A lineage-specific STAT5BN642H mouse model to study NK-cell leukemia.

Patients with T- and NK-cell neoplasms frequently have somatic STAT5B gain-of-function mutations. The most frequent STAT5B mutation is STAT5BN642H, which is known to drive murine T-cell leukemia although its role in NK-cell malignancies is unclear. Introduction of the STAT5BN642H mutation into human NK-cell lines enhances their potential to induce leukemia in mice. We have generated a mouse model that enables tissue-specific expression of STAT5BN642H and have selectively expressed the mutated STAT5B in hematopoietic cells (N642Hvav/+) or exclusively in NK cells (N642HNK/NK). All N642Hvav/+ mice rapidly develop an aggressive T-/NK T-cell leukemia, whereas N642HNK/NK mice display an indolent NK-large granular lymphocytic leukemia (NK-LGLL) that progresses to an aggressive leukemia with age. Samples from NK-cell leukemia patients have a distinctive transcriptional signature driven by mutant STAT5B, which overlaps with that of murine leukemic N642HNK/NK NK cells. We have generated the first reliable STAT5BN642H-driven pre-clinical mouse model that displays an indolent NK-LGLL progressing to aggressive NK-cell leukemia. This novel in vivo tool will enable us to explore the transition from an indolent to an aggressive disease and will thus permit the study of prevention and treatment options for NK-cell malignancies.

SLCO4A1 expression is associated with activated inflammatory pathways in high-grade serous ovarian cancer.

Patients with high-grade serous ovarian cancer (HGSOC) have a very poor overall survival. Current therapeutic approaches do not bring benefit to all patients. Although genetic alterations and molecular mechanisms are well characterized, the molecular pathological conditions are poorly investigated. Solute carrier organic anion transporter family member 4A1 (SLCO4A1) encodes OATP4A1, which is an uptake membrane transporter of metabolic products. Its expression may influence various signaling pathways associated with the molecular pathophysiological conditions of HGSOC and consequently tumor progression. RNA sequencing of 33 patient-derived HGSOC cell lines showed that SLCO4A1 expression was diverse by individual tumors, which was further confirmed by RT-qPCR, Western blotting and immunohistochemistry. Gene Set Enrichment Analysis revealed that higher SLCO4A1 level was associated with inflammation-associated pathways including NOD-like receptor, adipocytokine, TALL1, CD40, NF-κB, and TNF-receptor 2 signaling cascades, while low SLCO4A1 expression was associated with the mitochondrial electron transport chain pathway. The overall gene expression pattern in all cell lines was specific to each patient and remained largely unchanged during tumor progression. In addition, genes encoding ABCC3 along with SLCO4A1-antisense RNA 1, were associated with higher expression of the SLCO4A1, indicating their possible involvement in inflammation-associated pathways that are downstream to the prostaglandin E2/cAMP axis. Taken together, increased SLCO4A1/OATP4A1 expression is associated with the upregulation of specific inflammatory pathways, while the decreased level is associated with mitochondrial dysfunction. These molecular pathophysiological conditions are tumor specific and should be taken into consideration by the development of therapies against HGSOC.

Tumor Growth Rate Estimates Are Independently Predictive of Therapy Response and Survival in Recurrent High-Grade Serous Ovarian Cancer Patients.

This study aimed to assess the predictive value of tumor growth rate estimates based on serial cancer antigen-125 (CA-125) levels on therapy response and survival of patients with recurrent high-grade serous ovarian cancer (HGSOC). In total, 301 consecutive patients with advanced HGSOC (exploratory cohort: n = 155, treated at the Medical University of Vienna; external validation cohort: n = 146, from the Ovarian Cancer Therapy-Innovative Models Prolong Survival (OCTIPS) consortium) were enrolled. Tumor growth estimates were obtained using a validated two-phase equation model involving serial CA-125 levels, and their predictive value with respect to treatment response to the next chemotherapy and the prognostic value with respect to disease-specific survival and overall survival were assessed. Tumor growth estimates were an independent predictor for response to second-line chemotherapy and an independent prognostic factor for second-line chemotherapy use in both univariate and multivariable analyses, outperforming both the predictive (second line: p = 0.003, HR 5.19 [1.73-15.58] vs. p = 0.453, HR 1.95 [0.34-11.17]) and prognostic values (second line: p = 0.042, HR 1.53 [1.02-2.31] vs. p = 0.331, HR 1.39 [0.71-2.27]) of a therapy-free interval (TFI) < 6 months. Tumor growth estimates were a predictive factor for response to third- and fourth-line chemotherapy and a prognostic factor for third- and fourth-line chemotherapy use in the univariate analysis. The CA-125-derived tumor growth rate estimate may be a quantifiable and easily assessable surrogate to TFI in treatment decision making for patients with recurrent HGSOC.