Bone progenitor dysfunction induces myelodysplasia and secondary leukaemia

Mesenchymal cell populations contribute to microenvironments regulating stem cells and the growth of malignant cells. Osteolineage cells participate in the hematopoietic stem cell niche. Here, we report that deletion of the miRNA processing endonuclease Dicer1 selectively in mesenchymal osteoprogenitors induces markedly disordered hematopoiesis. Hematopoietic changes affected multiple lineages recapitulating key features of human myelodysplastic syndrome (MDS) including the development of acute myelogenous leukemia. These changes were microenvironment dependent and induced by specific cells in the osteolineage. Dicer1−/− osteoprogenitors expressed reduced levels of Sbds, the gene mutated in the human bone marrow failure and leukemia predisposition Shwachman-Bodian-Diamond Syndrome. Deletion of Sbds in osteoprogenitors largely phenocopied Dicer1 deletion. These data demonstrate that differentiation stage-specific perturbations in osteolineage cells can induce complex hematological disorders and indicate the central role individual cellular elements of ‘estroma’ can play in tissue homeostasis. They reveal that primary changes in the hematopoietic microenvironment can initiate secondary neoplastic disease

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases