Optimizing Detection of Kidney Transplant Injury by Assessment of Donor-Derived Cell-Free DNA via Massively Multiplex PCR.

Standard noninvasive methods for detecting renal allograft rejection and injury have poor sensitivity and specificity. Plasma donor-derived cell-free DNA (dd-cfDNA) has been reported to accurately detect allograft rejection and injury in transplant recipients and shown to discriminate rejection from stable organ function in kidney transplant recipients. This study used a novel single nucleotide polymorphism (SNP)-based massively multiplexed PCR (mmPCR) methodology to measure dd-cfDNA in various types of renal transplant recipients for the detection of allograft rejection/injury without prior knowledge of donor genotypes. A total of 300 plasma samples (217 biopsy-matched: 38 with active rejection (AR), 72 borderline rejection (BL), 82 with stable allografts (STA), and 25 with other injury (OI)) were collected from 193 unique renal transplant patients; dd- cfDNA was processed by mmPCR targeting 13,392 SNPs. Median dd-cfDNA was significantly higher in samples with biopsy-proven AR (2.3%) versus BL (0.6%), OI (0.7%), and STA (0.4%) (p < 0.0001 all comparisons). The SNP-based dd-cfDNA assay discriminated active from non-rejection status with an area under the curve (AUC) of 0.87, 88.7% sensitivity (95% CI, 77.7⁻99.8%) and 72.6% specificity (95% CI, 65.4⁻79.8%) at a prespecified cutoff (>1% dd-cfDNA). Of 13 patients with AR findings at a routine protocol biopsy six-months post transplantation, 12 (92%) were detected positive by dd-cfDNA. This SNP-based dd-cfDNA assay detected allograft rejection with superior performance compared with the current standard of care. These data support the feasibility of using this assay to detect disease prior to renal failure and optimize patient management in the case of allograft injury.

Corrigendum: Phylogenetic ctDNA analysis depicts early-stage lung cancer evolution.

This corrects the article DOI: 10.1038/nature22364.

Phylogenetic ctDNA analysis depicts early-stage lung cancer evolution.

The early detection of relapse following primary surgery for non-small-cell lung cancer and the characterization of emerging subclones, which seed metastatic sites, might offer new therapeutic approaches for limiting tumour recurrence. The ability to track the evolutionary dynamics of early-stage lung cancer non-invasively in circulating tumour DNA (ctDNA) has not yet been demonstrated. Here we use a tumour-specific phylogenetic approach to profile the ctDNA of the first 100 TRACERx (Tracking Non-Small-Cell Lung Cancer Evolution Through Therapy (Rx)) study participants, including one patient who was also recruited to the PEACE (Posthumous Evaluation of Advanced Cancer Environment) post-mortem study. We identify independent predictors of ctDNA release and analyse the tumour-volume detection limit. Through blinded profiling of postoperative plasma, we observe evidence of adjuvant chemotherapy resistance and identify patients who are very likely to experience recurrence of their lung cancer. Finally, we show that phylogenetic ctDNA profiling tracks the subclonal nature of lung cancer relapse and metastasis, providing a new approach for ctDNA-driven therapeutic studies.

Incidence of X and Y Chromosomal Aneuploidy in a Large Child Bearing Population.

BACKGROUND: X&Y chromosomal aneuploidies are among the most common human whole-chromosomal copy number changes, but the population-based incidence and prevalence in the child-bearing population is unclear. METHODS: This retrospective analysis of prospectively collected data leveraged a routine non-invasive prenatal test (NIPT) using parental genotyping to estimate the population-based incidence of X&Y chromosome variations in this population referred for NIPT (generally due to advanced maternal age). RESULTS: From 141,916 women and 29,336 men, 119 X&Y chromosomal abnormalities (prevalence: 1 in 1,439) were identified. Maternal findings include: 43 cases of 45,X (40 mosaic); 30 cases of 47,XXX (12 mosaic); 3 cases of 46,XX uniparental disomy; 2 cases of 46,XY/46,XX; 23 cases of mosaicism of unknown type; 2 cases of 47,XX,i(X)(q10). Paternal findings include: 2 cases of 47,XXY (1 mosaic); 10 cases of 47,XYY (1 mosaic); 4 partial Y deletions. CONCLUSIONS: Single chromosome aneuploidy was present in one of every 1,439 individuals considered in this study, showing 47,XXX; 47,XX,i(X)(q10); 47,XYY; 47,XXY, partial Y deletions, and a high level of mosaicism for 45,X. This expands significantly our understanding of X&Y chromosomal variations and fertility issues, and is critical for families and adults affected by these disorders. This current and extensive information on fertility will be beneficial for genetic counseling on prenatal diagnoses as well as for newly diagnosed postnatal cases.

Detection of Clonal and Subclonal Copy-Number Variants in Cell-Free DNA from Patients with Breast Cancer Using a Massively Multiplexed PCR Methodology.

We demonstrate proof-of-concept for the use of massively multiplexed PCR and next-generation sequencing (mmPCR-NGS) to identify both clonal and subclonal copy-number variants (CNVs) in circulating tumor DNA. This is the first report of a targeted methodology for detection of CNVs in plasma. Using an in vitro model of cell-free DNA, we show that mmPCR-NGS can accurately detect CNVs with average allelic imbalances as low as 0.5%, an improvement over previously reported whole-genome sequencing approaches. Our method revealed differences in the spectrum of CNVs detected in tumor tissue subsections and matching plasma samples from 11 patients with stage II breast cancer. Moreover, we showed that liquid biopsies are able to detect subclonal mutations that may be missed in tumor tissue biopsies. We anticipate that this mmPCR-NGS methodology will have broad applicability for the characterization, diagnosis, and therapeutic monitoring of CNV-enriched cancers, such as breast, ovarian, and lung cancer.

Detection of triploid, molar, and vanishing twin pregnancies by a single-nucleotide polymorphism-based noninvasive prenatal test.

OBJECTIVE: We sought to determine the ability of single-nucleotide polymorphism-based noninvasive prenatal testing (NIPT) to identify triploid, unrecognized twin, and vanishing twin pregnancies. STUDY DESIGN: The study included 30,795 consecutive reported clinical cases received for NIPT for fetal whole-chromosome aneuploidies; known multiple gestations were excluded. Cell-free DNA was isolated from maternal blood samples, amplified via 19,488-plex polymerase chain reaction, and sequenced. Sequencing results were analyzed to determine fetal chromosome copy number and to identify the presence of additional fetal haplotypes. RESULTS: Additional fetal haplotypes, indicative of fetal triploidy, vanishing twin, or undetected twin pregnancy, were identified in 130 (0.42%) cases. Clinical confirmation (karyotype for singleton pregnancies, ultrasound for multifetal pregnancies) was available for 58.5% (76/130) of cases. Of the 76 cases with confirmation, 42.1% were vanishing twin, 48.7% were viable twin, 5.3% were diandric triploids, and 3.9% were nontriploid pregnancies that lacked evidence of co-twin demise. One pregnancy had other indications suggesting triploidy but lacked karyotype confirmation. Of the 5 vanishing twin cases with a known date of demise, 100% of losses occurred in the first trimester; up to 8 weeks elapsed between loss and detection by NIPT. CONCLUSION: This single-nucleotide polymorphism-based NIPT successfully identified vanished twin, previously unrecognized twin, and triploid pregnancies. As vanishing twins are more likely to be aneuploid, and undetected residual cell-free DNA could bias NIPT results, the ability of this method to identify additional fetal haplotypes is expected to result in fewer false-positive calls and prevent incorrect fetal sex calls.

Evaluation of telemedicine for screening of diabetic retinopathy in the Veterans Health Administration.

OBJECTIVE: To explore the cost-effectiveness of telemedicine for the screening of diabetic retinopathy (DR) and identify changes within the demographics of a patient population after telemedicine implementation. DESIGN: A retrospective medical chart review (cohort study) was conducted. PARTICIPANTS: A total of 900 type 1 and type 2 diabetic patients enrolled in a medical system with a telemedicine screening program for DR. METHODS: The cost-effectiveness of the DR telemedicine program was determined by using a finite-horizon, discrete time, discounted Markov decision process model populated by parameters and testing frequency obtained from patient records. The model estimated the progression of DR and determined average quality-adjusted life years (QALYs) saved and average additional cost incurred by the telemedicine screening program. MAIN OUTCOME MEASURES: Diabetic retinopathy, macular edema, blindness, and associated QALYs. RESULTS: The results indicate that telemedicine screening is cost-effective for DR under most conditions. On average, it is cost-effective for patient populations of >3500, patients aged <80 years, and all racial groups. Observable trends were identified in the screening population since the implementation of telemedicine screening: the number of known DR cases has increased, the overall age of patients receiving screenings has decreased, the percentage of nonwhites receiving screenings has increased, the average number of miles traveled by a patient to receive a screening has decreased, and the teleretinal screening participation is increasing. CONCLUSIONS: The current teleretinal screening program is effective in terms of being cost-effective and increasing population reach. Future screening policies should give consideration to the age of patients receiving screenings and the system's patient pool size because our results indicate it is not cost-effective to screen patients aged older than 80 years or in populations with <3500 patients.

Timing of testing and treatment for asymptomatic diseases.

Many papers in the medical literature analyze the cost-effectiveness of screening for diseases by comparing a limited number of a priori testing policies under estimated problem parameters. However, this may be insufficient to determine the best timing of the tests or incorporate changes over time. In this paper, we develop and solve a Markov Decision Process (MDP) model for a simple class of asymptomatic diseases in order to provide the building blocks for analysis of a more general class of diseases. We provide a computationally efficient method for determining a cost-effective dynamic intervention strategy that takes into account (i) the results of the previous test for each individual and (ii) the change in the individual's behavior based on awareness of the disease. We demonstrate the usefulness of the approach by applying the results to screening decisions for Hepatitis C (HCV) using medical data, and compare our findings to current HCV screening recommendations.