Global profiling of the signaling network of papillary thyroid carcinoma

Protein Kinase C (PKC) Isozymes as Diagnostic and Prognostic Biomarkers and Therapeutic Targets for Cancer

Protein kinase C (PKC) is a large family of calcium- and phospholipid-dependent serine/threonine kinases that consists of at least 11 isozymes. Based on their structural characteristics and mode of activation, the PKC family is classified into three subfamilies: conventional or classic (cPKCs; α, βI, βII, and γ), novel or non-classic (nPKCs; δ, ε, η, and θ), and atypical (aPKCs; ζ, ι, and λ) (PKCλ is the mouse homolog of PKCι) PKC isozymes. PKC isozymes play important roles in proliferation, differentiation, survival, migration, invasion, apoptosis, and anticancer drug resistance in cancer cells. Several studies have shown a positive relationship between PKC isozymes and poor disease-free survival, poor survival following anticancer drug treatment, and increased recurrence. Furthermore, a higher level of PKC activation has been reported in cancer tissues compared to that in normal tissues. These data suggest that PKC isozymes represent potential diagnostic and prognostic biomarkers and therapeutic targets for cancer. This review summarizes the current knowledge and discusses the potential of PKC isozymes as biomarkers in the diagnosis, prognosis, and treatment of cancers.

High-throughput proteomics: a methodological mini-review

Proteomics plays a vital role in biomedical research in the post-genomic era. With the technological revolution and emerging computational and statistic models, proteomic methodology has evolved rapidly in the past decade and shed light on solving complicated biomedical problems. Here, we summarize scientific research and clinical practice of existing and emerging high-throughput proteomics approaches, including mass spectrometry, protein pathway array, next-generation tissue microarrays, single-cell proteomics, single-molecule proteomics, Luminex, Simoa and Olink Proteomics. We also discuss important computational methods and statistical algorithms that can maximize the mining of proteomic data with clinical and/or other 'omics data. Various principles and precautions are provided for better utilization of these tools. In summary, the advances in high-throughput proteomics will not only help better understand the molecular mechanisms of pathogenesis, but also to identify the signature signaling networks of specific diseases. Thus, modern proteomics have a range of potential applications in basic research, prognostic oncology, precision medicine, and drug discovery.

LncRNA LUCAT1 as a novel prognostic biomarker for patients with papillary thyroid cancer

In recent years, long non-coding RNAs have emerged as a novel class of regulators of cancer biological processes. While they are dysregulated in many cancer types, little is known about their expression and functional profiles. This study has been focused on the determination of the role of a specific lncRNA in papillary thyroid cancer. Quantitative reverse transcription PCR was performed to detect the expression levels of 84 lncRNAs in 61 papillary thyroid carcinoma tissues and their adjacent non-tumor tissues. The highest fold-change was obtained for lung cancer associated transcript 1 LUCAT1, and thus, this study determines the expression and biological implication of lncRNA LUCAT1 through different in vitro and ex vivo approaches in this tumor. LUCAT1 was specifically located at the cell nucleus in tumoral regions of patient tissues. Furthermore, LUCAT1 knockdown significantly reduced both cell proliferation and invasion ex vivo and induced cell-cycle arrest and apoptosis. These facts were corroborated by an enhanced expression of P21, P57, P53 and BAX, and a reduced expression of EZH2 and HDAC1. In addition, a significant decrease was observed on DNMT1 and NRF2 genes, helping to clarify the role of LUCAT1 on PTC. Our study reveals the involvement of LUCAT1 in PTC development, through acting in cell-cycle regulation, proliferation, epigenetic modifications through LUCAT1/ CDK1/ EZH2/ P57/ P21/ HDAC1/ DNMT1/ P53/ BAX axis and apoptosis, via extrinsic pathway activating caspases. These findings indicate that LUCAT1 is maybe a potential therapeutic target and molecular biomarker for PTC.

Decreased apolipoprotein A4 and increased complement component 3 as potential markers for papillary thyroid carcinoma: A proteomic study

BACKGROUND:

Thyroid carcinomas have comprised the fastest rising incidence of cancer in the past decade. Currently, the diagnosis of thyroid tumors is performed by the fine-needle aspiration biopsy (FNAB) method, which still holds some challenges and limitations, mostly in discriminating malignant and benign lesions. Therefore, the development of molecular markers to distinguish between these lesion types are in progress.

METHODS:

A 2D-PAGE separation of proteins was performed followed by tandem mass spectrometry with the aim of discovering potential serum protein markers for papillary thyroid carcinoma and multinodular goiter. Protein-protein interaction network analysis revealed the most important pathways involved in the progression of papillary thyroid cancer. The enzyme-linked immunosorbent assay method was used to confirm a part of the results.

RESULTS:

The significantly altered proteins included C3, C4A, GC, HP, TTR, APOA4, APOH, ORM2, KRT10, AHSG, IGKV3-20, and IGKC. We also confirmed that increased complement component 3 and decreased apolipoprotein A4 occurred in papillary thyroid cancer. Network investigations demonstrated that complement activation cascades and PPAR signaling might play a role in the pathogenesis of thyroid cancer.

CONCLUSION:

The results demonstrated that serum proteomics could serve as a viable method for proposing novel potential markers for thyroid tumors. Surely, further research must be performed in larger cohorts to validate the results.