Assessing lung cancer progression and survival with infrared spectroscopy of blood serum.

Background: Infrared molecular fingerprinting has been identified as a new minimally invasive technological tool for disease diagnosis. While the utility of cross-molecular infrared fingerprints of serum and plasma for in vitro cancer diagnostics has been recently demonstrated, their potential for stratifying and predicting the prognosis of lung cancer remained unexplored. This study investigates the capability of this approach to predict survival and stratify lung cancer patients.

Graph-Theoretical Prediction and Analysis of Biologically Relevant Substructures in an Open and Closed Conformation of Respiratory Complex I.

Protein complexes are functional modules within the hierarchy of the cellular organization. Large protein complexes often consist of smaller functional modules, which are biologically relevant substructures with specific functions. The first protein complex of the respiratory chain, complex I, consists of functional modules for the electron transfer from NADH to quinone and the translocation of protons across the inner mitochondrial membrane.

Plasma Proteome-Based Test for First-Line Treatment Selection in Metastatic Non-Small Cell Lung Cancer.

Purpose: Current guidelines for the management of metastatic non-small cell lung cancer (NSCLC) without driver mutations recommend checkpoint immunotherapy with PD-1/PD-L1 inhibitors, either alone or in combination with chemotherapy. This approach fails to account for individual patient variability and host immune factors and often results in less-than-ideal outcomes. To address the limitations of the current guidelines, we developed and subsequently blindly validated a machine learning algorithm using pretreatment plasma proteomic profiles for personalized treatment decisions.

Graph-theoretical prediction of biological modules in quaternary structures of large protein complexes.

Motivation: The functional complexity of biochemical processes is strongly related to the interplay of proteins and their assembly into protein complexes. In recent years, the discovery and characterization of protein complexes have substantially progressed through advances in cryo-electron microscopy, proteomics, and computational structure prediction. This development results in a strong need for computational approaches to analyse the data of large protein complexes for structural and functional characterization.

Does Dual-Energy Computed Tomography Material Decomposition Improve Radiomics Capability to Predict Survival in Head and Neck Squamous Cell Carcinoma Patients? A Preliminary Investigation.

Objective: Our study objective was to explore the additional value of dual-energy CT (DECT) material decomposition for squamous cell carcinoma of the head and neck (SCCHN) survival prognostication.

Methods: A group of 50 SCCHN patients (male, 37; female, 13; mean age, 63.6 ± 10.

Dataset of single nucleotide polymorphisms of immune-associated genes in patients with SARS-CoV-2 infection.

The SARS-CoV-2 pandemic has affected nations globally leading to illness, death, and economic downturn. Why disease severity, ranging from no symptoms to the requirement for extracorporeal membrane oxygenation, varies between patients is still incompletely understood. Consequently, we aimed at understanding the impact of genetic factors on disease severity in infection with SARS-CoV-2.

Preliminary results from the EMoLung clinical study showing early lung cancer detection by the LC score.

Background: Lung cancer (LC) causes more deaths worldwide than any other cancer type. Despite advances in therapeutic strategies, the fatality rate of LC cases remains high (95%) since the majority of patients are diagnosed at late stages when patient prognosis is poor. Analysis of the International Association for the Study of Lung Cancer (IASLC) database indicates that early diagnosis is significantly associated with favorable outcome.

Three-dimensional human germinal centers of different sizes in patients diagnosed with lymphadenitis show comparative constant relative volumes of B cells, T cells, follicular dendritic cells, and macrophages.

Germinal centers (GCs) are some of the most important structures in the human immune system. As such, their cell types and functions have been thoroughly investigated. B cells, T cells, follicular dendritic cells (FDCs), and macrophages have widely been found to typically be aggregated in GCs.

Pathogenetic mechanisms and therapeutic approaches of acute-to-chronic liver failure.

Liver cirrhosis is the end stage of all chronic liver diseases and contributes significantly to overall mortality of 2% globally. The age-standardized mortality from liver cirrhosis in Europe is between 10 and 20% and can be explained by not only the development of liver cancer but also the acute deterioration in the patient's overall condition. The development of complications including accumulation of fluid in the abdomen (ascites), bleeding in the gastrointestinal tract (variceal bleeding), bacterial infections, or a decrease in brain function (hepatic encephalopathy) define an acute decompensation that requires therapy and often leads to acute-on-chronic liver failure (ACLF) by different precipitating events.

Radiomics for therapy-specific head and neck squamous cell carcinoma survival prognostication (part I).

Background: Treatment plans for squamous cell carcinoma of the head and neck (SCCHN) are individually decided in tumor board meetings but some treatment decision-steps lack objective prognostic estimates. Our purpose was to explore the potential of radiomics for SCCHN therapy-specific survival prognostication and to increase the models' interpretability by ranking the features based on their predictive importance.

Methods: We included 157 SCCHN patients (male, 119; female, 38; mean age, 64.

The proteasome regulator PSME4 modulates proteasome activity and antigen diversity to abrogate antitumor immunity in NSCLC.

Immunotherapy revolutionized treatment options in cancer, yet the mechanisms underlying resistance in many patients remain poorly understood. Cellular proteasomes have been implicated in modulating antitumor immunity by regulating antigen processing, antigen presentation, inflammatory signaling and immune cell activation. However, whether and how proteasome complex heterogeneity may affect tumor progression and the response to immunotherapy has not been systematically examined.

High-resolution transcriptomic and epigenetic profiling identifies novel regulators of COPD.

Patients with chronic obstructive pulmonary disease (COPD) are still waiting for curative treatments. Considering its environmental cause, we hypothesized that COPD will be associated with altered epigenetic signaling in lung cells. We generated genome-wide DNA methylation maps at single CpG resolution of primary human lung fibroblasts (HLFs) across COPD stages.

Non-Oncogene Addiction of -Mutant Cancers to IL-1β via Versican and Mononuclear IKKβ.

-mutant cancers are frequent, metastatic, lethal, and largely undruggable. While interleukin (IL)-1β and nuclear factor (NF)-κB inhibition hold promise against cancer, untargeted treatments are not effective. Here, we show that human -mutant cancers are addicted to IL-1β via inflammatory versican signaling to macrophage inhibitor of NF-κB kinase (IKK) β.

USP15 Represses Hepatocellular Carcinoma Progression by Regulation of Pathways of Cell Proliferation and Cell Migration: A System Biology Analysis.

Background: Hepatocellular carcinoma (HCC) leads to 600,000 people's deaths every year. The protein ubiquitin carboxyl-terminal hydrolase 15 (USP15) is a ubiquitin-specific protease. The role of USP15 in HCC is still unclear.

Computational modeling of signal transduction networks without kinetic parameters: Petri net approaches.

More and more computational techniques have been applied to model biological systems, especially signaling pathways in medical systems. Due to the large number of experimental data driven by high-throughput technologies, new computational concepts have been developed. Nevertheless, often the necessary kinetic data cannot be determined in sufficient number and quality because of experimental complexity or ethical reasons.

Imaging bridges pathology and radiology.

In recent years, medical disciplines have moved closer together and rigid borders have been increasingly dissolved. The synergetic advantage of combining multiple disciplines is particularly important for radiology, nuclear medicine, and pathology to perform integrative diagnostics. In this review, we discuss how medical subdisciplines can be reintegrated in the future using state-of-the-art methods of digitization, data science, and machine learning.

Holistic View on the Structure of Immune Response: Petri Net Model.

The simulation of immune response is a challenging task because quantitative data are scarce. Quantitative theoretical models either focus on specific cell-cell interactions or have to make assumptions about parameters. The broad variation of, e.

Variation of butyrate production in the gut microbiome in type 2 diabetes patients.

Background: Diabetes mellitus type 2 is a common disease that poses a challenge to the healthcare system. The disease is very often diagnosed late. A better understanding of the relationship between the gut microbiome and type 2 diabetes can support early detection and form an approach for therapies.

Comparison of the sensitivity of different criteria to select lung cancer patients for screening in a cohort of German patients.

Introduction: Trials of CT-based screening for lung cancer have shown a mortality advantage for screening in North America and Europe. Before introducing a nationwide lung cancer screening program in Germany, it is important to assess the criteria used in international trials in the German population.

Methods: We used data from 3623 lung cancer patients from the data warehouse of the German Center for Lung Research (DZL).

CT-radiomics and clinical risk scores for response and overall survival prognostication in TACE HCC patients.

We aimed to identify hepatocellular carcinoma (HCC) patients who will respond to repetitive transarterial chemoembolization (TACE) to improve the treatment algorithm. Retrospectively, 61 patients (mean age, 65.3 years ± 10.

Evaluation of automatic discrimination between benign and malignant prostate tissue in the era of high precision digital pathology.

Background: Prostate cancer is a major health concern in aging men. Paralleling an aging society, prostate cancer prevalence increases emphasizing the need for efficient diagnostic algorithms.

Methods: Retrospectively, 106 prostate tissue samples from 48 patients (mean age, [Formula: see text] years) were included in the study.

Comparison of machine learning methods with logistic regression analysis in creating predictive models for risk of critical in-hospital events in COVID-19 patients on hospital admission.

Background: Machine learning (ML) algorithms have been trained to early predict critical in-hospital events from COVID-19 using patient data at admission, but little is known on how their performance compares with each other and/or with statistical logistic regression (LR). This prospective multicentre cohort study compares the performance of a LR and five ML models on the contribution of influencing predictors and predictor-to-event relationships on prediction model´s performance.

Methods: We used 25 baseline variables of 490 COVID-19 patients admitted to 8 hospitals in Germany (March-November 2020) to develop and validate (75/25 random-split) 3 linear (L1 and L2 penalty, elastic net [EN]) and 2 non-linear (support vector machine [SVM] with radial kernel, random forest [RF]) ML approaches for predicting critical events defined by intensive care unit transfer, invasive ventilation and/or death (composite end-point: 181 patients).

Mathematical modeling of the molecular switch of TNFR1-mediated signaling pathways applying Petri net formalism and in silico knockout analysis.

The paper describes a mathematical model of the molecular switches of cell survival, apoptosis, and necroptosis in cellular signaling pathways initiated by tumor necrosis factor 1. Based on experimental findings in the literature, we constructed a Petri net model based on detailed molecular reactions of the molecular players, protein complexes, post-translational modifications, and cross talk. The model comprises 118 biochemical entities, 130 reactions, and 299 edges.

KRAS signaling in malignant pleural mesothelioma.

Malignant pleural mesothelioma (MPM) arises from mesothelial cells lining the pleural cavity of asbestos-exposed individuals and rapidly leads to death. MPM harbors loss-of-function mutations in BAP1, NF2, CDKN2A, and TP53, but isolated deletion of these genes alone in mice does not cause MPM and mouse models of the disease are sparse. Here, we show that a proportion of human MPM harbor point mutations, copy number alterations, and overexpression of KRAS with or without TP53 changes.

Prognostic phenotypes of early-stage lung adenocarcinoma.

Background: Survival after curative resection of early-stage lung adenocarcinoma (LUAD) varies and prognostic biomarkers are urgently needed.

Methods: Large-format tissue samples from a prospective cohort of 200 patients with resected LUAD were immunophenotyped for cancer hallmarks TP53, NF1, CD45, PD-1, PCNA, TUNEL and FVIII, and were followed for a median of 2.34 (95% CI 1.