Modulation of CD4+ human Treg and Tconv cells by inhibition of the acid sphingomyelinase in vitro

Die saure Sphingomyelinase (ASM) stellt durch die Umwandlung von Sphingomyelin in Ceramid und Phosphorylcholin ein zentrales, fein reguliertes Enzym im Sphingolipidmetabolismus dar. Dadurch nimmt es Einfluss auf verschiedene zelluläre Mechanismen wie Signalvermittlung, Endo- und Exozytose und Zellaktivierung. Dementsprechend weitreichend ist auch die Bedeutung der ASM bei verschiedenen Krankheiten wie Arteriosklerose, Depression oder Neoplasien. Auch auf das Immunsystem, insbesondere auf die Signalvermittlung durch T-Zellen innerhalb des adaptiven Immunsystems, nimmt die saure Sphingomyelinase Einfluss. Aufbauend auf früheren Forschungsarbeiten zur pharmakologischen und genetischen Hemmung der ASM im Mausmodell untersuchten wir, welche Auswirkungen die Hemmung dieses Enzyms in humanen Zellkulturen auf die Population regulatorischer und konventioneller T-Zellen haben. Hierzu verwendeten wir die beiden selektiven Serotonin-Wiederaufnahmehemmer Sertralin und Citalopram; zwei antidepressiv wirksame Medikamente, die durch eine Verdrängung der ASM von der lysosomalen Membran eine hemmende Wirkung ausüben. Wir konnten zeigen, dass diese beiden Substanzen sowohl in Maus-T-Zellen, als auch in humanen T-Zellen, in der Lage sind, die Aktivität der sauren Sphingomyelinase zu inhibieren. Durch Kultivierung von Immunzellen der Maus zusammen mit den Inhibitoren konnte darüber hinaus eine Erhöhung der Treg-Zellfrequenz erreicht werden. Verschiedene Zellkulturexperimente mit humanen PBMCs zeigten weiterhin, dass unter gewissen Umständen so auch eine Vermehrung regulatorischer T-Zellen im Menschen möglich ist, und dass dies mutmaßlich durch Einbindung der ASM im CD3/CD28-Signalweg bedingt ist. In mit AntiCD3-Antikörper stimulierten experimentellen Ansätzen kam es jedoch nur bei einzelnen Individuen, die als Responder identifiziert werden konnten, zu einer Treg-Zellvermehrung. Umgekehrt kam es durch externe Zugabe von C6-Ceramid zu einer Verringerung des Anteils an regulatorischen T-Zellen. Des Weiteren wurden verschiedene Veränderungen im Expressionsverhalten von Treg- und Tconv-Zellen bezüglich CD25, CD69 und CTLA-4 in Anwesenheit der ASMInhibitoren beobachtet. Weiterhin bestätigte sich, dass die pharmakologische Hemmung der sauren Sphingomyelinase auch Auswirkungen auf die Effektorfunktion von T-Zellen hat. Während die Proliferation der Zellen weitgehend unbeeinträchtigt blieb, kam es zu einer verringerten Sekretion der Zytokine IFN-gamma, TNF, IL-5 und IL-10. In ihrer Gesamtheit sprechen diese Ergebnisse dafür, dass Inhibitoren der sauren Sphingomyelinase begünstigend auf Krankheitsgeschehen mit überschießender oder dysregulierter Aktivität des Immunsystems einwirken könnten. Immunmodulatorischen Wirkungen durch Inhibition der ASM erklären möglicherweise auch Einflüsse auf das Immunsystem, die für verschiedene Antidepressiva beschrieben wurden. Insgesamt ist die Bedeutung der sauren Sphingomyelinase innerhalb der Regulation des adaptiven Immunsystems jedoch noch ein weitgehend ungeklärtes Thema mit vielen offenen Fragen. Daher ist auch in Zukunft weitere klinische und experimentelle Forschung erforderlich, um zu klären, welchen Einfluss dieses Enzyms auf Immunzellen hat und wie sich dieser auch klinisch anwenden lässt.By catalyzing the transformation of sphingomyeline into ceramide and phosphocholine, the acid sphingomyelinase (ASM) plays a central role in the metabolism of sphingolipids and is tightly regulated. Therefore it takes essential influence upon different cellular mechanisms like signal transduction, endo-/exocytosis and cell activation. Accordingly complex is the importance of the ASM in different diseases like atherosclerosis, depression or neoplastic diseases. The acid sphingomyelinase also greatly influences the signal mediation of T cells within the adaptive immune system. Based on previous research about the pharmacological and genetic inhibition of the ASM in mice we investigated, which impact an inhibition of this enzyme in human cell cultures may have on the populations of regulatory and conventional T cells. Therefore we mostly used the two selective serotonin reuptake inhibitors sertraline and citalopram. These two antidepressive drugs detach the ASM from the lysosomal membrane and thereby inhibit the enzyme. Here we show, that these two substances efficiently inhibit the ASM mice T cells as well as human T cells. Cultivating immune cells of mice together with the inhibitors led to an essential increase in the frequency of regulatory T cells. Various cell culture experiments with human PBMCs showed that under certain circumstances an increase in regulatory T cells is also possible in the human, most likely due to the involvement of the ASM in the CD3/CD28 signal pathway. Experimental approaches using � CD3-antibodies showed an increase in Treg cells in a fraction of the tested individuals. External addition of C6-ceramide led to a decrease in the frequency of regulatory T cells. In addition to that, we were able to observe diverse effects regarding the expression of CD25, CD69 and CTLA-4 in Treg and Tconv cells in the presence of the ASM-inhibitors. We were also able to confirm that the pharmacological inhibition of the acid sphingomyelinase has an impact on the effector functions of T cells. While there was no effect on cell proliferation, we observed a decreased secretion of the cytokines IFN-gamma, TNF, IL-5 and IL-10. Alltogether these results indicate that inhibitors of the acid sphingomyelinase might have positive effects in pathologies of overshooting or dysregulated activity of the immune system. Immunomodulatory effects after inhibition of the ASM might also explain observations of an influence of antidepressants on the immune system that have been described in the literature. Overall the importance of the acid sphingomyelinase within the regulation of the adaptive immune system is a new field of research with many open questions. Therefore further clinical and experimental research is needed to clarify, which impact this enzyme has on immune cells and how this impact might be used therapeutically

Creation of clinical algorithms for decision-making in oncology: an example with dose prescription in radiation oncology.

In oncology, decision-making in individual situations is often very complex. To deal with such complexity, people tend to reduce it by relying on their initial intuition. The downside of this intuitive, subjective way of decision-making is that it is prone to cognitive and emotional biases such as overestimating the quality of its judgements or being influenced by one's current mood. Hence, clinical predictions based on intuition often turn out to be wrong and to be outperformed by statistical predictions. Structuring and objectivizing oncological decision-making may thus overcome some of these issues and have advantages such as avoidance of unwarranted clinical practice variance or error-prevention. Even for uncertain situations with limited medical evidence available or controversies about the best treatment option, structured decision-making approaches like clinical algorithms could outperform intuitive decision-making. However, the idea of such algorithms is not to prescribe the clinician which decision to make nor to abolish medical judgement, but to support physicians in making decisions in a systematic and structured manner. An example for a use-case scenario where such an approach may be feasible is the selection of treatment dose in radiation oncology. In this paper, we will describe how a clinical algorithm for selection of a fractionation scheme for palliative irradiation of bone metastases can be created. We explain which steps in the creation process of a clinical algorithm for supporting decision-making need to be  performed and which challenges and limitations have to be considered

(Common) Data Elements in Radiation Oncology: A Systematic Literature Review.

PURPOSE Structured medical data documentation is highly relevant in a data-driven discipline such as radiation oncology. Defined (common) data elements (CDEs) can be used to record data in clinical trials, health records, or computer systems for improved standardization and data exchange. The International Society for Radiation Oncology Informatics initiated a project for a scientific literature analysis of defined data elements for structured documentation in radiation oncology. METHODS We performed a systematic literature review on both PubMed and Scopus to analyze publications relevant to the utilization of specified data elements for the documentation of radiation therapy (RT)-related information. Relevant publications were retrieved as full-text and searched for published data elements. Finally, the extracted data elements were quantitatively analyzed and classified. RESULTS We found a total of 452 publications, of which 46 were considered relevant for structured data documentation. Twenty-nine publications addressed defined RT-specific data elements, of which 12 publications provided data elements. Only two publications focused on data elements in radiation oncology. The 29 analyzed publications were heterogeneous regarding the subject and usage of the defined data elements, and different concepts/terms for defined data elements were used. CONCLUSION The literature about structured data documentation in radiation oncology using defined data elements is scarce. There is a need for a comprehensive list of RT-specific CDEs the radio-oncologic community can rely on. As it has been done in other medical fields, establishing such a list would be of great value for clinical practice and research as it would promote interoperability and standardization

Parameters of the Lyman model for calculation of normal tissue complication probability: a systematic literature review.

PURPOSE The Lyman model is one of the most used radiobiological models for calculation of Normal Tissue Complication Probability (NTCP). Since its introduction in 1985 many authors have published parameter values for the model based on clinical data of different radiotherapeutic situations. We attempted to collect the entirety of radiobiological parameter sets published until now and to provide an overview of the data basis for different variations of the model. Furthermore, we sought to compare the parameter values and calculated NTCPs for selected endpoints with sufficient data available. METHODS AND MATERIALS A systematic literature analysis was performed searching for publications that provided parameters for the different variations of the Lyman model in the Medline database using PubMed. Parameter sets were grouped into 13 toxicity-related endpoint groups. For three selected endpoint groups "reduction of saliva ≤ 25% twelve months after irradiation of the parotid", "symptomatic pneumonitis after irradiation of the lung" and "bleeding ≥ grade 2 after irradiation of the rectum", we compared parameter values and analyzed differences in calculated NTCP values. RESULTS A total of 509 parameter sets from 130 publications were identified. We detected considerable heterogeneities regarding the number of parameters available for different radiooncological situations. Furthermore, for the three selected endpoints we found large differences in published parameter values. These translate into great variations of calculated NTCPs, with maximum ranges of 35.2%-93.4% for the saliva endpoint, of 39.4%-90.4% for the pneumonitis endpoint and of 5.4%-99.3% for the rectal bleeding endpoint. CONCLUSIONS The detected heterogeneity of the data basis as well as the large variations of published radiobiological parameters underline the necessity for careful interpretation when using such parameters for NTCP calculations. Appropriate selection of parameters as well as validation of values is essential when using the Lyman model

Extraction of interoperable data from healthcare documents by identifying Common Data Elements: an analysis of Radiation Therapy Planning CT Physician Order Entry records.

INTRODUCTION Documentation as well as IT-based management of medical data is of ever-increasing relevance in modern medicine. As radiation oncology is a rather technical, data-driven discipline, standardization and data exchange are in principle possible. We examined electronic healthcare documents to extract structured information. Planning CT order entry documents were chosen for the analysis, as this covers a common and structured step in radiation oncology, for which standardized documentation may be achieved. Aim was to examine the extent to which relevant information may be exchanged among different institutions. MATERIALS AND METHODS We contacted representatives of nine radiation oncology departments. Departments using standardized electronic documentation for planning CT were asked to provide templates of their records, which were analyzed in terms of form and content. Structured information was extracted by identifying definite common data elements, containing explicit information. Relevant common data elements were identified and classified. A quantitative analysis was performed to evaluate the possibility of data exchange. RESULTS We received data of seven documents that were heterogeneous regarding form and content. 181 definite common data elements considered relevant for the planning CT were identified and assorted into five semantic groups. 139 data elements (76.8%) were present in only one document. The other 42 data elements were present in two to six documents, while none was shared among all seven documents. CONCLUSION Structured and interoperable documentation of medical information can be achieved using common data elements. Our analysis showed that a lot of information recorded with healthcare documents can be presented with this approach. Yet, in the analyzed cohort of planning CT order entries, only a few common data elements were shared among the majority of documents. A common vocabulary and consensus upon relevant information is required to promote interoperability and standardization

Exploring Capabilities of Large Language Models such as ChatGPT in Radiation Oncology

Purpose: Technological progress of machine learning and natural language processing has led to the development of large language models (LLMs), capable of producing well-formed text responses and providing natural language access to knowledge. Modern conversational LLMs such as ChatGPT have shown remarkable capabilities across a variety of fields, including medicine. These models may assess even highly specialized medical knowledge within specific disciplines, such as radiation therapy. We conducted an exploratory study to examine the capabilities of ChatGPT to answer questions in radiation therapy. Methods and Materials: A set of multiple-choice questions about clinical, physics, and biology general knowledge in radiation oncology as well as a set of open-ended questions were created. These were given as prompts to the LLM ChatGPT, and the answers were collected and analyzed. For the multiple-choice questions, it was checked how many of the answers of the model could be clearly assigned to one of the allowed multiple-choice-answers, and the proportion of correct answers was determined. For the open-ended questions, independent blinded radiation oncologists evaluated the quality of the answers regarding correctness and usefulness on a 5-point Likert scale. Furthermore, the evaluators were asked to provide suggestions for improving the quality of the answers. Results: For 70 multiple-choice questions, ChatGPT gave valid answers in 66 cases (94.3%). In 60.61% of the valid answers, the selected answer was correct (50.0% of clinical questions, 78.6% of physics questions, and 58.3% of biology questions). For 25 open-ended questions, 12 answers of ChatGPT were considered as “acceptable,” “good,” or “very good” regarding both correctness and helpfulness by all 6 participating radiation oncologists. Overall, the answers were considered “very good” in 29.3% and 28%, “good” in 28% and 29.3%, “acceptable” in 19.3% and 19.3%, “bad” in 9.3% and 9.3%, and “very bad” in 14% and 14% regarding correctness/helpfulness. Conclusions: Modern conversational LLMs such as ChatGPT can provide satisfying answers to many relevant questions in radiation therapy. As they still fall short of consistently providing correct information, it is problematic to use them for obtaining medical information. As LLMs will further improve in the future, they are expected to have an increasing impact not only on general society, but also on clinical practice, including radiation oncology

Inhibition of acid sphingomyelinase increases regulatory T cells in humans

Genetic deficiency for acid sphingomyelinase or its pharmacological inhibition has been shown to increase Foxp3$^+$ regulatory T-cell frequencies among CD4$^+$ T cells in mice. We now investigated whether pharmacological targeting of the acid sphingomyelinase, which catalyzes the cleavage of sphingomyelin to ceramide and phosphorylcholine, also allows to manipulate relative CD4$^+$ Foxp3$^+$ regulatory T-cell frequencies in humans. Pharmacological acid sphingomyelinase inhibition with antidepressants like sertraline, but not those without an inhibitory effect on acid sphingomyelinase activity like citalopram, increased the frequency of Foxp3$^+$ regulatory T cell among human CD4$^+$ T cells in vitro. In an observational prospective clinical study with patients suffering from major depression, we observed that acid sphingomyelinase-inhibiting antidepressants induced a stronger relative increase in the frequency of CD4$^+$ Foxp3$^+$ regulatory T cells in peripheral blood than acid sphingomyelinase-non- or weakly inhibiting antidepressants. This was particularly true for CD45RA$^-$ CD25$^{high}$ effector CD4$^+$ Foxp3$^+$ regulatory T cells. Mechanistically, our data indicate that the positive effect of acid sphingomyelinase inhibition on CD4$^+$ Foxp3$^+$ regulatory T cells required CD28 co-stimulation, suggesting that enhanced CD28 co-stimulation was the driver of the observed increase in the frequency of Foxp3+ regulatory T cells among human CD4$^+$ T cells. In summary, the widely induced pharmacological inhibition of acid sphingomyelinase activity in patients leads to an increase in Foxp3+ regulatory T-cell frequencies among CD4$^+$ T cells in humans both in vivo and in vitro