Germline genetic factors influence the outcome of interferon-α therapy in polycythemia vera.

Interferon-α (IFN-α)-based treatments can induce hematologic and molecular responses (HRs and MRs, respectively) in polycythemia vera (PV); however, patients do not respond equally. Germline genetic factors have been implicated in differential drug responses. We addressed the effect of common germline polymorphisms on HR and MR after treatment of PV in the PROUD-PV and CONTINUATION-PV studies in a total of 122 patients who received ropeginterferon alfa-2b. Genome-wide association studies using longitudinal data on HR and MR over a 36-month follow-up did not reveal any associations at the level of genome-wide statistical significance. Furthermore, we performed targeted association analyses at the interferon lambda 4 (IFNL4) locus, well known for its role in hepatitis C viral clearance and recently reported to influence HR during treatment of myeloproliferative neoplasms. We did not observe any association of IFNL4 polymorphisms with HR in our study cohort; however, we demonstrated a statistically significant effect of the functionally causative IFNL4 diplotype (haplotype pair, including the protein-coding variants rs368234815/rs117648444) on MR (P = 3.91 × 10-4; odds ratio, 10.80; 95% confidence interval, 2.39-69.97) as reflected in differential JAK2V617F mutational burden changes according to IFNL4 diplotype status. Stratification of patients with PV based on IFNL4 functionality may allow for optimizing patient management during IFN-α-based therapy.

Myelomonocytic Skewing In Vitro Discriminates Subgroups of Patients with Myelofibrosis with A Different Phenotype, A Different Mutational Profile and Different Prognosis.

Normal hematopoietic function is maintained by a well-controlled balance of myelomonocytic, megaerythroid and lymphoid progenitor cell populations which may be skewed during pathologic conditions. Using semisolid in vitro cultures supporting the growth of myelomonocytic (CFU-GM) and erythroid (BFU-E) colonies, we investigated skewed differentiation towards the myelomonocytic over erythroid commitment in 81 patients with myelofibrosis (MF). MF patients had significantly increased numbers of circulating CFU-GM and BFU-E. Myelomonocytic skewing as indicated by a CFU-GM/BFU-E ratio ≥ 1 was found in 26/81 (32%) MF patients as compared to 1/98 (1%) in normal individuals. Patients with myelomonocytic skewing as compared to patients without skewing had higher white blood cell and blast cell counts, more frequent leukoerythroblastic features, but lower hemoglobin levels and platelet counts. The presence of myelomonocytic skewing was associated with a higher frequency of additional mutations, particularly in genes of the epigenetic and/or splicing machinery, and a significantly shorter survival (46 vs. 138 mo, p < 0.001). The results of this study show that the in vitro detection of myelomonocytic skewing can discriminate subgroups of patients with MF with a different phenotype, a different mutational profile and a different prognosis. Our findings may be important for the understanding and management of MF.

Mutational landscape of the transcriptome offers putative targets for immunotherapy of myeloproliferative neoplasms.

Ph-negative myeloproliferative neoplasms (MPNs) are hematological cancers that can be subdivided into entities with distinct clinical features. Somatic mutations in JAK2, CALR, and MPL have been described as drivers of the disease, together with a variable landscape of nondriver mutations. Despite detailed knowledge of disease mechanisms, targeted therapies effective enough to eliminate MPN cells are still missing. In this study of 113 MPN patients, we aimed to comprehensively characterize the mutational landscape of the granulocyte transcriptome using RNA sequencing data and subsequently examine the applicability of immunotherapeutic strategies for MPN patients. Following implementation of customized workflows and data filtering, we identified a total of 13 (12/13 novel) gene fusions, 231 nonsynonymous single nucleotide variants, and 21 insertions and deletions in 106 of 113 patients. We found a high frequency of SF3B1-mutated primary myelofibrosis patients (14%) with distinct 3' splicing patterns, many of these with a protein-altering potential. Finally, from all mutations detected, we generated a virtual peptide library and used NetMHC to predict 149 unique neoantigens in 62% of MPN patients. Peptides from CALR and MPL mutations provide a rich source of neoantigens as a result of their unique ability to bind many common MHC class I molecules. Finally, we propose that mutations derived from splicing defects present in SF3B1-mutated patients may offer an unexplored neoantigen repertoire in MPNs. We validated 35 predicted peptides to be strong MHC class I binders through direct binding of predicted peptides to MHC proteins in vitro. Our results may serve as a resource for personalized vaccine or adoptive cell-based therapy development.

Heterologous protein production using euchromatin-containing expression vectors in mammalian cells.

Upon stable cell line generation, chromosomal integration site of the vector DNA has a major impact on transgene expression. Here we apply an active gene environment, rather than specified genetic elements, in expression vectors used for random integration. We generated a set of Bacterial Artificial Chromosome (BAC) vectors with different open chromatin regions, promoters and gene regulatory elements and tested their impact on recombinant protein expression in CHO cells. We identified the Rosa26 BAC as the most efficient vector backbone showing a nine-fold increase in both polyclonal and clonal production of the human IgG-Fc. Clonal protein production was directly proportional to integrated vector copy numbers and remained stable during 10 weeks without selection pressure. Finally, we demonstrated the advantages of BAC-based vectors by producing two additional proteins, HIV-1 glycoprotein CN54gp140 and HIV-1 neutralizing PG9 antibody, in bioreactors and shake flasks reaching a production yield of 1 g/l.

Disruption of STAT3 signalling promotes KRAS-induced lung tumorigenesis.

STAT3 is considered to play an oncogenic role in several malignancies including lung cancer; consequently, targeting STAT3 is currently proposed as therapeutic intervention. Here we demonstrate that STAT3 plays an unexpected tumour-suppressive role in KRAS mutant lung adenocarcinoma (AC). Indeed, lung tissue-specific inactivation of Stat3 in mice results in increased Kras(G12D)-driven AC initiation and malignant progression leading to markedly reduced survival. Knockdown of STAT3 in xenografted human AC cells increases tumour growth. Clinically, low STAT3 expression levels correlate with poor survival and advanced malignancy in human lung AC patients with smoking history, which are prone to KRAS mutations. Consistently, KRAS mutant lung tumours exhibit reduced STAT3 levels. Mechanistically, we demonstrate that STAT3 controls NF-κB-induced IL-8 expression by sequestering NF-κB within the cytoplasm, thereby inhibiting IL-8-mediated myeloid tumour infiltration and tumour vascularization and hence tumour progression. These results elucidate a novel STAT3-NF-κB-IL-8 axis in KRAS mutant AC with therapeutic and prognostic relevance.

Modeling cancer using genetically engineered mice.

Genetically engineered mouse (GEM) models have proven to be a powerful tool to study tumorigenesis. The mouse is the preferred complex organism used in cancer studies due to the high number and versatility of genetic tools available for this species. GEM models can mimic point mutations, gene amplifications, short and large deletions, translocations, etc.; thus, most of the genetic aberrations found in human tumors can be modeled in GEM, making GEM models a very attractive system. Furthermore, recent developments in mouse genetics may facilitate the generation of GEM models with increased mutational complexity, therefore resembling human tumors better. Within this review, we will discuss the different possibilities of modeling tumorigenesis using GEM and the future developments within the field.