The transforming growth factor (TGF-β) family of growth factors controls an immense number of cellular responses and figures prominently in development and homeostasis of most human tissues. Work over the past decades has revealed significant insight into the TGF-β signal transduction network, such as activation of serine/threonine receptors through ligand binding, activation of SMAD proteins through phosphorylation, regulation of target genes expression in association with DNA-binding partners and regulation of SMAD activity and degradation. Disruption of the TGF-β pathway has been implicated in many human diseases, including solid and hematopoietic tumors. As a potent inhibitor of cell proliferation, TGF-β acts as a tumor suppressor; however in tumor cells, TGF-β looses anti-proliferative response and become an oncogenic factor. This article reviews current understanding of TGF-β signaling and different mechanisms that lead to its impairment in various solid tumors and hematological malignancies.

Inhibition of proteasome, a proteolytic complex responsible for the degradation of ubiquitinated proteins, has emerged as a powerful strategy for treatment of multiple myeloma (MM), a plasma cell malignancy. First-in-class agent, bortezomib, has demonstrated great positive therapeutic efficacy in MM, both in pre-clinical and in clinical studies. However, despite its high efficiency, a large proportion of patients do not achieve sufficient clinical response. Therefore, the development of a second-generation of proteasome inhibitors (PIs) with improved pharmacological properties was needed. Recently, several of these new agents have been introduced into clinics including carfilzomib, marizomib and ixazomib. Further, new orally administered second-generation PI oprozomib is being investigated. This review provides an overview of main mechanisms of action of PIs in MM, focusing on the ongoing development and progress of novel anti-proteasome therapeutics.

The insufficient standardization of diagnostic next-generation sequencing (NGS) still limits its implementation in clinical practice, with the correct detection of mutations at low variant allele frequencies (VAF) facing particular challenges. We address here the standardization of sequencing coverage depth in order to minimize the probability of false positive and false negative results, the latter being underestimated in clinical NGS. There is currently no consensus on the minimum coverage depth, and so each laboratory has to set its own parameters. To assist laboratories with the determination of the minimum coverage parameters, we provide here a user-friendly coverage calculator. Using the sequencing error only, we recommend a minimum depth of coverage of 1,650 together with a threshold of at least 30 mutated reads for a targeted NGS mutation analysis of ≥3% VAF, based on the binomial probability distribution. Moreover, our calculator also allows adding assay-specific errors occurring during DNA processing and library preparation, thus calculating with an overall error of a specific NGS assay. The estimation of correct coverage depth is recommended as a starting point when assessing thresholds of NGS assay. Our study also points to the need for guidance regarding the minimum technical requirements, which based on our experience should include the limit of detection (LOD), overall NGS assay error, input, source and quality of DNA, coverage depth, number of variant supporting reads, and total number of target reads covering variant region. Further studies are needed to define the minimum technical requirements and its reporting in diagnostic NGS.