Sequencing Of Cell-free DNA Research Articles

Analytical and clinical validation of direct detection of antimicrobial resistance markers by plasma microbial cell-free DNA sequencing.

This manuscript is ideally suited for the Innovative Diagnostic Methods sections as it reports the analytical and clinical validation of a novel application of plasma microbial cell-free DNA sequencing for direct detection of seven selected antimicrobial resistance markers in 18 target pathogens. Clearly, it has potential clinical utility in optimizing therapy and was incorporated into the Karius test workflow in September 2023. In addition, the workflow could readily be adapted to expand the number of target bacteria and antimicrobial resistance markers as needed.

Clinical Utility of Metagenomic Next-Generation Sequencing of Plasma Microbial Cell-Free DNA: a Single-Center Retrospective Study

Abstract Infectious diseases account for significant morbidity and mortality in healthcare, and metagenomic next-generation sequencing of plasma microbial cell-free DNA has emerged as a promising non-invasive diagnostic tool in this scenario. However, the available data on the real impact of this test in clinical practice is limited and conflicting. In this context, we performed a retrospective evaluation of the utilization of this test at our institution since February 17, 2019. A total of 76 tests were performed in this period in 68 different patients. The mean age of the patients was 9 years old, with 40 being male (58.82%) and 28 female (41.18%). The ordering specialties included infectious diseases (82.90%), hematology/oncology (9.21%), neurology (3.95%), pulmonology (2.63%), and dermatology (1.31%). The vast majority of the tests were ordered as inpatient (73 tests, 96.05%). 45 tests (59.21%) resulted as positive, of which 19 (42.22%) were polymicrobial. The tests were concordant with conventional microbiological studies 47 times (61.84%). Most tests (67 tests, 88.16%) had no significant clinical impact, 8 tests (10.53%) had a positive impact, and one test (1.31%) had an indeterminate impact. No tests were determined to have a negative clinical impact. Overall, our data is consistent with most studies which assessed the clinical utility of metagenomic next-generation sequencing of plasma microbial cell-free DNA in the literature, showing that testing did not have a significant impact on patient care for the majority of cases. There were some cases, however, in which testing showed a positive impact in escalating or de-escalating antibiotic therapy. In conclusion, despite being mostly a bystander, in selected cases and in the right clinical context, the test can be useful to guide antimicrobial treatment without causing significant harm. More studies are needed to further investigate the real utility of the test.

Genomic and epigenomic analysis of plasma cell-free DNA identifies stemness features associated with worse survival in lethal prostate cancer.

Metastatic castration-resistant prostate cancer (mCRPC) resistant to androgen receptor signaling inhibitors (ARSIs) is often lethal. Liquid biopsy biomarkers for this deadly form of disease remain under investigation, and underpinning mechanisms remain ill-understood. We applied targeted cell-free DNA sequencing to 126 mCRPC patients from three academic cancer centers, and separately performed genome-wide cell-free DNA methylation sequencing on 43 plasma samples collected prior to the initiation of first-line ARSI treatment. To analyze the genome-wide sequencing data, we performed nucleosome-positioning and differential methylated region analysis. We additionally analyzed single-cell and bulk RNA sequencing data from 14 and 80 mCRPC patients, respectively, to develop and validate a stem-like signature, which we inferred from cell-free DNA. Targeted cell-free DNA sequencing detected AR/enhancer alterations prior to first-line ARSIs which correlated with significantly worse PFS (p = 0.01; HR = 2.12) and OS (p = 0.02; HR = 2.48). Plasma methylome analysis revealed that AR/enhancer lethal mCRPC patients have significantly higher promoter-level hypomethylation than AR/enhancer wild-type mCRPC patients (p < 0.0001). Moreover, gene ontology and CytoTRACE analysis of nucleosomally more accessible transcription factors in cell-free DNA revealed enrichment for stemness-associated transcription factors in lethal mCRPC patients. The resulting stemness signature was then validated in a completely held-out cohort of 80 mCRPC patients profiled by tumor RNA sequencing. We analyzed a total of 220 mCRPC patients, validated the importance of cell-free AR/enhancer alterations as a prognostic biomarker in lethal mCRPC and showed that the underlying mechanism for lethality involves reprogramming developmental states toward increased stemness.

The role of microbial cell free DNA sequencing in sepsis detection in the neonate.

The role of microbial cell free DNA sequencing in sepsis detection in the neonate.

Ultra-sensitive molecular residual disease detection through whole genome sequencing with single-read error correction

While whole genome sequencing (WGS) of cell-free DNA (cfDNA) holds enormous promise for detection of molecular residual disease (MRD), its performance is limited by WGS error rate. Here we introduce AccuScan, an efficient cfDNA WGS technology that enables genome-wide error correction at single read-level, achieving an error rate of 4.2 × 10−7, which is about two orders of magnitude lower than a read-centric de-noising method. The application of AccuScan to MRD demonstrated analytical sensitivity down to 10−6 circulating variant allele frequency at 99% sample-level specificity. AccuScan showed 90% landmark sensitivity (within 6 weeks after surgery) and 100% specificity for predicting relapse in colorectal cancer. It also showed 67% sensitivity and 100% specificity in esophageal cancer using samples collected within one week after surgery. When AccuScan was applied to monitor immunotherapy in melanoma patients, the circulating tumor DNA (ctDNA) levels and dynamic profiles were consistent with clinical outcomes. Overall, AccuScan provides a highly accurate WGS solution for MRD detection, empowering ctDNA detection at parts per million range without requiring high sample input or personalized reagents.

Longitudinal integrative cell-free DNA analysis in gestational diabetes mellitus

Gestational diabetes mellitus (GDM) presents varied manifestations throughout pregnancy and poses a complex clinical challenge. High-depth cell-free DNA (cfDNA) sequencing analysis holds promise in advancing our understanding of GDM pathogenesis and prediction. In 299 women with GDM and 299 matched healthy pregnant women, distinct cfDNA fragment characteristics associated with GDM are identified throughout pregnancy. Integrating cfDNA profiles with lipidomic and single-cell transcriptomic data elucidates functional changes linked to altered lipid metabolism processes in GDM. Transcription start site (TSS) scores in 50 feature genes are used as the cfDNA signature to distinguish GDM cases from controls effectively. Notably, differential coverage of the islet acinar marker gene PRSS1 emerges as a valuable biomarker for GDM. A specialized neural network model is developed, predicting GDM occurrence and validated across two independent cohorts. This research underscores the high-depth cfDNA early prediction and characterization of GDM, offering insights into its molecular underpinnings and potential clinical applications.

Clinical Utility of Plasma Microbial Cell-Free DNA Sequencing Among Immunocompromised Patients With Pneumonia.

Plasma microbial cell-free DNA (mcfDNA) sequencing can establish the etiology of multiple infectious syndromes by identifying microbial DNA in plasma. However, data are needed to define the clinical scenarios where this tool offers the highest clinical benefit. We conducted a prospective multicenter observational study that evaluated the impact of plasma mcfDNA sequencing compared with usual care testing among adults with hematologic malignancies. This is a secondary analysis of an expanded cohort that evaluated the clinical utility of plasma mcfDNA sequencing across prespecified and adjudicated outcomes. We examined the percentage of participants for whom plasma mcfDNA sequencing identified a probable cause of pneumonia or clinically relevant nonpneumonia infection. We then assessed potential changes in antimicrobial therapy based on plasma mcfDNA sequencing results and the potential for early mcfDNA testing to avoid bronchoscopy and its associated adverse events. Of 223 participants, at least 1 microbial detection by plasma mcfDNA sequencing was adjudicated as a probable cause of pneumonia in 57 (25.6%) and a clinically relevant nonpneumonia infection in 88 (39.5%). A probable cause of pneumonia was exclusively identified by plasma mcfDNA sequencing in 23 (10.3%) participants. Antimicrobial therapy would have changed for 41 (18.4%) participants had plasma mcfDNA results been available in real time. Among the 57 participants with a probable cause of pneumonia identified by plasma mcfDNA sequencing, bronchoscopy identified no additional probable cause of pneumonia in 52 (91.2%). Plasma mcfDNA sequencing could improve management of both pneumonia and other concurrent infections in immunocompromised patients with suspected pneumonia.

Non-invasive determination of gene expression in placental tissue using maternal plasma cell-free DNA fragmentation characters

BackgroundThe expression profiles of placental genes are crucial for understanding the pathogenesis of fetal development and placental-origin pregnancy syndromes. However, owing to ethical limitations and the risks of puncture sampling, it is difficult to obtain placental tissue samples repeatedly, continuously, multiple times, or in real time. Establishing a non-invasive method for predicting placental gene expression profiles through maternal plasma cell-free DNA (cfDNA) sequencing, which carries information about the source tissue and gene expression, can potentially solve this problem. MethodsPeripheral blood and placental samples were collected simultaneously from pregnant women who underwent cesarean section. Deep sequencing was performed on the separated plasma cfDNA and single-cell sequencing was performed on peripheral blood mononuclear cells (PBMC), chorioamniotic membranes (CAM), placental villi (PV), and decidua basalis (DB). The aggregation of corresponding information for each gene was combined with the transcriptome of PBMCs and a differential resolution transcriptome of the placenta. This combined information was then utilized for the construction of gene expression prediction models. After training, all models evaluated the correlation between the predicted and actual gene expression levels using external test set data. ResultsFrom five women, more than 20 million reads were obtained using deep sequencing for plasma cfDNA; PBMCs obtained 32,401 single-cell expression profiles; and placental tissue obtained 156,546 single-cell expression profiles (59,069, 44,921, and 52,556 for CAM, PV, and DB, respectively). The cells in the PBMC and placenta were clustered and annotated into five and eight cell types, respectively. A “DEPICT” gene expression prediction model was successfully constructed using deep neural networks. The predicted correlation coefficients were 0.75 in PBMCs, 0.84 in the placenta, and 0.78, 0.80, and 0.77 in CAM, BP, and PV respectively, and greater than 0.68 in different cell lines in the placenta. ConclusionThe DEPICT model, which can noninvasively predict placental gene expression profiles based on maternal plasma cfDNA fragmentation characteristics, was constructed to overcome the limitation of the inability to obtain real-time placental gene expression profiles and to improve research on noninvasive prediction of placental origin pregnancy syndrome.

Confirmation of Recurrent Lung Cancer Following Resection Using Liquid Biopsy, a Proof-of-Concept Real-World Study.

Appropriate management requires timely and accurate confirmation of non-small cell lung cancer (NSCLC) recurrence in patients who have had curative-intent surgical resection. We assessed the association between circulating tumor DNA (ctDNA) identified using amplicon sequencing and evidence of recurrence on CT surveillance. A prospective cohort study of NSCLC patients with early-stage disease undergoing curative-intent resection was conducted. Surveillance was performed post-operatively at pre-defined intervals with both liquid biopsy and chest CT imaging. Amplicon panel next-generation sequencing was performed on DNA and RNA from tumor tissue and on plasma cell-free DNA for tumor-informed ctDNA detection. Resected tumors from 78 NSCLC patients were analyzed. Alterations were detected on the DNA assay for 65 tumors and only on the RNA assay for 4 tumors. Of the 65 patients with alterations detected on the tumor DNA assay, 29 completed post-operative liquid biopsy testing. Four of those 29 patients had evidence of recurrence on imaging, of whom two had biopsy confirmation of recurrence and detectable ctDNA at the 12-month follow-up. Molecular confirmation of NSCLC recurrence can be provided through amplicon sequencing of plasma cell-free DNA in cases with imaging evidence of recurrence. Invasive tissue diagnosis may be avoidable in patients with ctDNA confirmation of recurrence that is suspected based on imaging. Further study of ctDNA assessment technologies in the setting of suspected recurrence is necessary to inform post-operative lung cancer surveillance guidelines.

Utility of Serial Microbial Cell-free DNA Sequencing for Inpatient and Outpatient Pathogen Surveillance Among Allogeneic Hematopoietic Stem Cell Transplant Recipients.

This study characterizes the clinical utility and validity of the Karius test (KT), a plasma microbial cell-free DNA sequencing platform, as an infection surveillance tool among hematopoietic stem cell transplant (HCT) recipients, including monitoring for cytomegalovirus (CMV) and detecting infections relative to standard microbiologic testing (SMT). A prospective, observational cohort study was performed among adult HCT recipients as inpatients and outpatients. Serial KTs were performed starting with 1 sample within 14 days before HCT, then weekly from 7-63 days posttransplant then monthly from 3-12 months post-HCT. Diagnostic performance of KT versus CMV polymerase chain reaction was evaluated with positive percent agreement and negative percent agreement. Infectious events (<12 months post-HCT) were extracted from medical records. For infectious events without positive SMT, 2 clinicians adjudicated KT results to determine if any detections were a probable cause. Difference in time from KT pathogen detection and infection onset was calculated. Of the 70 participants, mean age was 49.9 years. For CMV surveillance, positive percent agreement was 100% and negative percent agreement was 90%. There was strong correlation between CMV DNA and KT molecules per microliter (r 2: 0.84, P < .001). Of the 32 SMT+/KT+ infectious events, KT identified 26 earlier than SMT (median: -12 days) and an additional 5 diagnostically difficult pathogens identified by KT but not SMT. KT detected CMV with high accuracy and correlation with quantitative polymerase chain reaction. Among infectious events, KT demonstrated additive clinical utility by detecting pathogens earlier than SMT and those not detected by SMT.

Cost-Effectiveness of Plasma Microbial Cell-Free DNA Sequencing When Added to Usual Care Diagnostic Testing for Immunocompromised Host Pneumonia.

Immunocompromised host pneumonia (ICHP) is an important cause of morbidity and mortality, yet usual care (UC) diagnostic tests often fail to identify an infectious etiology. A US-based, multicenter study (PICKUP) among ICHP patients with hematological malignancies, including hematological cell transplant recipients, showed that plasma microbial cell-free DNA (mcfDNA) sequencing provided significant additive diagnostic value. The objective of this study was to perform a cost-effectiveness analysis (CEA) of adding mcfDNA sequencing to UC diagnostic testing for hospitalized ICHP patients. A semi-Markov model was utilized from the US third-party payer's perspective such that only direct costs were included, using a lifetime time horizon with discount rates of 3% for costs and benefits. Three comparators were considered: (1) All UC, which included non-invasive (NI) and invasive testing and early bronchoscopy; (2) All UC & mcfDNA; and (3) NI UC & mcfDNA & conditional UC Bronch (later bronchoscopy if the initial tests are negative). The model considered whether a probable causative infectious etiology was identified and if the patient received appropriate antimicrobial treatment through expert adjudication, and if the patient died in-hospital. The primary endpoints were total costs, life-years (LYs), equal value life-years (evLYs), quality-adjusted life-years (QALYs), and the incremental cost-effectiveness ratio per QALY. Extensive scenario and probabilistic sensitivity analyses (PSA) were conducted. At a price of $2000 (2023 USD) for the plasma mcfDNA, All UC & mcfDNA was more costly ($165,247 vs $153,642) but more effective (13.39 vs 12.47 LYs gained; 10.20 vs 9.42 evLYs gained; 10.11 vs 9.42 QALYs gained) compared to All UC alone, giving a cost/QALY of $16,761. NI UC & mcfDNA & conditional UC Bronch was also more costly ($162,655 vs $153,642) and more effective (13.19 vs 12.47 LYs gained; 9.96 vs 9.42 evLYs gained; 9.96 vs 9.42 QALYs gained) compared to All UC alone, with a cost/QALY of $16,729. The PSA showed that above a willingness-to-pay threshold of $50,000/QALY, All UC & mcfDNA was the preferred scenario on cost-effectiveness grounds (as it provides the most QALYs gained). Further scenario analyses found that All UC & mcfDNA always improved patient outcomes but was not cost saving, even when the price of mcfDNA was set to $0. Based on the evidence available at the time of this analysis, this CEA suggests that mcfDNA may be cost-effective when added to All UC, as well as in a scenario using conditional bronchoscopy when NI testing fails to identify a probable infectious etiology for ICHP. Adding mcfDNA testing to UC diagnostic testing should allow more patients to receive appropriate therapy earlier and improve patient outcomes.

Blood-based markers of differential efficacy of bipolar androgen therapy and enzalutamide in the randomized TRANSFORMER trial.

LBA5014 Background: Bipolar androgen therapy (BAT) for metastatic castration-resistant prostate cancer (mCRPC) is administered by alternating between supraphysiologic and near-castrate serum testosterone levels through intramuscular administration of testosterone cypionate 400mg given every 28 days together with ongoing androgen suppression. BAT is effective in a subset of patients, but evidence for predictive treatment selection is lacking. The goal of the study is to determine whether blood-based markers can be identified in the TRANSFORMER study, a randomized trial of abiraterone-pretreated mCRPC patients assigned to BAT or enzalutamide (Enza). Methods: We conducted whole genome and whole exome sequencing of circulating tumor DNA samples collected from the TRANSFORMER study. In this post-hoc biomarker study of a randomized trial, we sought to identify markers that predict preferential benefit from BAT or Enza in mCRPC patients progressing on abiraterone. We compared clinical or radiographic progression-free survival (PFS) and overall survival (OS) between BAT and Enza arms in subgroups defined by biomarker status and estimated treatment effects via the Cox regression model, stratified by duration of prior abiraterone treatment. To determine whether a molecular event is a predictive biomarker, we tested the interaction term of the dichotomized marker status by treatment arms. Statistical tests were two-sided, and p values ≤ 0.05 were deemed to indicate statistical significance. Results: We focused on somatic alterations implicated in androgen receptor (AR) signaling that can be detected at a relatively high frequency in blood samples. Whole genome sequencing and whole exome sequencing of cell-free DNA from 62 patients revealed tumor-specific AR pathway alterations, including AR point mutations and amplifications (33/62, 53.2%). In men with positive AR alterations detected in blood, BAT was more efficacious than Enza (median PFS 4.2 months vs. 2.9 months; hazard ratio [HR] 0.59[95% CI 0.25-1.37], P=0.22), while Enza was superior to BAT in those without AR alterations (median PFS 8.4 months vs. 3 months; HR 3.62[95%CI 1.44-9.1], P=0.006). We detected a significant interaction between AR alteration status and treatment types using PFS as the endpoint ( Pinteraction=0.002). The differential benefit is upheld with OS as the endpoint ( Pinteraction &lt;0.001). In men with positive AR alterations, OS was longer with BAT compared with Enza (median OS 29.6 months vs. 24.1 months; HR 0.41[95% CI 0.16-1.03], P=0.058). In contrast, in men without AR alterations, OS was worse with BAT compared with Enza (median OS 19.3 months vs. NR; HR 4.38[95% CI 1.21-15.89], P=0.025). Conclusions: Metastatic CRPC patients progressing on abiraterone with AR alterations detected in blood may benefit preferentially from BAT. Routine liquid biopsy testing may enable further adoption of BAT.

Longitudinal cell-free DNA characterization by low-coverage whole-genome sequencing in patients undergoing high-dose radiotherapy

Background and PurposeCurrent radiotherapy guidelines rely heavily on imaging-based monitoring. Liquid biopsy monitoring promises to complement imaging by providing frequent systemic information about the tumor. In particular, cell-free DNA (cfDNA) sequencing offers a tumor-agnostic approach, which lends itself to monitoring heterogeneous cohorts of cancer patients. MethodsWe collected plasma cfDNA from oligometastatic patients (OMD) and head-and-neck cancer patients (SCCHN) at six time points before, during, and after radiotherapy, and compared them to the plasma samples of healthy and polymetastatic volunteers. We performed low-pass (on average 7x) whole-genome sequencing on 93 plasma cfDNA samples and correlated copy number alterations and fragment length distributions to clinical and imaging findings. ResultsWe observed copy number alterations in 4/7 polymetastatic cancer patients, 1/7 OMD and 1/7 SCCHN patients, these patients’ imaging showed progression following radiotherapy. Using unsupervised learning, we identified cancer-specific fragment length features that showed a strong correlation with copy number-based tumor fraction estimates. In 4/4 HPV-positive SCCHN patient samples, we detected viral DNA that enabled the monitoring of very low tumor fraction samples. ConclusionsOur results indicate that an elevated tumor fraction is associated with tumor aggressiveness and systemic tumor spread. This information may be used to adapt treatment strategies. Further, we show that by detecting specific sequences such as viral DNA, the sensitivity of detecting cancer from cell-free DNA sequencing data can be greatly increased.

Diagnosis and genetic characterization of CNS metastases in lung cancer via shallow whole-genome sequencing of CSF cell-free DNA.

e14013 Background: The genetic characterization of CNS metastases in lung cancer is hindered by the limited sampling opportunities and genetic heterogeneity between intracranial and extracranial lesions. To address these challenges, this study uses cerebrospinal fluid (CSF) and blood samples, to detect and characterize CNS metastasis variants through shallow whole-genome sequencing (sWGS). Methods: From Dec. 2021 to Aug. 2023, 57 lung cancer patients were recruited, comprising 29 with leptomeningeal metastases (LMs) and 28 with only parenchymal brain metastases (PMs). A total of 66 blood and 112 CSF samples were collected for cfDNA sWGS to analyze chromosomal arm CNVs, focal amplifications (CN &gt; 5) and SNV/InDels. Cytology was also conducted on 95 of these CSF samples. Variant differences between PMs and extracranial metastases (EMs) were analyzed using the MSK-MET database. Results: CSF cfDNA concentration was significantly lower than that in plasma (p &lt; 0.0001), with 41.7% of samples unquantifiable, yet all samples successfully completed sWGS. The cfDNA tumor fraction in CSF was significantly higher than in paired plasma (p &lt; 0.0001), and most arm CNVs and gene amplifications exclusively detected in CSF. Cytology, as the gold standard for LM diagnosis, had a sensitivity of 0.76. The sensitivity for LM diagnosis based on aneuploidy and genomic amplification fraction (GAF) were 0.51 and 0.80, respectively, without compromising specificity. Gains in 1p, 7p, 11q, 16p, and 17q, as well as losses in 9p and 9q, were significantly more frequent in PMs compared to EMs and further increased in the LMs (p &lt; 0.05). Notably, losses in 1p, 4p, 5q, and 11p, significantly more frequent in PMs than in extracranial metastases, but showed a significant increase in gain frequency in LMs (p &lt; 0.05). In the LM group, the frequency of EGFR L858R and amplification of nearly the entire 7p where the EGFR located, were significantly increased, whereas KRAS G12D frequency significantly decreased (p &lt; 0.05). Conclusions: The characteristics of extremely low concentration but high tumor fraction of CSF cfDNA make it suitable for sWGS, enhancing LM diagnostic sensitivity without compromising specificity, and identifying molecular characteristics of CNS metastasis. These molecular features require further validation in larger prospective clinical cohorts, offering potential for personalized diagnosis and treatment of CNS metastases.

Liquid biopsy-based prediction of clinical benefit from immune checkpoint inhibitors in advanced biliary tract cancer.

e16179 Background: Immune checkpoint inhibitors (ICIs) show promising efficacy as first-line therapy for advanced biliary tract cancer (aBTC), but validated predictive biomarkers are lacking. Here, we identified liquid biopsy-based biomarkers and developed a prediction model. Methods: aBTC patients who received ICIs-based combination therapy as the first-line treatment were prospectively enrolled in this study (NCT06074029). Plasma samples were collected before the first and second immunotherapy infusion to perform cell-free DNA (cfDNA) sequencing of 1021 genes. Circulating tumor DNA (ctDNA) concentration was calculated by multiplying the mean variant allele frequency by the cfDNA concentration and ctDNA fold change was calculated by dividing on-treatment ctDNA concentration by the pre-treatment ctDNA concentration. Tumor mutation burden (TMB) was normalized using the cfDNA concentration. In addition, RNA was extracted from peripheral blood mononuclear cells to profile the leukocyte transcriptome using whole transcriptome sequencing, and the relative proportions of immune cells in leukocytes was deconvoluted using CIBERSORT algorithm. Log-rank and univariate Cox regression were used to evaluate the relationship between features and progression-free survival (PFS). Results: 37 patients were enrolled, with 62.2% having intrahepatic cholangiocarcinoma. The median age was 61 years and 54.1% of patients were females. The median PFS was 4.4 months. Variables related to PFS with the log-rank p value smaller than 0.05 (Table) were entered into a multivariate Cox regression using a stepwise approach for final variable selection. As a result, ctDNA fold change, KRAS mutation, and resting memory CD4 T cell level were used to construct a COX regression model to predict clinical benefit from ICIs. The model predicting 6-month PFS demonstrated an AUC of 0.909 (95% CI, 0.795-1.024). Internal validation, performed through a bootstrap analysis with 100 iterations, yielded an optimism-adjusted AUC estimate of 0.859. Conclusions: Our preliminary results support the excellent performance of this liquid biopsy-based multivariable model to early predict durable benefit from ICIs in aBTC. A large sample size and verifying this model with internal and external data are warranted. Clinical trial information: NCT06074029 . [Table: see text]

High-dose almonertinib in treatment-naïve EGFR-mutated NSCLC with CNS metastases: Efficacy and biomarker analysis.

2007 Background: Central nervous system (CNS) metastases is inevitable for epidermal growth factor receptor (EGFR)mutant non-small cell lung cancer (NSCLC). The pre-specified analysis of the FLAURA and other phase III studies has unveiled encouraging results in patients with CNS metastasis. Nevertheless, the availability of limited biomarkers poses a challenge for the early prediction of clinical effects. Methods: We launched a prospective, open-label, single-arm clinical trial across multiple centers (ACHIEVE). Participants, all diagnosed with EGFR-mutated NSCLC with CNS metastases, received first line treatment with high dose Almonertinib through once-daily oral administration, with each dose being 165 mg. The primary endpoints focused on progression free survival (PFS). Concurrently, we gathered baseline and end-of-first-cycle plasma samples, subjecting them to a comprehensive 520 gene-based sequencing analysis. Results: A total of 63 patients were selected and enrolled between Jul 6,2021 and Aug 31,2022. The median follow-up time, until Nov 30,2023, was 538 days. The confirmed Overall Response Rate (ORR) was 88.9% (56/63), while 42.9% (27/63) of patients progressed, with a median PFS of 17.71 months (11.96-NE). Moreover, a notable 88.9% (56/63) of intracranial lesions achieved either a Complete Response (CR) in 21 cases (33.3%) or a Partial Response (PR) in 35 cases (55.6%). To guide and enhance clinical strategy selection, we conducted a comprehensive biomarker evaluation using cell-free DNA (cfDNA) sequencing. Of the 60 baseline plasmas that passed quality control, 81.7% (46/60) were identified as having at least one somatic mutation (ctDNA+). No significant differences were observed between ctDNA+ and ctDNA- groups in terms of ORR (p = 0.33), intracranial ORR (p = 0.499), PFS (p = 0.363, HR = 1.75), and intracranial PFS (p = 0.562, HR = 1.56). Furthermore, we developed a novel algorithm named MedSR (Median Short cfDNA fragment Ratio) based on cfDNA fragment distribution patterns to quantify ctDNA amount. Notably, higher baseline MedSR values (above the median) predicted significantly poorer PFS (p = 0.001, HR = 0.22) and intracranial PFS (p = 0.067, HR = 0.35), demonstrating superior efficacy compared to traditional cfDNA biomarkers like maxAF. On Cycle 2, those achieving ctDNA clearance in C2D1, regardless of their ctDNA status on baseline, exhibited significantly improved PFS (p &lt; 0.001, HR = 4.63) and intracranial PFS (p = 0.001, HR = 5.71). Conclusions: High dose Almonertinib exhibited promising efficacy and maintained tolerable safety as a first-line therapy in EGFR-mutated NSCLC with CNS metastases. The novel MedSR score demonstrated potential value in predicting the efficacy of TKI treatment. Clinical trial information: NCT04808752 .

Serial Cell-Free DNA Sequencing in ROS1 Fusion-Positive Lung Cancers During Treatment With Entrectinib.

Patients with metastatic ROS1 fusion-positive non-small cell lung cancer (NSCLC) are effectively treated with entrectinib, a multikinase inhibitor. Whether serial targeted gene panel sequencing of cell-free DNA (cfDNA) can identify response and progression along with mechanisms of acquired resistance to entrectinib is underexplored. In patients with ROS1 fusion-positive NSCLC, coclinical trial plasma samples were collected before treatment, after two cycles, and after progression on entrectinib (global phase II clinical trial, ClinicalTrials.gov identifier: NCT02568267). Samples underwent cfDNA analysis using MSK-ACCESS. Variant allele frequencies of detectable alterations were correlated with objective response per RECIST v1.1 criteria. Twelve patients were included, with best response as partial response (n = 9, 75%), stable disease (n = 2, 17%), and progressive disease (PD; n = 1, 8%). A ROS1 fusion was variably detected in cfDNA; however, patients without a ROS1 fusion in cfDNA had no other somatic alterations detected, indicative of possible low cfDNA shedding. Clearance of the enrolling ROS1 fusion or concurrent non-ROS1 alterations (TP53, CDH1, NF1, or ARID1A mutations) was observed in response to entrectinib therapy. Radiologic PD was accompanied by redemonstration of a ROS1 fusion or non-ROS1 alterations. On-target resistance was rare; only one patient acquired ROS1 G2032R at the time of progression. Several patients acquired new off-target likely oncogenic alterations, including a truncating alteration in NF1. Serial cfDNA monitoring may complement radiographic assessments as determinants of response and resistance to entrectinib in ROS1 fusion-positive lung cancers in addition to detecting putative resistance mechanisms on progression.

Comprehensive analysis of plasma methylome reveals distinct patterns of methylation changes between responders and non-responders to neoadjuvant chemotherapy in breast cancer

The potential of cell-free DNA (cfDNA) methylation profiling in oncology is increasingly recognized for its ability to offer a comprehensive assessment of tumor biology. In this report, we explore the plasma methylome dynamics in patients with early breast cancer (BC) undergoing neoadjuvant chemotherapy (NACT) using an agnostic genome-wide approach with cell-free DNA immunoprecipitation and sequencing (cfMeDIP-seq). Our cohort comprised seven women with triple-positive BC, assessed for cfDNA methylation changes at multiple time points during their treatment course. Genome-wide analysis revealed distinctive patterns of differential methylation in patients achieving pathological complete response (pCR), with no significant epigenomic modifications in patients with residual disease (RD). Gene set enrichment analysis highlighted dynamic variations in functional pathways associated with therapy response, including metabolism, immune response, and response to xenobiotics, with a notable reversibility post-treatment. Principal component analysis of the differentially methylated regions demonstrated a clear distinction between pCR and RD patients, indicating the potential of cfMeDIP-seq for the non-invasive assessment of therapy response. Such findings suggest that cfMeDIP-seq could complement ctDNA offering broader insights into the global modifications induced by chemotherapy. Although future research is needed to validate and expand on our findings, we offer a proof-of-principle of the potential utility of cfMeDIP-seq in the personalized management of BC.

NIPT-PG: empowering non-invasive prenatal testing to learn from population genomics through an incremental pan-genomic approach.

Non-invasive prenatal testing (NIPT) is a quite popular approach for detecting fetal genomic aneuploidies. However, due to the limitations on sequencing read length and coverage, NIPT suffers a bottleneck on further improving performance and conducting earlier detection. The errors mainly come from reference biases and population polymorphism. To break this bottleneck, we proposed NIPT-PG, which enables the NIPT algorithm to learn from population data. A pan-genome model is introduced to incorporate variant and polymorphic loci information from tested population. Subsequently, we proposed a sequence-to-graph alignment method, which considers the read mis-match rates during the mapping process, and an indexing method using hash indexing and adjacency lists to accelerate the read alignment process. Finally, by integrating multi-source aligned read and polymorphic sites across the pan-genome, NIPT-PG obtains a more accurate z-score, thereby improving the accuracy of chromosomal aneuploidy detection. We tested NIPT-PG on two simulated datasets and 745 real-world cell-free DNA sequencing data sets from pregnant women. Results demonstrate that NIPT-PG outperforms the standard z-score test. Furthermore, combining experimental and theoretical analyses, we demonstrate the probably approximately correct learnability of NIPT-PG. In summary, NIPT-PG provides a new perspective for fetal chromosomal aneuploidies detection. NIPT-PG may have broad applications in clinical testing, and its detection results can serve as a reference for false positive samples approaching the critical threshold.

A Machine learning model for predicting sepsis based on an optimized assay for microbial cell-free DNA sequencing

ObjectiveTo integrate an enhanced molecular diagnostic technique to develop and validate a machine-learning model for diagnosing sepsis. MethodsWe prospectively enrolled patients suspected of sepsis from August 2021 to August 2023. Various feature selection algorithms and machine learning models were used to develop the model. The best classifier was selected using 5-fold cross validation set and then was applied to assess the performance of the model in the testing set. Additionally, we employed the Shapley Additive exPlanations (SHAP) method to illustrate the effects of the features. ResultsWe established an optimized mNGS assay and proposed using the copies of microbe-specific cell-free DNA per milliliter of plasma (CPM) as the detection signal to evaluate the real burden, with strong precision and high accuracy. In total, 237 patients were eligible for participation, which were randomly assigned to either the training set (70 %, n = 165) or the testing set (30 %, n = 72). The random forest classifier achieved accuracy, AUC and F1 scores of 0.830, 0.918 and 0.856, respectively, outperforming other machine learning models in the training set. Our model demonstrated clinical interpretability and achieved good prediction performance in differentiating between bacterial sepsis and non-sepsis, with an AUC value of 0.85 and an average precision of 0.91 in the testing set. Based on the SHAP value, the top nine features of the model were PCT, CPM, CRP, ALB, SBPmin, RRmax, CREA, PLT and HRmax. ConclusionWe demonstrated the potential of machine-learning approaches for predicting bacterial sepsis based on optimized mcfDNA sequencing assay accurately.