Malignancy of Cancers and Synthetic Lethal Interactions Associated With Mutations of Cancer Driver Genes

In Silico Pleiotropy Analysis in KEGG Signaling Networks Using a Boolean Network Model

Pleiotropy, which refers to the ability of different mutations on the same gene to cause different pathological effects in human genetic diseases, is important in understanding system-level biological diseases. Although some biological experiments have been proposed, still little is known about pleiotropy on gene–gene dynamics, since most previous studies have been based on correlation analysis. Therefore, a new perspective is needed to investigate pleiotropy in terms of gene–gene dynamical characteristics. To quantify pleiotropy in terms of network dynamics, we propose a measure called in silico Pleiotropic Scores (sPS), which represents how much a gene is affected against a pair of different types of mutations on a Boolean network model. We found that our model can identify more candidate pleiotropic genes that are not known to be pleiotropic than the experimental database. In addition, we found that many types of functionally important genes tend to have higher sPS values than other genes; in other words, they are more pleiotropic. We investigated the relations of sPS with the structural properties in the signaling network and found that there are highly positive relations to degree, feedback loops, and centrality measures. This implies that the structural characteristics are principles to identify new pleiotropic genes. Finally, we found some biological evidence showing that sPS analysis is relevant to the real pleiotropic data and can be considered a novel candidate for pleiotropic gene research. Taken together, our results can be used to understand the dynamics pleiotropic characteristics in complex biological systems in terms of gene–phenotype relations.

Development of Metabolic Synthetic Lethality and Its Implications for Thyroid Cancer

Cancer therapies targeting genetic alterations are a topic of great interest in the field of thyroid cancer, which frequently harbors mutations in the RAS, RAF, and RET genes. Unfortunately, U.S. Food and Drug Administration-approved BRAF inhibitors have relatively low therapeutic efficacy against BRAF-mutant thyroid cancer; in addition, the cancer often acquires drug resistance, which prevents effective treatment. Recent advances in genomics and transcriptomics are leading to a more complete picture of the range of mutations, both driver and messenger, present in thyroid cancer. Furthermore, our understanding of cancer suggests that oncogenic mutations drive tumorigenesis and induce rewiring of cancer cell metabolism, which promotes survival of mutated cells. Synthetic lethality (SL) is a method of neutralizing mutated genes that were previously considered untargetable by traditional genotype-targeted treatments. Because these metabolic events are specific to cancer cells, we have the opportunity to develop new therapies that target tumor cells specifically without affecting healthy tissue. Here, we describe developments in metabolism-based cancer therapy, focusing on the concept of metabolic SL in thyroid cancer. Finally, we discuss the essential implications of metabolic reprogramming and its role in the future direction of SL for thyroid cancer.

Expression of the CLCA4 Gene in Esophageal Carcinoma and Its Impact on the Biologic Function of Esophageal Carcinoma Cells

Background

Esophageal carcinoma (ESCA) is one of the malignant tumors with a high mortality rate worldwide, which seriously affects people's health. Calcium-activated chloride channel 4 (CLCA4) was reported to be a tumor inhibitor in hepatocellular carcinoma. Nevertheless, the role of CLCA4 in ESCA is still unclear.

Methods

RT-qPCR and western blot assay were used to test the expression pattern of CLCA4 in ESCA tissues and cells. CCK-8 assay was performed to detect the effect of CLCA4 overexpression on cell proliferation in ESCA cells. Transwell assay was used to measure the effect of CLCA4 upregulation on migration and invasion abilities of ESCA cells. Animal experiments were conducted to investigate the role of CLCA4 upregulation in tumor growth in vivo.

Results

CLCA4 was significantly reduced in ESCA tissues and correlated with T stage, differentiation, and lymph node metastasis. CLCA4 overexpression was found to inhibit cell proliferation, migration, invasion, and EMT progression in ESCA cells. Moreover, CLCA4 overexpression suppressed tumor growth in vivo.

Conclusion

CLCA4 was suggested to act as a tumor inhibitor in ESCA and might be a therapeutic target gene for the treatment of patients with ESCA.

Genetic Abnormalities in Multiple Myeloma: Prognostic and Therapeutic Implications

Some genetic abnormalities of multiple myeloma (MM) detected more than two decades ago remain major prognostic factors. In recent years, the introduction of cutting-edge genomic methodologies has enabled the extensive deciphering of genomic events in MM. Although none of the alterations newly discovered have significantly improved the stratification of the outcome of patients with MM, some of them, point mutations in particular, are promising targets for the development of personalized medicine. This review summarizes the main genetic abnormalities described in MM together with their prognostic impact, and the therapeutic approaches potentially aimed at abrogating the undesirable pathogenic effect of each alteration.

Data on arsenic trioxide modulates Treg/Th17/Th1/Th2 cells in treatment-naïve rheumatoid arthritis patients and collagen-induced arthritis model mice

In this article, we share the raw protein and mRNA data obtained from basal and stimulated human peripheral blood mononuclear cells (PBMCs) derived from 15 individual treatment-naïve rheumatoid arthritis (RA) patients and synovial fluid mononuclear cells (SFMCs). In treatment-naïve RA patients, PBMCs were treated with a gradient of concentrations of As₂O₃ (0, 0.1, 0.5, 1.0, 2.0, 4.0 μM) for 48 hours. We found that 2.0 μM As₂O₃ promoted the apoptosis of PBMCs significantly, and 0.5 μM As₂O₃ was the lowest and effective concentration that contributed to Treg cell generation but it prevented Th17 cell differentiation, as assessed by flow cytometry. Furthermore, As₂O₃ decreased the transcription factor STAT3 mRNA expression of Th17 cells but increased the transcription factor Foxp3 of Treg cells. In synovial fluid from RA patients, consistent with PBMCs, As₂O₃ inhibited Th17 cell differentiation but promoted Treg cell generation. In an animal experiment, we analyzed the body-weight of mice as the indicator of As₂O₃ toxicity and calculated the spleen index. As₂O₃ significantly decreased the hematoxylin and eosin score in Type II collagen-induced arthritis in mice. Furthermore, As₂O₃ downregulated the frequency of Th1 but upregulated Th2 cells. For more insight please see Arsenic trioxide improves Treg and Th17 balance by modulating STAT3 in treatment-naive rheumatoid arthritis patients [1].

Arsenic Trioxide in Synergy with Vitamin D Rescues the Defective VDR-PPAR-γ Functional Module of Autophagy in Rheumatoid Arthritis

Dysregulated autophagy leads to autoimmune diseases including rheumatoid arthritis (RA). Arsenic trioxide (ATO) is a single agent used for the treatment of acute promyelocytic leukemia and is highly promising for other malignancies but is also attractive for RA, although its relationship with autophagy remains to be further clarified and its application optimized. For the first time, we report a defective functional module of autophagy comprising the Vitamin D receptor (VDR), PPAR-γ, microtubule-associated protein 1 light-chain 3 (LC3), and p62 which appears in RA synovial fibroblasts. ATO alleviated RA symptoms by boosting effective autophagic flux through significantly downregulating p62, the inflammation and catabolism protein. Importantly, low-dose ATO synergizes with Vitamin D in RA treatment.

Conceptual frameworks of synthetic lethality in clear cell carcinoma of the ovary

Targeting non-oncogenes may result in the selective death of cancer cells. Clear cell carcinoma of the ovary (CCC) may exhibit resistance against conventional chemotherapy and is associated with poor prognosis. The aim of the present report was to review synthetic lethality-based therapies for CCC. Previous English-language studies were reviewed to accumulate preclinical and clinical data on targeting synthetic lethal partners. Synthetic lethal interactions have a variety of types, involving components of a backup or parallel pathway with overlapping functions, components encoded by paralogous pairs, subunit components that form heteromeric complexes and components that are arranged in a single linear pathway. A set of candidate gene targets potentially resulting in synthetic lethality have been previously identified. HNF class homeobox, AT-rich interaction domain 1A, ATR serine/threonine kinase, ATM serine/threonine kinase, checkpoint kinase 1 and phosphatase and tensin homolog may be the key partner genes. A variety of loss of function genes in CCC are driver or passenger events and may function as synthetic lethal pairs under replication stress conditions. Further clinical studies will be required to investigate the safety and therapeutic effect of synthetic lethality pairs in CCC tumor types with replication stress.

TP53 mutations, expression and interaction networks in human cancers

Although the associations of p53 dysfunction, p53 interaction networks and oncogenesis have been widely explored, a systematic analysis of TP53 mutations and its related interaction networks in various types of human cancers is lacking. Our study explored the associations of TP53 mutations, gene expression, clinical outcomes, and TP53 interaction networks across 33 cancer types using data from The Cancer Genome Atlas (TCGA). We show that TP53 is the most frequently mutated gene in a number of cancers, and its mutations appear to be early events in cancer initiation. We identified genes potentially repressed by p53, and genes whose expression correlates significantly with TP53 expression. These gene products may be especially important nodes in p53 interaction networks in human cancers. This study shows that while TP53-truncating mutations often result in decreased TP53 expression, other non-truncating TP53 mutations result in increased TP53 expression in some cancers. Survival analyses in a number of cancers show that patients with TP53 mutations are more likely to have worse prognoses than TP53-wildtype patients, and that elevated TP53 expression often leads to poor clinical outcomes. We identified a set of candidate synthetic lethal (SL) genes for TP53, and validated some of these SL interactions using data from the Cancer Cell Line Project. These predicted SL genes are promising candidates for experimental validation and the development of personalized therapeutics for patients with TP53-mutated cancers.

Synthetic lethality: emerging targets and opportunities in melanoma

Great progress has been made in the treatment of melanoma through use of targeted therapies and immunotherapy. One approach that has not been fully explored is synthetic lethality, which exploits somatically acquired changes, usually driver mutations, to specifically kill tumour cells. We outline the various approaches that may be applied to identify synthetic lethal interactions and define how these interactions may drive drug discovery efforts.