Ultrasensitive Detection of Chimerism by Single-Molecule Molecular Inversion Probe Capture and High-Throughput Sequencing of Copy Number Deletion Polymorphisms

IMPRESS: Improved methylation profiling using restriction enzymes and smMIP sequencing, combined with a new biomarker panel, creating a multi-cancer detection assay

BACKGROUND

Despite the worldwide progress in cancer diagnostics, more sensitive diagnostic biomarkers are needed. The methylome has been extensively investigated in the last decades, but a low-cost, bisulfite-free detection method for multiplex analysis is still lacking.

METHODS

We developed a methylation detection technique called IMPRESS, which combines methylation-sensitive restriction enzymes and single-molecule Molecular Inversion Probes. We used this technique for the development of a multi-cancer detection assay for eight of the most lethal cancer types worldwide. We selected 1791 CpG sites that can distinguish tumor from normal tissue based on DNA methylation. These sites were analysed with IMPRESS in 35 blood, 111 tumor and 114 normal samples. Finally, a classifier model was built.

RESULTS

We present the successful development of IMPRESS and validated it with ddPCR. The final classifier model discriminating tumor from normal samples was built with 358 CpG target sites and reached a sensitivity of 0.95 and a specificity of 0.91. Moreover, we provide data that highlight IMPRESS's potential for liquid biopsies.

CONCLUSIONS

We successfully created an innovative DNA methylation detection technique. By combining this method with a new multi-cancer biomarker panel, we developed a sensitive and specific multi-cancer assay, with potential use in liquid biopsies.

Ultrasensitive Quantitation of Genomic Chimerism by Single-Molecule Molecular Inversion Probe Capture and High-Throughput Sequencing of Copy Number Deletion Polymorphisms

Genomic chimerism represents co-existing cells with different genotypes and has diagnostic significance in transplant engraftment monitoring, residual cancer detection, and other contexts. We previously described an approach to chimerism detection by interrogating variably present or absent genomic loci using single-molecule molecular inversion probes (smMIPs) and next-generation sequencing, which provided ultrasensitive limits of detection (<1 in 10,000 cells) but was not reliably quantitative. Herein, smMIP testing was modified to accurately quantitate chimeric cells by incorporating copy number neutral control loci for data normalization and computationally modeling cell mixtures from individual-specific genotypes. Data demonstrate precision and accuracy over three orders of magnitude (0.01% to 50% chimerism). Seventy hematopoietic stem cell transplant specimens from single (n = 42) or double (n = 28) donors were evaluated, benchmarking smMIP against conventional variable number tandem repeat (VNTR) analysis and an unrelated, ultrasensitive polymorphism-specific quantitative PCR (PS-qPCR) assay. Quantitative concordance of all three assays was high (P < 0.0005, Pearson correlation coefficient), although smMIP correlated better with VNTR testing than PS-qPCR. smMIP and PS-qPCR collectively identified low-level chimerism in all specimens testing negative by VNTR (n = 41 and n = 45 of 48 specimens, respectively). This work demonstrates the feasibility of smMIP-based chimerism testing for quantitative and ultrasensitive measurement of genomic chimerism at practical levels approaching one in one million cells, and cross-validates the approach.

Promising Biomarkers of Radiation-Induced Lung Injury: A Review

Radiation-induced lung injury (RILI) is one of the main dose-limiting side effects in patients with thoracic cancer during radiotherapy. No reliable predictors or accurate risk models are currently available in clinical practice. Severe radiation pneumonitis (RP) or pulmonary fibrosis (PF) will reduce the quality of life, even when the anti-tumor treatment is effective for patients. Thus, precise prediction and early diagnosis of lung toxicity are critical to overcome this longstanding problem. This review summarizes the primary mechanisms and preclinical animal models of RILI reported in recent decades, and analyzes the most promising biomarkers for the early detection of lung complications. In general, ideal integrated models considering individual genetic susceptibility, clinical background parameters, and biological variations are encouraged to be built up, and more prospective investigations are still required to disclose the molecular mechanisms of RILI as well as to discover valuable intervention strategies.

A Curriculum for Genomic Education of Molecular Genetic Pathology Fellows: A Report of the Association for Molecular Pathology Training and Education Committee

Molecular genetic pathology (MGP) is a subspecialty of pathology and medical genetics and genomics. Genomic testing, which we define as that which generates large data sets and interrogates large segments of the genome in a single assay, is increasingly recognized as essential for optimal patient care through precision medicine. The most common genomic testing technologies in clinical laboratories are next-generation sequencing and microarray. It is essential to train in these methods and to consider the data generated in the context of the diagnosis, medical history, and other clinical findings of individual patients. Accordingly, updating the MGP fellowship curriculum to include genomics is timely, important, and challenging. At the completion of training, an MGP fellow should be capable of independently interpreting and signing out results of a wide range of genomic assays and, given the appropriate context and institutional support, of developing and validating new assays in compliance with applicable regulations. The Genomics Task Force of the MGP Program Directors, a working group of the Association for Molecular Pathology Training and Education Committee, has developed a genomics curriculum framework and recommendations specific to the MGP fellowship. These recommendations are presented for consideration and implementation by MGP fellowship programs with the understanding that MGP programs exist in a diversity of clinical practice environments with a spectrum of available resources.