On dynamic network entropy in cancer

The cellular phenotype is described by a complex network of molecular interactions. Elucidating network properties that distinguish disease from the healthy cellular state is therefore of critical importance for gaining systems-level insights into disease mechanisms and ultimately for developing improved therapies. By integrating gene expression data with a protein interaction network to induce a stochastic dynamics on the network, we here demonstrate that cancer cells are characterised by an increase in the dynamic network entropy, compared to cells of normal physiology. Using a fundamental relation between the macroscopic resilience of a dynamical system and the uncertainty (entropy) in the underlying microscopic processes, we argue that cancer cells will be more robust to random gene perturbations. In addition, we formally demonstrate that gene expression differences between normal and cancer tissue are anticorrelated with local dynamic entropy changes, thus providing a systemic link between gene expression changes at the nodes and their local network dynamics. In particular, we also find that genes which drive cell-proliferation in cancer cells and which often encode oncogenes are associated with reductions in the dynamic network entropy. In summary, our results support the view that the observed increased robustness of cancer cells to perturbation and therapy may be due to an increase in the dynamic network entropy that allows cells to adapt to the new cellular stresses. Conversely, genes that exhibit local flux entropy decreases in cancer may render cancer cells more susceptible to targeted intervention and may therefore represent promising drug targets.Comment: 10 pages, 3 figures, 4 tables. Submitte

Aurora kinases in childhood acute leukemia: The promise of aurora B as therapeutic target

We investigated the effects of targeting the mitotic regulators aurora kinase A and B in pediatric acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML). Aurora protein expression levels in pediatric ALL and AML patient samples were determined by western blot and reverse phase protein array. Both kinases were overexpressed in ALL and AML patients (P<0.0002), especially in E2A-PBX1-translocated ALL cases (P<0.002), compared with normal bone-marrow mononuclear cells. Aurora kinase expression was silenced in leukemic cell lines using short hairpin RNAs and locked nucleic acid-based mRNA antagonists. Aurora B knockdown resulted in proliferation arrest and apoptosis, whereas aurora A knockdown caused no or only minor growth delay. Most tested cell lines were highly sensitive to the AURKB-selective inhibitor barasertib-hydroxyquinazoline-pyrazol-anilide (AZD1152-HQPA) in the nanomolar range, as tested with an MTS (3-(4,5-dimethylthiazol-2-yl)-5-(3- carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium) assay. But most importantly, primary ALL cells with a high aurora B protein expression, especially E2A-PBX1-positive cases, were sensitive as well. In adult AML early clinical trials, clear responses are observed with barasertib. Here we show that inhibition of aurora B, more than aurora A, has an antiproliferative and pro-apoptotic effect on acute leukemia cells, indicating that particularly targeting aurora B may offer a new strategy to treat pediatric ALL and AML

Integrating clinical features with genetic factors enhances survival prediction for adults with acute myeloid leukemia

The 2017 European LeukemiaNet 2017 acute myeloid leukemia (AML) risk stratification (ELN2017) is widely used for risk-stratifying patients with AML. However, its applicability in low- and middle-income countries is limited because of a lack of full cytogenetic and molecular information at diagnosis. Here, we propose an alternative for risk stratification (the Adapted Genetic Risk [AGR]), which permits cytogenetic or molecular missing data while retaining prognostic power. We first analyzed 167 intensively treated patients with nonacute promyelocytic leukemia AML enrolled in São Paulo, Brazil (Faculdade de Medicina da Universidade de São Paulo), as our training data set, using ELN2017 as the standard for comparison with our AGR. Next, we combined our AGR with clinical prognostic parameters found in a Cox proportional hazards model to create a novel scoring system (survival AML score, SAMLS) that stratifies patients with newly diagnosed AML. Finally, we have used 2 independent test cohorts, Faculdade de Medicina de Ribeirão Preto (FMRP; Brazil, n = 145) and Oxford University Hospitals (OUH; United Kingdom, n = 157) for validating our findings. AGR was statistically significant for overall survival (OS) in both test cohorts (FMRP, P = .037; OUH, P = .012) and disease-free survival in FMRP (P = .04). The clinical prognostic features in SAMLS were age (>45 years), white blood cell count (30.0 × 103/μL), and low albumin levels (<3.8 g/dL), which were associated with worse OS in all 3 cohorts. SAMLS showed a significant difference in OS in the training cohort (P < .001) and test cohorts (FMRP, P = .0018; OUH, P < .001). Therefore, SAMLS, which incorporates the novel AGR evaluation with clinical parameters, is an accurate tool for AML risk assessment

Clinical impact ofBAALCexpression in high-risk acute promyelocytic leukemia

Although overexpression of the brain and acute leukemia, cytoplasmic (BAALC) gene is associated with primary resistant disease and shorter relapse-free, disease-free, and overall survival in different subsets of acute myeloid leukemia (AML), little is known about its clinical impact in acute promyelocytic leukemia (APL). Using real-time reverse transcriptase polymerase chain reaction, we showed thatBAALCexpression is significantly lower in APL compared with other subsets of AML (P10 × 109/L) (HR, 5.3; 95% CI, 1.14-24.5;P= .033). We conclude thatBAALCexpression could be useful for refining risk stratification in APL, although this needs to be confirmed in independent cohorts

Prognostic impact of KMT2E transcript levels on outcome of patients with acute promyelocytic leukaemia treated with all-trans retinoic acid and anthracycline-based chemotherapy: An International Consortium on Acute Promyelocytic Leukaemia study

The KMT2E (MLL5) gene encodes a histone methyltransferase implicated in the positive control of genes related to haematopoiesis. Its close relationship with retinoic acid-induced granulopoiesis suggests that the deregulated expression of KMT2E might lead acute promyelocytic leukaemia (APL) blasts to become less susceptible to the conventional treatment protocols. Here, we assessed the impact of KMT2E expression on the prognosis of 121 APL patients treated with ATRA and anthracycline-based chemotherapy. Univariate analysis showed that complete remission (P = 0·006), 2-year overall survival (OS) (P = 0·005) and 2-year disease-free survival (DFS) rates (P = 0·037) were significantly lower in patients with low KMT2E expression; additionally, the 2-year cumulative incidence of relapse was higher in patients with low KMT2E expression (P = 0·04). Multivariate analysis revealed that low KMT2E expression was independently associated with lower remission rate (odds ratio [OR]: 7·18, 95% confidence interval [CI]: 1·71-30·1; P = 0·007) and shorter OS (hazard ratio [HR]: 0·27, 95% CI: 0·08-0·87; P = 0·029). Evaluated as a continuous variable, KMT2E expression retained association with poor remission rate (OR: 10·3, 95% CI: 2·49-43·2; P = 0·001) and shorter survival (HR: 0·17, 95% IC: 0·05-0·53; P = 0·002), while the association with DFS was of marginal significance (HR: 1·01; 95% CI: 0·99-1·02; P = 0·06). In summary, low KMT2E expression may predict poor outcome in APL patients