Peptidase inhibitor 15 as a novel blood diagnostic marker for cholangiocarcinoma

Triterpenoid ursolic acid regulates the environmental carcinogen benzo[a]pyrene-driven epigenetic and metabolic alterations in SKH-1 hairless mice for skin cancer interception

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous environmental carcinogens accountable to developing skin cancers. Recently, we reported that exposure to benzo[a]pyrene (B[a]P), a common PAH, causes epigenetic and metabolic alterations in the initiation, promotion and progression of non-melanoma skin cancer (NMSC). As a follow-up investigation, this study examines how dietary triterpenoid ursolic acid (UA) regulates B[a]P-driven epigenetic and metabolic pathways in SKH-1 hairless mice. Our results show UA intercepts against B[a]P-induced tumorigenesis at different stages of NMSC. Epigenomic cytosines followed by guanine residues (CpG) methyl-seq data showed UA diminished B[a]P-mediated differentially methylated regions (DMRs) profiles. Transcriptomic RNA-seq revealed UA revoked B[a]P-induced differentially expressed genes (DEGs) of skin cancer-related genes, such as leucine-rich repeat LGI family member 2 (Lgi2) and kallikrein-related peptidase 13 (Klk13), indicating UA plays a vital role in B[a]P-mediated gene regulation and its potential consequences in NMSC interception. Association analysis of DEGs and DMRs found that the mRNA expression of KLK13 gene was correlated with the promoter CpG methylation status in the early-stage comparison group, indicating UA could regulate the KLK13 by modulating its promoter methylation at an early stage of NMSC. The metabolomic study showed UA alters B[a]P-regulated cancer-associated metabolisms like thiamin metabolism, ascorbate and aldarate metabolism during the initiation phase; pyruvate, citrate and thiamin metabolism during the promotion phase; and beta-alanine and pathothenate coenzyme A (CoA) biosynthesis during the late progression phase. Taken together, UA reverses B[a]P-driven epigenetic, transcriptomic and metabolic reprogramming, potentially contributing to the overall cancer interception against B[a]P-mediated NMSC.

Leptospiral imelysin (LIC_10713) is secretory, immunogenic and binds to laminin, fibronectin, and collagen IV

Leptospirosis is a widespread zoonotic disease caused by pathogenic Leptospira. Early and accurate diagnosis is the prime step in managing the disease. Secretory proteins of Leptospira remain distinguished for diagnosis due to their availability as soluble proteins in the serum and their interaction with the host immune response due to their extracellular presence. This study presents the cloning, expression, purification, and characterization of imelysin or LruB (LIC_10713), a putative leptospiral protein. We report that the localization of imelysin showed its presence in the inner membrane and in the culture supernatant. The imelysin was upregulated under in vitro physiological conditions of infection. The LIC_10713 interacted significantly with laminin, fibronectin, collagen type I, and collagen type IV in a dose-dependent manner. Phylogenetic analysis showed that LIC_10713 is predominately found in the pathogenic species of Leptospira, and the GxHxxE motif of imelysin-like proteins is represented as the amino acid sequence G_WH_AIE. Also, immunoglobulins in leptospirosis-infected patients recognize recombinant-LIC_10713 with 100% specificity and 90.9% sensitivity. The secretion nature, abundance, upregulation, binding to ECM components, and immunogenicity determine LIC_10713 as an important molecule that can be used as an anti-leptospirosis measure. KEY POINTS: • The imelysin-like protein (LIC_10713) of Leptospira is a secretory protein • The protein LIC_10713 can bind ECM molecules • The LIC_10713 is mainly found in pathogenic leptospires • The anti-LIC_10713 antibody from human serum can detect the r-LIC_10713.

Breast Cancer Prognostic Hub Genes Identified by Integrated Transcriptomic and Weighted Network Analysis: A Road Toward Personalized Medicine

Breast cancer (BC) is the second-most common type and among the leading causes of worldwide cancer-related deaths. There is marked person-to-person variability in susceptibility to, and phenotypic expression and prognosis of BC, a predicament that calls for personalized medicine and individually tailored therapeutics. In this study, we report new observations on prognostic hub genes and key pathways involved in BC. We used the data set GSE109169, comprising 25 pairs of BC and adjacent normal tissues. Using a high-throughput transcriptomic approach, we selected data on 293 differentially expressed genes to establish a weighted gene coexpression network. We identified three age-linked modules where the light-gray module strongly correlated with BC. Based on the gene significance and module membership features, peptidase inhibitor 15 (PI15) and KRT5 were identified as our hub genes from the light-gray module. These genes were further verified at transcriptional and translational levels across 25 pairs of BC and adjacent normal tissues. Their promoter methylation profiles were assessed based on various clinical parameters. In addition, these hub genes were used for Kaplan-Meier survival analysis, and their correlation with tumor-infiltrating immune cells was investigated. We found that PI15 and KRT5 may be potential biomarkers and potential drug targets. These findings call for future research in a larger sample size, which could inform diagnosis and clinical management of BC, thus paving the way toward personalized medicine.

Prediction of Adrenocortical Carcinoma Relapse and Prognosis with a Set of Novel Multigene Panels

Effective assessment of adrenocortical carcinoma (ACC) prognosis is critical in patient management. We report four novel and robust prognostic multigene panels. Sig27var25, SigIQvar8, SigCmbnvar5, and SigCmbn_B predict ACC relapse at area under the curve (AUC) of 0.89, 0.79, 0.78, and 0.80, respectively, and fatality at AUC of 0.91, 0.88, 0.85, and 0.87, respectively. Among their 33 component genes, 31 are novel. They could be differentially expressed in ACCs from normal tissues, tumors with different severity (stages and lymph node metastasis), ACCs with TP53 mutations, and tumors with differentially expressed immune checkpoints (CTLA4, PD1, TGFBR1, and others). All panels correlate with reductions of ACC-associated CD8+ and/or NK cells. Furthermore, we provide the first evidence for the association of mesenchymal stem cells (MSCs) with ACC relapse (p = 2 × 10−6) and prognosis (p = 2 × 10−8). Sig27var25, SigIQvar8, SigCmbnvar5, and SigCmbn_B correlate with MSC (spearman r ≥ 0.53, p ≤ 1.38 × 10−5). Sig27var25 and SigIQvar8 were derived from a prostate cancer (PC) and clear cell renal cell carcinoma (ccRCC) multigene signature, respectively; SigCmbnvar5 and SigCmbn_B are combinations of both panels, revealing close relationships of ACC with PC and ccRCC. The origin of these four panels from PC and ccRCC favors their prognostic potential towards ACC.

Gastric Cancer Pre-Stage Detection and Early Diagnosis of Gastritis Using Serum Protein Signatures

Background: A gastric cancer (GC) diagnosis relies on histopathology. Endoscopy rates are increasing. Helicobacter pylori infection is a major GC risk factor. In an effort to elucidate abundant blood biomarkers, and potentially reduce the number of diagnostic surgical interventions, we investigated sera and biopsies from a cohort of 219 H. pylori positive and negative patients diagnosed with GC, gastritis, and ulcers. This allowed the comparative investigation of the different gastroduodenal diseases, and the exclusion of protein changes resulting from bacterial infection or inflammation of the gastric mucosa when searching for GC-dependent proteins. Methods: High-definition mass spectrometry-based expression analysis of tryptically digested proteins was performed, followed by multivariate statistical and network analyses for the different disease groups, with respect to H. pylori infection status. Significantly regulated proteins differing more than two-fold between groups were shortlisted, and their role in gastritis and GC discussed. Results: We present data of comparative protein analyses of biopsies and sera from patients suffering from mild to advanced gastritis, ulcers, and early to advanced GC, in conjunction with a wealth of metadata, clinical information, histopathological evaluation, and H. pylori infection status. We used samples from pre-malignant stages to extract prospective serum markers for early-stage GC, and present a 29-protein marker panel containing, amongst others, integrin β-6 and glutathione peroxidase. Furthermore, ten serum markers specific for advanced GC, independent of H. pylori infection, are provided. They include CRP, protein S100A9, and kallistatin. The majority of these proteins were previously discussed in the context of cancer or GC. In addition, we detected hypoalbuminemia and increased fibrinogen serum levels in gastritis. Conclusion: Two protein panels were suggested for the development of multiplex tests for GC serum diagnostics. For most of the elements contained in these panels, individual commercial tests are available. Thus, we envision the design of multi-protein assays, incorporating several to all of the panel members, in order to gain a level of specificity that cannot be achieved by testing a single protein alone. As their development and validation will take time, gastritis diagnosis based on the fibrinogen to albumin serum ratio may be a quick way forward. Its determination at the primary/secondary care level for early diagnosis could significantly reduce the number of referrals to endoscopy. Preventive measures are in high demand. The protein marker panels presented in this work will contribute to improved GC diagnostics, once they have been transferred from a research result to a practical tool.

Integrated Analysis of miR-7-5p-Related ceRNA Network Reveals Potential Biomarkers for the Clinical Outcome of Gastric Cancer

Gastric cancer (GC) is the second leading cause of tumor-associated death and the fourth most commonly seen tumor across the world. Abnormal ncRNAs have been verified to be involved in potential metastasis via modulating epithelial-to-mesenchymal transition progression and are vital for the progression of cancers. Tumor-infiltrating immune cells (TICs) are a vital indicator of whether cancer patients will benefit from immunotherapy. Nonetheless, the association between ceRNAs and immune cells remained largely unclear. We used the ceRNA network combined with TICs for the prediction of the clinical outcome of GC patients based on TCGA datasets. The percentage of immunocytes in GC was speculated by the use of CIBERSORT. Via Lasso and multivariate assays, prognostic models were established applying survival-related genes and immune cells. Nomograms were developed, and the accuracy of the nomograms was determined using calibration curves. The association between ceRNAs and TICs was validated by the use of integration analysis. In this study, there were 2219 mRNAs (1308 increased and 911 decreased), 171 lncRNAs (51 decreased and 120 increased), and 123 miRNAs (55 decreased and 68 increased) differentially expressed between tumor groups and nontumor groups. Five lncRNAs, six miRNAs, and 64 mRNAs were used for ceRNA network construction. Eight genes including LOX, SPARC, MASTL, PI15, BMPR1B, ANKRD13B, PVT1, and miR-7-5p were applied for the development of the prognostic model. Survival assays suggested that tumor cases with high risk exhibited a shorter overall survival. In addition, we included T-cell CD4 memory activated, monocytes, and neutrophils for the development of a prognosis model. Eventually, our team demonstrated the possible associations between the ceRNA prognosis model and prognostic model based on immune cells. To sum up, the ceRNA network could be used for gene regulation and predict clinical outcomes of GC patients.

Diagnostic and Prognostic Significance of Keap1 mRNA Expression for Lung Cancer Based on Microarray and Clinical Information from Oncomine Database

We performed a bioinformatics analysis with validation by multiple databases, aiming to evaluate the diagnostic and prognostic value of Kelch-like ECH-associated protein 1 (Keap1) mRNA for lung cancer, and to explore possible mechanisms. Diagnostic performance of Keap1 mRNA was determined by receiver operating characteristic (ROC) curve analysis. Prognostic implication of Keap1 mRNA was estimated by Kaplan-Meier survival analysis. Co-expressed genes with both Keap1 and Nfe2L2 were identified by LinkedOmics. Mechanisms of Keap1-Nfe2L2-co-expressed genes underlying the pathogenesis of lung cancer were explored by function enrichment and pathway analysis. The ROC curve analysis determined a good diagnostic performance of Keap1 mRNA for lung squamous cell carcinoma (LUSC), with an area under the ROC curve (AUC) of 0.833, sensitivity of 72.7%, and specificity of 90.6% (P<0.001). Multivariate Cox regression recognized high Keap1 mRNA to be an independent risk factor of mortality for overall lung cancer [hazard ratio (HR): 11.034, P=0.044], but an independent antagonistic factor for lung adenocarcinoma (LUAD) (HR: 0.404, P<0.001). Validation by UALCAN and GEPIA supported Oncomine findings regarding the diagnostic value of Keap1 mRNA for LUSC, but denied its prognostic value. After screening, we identified 17 co-expressed genes with both Keap1 and Nfe2L2 for LUAD, and 22 for LUSC, mainly enriched in signaling pathway of oxidative stress-induced gene expression via Nrf2. In conclusion, Keap1 mRNA has a good diagnostic performance, but controversial prognostic efficacy for LUSC. The pathogenesis of lung cancer is associated with Keap1-Nfe2L2-co-expressed genes by signaling pathway of oxidative stress-induced gene expression via Nrf2.

Screening and Identification of Key Common and Specific Genes and Their Prognostic Roles in Different Molecular Subtypes of Breast Cancer

Breast cancer is one of the most common cancers. Although the present molecular classification improves the treatment effect and prognosis of breast cancer, the heterogeneity of the molecular subtype remains very complex, and the applicability and effectiveness of treatment methods are still limited leading to poorer patient prognosis than expected. Further identification of more refined molecular typing based on gene expression profile will yield better understanding of the heterogeneity, improving treatment effects and prolonging prognosis of patients. Here, we downloaded the mRNA expression profiles and corresponding clinical data of patients with breast cancer from public databases and performed typical molecular typing using PAM50 (Prediction Analysis of Microarray 50) method. Comparative analyses were performed to screen the common and specific differentially expressed genes (DEGs) between cancer and corresponding para-cancerous tissues in each breast cancer subtype. The GO and KEGG analyses of the DEGs were performed to enrich the common and specific functional progress and signaling pathway involved in breast cancer subtypes. A total of 38 key common and specific DEGs were identified and selected based on the validated results, GO/KEGG enrichments, and the priority of expression, including four common DEGs and 34 specific DEGs in different subtypes. The prognostic value of these key common and specific DEGs was further analyzed to obtain useful potential markers in clinic. Finally, the potential roles and the specific prognostic values of the common and specific DEGs were speculated and summarized in total breast cancer and different subtype breast cancer based on the results of these analyses. The findings of our study provide the basis of more refined molecular typing of breast cancer, potential new therapeutic targets and prognostic markers for different breast cancer subtypes

Effective Prediction of Prostate Cancer Recurrence through the IQGAP1 Network

IQGAP1 expression was analyzed in: (1) primary prostate cancer, (2) xenografts produced from LNCaP, DU145, and PC3 cells, 3) tumor of PTEN-/- and TRAMP mice, and (3) castration resistant PC (CRPC) produced by LNCaP xenografts and PTEN-/- mice. IQGAP1 downregulations occurred in CRPC and advanced PCs. The downregulations were associated with rapid PC recurrence in the TCGA PanCancer (n = 492, p = 0.01) and MSKCC (n = 140, p = 4 × 10-6) cohorts. Differentially expressed genes (n = 598) relative to IQGAP1 downregulation were identified with enrichment in chemotaxis, cytokine signaling, and others along with reductions in immune responses. A novel 27-gene signature (Sig27gene) was constructed from these DEGs through random division of the TCGA cohort into a Training and Testing population. The panel was validated using an independent MSKCC cohort. Sig27gene robustly predicts PC recurrence at (hazard ratio) HR 2.72 and p < 2 × 10-16 in two independent PC cohorts. The prediction remains significant after adjusting for multiple clinical features. The novel and robust nature of Sig27gene underlie its great translational potential as a prognostic biomarker to predict PC relapse risk in patients with primary PC.

Investigation of the miRNA and mRNA Coexpression Network and Their Prognostic Value in Hepatocellular Carcinoma

Purpose

To identify pivotal differentially expressed miRNAs and genes and construct their regulatory network in hepatocellular carcinoma.

Methods

mRNA (GSE101728) and microRNA (GSE108724) microarray datasets were obtained from the NCBI Gene Expression Omnibus (GEO) database. Then, we identified the differentially expressed miRNAs and mRNAs. Sequentially, transcription factor enrichment and gene ontology (GO) enrichment analysis for miRNA were performed. Target genes of these differential miRNAs were obtained using packages in R language (R package multiMiR). After that, downregulated miRNAs were matched with target mRNAs which were upregulated, while upregulated miRNAs were paired with downregulated target mRNA using scripts written in Perl. An miRNA-mRNA network was constructed and visualized in Cytoscape software. For miRNAs in the network, survival analysis was performed. And for genes in the network, we did gene ontology (GO) and KEGG pathway enrichment analysis.

Results

A total of 35 miRNAs and 295 mRNAs were involved in the network. These differential genes were enriched in positive regulation of cell-cell adhesion, positive regulation of leukocyte cell-cell adhesion, and so on. Eight differentially expressed miRNAs were found to be associated with the OS of patients with HCC. Among which, miR-425 and miR-324 were upregulated while the other six, including miR-99a, miR-100, miR-125b, miR-145, miR-150, and miR-338, were downregulated.

Conclusion

In conclusion, these results can provide a potential research direction for further studies about the mechanisms of how miRNA affects malignant behavior in hepatocellular carcinoma.