Detection of Simultaneous Group Effects in MicroRNA Expression and Related Target Gene Sets

Expression levels of mRNAs are among other factors regulated by microRNAs. A particular microRNA can bind specifically to several target mRNAs and lead to their degradation. Expression levels of both, mRNAs and microRNAs, can be obtained by microarray experiments. In order to increase the power of detecting microRNAs that are differentially expressed between two different groups of samples, we incorporate expression levels of their related target gene sets. Group effects are determined individually for each microRNA, and by enrichment tests and global tests for target gene sets. The resulting lists of p-values from individual and set-wise testing are combined by means of meta analysis. We propose a new approach to connect microRNA-wise and gene set-wise information by means of p-value combination as often used in meta-analysis. In this context, we evaluate the usefulness of different approaches of gene set tests. In a simulation study we reveal that our combination approach is more powerful than microRNA-wise testing alone. Furthermore, we show that combining microRNA-wise results with ‘competitive’ gene set tests maintains a pre-specified false discovery rate. In contrast, a combination with ‘self-contained’ gene set tests can harm the false discovery rate, particularly when gene sets are not disjunct

Utilizing molecular network information via graph convolutional neural networks to predict metastatic event in breast cancer

Gene expression data is commonly available in cancer research and provides a snapshot of the molecular status of a specific tumor tissue. This high-dimensional data can be analyzed for diagnoses, prognoses, and to suggest treatment options. Machine learning based methods are widely used for such analysis. Recently, a set of deep learning techniques was successfully applied in different domains including bioinformatics. One of these prominent techniques are convolutional neural networks (CNN). Currently, CNNs are extending to non-Euclidean domains like graphs. Molecular networks are commonly represented as graphs detailing interactions between molecules. Gene expression data can be assigned to the vertices of these graphs, and the edges can depict interactions, regulations and signal flow. In other words, gene expression data can be structured by utilizing molecular network information as prior knowledge. Here, we applied graph CNN to gene expression data of breast cancer patients to predict the occurrence of metastatic events. To structure the data we utilized a protein-protein interaction network. We show that the graph CNN exploiting the prior knowledge is able to provide classification improvements for the prediction of metastatic events compared to existing methods

Comparative study on gene set and pathway topology-based enrichment methods

Background Enrichment analysis is a popular approach to identify pathways or sets of genes which are significantly enriched in the context of differentially expressed genes. The traditional gene set enrichment approach considers a pathway as a simple gene list disregarding any knowledge of gene or protein interactions. In contrast, the new group of so called pathway topology-based methods integrates the topological structure of a pathway into the analysis. Methods We comparatively investigated gene set and pathway topology-based enrichment approaches, considering three gene set and four topological methods. These methods were compared in two extensive simulation studies and on a benchmark of 36 real datasets, providing the same pathway input data for all methods. Results In the benchmark data analysis both types of methods showed a comparable ability to detect enriched pathways. The first simulation study was conducted with KEGG pathways, which showed considerable gene overlaps between each other. In this study with original KEGG pathways, none of the topology-based methods outperformed the gene set approach. Therefore, a second simulation study was performed on non-overlapping pathways created by unique gene IDs. Here, methods accounting for pathway topology reached higher accuracy than the gene set methods, however their sensitivity was lower. Conclusions We conducted one of the first comprehensive comparative works on evaluating gene set against pathway topology-based enrichment methods. The topological methods showed better performance in the simulation scenarios with non-overlapping pathways, however, they were not conclusively better in the other scenarios. This suggests that simple gene set approach might be sufficient to detect an enriched pathway under realistic circumstances. Nevertheless, more extensive studies and further benchmark data are needed to systematically evaluate these methods and to assess what gain and cost pathway topology information introduces into enrichment analysis. Both types of methods for enrichment analysis require further improvements in order to deal with the problem of pathway overlaps

Clinical benefit and cost‑effectiveness analysis of liquid biopsy application in patients with advanced non‑small cell lung cancer (NSCLC) : a modelling approach

Abstract Purpose Targeted therapies are effective therapeutic approaches in advanced stages of NSCLC and require precise molecular profiling to identify oncogenic drivers. Differential diagnosis on a molecular level contributes to clinical decision making. Liquid biopsy (LB) use has demonstrated its potential to serve as an alternative to tissue biopsy (TB) particularly in cases where tissue sampling is not feasible or insufficient. We aimed at evaluating the cost-effectiveness of ctDNA-based LB use (molecular multigene testing) according to German care guidelines for metastatic NSCLC. Methods A Markov model was developed to compare the costs and clinical benefits associated with the use of LB as an add-on to TB according to the guidelines for NSCLC patients. Usual care TB served as comparator. A microsimulation model was used to simulate a cohort of non-squamous NSCLC patients stage IV. The parameters used for modelling were obtained from the literature and from the prospective German CRISP registry (“Clinical Research platform Into molecular testing, treatment, and outcome of non-Small cell lung carcinoma Patients”). For each pathway, average direct medical costs, and QALYs gained per patient were used for calculating incremental cost-effectiveness ratios (ICER). Results The use of LB as an add-on was costlier (€144,981 vs. €144,587) but more effective measured in QALYs (1.20 vs. 1.19) for the care pathway of NSCLC patients (ICER €53,909/QALY). Cost-effectiveness was shown for EGFR-mutated patients (ICER €-13,247/QALY). Conclusion Including LB as an add-on into the care pathway of advanced NSCLC has positive clinical effects in terms of QALYs accompanied by a moderate cost-effectiveness.RocheUniversität Bayreut

Surgery for brain metastases: radiooncology scores predict survival-score index for radiosurgery, graded prognostic assessment, recursive partitioning analysis

BACKGROUND: Radiooncological scores are used to stratify patients for radiation therapy. We assessed their ability to predict overall survival (OS) in patients undergoing surgery for metastatic brain disease. METHODS: We performed a post-hoc single-center analysis of 175 patients, prospectively enrolled in the MetastaSys study data. Score index of radiosurgery (SIR), graded prognostic assessment (GPA), and recursive partitioning analysis (RPA) were assessed. All scores consider age, systemic disease, and performance status prior to surgery. Furthermore, GPA and SIR include the number of intracranial lesions while SIR additionally requires metastatic lesion volume. Predictive values for case fatality at 1 year after surgery were compared among scoring systems. RESULTS: All scores produced accurate reflections on OS after surgery (p ≤ 0.003). Median survival was 21–24 weeks in patients scored in the unfavorable cohorts, respectively. In cohorts with favorable scores, median survival ranged from 42 to 60 weeks. Favorable SIR was associated with a hazard ratio (HR) of 0.44 [0.29, 0.66] for death within 1 year. For GPA, the HR amounted to 0.44 [0.25, 0.75], while RPA had a HR of 0.30 [0.14, 0.63]. Overall test performance was highest for the SIR. CONCLUSIONS: All scores proved useful in predicting OS. Considering our data, we recommend using the SIR for preoperative prognostic evaluation and counseling

Efficacy of COVID-19 Booster Vaccines in Patients with Hematologic Malignancies: Experiences in a Real-World Scenario.

BACKGROUND Two-dose COVID-19 vaccination often results in poor humoral response rates in patients with hematologic malignancies (HMs); yet responses to COVID-19 booster vaccines and the risk of COVID-19 infection post-booster are mostly uncertain. METHODS We included 200 outpatients with HMs and predominantly lymphoid neoplasms (96%, 191/200) in our academic center and reported on the humoral responses, which were assessed by measurement of anti-spike IgG antibodies in peripheral blood as early as 14 days after mRNA-based prime-boost vaccination, as well as factors hampering booster efficacy. Previous basic (double) immunization was applied according to the local recommendations with mRNA- and/or vector-based vaccines. We also report on post-booster COVID-19 breakthrough infections that emerged in the Omicron era and the prophylaxis strategies that were applied to poor and non-responders to booster vaccines. RESULTS A total of 55% (110/200) of the patients achieved seroconversion (i.e., anti-spike protein IgG antibody titer > 100 AU/mL assessed in median 48 days after prime-boost vaccination) after prime-boost vaccination. Multivariable analyses revealed age, lymphocytopenia, ongoing treatment and prior anti-CD20 B-cell depletion to be independent predictors for booster failure. With each month between anti-CD20-mediated B-cell depletion and booster vaccination, the probability of seroconversion increased by approximately 4% (p < 0.001) and serum-antibody titer (S-AbT) levels increased by 90 AU/mL (p = 0.011). Notably, obinutuzumab treatment was associated with an 85% lower probability for seroconversion after prime-boost vaccination compared to rituximab (p = 0.002). Of poor or non-responders to prime-boost vaccination, 41% (47/114) underwent a second booster and 73% (83/114) underwent passive immunization. COVID-19 breakthrough infections were observed in 15% (29/200) of patients after prime-boost vaccination with predominantly mild courses (93%). Next to seroconversion, passive immunization was associated with a significantly lower risk of COVID-19 breakthrough infections after booster, even in vaccine non-responders (all p < 0.05). In a small proportion of analyzed patients with myeloid neoplasms (9/200), the seroconversion rate was higher compared to those with lymphoid ones (78% vs. 54%, accordingly), while the incidence rate of COVID-19 breakthrough infections was similar (22% vs. 14%, respectively). Following the low frequency of myeloid neoplasms in this study, the results may not be automatically applied to a larger cohort. CONCLUSIONS Patients with HMs are at a high risk of COVID-19 booster vaccine failure; yet COVID-19 breakthrough infections after prime-boost vaccination are predominantly mild. Booster failure can likely be overcome by passive immunization, thereby providing immune protection against COVID-19 and attenuating the severity of COVID-19 courses. Further sophistication of clinical algorithms for preventing post-vaccination COVID-19 breakthrough infections is urgently needed

Thymidylate Synthase as a Prognostic Biomarker for Locally Advanced Rectal Cancer after multimodal Treatment

PURPOSE: For years, 5-fluorouracil (5-FU) has been the backbone of radiochemotherapy (RCT) of locally advanced rectal cancer. Its main target, thymidylate synthase (TS), is speculated to be an important biomarker for response prediction and long-term prognosis. In this study, we analyzed TS expression in the rectal cancer tissue of 208 patients to evaluate its predictive/prognostic potential. METHODS: All patients included were diagnosed with locally advanced adenocarcinoma of the rectum (UICC II and III) and were treated within randomized clinical trials of the German Rectal Cancer Study Group. Preoperative RCT (50.4 Gy and concomitant either 5-FU or 5-FU and oxaliplatin) was administered in 167 patients followed by surgical resection with total mesorectal excision (TME). Another 41 patients received postoperative RCT. TS levels and further clinicopathological parameters were assessed in univariate and multivariate analyses. Additionally, a TS gene polymorphism was analyzed with respect to the intratumoral protein levels. RESULTS: Low TS expression in pretreatment biopsies correlated with impaired patient survival (p = 0.015). Analysis of a 28-bp repeat revealed a correlation between the *3/*3 genotype and high TS expression in pretherapeutic biopsies. In this study, a correlation of TS expression and grade of RCT-induced tumor regression was not found. Histopathological examination confirmed a complete tumor remission in 16 patients (9.6%). Analyses of the resection specimen indicated an unfavorable prognosis for patients with low intratumoral TS expression in case of detected lymph node metastases (p = 0.04). CONCLUSIONS: TS can serve as a prognostic biomarker indicating an unfavorable prognosis for patients with low TS expression. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1245/s10434-011-1608-4) contains supplementary material, which is available to authorized users

Clinical Post-SARS-CoV-2 Infection Scenarios in Vaccinated and Non-Vaccinated Cancer Patients in Three German Cancer Centers: A Retrospective Analysis.

COVID-19 vaccines have become an integral element in the protection of cancer patients against SARS-CoV-2. To date, there are no direct comparisons of the course of COVID-19 infection in cancer patients between the pre- and post-vaccine era. We analyzed SARS-CoV-2 infections and their impact on cancer in COVID-19 vaccinated and non-vaccinated patients from three German cancer centers. Overall, 133 patients with SARS-CoV-2 were enrolled in pre- and post-vaccine eras: 84 non-vaccinated and 49 vaccinated, respectively. A mild course of COVID-19 was documented more frequently in vaccinated patients (49% vs. 29%), while the frequency of severe and critical courses occurred in approximately one-half of the non-vaccinated patients (22% vs. 42%, p = 0.023). Particularly, patients with hematologic neoplasms benefited from vaccination in this context (p = 0.031). Admissions to intermediate- and intensive-care units and the necessity of non-invasive and invasive respiratory support were reduced by 71% and 50% among vaccinated patients, respectively. The median length of admission was 11 days for non-vaccinated and 5 days for vaccinated patients (p = 0.002). COVID-19 mortality was reduced by 83% in vaccinated patients (p = 0.046). Finally, the median time from SARS-CoV-2 infection to restarting cancer therapy was 12 and 26 days among vaccinated and non-vaccinated groups, respectively (p = 0.002). Although this study does not have enough power to perform multivariate analyses to account for confounders, it provides data on COVID-19 in non-vaccinated and vaccinated cancer patients and illustrates the potential benefits of COVID-19 vaccines for these patients

Predicting restoration of kidney function during CRRT-free intervals

<p>Abstract</p> <p>Background</p> <p>Renal failure is common in critically ill patients and frequently requires continuous renal replacement therapy (CRRT). CRRT is discontinued at regular intervals for routine changes of the disposable equipment or for replacing clogged filter membrane assemblies. The present study was conducted to determine if the necessity to continue CRRT could be predicted during the CRRT-free period.</p> <p>Materials and methods</p> <p>In the period from 2003 to 2006, 605 patients were treated with CRRT in our ICU. A total of 222 patients with 448 CRRT-free intervals had complete data sets and were used for analysis. Of the total CRRT-free periods, 225 served as an evaluation group. Twenty-nine parameters with an assumed influence on kidney function were analyzed with regard to their potential to predict the restoration of kidney function during the CRRT-free interval. Using univariate analysis and logistic regression, a prospective index was developed and validated in the remaining 223 CRRT-free periods to establish its prognostic strength.</p> <p>Results</p> <p>Only three parameters showed an independent influence on the restoration of kidney function during CRRT-free intervals: the number of previous CRRT cycles (medians in the two outcome groups: 1 vs. 2), the "Sequential Organ Failure Assessment"-score (means in the two outcome groups: 8.3 vs. 9.2) and urinary output after the cessation of CRRT (medians in two outcome groups: 66 ml/h vs. 10 ml/h). The prognostic index, which was calculated from these three variables, showed a satisfactory potential to predict the kidney function during the CRRT-free intervals; Receiver operating characteristic (ROC) analysis revealed an area under the curve of 0.798.</p> <p>Conclusion</p> <p>Restoration of kidney function during CRRT-free periods can be predicted with an index calculated from three variables. Prospective trials in other hospitals must clarify whether our results are generally transferable to other patient populations.</p