Acute left ventricular insufficiency in a Burkitt Lymphoma patient with myocardial involvement and extensive local tumor cell lysis: a case report

BACKGROUND: Burkitt lymphoma (BL) is a rare disease with the sporadic variant accounting for less than 1% of adult non-Hodgkin lymphomas. BL usually presents with an abdominal bulk, but extranodal disease affecting the bone marrow and central nervous system is common. Cardiac manifestations, however, are exceedingly rare, with less than 30 cases reported in the literature. CASE PRESENTATION: We report on a 54-year-old male patient with a six week-long history of paranasal sinus swelling, fatigue and dyspnea on exertion. Stage IV sporadic BL with extensive lymphonodal and cardiovascular involvement was diagnosed. Manifestations included supra- and infradiaphragmatic lymphadenopathy as well as infiltration of the aortic root, the pericardium, the right atrium and the right ventricle. EBV-reactivation was detected, which is uncommon in the sporadic subtype. After initial full-dose chemotherapy with very good BL control, the patient developed acute, but fully reversible cardiac insufficiency. Myocardial lymphoma involvement receded completely during the following two therapy cycles, while cardiac function periodically deteriorated shortly after chemotherapy administration and quickly recovered thereafter. Interestingly, the decline in cardiac function lessened with decreasing myocardial lymphoma manifestation. Once the cardiovascular BL infiltration was resolved, cardiac function remained stable throughout further treatment. Following seven cycles of chemotherapy and mediastinal radiation, the patient is now in continued complete remission. CONCLUSIONS: Although rare, cardiac involvement in BL can quickly become life-threatening due to rapid lymphoma doubling time and should therefore be considered at initial diagnosis. This case suggests an association between myocardial infiltration, chemotherapy associated tumor cell lysis and transient deterioration of cardiac function until the damage caused by the underlying lymphoma could be restored. While additional studies are needed to further elucidate the mechanisms of acute cardiac insufficiency due to lymphoma lysis in the infiltrated structures, prompt BL control and full recovery of the patient supports courageous treatment start despite extensive cardiovascular involvement

Flow cytometry can reliably capture gut microbial composition in healthy adults as well as dysbiosis dynamics in patients with aggressive B-cell non-Hodgkin lymphoma

Modulation of commensal gut microbiota is increasingly recognized as a promising strategy to reduce mortality in patients with malignant diseases, but monitoring for dysbiosis is generally not routine clinical practice due to equipment, expertise and funding required for sequencing analysis. A low-threshold alternative is microbial diversity profiling by single-cell flow cytometry (FCM), which we compared to 16S rRNA sequencing in human fecal samples and employed to characterize longitudinal changes in the microbiome composition of patients with aggressive B-cell non-Hodgkin lymphoma undergoing chemoimmunotherapy. Diversity measures obtained from both methods were correlated and captured identical trends in microbial community structures, finding no difference in patients' pretreatment alpha or beta diversity compared to healthy controls and a significant and progressive loss of alpha diversity during chemoimmunotherapy. Our results highlight the potential of FCM-based microbiome profiling as a reliable and accessible diagnostic tool that can provide novel insights into cancer therapy-associated dysbiosis dynamics

Comorbidities rather than older age define outcome in adult patients with tumors of the Ewing sarcoma family

BACKGROUND: Ewing family of tumors (EFT) is rarely diagnosed in patients (pts) over the age of 18 years (years), and data on the clinical course and the outcome of adult EFT pts is sparse. METHODS: In this retrospective analysis, we summarize our experience with adult EFT pts. From 2002 to 2020, we identified 71 pts of whom 58 were evaluable for the final analysis. RESULTS: Median age was 31 years (18-90 years). Pts presented with skeletal (n = 26), and extra-skeletal primary disease (n =32). Tumor size was ≥8 cm in 20 pts and 19 pts were metastasized at first diagnosis. Between the age groups (≤25 vs. 26-40 vs. ≥41 years) we observed differences of Charlson comorbidity index (CCI), tumor origin, as well as type and number of therapy cycles. Overall, median overall survival (OS) was 79 months (95% confidence interval, CI; 28.5-131.4 months), and median progression-free survival (PFS) 34 months (95% CI; 21.4-45.8 months). We observed a poorer outcome (OS, PFS) in older pts. This could be in part due to differences in treatment intensity and the CCI (<3 vs. ≥3; hazard ratio, HR 0.334, 95% CI 0.15-0.72, p = 0.006). In addition, tumor stage had a significant impact on PFS (localized vs. metastasized stage: HR 0.403, 95% CI 0.18-0.87, p = 0.021). CONCLUSIONS: Our data confirms the feasibility of intensive treatment regimens in adult EFT pts. While in our cohort outcome was influenced by age, due to differences in treatment intensity, CCI, and tumor stage, larger studies are warranted to further explore optimized treatment protocols in adult EFT pts

Combination therapy with Olaratumab/doxorubicin in advanced or metastatic soft tissue sarcoma -a single-Centre experience

BACKGROUND: The antibody targeting platelet-derived growth factor receptor alpha (PDGFRA), olaratumab, was approved in 2016 for metastatic soft tissue sarcoma (STS) in combination with doxorubicin based on promising results of a phase Ib/II trial by the Food and Drug Administration (FDA). However, recently the phase III ANNOUNCE trial could not confirm the additional value of olaratumab in this context. METHODS: Here, in a retrospective analysis we share our single-centre experience with olaratumab/doxorubicin in STS by including n = 32 patients treated with olaratumab/doxorubicin between 2016 and 2019. RESULTS: Median progression-free survival (PFS) in the overall cohort was 3.1 months (range 0.6-16.2). A response [complete remission (CR), partial remission (PR) or stable disease (SD)] was seen in n = 11 (34%) cases, whereas n = 21 (66%) patients showed progressive disease (PD). In n = 9 patients surgery was performed subsequently in an individual therapeutic approach. Out of n = 5 patients receiving additional regional hyperthermia, n = 3 achieved PR or SD. CONCLUSIONS: This single-centre experience does also not support the promising phase Ib/II results for olaratumab/doxorubicin in STS. However, our findings do not preclude that olaratumab combination therapy could be valuable in a neoadjuvant setting. This warrants further exploration also taking into account the heterogeneous nature of STS

PEtab -- interoperable specification of parameter estimation problems in systems biology

Reproducibility and reusability of the results of data-based modeling studies are essential. Yet, there has been -- so far -- no broadly supported format for the specification of parameter estimation problems in systems biology. Here, we introduce PEtab, a format which facilitates the specification of parameter estimation problems using Systems Biology Markup Language (SBML) models and a set of tab-separated value files describing the observation model and experimental data as well as parameters to be estimated. We already implemented PEtab support into eight well-established model simulation and parameter estimation toolboxes with hundreds of users in total. We provide a Python library for validation and modification of a PEtab problem and currently 20 example parameter estimation problems based on recent studies. Specifications of PEtab, the PEtab Python library, as well as links to examples, and all supporting software tools are available at https://github.com/PEtab-dev/PEtab, a snapshot is available at https://doi.org/10.5281/zenodo.3732958. All original content is available under permissive licenses

Impact of a specialised palliative care intervention in patients with advanced soft tissue sarcoma - a single-centre retrospective analysis

BACKGROUND: Soft tissue sarcomas (STS) account for less than 1% of all malignancies. Approximately 50% of the patients develop metastases with limited survival in the course of their disease. For those patients, palliative treatment aiming at symptom relief and improvement of quality of life is most important. However, data on symptom burden and palliative intervention are limited in STS patients. AIM: Our study evaluates the effectiveness of a palliative care intervention on symptom relief and quality of life in STS patients. DESIGN/SETTING: We retrospectively analysed 53 inpatient visits of 34 patients with advanced STS, admitted to our palliative care unit between 2012 and 2018. Symptom burden was measured with a standardised base assessment questionnaire at admission and discharge. RESULTS: Median disease duration before admission was 24 months, 85% of patients had metastases. The predominant indication for admission was pain, weakness and fatigue. Palliative care intervention led to a significant reduction of pain: median NRS for acute pain was reduced from 3 to 1 (p < 0.001), pain within the last 24 h from 5 to 2 (p < 0.001) and of the median MIDOS symptom score: 18 to 13 (p < 0.001). Also, the median stress level, according to the distress thermometer, was reduced significantly: 7.5 to 5 (p = 0.027). CONCLUSIONS: Our data underline that specialised palliative care intervention leads to significant symptom relief in patients with advanced STS. Further efforts should aim for an early integration of palliative care in these patients focusing primarily on the identification of subjects at high risk for severe symptomatic disease

TFE3 activation in a TSC1-altered malignant PEComa: challenging the dichotomy of the underlying pathogenic mechanisms

Perivascular epithelioid cell tumors (PEComas) form a family of rare mesenchymal neoplasms that typically display myomelanocytic differentiation. Upregulation of mTOR signaling due the inactivation of TSC1/2 (Tuberous Sclerosis 1 and 2) is believed to be a key oncogenic driver in this disease. Recently, a subgroup of PEComas harboring TFE3 (Transcription Factor E3) rearrangements and presenting with a distinctive morphology has been identified. TSC1/2 and TFE3 aberrations are deemed to be mutually exclusive in PEComa, with two different pathogenic mechanisms assumed to lead to tumorigenesis. Here, we challenge this dichotomy by presenting a case of a clinically aggressive TCS1-mutated PEComa displaying a TFE3-altered phenotype. FISH analysis was suggestive of a TFE3 inversion; however, RNA and whole genome sequencing was ultimately unable to identify a fusion involving the gene. However, a copy number increase of the chromosomal region encompassing TFE3 was detected and transcriptome analysis confirmed upregulation of TFE3, which was also seen at the protein level. Therefore, we believe that the TSC1/2-mTOR pathway and TFE3 overexpression can simultaneously contribute to tumorigenesis in PEComa. Our comprehensive genetic analyses add to the understanding of the complex pathogenic mechanisms underlying PEComa and harbor insights for clinical treatment options

Efficient gradient-based parameter estimation for dynamic models using qualitative data.

MOTIVATION: Unknown parameters of dynamical models are commonly estimated from experimental data. However, while various efficient optimization and uncertainty analysis methods have been proposed for quantitative data, methods for qualitative data are rare and suffer from bad scaling and convergence. RESULTS: Here, we propose an efficient and reliable framework for estimating the parameters of ordinary differential equation models from qualitative data. In this framework, we derive a semi-analytical algorithm for gradient calculation of the optimal scaling method developed for qualitative data. This enables the use of efficient gradient-based optimization algorithms. We demonstrate that the use of gradient information improves performance of optimization and uncertainty quantification on several application examples. On average, we achieve a speedup of more than one order of magnitude compared to gradient-free optimization. Additionally, in some examples, the gradient-based approach yields substantially improved objective function values and quality of the fits. Accordingly, the proposed framework substantially improves the parameterization of models from qualitative data. AVAILABILITY: The proposed approach is implemented in the open-source Python Parameter EStimation TOolbox (pyPESTO). pyPESTO is available at https://github.com/ICB-DCM/pyPESTO. All application examples and code to reproduce this study are available at https://doi.org/10.5281/zenodo.4507613. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online

Parameterization of mechanistic models from qualitative data using an efficient optimal scaling approach.

Quantitative dynamical models facilitate the understanding of biological processes and the prediction of their dynamics. These models usually comprise unknown parameters, which have to be inferred from experimental data. For quantitative experimental data, there are several methods and software tools available. However, for qualitative data the available approaches are limited and computationally demanding. Here, we consider the optimal scaling method which has been developed in statistics for categorical data and has been applied to dynamical systems. This approach turns qualitative variables into quantitative ones, accounting for constraints on their relation. We derive a reduced formulation for the optimization problem defining the optimal scaling. The reduced formulation possesses the same optimal points as the established formulation but requires less degrees of freedom. Parameter estimation for dynamical models of cellular pathways revealed that the reduced formulation improves the robustness and convergence of optimizers. This resulted in substantially reduced computation times. We implemented the proposed approach in the open-source Python Parameter EStimation TOolbox (pyPESTO) to facilitate reuse and extension. The proposed approach enables efficient parameterization of quantitative dynamical models using qualitative data

Benchmarking of numerical integration methods for ODE models of biological systems.

Ordinary differential equation (ODE) models are a key tool to understand complex mechanisms in systems biology. These models are studied using various approaches, including stability and bifurcation analysis, but most frequently by numerical simulations. The number of required simulations is often large, e.g., when unknown parameters need to be inferred. This renders efficient and reliable numerical integration methods essential. However, these methods depend on various hyperparameters, which strongly impact the ODE solution. Despite this, and although hundreds of published ODE models are freely available in public databases, a thorough study that quantifies the impact of hyperparameters on the ODE solver in terms of accuracy and computation time is still missing. In this manuscript, we investigate which choices of algorithms and hyperparameters are generally favorable when dealing with ODE models arising from biological processes. To ensure a representative evaluation, we considered 142 published models. Our study provides evidence that most ODEs in computational biology are stiff, and we give guidelines for the choice of algorithms and hyperparameters. We anticipate that our results will help researchers in systems biology to choose appropriate numerical methods when dealing with ODE models