Bioinformatic analysis of the four transcription factors used to induce pluripotent stem cells

Application of the Yamanaka Transcription Factors Oct4, Sox2, Klf4, and c-Myc from the Laboratory to the Clinic

The transcription factors Oct4, Sox2, Klf4, and c-Myc enable the reprogramming of somatic cells into induced pluripotent cells. Reprogramming generates newly differentiated cells for potential therapies in cancer, neurodegenerative diseases, and rejuvenation processes. In cancer therapies, these transcription factors lead to a reduction in the size and aggressiveness of certain tumors, such as sarcomas, and in neurodegenerative diseases, they enable the production of dopaminergic cells in Parkinson's disease, the replacement of affected neuronal cells in olivopontocerebellar atrophy, and the regeneration of the optic nerve. However, there are limitations, such as an increased risk of cancer development when using Klf4 and c-Myc and the occurrence of abnormal dyskinesias in the medium term, possibly generated by the uncontrolled growth of differentiated dopaminergic cells and the impairment of the survival of the new cells. Therefore, the Yamanaka transcription factors have shown therapeutic potential through cell reprogramming for some carcinomas, neurodegenerative diseases, and rejuvenation. However, the limitations found in the studies require further investigation before the use of these transcription factors in humans.

The developmental and evolutionary origins of cellular pluripotency in the vertebrate neural crest

Neural crest cells are central to vertebrate development and evolution, endowing vertebrates with a "new head" that resulted in morphological, physiological, and behavioral features that allowed vertebrates to become active predators. One remarkable feature of neural crest cells is their multi-germ layer potential that allows for the formation of both ectodermal (pigmentation, peripheral glia, sensory neurons) and mesenchymal (connective tissue, cartilage/bone, dermis) cell types. Understanding the cellular and evolutionary origins of this broad cellular potential in the neural crest has been a long-standing focus for developmental biologists. Here, we review recent work that has demonstrated that neural crest cells share key features with pluripotent blastula stem cells, including expression of the Yamanaka stem cell factors (Oct3/4, Klf4, Sox2, c-Myc). These shared features suggest that pluripotency is either retained in the neural crest from blastula stages or subsequently reactivated as the neural crest forms. We highlight the cellular and molecular parallels between blastula stem cells and neural crest cells and discuss the work that has led to current models for the cellular origins of broad potential in the crest. Finally, we explore how these themes can provide new insights into how and when neural crest cells and pluripotency evolved in vertebrates and the evolutionary relationship between these populations.

Bioinformatic analysis identifies potentially key differentially expressed genes in oncogenesis and progression of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is one of the most common and lethal types of cancer within the urinary system. Great efforts have been made to elucidate the pathogeny. However, the molecular mechanism of ccRCC is still not well understood. The aim of this study is to identify key genes in the carcinogenesis and progression of ccRCC. The mRNA microarray dataset GSE53757 was downloaded from the Gene Expression Omnibus database. The GSE53757 dataset contains tumor and matched paracancerous specimens from 72 ccRCC patients with clinical stage I to IV. The linear model of microarray data (limma) package in R language was used to identify differentially expressed genes (DEGs). The protein–protein interaction (PPI) network of the DEGs was constructed using the search tool for the retrieval of interacting genes (STRING). Subsequently, we visualized molecular interaction networks by Cytoscape software and analyzed modules with MCODE. A total of 1,284, 1,416, 1,610 and 1,185 up-regulated genes, and 932, 1,236, 1,006 and 929 down-regulated genes were identified from clinical stage I to IV ccRCC patients, respectively. The overlapping DEGs among the four clinical stages contain 870 up-regulated and 645 down-regulated genes. The enrichment analysis of DEGs in the top module was carried out with DAVID. The results showed the DEGs of the top module were mainly enriched in microtubule-based movement, mitotic cytokinesis and mitotic chromosome condensation. Eleven up-regulated genes and one down-regulated gene were identified as hub genes. Survival analysis showed the high expression of CENPE, KIF20A, KIF4A, MELK, NCAPG, NDC80, NUF2, TOP2A, TPX2 and UBE2C, and low expression of ACADM gene could be involved in the carcinogenesis, invasion or recurrence of ccRCC. Literature retrieval results showed the hub gene NDC80, CENPE and ACADM might be novel targets for the diagnosis, clinical treatment and prognosis of ccRCC. In conclusion, the findings of present study may help us understand the molecular mechanisms underlying the carcinogenesis and progression of ccRCC, and provide potential diagnostic, therapeutic and prognostic biomarkers.