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(1) Background: molecular tumor boards (MTBs) are crucial instruments for discussing and allocating targeted therapies to suitable cancer patients based on genetic findings. Currently, limited evidence is available regarding the regional impact and the outreach component of MTBs; (2) Methods: we analyzed MTB patient data from four neighboring Bavarian tertiary care oncology centers in Würzburg, Erlangen, Regensburg, and Augsburg, together constituting the WERA Alliance. Absolute patient numbers and regional distribution across the WERA-wide catchment area were weighted with local population densities; (3) Results: the highest MTB patient numbers were found close to the four cancer centers. However, peaks in absolute patient numbers were also detected in more distant and rural areas. Moreover, weighting absolute numbers with local population density allowed for identifying so-called white spots—regions within our catchment that were relatively underrepresented in WERA MTBs; (4) Conclusions: investigating patient data from four neighboring cancer centers, we comprehensively assessed the regional impact of our MTBs. The results confirmed the success of existing collaborative structures with our regional partners. Additionally, our results help identifying potential white spots in providing precision oncology and help establishing a joint WERA-wide outreach strategy.
Pilot study on the value of Raman spectroscopy in the entity assignment of salivary gland tumors
(2021)
Background
The entity assignment of salivary gland tumors (SGT) based on histomorphology can be challenging. Raman spectroscopy has been applied to analyze differences in the molecular composition of tissues. The aim of this study was to evaluate the suitability of RS for entity assignment in SGT.
Methods
Raman data were collected in deparaffinized sections of pleomorphic adenomas (PA) and adenoid cystic carcinomas (ACC). Multivariate data and chemometric analysis were completed using the Unscrambler software.
Results
The Raman spectra detected in ACC samples were mostly assigned to nucleic acids, lipids, and amides. In a principal component-based linear discriminant analysis (LDA) 18 of 20 tumor samples were classified correctly.
Conclusion
In this proof of concept study, we show that a reliable SGT diagnosis based on LDA algorithm appears possible, despite variations in the entity-specific mean spectra. However, a standardized workflow for tissue sample preparation, measurement setup, and chemometric algorithms is essential to get reliable results.
The Indigenous tribe called the Wiwa lives retracted in the Sierra Nevada de Santa Marta, Colombia. Little is known about their health status and whether the health care system in place covers their needs. In 2017 and 2018, a permanent physician was in charge for the Wiwa. Diseases and complaints were registered, ranked, and classified with the ICD-10 coding. Datasets from the Indigenous health care provider Dusakawi, collected from local health points and health brigades travelling sporadically into the fields for short visits, were compared. Furthermore, a list of provided medication was evaluated regarding the recorded needs. The most common complaints found were respiratory, infectious and parasitic, and digestive diseases. The top ten diagnoses collected in the health points and in the health brigade datasets were similar, although with a different ranking. The available medication showed a basic coverage only, with a critical lack of treatment for many severe, chronic, and life-threatening diseases. Most of the detected diseases in the Indigenous population are avoidable by an improvement in health care access, an expansion of the provided medication, and an increase in knowledge, hygiene, and life standards.
Due to the wide variety of benign and malignant salivary gland tumors, classification and malignant behavior determination based on histomorphological criteria can be difficult and sometimes impossible. Spectroscopical procedures can acquire molecular biological information without destroying the tissue within the measurement processes. Since several tissue preparation procedures exist, our study investigated the impact of these preparations on the chemical composition of healthy and tumorous salivary gland tissue by Fourier-transform infrared (FTIR) microspectroscopy. Sequential tissue cross-sections were prepared from native, formalin-fixed and formalin-fixed paraffin-embedded (FFPE) tissue and analyzed. The FFPE cross-sections were dewaxed and remeasured. By using principal component analysis (PCA) combined with a discriminant analysis (DA), robust models for the distinction of sample preparations were built individually for each parotid tissue type. As a result, the PCA-DA model evaluation showed a high similarity between native and formalin-fixed tissues based on their chemical composition. Thus, formalin-fixed tissues are highly representative of the native samples and facilitate a transfer from scientific laboratory analysis into the clinical routine due to their robust nature. Furthermore, the dewaxing of the cross-sections entails the loss of molecular information. Our study successfully demonstrated how FTIR microspectroscopy can be used as a powerful tool within existing clinical workflows.
Salivary gland tumors (SGTs) are a relevant, highly diverse subgroup of head and neck tumors whose entity determination can be difficult. Confocal Raman imaging in combination with multivariate data analysis may possibly support their correct classification. For the analysis of the translational potential of Raman imaging in SGT determination, a multi-stage evaluation process is necessary. By measuring a sample set of Warthin tumor, pleomorphic adenoma and non-tumor salivary gland tissue, Raman data were obtained and a thorough Raman band analysis was performed. This evaluation revealed highly overlapping Raman patterns with only minor spectral differences. Consequently, a principal component analysis (PCA) was calculated and further combined with a discriminant analysis (DA) to enable the best possible distinction. The PCA-DA model was characterized by accuracy, sensitivity, selectivity and precision values above 90% and validated by predicting model-unknown Raman spectra, of which 93% were classified correctly. Thus, we state our PCA-DA to be suitable for parotid tumor and non-salivary salivary gland tissue discrimination and prediction. For evaluation of the translational potential, further validation steps are necessary.
In heart failure and atrial fibrillation, a persistent Na\(^+\) current (I\(_{NaL}\)) exerts detrimental effects on cellular electrophysiology and can induce arrhythmias. We have recently shown that Na\(_V\)1.8 contributes to arrhythmogenesis by inducing a I\(_{NaL}\). Genome-wide association studies indicate that mutations in the SCN10A gene (Na\(_V\)1.8) are associated with increased risk for arrhythmias, Brugada syndrome, and sudden cardiac death. However, the mediation of these Na\(_V\)1.8-related effects, whether through cardiac ganglia or cardiomyocytes, is still a subject of controversial discussion. We used CRISPR/Cas9 technology to generate homozygous atrial SCN10A-KO-iPSC-CMs. Ruptured-patch whole-cell patch-clamp was used to measure the I\(_{NaL}\) and action potential duration. Ca\(^{2+}\) measurements (Fluo 4-AM) were performed to analyze proarrhythmogenic diastolic SR Ca\(^{2+}\) leak. The I\(_{NaL}\) was significantly reduced in atrial SCN10A KO CMs as well as after specific pharmacological inhibition of Na\(_V\)1.8. No effects on atrial APD\(_{90}\) were detected in any groups. Both SCN10A KO and specific blockers of Na\(_V\)1.8 led to decreased Ca\(^{2+}\) spark frequency and a significant reduction of arrhythmogenic Ca\(^{2+}\) waves. Our experiments demonstrate that Na\(_V\)1.8 contributes to I\(_{NaL}\) formation in human atrial CMs and that Na\(_V\)1.8 inhibition modulates proarrhythmogenic triggers in human atrial CMs and therefore Na\(_V\)1.8 could be a new target for antiarrhythmic strategies.