Increased entropy of signal transduction in the cancer metastasis phenotype

Studies into the statistical properties of biological networks have led to important biological insights, such as the presence of hubs and hierarchical modularity. There is also a growing interest in studying the statistical properties of networks in the context of cancer genomics. However, relatively little is known as to what network features differ between the cancer and normal cell physiologies, or between different cancer cell phenotypes. Based on the observation that frequent genomic alterations underlie a more aggressive cancer phenotype, we asked if such an effect could be detectable as an increase in the randomness of local gene expression patterns. Using a breast cancer gene expression data set and a model network of protein interactions we derive constrained weighted networks defined by a stochastic information flux matrix reflecting expression correlations between interacting proteins. Based on this stochastic matrix we propose and compute an entropy measure that quantifies the degree of randomness in the local pattern of information flux around single genes. By comparing the local entropies in the non-metastatic versus metastatic breast cancer networks, we here show that breast cancers that metastasize are characterised by a small yet significant increase in the degree of randomness of local expression patterns. We validate this result in three additional breast cancer expression data sets and demonstrate that local entropy better characterises the metastatic phenotype than other non-entropy based measures. We show that increases in entropy can be used to identify genes and signalling pathways implicated in breast cancer metastasis. Further exploration of such integrated cancer expression and protein interaction networks will therefore be a fruitful endeavour.Comment: 5 figures, 2 Supplementary Figures and Table

Mutations in epigenetic regulators including SETD2 are gained during relapse in pediatric acute lymphoblastic leukemia

Relapsed pediatric acute lymphoblastic leukemia (ALL) has high rates of treatment failure. Epigenetic regulators have been proposed as modulators of chemoresistance, here we sequence genes encoding epigenetic regulators in matched diagnosis-remission-relapse ALL samples. We find significant enrichment of mutations in epigenetic regulators at relapse with recurrent somatic mutations in SETD2, CREBBP, MSH6, KDM6A and MLL2, mutations in signaling factors are not enriched. Somatic alterations in SETD2, including frameshift and nonsense mutations, are present at 12% in a large de novo ALL patient cohort. We conclude that the enrichment of mutations in epigenetic regulators at relapse is consistent with a role in mediating therapy resistance

Mutations of the transcription factor PU.1 are not associated with acute lymphoblastic leukaemia

The transcription factor PU.1 plays a crucial role during normal haematopoiesis in both myeloid cells and B-lymphocytes. Mice with a disruption in both alleles of the PU.1 locus were found to lack macrophages and B cells and had delayed appearance of neutrophils. In addition, critical decrease of PU.1 expression is sufficient to cause acute myeloid leukaemia (AML) and lymphomas in mice. Recently, we reported that heterozygous mutations in the PU.1 gene are present in some patients with AML. Thus, we hypothesised that PU.1 mutations might also contribute to the development of acute leukaemias of the B-cell lineage. Here, we screened 62 patients with B-cell acute lymphoblastic leukaemia (B-ALL) at diagnosis for genomic mutations by direct sequencing of all five exons of the PU.1 gene. We found no genomic alteration of the PU.1 gene suggesting that PU.1 mutations are not likely to be common in B-ALL

MicroRNA Expression Profiling Identifies Activated B Cell Status in Chronic Lymphocytic Leukemia Cells

Chronic lymphocytic leukemia (CLL) is thought to be a disease of resting lymphocytes. However, recent data suggest that CLL cells may more closely resemble activated B cells. Using microRNA (miRNA) expression profiling of highly-enriched CLL cells from 38 patients and 9 untransformed B cells from normal donors before acute CpG activation and 5 matched B cells after acute CpG activation, we demonstrate an activated B cell status for CLL. Gene set enrichment analysis (GSEA) identified statistically-significant similarities in miRNA expression between activated B cells and CLL cells including upregulation of miR-34a, miR-155, and miR-342-3p and downregulation of miR-103, miR-181a and miR-181b. Additionally, decreased levels of two CLL signature miRNAs miR-29c and miR-223 are associated with ZAP70+ and IgVH unmutated status and with shorter time to first therapy. These data indicate an activated B cell status for CLL cells and suggest that the direction of change of individual miRNAs may predict clinical course in CLL

Implications of TP53 allelic state for genome stability, clinical presentation and outcomes in myelodysplastic syndromes

Tumor protein p53 (TP53) is the most frequently mutated gene in cancer1,2. In patients with myelodysplastic syndromes (MDS), TP53 mutations are associated with high-risk disease3,4, rapid transformation to acute myeloid leukemia (AML)5, resistance to conventional therapies6–8 and dismal outcomes9. Consistent with the tumor-suppressive role of TP53, patients harbor both mono- and biallelic mutations10. However, the biological and clinical implications of TP53 allelic state have not been fully investigated in MDS or any other cancer type. We analyzed 3,324 patients with MDS for TP53 mutations and allelic imbalances and delineated two subsets of patients with distinct phenotypes and outcomes. One-third of TP53-mutated patients had monoallelic mutations whereas two-thirds had multiple hits (multi-hit) consistent with biallelic targeting. Established associations with complex karyotype, few co-occurring mutations, high-risk presentation and poor outcomes were specific to multi-hit patients only. TP53 multi-hit state predicted risk of death and leukemic transformation independently of the Revised International Prognostic Scoring System (IPSS-R)11. Surprisingly, monoallelic patients did not differ from TP53 wild-type patients in outcomes and response to therapy. This study shows that consideration of TP53 allelic state is critical for diagnostic and prognostic precision in MDS as well as in future correlative studies of treatment response