Differences in gene expression profiles and carcinogenesis pathways involved in cisplatin resistance of four types of cancer

The role of PLCγ2 in immunological disorders, cancer, and neurodegeneration

Phosphatidylinositol-specific phospholipase Cγ2 (PLCγ2) is a critical signaling molecule activated downstream from a variety of cell surface receptors that contain an intracellular immunoreceptor tyrosine-based activation motif. These receptors recruit kinases such as Syk, BTK, and BLNK to phosphorylate and activate PLCγ2, which then generates 1D-myo-inositol 1,4,5-trisphosphate and diacylglycerol. These well-known second messengers are required for diverse membrane functionality including cellular proliferation, endocytosis, and calcium flux. As a result, PLCγ2 dysfunction is associated with a variety of diseases including cancer, neurodegeneration, and immune disorders. The diverse pathologies associated with PLCγ2 are exemplified by distinct genetic variants. Inherited mutations at this locus cause PLCγ2-associated antibody deficiency and immune dysregulation, in some cases with autoinflammation. Acquired mutations at this locus, which often arise as a result of BTK inhibition to treat chronic lymphocytic leukemia, result in constitutive downstream signaling and lymphocyte proliferation. Finally, a third group of PLCγ2 variants actually has a protective effect in a variety of neurodegenerative disorders, presumably by increased uptake and degradation of deleterious neurological aggregates. Therefore, manipulating PLCγ2 activity either up or down could have therapeutic benefit; however, we require a better understanding of the signaling pathways propagated by these variants before such clinical utility can be realized. Here, we review the signaling roles of PLCγ2 in hematopoietic cells to help understand the effect of mutations driving immune disorders and cancer and extrapolate from this to roles which may relate to protection against neurodegeneration.

Advanced bioinformatic analysis and pathway prediction of NSCLC cells upon cisplatin resistance

This study aims to identify pathway involvement in the development of cisplatin (cis-diamminedichloroplatinum (II); CDDP) resistance in A549 lung cancer (LC) cells by utilizing advanced bioinformatics software. We developed CDDP-resistant A549 (A549/DDP) cells through prolonged incubation with the drug and performed RNA-seq on RNA extracts to determine differential mRNA and miRNA expression between A549/DDP and A549 cells. We analyzed the gene dysregulation with Ingenuity Pathway Analysis (IPA; QIAGEN) software. In contrast to prior research, which relied on the clustering of dysregulated genes to pathways as an indication of pathway activity, we utilized the IPA software for the dynamic evaluation of pathway activity depending on the gene dysregulation levels. We predicted 15 pathways significantly contributing to the chemoresistance, with several of them to have not been previously reported or analyzed in detail. Among them, the PKR signaling, cholesterol biosynthesis, and TEC signaling pathways are included, as well as genes, such as PIK3R3, miR-34c-5p, and MDM2, among others. We also provide a preliminary analysis of SNPs and indels, present exclusively in A549/DDP cells. This study's results provide novel potential mechanisms and molecular targets that can be explored in future studies and assist in improving the understanding of the chemoresistance phenotype.

Bioinformatics-based identification of potential microRNA biomarkers in frequent and non-frequent exacerbators of COPD

Objectives

MicroRNAs (miRNAs) play essential roles in the development of COPD. In this study, we aimed to identify and validate potential miRNA biomarkers in frequent and non-frequent exacerbators of COPD patients using bioinformatic analysis.

Materials and methods

The candidate miRNA biomarkers in COPD were screened from Gene Expression Omnibus (GEO) dataset and identified using GEO2R online tool. Then, we performed bioinformatic analyses including target prediction, gene ontology (GO), pathway enrichment analysis and construction of protein–protein interaction (PPI) network. Furthermore, the expression of the identified miRNAs in peripheral blood monocular cells (PBMCs) of COPD patients was validated using quantitative real-time polymerase chain reaction (qRT-PCR).

Results

MiR-23a, miR-25, miR-145 and miR-224 were identified to be significantly downregulated in COPD patients compared with healthy controls. GO analysis showed the four miRNAs involved in apoptotic, cell differentiation, cell proliferation and innate immune response. Pathway analysis showed that the targets of these miRNAs were associated with p53, TGF-β, Wnt, VEGF and MAPK signal pathway. In healthy controls, the miR-25 and miR-224 levels were significantly decreased in smokers compared with nonsmokers (P<0.001 and P<0.05, respectively). In COPD patients, the levels of miR-23a, miR-25, miR-145 and miR-224 were associated with Global Initiative for Chronic Obstructive Lung Disease (GOLD) stages. Notably, miR-23a and miR-145 were significantly elevated in non-frequent exacerbators compared with frequent exacerbators (P<0.05), and miR-23a showed higher area under the receiver–operator characteristic curve (AUROC) than miR-145 (0.707 vs 0.665, P<0.05).

Conclusion

MiR-23a, miR-25, miR-145 and miR-224 were associated with the development of COPD, and miR-23a might be a potential biomarker for discriminating the frequent exacerbators from non-frequent exacerbators.

Key Players of Cisplatin Resistance: Towards a Systems Pharmacology Approach

The major obstacle in the clinical use of the antitumor drug cisplatin is inherent and acquired resistance. Typically, cisplatin resistance is not restricted to a single mechanism demanding for a systems pharmacology approach to understand a whole cell's reaction to the drug. In this study, the cellular transcriptome of untreated and cisplatin-treated A549 non-small cell lung cancer cells and their cisplatin-resistant sub-line A549^rCDDP²⁰⁰⁰ was screened with a whole genome array for relevant gene candidates. By combining statistical methods with available gene annotations and without a previously defined hypothesis HRas, MAPK14 (p38), CCL2, DOK1 and PTK2B were identified as genes possibly relevant for cisplatin resistance. These and related genes were further validated on transcriptome (qRT-PCR) and proteome (Western blot) level to select candidates contributing to resistance. HRas, p38, CCL2, DOK1, PTK2B and JNK3 were integrated into a model of resistance-associated signalling alterations describing differential gene and protein expression between cisplatin-sensitive and -resistant cells in reaction to cisplatin exposure.

Gene expression correlation for cancer diagnosis: a pilot study

Poor prognosis for late-stage, high-grade, and recurrent cancers has been motivating cancer researchers to search for more efficient biomarkers to identify the onset of cancer. Recent advances in constructing and dynamically analyzing biomolecular networks for different types of cancer have provided a promising novel strategy to detect tumorigenesis and metastasis. The observation of different biomolecular networks associated with normal and cancerous states led us to hypothesize that correlations for gene expressions could serve as valid indicators of early cancer development. In this pilot study, we tested our hypothesis by examining whether the mRNA expressions of three randomly selected cancer-related genes PIK3C3, PIM3, and PTEN were correlated during cancer progression and the correlation coefficients could be used for cancer diagnosis. Strong correlations (0.68 ≤ r ≤ 1.0) were observed between PIK3C3 and PIM3 in breast cancer, between PIK3C3 and PTEN in breast and ovary cancers, and between PIM3 and PTEN in breast, kidney, liver, and thyroid cancers during disease progression, implicating that the correlations for cancer network gene expressions could serve as a supplement to current clinical biomarkers, such as cancer antigens, for early cancer diagnosis.