Tumor formation is a multistep process during which cells acquire genetic and epigenetic changes until they reach a fully transformed state. We show that CDK6 contributes to tumor formation by regulating transcriptional responses in a stage-specific manner. In early stages, the CDK6 kinase induces a complex transcriptional program to block p53 in hematopoietic cells. Cells lacking CDK6 kinase function are required to mutate (encoding p53) to achieve a fully transformed immortalized state. CDK6 binds to the promoters of genes including the p53 antagonists, and The findings are relevant to human patients: Tumors with low levels of CDK6 have mutations in significantly more often than expected. CDK6 acts at the interface of p53 and RB by driving cell-cycle progression and antagonizing stress responses. While sensitizing cells to p53-induced cell death, specific inhibition of CDK6 kinase activity may provoke the outgrowth of p53-mutant clones from premalignant cells. .

Acute myeloid leukemia (AML) with NPM1 mutation (NPM1mut) defines a World Health Organization entity. Absence of minimal residual disease (MRD) following induction chemotherapy is associated with an excellent prognosis. Data are conflicting on NPM1mut AML relapsing with wild-type NPM1 (NPM1wt). We analyzed 104 paired samples of NPM1mut AML patients with relapse and identified 14/104 that relapsed with NPM1wt AML. Blood counts at diagnosis differed significantly between patients with NPM1mut and NPM1wt relapse (median white blood cell count, 30 vs 3 × 109/L, P = .008; platelet count, 66 vs 128 × 109/l, P = .018). NPM1mut relapse occurred significantly earlier than NPM1wt relapse (14 vs 43 months, P = .004). At diagnosis, FLT3-ITD were more frequent in patients with NPM1mut relapse (P = .029), whereas DNMT3A mutations were more frequent in patients with NPM1wt relapse (P = .035). Sequencing analysis of paired samples at diagnosis, molecular remission, and NPM1wt relapse identified cooccurring mutations that persist from diagnosis throughout remission and at relapse, suggestive of a preexisting clonal hematopoiesis. We provide evidence that AML relapsing with NPM1wt is a distinct disease and that initial leukemia and relapse potentially arise from a premalignant clonal hematopoiesis.

The diagnosis and risk stratification of multiple myeloma (MM) is based on clinical and cytogenetic tests. Magnetic CD138 enrichment followed by interphase FISH (fluorescence in situ hybridisation) is the gold standard to identify prognostic translocations and copy number alterations (CNA). Although clinical implications of gene expression profiling (GEP) or panel based sequencing results are evident, those tests have not yet reached routine clinical application. We set up a single workflow to analyse MM of 211 patients at first diagnosis by whole genome sequencing (WGS) and RNA-Seq and validate the results by FISH analysis. We observed a 96% concordance of FISH and WGS results when assessing translocations involving the IGH locus and an overall concordance of FISH and WGS of 92% when assessing CNA. WGS analysis resulted in the identification of 17 additional MYC-translocations that were missed by FISH analysis. RNA-Seq followed by supervised clustering grouped patients in their expected genetically defined subgroup and prompted the assessment of WGS data in cases that were not congruent with FISH. This allowed the identification of additional IGH-translocations and hyperdiploid cases. We show the reliability of WGS an RNA-Seq in a clinical setting, which is a prerequisite for a novel routine diagnostic test.

The wealth of information captured by multiparameter flow cytometry (MFC) can be analyzed by recent methods of computer vision when represented as a single image file. We therefore transformed MFC raw data into a multicolor 2D image by a selforganizing map and classified this representation using a convolutional neural network. By this means, we built an artificial intelligence that is not only able to distinguish diseased from healthy samples, but it can also differentiate seven subtypes of mature B-cell neoplasm. We trained our model with 18,274 cases including chronic lymphocytic leukemia and its precursor monoclonal B-cell lymphocytosis, marginal zone lymphoma, mantle cell lymphoma, prolymphocytic leukemia, follicular lymphoma, hairy cell leukemia, lymphoplasmacytic lymphoma and achieved a weighted F1 score of 0.94 on a separate test set of 2,348 cases. Furthermore, we estimated the trustworthiness of a classification and could classify 70% of all cases with a confidence of 0.95 and higher. Our performance analyses indicate that particularly for rare subtypes further improvement can be expected when even more samples are available for training.