Evaluation of the prognostic significances of γ-secretase genes in pancreatic cancer

The critical role of γ-secretase and its inhibitors in cancer and cancer therapeutics

As a multi-substrate transmembrane protease, γ-secretase exists widely in various cells. It controls multiple important cellular activities through substrate cleavage. γ-secretase inhibitors (GSIs) play a role in cancer inhibition by blocking Notch cleavage, and are considered as potential therapeutic strategies for cancer. Currently, GSIs have encouraging performance in preclinical models, yet this success does not translate well in clinical trials. In recent years, a number of breakthrough discoveries have shown us the promise of targeting γ-secretase for the treatment of cancer. Here, we integrate a large amount of data from γ-secretase and its inhibitors and cancer in nearly 30 years, comb and discuss the close connection between γ-secretase and cancer, as well as the potential and problems of current GSIs in cancer treatment. We analyze the possible reasons for the failure performance of current GSIs in clinical trials, and make recommendations for future research areas.

Notch signaling pathway: a comprehensive prognostic and gene expression profile analysis in breast cancer

Breast cancer is a complex disease exhibiting a great degree of heterogeneity due to different molecular subtypes. Notch signaling regulates the differentiation of breast epithelial cells during normal development and plays a crucial role in breast cancer progression through the abnormal expression of the Notch up-and down-stream effectors. To date, there are only a few patient-centered clinical studies using datasets characterizing the role of Notch signaling pathway regulators in breast cancer; thus, we investigate the role and functionality of these factors in different subtypes using publicly available databases containing records from large studies. High-throughput genomic data and clinical information extracted from TCGA were analyzed. We performed Kaplan-Meier survival and differential gene expression analyses using the HALLMARK_NOTCH_SIGNALING gene set. To determine if epigenetic regulation of the Notch regulators contributes to their expression, we analyzed methylation levels of these factors using the TCGA HumanMethylation450 Array data. Notch receptors and ligands expression is generally associated with the tumor subtype, grade, and stage. Furthermore, we showed gene expression levels of most Notch factors were associated with DNA methylation rate. Modulating the expression levels of Notch receptors and effectors can be a potential therapeutic approach for breast cancer. As we outline herein, elucidating the novel prognostic and regulatory roles of Notch implicate this pathway as an essential mediator controlling breast cancer progression.

The Role of ANGPTL Gene Family Members in Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is highly aggressive with a poor prognosis and survival rate. Certain ANGPTL members have been implicated in tumor progression. However, the relevance of the ANGPTL gene family to HCC remains poorly understood. In this study, we explored the role of ANGPTLs in the prognosis of HCC.

Methods

From the CCLE database, we studied the expression of ANGPTLs in a range of cancer cell lines. The UCSC, HCCDB, and Human Protein Atlas databases were used to analyze the differences in mRNA and protein expression of ANGPTLs in HCC tissues. Additionally, the correlation between ANGPTL mRNA and methylation levels and clinicopathological features were assessed in the TCGA database. The correlation between ANGPTL mRNA and overall survival was determined by the Kaplan-Meier plotter. cBioPortal database was used to analyze ANGPTL genomic alterations. Genes associated with ANGPTLs were determined by enrichment with KEGG. Moreover, the differentially expressed genes of ANGPTLs were analyzed by the LinkedOmics database, and the KEGG pathway and miRNA targets of ANGPTLs were also enriched.

Results

There was a significant correlation between the ANGPTL members (excluding ANGPTL2) and the prognosis of HCC patients according to the Kaplan-Meier plotter analysis (p < 0.05). ANGPTL1 was the gene with the highest mutation frequency. ANGPTLs are involved in certain pathways that may influence the development of HCC.

Conclusion

In summary, the expression of some members of ANGPTLs was significantly correlated with HCC prognosis, suggesting that the ANGPTL gene family members may be promising molecular markers for HCC treatment and prognosis.

A Data Science Approach for the Identification of Molecular Signatures of Aggressive Cancers

The main hallmarks of cancer include sustaining proliferative signaling and resisting cell death. We analyzed the genes of the WNT pathway and seven cross-linked pathways that may explain the differences in aggressiveness among cancer types. We divided six cancer types (liver, lung, stomach, kidney, prostate, and thyroid) into classes of high (H) and low (L) aggressiveness considering the TCGA data, and their correlations between Shannon entropy and 5-year overall survival (OS). Then, we used principal component analysis (PCA), a random forest classifier (RFC), and protein-protein interactions (PPI) to find the genes that correlated with aggressiveness. Using PCA, we found GRB2, CTNNB1, SKP1, CSNK2A1, PRKDC, HDAC1, YWHAZ, YWHAB, and PSMD2. Except for PSMD2, the RFC analysis showed a different list, which was CAD, PSMD14, APH1A, PSMD2, SHC1, TMEFF2, PSMD11, H2AFZ, PSMB5, and NOTCH1. Both methods use different algorithmic approaches and have different purposes, which explains the discrepancy between the two gene lists. The key genes of aggressiveness found by PCA were those that maximized the separation of H and L classes according to its third component, which represented 19% of the total variance. By contrast, RFC classified whether the RNA-seq of a tumor sample was of the H or L type. Interestingly, PPIs showed that the genes of PCA and RFC lists were connected neighbors in the PPI signaling network of WNT and cross-linked pathways.

Nicastrin-Like, a Novel Transmembrane Protein from Trypanosoma cruzi Associated to the Flagellar Pocket

Nicastrin (NICT) is a transmembrane protein physically associated with the polytypical aspartyl protease presenilin that plays a vital role in the correct localization and stabilization of presenilin to the membrane-bound γ-secretase complex. This complex is involved in the regulation of a wide range of cellular events, including cell signaling and the regulation of endocytosed membrane proteins for their trafficking and protein processing. Methods: In Trypanosoma cruzi, the causal agent of the Chagas disease, a NICT-like protein (Tc/NICT) was identified with a short C-terminus orthologous to the human protein, a large ectodomain (ECD) with numerous glycosylation sites and a single-core transmembrane domain containing a putative TM-domain (457GSVGA461) important for the γ-secretase complex activity. Results: Using the Spot-synthesis strategy with Chagasic patient sera, five extracellular epitopes were identified and synthetic forms were used to generate rabbit anti-Tc/NICT polyclonal serum that recognized a ~72-kDa molecule in immunoblots of T. cruzi epimastigote extracts. Confocal microscopy suggests that Tc/NICT is localized in the flagellar pocket, which is consistent with data from our previous studies with a T. cruzi presenilin-like protein. Phylogenetically, Tc/NICT was localized within a subgroup with the T. rangeli protein that is clearly detached from the other Trypanosomatidae, such as T. brucei. These results, together with a comparative analysis of the selected peptide sequence regions between the T. cruzi and mammalian proteins, suggest a divergence from the human NICT that might be relevant to Chagas disease pathology. As a whole, our data show that a NICT-like protein is expressed in the infective and replicative stages of T. cruzi and may be considered further evidence for a γ-secretase complex in trypanosomatids.

Gamma Secretase Inhibitors in Cancer: A Current Perspective on Clinical Performance

Gamma secretase inhibitors (GSIs), initially developed as Alzheimer's therapies, have been repurposed as anticancer agents given their inhibition of Notch receptor cleavage. The success of GSIs in preclinical models has been ascribed to induction of cancer stem-like cell differentiation and apoptosis, while also impairing epithelial-to-mesenchymal transition and sensitizing cells to traditional chemoradiotherapies. The promise of these agents has yet to be realized in the clinic, however, as GSIs have failed to demonstrate clinical benefit in most solid tumors with the notable exceptions of CNS malignancies and desmoid tumors. Disappointing clinical performance to date reflects important questions that remain to be answered. For example, what is the net impact of these agents on antitumor immune responses, and will they require concurrent targeting of tumor-intrinsic compensatory pathways? Addressing these limitations in our current understanding of GSI mechanisms will undoubtedly facilitate their rational incorporation into combinatorial strategies and provide a valuable tool with which to combat Notch-dependent cancers. In the present review, we provide a current understanding of GSI mechanisms, discuss clinical performance to date, and suggest areas for future investigation that might maximize the utility of these agents. IMPLICATIONS FOR PRACTICE: The performance of gamma secretase inhibitors (GSIs) in clinical trials generally has not reflected their encouraging performance in preclinical studies. This review provides a current perspective on the clinical performance of GSIs across various solid tumor types alongside putative mechanisms of antitumor activity. Through exploration of outstanding gaps in knowledge as well as reasons for success in certain cancer types, the authors identify areas for future investigation that will likely enable incorporation of GSIs into rational combinatorial strategies for superior tumor control and patient outcomes.