ARHGDIA, a mutant TP53-associated Rho GDP dissociation inhibitor, is over-expressed in gene expression profiles of TP53 disrupted chronic lymphocytic leukaemia cells

HIF-1α is over-expressed in leukemic cells from TP53-disrupted patients and is a promising therapeutic target in chronic lymphocytic leukemia

In chronic lymphocytic leukemia (CLL), the hypoxia-inducible factor 1 (HIF-1) regulates the response of tumor cells to hypoxia and their protective interactions with the leukemic microenvironment. In this study, we demonstrate that CLL cells from TP53-disrupted (TP53^dis) patients have constitutively higher expression levels of the α-subunit of HIF-1 (HIF-1α) and increased HIF-1 transcriptional activity compared to the wild-type counterpart. In the TP53^dis subset, HIF-1α upregulation is due to reduced expression of the HIF-1α ubiquitin ligase von Hippel-Lindau protein (pVHL). Hypoxia and stromal cells further enhance HIF-1α accumulation, independently of TP53 status. Hypoxia acts through the downmodulation of pVHL and the activation of the PI3K/AKT and RAS/ERK1-2 pathways, whereas stromal cells induce an increased activity of the RAS/ERK1-2, RHOA/RHOA kinase and PI3K/AKT pathways, without affecting pVHL expression. Interestingly, we observed that higher levels of HIF-1A mRNA correlate with a lower susceptibility of leukemic cells to spontaneous apoptosis, and associate with the fludarabine resistance that mainly characterizes TP53^dis tumor cells. The HIF-1α inhibitor BAY87-2243 exerts cytotoxic effects toward leukemic cells, regardless of the TP53 status, and has anti-tumor activity in Em-TCL1 mice. BAY87-2243 also overcomes the constitutive fludarabine resistance of TP53^dis leukemic cells and elicits a strongly synergistic cytotoxic effect in combination with ibrutinib, thus providing preclinical evidence to stimulate further investigation into use as a potential new drug in CLL.

NOTCH1, SF3B1, MDM2 and MYD88 mutations in patients with chronic lymphocytic leukemia

Mutations in certain genes have been suggested to be associated with the pathogenesis of chronic lymphocytic leukemia (CLL), which is the most common leukemia in adults. In a case-control study, 100 patients with CLL and 105 healthy individuals were investigated for Notch homolog 1, translocation-associated (Drosophila) (NOTCH1) c.7544-7545delCT, recombinant splicing factor 3B subunit 1 (SF3B1) c.2098A>G, mouse double minute 2 homolog (MDM2) 40-bp insertion/deletion and myeloid differentiation primary response 88 (MYD88) L265P mutations by using allele specific-polymerase chain reaction (AS-PCR), a designed AS-PCR, PCR and PCR-restriction fragment length polymorphism methods, respectively. The presence of NOTCH1 and SF3B1 mutations were confirmed by genomic DNA sequencing. The NOTCH1 mutation was detected in 10% of patients and not detected in the control group. A higher frequency of NOTCH1 mutation was detected in patients with stage III CLL (62.5%) compared with stages 0-II CLL (37.5%) (odds ratio, 4.69-fold; 95% confidence interval, 1.0-21.9; P=0.049). The SF3B1 mutation was observed in 12% of the patients compared with 1.9% of the controls (P=0.012). The presence of MDM2 polymorphism was not associated with the risk or the stage of the disease. In addition, the MYD88 L265P mutation was not detected in the patients or the controls. The current study established the frequency of NOTCH1, SF3B1, MDM2 and MYD88 mutations in patients with CLL from the Kurdish population of Western Iran. In summary, a high frequency of NOTCH1 and SF3B1 mutations were identified in patients with CLL compared with healthy individuals, and the NOTCH1 mutation was associated with a high stage of the disease.

Mining for Candidate Genes Related to Pancreatic Cancer Using Protein-Protein Interactions and a Shortest Path Approach

Pancreatic cancer (PC) is a highly malignant tumor derived from pancreas tissue and is one of the leading causes of death from cancer. Its molecular mechanism has been partially revealed by validating its oncogenes and tumor suppressor genes; however, the available data remain insufficient for medical workers to design effective treatments. Large-scale identification of PC-related genes can promote studies on PC. In this study, we propose a computational method for mining new candidate PC-related genes. A large network was constructed using protein-protein interaction information, and a shortest path approach was applied to mine new candidate genes based on validated PC-related genes. In addition, a permutation test was adopted to further select key candidate genes. Finally, for all discovered candidate genes, the likelihood that the genes are novel PC-related genes is discussed based on their currently known functions.