Why Cell-Free DNA Can Be a "Game Changer" for Lung Allograft Monitoring for Rejection and Infection.

Purpose Of Review: Although there has been improvement in short-term clinical outcomes for patients following lung transplant (LT), advances have not translated into longer-term allograft survival. Furthermore, invasive biopsies are still standard of practice for monitoring LT recipients for allograft injury. We review the relevant literature supporting the role of using plasma donor-derived cell-free DNA (dd-cfDNA) as a non-invasive biomarker for LT allograft injury surveillance and discuss future research directions.

Association Between Total Cell Free DNA and SARS-CoV-2 In Kidney Transplant Patients: A Preliminary Study.

Background: Kidney transplant (KT) recipients are at high risk for developing severe COVID-19. Lowering immunosuppression levels in KT recipients with COVID-19 encourages native immune responses but can raise the risk of rejection. Donor-derived cell-free DNA (dd-cfDNA), reported as a fraction of total cfDNA, is a proven biomarker for KT rejection.

A novel donor-derived cell-free DNA assay for the detection of acute rejection in heart transplantation.

Background: Endomyocardial biopsy (EMB), the reference surveillance test for acute rejection (AR) in heart transplant (HTx) recipients, is invasive, costly, and shows significant interobserver variability. Recent studies indicate that donor-derived cell-free DNA (dd-cfDNA), obtained non-invasively from blood, is associated with AR and could reduce the frequency of EMB surveillance. The aim of this study was to examine the performance characteristics of a novel test for detecting AR in adult HTx recipients.

Clinical Validation of a Plasma Donor-derived Cell-free DNA Assay to Detect Allograft Rejection and Injury in Lung Transplant.

Background: Lung transplant patients are vulnerable to various forms of allograft injury, whether from acute rejection (AR) (encompassing acute cellular rejection [ACR] and antibody-mediated rejection [AMR]), chronic lung allograft dysfunction (CLAD), or infection (INFXN). Previous research indicates that donor-derived cell-free DNA (dd-cfDNA) is a promising noninvasive biomarker for the detection of AR and allograft injury. Our aim was to validate a clinical plasma dd-cfDNA assay for detection of AR and other allograft injury and to confirm and expand on dd-cfDNA and allograft injury associations observed in previous studies.

Impact of Circulating Tumor DNA-Based Detection of Molecular Residual Disease on the Conduct and Design of Clinical Trials for Solid Tumors.

Purpose: Earlier detection of cancer recurrence using circulating tumor DNA (ctDNA) to detect molecular residual disease (MRD) has the potential to dramatically affect cancer management. We review evidence supporting the use of ctDNA as a biomarker for detection of MRD and highlight the potential impact that ctDNA testing could have on the conduct of clinical trials.

Methods: We searched the literature using MEDLINE (via PubMed) for articles from January 1, 2000, focusing on studies that assessed ctDNA as a predictor of cancer recurrence.

Incorporation of Donor-derived Cell-free DNA Into Clinical Practice for Renal Allograft Management.

Background: Donor-derived cell-free DNA (dd-cfDNA) in plasma is an established noninvasive biomarker for allograft injury and rejection. A single-nucleotide polymorphism (SNP)-based massively multiplexed polymerase chain reaction methodology can be used to quantify dd-cfDNA in kidney transplant recipients. In this study we describe our clinical experience in using a SNP-based dd-cfDNA assay for the management of active rejection in renal transplant recipients.

Laplacian Scores-Based Feature Reduction in IoT Systems for Agricultural Monitoring and Decision-Making Support.

Internet of things (IoT) systems generate a large volume of data all the time. How to choose and transfer which data are essential for decision-making is a challenge. This is especially important for low-cost and low-power designs, for example Long-Range Wide-Area Network (LoRaWan)-based IoT systems, where data volume and frequency are constrained by the protocols.

Gene-set meta-analysis of lung cancer identifies pathway related to systemic lupus erythematosus.

Introduction: Gene-set analysis (GSA) is an approach using the results of single-marker genome-wide association studies when investigating pathways as a whole with respect to the genetic basis of a disease.

Methods: We performed a meta-analysis of seven GSAs for lung cancer, applying the method META-GSA. Overall, the information taken from 11,365 cases and 22,505 controls from within the TRICL/ILCCO consortia was used to investigate a total of 234 pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database.

Alcohol and lung cancer risk among never smokers: A pooled analysis from the international lung cancer consortium and the SYNERGY study.

It is not clear whether alcohol consumption is associated with lung cancer risk. The relationship is likely confounded by smoking, complicating the interpretation of previous studies. We examined the association of alcohol consumption and lung cancer risk in a large pooled international sample, minimizing potential confounding of tobacco consumption by restricting analyses to never smokers.

Cross-Cancer Genome-Wide Analysis of Lung, Ovary, Breast, Prostate, and Colorectal Cancer Reveals Novel Pleiotropic Associations.

Identifying genetic variants with pleiotropic associations can uncover common pathways influencing multiple cancers. We took a two-stage approach to conduct genome-wide association studies for lung, ovary, breast, prostate, and colorectal cancer from the GAME-ON/GECCO Network (61,851 cases, 61,820 controls) to identify pleiotropic loci. Findings were replicated in independent association studies (55,789 cases, 330,490 controls).

Fine mapping of chromosome 5p15.33 based on a targeted deep sequencing and high density genotyping identifies novel lung cancer susceptibility loci.

Chromosome 5p15.33 has been identified as a lung cancer susceptibility locus, however the underlying causal mechanisms were not fully elucidated. Previous fine-mapping studies of this locus have relied on imputation or investigated a small number of known, common variants.

META-GSA: Combining Findings from Gene-Set Analyses across Several Genome-Wide Association Studies.

Introduction: Gene-set analysis (GSA) methods are used as complementary approaches to genome-wide association studies (GWASs). The single marker association estimates of a predefined set of genes are either contrasted with those of all remaining genes or with a null non-associated background. To pool the p-values from several GSAs, it is important to take into account the concordance of the observed patterns resulting from single marker association point estimates across any given gene set.

Identification of shared and unique susceptibility pathways among cancers of the lung, breast, and prostate from genome-wide association studies and tissue-specific protein interactions.

Results from genome-wide association studies (GWAS) have indicated that strong single-gene effects are the exception, not the rule, for most diseases. We assessed the joint effects of germline genetic variations through a pathway-based approach that considers the tissue-specific contexts of GWAS findings. From GWAS meta-analyses of lung cancer (12 160 cases/16 838 controls), breast cancer (15 748 cases/18 084 controls) and prostate cancer (14 160 cases/12 724 controls) in individuals of European ancestry, we determined the tissue-specific interaction networks of proteins expressed from genes that are likely to be affected by disease-associated variants.

A two-dimensional pooling strategy for rare variant detection on next-generation sequencing platforms.

We describe a method for pooling and sequencing DNA from a large number of individual samples while preserving information regarding sample identity. DNA from 576 individuals was arranged into four 12 row by 12 column matrices and then pooled by row and by column resulting in 96 total pools with 12 individuals in each pool. Pooling of DNA was carried out in a two-dimensional fashion, such that DNA from each individual is present in exactly one row pool and exactly one column pool.

Empirical hierarchical bayes approach to gene-environment interactions: development and application to genome-wide association studies of lung cancer in TRICL.

The analysis of gene-environment (G × E) interactions remains one of the greatest challenges in the postgenome-wide association studies (GWASs) era. Recent methods constitute a compromise between the robust but underpowered case-control and powerful case-only methods. Inferences of the latter are biased when the assumption of gene-environment (G-E) independence in controls fails.

Association of the 15q25 and 5p15 lung cancer susceptibility regions with gene expression in lung tumor tissue.

Background: Genome-wide association studies have identified two independent lung cancer susceptibility loci at chromosome 15q25 and one locus at 5p15. We examined the association of genetic variants in these regions with gene expression in lung tumor tissue, in an effort to elucidate carcinogenic mechanisms by which these variants influence lung cancer risk.

Methods: We used data from 2 independent studies of non-small cell lung carcinoma patients: the JBR.

Comparison of pathway analysis approaches using lung cancer GWAS data sets.

Pathway analysis has been proposed as a complement to single SNP analyses in GWAS. This study compared pathway analysis methods using two lung cancer GWAS data sets based on four studies: one a combined data set from Central Europe and Toronto (CETO); the other a combined data set from Germany and MD Anderson (GRMD). We searched the literature for pathway analysis methods that were widely used, representative of other methods, and had available software for performing analysis.

Family-based association study of IGF1 microsatellites and height, weight, and body mass index.

Height, weight, and body mass index (BMI) are partly heritable, known to be associated with chronic diseases, and are linked to circulating insulin-like growth factor I (IGF-I) concentrations. IGF-I concentrations are also partly heritable and thus genetic variation at IGF1 could influence height, weight, BMI and the risk of developing chronic diseases. Our objective was to examine the association of genetic variation at IGF1 with height, weight and BMI using a sample of premenopausal women.

Family-based genetic association study of insulin-like growth factor I microsatellite markers and premenopausal breast cancer risk.

Several studies suggest that higher circulating insulin-like growth factor I (IGF-I) levels are associated with premenopausal breast cancer risk. Breast cancer risk and circulating IGF-I concentration appear to be partly heritable, thus genetic variation at IGF1 could influence IGF-I levels and breast cancer risk. We investigated the association of IGF1 CA repeat variants with premenopausal breast cancer risk using a family-based design.