Integrating multiple molecular sources into a clinical risk prediction signature by extracting complementary information

Single nucleotide polymorphism (SNP) microarray data. SNP data underlying the finding in this article. (Rdata 50688 kb

Off-target effects of siRNA specific for GFP

<p>Abstract</p> <p>Background</p> <p>Gene knock down by RNAi is a highly effective approach to silence gene expression in experimental as well as therapeutic settings. However, this widely used methodology entails serious pitfalls, especially concerning specificity of the RNAi molecules.</p> <p>Results</p> <p>We tested the most widely used control siRNA directed against <it>GFP </it>for off-target effects and found that it deregulates in addition to <it>GFP </it>a set of endogenous target genes. The off-target effects were dependent on the amount of <it>GFP </it>siRNA transfected and were detected in a variety of cell lines. Since the respective siRNA molecule specific for <it>GFP </it>is widely used as negative control for RNAi experiments, we studied the complete set of off-target genes of this molecule by genome-wide expression profiling. The detected modulated mRNAs had target sequences homologous to the siRNA as small as 8 basepairs in size. However, we found no restriction of sequence homology to 3'UTR of target genes.</p> <p>Conclusion</p> <p>We can show that even siRNAs without a physiological target have sequence-specific off-target effects in mammalian cells. Furthermore, our analysis defines the off-target genes affected by the siRNA that is commonly used as negative control and directed against <it>GFP</it>. Since off-target effects can hardly be avoided, the best strategy is to identify false positives and exclude them from the results. To this end, we provide the set of false positive genes deregulated by the commonly used <it>GFP </it>siRNA as a reference resource for future siRNA experiments.</p

A randomized phase II study of radiation induced immune boost in operable non-small cell lung cancer (RadImmune trial)

Background: Lung cancer is the leading cause of cancer deaths worldwide. Surgery, radiotherapy at conventional and high dose and chemotherapy are the mainstay for lung cancer treatment. Insufficient migration and activation of tumour specific effector T cells seem to be important reasons for inadequate host anti-tumour immune response. Ionizing radiation can induce a variety of immune responses. The goal of this randomized trial is to assess if a preoperative single fraction low dose radiation is able to improve anti-tumour immune response in operable early stage lung cancer. Methods/Design: This trial has been designed as an investigator-initiated, prospective, randomized, 2-armed phase II trial. Patients who are candidates for elective resection of early stage non-small cell lung cancer will be randomized into 2 arms. A total of 36 patients will be enrolled. The patients receive either 2 Gy or no radiation prescribed to their primary tumour. Radiation will be delivered by external beam radiotherapy using 3D radiotherapy or intensity-modulated radiation technique (IMRT) 7 days prior to surgical resection. The primary objective is to compare CD8+ T cell counts detected by immunohistochemistry in resected tumours following preoperative radiotherapy versus no radiotherapy. Secondary objectives include the association between CD8+ T cell counts and progression free survival, the correlation of CD8+ T cell counts quantified by immunohistochemistry and flow cytometry, local tumour control and recurrence patterns, survival, radiogenic treatment toxicity and postoperative morbidity and mortality. Further, frequencies of tumour reactive T cells in blood and bone marrow as well as whole blood cell transcriptomics and plasma-proteomics will be correlated with clinical outcome. Discussion: This unique intervention combining preoperative low dose radiation and surgical removal of early stage non-small cell lung cancer is designed to address the problem of inadequate host anti-tumour immune response. If successful, this study may affect the role of radiotherapy in lung cancer treatment. Trial registration: NCT02319408; Registration: December 29, 2014

EASIX for Prediction of Outcome in Hospitalized SARS-CoV-2 Infected Patients

Background: The coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and has evoked a pandemic that challenges public health-care systems worldwide. Endothelial cell dysfunction plays a key role in pathophysiology, and simple prognosticators may help to optimize allocation of limited resources. Endothelial activation and stress index (EASIX) is a validated predictor of endothelial complications and outcome after allogeneic stem cell transplantation. Aim of this study was to test if EASIX could predict life-threatening complications in patients with COVID-19. Methods: SARS-CoV-2-positive, hospitalized patients were enrolled onto a prospective non-interventional register study (n=100). Biomarkers were assessed at hospital admission. Primary endpoint was severe course of disease (mechanical ventilation and/or death, V/D). Results were validated in 126 patients treated in two independent institutions. Results: EASIX at admission was a strong predictor of severe course of the disease (odds ratio for a two-fold change 3.4, 95%CI 1.8-6.3, p<0.001), time to V/D (hazard ratio (HR) for a two-fold change 2.0, 95%CI 1.5-2.6, p<0.001) as well as survival (HR for a two-fold change 1.7, 95%CI 1.2-2.5, p=0.006). The effect was retained in multivariable analysis adjusting for age, gender, and comorbidities and could be validated in the independent cohort. At hospital admission EASIX correlated with increased suppressor of tumorigenicity-2, soluble thrombomodulin, angiopoietin-2, CXCL8, CXCL9 and interleukin-18, but not interferon-alpha. Conclusion: EASIX is a validated predictor of COVID19 outcome and an easy-to-access tool to segregate patients in need for intensive surveillance

Statistical analysis of high-dimensional biomedical data: a gentle introduction to analytical goals, common approaches and challenges

International audienceBackground: In high-dimensional data (HDD) settings, the number of variables associated with each observation is very large. Prominent examples of HDD in biomedical research include omics data with a large number of variables such as many measurements across the genome, proteome, or metabolome, as well as electronic health records data that have large numbers of variables recorded for each patient. The statistical analysis of such data requires knowledge and experience, sometimes of complex methods adapted to the respective research questions. Methods: Advances in statistical methodology and machine learning methods offer new opportunities for innovative analyses of HDD, but at the same time require a deeper understanding of some fundamental statistical concepts. Topic group TG9 “High-dimensional data” of the STRATOS (STRengthening Analytical Thinking for Observational Studies) initiative provides guidance for the analysis of observational studies, addressing particular statistical challenges and opportunities for the analysis of studies involving HDD. In this overview, we discuss key aspects of HDD analysis to provide a gentle introduction for non-statisticians and for classically trained statisticians with little experience specific to HDD. Results: The paper is organized with respect to subtopics that are most relevant for the analysis of HDD, in particular initial data analysis, exploratory data analysis, multiple testing, and prediction. For each subtopic, main analytical goals in HDD settings are outlined. For each of these goals, basic explanations for some commonly used analysis methods are provided. Situations are identified where traditional statistical methods cannot, or should not, be used in the HDD setting, or where adequate analytic tools are still lacking. Many key references are provided. Conclusions: This review aims to provide a solid statistical foundation for researchers, including statisticians and non-statisticians, who are new to research with HDD or simply want to better evaluate and understand the results of HDD analyses

Dissecting the Prognostic Significance and Functional Role of Progranulin in Chronic Lymphocytic Leukemia

Chronic lymphocytic leukemia (CLL) is known for its strong dependency on the tumor microenvironment. We found progranulin (GRN), a protein that has been linked to inflammation and cancer, to be upregulated in the serum of CLL patients compared to healthy controls, and increased GRN levels to be associated with an increased hazard for disease progression and death. This raised the question of whether GRN is a functional driver of CLL. We observed that recombinant GRN did not directly affect viability, activation, or proliferation of primary CLL cells in vitro. However, GRN secretion was induced in co-cultures of CLL cells with stromal cells that enhanced CLL cell survival. Gene expression profiling and protein analyses revealed that primary mesenchymal stromal cells (MSCs) in co-culture with CLL cells acquire a cancer-associated fibroblast-like phenotype. Despite its upregulation in the co-cultures, GRN treatment of MSCs did not mimic this effect. To test the relevance of GRN for CLL in vivo, we made use of the Eμ-TCL1 CLL mouse model. As we detected strong GRN expression in myeloid cells, we performed adoptive transfer of Eμ-TCL1 leukemia cells to bone marrow chimeric Grn−/− mice that lack GRN in hematopoietic cells. Thereby, we observed that CLL-like disease developed comparable in Grn−/− chimeras and respective control mice. In conclusion, serum GRN is found to be strongly upregulated in CLL, which indicates potential use as a prognostic marker, but there is no evidence that elevated GRN functionally drives the disease

Molecular Alterations and Association with Clinical Parameters

Lynch syndrome is caused by germline mutations of DNA mismatch repair (MMR) genes, most frequently MLH1 and MSH2. Recently, MMR-deficient crypt foci (MMR- DCF) have been identified as a novel lesion which occurs at high frequency in the intestinal mucosa from Lynch syndrome mutation carriers, but very rarely progress to cancer. To shed light on molecular alterations and clinical associations of MMR-DCF, we systematically searched the intestinal mucosa from Lynch syndrome patients for MMR-DCF by immunohistochemistry. The identified lesions were characterised for alterations in microsatellite-bearing genes with proven or suspected role in malignant transformation. We demonstrate that the prevalence of MMR-DCF (mean 0.84 MMR-DCF per 1 cm2 mucosa in the colorectum of Lynch syndrome patients) was significantly associated with patients’ age, but not with patients’ gender. No MMR-DCF were detectable in the mucosa of patients with sporadic MSI-H colorectal cancer (n = 12). Microsatellite instability of at least one tested marker was detected in 89% of the MMR-DCF examined, indicating an immediate onset of microsatellite instability after MMR gene inactivation. Coding microsatellite mutations were most frequent in the genes HT001 (ASTE1) with 33%, followed by AIM2 (17%) and BAX (10%). Though MMR deficiency alone appears to be insufficient for malignant transformation, it leads to measurable microsatellite instability even in single MMR-deficient crypts. Our data indicate for the first time that the frequency of MMR-DCF increases with patients’ age. Similar patterns of coding microsatellite instability in MMR-DCF and MMR-deficient cancers suggest that certain combinations of coding microsatellite mutations, including mutations of the HT001, AIM2 and BAX gene, may contribute to the progression of MMR-deficient lesions into MMR-deficient cancers