Reviving the guardian of the genome: Small molecule activators of p53

Role of tumor suppressor p53 and micro-RNA interplay in multiple myeloma pathogenesis

The molecular mechanisms underlying dysregulated wild type (wt) p53 in multiple myeloma (MM) have been subjects of intense investigation for years. Indeed, correlation of rarely occurring TP53 gene mutations or deletions with adverse clinical outcomes in MM patients is strongly established, while in majority of cases wtp53 seems to be non-functional or dysregulated bearing a high clinical impact. Interestingly, findings from recent investigations show that micro-RNAs (miRNAs) may contribute to suppression of wtp53 in MM, as they are now known to function as key regulatory elements in the p53 network. This area is shedding new light on understanding the biologic effects of dysregulated p53 in MM pathogenesis especially drug resistance. miRNAs such as miR-125b (oncomiR) or miR-34a (tumor suppressor-miR) can be negative or positive regulators of wtp53 function, respectively, with specific effects on MM cell viability. On the other hand, our knowledge of miRNA interaction with mutant (mt) p53 in MM, which is rather related to disease progression and resistance to therapy, is limited which demands in-depth exploration. Here, we will put forward the current knowledge on miRNA-p53 interaction in MM and its role in MM pathogenesis including drug resistance. We will also highlight the pre-clinical approaches for therapeutic application of miRNAs targeting p53 pathway.

Differential protein-coding gene and long noncoding RNA expression in smoking-related lung squamous cell carcinoma

Background

Cigarette smoking is one of the greatest preventable risk factors for developing cancer, and most cases of lung squamous cell carcinoma (lung SCC) are associated with smoking. The pathogenesis mechanism of tumor progress is unclear. This study aimed to identify biomarkers in smoking‐related lung cancer, including protein‐coding gene, long noncoding RNA, and transcription factors.

Methods

We selected and obtained messenger RNA microarray datasets and clinical data from the Gene Expression Omnibus database to identify gene expression altered by cigarette smoking. Integrated bioinformatic analysis was used to clarify biological functions of the identified genes, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, the construction of a protein–protein interaction network, transcription factor, and statistical analyses. Subsequent quantitative real‐time PCR was utilized to verify these bioinformatic analyses.

Results

Five hundred and ninety‐eight differentially expressed genes and 21 long noncoding RNA were identified in smoking‐related lung SCC. GO and KEGG pathway analysis showed that identified genes were enriched in the cancer‐related functions and pathways. The protein–protein interaction network revealed seven hub genes identified in lung SCC. Several transcription factors and their binding sites were predicted. The results of real‐time quantitative PCR revealed that AURKA and BIRC5 were significantly upregulated and LINC00094 was downregulated in the tumor tissues of smoking patients. Further statistical analysis indicated that dysregulation of AURKA, BIRC5, and LINC00094 indicated poor prognosis in lung SCC.

Conclusion

Protein‐coding genes AURKA, BIRC5, and LINC00094 could be biomarkers or therapeutic targets for smoking‐related lung SCC.