrichment analyses of these genes were then carried out. Protein-protein interaction (PPI) networks were constructed using STRING and visualized in Cytoscape to determine hub genes. Finally, the results were verified based on The Cancer Genome Atlas (TCGA) database.

RESULTS

We identified 98 hypermethylated, downregulated genes and 93 hypomethylated, upregulated genes after overlapping the DEGs and DMGs. These genes were mainly enriched in the biological processes of the cell cycle, nuclear division, xenobiotic metabolism, drug catabolism, and negative regulation of proteolysis. The top nine hub genes of the PPI network were F2, AHSG, RRM2, AURKB, CCNA2, TOP2A, BIRC5, PLK1, and ASPM. Moreover, the expression and methylation status of the hub genes were significantly altered in TCGA.

CONCLUSIONS

Our study identified novel methylation-regulated differentially expressed genes (MeDEGs) and explored their related pathways and functions in CCA, which may provide novel insights into a further understanding of methylation-mediated regulatory mechanisms in CCA.

Identification of potential biomarkers and pivotal biological pathways for prostate cancer using bioinformatics analysis methods

Background

Prostate cancer (PCa) is a common urinary malignancy, whose molecular mechanism has not been fully elucidated. We aimed to screen for key genes and biological pathways related to PCa using bioinformatics method.

Methods

Differentially expressed genes (DEGs) were filtered out from the GSE103512 dataset and subjected to the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. The protein–protein interactions (PPI) network was constructed, following by the identification of hub genes. The results of former studies were compared with ours. The relative expression levels of hub genes were examined in The Cancer Genome Atlas (TCGA) and Oncomine public databases. The University of California Santa Cruz Xena online tools were used to study whether the expression of hub genes was correlated with the survival of PCa patients from TCGA cohorts.

Results

Totally, 252 (186 upregulated and 66 downregulated) DEGs were identified. GO analysis enriched mainly in “oxidation-reduction process” and “positive regulation of transcription from RNA polymerase II promoter”; KEGG pathway analysis enriched mostly in “metabolic pathways” and “protein digestion and absorption.” Kallikrein-related peptidase 3, cadherin 1 (CDH1), Kallikrein-related peptidase 2 (KLK2), forkhead box A1 (FOXA1), and epithelial cell adhesion molecule (EPCAM) were identified as hub genes from the PPI network. CDH1, FOXA1, and EPCAM were validated by other relevant gene expression omnibus datasets. All hub genes were validated by both TCGA and Oncomine except KLK2. Two additional top DEGs (ABCC4 and SLPI) were found to be associated with the prognosis of PCa patients.

Conclusions

This study excavated the key genes and pathways in PCa, which might be biomarkers for diagnosis, prognosis, and potential therapeutic targets.