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Background: First-line pembrolizumab plus chemotherapy has shown clinical benefit in patients with metastatic non-small cell lung cancer (NSCLC) regardless of tissue tumor mutational burden (tTMB) status. Blood tumor mutational burden (bTMB), assessed using plasma-derived circulating tumor DNA (ctDNA), may be a surrogate for tTMB. The KEYNOTE-782 study evaluated the correlation of bTMB with the efficacy of first-line pembrolizumab plus chemotherapy in NSCLC., Methods: Previously untreated patients with stage IV nonsquamous NSCLC received pembrolizumab 200 mg plus pemetrexed 500 mg/m 2 and investigator's choice of carboplatin area under the curve 5 mg/mL/min or cisplatin 75 mg/m 2 for 4 cycles, then pembrolizumab plus pemetrexed for ≤31 additional cycles every 3 weeks. Study objectives were to evaluate the association of baseline bTMB with objective response rate (ORR) (RECIST v1.1 by investigator assessment; primary), progression-free survival (PFS; RECIST v1.1 by investigator assessment), overall survival (OS), and adverse events (AEs; all secondary). A next-generation sequencing assay (GRAIL LLC) with a ctDNA panel that included lung cancer-associated and immune gene targets was used to measure bTMB., Results: 117 patients were enrolled; median time from first dose to data cutoff was 19.3 months (range, 1.0-35.5). ORR was 40.2 % (95 % CI 31.2-49.6 %), median PFS was 7.2 months (95 % CI 5.6-9.8) and median OS was 18.1 months (95 % CI 13.5-25.6). Treatment-related AEs occurred in 113 patients (96.6 %; grade 3-5, n = 56 [47.9 %]). Of patients with evaluable bTMB (n = 101), the area under the receiver operating characteristics curve for continuous bTMB to discriminate response was 0.47 (95 % CI 0.36-0.59). Baseline bTMB was not associated with PFS or OS (posterior probabilities of positive association: 16.8 % and 7.8 %, respectively)., Conclusions: AEs were consistent with the established safety profile of first-line pembrolizumab plus chemotherapy in NSCLC. Baseline bTMB did not show evidence of an association with efficacy., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: J.B. reports advisory roles with AbbVie, AstraZeneca, Bayer, BMS, Causalis, Merck Serono, MSD, Novartis, Roche, and Takeda and receiving research funding from Immunai, OncoHost, MSD, and AstraZeneca. D.R.A. reports personal fees/honoraria for consultancy or advisory roles and lectures from Roche, Genentech, AstraZeneca, Bristol Myers Squibb, Boehringer Ingleheim, MSD, Merck Serono, Eli Lilly, Gilead, Sanofi, Regeneron, Incyte, Pfizer, Takeda, and Novartis; and travel expenses from Roche, Bristol Myers Squibb, MSD, Sanofi, Regeneron, and Novartis. E.F. reports personal fees or honoraria for advisory roles from Abbvie, Amgen, AstraZeneca, Bayer, Bergen Bio, Bristol-Myers Squibb, Daiichi Sankyo, Eli Lilly, F. Hoffman-La Roche, GSK, Janssen, Merck Serono, MSD, Novartis, Peptomyc, Pfizer, Regeneron, Sanofi, Takeda, and Turning Point; speaker’s bureau fees from Amgen, AstraZeneca, Bristol Myers Squibb, Eli Lilly and Company, F. Hoffman-La Roche, Janssen, Medical Trends, Medscape, Merck Serono, MSD, Peervoice, Pfizer, Sanofi, Takeda, and Touch Oncology; and independent board membership with Grifols. M.P. reports lecture fees, honoraria, or other fees from Bristol Myers Squibb, Roche, MSD, AstraZeneca, Takeda, Eli Lilly and Company, F. Hoffman-La Roche, Janssen, and Pfizer; and research funds from MSD, AstraZeneca, Roche, Boehringer Ingleheim, and Bristol Myers Squibb. D.R.C. reports lecture fees, honoraria or other fees from Roche and AstraZeneca. S.M.T, J.K., and E.J.D. report employment with MSD. M.A. reports employment and stock ownership with MSD. N.H. reports advisory or consultancy roles and stock ownership with Curve Biosciences. R.Mc. and B.J. report employment with Grail LLC. R.Ma reports employment with Grail LLC and stock ownership with Illumina. D.B. reports employment with GRAIL LLC and stock ownership with Illumina. E.E., S.P.A., M.G., A.R., A.F., S.B.R., G.S., T.C. have no conflicts of interest to disclose., (Copyright © 2024 Merck Sharp & Dohme LLC., a subsidiary of Merck & Co., Inc., Rahway, NJ, USA, The Author(s). Published by Elsevier B.V. All rights reserved.)

The analytical validation is reported for a targeted methylation-based cell-free DNA multi-cancer early detection test designed to detect cancer and predict the cancer signal origin (tissue of origin). A machine-learning classifier was used to analyze the methylation patterns of >105 genomic targets covering >1 million methylation sites. Analytical sensitivity (limit of detection [95% probability]) was characterized with respect to tumor content by expected variant allele frequency and was determined to be 0.07%-0.17% across five tumor cases and 0.51% for the lymphoid neoplasm case. Test specificity was 99.3% (95% confidence interval, 98.6-99.7%). In the reproducibility and repeatability study, results were consistent in 31/34 (91.2%) pairs with cancer and 17/17 (100%) pairs without cancer; between runs, results were concordant for 129/133 (97.0%) cancer and 37/37 (100%) non-cancer sample pairs. Across 3- to 100-ng input levels of cell-free DNA, cancer was detected in 157/182 (86.3%) cancer samples but not in any of the 62 non-cancer samples. In input titration tests, cancer signal origin was correctly predicted in all tumor samples detected as cancer. No cross-contamination events were observed. No potential interferent (hemoglobin, bilirubin, triglycerides, genomic DNA) affected performance. The results of this analytical validation study support continued clinical development of a targeted methylation cell-free DNA multi-cancer early detection test., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: GA, WL, FEO, MR, PS, JRB, LE, GN, AM, PWM and NH are former employees of GRAIL, LLC and may have equity in the company. MHM is a consultant to Delfi Diagnostics and to Fellow Health and a former employee of GRAIL, LLC, with equity in all three companies. AMA is an advisor to Foresite Labs, San Francisco, California and Boston, Massachusetts, and a former employee of GRAIL, LLC, and holds equity in both companies. All other authors are employees of GRAIL, LLC, with equity in the company. GRAIL, LLC is a subsidiary of Illumina, Inc. currently held separate from Illumina Inc. under the terms of the Interim Measures Order of the European Commission dated 29 October 2021., (Copyright: © 2023 Alexander et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

In the Circulating Cell-free Genome Atlas (NCT02889978) substudy 1, we evaluate several approaches for a circulating cell-free DNA (cfDNA)-based multi-cancer early detection (MCED) test by defining clinical limit of detection (LOD) based on circulating tumor allele fraction (cTAF), enabling performance comparisons. Among 10 machine-learning classifiers trained on the same samples and independently validated, when evaluated at 98% specificity, those using whole-genome (WG) methylation, single nucleotide variants with paired white blood cell background removal, and combined scores from classifiers evaluated in this study show the highest cancer signal detection sensitivities. Compared with clinical stage and tumor type, cTAF is a more significant predictor of classifier performance and may more closely reflect tumor biology. Clinical LODs mirror relative sensitivities for all approaches. The WG methylation feature best predicts cancer signal origin. WG methylation is the most promising technology for MCED and informs development of a targeted methylation MCED test., Competing Interests: Declaration of interests A.J., O.V., E.H., J.F.B., S.G., Q.L., N.Z., E.T.F., K.N.K., H.A., C.B., D.C., K.D., S.F., C.H., R.J., B.J., S.T., C.M., V.D., J.N., O.S., E.S., A.S., S.S., K.K.S., V.N., A.P.F., T.C.C., S.B., N.H., M.D., Z.D., and M.P.H. are employees of GRAIL, LLC, with equity in Illumina, Inc. C.M. also holds stock in Novartis, Clovis, Cara, Gilead, and Bluebird. M.C.L. is an uncompensated consultant for GRAIL, LLC. The Mayo Clinic was compensated for M.C.L.’s and D.D.T.’s advisory board activities for GRAIL, LLC. E.A.K. is a consultant for GRAIL, LLC. D.A.R. is a consultant for Ipsen. M.A.S. is a consultant for Celgene, Millennium, and Syros Pharmaceuticals. A.M.A. was previously employed by GRAIL, LLC; has equity in Illumina, Inc.; is currently employed by Illumina, Inc.; and is an advisor to and an equity holder in Foresite Labs and Myst Therapeutics. M.V.S. is an employee of and holds stock in McKesson Corporation, and is a clinical adviser for GRAIL, LLC. D.A.B. is a co-owner of Berry Consultants, LLC. A.H.B. is a consultant for Pfizer, Merck, Bayer, and Astellas Pharmaceuticals. C.S. holds stock in Illumina, Inc., Epic Biosciences, and Apogen Biotech; receives grants from Pfizer and AstraZeneca; receives honoraria or consultant fees from Roche Ventana, Celgene, Pfizer, Novartis, Genentech, and BMS; and is a co-founder of Achilles Therapeutics. S.G., O.V., A.P.F., A.J., K.D., V.N., J.F.B., C.M., E.H., Q.L., N.Z., P.F., and O.S. are inventors on pending patent applications related to this work, for which GRAIL, LLC, has ownership rights. GRAIL, LLC, a subsidiary of Illumina, Inc., is currently held separate from Illumina, Inc., under the terms of the Interim Measures Order of the European Commission dated October 29, 2021. C.S. recieved grant support from AstraZeneca, Boehringer-Ingelheim, Bristol Myers Squibb, Pfizer, Roche-Ventana, Invitae (previously Archer Dx Inc), and Ono Pharmaceutical; is an AstraZeneca Advisory Board member and Chief Investigator for the AZ MeRmaiD 1 and 2 clinical trials and is also Co-Chief Investigator of the NHS Galleri trial funded by GRAIL and a paid member of GRAIL’s Scientific Advisory Board (SAB); received consultant fees from Achilles Therapeutics (also SAB member), Bicycle Therapeutics (also a SAB member), Genentech, Medicxi, Roche Innovation Centre – Shanghai, Metabomed, and the Sarah Cannon Research Institute; received honoraria from Amgen, AstraZeneca, Pfizer, Novartis, GlaxoSmithKline, MSD, Bristol Myers Squibb, Illumina, and Roche-Ventana; had stock options in Apogen Biotechnologies and GRAIL until June 2021, and currently has stock options in Epic Bioscience, Bicycle Therapeutics, and Achilles Therapeutics; and is a co-founder of Achilles Therapeutics; holds patents relating to assay technology to detect tumour recurrence (PCT/GB2017/053289), targeting neoantigens (PCT/EP2016/059401), identifying patent response to immune checkpoint blockade (PCT/EP2016/071471), determining HLA LOH (PCT/GB2018/052004), predicting survival rates of patients with cancer (PCT/GB2020/050221), and identifying patients who respond to cancer treatment (PCT/GB2018/051912); holds US patent relating to detecting tumour mutations (PCT/US2017/28013), methods for lung cancer detection (US20190106751A1); and holds both a European and US patent related to identifying insertion/deletion mutation targets (PCT/GB2018/051892). C.S. is a Royal Society Napier Research Professor (RSRP\R\210001) and has received funding from the Francis Crick Institute that receives its core funding from Cancer Research UK (CC2041), the UK Medical Research Council (CC2041), and the Wellcome Trust (CC2041); Cancer Research UK (TRACERx [C11496/A17786], PEACE [C416/A21999], and CRUK Cancer Immunotherapy Catalyst Network); Cancer Research UK Lung Cancer Centre of Excellence (C11496/A30025); the Rosetrees Trust, Butterfield and Stoneygate Trusts; NovoNordisk Foundation (ID16584); Royal Society Professorship Enhancement Award (RP/EA/180007); National Institute for Health Research (NIHR) University College London Hospitals Biomedical Research Centre; the Cancer Research UK-University College London Centre; Experimental Cancer Medicine Centre; the Breast Cancer Research Foundation (US) (BCRF-22-157); Cancer Research UK Early Detection and Diagnosis Primer Award (Grant EDDPMA-Nov21/100034); The Mark Foundation for Cancer Research Aspire Award (Grant 21-029-ASP); Stand Up To Cancer-LUNGevity American Lung Association Lung Cancer Interception Dream Team Translational Research Grant (Grant Number: SU2C-AACR-DT23-17); and an ERC Advanced Grant (PROTEUS) from the European Research Council under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 835297)., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

Purpose: As immune checkpoint inhibitors (ICI) become increasingly used in frontline settings, identifying early indicators of response is needed. Recent studies suggest a role for circulating tumor DNA (ctDNA) in monitoring response to ICI, but uncertainty exists in the generalizability of these studies. Here, the role of ctDNA for monitoring response to ICI is assessed through a standardized approach by assessing clinical trial data from five independent studies., Patients and Methods: Patient-level clinical and ctDNA data were pooled and harmonized from 200 patients across five independent clinical trials investigating the treatment of patients with non-small-cell lung cancer with programmed cell death-1 (PD-1)/programmed death ligand-1 (PD-L1)-directed monotherapy or in combination with chemotherapy. CtDNA levels were measured using different ctDNA assays across the studies. Maximum variant allele frequencies were calculated using all somatic tumor-derived variants in each unique patient sample to correlate ctDNA changes with overall survival (OS) and progression-free survival (PFS)., Results: We observed strong associations between reductions in ctDNA levels from on-treatment liquid biopsies with improved OS (OS; hazard ratio, 2.28; 95% CI, 1.62 to 3.20; P < .001) and PFS (PFS; hazard ratio 1.76; 95% CI, 1.31 to 2.36; P < .001). Changes in the maximum variant allele frequencies ctDNA values showed strong association across different outcomes., Conclusion: In this pooled analysis of five independent clinical trials, consistent and robust associations between reductions in ctDNA and outcomes were found across multiple end points assessed in patients with non-small-cell lung cancer treated with an ICI. Additional tumor types, stages, and drug classes should be included in future analyses to further validate this. CtDNA may serve as an important tool in clinical development and an early indicator of treatment benefit.

Introduction: Non-invasive prenatal testing (NIPT) for aneuploidy using cell-free DNA in maternal plasma has been widely adopted. Recently, NIPT coverage has expanded to detect subchromosomal abnormalities including the 22q11.2 deletion. Validation of a SNP-based NIPT for detection of 22q11.2 deletions demonstrating a high sensitivity (97.8%) and specificity (99.75%) has been reported. We sought to further demonstrate the performance of a revised version of the test in a larger set of pregnancy plasma samples., Methods: Blood samples from pregnant women (10 with 22q11.2-deletion‒affected fetuses and 390 negative controls) were successfully analyzed using a revised SNP-based NIPT for the 22q11.2 deletion. The sensitivity and specificity of the assay were measured., Results: Sensitivity of the assay was 90% (9/10), and specificity of the assay was 99.74% (389/390), with a corresponding false positive-rate of 0.26%., Discussion: The data presented in this study add to the growing body of evidence demonstrating the ability of the SNP-based NIPT to detect 22q11.2 deletions with high sensitivity and specificity.

Objective: To validate an updated version (Version 2) of a single-nucleotide polymorphism (SNP)-based noninvasive prenatal test (NIPT) and to determine the likelihood of success when testing for fetal aneuploidies following a redraw., Methods: Version 2 was analytically validated using 587 plasma samples with known genotype (184 trisomy 21, 37 trisomy 18, 15 trisomy 13, 9 monosomy X, 4 triploidy and 338 euploid). Sensitivity, specificity and no-call rate were calculated, and a fetal-fraction adjustment was applied to enable projection of these values in a commercial distribution. Likelihood of success of a second blood draw was computed based on fetal fraction and maternal weight from the first draw., Results: Validation of this methodology yielded high sensitivities (≥99.4%) and specificities (100%) for all conditions tested with an observed no-call rate of 2.3%. The no-call threshold for sample calling was reduced to 2.8% fetal fraction. The redraw success rate was driven by higher initial fetal fractions and lower maternal weights, with the fetal fraction being the more significant variable., Conclusions: The enhanced version of this SNP-based NIPT method showed a reduced no-call rate and a reduced fetal-fraction threshold for sample calling in comparison to the earlier version, while maintaining high sensitivity and specificity., (© 2016 The Author(s) Published by S. Karger AG, Basel.)

Objective: To estimate performance of a single-nucleotide polymorphism-based noninvasive prenatal screen for fetal aneuploidy in high-risk and low-risk populations on single venopuncture., Methods: One thousand sixty-four maternal blood samples from 7 weeks of gestation and beyond were included; 1,051 were within specifications and 518 (49.3%) were low risk. Cell-free DNA was amplified, sequenced, and analyzed using the Next-generation Aneuploidy Test Using SNPs algorithm. Samples were called as trisomies 21, 18, 13, or monosomy X, or euploid, and male or female., Results: Nine hundred sixty-six samples (91.9%) successfully generated a cell-free DNA result. Among these, sensitivity was 100% for trisomy 21 (58/58, confidence interval [CI] 93.8-100%), trisomy 13 (12/12, CI 73.5-100%), and fetal sex (358/358 female, CI 99.0-100%; 418/418 male, CI 99.1-100%), 96.0% for trisomy 18 (24/25, CI 79.7-99.9%), and 90% for monosomy X (9/10, CI 55.5-99.8%). Specificity for trisomies 21 and 13 was 100% (905/905, CI 99.6-100%; and 953/953, CI 99.6-100%, respectively) and for trisomy 18 and monosomy X was 99.9% (938/939, CI 99.4-100%; and 953/954, CI 99.4-100%, respectively). However, 16% (20/125) of aneuploid samples did not return a result; 50% (10/20) had a fetal fraction below the 1.5th percentile of euploid pregnancies. Aneuploidy rate was significantly higher in these samples (P<.001, odds ratio 9.2, CI 4.4-19.0). Sensitivity and specificity did not differ in low-risk and high-risk populations., Conclusions: This noninvasive prenatal screen performed with high sensitivity and specificity in high-risk and low-risk cohorts. Aneuploid samples were significantly more likely to not return a result; the number of aneuploidy samples was especially increased among samples with low fetal fraction. This underscores the importance of redraws or, in rare cases, invasive procedures based on low fetal fraction., Level of Evidence: II.

Profiling miRNA expression in cells that directly contribute to human disease pathogenesis is likely to aid the discovery of novel drug targets and biomarkers. However, tissue heterogeneity and the limited amount of human diseased tissue available for research purposes present fundamental difficulties that often constrain the scope and potential of such studies. We established a flow cytometry-based method for isolating pure populations of pathogenic T cells from bronchial biopsy samples of asthma patients, and optimized a high-throughput nano-scale qRT-PCR method capable of accurately measuring 96 miRNAs in as little as 100 cells. Comparison of circulating and airway T cells from healthy and asthmatic subjects revealed asthma-associated and tissue-specific miRNA expression patterns. These results establish the feasibility and utility of investigating miRNA expression in small populations of cells involved in asthma pathogenesis, and set a precedent for application of our nano-scale approach in other human diseases. The microarray data from this study (Figure 7) has been submitted to the NCBI Gene Expression Omnibus (GEO; http://ncbi.nlm.nih.gov/geo) under accession no. GSE31030.

The broad involvement of miRNAs in critical processes underlying development, tissue homoeostasis and disease has led to a surging interest among the research and pharmaceutical communities. To study miRNAs, it is essential that the quantification of microRNA levels is accurate and robust. By comparing wild-type to small RNA deficient mouse embryonic stem cells (mESC), we revealed a lack of accuracy and robustness in previous published multiplex qRT-PCR techniques. Here, we describe an optimized method, including purifying away excessive primers from previous multiplex steps before singleplex real time detection, which dramatically increases the accuracy and robustness of the technique. Furthermore, we explain how performing the technique on a microfluidic chip at nanoliter volumes significantly reduces reagent costs and permits time effective high throughput miRNA expression profiling.

Gene expression profiling using an AFLP-based technique generates a large number of gene fragments that require identification by sequencing. The DNA fragments vary in length from about 50-500 bp. Ion-pair reversed-phase HPLC can be used to purify selected double-stranded DNA fragments that represent differentially expressed genes. The gene fragments are sequenced directly after vacuum drying of the collected HPLC fractions.