Prediction of resistance to bevacizumab plus FOLFOX in metastatic colorectal cancer-Results of the prospective multicenter PERMAD trial.

BACKGROUND: Anti-vascular endothelial growth factor (VEGF) monoclonal antibodies (mAbs) are widely used for tumor treatment, including metastatic colorectal cancer (mCRC). So far, there are no biomarkers that reliably predict resistance to anti-VEGF mAbs like bevacizumab. A biomarker-guided strategy for early and accurate assessment of resistance could avoid the use of non-effective treatment and improve patient outcomes. We hypothesized that repeated analysis of multiple cytokines and angiogenic growth factors (CAFs) before and during treatment using machine learning could provide an accurate and earlier, i.e., 100 days before conventional radiologic staging, prediction of resistance to first-line mCRC treatment with FOLFOX plus bevacizumab. PATIENTS AND METHODS: 15 German and Austrian centers prospectively recruited 50 mCRC patients receiving FOLFOX plus bevacizumab as first-line treatment. Plasma samples were collected every two weeks until radiologic progression (RECIST 1.1) as determined by CT scans performed every 2 months. 102 pre-selected CAFs were centrally analyzed using a cytokine multiplex assay (Luminex, Myriad RBM). RESULTS: Using random forests, we developed a predictive machine learning model that discriminated between the situations of "no progress within 100 days before radiological progress" and "progress within 100 days before radiological progress". We could further identify a combination of ten out of the 102 CAF markers, which fulfilled this task with 78.2% accuracy, 71.8% sensitivity, and 82.5% specificity. CONCLUSIONS: We identified a CAF marker combination that indicates treatment resistance to FOLFOX plus bevacizumab in patients with mCRC within 100 days prior to radiologic progress.

AMBAR - Interactive Alteration annotations for molecular tumor boards.

MOTIVATION: Personalized decision-making for cancer therapy relies on molecular profiling from sequencing data in combination with database evidence and expert knowledge. Molecular tumor boards (MTBs) bring together clinicians and scientists with diverse expertise and are increasingly established in the clinical routine for therapeutic interventions. However, the analysis and documentation of patients data are still time-consuming and difficult to manage for MTBs, especially as few tools are available for the amount of information required. RESULTS: To overcome these limitations, we developed an interactive web application AMBAR (Alteration annotations for Molecular tumor BoARds), for therapeutic decision-making support in MTBs. AMBAR is an R shiny-based application that allows customization, interactive filtering, visualization, adding expert knowledge, and export to clinical systems of annotated mutations. AVAILABILITY: AMBAR is dockerized, open source and available at https://sysbio.uni-ulm.de/?Software:Ambar Contact:hans.kestler@uni-ulm.de.

A systems biology approach to define mechanisms, phenotypes, and drivers in PanNETs with a personalized perspective.

Pancreatic neuroendocrine tumors (PanNETs) are a rare tumor entity with largely unpredictable progression and increasing incidence in developed countries. Molecular pathways involved in PanNETs development are still not elucidated, and specific biomarkers are missing. Moreover, the heterogeneity of PanNETs makes their treatment challenging and most approved targeted therapeutic options for PanNETs lack objective responses. Here, we applied a systems biology approach integrating dynamic modeling strategies, foreign classifier tailored approaches, and patient expression profiles to predict PanNETs progression as well as resistance mechanisms to clinically approved treatments such as the mammalian target of rapamycin complex 1 (mTORC1) inhibitors. We set up a model able to represent frequently reported PanNETs drivers in patient cohorts, such as Menin-1 (MEN1), Death domain associated protein (DAXX), Tuberous Sclerosis (TSC), as well as wild-type tumors. Model-based simulations suggested drivers of cancer progression as both first and second hits after MEN1 loss. In addition, we could predict the benefit of mTORC1 inhibitors on differentially mutated cohorts and hypothesize resistance mechanisms. Our approach sheds light on a more personalized prediction and treatment of PanNET mutant phenotypes.

[Exocrine pancreatic cancer - what is new in the update of the S3 guideline?] / Exokrines Pankreaskarzinom ­ Welche Neuerungen bringt die neue S3-Leitlinie?

In 2020, worldwide 495,773 people were diagnosed with pancreatic ductal adenocarcinoma and 466,003 patients died from pancreatic cancer. Pancreatic cancer ranks 13th among cancer diagnosis and is the 7th most common cause of cancer-related deaths 1.In Germany, each year approximately 10,000 people develop pancreatic cancer and around the same number of patients die from this disease 2. The relative 5-year survival rate is only 10%. The majority of patients die within the year of diagnosis.Incidence and mortality of pancreatic cancer have continuously increased over the recent years. There are multiple reasons for this finding: pancreatic cancer occurs more frequently in older patients which leads to a higher incidence in an aging society. There are no effective screening and early detection measures for sporadic pancreatic cancer. Therefore, the majority of patients are diagnosed at an advanced stage where the tumor is no longer amenable to curative treatment. Furthermore, the majority of pancreatic cancers is per se likely to constitute a disseminated disease, even if initial imaging suggests a localized, surgically amenable disease. This is reflected by the high rate of early metastases and the small number of patients with long-term survival after surgery with curative intent.The S3 guideline exocrine pancreatic cancer aims to present the available evidence on epidemiology, molecular alterations, diagnostics, surgical and non-surgical treatment as well as palliative measures in order to support all those involved in the treatment of this tumor and to improve the care of patients.To better address this need, the S3 guideline was updated again in 2022 and also changed to a living guideline with regular updates to further improve the timeliness of the guideline.

Detection and quantification of a focal fat deposition in a liver undergoing multiple operations for neuroendocrine tumor disease using attenuation imaging: a case report.

BACKGROUND: In patients with history of malignancy, new-onset liver lesions often present diagnostic challenges. We present the case of a patient with history of neuroendocrine tumor and new-onset echo-rich hepatic lesion, in whom attenuation imaging helped to make the diagnosis. Attenuation imaging is an ultrasound-based technique that allows for the quantification of hepatic fat content on the basis of a measurement of sound attenuation. CASE PRESENTATION: We present the case of a 62-year-old Caucasian female patient who underwent pylorus-preserving pancreaticoduodenectomy Whipple surgery in 2004 for histologically well-differentiated neuroendocrine tumor with a proliferation rate of 3% of the pancreatic head. During the course, single liver metastases were resected in 2009, 2010, and 2013. In 2019, hemihepatectomy was performed when two liver metastases recurred. The liver metastases each showed a proliferation rate of 10% with vigorous expression of chromogranin A, synaptophysin, and somatostatin. The most recent follow-up examinations showed a normal chromogranin A value and the patient reported a good general condition. However, sonography revealed a blurred, echoic lesion in the liver. On contrast-enhanced sonography, the lesion showed identical behavior to the surrounding liver parenchyma. In the asymptomatic patient, liver biopsy did not seem to be indicated at the current time. Measurement of the attenuation coefficient by attenuation imaging showed a significantly higher measurement in the area of the echo-rich lesion than in the rest of the liver. The overall findings are consistent with focal fat deposition. CONCLUSIONS: Attenuation imaging appears to be useful in the evaluation of unclear echo-rich liver lesions. In particular, primary non-malignant-appearing liver lesions that are unremarkable on abdominal contrast-enhanced ultrasound can be more accurately assessed.

Interaction Empowerment in Mobile Health: Concepts, Challenges, and Perspectives.

In its most trending interpretation, empowerment in health care is implemented as a patient-centered approach. In the same sense, many mobile health (mHealth) apps are being developed with a primary focus on the individual user. The integration of mHealth apps into the health care system has the potential to counteract existing challenges, including incomplete or nonstandardized medical data and lack of communication, especially in the intersectional context (eg, patients, medical forces). However, concerns about data security and privacy, regional differences in regulations, lack of accessibility, and nontransparent apps hinder the successful integration of mHealth into the health care system. One approach to address this is to rethink the interpretation of empowerment. On that basis, we here examine existing approaches of individual empowerment and subsequently analyze a different view of empowerment in digital health, namely interaction empowerment. Such a change of perspective could positively influence intersectoral communication and facilitate secure data and knowledge sharing. We discuss this novel viewpoint on empowerment, focusing on more efficient integration and development of mHealth approaches. A renewed interpretation of empowerment could thus buffer current limitations of individual empowerment while also advancing digitization of the health system.

Digitalization of adverse event management in oncology to improve treatment outcome-A prospective study protocol.

The occurrence of adverse events frequently accompanies tumor treatments. Side effects should be detected and treated as soon as possible to maintain the best possible treatment outcome. Besides the standard reporting system Common Terminology Criteria for Adverse Events (CTCAE), physicians have recognized the potential of patient-reporting systems. These are based on a more subjective description of current patient reporting symptoms. Patient-reported symptoms are essential to define the impact of a given treatment on the quality of life and the patient's wellbeing. They also act against an underreporting of side effects which are paramount to define the actual value of a treatment for the individual patient. Here, we present a study protocol for a clinical trial that assesses the potential of a smartphone application for CTCAE conform symptom reporting and tracking that is adjusted to the standard clinical reporting system rather than symptom oriented descriptive trial tools. The presented study will be implemented in two parts, both lasting over six months. The first part will assess the feasibility of the application with 30 patients non-randomly divided into three equally-sized age groups (<55years, 55-75years, >75years). In the second part 36 other patients will be randomly assigned to two groups, one reporting using the smartphone and one not. This prospective second part will compare the impact of smartphone reported adverse events regarding applied therapy doses and quality of life to those of patients receiving standard care. We aim for early detection and treatment of adverse events in oncological treatment to improve patients' safety and outcomes. For this purpose, we will capture frequent adverse events of chemotherapies, immunotherapies, or other targeted therapies with our smartphone application. The presented trial is registered at the U.S. National Library of Medicine ClinicalTrials.gov (NCT04493450) on July 30, 2020.