Prognostic role of lymph node micrometastasis in oral and oropharyngeal cancer: A systematic review.

BACKGROUND: An estimated 20% of patients with oral and oropharyngeal squamous cell carcinoma (OOSCC) have micrometastases (Mi) or isolated tumor cells (ITC) in the cervical lymph nodes that evade detection by standard histological evaluation of lymph node sections. Lymph node Mi and ITC could be one reason for regional recurrence after neck dissection. The aim of this study was to review the existing data regarding the impact of Mi on the survival of patients with OOSCC. METHODS: PubMed and the Cochrane Library were searched for articles reporting the impact of Mi and ITC on patient survival. Two authors independently assessed the methodological quality of retrieved studies using the Downs and Black index. Data were also extracted on study type, number of included patients, mode of histological analysis, statistical analysis, and prognostic impact. RESULTS: Sixteen articles with a total of 2064 patients were included in the review. Among the 16 included studies, eight revealed a statistically significant impact of Mi on at least one endpoint in the Kaplan-Meier and/or multivariate analysis. Three studies regarded Mi as Ma, while five studies found no impact of Mi on survival. Only one study demonstrated an impact of ITC on patient's prognosis in the univariate but not in the multivariate analysis. CONCLUSION: The majority of cases included in the review were patients with oral cancer. The findings provide low-certainty evidence that Mi negatively impacts survival. Data on ITC were scarcer, so no conclusions can be drawn about their effect on survival. The lower threshold to discriminate between Mi and ITC should be defined for OOSCC since the existing thresholds are based on data from different tumors. The histological, immunohistological, and anatomical characteristics of Mi and ITC in OOSCC as well as the effect of radiotherapy on Mi should be further investigated separately for oral and oropharyngeal carcinomas.

[Explainable artificial intelligence in pathology]. / Erklärbare Künstliche Intelligenz in der Pathologie.

With the advancements in precision medicine, the demands on pathological diagnostics have increased, requiring standardized, quantitative, and integrated assessments of histomorphological and molecular pathological data. Great hopes are placed in artificial intelligence (AI) methods, which have demonstrated the ability to analyze complex clinical, histological, and molecular data for disease classification, biomarker quantification, and prognosis estimation. This paper provides an overview of the latest developments in pathology AI, discusses the limitations, particularly concerning the black box character of AI, and describes solutions to make decision processes more transparent using methods of so-called explainable AI (XAI).

Reimbursement in the Context of Precision Oncology Approaches in Metastatic Breast Cancer: Challenges and Experiences.

Background: Precision oncology programs using next-generation sequencing to detect predictive biomarkers are extending therapeutic options for patients with metastatic breast cancer (mBC). Regularly, based on the recommendations of the interdisciplinary molecular tumor board (iMTB), an inclusion in a clinical trial is not possible. In this case, the German health insurance system allows for the application of reimbursement for an off-label drug use. Here, we describe the current challenges and our experience with reimbursement of molecular therapies in mBC. Methods: A total of 100 applications for reimbursement of off-label therapies recommended by an iMTB were filed for patients with mBC, of which 89 were evaluable for this analysis. The approval rate was correlated with the molecular level of evidence of the respective therapy according to the National Center for Tumor Diseases (NCT) and European Society for Medical Oncology Scale for Clinical Actionability of molecular Targets (ESCAT) classification as well as with pretreatment therapy lines. Findings: Overall, 53.9% (48/89) of reimbursement applications were approved. Applications for therapies based on level of evidence m1 (NCT classification), tier I and II (ESCAT classification) had a significantly and clinically relevant increased chance of reimbursement, while a greater number of previous treatment lines had no significantly increased chance of approval, though a trend of approval toward higher treatment lines was detectable. Interpretation: Currently, the German jurisdiction seems to aggravate the clinical implementation of clinically urgently needed molecular therapies.

Toward Explainable Artificial Intelligence for Precision Pathology.

The rapid development of precision medicine in recent years has started to challenge diagnostic pathology with respect to its ability to analyze histological images and increasingly large molecular profiling data in a quantitative, integrative, and standardized way. Artificial intelligence (AI) and, more precisely, deep learning technologies have recently demonstrated the potential to facilitate complex data analysis tasks, including clinical, histological, and molecular data for disease classification; tissue biomarker quantification; and clinical outcome prediction. This review provides a general introduction to AI and describes recent developments with a focus on applications in diagnostic pathology and beyond. We explain limitations including the black-box character of conventional AI and describe solutions to make machine learning decisions more transparent with so-called explainable AI. The purpose of the review is to foster a mutual understanding of both the biomedical and the AI side. To that end, in addition to providing an overview of the relevant foundations in pathology and machine learning, we present worked-through examples for a better practical understanding of what AI can achieve and how it should be done.

NCT/DKFZ MASTER handbook of interpreting whole-genome, transcriptome, and methylome data for precision oncology.

Analysis of selected cancer genes has become an important tool in precision oncology but cannot fully capture the molecular features and, most importantly, vulnerabilities of individual tumors. Observational and interventional studies have shown that decision-making based on comprehensive molecular characterization adds significant clinical value. However, the complexity and heterogeneity of the resulting data are major challenges for disciplines involved in interpretation and recommendations for individualized care, and limited information exists on how to approach multilayered tumor profiles in clinical routine. We report our experience with the practical use of data from whole-genome or exome and RNA sequencing and DNA methylation profiling within the MASTER (Molecularly Aided Stratification for Tumor Eradication Research) program of the National Center for Tumor Diseases (NCT) Heidelberg and Dresden and the German Cancer Research Center (DKFZ). We cover all relevant steps of an end-to-end precision oncology workflow, from sample collection, molecular analysis, and variant prioritization to assigning treatment recommendations and discussion in the molecular tumor board. To provide insight into our approach to multidimensional tumor profiles and guidance on interpreting their biological impact and diagnostic and therapeutic implications, we present case studies from the NCT/DKFZ molecular tumor board that illustrate our daily practice. This manual is intended to be useful for physicians, biologists, and bioinformaticians involved in the clinical interpretation of genome-wide molecular information.

A Retrospective Analysis of Biliary Tract Cancer Patients Presented to the Molecular Tumor Board at the Comprehensive Cancer Center Munich.

BACKGROUND AND OBJECTIVE: With the rising importance of precision oncology in biliary tract cancer (BTC), the aim of this retrospective single-center analysis was to describe the clinical and molecular characteristics of patients with BTC who underwent comprehensive genomic profiling (CGP) and were discussed in the CCCMunichLMU molecular tumor board (MTB). PATIENTS AND METHODS: In this single-center observational study, we included BTC patients with intrahepatic cholangiocarcinoma (iCCA), extrahepatic CCA (eCCA), and gallbladder cancer (GB), who had been discussed in the institutional MTB from May 29, 2017, to July 25, 2022. Patients were followed up until 31 January 2023. Data were retrospectively collected by review of medical charts, and MTB recommendation. RESULTS: In total, 153 cases were registered to the MTB with a median follow-up of 15 months. Testing was successful in 81.7% of the patients. CGP detected targetable alterations in 35.3% of our BTC patients (most commonly ARID1A/ERBB2/IDH1/PIK3CA/BRAF-mutations and FGFR2-fusions). Recommendations for molecularly guided therapy were given in 46.4%. Of those, treatment implementation of targeted therapy followed in 19.4%. In patients receiving the recommended treatment, response rate was 57% and median overall survival was 19 months (vs 8 months in the untreated cohort). The progression-free survival ratio of 1.45 suggest a clinical benefit of molecularly guided treatment. CONCLUSIONS: In line with previous work, our series demonstrates feasibility and clinical utility of comprehensive genomic profiling in BTC patients. With the growing number of targeted agents with clinical activity in BTC, CGP should become standard of care in the management of this group of patients.

Targeted therapy of advanced parathyroid carcinoma guided by genomic and transcriptomic profiling.

Parathyroid carcinoma (PC) is an ultra-rare malignancy with a high risk of recurrence after surgery. Tumour-directed systemic treatments for PC are not established. We used whole-genome and RNA sequencing in four patients with advanced PC to identify molecular alterations that could guide clinical management. In two cases, the genomic and transcriptomic profiles provided targets for experimental therapies that resulted in biochemical response and prolonged disease stabilization: (a) immune checkpoint inhibition with pembrolizumab based on high tumour mutational burden and a single-base substitution signature associated with APOBEC (apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like) overactivation; (b) multi-receptor tyrosine kinase inhibition with lenvatinib due to overexpression of FGFR1 (Fibroblast Growth Factor Receptor 1) and RET (Ret Proto-Oncogene) and, (c) later in the course of the disease, PARP (Poly(ADP-Ribose) Polymerase) inhibition with olaparib prompted by signs of defective homologous recombination DNA repair. In addition, our data provided new insights into the molecular landscape of PC with respect to the genome-wide footprints of specific mutational processes and pathogenic germline alterations. These data underscore the potential of comprehensive molecular analyses to improve care for patients with ultra-rare cancers based on insight into disease biology.

Transcriptome profiling for precision cancer medicine using shallow nanopore cDNA sequencing.

Transcriptome profiling is a mainstay of translational cancer research and is increasingly finding its way into precision oncology. While bulk RNA sequencing (RNA-seq) is widely available, high investment costs and long data return time are limiting factors for clinical applications. We investigated a portable nanopore long-read sequencing device (MinION, Oxford Nanopore Technologies) for transcriptome profiling of tumors. In particular, we investigated the impact of lower coverage than that of larger sequencing devices by comparing shallow nanopore RNA-seq data with short-read RNA-seq data generated using reversible dye terminator technology (Illumina) for ten samples representing four cancer types. Coupled with ShaNTi (Shallow Nanopore sequencing for Transcriptomics), a newly developed data processing pipeline, a turnaround time of five days was achieved. The correlation of normalized gene-level counts between nanopore and Illumina RNA-seq was high for MinION but not for very low-throughput Flongle flow cells (r = 0.89 and r = 0.24, respectively). A cost-saving approach based on multiplexing of four samples per MinION flow cell maintained a high correlation with Illumina data (r = 0.56-0.86). In addition, we compared the utility of nanopore and Illumina RNA-seq data for analysis tools commonly applied in translational oncology: (1) Shallow nanopore and Illumina RNA-seq were equally useful for inferring signaling pathway activities with PROGENy. (2) Highly expressed genes encoding kinases targeted by clinically approved small-molecule inhibitors were reliably identified by shallow nanopore RNA-seq. (3) In tumor microenvironment composition analysis, quanTIseq performed better than CIBERSORT, likely due to higher average expression of the gene set used for deconvolution. (4) Shallow nanopore RNA-seq was successfully applied to detect fusion genes using the JAFFAL pipeline. These findings suggest that shallow nanopore RNA-seq enables rapid and biologically meaningful transcriptome profiling of tumors, and warrants further exploration in precision cancer medicine studies.

Bcl-xL as prognostic marker and potential therapeutic target in cholangiocarcinoma.

Intrahepatic, perihilar, and distal cholangiocarcinoma (iCCA, pCCA, dCCA) are highly malignant tumours with increasing mortality rates due to therapy resistances. Among the mechanisms mediating resistance, overexpression of anti-apoptotic Bcl-2 proteins (Bcl-2, Bcl-xL , Mcl-1) is particularly important. In this study, we investigated whether antiapoptotic protein patterns are prognostically relevant and potential therapeutic targets in CCA. Bcl-2 proteins were analysed in a pan-cancer cohort from the NCT/DKFZ/DKTK MASTER registry trial (n = 1140, CCA n = 72) via RNA-sequencing and transcriptome-based protein activity interference revealing high ranks of CCA for Bcl-xL and Mcl-1. Expression of Bcl-xL , Mcl-1, and Bcl-2 was assessed in human CCA tissue and cell lines compared with cholangiocytes by immunohistochemistry, immunoblotting, and quantitative-RT-PCR. Immunohistochemistry confirmed the upregulation of Bcl-xL and Mcl-1 in iCCA tissues. Cell death of CCA cell lines upon treatment with specific small molecule inhibitors of Bcl-xL (Wehi-539), of Mcl-1 (S63845), and Bcl-2 (ABT-199), either alone, in combination with each other or together with chemotherapeutics was assessed by flow cytometry. Targeting Bcl-xL induced cell death and augmented the effect of chemotherapy in CCA cells. Combined inhibition of Bcl-xL and Mcl-1 led to a synergistic increase in cell death in CCA cell lines. Correlation between Bcl-2 protein expression and survival was analysed within three independent patient cohorts from cancer centers in Germany comprising 656 CCA cases indicating a prognostic value of Bcl-xL in CCA depending on the CCA subtype. Collectively, these observations identify Bcl-xL as a key protein in cell death resistance of CCA and may pave the way for clinical application.

Comprehensive genomic and epigenomic analysis in cancer of unknown primary guides molecularly-informed therapies despite heterogeneity.

The benefit of molecularly-informed therapies in cancer of unknown primary (CUP) is unclear. Here, we use comprehensive molecular characterization by whole genome/exome, transcriptome and methylome analysis in 70 CUP patients to reveal substantial mutational heterogeneity with TP53, MUC16, KRAS, LRP1B and CSMD3 being the most frequently mutated known cancer-related genes. The most common fusion partner is FGFR2, the most common focal homozygous deletion affects CDKN2A. 56/70 (80%) patients receive genomics-based treatment recommendations which are applied in 20/56 (36%) cases. Transcriptome and methylome data provide evidence for the underlying entity in 62/70 (89%) cases. Germline analysis reveals five (likely) pathogenic mutations in five patients. Recommended off-label therapies translate into a mean PFS ratio of 3.6 with a median PFS1 of 2.9 months (17 patients) and a median PFS2 of 7.8 months (20 patients). Our data emphasize the clinical value of molecular analysis and underline the need for innovative, mechanism-based clinical trials.

Gene expression-based prediction of pazopanib efficacy in sarcoma.

BACKGROUND: The multi-receptor tyrosine kinase inhibitor pazopanib is approved for the treatment of advanced soft-tissue sarcoma and has also shown activity in other sarcoma subtypes. However, its clinical efficacy is highly variable, and no reliable predictors exist to select patients who are likely to benefit from this drug. PATIENTS AND METHODS: We analysed the molecular profiles and clinical outcomes of patients with pazopanib-treated sarcoma enrolled in a prospective observational study by the German Cancer Consortium, DKTK MASTER, that employs whole-genome/exome sequencing and transcriptome sequencing to inform the care of young adults with advanced cancer across histology and patients with rare cancers. RESULTS: Among 109 patients with available whole-genome/exome sequencing data, there was no correlation between clinical parameters, specific genetic alterations or mutational signatures and clinical outcome. In contrast, the analysis of a subcohort of 62 patients who underwent molecular analysis before pazopanib treatment and had transcriptome sequencing data available showed that mRNA levels of NTRK3 (hazard ratio [HR] = 0.53, p = 0.021), IGF1R (HR = 1.82, p = 0.027) and KDR (HR = 0.50, p = 0.011) were independently associated with progression-free survival (PFS). Based on the expression of these receptor tyrosine kinase genes, i.e. the features NTRK3-high, IGF1R-low and KDR-high, we developed a pazopanib efficacy predictor that stratified patients into three groups with significantly different PFS (p < 0.0001). Application of the pazopanib efficacy predictor to an independent cohort of patients with pazopanib-treated sarcoma from DKTK MASTER (n = 43) confirmed its potential to separate patient groups with significantly different PFS (p = 0.02), whereas no such association was observed in patients with sarcoma from DKTK MASTER (n = 97) or The Cancer Genome Atlas sarcoma cohort (n = 256) who were not treated with pazopanib. CONCLUSION: A score based on the combined expression of NTRK3, IGF1R and KDR allows the identification of patients with sarcoma and with good, intermediate and poor outcome following pazopanib therapy and warrants prospective investigation as a predictive tool to optimise the use of this drug in the clinic.

MEK1/2 inhibition transiently alters the tumor immune microenvironment to enhance immunotherapy efficacy against head and neck cancer.

BACKGROUND: Although the mitogen-activated protein kinases (MAPK) pathway is hyperactive in head and neck cancer (HNC), inhibition of MEK1/2 in HNC patients has not shown clinically meaningful activity. Therefore, we aimed to characterize the effect of MEK1/2 inhibition on the tumor microenvironment (TME) of MAPK-driven HNC, elucidate tumor-host interaction mechanisms facilitating immune escape on treatment, and apply rationale-based therapy combination immunotherapy and MEK1/2 inhibitor to induce tumor clearance. METHODS: Mouse syngeneic tumors and xenografts experiments were used to analyze tumor growth in vivo. Single-cell cytometry by time of flight, flow cytometry, and tissue stainings were used to profile the TME in response to trametinib (MEK1/2 inhibitor). Co-culture of myeloid-derived suppressor cells (MDSC) with CD8+ T cells was used to measure immune suppression. Overexpression of colony-stimulating factor-1 (CSF-1) in tumor cells was used to show the effect of tumor-derived CSF-1 on sensitivity to trametinib and anti-programmed death- 1 (αPD-1) in mice. In HNC patients, the ratio between CSF-1 and CD8A was measured to test the association with clinical benefit to αPD-1 and αPD-L1 treatment. RESULTS: Using preclinical HNC models, we demonstrated that treatment with trametinib delays HNC initiation and progression by reducing tumor cell proliferation and enhancing the antitumor immunity of CD8+ T cells. Activation of CD8+ T cells by supplementation with αPD-1 antibody eliminated tumors and induced an immune memory in the cured mice. Mechanistically, an early response to trametinib treatment sensitized tumors to αPD-1-supplementation by attenuating the expression of tumor-derived CSF-1, which reduced the abundance of two CSF-1R+CD11c+ MDSC populations in the TME. In contrast, prolonged treatment with trametinib abolished the antitumor activity of αPD-1, because tumor cells undergoing the epithelial to mesenchymal transition in response to trametinib restored CSF-1 expression and recreated an immune-suppressive TME. CONCLUSION: Our findings provide the rationale for testing the trametinib/αPD-1 combination in HNC and highlight the importance of sensitizing tumors to αPD-1 by using MEK1/2 to interfere with the tumor-host interaction. Moreover, we describe the concept that treatment of cancer with a targeted therapy transiently induces an immune-active microenvironment, and supplementation of immunotherapy during this time further activates the antitumor machinery to cause tumor elimination.

Receptor-Tyrosine Kinase Inhibitor Ponatinib Inhibits Meningioma Growth In Vitro and In Vivo.

To date, there is no standard-of-care systemic therapy for the treatment of aggressive meningiomas. Receptor tyrosine kinases (RTK) are frequently expressed in aggressive meningiomas and are associated with poor survival. Ponatinib is a FDA- and EMA-approved RTK inhibitor and its efficacy in meningioma has not been studied so far. Therefore, we investigated ponatinib as a potential drug candidate against meningioma. Cell viability and cell proliferation of ponatinib-treated meningioma cells were assessed using crystal violet assay, manual counting and BrdU assay. Treated meningioma cell lines were subjected to flow cytometry to evaluate the effects on cell cycle and apoptosis. Meningioma-bearing mice were treated with ponatinib to examine antitumor effects in vivo. qPCR was performed to assess the mRNA levels of tyrosine kinase receptors after ponatinib treatment. Full-length cDNA sequencing was carried out to assess differential gene expression. IC50 values of ponatinib were between 171.2 and 341.9 nM in three meningioma cell lines. Ponatinib induced G0/G1 cell cycle arrest and subsequently led to an accumulation of cells in the subG1-phase. A significant induction of apoptosis was observed in vitro. In vivo, ponatinib inhibited meningioma growth by 72.6%. Mechanistically, this was associated with downregulation of PDGFRA/B and FLT3 mRNA levels, and mitochondrial dysfunction. Taken together, ponatinib is a promising candidate for targeted therapy in the treatment of aggressive meningioma.

Digital Pathology Scoring of Immunohistochemical Staining Reliably Identifies Prognostic Markers and Anatomical Associations in a Large Cohort of Oral Cancers.

Utilizing digital pathology algorithms for the objective quantification of immunohistochemical staining, this study aimed to identify robust prognostic biomarkers for oral cancer. Tissue microarrays with specimens of a large cohort of oral squamous cell carcinoma (n=222) were immunohistochemically stained to determine the expression of PD-L1, EGFR, and COX-2 and the amount of infiltrating NK cells and CD8-positive T cells. Immunoreactivity scores were assessed using both a classical manual scoring procedure and a digital semi-automatic approach using QuPath. Digital scoring was successful in quantifying the expression levels of different prognostic biomarkers (CD8: p<0.001; NK cells: p=0.002, PD-L1: p=0.026) and high levels of concordance with manual scoring results were observed. A combined score integrating EGFR expression, neck node status and immune cell signatures with a significant impact on overall and progression-free survival was identified (p<0.001). These data may contribute to the ongoing research on the identification of reliable and clinically relevant biomarkers for the individualization of primary and adjuvant treatment in oral cancer.

EGFR and PI3K Pathway Activities Might Guide Drug Repurposing in HPV-Negative Head and Neck Cancers.

While genetic alterations in Epidermal growth factor receptor (EGFR) and PI3K are common in head and neck squamous cell carcinomas (HNSCC), their impact on oncogenic signaling and cancer drug sensitivities remains elusive. To determine their consequences on the transcriptional network, pathway activities of EGFR, PI3K, and 12 additional oncogenic pathways were inferred in 498 HNSCC samples of The Cancer Genome Atlas using PROGENy. More than half of HPV-negative HNSCC showed a pathway activation in EGFR or PI3K. An amplification in EGFR and a mutation in PI3KCA resulted in a significantly higher activity of the respective pathway (p = 0.017 and p = 0.007). Interestingly, both pathway activations could only be explained by genetic alterations in less than 25% of cases indicating additional molecular events involved in the downstream signaling. Suitable in vitro pathway models could be identified in a published drug screen of 45 HPV-negative HNSCC cell lines. An active EGFR pathway was predictive for the response to the PI3K inhibitor buparlisib (p = 6.36E-03) and an inactive EGFR and PI3K pathway was associated with efficacy of the B-cell lymphoma (BCL) inhibitor navitoclax (p = 9.26E-03). In addition, an inactive PI3K pathway correlated with a response to multiple Histone deacetylase inhibitor (HDAC) inhibitors. These findings require validation in preclinical models and clinical studies.

Comprehensive Genomic and Transcriptomic Analysis for Guiding Therapeutic Decisions in Patients with Rare Cancers.

The clinical relevance of comprehensive molecular analysis in rare cancers is not established. We analyzed the molecular profiles and clinical outcomes of 1,310 patients (rare cancers, 75.5%) enrolled in a prospective observational study by the German Cancer Consortium that applies whole-genome/exome and RNA sequencing to inform the care of adults with incurable cancers. On the basis of 472 single and six composite biomarkers, a cross-institutional molecular tumor board provided evidence-based management recommendations, including diagnostic reevaluation, genetic counseling, and experimental treatment, in 88% of cases. Recommended therapies were administered in 362 of 1,138 patients (31.8%) and resulted in significantly improved overall response and disease control rates (23.9% and 55.3%) compared with previous therapies, translating into a progression-free survival ratio >1.3 in 35.7% of patients. These data demonstrate the benefit of molecular stratification in rare cancers and represent a resource that may promote clinical trial access and drug approvals in this underserved patient population. SIGNIFICANCE: Rare cancers are difficult to treat; in particular, molecular pathogenesis-oriented medical therapies are often lacking. This study shows that whole-genome/exome and RNA sequencing enables molecularly informed treatments that lead to clinical benefit in a substantial proportion of patients with advanced rare cancers and paves the way for future clinical trials.See related commentary by Eggermont et al., p. 2677.This article is highlighted in the In This Issue feature, p. 2659.

Knowledge bases and software support for variant interpretation in precision oncology.

Precision oncology is a rapidly evolving interdisciplinary medical specialty. Comprehensive cancer panels are becoming increasingly available at pathology departments worldwide, creating the urgent need for scalable cancer variant annotation and molecularly informed treatment recommendations. A wealth of mainly academia-driven knowledge bases calls for software tools supporting the multi-step diagnostic process. We derive a comprehensive list of knowledge bases relevant for variant interpretation by a review of existing literature followed by a survey among medical experts from university hospitals in Germany. In addition, we review cancer variant interpretation tools, which integrate multiple knowledge bases. We categorize the knowledge bases along the diagnostic process in precision oncology and analyze programmatic access options as well as the integration of knowledge bases into software tools. The most commonly used knowledge bases provide good programmatic access options and have been integrated into a range of software tools. For the wider set of knowledge bases, access options vary across different parts of the diagnostic process. Programmatic access is limited for information regarding clinical classifications of variants and for therapy recommendations. The main issue for databases used for biological classification of pathogenic variants and pathway context information is the lack of standardized interfaces. There is no single cancer variant interpretation tool that integrates all identified knowledge bases. Specialized tools are available and need to be further developed for different steps in the diagnostic process.

Perioperative changes in the plasma metabolome of patients receiving general anesthesia for pancreatic cancer surgery.

BACKGROUND: Modern anesthesia strives to offer personalized concepts to meet the patient's individual needs in sight of clinical outcome. Still, little is known about the impact of anesthesia on the plasma metabolome, although many metabolites have been shown to modulate the function of various immune cells, making it particularly interesting in the context of oncological surgery. In this study longitudinal dynamics in the plasma metabolome during general anesthesia in patients undergoing pancreatic surgery were analyzed. MATERIALS AND METHODS: Prospective, observational study with 10 patients diagnosed with pancreatic (pre-) malignancy and subjected to elective resection surgery under general anesthesia. Plasma metabolites (n = 630) were quantified at eight consecutive perioperative timepoints using mass spectrometry-based targeted metabolomics. RESULTS: 39 metabolites significantly changed during the perioperative period. Tryptophan concentrations decreased by 45% with the maximum decrease after anesthesia induction (p = 6.24E-07), while taurine synthesis increased (p = 1.46E-04). Triacylglycerides and lysophosphatidylcholines were significantly reduced with increased liberation of free monounsaturated fatty acids (p = 0.03). Carnitine levels decreased significantly (p = 9.30E-04). CONCLUSIONS: The major finding of this study was perioperative tryptophan depletion and increased taurine synthesis. Both are essential for immune cell function and are therefore of significant interest for perioperative management. Further studies are needed to identify influencing anesthetic factors.