Management and outcome of patients with chronic myeloid leukemia in blast phase in the tyrosine kinase inhibitor era - analysis of the European LeukemiaNet Blast Phase Registry.

Blast phase (BP) of chronic myeloid leukemia (CML) still represents an unmet clinical need with a dismal prognosis. Due to the rarity of the condition and the heterogeneity of the biology and clinical presentation, prospective trials and concise treatment recommendations are lacking. Here we present the analysis of the European LeukemiaNet Blast Phase Registry, an international collection of the clinical presentation, treatment and outcome of blast phases which had been diagnosed in CML patients after 2015. Data reveal the expected heterogeneity of the entity, lacking a clear treatment standard. Outcomes remain dismal, with a median overall survival of 23.8 months (median follow up 27.8 months). Allogeneic stem cell transplantation (alloSCT) increases the rate of deep molecular responses. De novo BP and BP evolving from a previous CML do show slightly different features, suggesting a different biology between the two entities. Data show that outside clinical trials and in a real-world setting treatment of blast phase is individualized according to disease- and patient-related characteristics, with the aim of blast clearance prior to allogeneic stem cell transplantation. AlloSCT should be offered to all patients eligible for this procedure.

Usability and usefulness of (electronic) patient identification systems-A cross-sectional evaluation in German-speaking radiation oncology departments.

PURPOSE: Patient misidentification in radiation oncology (RO) is a significant concern due to the potential harm to patient health and the burden on healthcare systems. Electronic patient identification systems (ePIS) are increasingly being used as an alternative or supplement to organizational systems (oPIS). The objective of this study was to assess the usability and usefulness of ePIS and oPIS in German-speaking countries. METHODS: A cross-sectional survey was designed by a group of experts from various professional backgrounds in RO. The survey consisted of 38 questions encompassing quantitative and qualitative data on usability, user experience, and usefulness of PIS. It was available between August and October 2022. RESULTS: Of 118 eligible participants, 37% had implemented some kind of ePIS. Overall, 22% of participants who use an oPIS vs. 10% of participants who use an ePIS reported adverse events in terms of patients' misidentification in the past 5 years. Frequent or very frequent drop-outs of electronic systems were reported by 31% of ePIS users. Users of ePIS significantly more often affirmed a positive cost-benefit ratio of ePIS as well as an improvement of workflow, whereas users of oPIS more frequently apprehended a decrease in staffs' attention through ePIS. The response rate was 8%. CONCLUSION: The implementation of ePIS can contribute to efficient PI and improved processes. Apprehensions by oPIS users and assessments of ePIS users differ significantly in aspects of the perceived usefulness of ePIS. However, technical problems need to be addressed to ensure the reliability of ePIS. Further research is needed to assess the impact of different PIS on patient safety in RO.

Histone demethylase KDM4C is a functional dependency in JAK2-mutated neoplasms.

Mutations of the JAK2 gene are frequent aberrations in the aging hematopoietic system and in myeloid neoplasms. While JAK-inhibitors efficiently reduce hyperinflammation induced by the constitutively active mutated JAK2 kinase, the malignant clone and abundance of mutated cells remains rather unaffected. Here, we sought to assess for genetic vulnerabilities of JAK2-mutated clones. We identified lysine-specific demethylase KDM4C as a selective genetic dependency that persists upon JAK-inhibitor treatment. Genetic inactivation of KDM4C in human and murine JAK2-mutated cells resulted in loss of cell competition and reduced proliferation. These findings led to reduced disease penetrance and improved survival in xenograft models of human JAK2-mutated cells. KDM4C deleted cells showed alterations in target histone residue methylation and target gene expression, resulting in induction of cellular senescence. In summary, these data establish KDM4C as a specific dependency and therapeutic target in JAK2-mutated cells that is essential for oncogenic signaling and prevents induction of senescence.

Dual Skip Connections Minimize the False Positive Rate of Lung Nodule Detection in CT images.

Pulmonary cancer is one of the most commonly diagnosed and fatal cancers and is often diagnosed by incidental findings on computed tomography. Automated pulmonary nodule detection is an essential part of computer-aided diagnosis, which is still facing great challenges and difficulties to quickly and accurately locate the exact nodules' positions. This paper proposes a dual skip connection upsampling strategy based on Dual Path network in a U-Net structure generating multiscale feature maps, which aims to minimize the ratio of false positives and maximize the sensitivity for lesion detection of nodules. The results show that our new upsampling strategy improves the performance by having 85.3% sensitivity at 4 FROC per image compared to 84.2% for the regular upsampling strategy or 81.2% for VGG16-based Faster-R-CNN.

Fully automated deep learning-based localization and segmentation of the locus coeruleus in aging and Parkinson's disease using neuromelanin-sensitive MRI.

PURPOSE: Development and performance measurement of a fully automated pipeline that localizes and segments the locus coeruleus in so-called neuromelanin-sensitive magnetic resonance imaging data for the derivation of quantitative biomarkers of neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease. METHODS: We propose a pipeline composed of several 3D-Unet-based convolutional neural networks for iterative multi-scale localization and multi-rater segmentation and non-deep learning-based components for automated biomarker extraction. We trained on the healthy aging cohort and did not carry out any adaption or fine-tuning prior to the application to Parkinson's disease subjects. RESULTS: The localization and segmentation pipeline demonstrated sufficient performance as measured by Euclidean distance (on average around 1.3mm on healthy aging subjects and 2.2mm in Parkinson's disease subjects) and Dice similarity coefficient (overall around [Formula: see text] on healthy aging subjects and [Formula: see text] for subjects with Parkinson's disease) as well as promising agreement with respect to contrast ratios in terms of intraclass correlation coefficient of [Formula: see text] for healthy aging subjects compared to a manual segmentation procedure. Lower values ([Formula: see text]) for Parkinson's disease subjects indicate the need for further investigation and tests before the application to clinical samples. CONCLUSION: These promising results suggest the usability of the proposed algorithm for data of healthy aging subjects and pave the way for further investigations using this approach on different clinical datasets to validate its practical usability more conclusively.

Molecular Mechanisms of Senescence and Implications for the Treatment of Myeloid Malignancies.

Senescence is a cellular state that is involved in aging-associated diseases but may also prohibit the development of pre-cancerous lesions and tumor growth. Senescent cells are actively secreting chemo- and cytokines, and this senescence-associated secretory phenotype (SASP) can contribute to both early anti-tumorigenic and long-term pro-tumorigenic effects. Recently, complex mechanisms of cellular senescence and their influence on cellular processes have been defined in more detail and, therefore, facilitate translational development of targeted therapies. In this review, we aim to discuss major molecular pathways involved in cellular senescence and potential therapeutic strategies, with a specific focus on myeloid malignancies.

CHAOS Challenge - combined (CT-MR) healthy abdominal organ segmentation.

Segmentation of abdominal organs has been a comprehensive, yet unresolved, research field for many years. In the last decade, intensive developments in deep learning (DL) introduced new state-of-the-art segmentation systems. Despite outperforming the overall accuracy of existing systems, the effects of DL model properties and parameters on the performance are hard to interpret. This makes comparative analysis a necessary tool towards interpretable studies and systems. Moreover, the performance of DL for emerging learning approaches such as cross-modality and multi-modal semantic segmentation tasks has been rarely discussed. In order to expand the knowledge on these topics, the CHAOS - Combined (CT-MR) Healthy Abdominal Organ Segmentation challenge was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI), 2019, in Venice, Italy. Abdominal organ segmentation from routine acquisitions plays an important role in several clinical applications, such as pre-surgical planning or morphological and volumetric follow-ups for various diseases. These applications require a certain level of performance on a diverse set of metrics such as maximum symmetric surface distance (MSSD) to determine surgical error-margin or overlap errors for tracking size and shape differences. Previous abdomen related challenges are mainly focused on tumor/lesion detection and/or classification with a single modality. Conversely, CHAOS provides both abdominal CT and MR data from healthy subjects for single and multiple abdominal organ segmentation. Five different but complementary tasks were designed to analyze the capabilities of participating approaches from multiple perspectives. The results were investigated thoroughly, compared with manual annotations and interactive methods. The analysis shows that the performance of DL models for single modality (CT / MR) can show reliable volumetric analysis performance (DICE: 0.98 ± 0.00 / 0.95 ± 0.01), but the best MSSD performance remains limited (21.89 ± 13.94 / 20.85 ± 10.63 mm). The performances of participating models decrease dramatically for cross-modality tasks both for the liver (DICE: 0.88 ± 0.15 MSSD: 36.33 ± 21.97 mm). Despite contrary examples on different applications, multi-tasking DL models designed to segment all organs are observed to perform worse compared to organ-specific ones (performance drop around 5%). Nevertheless, some of the successful models show better performance with their multi-organ versions. We conclude that the exploration of those pros and cons in both single vs multi-organ and cross-modality segmentations is poised to have an impact on further research for developing effective algorithms that would support real-world clinical applications. Finally, having more than 1500 participants and receiving more than 550 submissions, another important contribution of this study is the analysis on shortcomings of challenge organizations such as the effects of multiple submissions and peeking phenomenon.

Polymethine Dye-Functionalized Nanoparticles for Targeting CML Stem Cells.

In chronic myelogenous leukemia (CML), treatment with tyrosine kinase inhibitors (TKI) is unable to eradicate leukemic stem cells (LSC). Polymethine dye-functionalized nanoparticles can be internalized by specific cell types using transmembrane carrier proteins. In this study we investigated the uptake behavior of various polymethine dyes on leukemia cell lines and searched for carrier proteins that guide dye transport using RNA interference. The results show that the uptake of DY-635 is dependent on organic anion transport protein 1B3 (OATP1B3) in CML cells and immature myeloid precursor cells of CML patients. In contrast to nonspecific poly(lactide-co-glycolic acid) (PLGA) nanoparticle constructs, DY-635-functionalization of nanoparticles led to an uptake in CML cells. Investigation of these nanoparticles on bone marrow of CML patients showed a preferred uptake in LSC. The transcription of OATP1B3 is known to be induced under hypoxic conditions via the hypoxia-inducing factor 1 alpha (HIF1α), thus also in the stem cells niche. Since these cells have the potential to repopulate the bone marrow after CML treatment discontinuation, eliminating them by means of drug-loaded DY-635-functionalized PLGA nanoparticles deployed as a selective delivery system to LSC is highly relevant to the ongoing search for curative treatment options for CML patients.

Correction: Frequency of infections in 948 MPN patients: a prospective multicenter patient-reported pilot study.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Only SETBP1 hotspot mutations are associated with refractory disease in myeloid malignancies.

INTRODUCTION: SETBP1 mutations have been established as a diagnostic marker in myeloid malignancies and are associated with inferior survival. Since there is limited data on their clinical impact and stability during disease progression, we sought to investigate the relationship between SETBP1 mutations and disease evolution. METHODS: Bidirectional Sanger sequencing of the SETBP1 gene was performed for 442 unselected patients with World Health Organization (WHO) defined myeloid disorders. Follow-up analysis was performed on samples from 123/442 patients to investigate SETBP1 mutation dynamics. Targeted deep next-generation sequencing for a panel of 30 leukemia-associated genes was established to study SETBP1 cooperating mutations. RESULTS: 10/442 patients (2.3%) had SETBP1 hotspot mutations (MDS/MPN, n = 7, sAML, n = 3), whereas four patients (1%) had SETBP1 non-hotspot mutations (MPN, n = 1; MDS, n = 2; sAML, n = 1). The median overall survival for patients with SETBP1 hotspot mutations, SETBP1 non-hotspot mutations, and SETBP1 wild type was 14 (range 0-31), 50 (range 0-71), and 47 months (range 0-402), respectively. In Kaplan-Meier analysis, SETBP1 hotspot mutations were significantly associated with reduced overall survival compared to SETBP1 non-hotspot mutations and the SETBP1 wild type (p < 0.001). All 10 patients with SETBP1 hotspot mutations died from relapse or disease progression. Three of four patients with SETBP1 non-hotspot mutations are alive with stable disease. Cooperating CSF3R and TET2 mutations were most frequently observed in patients with SETBP1 hotspot mutations. CONCLUSIONS: Patients with SETBP1 hotspot mutations suffered from aggressive disease with rapid evolution and inferior overall survival. Patients with SETBP1 non-hotspot mutations had less aggressive disease and a more favorable prognosis. Diagnostic screens for SETBP1 hotspot mutations may help identifying this dismal patient group and treat them in multicenter clinical studies.