Genome-wide cell-free DNA mutational integration enables ultra-sensitive cancer monitoring

The landscape of cell-free mitochondrial DNA in liquid biopsy for cancer detection

BACKGROUND

Existing methods to detect tumor signal in liquid biopsy have focused on the analysis of nuclear cell-free DNA (cfDNA). However, non-nuclear cfDNA and in particular mitochondrial DNA (mtDNA) has been understudied. We hypothesize that an increase in mtDNA in plasma could reflect the presence of cancer, and that leveraging cell-free mtDNA could enhance cancer detection.

RESULTS

We survey 203 healthy and 664 cancer plasma samples from three collection centers covering 12 cancer types with whole genome sequencing to catalogue the plasma mtDNA fraction. The mtDNA fraction is increased in individuals with cholangiocarcinoma, colorectal, liver, pancreatic, or prostate cancer, in comparison to that in healthy individuals. We detect almost no increase of mtDNA fraction in individuals with other cancer types. The mtDNA fraction in plasma correlates with the cfDNA tumor fraction as determined by somatic mutations and/or copy number aberrations. However, the mtDNA fraction is also elevated in a fraction of patients without an apparent increase in tumor-derived cfDNA. A predictive model integrating mtDNA and copy number analysis increases the area under the curve (AUC) from 0.73 when using copy number alterations alone to an AUC of 0.81.

CONCLUSIONS

The mtDNA signal retrieved by whole genome sequencing has the potential to boost the detection of cancer when combined with other tumor-derived signals in liquid biopsies.

Current and new frontiers in hereditary cancer surveillance: Opportunities for liquid biopsy

At least 5% of cancer diagnoses are attributed to a causal pathogenic or likely pathogenic germline genetic variant (hereditary cancer syndrome-HCS). These individuals are burdened with lifelong surveillance monitoring organs for a wide spectrum of cancers. This is associated with substantial uncertainty and anxiety in the time between screening tests and while the individuals are awaiting results. Cell-free DNA (cfDNA) sequencing has recently shown potential as a non-invasive strategy for monitoring cancer. There is an opportunity for high-yield cancer early detection in HCS. To assess clinical validity of cfDNA in individuals with HCS, representatives from eight genetics centers from across Canada founded the CHARM (cfDNA in Hereditary and High-Risk Malignancies) Consortium in 2017. In this perspective, we discuss operationalization of this consortium and early data emerging from the most common and well-characterized HCSs: hereditary breast and ovarian cancer, Lynch syndrome, Li-Fraumeni syndrome, and Neurofibromatosis type 1. We identify opportunities for the incorporation of cfDNA sequencing into surveillance protocols; these opportunities are backed by examples of earlier cancer detection efficacy in HCSs from the CHARM Consortium. We seek to establish a paradigm shift in early cancer surveillance in individuals with HCSs, away from highly centralized, regimented medical screening visits and toward more accessible, frequent, and proactive care for these high-risk individuals.

The role of platelets in the regulation of tumor growth and metastasis: the mechanisms and targeted therapy

Platelets are a class of pluripotent cells that, in addition to hemostasis and maintaining vascular endothelial integrity, are also involved in tumor growth and distant metastasis. The tumor microenvironment is a complex and comprehensive system composed of tumor cells and their surrounding immune and inflammatory cells, tumor-related fibroblasts, nearby interstitial tissues, microvessels, and various cytokines and chemokines. As an important member of the tumor microenvironment, platelets can promote tumor invasion and metastasis through various mechanisms. Understanding the role of platelets in tumor metastasis is important for diagnosing the risk of metastasis and prolonging survival. In this study, we more fully elucidate the underlying mechanisms by which platelets promote tumor growth and metastasis by modulating processes, such as immune escape, angiogenesis, tumor cell homing, and tumor cell exudation, and further summarize the effects of platelet-tumor cell interactions in the tumor microenvironment and possible tumor treatment strategies based on platelet studies. Our summary will more comprehensively and clearly demonstrate the role of platelets in tumor metastasis, so as to help clinical judgment of the potential risk of metastasis in cancer patients, with a view to improving the prognosis of patients.

Analysis of circulating tumor DNA during checkpoint inhibition in metastatic melanoma using a tumor-agnostic panel

Immunotherapy has revolutionized treatment of patients diagnosed with metastatic melanoma, where nearly half of patients receive clinical benefit. However, immunotherapy is also associated with immune-related adverse events, which may be severe and persistent. It is therefore important to identify patients that do not benefit from therapy early. Currently, regularly scheduled CT scans are used to investigate size changes in target lesions to evaluate progression and therapy response. This study aims to explore if panel-based analysis of circulating tumor DNA (ctDNA) taken at 3-week intervals may provide a window into the growing cancer, can be used to identify nonresponding patients early, and determine genomic alterations associated with acquired resistance to checkpoint immunotherapy without analysis of tumor tissue biopsies. We designed a gene panel for ctDNA analysis and sequenced 4-6 serial plasma samples from 24 patients with unresectable stage III or IV melanoma and treated with first-line checkpoint inhibitors enrolled at the Department of Oncology at Aarhus University Hospital, Denmark. TERT was the most mutated gene found in ctDNA and associated with a poor prognosis. We detected more ctDNA in patients with high metastatic load, which indicates that more aggressive tumors release more ctDNA into the bloodstream. Although we did not find evidence of specific mutations associated with acquired resistance, we did demonstrate in this limited cohort of 24 patients that untargeted, panel-based ctDNA analysis has the potential to be used as a minimally invasive tool in clinical practice to identify patients where the benefits of immunotherapy outweigh the drawbacks.

The impact of adjuvant EGFR-TKIs and 14-gene molecular assay on stage I non-small cell lung cancer with sensitive EGFR mutations

Background

Currently, the role of EGFR-TKIs as adjuvant therapy for stage I, especially IA NSCLC, after surgical resection remains unclear. We aimed to compare the effect of adjuvant EGFR-TKIs with observation in such patients by incorporating an established 14-gene molecular assay for risk stratification.

Methods

This retrospective cohort study was conducted at the First Affiliated Hospital of Guangzhou Medical University (Study ID: ChNCRCRD-2022-GZ01). From March 2013 to February 2019, completely resected stage I NSCLC (8th TNM staging) patients with sensitive EGFR mutation were included. Patients with eligible samples for molecular risk stratification were subjected to the 14-gene prognostic assay. Inverse probability of treatment weighting (IPTW) was employed to minimize imbalances in baseline characteristics.

Findings

A total of 227 stage I NSCLC patients were enrolled, with 55 in EGFR-TKI group and 172 in the observation group. The median duration of follow-up was 78.4 months. After IPTW, the 5-year DFS (HR = 0.30, 95% CI, 0.14-0.67; P = 0.003) and OS (HR = 0.26, 95% CI, 0.07-0.96; P = 0.044) of the EGFR-TKI group were significantly better than the observation group. For subgroup analyses, adjuvant EGFR-TKIs were associated with favorable 5-year DFS rates in both IA (100.0% vs. 84.5%; P = 0.007), and IB group (98.8% vs. 75.3%; P = 0.008). The 14-gene assay was performed in 180 patients. Among intermediate-high-risk patients, EGFR-TKIs were associated with a significant improvement in 5-year DFS rates compared to observation (96.0% vs. 70.5%; P = 0.012), while no difference was found in low-risk patients (100.0% vs. 94.9%; P = 0.360).

Interpretation

Our study suggested that adjuvant EGFR-TKI might improve DFS and OS of stage IA and IB EGFR-mutated NSCLC, and the 14-gene molecular assay could help patients that would benefit the most from treatment.

Funding

This work was supported by China National Science Foundation (82022048, 82373121).

Leveraging physiology and artificial intelligence to deliver advancements in health care

Artificial intelligence in health care has experienced remarkable innovation and progress in the last decade. Significant advancements can be attributed to the utilization of artificial intelligence to transform physiology data to advance health care. In this review, we explore how past work has shaped the field and defined future challenges and directions. In particular, we focus on three areas of development. First, we give an overview of artificial intelligence, with special attention to the most relevant artificial intelligence models. We then detail how physiology data have been harnessed by artificial intelligence to advance the main areas of health care: automating existing health care tasks, increasing access to care, and augmenting health care capabilities. Finally, we discuss emerging concerns surrounding the use of individual physiology data and detail an increasingly important consideration for the field, namely the challenges of deploying artificial intelligence models to achieve meaningful clinical impact.

Predicting tumour content of liquid biopsies from cell-free DNA

BACKGROUND

Liquid biopsy is a minimally-invasive method of sampling bodily fluids, capable of revealing evidence of cancer. The distribution of cell-free DNA (cfDNA) fragment lengths has been shown to differ between healthy subjects and cancer patients, whereby the distributional shift correlates with the sample's tumour content. These fragmentomic data have not yet been utilised to directly quantify the proportion of tumour-derived cfDNA in a liquid biopsy.

RESULTS

We used statistical learning to predict tumour content from Fourier and wavelet transforms of cfDNA length distributions in samples from 118 cancer patients. The model was validated on an independent dilution series of patient plasma.

CONCLUSIONS

This proof of concept suggests that our fragmentomic methodology could be useful for predicting tumour content in liquid biopsies.

Liquid Biopsies for Colorectal Cancer and Advanced Adenoma Screening and Surveillance: What to Measure?

Colorectal cancer (CRC) colonoscopic surveillance is effective but burdensome. Circulating tumor DNA (ctDNA) analysis has emerged as a promising, minimally invasive tool for disease detection and management. Here, we assessed which ctDNA assay might be most suitable for a ctDNA-based CRC screening/surveillance blood test. In this prospective, proof-of-concept study, patients with colonoscopies for Lynch surveillance or the National Colorectal Cancer screening program were included between 7 July 2019 and 3 June 2022. Blood was drawn, and if advanced neoplasia (adenoma with villous component, high-grade dysplasia, ≥10 mm, or CRC) was detected, it was analyzed for chromosomal copy number variations, single nucleotide variants, and genome-wide methylation (MeD-seq). Outcomes were compared with corresponding patients' tissues and the MeD-seq results of healthy blood donors. Two Lynch carriers and eight screening program patients were included: five with CRC and five with advanced adenomas. cfDNA showed copy number variations and single nucleotide variants in one patient with CRC and liver metastases. Eight patients analyzed with MeD-seq showed clustering of Lynch-associated and sporadic microsatellite instable lesions separate from microsatellite stable lesions, as did healthy blood donors. In conclusion, whereas copy number changes and single nucleotide variants were only detected in one patient, cfDNA methylation profiles could discriminate all microsatellite instable advanced neoplasia, rendering this tool particularly promising for LS surveillance. Larger studies are warranted to validate these findings.

Identifying Mechanisms of Resistance by Circulating Tumor DNA in EVOLVE, a Phase II Trial of Cediranib Plus Olaparib for Ovarian Cancer at Time of PARP Inhibitor Progression

PURPOSE

To evaluate the use of blood cell-free DNA (cfDNA) to identify emerging mechanisms of resistance to PARP inhibitors (PARPi) in high-grade serous ovarian cancer (HGSOC).

EXPERIMENTAL DESIGN

We used targeted sequencing (TS) to analyze 78 longitudinal cfDNA samples collected from 30 patients with HGSOC enrolled in a phase II clinical trial evaluating cediranib (VEGF inhibitor) plus olaparib (PARPi) after progression on PARPi alone. cfDNA was collected at baseline, before treatment cycle 2, and at end of treatment. These were compared with whole-exome sequencing (WES) of baseline tumor tissues.

RESULTS

At baseline (time of initial PARPi progression), cfDNA tumor fractions were 0.2% to 67% (median, 3.25%), and patients with high ctDNA levels (>15%) had a higher tumor burden (sum of target lesions; P = 0.043). Across all timepoints, cfDNA detected 74.4% of mutations known from prior tumor WES, including three of five expected BRCA1/2 reversion mutations. In addition, cfDNA identified 10 novel mutations not detected by WES, including seven TP53 mutations annotated as pathogenic by ClinVar. cfDNA fragmentation analysis attributed five of these novel TP53 mutations to clonal hematopoiesis of indeterminate potential (CHIP). At baseline, samples with significant differences in mutant fragment size distribution had shorter time to progression (P = 0.001).

CONCLUSIONS

Longitudinal testing of cfDNA by TS provides a noninvasive tool for detection of tumor-derived mutations and mechanisms of PARPi resistance that may aid in directing patients to appropriate therapeutic strategies. With cfDNA fragmentation analyses, CHIP was identified in several patients and warrants further investigation.

Phase I trial of Ganitumab plus Dasatinib to Cotarget the Insulin-Like Growth Factor 1 Receptor and Src Family Kinase YES in Rhabdomyosarcoma

PURPOSE

Antibodies against insulin-like growth factor (IGF) type 1 receptor have shown meaningful but transient tumor responses in patients with rhabdomyosarcoma (RMS). The SRC family member YES has been shown to mediate IGF type 1 receptor (IGF-1R) antibody acquired resistance, and cotargeting IGF-1R and YES resulted in sustained responses in murine RMS models. We conducted a phase I trial of the anti-IGF-1R antibody ganitumab combined with dasatinib, a multi-kinase inhibitor targeting YES, in patients with RMS (NCT03041701).

PATIENTS AND METHODS

Patients with relapsed/refractory alveolar or embryonal RMS and measurable disease were eligible. All patients received ganitumab 18 mg/kg intravenously every 2 weeks. Dasatinib dose was 60 mg/m2/dose (max 100 mg) oral once daily [dose level (DL)1] or 60 mg/m2/dose (max 70 mg) twice daily (DL2). A 3+3 dose escalation design was used, and maximum tolerated dose (MTD) was determined on the basis of cycle 1 dose-limiting toxicities (DLT).

RESULTS

Thirteen eligible patients, median age 18 years (range 8-29) enrolled. Median number of prior systemic therapies was 3; all had received prior radiation. Of 11 toxicity-evaluable patients, 1/6 had a DLT at DL1 (diarrhea) and 2/5 had a DLT at DL2 (pneumonitis, hematuria) confirming DL1 as MTD. Of nine response-evaluable patients, one had a confirmed partial response for four cycles, and one had stable disease for six cycles. Genomic studies from cell-free DNA correlated with disease response.

CONCLUSIONS

The combination of dasatinib 60 mg/m2/dose daily and ganitumab 18 mg/kg every 2 weeks was safe and tolerable. This combination had a disease control rate of 22% at 5 months.

Cell-free DNA approaches for cancer early detection and interception

Rapid advancements in the area of early cancer detection have brought us closer to achieving the goals of finding cancer early enough to treat or cure it, while avoiding harms of overdiagnosis. We evaluate progress in the development of early cancer detection tests in the context of the current principles for cancer screening. We review cell-free DNA (cfDNA)-based approaches using mutations, methylation, or fragmentomes for early cancer detection. Lastly, we discuss the challenges in demonstrating clinical utility of these tests before integration into routine clinical care.

Circulating tumor DNA in breast cancer: a biomarker for patient selection

PURPOSE OF REVIEW

This review aims to explore the role of circulating tumor DNA (ctDNA) as a biomarker for patient selection in breast cancer. We describe the current evidence and the main ongoing trials both in the early and metastatic setting.

RECENT FINDINGS

In the metastatic setting, the analysis of ctDNA can identify specific genetic alterations amenable of molecularly targeted treatments. Several assays are now approved for the detection of genetic alterations in plasma cell-free DNA to guide treatment decision (e.g., PIK3CA mutations for PI3K inhibitors, and ESR1 mutations for the selective estrogen receptor degrader elacestrant). In the early setting, emerging evidence is demonstrating that ctDNA can identify a disease relapse with a lead-time of approximately 10 months before imaging. This could help select patients who may benefit from escalation treatment strategy, although this hypothesis needs to be first prospectively validated.

SUMMARY

Liquid biopsy for ctDNA detection represents an exciting new field in rapid evolution. Several trials are ongoing to validate the clinical utility of ctDNA in daily practice in the early setting and to expand its current indications in the metastatic one.

Strategies for improving detection of circulating tumor DNA using next generation sequencing

Cancer has become a global health issue and liquid biopsy has emerged as a non-invasive tool for various applications. In cancer, circulating tumor DNA (ctDNA) can be detected from cell-free DNA (cfDNA) obtained from plasma and has potential for early diagnosis, treatment, resistance, minimal residual disease detection, and tumoral heterogeneity identification. However, the low frequency of ctDNA requires techniques for accurate analysis. Multitarget assay such as Next Generation Sequencing (NGS) need improvement to achieve limits of detection that can identify the low frequency variants present in the cfDNA. In this review, we provide a general overview of the use of cfDNA and ctDNA in cancer, and discuss techniques developed to optimize NGS as a tool for ctDNA detection. We also summarize the results obtained using NGS strategies in both investigational and clinical contexts.

Single-molecule genome-wide mutation profiles of cell-free DNA for non-invasive detection of cancer

Somatic mutations are a hallmark of tumorigenesis and may be useful for non-invasive diagnosis of cancer. We analyzed whole-genome sequencing data from 2,511 individuals in the Pan-Cancer Analysis of Whole Genomes (PCAWG) study as well as 489 individuals from four prospective cohorts and found distinct regional mutation type-specific frequencies in tissue and cell-free DNA from patients with cancer that were associated with replication timing and other chromatin features. A machine-learning model using genome-wide mutational profiles combined with other features and followed by CT imaging detected >90% of patients with lung cancer, including those with stage I and II disease. The fixed model was validated in an independent cohort, detected patients with cancer earlier than standard approaches and could be used to monitor response to therapy. This approach lays the groundwork for non-invasive cancer detection using genome-wide mutation features that may facilitate cancer screening and monitoring.

Personalised circulating tumour DNA assay with large-scale mutation coverage for sensitive minimal residual disease detection in colorectal cancer

BACKGROUND

Postoperative minimal residual disease (MRD) detection using circulating-tumour DNA (ctDNA) requires a highly sensitive analysis platform. We have developed a tumour-informed, hybrid-capture ctDNA sequencing MRD assay.

METHODS

Personalised target-capture panels for ctDNA detection were designed using individual variants identified in tumour whole-exome sequencing of each patient. MRD status was determined using ultra-high-depth sequencing data of plasma cell-free DNA. The MRD positivity and its association with clinical outcome were analysed in Stage II or III colorectal cancer (CRC).

RESULTS

In 98 CRC patients, personalised panels for ctDNA sequencing were built from tumour data, including a median of 185 variants per patient. In silico simulation showed that increasing the number of target variants increases MRD detection sensitivity in low fractions (<0.01%). At postoperative 3-week, 21.4% of patients were positive for MRD by ctDNA. Postoperative positive MRD was strongly associated with poor disease-free survival (DFS) (adjusted hazard ratio 8.40, 95% confidence interval 3.49-20.2). Patients with a negative conversion of MRD after adjuvant therapy showed significantly better DFS (P < 0.001).

CONCLUSION

Tumour-informed, hybrid-capture-based ctDNA assay monitoring a large number of patient-specific mutations is a sensitive strategy for MRD detection to predict recurrence in CRC.

Minimal residual disease in solid tumors: an overview

Minimal residual disease (MRD) is termed as the small numbers of remnant tumor cells in a subset of patients with tumors. Liquid biopsy is increasingly used for the detection of MRD, illustrating the potential of MRD detection to provide more accurate management for cancer patients. As new techniques and algorithms have enhanced the performance of MRD detection, the approach is becoming more widely and routinely used to predict the prognosis and monitor the relapse of cancer patients. In fact, MRD detection has been shown to achieve better performance than imaging methods. On this basis, rigorous investigation of MRD detection as an integral method for guiding clinical treatment has made important advances. This review summarizes the development of MRD biomarkers, techniques, and strategies for the detection of cancer, and emphasizes the application of MRD detection in solid tumors, particularly for the guidance of clinical treatment.

Cancer Associated Macrophage-like Cells Are Prognostic for Highly Aggressive Prostate Cancer in Both the Non-Metastatic and Metastatic Settings

Despite advancements in the early-stage detection and expansion of treatments for prostate cancer (PCa), patient mortality rates remain high in patients with aggressive disease and the overtreatment of indolent disease remains a major issue. Prostate-specific antigen (PSA), a standard PCa blood biomarker, is limited in its ability to differentiate disease subtypes resulting in the overtreatment of non-aggressive indolent disease. Here we assess engorged cancer-associated macrophage-like cells (CAMLs), a ≥50 µm, cancer-specific, polynucleated circulating cell type found in the blood of patients with PCa as a potential companion biomarker to PSA for patient risk stratification. We found that rising PSA is positively correlated with increasing CAML size (r = 0.307, p = 0.004) and number of CAMLs in circulation (r = 0.399, p < 0.001). Over a 2-year period, the presence of a single engorged CAML was associated with 20.9 times increased likelihood of progression (p = 0.016) in non-metastatic PCa, and 2.4 times likelihood of progression (p = 0.031) with 5.4 times likelihood of death (p < 0.001) in metastatic PCa. These preliminary data suggest that CAML cell monitoring, in combination with PSA, may aid in differentiating non-aggressive from aggressive PCas by adding biological information that complements traditional clinical biomarkers, thereby helping guide treatment strategies.

Individualized dynamic methylation-based analysis of cell-free DNA in postoperative monitoring of lung cancer

BACKGROUND

The feasibility of DNA methylation-based assays in detecting minimal residual disease (MRD) and postoperative monitoring remains unestablished. We aim to investigate the dynamic characteristics of cancer-related methylation signals and the feasibility of methylation-based MRD detection in surgical lung cancer patients.

METHODS

Matched tumor, tumor-adjacent tissues, and longitudinal blood samples from a cohort (MEDAL) were analyzed by ultra-deep targeted sequencing and bisulfite sequencing. A tumor-informed methylation-based MRD (timMRD) was employed to evaluate the methylation status of each blood sample. Survival analysis was performed in the MEDAL cohort (n = 195) and validated in an independent cohort (DYNAMIC, n = 36).

RESULTS

Tumor-informed methylation status enabled an accurate recurrence risk assessment better than the tumor-naïve methylation approach. Baseline timMRD-scores were positively correlated with tumor burden, invasiveness, and the existence and abundance of somatic mutations. Patients with higher timMRD-scores at postoperative time-points demonstrated significantly shorter disease-free survival in the MEDAL cohort (HR: 3.08, 95% CI: 1.48-6.42; P = 0.002) and the independent DYNAMIC cohort (HR: 2.80, 95% CI: 0.96-8.20; P = 0.041). Multivariable regression analysis identified postoperative timMRD-score as an independent prognostic factor for lung cancer. Compared to tumor-informed somatic mutation status, timMRD-scores yielded better performance in identifying the relapsed patients during postoperative follow-up, including subgroups with lower tumor burden like stage I, and was more accurate among relapsed patients with baseline ctDNA-negative status. Comparing to the average lead time of ctDNA mutation, timMRD-score yielded a negative predictive value of 97.2% at 120 days prior to relapse.

CONCLUSIONS

The dynamic methylation-based analysis of peripheral blood provides a promising strategy for postoperative cancer surveillance.

TRIAL REGISTRATION

This study (MEDAL, MEthylation based Dynamic Analysis for Lung cancer) was registered on ClinicalTrials.gov on 08/05/2018 (NCT03634826). https://clinicaltrials.gov/ct2/show/NCT03634826 .

Emerging Roles of Circulating Tumor DNA for Increased Precision and Personalization in Radiation Oncology

Recent breakthroughs in circulating tumor DNA (ctDNA) technologies present a compelling opportunity to combine this emerging liquid biopsy approach with the field of radiogenomics, the study of how tumor genomics correlate with radiotherapy response and radiotoxicity. Canonically, ctDNA levels reflect metastatic tumor burden, although newer ultrasensitive technologies can be used after curative-intent radiotherapy of localized disease to assess ctDNA for minimal residual disease (MRD) detection or for post-treatment surveillance. Furthermore, several studies have demonstrated the potential utility of ctDNA analysis across various cancer types managed with radiotherapy or chemoradiotherapy, including sarcoma and cancers of the head and neck, lung, colon, rectum, bladder, and prostate . Additionally, because peripheral blood mononuclear cells are routinely collected alongside ctDNA to filter out mutations associated with clonal hematopoiesis, these cells are also available for single nucleotide polymorphism analysis and could potentially be used to detect patients at high risk for radiotoxicity. Lastly, future ctDNA assays will be utilized to better assess locoregional MRD in order to more precisely guide adjuvant radiotherapy after surgery in cases of localized disease, and guide ablative radiotherapy in cases of oligometastatic disease.

Circulating tumor DNA minimal residual disease in clinical practice of non-small cell lung cancer

INTRODUCTION

The advance of diagnostics and treatments has greatly improved the prognosis of non-small cell lung cancer (NSCLC) patients. However, relapse and metastasis are still common problems encountered by NSCLC patients who have achieved complete remission. Therefore, overcoming the challenge of relapse and metastasis is particularly important for improving the prognosis of NSCLC patients. Research has shown that minimal residual disease (MRD) was a potential source of tumor relapse and metastasis, and circulating tumor DNA (ctDNA) MRD has obvious advantages in predicting the relapse and metastasis of NSCLC and evaluating treatment effectiveness. Therefore, dynamic monitoring of MRD is of great significance for NSCLC patient management strategies.

AREAS COVERED

We have reviewed articles related to NSCLC MRD included in PubMed and describes the biological significance and historical context of MRD research, reasons for using ctDNA to evaluate MRD, and potential value and challenges of ctDNA MRD in assessing relapse and metastasis of NSCLC, ultimately guiding clinical therapeutic strategies and management.

EXPERT OPINION

The standardized scope of ctDNA MRD detection for NSCLC requires more clinical research evidence to minimize study differences, making it possible to include in the clinical staging as a reliable indicator.

Sustained complete response to first-line immunochemotherapy for highly aggressive TP53/MDM2-mutated upper tract urothelial carcinoma with ERBB2 mutations, luminal immune-infiltrated contexture, and non-mesenchymal state: a case report and literature review

Background

Upper tract urothelial carcinoma (UTUC) is a rare malignancy. The management of metastatic or unresectable UTUC is mainly based on evidence extrapolated from histologically homologous bladder cancer, including platinum-based chemotherapy and immune checkpoint inhibitor alone, whereas UTUC exhibits more invasiveness, worse prognosis, and comparatively inferior response to treatments. First-line immunochemotherapy regimens have been attempted in clinical trials for unselected naïve-treated cases, but their efficacies relative to standard chemo- or immuno-monotherapy still remain controversial. Here, we present a case of highly aggressive UTUC for whom comprehensive genetic and phenotypic signatures predicted sustained complete response to first-line immunochemotherapy.

Case presentation

A 50-year-old man received retroperitoneoscopic nephroureterectomy and regional lymphadenectomy for high-risk locally advanced UTUC. Postoperatively, he developed rapid progression of residual unresectable metastatic lymph nodes. Pathologic analysis and next-generation sequencing classified the tumor as highly aggressive TP53/MDM2-mutated subtype with features more than expression of programmed death ligand-1, including ERBB2 mutations, luminal immune-infiltrated contexture, and non-mesenchymal state. Immunochemotherapy combining gemcitabine, carboplatin, and off-label programmed death-1 inhibitor sintilimab was initiated, and sintilimab monotherapy was maintained up to 1 year. Retroperitoneal lymphatic metastases gradually regressed to complete response. Blood-based analyses were performed longitudinally for serum tumor markers, inflammatory parameters, peripheral immune cells, and circulating tumor DNA (ctDNA) profiling. The ctDNA kinetics of tumor mutation burden and mean variant allele frequency accurately predicted postoperative progression and sustained response to the following immunochemotherapy, which were mirrored by dynamic changes in abundances of ctDNA mutations from UTUC-typical variant genes. The patient remained free of recurrence or metastasis as of this publishing, over 2 years after the initial surgical treatment.

Conclusion

Immunochemotherapy may be a promising first-line option for advanced or metastatic UTUC selected with specific genomic or phenotypic signatures, and blood-based analyses incorporating ctDNA profiling provide precise longitudinal monitoring.

Current and emerging applications of liquid biopsy in pan-cancer

Cancer morbidity and mortality are growing rapidly worldwide and it is urgent to develop a convenient and effective method that can identify cancer patients at an early stage and predict treatment outcomes. As a minimally invasive and reproducible tool, liquid biopsy (LB) offers the opportunity to detect, analyze and monitor cancer in any body fluids including blood, complementing the limitations of tissue biopsy. In liquid biopsy, circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA) are the two most common biomarkers, displaying great potential in the clinical application of pan-cancer. In this review, we expound the samples, targets, and newest techniques in liquid biopsy and summarize current clinical applications in several specific cancers. Besides, we put forward a bright prospect for further exploring the emerging application of liquid biopsy in the field of pan-cancer precision medicine.

Comparison of tumor-informed and tumor-naïve sequencing assays for ctDNA detection in breast cancer

Analysis of circulating tumor DNA (ctDNA) to monitor cancer dynamics and detect minimal residual disease has been an area of increasing interest. Multiple methods have been proposed but few studies have compared the performance of different approaches. Here, we compare detection of ctDNA in serial plasma samples from patients with breast cancer using different tumor-informed and tumor-naïve assays designed to detect structural variants (SVs), single nucleotide variants (SNVs), and/or somatic copy-number aberrations, by multiplex PCR, hybrid capture, and different depths of whole-genome sequencing. Our results demonstrate that the ctDNA dynamics and allele fractions (AFs) were highly concordant when analyzing the same patient samples using different assays. Tumor-informed assays showed the highest sensitivity for detection of ctDNA at low concentrations. Hybrid capture sequencing targeting between 1,347 and 7,491 tumor-identified mutations at high depth was the most sensitive assay, detecting ctDNA down to an AF of 0.00024% (2.4 parts per million, ppm). Multiplex PCR targeting 21-47 tumor-identified SVs per patient detected ctDNA down to 0.00047% AF (4.7 ppm) and has potential as a clinical assay.

Genomic approaches to cancer and minimal residual disease detection using circulating tumor DNA

Liquid biopsies using cell-free circulating tumor DNA (ctDNA) are being used frequently in both research and clinical settings. ctDNA can be used to identify actionable mutations to personalize systemic therapy, detect post-treatment minimal residual disease (MRD), and predict responses to immunotherapy. ctDNA can also be isolated from a range of different biofluids, with the possibility of detecting locoregional MRD with increased sensitivity if sampling more proximally than blood plasma. However, ctDNA detection remains challenging in early-stage and post-treatment MRD settings where ctDNA levels are minuscule giving a high risk for false negative results, which is balanced with the risk of false positive results from clonal hematopoiesis. To address these challenges, researchers have developed ever-more elegant approaches to lower the limit of detection (LOD) of ctDNA assays toward the part-per-million range and boost assay sensitivity and specificity by reducing sources of low-level technical and biological noise, and by harnessing specific genomic and epigenomic features of ctDNA. In this review, we highlight a range of modern assays for ctDNA analysis, including advancements made to improve the signal-to-noise ratio. We further highlight the challenge of detecting ultra-rare tumor-associated variants, overcoming which will improve the sensitivity of post-treatment MRD detection and open a new frontier of personalized adjuvant treatment decision-making.

Accuracy of minimal residual disease detection by circulating tumor DNA profiling in lung cancer: a meta-analysis

BACKGROUND

The sensitivity and specificity of minimal residual disease detected by circulating tumor DNA profiling (ctDNA MRD) in lung cancer, with particular attention to the distinction between landmark strategy and surveillance strategy, for predicting relapse in lung cancer patients after definitive therapy has yet to be determined.

METHODS

The prognostic value of ctDNA MRD by landmark strategy and surveillance strategy was evaluated in a large cohort of patients with lung cancer who received definitive therapy using a systemic literature review and meta-analysis. Recurrence status stratified by ctDNA MRD result (positive or negative) was extracted as the clinical endpoint. We calculated the area under the summary receiver operating characteristic curves, and pooled sensitivities and specificities. Subgroup analyses were conducted based on histological type and stage of lung cancer, types of definitive therapy, and ctDNA MRD detection methods (detection technology and strategy such as tumor-informed or tumor-agnostic).

RESULTS

This systematic review and meta-analysis of 16 unique studies includes 1251 patients with lung cancer treated with definitive therapy. The specificity of ctDNA MRD in predicting recurrence is high (0.86-0.95) with moderate sensitivity (0.41-0.76), whether shortly after treatment or during the surveillance. The landmark strategy appears to be more specific but less sensitive than the surveillance strategy.

CONCLUSIONS

Our study suggests that ctDNA MRD is a relatively promising biomarker for relapse prediction among lung cancer patients after definitive therapy, with a high specificity but suboptimal sensitivity, whether in landmark strategy or surveillance strategy. Although surveillance ctDNA MRD analysis decreases specificity compared with the landmark strategy, the decrease is minimal compared to the increase in sensitivity for relapse prediction of lung cancer.

Enhanced Detection of Landmark Minimal Residual Disease in Lung Cancer Using Cell-free DNA Fragmentomics

Currently, approximately 30%-55% of the patients with non-small cell lung cancer (NSCLC) develop recurrence due to minimal residual disease (MRD) after receiving surgical resection of the tumor. This study aims to develop an ultrasensitive and affordable fragmentomic assay for MRD detection in patients with NSCLC. A total of 87 patients with NSCLC, who received curative surgical resections (23 patients relapsed during follow-up), enrolled in this study. A total of 163 plasma samples, collected at 7 days and 6 months postsurgical, were used for both whole-genome sequencing (WGS) and targeted sequencing. WGS-based cell-free DNA (cfDNA) fragment profile was used to fit regularized Cox regression models, and leave-one-out cross-validation was further used to evaluate models' performance. The models showed excellent performances in detecting patients with a high risk of recurrence. At 7 days postsurgical, the high-risk patients detected by our model showed an increased risk of 4.6 times, while the risk increased to 8.3 times at 6 months postsurgical. These fragmentomics determined higher risk compared with the targeted sequencing-based circulating mutations both at 7 days and 6 months postsurgical. The overall sensitivity for detecting patients with recurrence reached 78.3% while using both fragmentomics and mutation results from 7 days and 6 months postsurgical, which increased from the 43.5% sensitivity by using only the circulating mutations. The fragmentomics showed great sensitivity in predicting patient recurrence compared with the traditional circulating mutation, especially after the surgery for early-stage NSCLC, therefore exhibiting great potential to guide adjuvant therapeutics.

Significance

The circulating tumor DNA mutation-based approach shows limited performance in MRD detection, especially for landmark MRD detection at an early-stage cancer after surgery. Here, we describe a cfDNA fragmentomics-based method in MRD detection of resectable NSCLC using WGS, and the cfDNA fragmentomics showed a great sensitivity in predicting prognosis.

cfSNV: a software tool for the sensitive detection of somatic mutations from cell-free DNA

Cell-free DNA (cfDNA) in blood, viewed as a surrogate for tumor biopsy, has many clinical applications, including diagnosing cancer, guiding cancer treatment and monitoring treatment response. All these applications depend on an indispensable, yet underdeveloped task: detecting somatic mutations from cfDNA. The task is challenging because of the low tumor fraction in cfDNA. Recently, we developed the computational method cfSNV, the first method that comprehensively considers the properties of cfDNA for the sensitive detection of mutations from cfDNA. cfSNV vastly outperformed the conventional methods that were developed primarily for calling mutations from solid tumor tissues. cfSNV can accurately detect mutations in cfDNA even with medium-coverage (e.g., ≥200×) sequencing, which makes whole-exome sequencing (WES) of cfDNA a viable option for various clinical utilities. Here, we present a user-friendly cfSNV package that exhibits fast computation and convenient user options. We also built a Docker image of it, which is designed to enable researchers and clinicians with a limited computational background to easily carry out analyses on both high-performance computing platforms and local computers. Mutation calling from a standard preprocessed WES dataset (~250× and ~70 million base pair target size) can be carried out in 3 h on a server with eight virtual CPUs and 32 GB of random access memory.

Multi-omics integrated circulating cell-free DNA genomic signatures enhanced the diagnostic performance of early-stage lung cancer and postoperative minimal residual disease

BACKGROUND

Liquid biopsy is a promising non-invasive alternative for cancer screening and minimal residual disease (MRD) detection, although there are some concerns regarding its clinical applications. We aimed to develop an accurate detection platform based on liquid biopsy for both cancer screening and MRD detection in patients with lung cancer (LC), which is also applicable to clinical use.

METHODS

We applied a modified whole-genome sequencing (WGS) -based High-performance Infrastructure For MultIomics (HIFI) method for LC screening and postoperative MRD detection by combining the hyper-co-methylated read approach and the circulating single-molecule amplification and resequencing technology (cSMART2.0).

FINDINGS

For early screening of LC, the LC score model was constructed using the support vector machine, which showed sensitivity (51.8%) at high specificity (96.3%) and achieved an AUC of 0.912 in the validation set prospectively enrolled from multiple centers. The screening model achieved detection efficiency with an AUC of 0.906 in patients with lung adenocarcinoma and outperformed other clinical models in solid nodule cohort. When applied the HIFI model to real social population, a negative predictive value (NPV) of 99.92% was achieved in Chinese population. Additionally, the MRD detection rate improved significantly by combining results from WGS and cSMART2.0, with sensitivity of 73.7% at specificity of 97.3%.

INTERPRETATION

In conclusion, the HIFI method is promising for diagnosis and postoperative monitoring of LC.

FUNDING

This study was supported by CAMS Innovation Fund for Medical Sciences, Chinese Academy of Medical Sciences, National Natural Science Foundation of China, Beijing Natural Science Foundation and Peking University People's Hospital.

DREAMS: deep read-level error model for sequencing data applied to low-frequency variant calling and circulating tumor DNA detection

Circulating tumor DNA detection using next-generation sequencing (NGS) data of plasma DNA is promising for cancer identification and characterization. However, the tumor signal in the blood is often low and difficult to distinguish from errors. We present DREAMS (Deep Read-level Modelling of Sequencing-errors) for estimating error rates of individual read positions. Using DREAMS, we develop statistical methods for variant calling (DREAMS-vc) and cancer detection (DREAMS-cc). For evaluation, we generate deep targeted NGS data of matching tumor and plasma DNA from 85 colorectal cancer patients. The DREAMS approach performs better than state-of-the-art methods for variant calling and cancer detection.

ACT-Discover: identifying karyotype heterogeneity in pancreatic cancer evolution using ctDNA

BACKGROUND

Liquid biopsies and the dynamic tracking of somatic mutations within circulating tumour DNA (ctDNA) can provide insight into the dynamics of cancer evolution and the intra-tumour heterogeneity that fuels treatment resistance. However, identifying and tracking dynamic changes in somatic copy number alterations (SCNAs), which have been associated with poor outcome and metastasis, using ctDNA is challenging. Pancreatic adenocarcinoma is a disease which has been considered to harbour early punctuated events in its evolution, leading to an early fitness peak, with minimal further subclonal evolution.

METHODS

To interrogate the role of SCNAs in pancreatic adenocarcinoma cancer evolution, we applied whole-exome sequencing of 55 longitudinal cell-free DNA (cfDNA) samples taken from 24 patients (including 8 from whom a patient-derived xenograft (PDX) was derived) with metastatic disease prospectively recruited into a clinical trial. We developed a method, Aneuploidy in Circulating Tumour DNA (ACT-Discover), that leverages haplotype phasing of paired tumour biopsies or PDXs to identify SCNAs in cfDNA with greater sensitivity.

RESULTS

SCNAs were observed within 28 of 47 evaluable cfDNA samples. Of these events, 30% could only be identified by harnessing the haplotype-aware approach leveraged in ACT-Discover. The exceptional purity of PDX tumours enabled near-complete phasing of genomic regions in allelic imbalance, highlighting an important auxiliary function of PDXs. Finally, although the classical model of pancreatic cancer evolution emphasises the importance of early, homogenous somatic events as a key requirement for cancer development, ACT-Discover identified substantial heterogeneity of SCNAs, including parallel focal and arm-level events, affecting different parental alleles within individual tumours. Indeed, ongoing acquisition of SCNAs was identified within tumours throughout the disease course, including within an untreated metastatic tumour.

CONCLUSIONS

This work demonstrates the power of haplotype phasing to study genomic variation in cfDNA samples and reveals undiscovered intra-tumour heterogeneity with important scientific and clinical implications. Implementation of ACT-Discover could lead to important insights from existing cohorts or underpin future prospective studies seeking to characterise the landscape of tumour evolution through liquid biopsy.

Pillar[5]arene-based supramolecular pseudorotaxane polymer material for ultra-sensitive detection of Fe3+ and F. RSC Adv 2023;13:12270-12275. [PMID: 37091614 PMCID: PMC10113919 DOI: 10.1039/d3ra00997a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Recent advancements in ultra-sensitive detection, particularly the Aggregation Induced Emission (AIE) materials, have demonstrated a promising detection method due to their low cost, real-time detection, and simplicity of operation. Here, coumarin functionalized pillar[5]arene (P5C) and bis-bromohexyl pillar[5]arene (DP5) were successfully combined to create a linear AIE supramolecular pseudorotaxane polymer (PCDP-G). The use of PCDP-G as a supramolecular AIE polymer material for recyclable ultra-sensitive Fe³⁺ and F^- detection is an interesting application of the materials. According to measurements, the low detection limits of PCDP-G for Fe³⁺ and F^- are 4.16 × 10^-10 M and 6.8 × 10^-10 M, respectively. The PCDP-G is also a very effective logic gate and a material for luminous displays.

From patterns to patients: Advances in clinical machine learning for cancer diagnosis, prognosis, and treatment

Machine learning (ML) is increasingly used in clinical oncology to diagnose cancers, predict patient outcomes, and inform treatment planning. Here, we review recent applications of ML across the clinical oncology workflow. We review how these techniques are applied to medical imaging and to molecular data obtained from liquid and solid tumor biopsies for cancer diagnosis, prognosis, and treatment design. We discuss key considerations in developing ML for the distinct challenges posed by imaging and molecular data. Finally, we examine ML models approved for cancer-related patient usage by regulatory agencies and discuss approaches to improve the clinical usefulness of ML.

Integrative modeling of tumor genomes and epigenomes for enhanced cancer diagnosis by cell-free DNA

Multi-cancer early detection remains a key challenge in cell-free DNA (cfDNA)-based liquid biopsy. Here, we perform cfDNA whole-genome sequencing to generate two test datasets covering 2125 patient samples of 9 cancer types and 1241 normal control samples, and also a reference dataset for background variant filtering based on 20,529 low-depth healthy samples. An external cfDNA dataset consisting of 208 cancer and 214 normal control samples is used for additional evaluation. Accuracy for cancer detection and tissue-of-origin localization is achieved using our algorithm, which incorporates cancer type-specific profiles of mutation distribution and chromatin organization in tumor tissues as model references. Our integrative model detects early-stage cancers, including those of pancreatic origin, with high sensitivity that is comparable to that of late-stage detection. Model interpretation reveals the contribution of cancer type-specific genomic and epigenomic features. Our methodologies may lay the groundwork for accurate cfDNA-based cancer diagnosis, especially at early stages.

Enhancing clinical potential of liquid biopsy through a multi-omic approach: A systematic review

In the last years, liquid biopsy gained increasing clinical relevance for detecting and monitoring several cancer types, being minimally invasive, highly informative and replicable over time. This revolutionary approach can be complementary and may, in the future, replace tissue biopsy, which is still considered the gold standard for cancer diagnosis. "Classical" tissue biopsy is invasive, often cannot provide sufficient bioptic material for advanced screening, and can provide isolated information about disease evolution and heterogeneity. Recent literature highlighted how liquid biopsy is informative of proteomic, genomic, epigenetic, and metabolic alterations. These biomarkers can be detected and investigated using single-omic and, recently, in combination through multi-omic approaches. This review will provide an overview of the most suitable techniques to thoroughly characterize tumor biomarkers and their potential clinical applications, highlighting the importance of an integrated multi-omic, multi-analyte approach. Personalized medical investigations will soon allow patients to receive predictable prognostic evaluations, early disease diagnosis, and subsequent ad hoc treatments.

Bridging biological cfDNA features and machine learning approaches

Liquid biopsies (LBs), particularly using circulating tumor DNA (ctDNA), are expected to revolutionize precision oncology and blood-based cancer screening. Recent technological improvements, in combination with the ever-growing understanding of cell-free DNA (cfDNA) biology, are enabling the detection of tumor-specific changes with extremely high resolution and new analysis concepts beyond genetic alterations, including methylomics, fragmentomics, and nucleosomics. The interrogation of a large number of markers and the high complexity of data render traditional correlation methods insufficient. In this regard, machine learning (ML) algorithms are increasingly being used to decipher disease- and tissue-specific signals from cfDNA. Here, we review recent insights into biological ctDNA features and how these are incorporated into sophisticated ML applications.

Longitudinal ctDNA profiling in precision oncology and immunο-oncology

Serial analysis of circulating tumor DNA (ctDNA) over the disease course is emerging as a prognostic, predictive and patient-monitoring biomarker. In the metastatic setting, several multigene ctDNA assays have been approved or recommended by regulatory organizations for personalized targeted therapy, especially for lung cancer. By contrast, in nonmetastatic disease, detection of ctDNA resulting from minimal residual disease (MRD) following multimodal treatment with curative intent presents major technical challenges. Several studies using tumor genotyping-informed serial ctDNA profiling have provided promising findings on the sensitivity and specificity of ctDNA in predicting the risk of recurrence. We discuss progress, limitations and future perspectives relating to the use of ctDNA as a biomarker to guide targeted therapy in metastatic disease, as well as the use of ctDNA MRD detection to guide adjuvant treatment in the nonmetastatic setting.

Lynch syndrome cancer vaccines: A roadmap for the development of precision immunoprevention strategies

Hereditary cancer syndromes (HCS) account for 5~10% of all cancer diagnosis. Lynch syndrome (LS) is one of the most common HCS, caused by germline mutations in the DNA mismatch repair (MMR) genes. Even with prospective cancer surveillance, LS is associated with up to 50% lifetime risk of colorectal, endometrial, and other cancers. While significant progress has been made in the timely identification of germline pathogenic variant carriers and monitoring and early detection of precancerous lesions, cancer-risk reduction strategies are still centered around endoscopic or surgical removal of neoplastic lesions and susceptible organs. Safe and effective cancer prevention strategies are critically needed to improve the life quality and longevity of LS and other HCS carriers. The era of precision oncology driven by recent technological advances in tumor molecular profiling and a better understanding of genetic risk factors has transformed cancer prevention approaches for at-risk individuals, including LS carriers. MMR deficiency leads to the accumulation of insertion and deletion mutations in microsatellites (MS), which are particularly prone to DNA polymerase slippage during DNA replication. Mutations in coding MS give rise to frameshift peptides (FSP) that are recognized by the immune system as neoantigens. Due to clonal evolution, LS tumors share a set of recurrent and predictable FSP neoantigens in the same and in different LS patients. Cancer vaccines composed of commonly recurring FSP neoantigens selected through prediction algorithms have been clinically evaluated in LS carriers and proven safe and immunogenic. Preclinically analogous FSP vaccines have been shown to elicit FSP-directed immune responses and exert tumor-preventive efficacy in murine models of LS. While the immunopreventive efficacy of "off-the-shelf" vaccines consisting of commonly recurring FSP antigens is currently investigated in LS clinical trials, the feasibility and utility of personalized FSP vaccines with individual HLA-restricted epitopes are being explored for more precise targeting. Here, we discuss recent advances in precision cancer immunoprevention approaches, emerging enabling technologies, research gaps, and implementation barriers toward clinical translation of risk-tailored prevention strategies for LS carriers. We will also discuss the feasibility and practicality of next-generation cancer vaccines that are based on personalized immunogenic epitopes for precision cancer immunoprevention.

Liquid biopsy at the frontier in renal cell carcinoma: recent analysis of techniques and clinical application

Renal cell carcinoma (RCC) is a major pathological type of kidney cancer and is one of the most common malignancies worldwide. The unremarkable symptoms of early stages, proneness to postoperative metastasis or recurrence, and low sensitivity to radiotherapy and chemotherapy pose a challenge for the diagnosis and treatment of RCC. Liquid biopsy is an emerging test that measures patient biomarkers, including circulating tumor cells, cell-free DNA/cell-free tumor DNA, cell-free RNA, exosomes, and tumor-derived metabolites and proteins. Owing to its non-invasiveness, liquid biopsy enables continuous and real-time collection of patient information for diagnosis, prognostic assessment, treatment monitoring, and response evaluation. Therefore, the selection of appropriate biomarkers for liquid biopsy is crucial for identifying high-risk patients, developing personalized therapeutic plans, and practicing precision medicine. In recent years, owing to the rapid development and iteration of extraction and analysis technologies, liquid biopsy has emerged as a low cost, high efficiency, and high accuracy clinical detection method. Here, we comprehensively review liquid biopsy components and their clinical applications over the past 5 years. Additionally, we discuss its limitations and predict its future prospects.

Integrated, Longitudinal Analysis of Cell-free DNA in Uveal Melanoma

Uveal melanomas are rare tumors arising from melanocytes that reside in the eye. Despite surgical or radiation treatment, approximately 50% of patients with uveal melanoma will progress to metastatic disease, most often to the liver. Cell-free DNA (cfDNA) sequencing is a promising technology due to the minimally invasive sample collection and ability to infer multiple aspects of tumor response. We analyzed 46 serial cfDNA samples from 11 patients with uveal melanoma over a 1-year period following enucleation or brachytherapy (n = ∼4/patient) using targeted panel, shallow whole genome, and cell-free methylated DNA immunoprecipitation sequencing. We found detection of relapse was highly variable using independent analyses (P = 0.06-0.46), whereas a logistic regression model integrating all cfDNA profiles significantly improved relapse detection (P = 0.02), with greatest power derived from fragmentomic profiles. This work provides support for the use of integrated analyses to improve the sensitivity of circulating tumor DNA detection using multi-modal cfDNA sequencing.

Significance

Here, we demonstrate integrated, longitudinal cfDNA sequencing using multi-omic approaches is more effective than unimodal analysis. This approach supports the use of frequent blood testing using comprehensive genomic, fragmentomic, and epigenomic techniques.

Cell-free Chromatin Immunoprecipitation to detect molecular pathways in Physiological and Disease States

Patient monitoring is a cornerstone in clinical practice to define disease phenotypes and guide clinical management. Unfortunately, this is often reliant on invasive and/or less sensitive methods that do not provide deep phenotype assessments of disease state to guide treatment. This paper examined plasma cell-free DNA chromatin immunoprecipitation sequencing (cfChIP-seq) to define molecular gene sets in physiological and heart transplant patients taking immunosuppression medications. We show cfChIP-seq reliably detect gene signals that correlate with gene expression. In healthy controls and in heart transplant patients, cfChIP-seq reliably detected housekeeping genes. cfChIP-seq identified differential gene signals of the relevant immune and non-immune molecular pathways that were predominantly downregulated in immunosuppressed heart transplant patients compared to healthy controls. cfChIP-seq also identified tissue sources of cfDNA, detecting greater cell-free DNA from cardiac, hematopoietic, and other non-hematopoietic tissues such as the pulmonary, digestive, and neurological tissues in transplant patients than healthy controls. cfChIP-seq gene signals were reproducible between patient populations and blood collection methods. cfChIP-seq may therefore be a reliable approach to provide dynamic assessments of molecular pathways and tissue injury associated to disease.

Molecular Monitoring of Lymphomas

Molecular monitoring of tumor-derived alterations has an established role in the surveillance of leukemias, and emerging nucleic acid sequencing technologies are likely to similarly transform the clinical management of lymphomas. Lymphomas are well suited for molecular surveillance due to relatively high cell-free DNA and circulating tumor DNA concentrations, high somatic mutational burden, and the existence of stereotyped variants enabling focused interrogation of recurrently altered regions. Here, we review the clinical scenarios and key technologies applicable for the molecular monitoring of lymphomas, summarizing current evidence in the literature regarding molecular subtyping and classification, evaluation of treatment response, the surveillance of active cellular therapies, and emerging clinical trial strategies.

Molecular Monitoring in Endometrial Cancer-Ready for Prime Time?

SUMMARY

Efforts are under way to define the role of minimally invasive strategies for molecular monitoring and risk stratification in endometrial cancer. A recent publication aims to define the association between circulating tumor DNA level and disease stage in patients with newly diagnosed endometrial cancer and determine whether sequencing of longitudinal cell-free DNA samples can be used for disease monitoring and detection of progression or recurrence. These results accelerate the current knowledge of molecular follow-up in endometrial cancer. See related article by Ashley et al., p. 410.

A nanoparticle priming agent reduces cellular uptake of cell-free DNA and enhances the sensitivity of liquid biopsies

Liquid biopsies are enabling minimally invasive monitoring and molecular profiling of diseases across medicine, but their sensitivity remains limited by the scarcity of cell-free DNA (cfDNA) in blood. Here, we report an intravenous priming agent that is given prior to a blood draw to increase the abundance of cfDNA in circulation. Our priming agent consists of nanoparticles that act on the cells responsible for cfDNA clearance to slow down cfDNA uptake. In tumor-bearing mice, this agent increases the recovery of circulating tumor DNA (ctDNA) by up to 60-fold and improves the sensitivity of a ctDNA diagnostic assay from 0% to 75% at low tumor burden. We envision that this priming approach will significantly improve the performance of liquid biopsies across a wide range of clinical applications in oncology and beyond.

Cell-Free DNA Fragmentomics: The Novel Promising Biomarker

Cell-free DNA molecules are released into the plasma via apoptotic or necrotic events and active release mechanisms, which carry the genetic and epigenetic information of its origin tissues. However, cfDNA is the mixture of various cell fragments, and the efficient enrichment of cfDNA fragments with diagnostic value remains a great challenge for application in the clinical setting. Evidence from recent years shows that cfDNA fragmentomics' characteristics differ in normal and diseased individuals without the need to distinguish the source of the cfDNA fragments, which makes it a promising novel biomarker. Moreover, cfDNA fragmentomics can identify tissue origins by inferring epigenetic information. Thus, further insights into the fragmentomics of plasma cfDNA shed light on the origin and fragmentation mechanisms of cfDNA during physiological and pathological processes in diseases and enhance our ability to take the advantage of plasma cfDNA as a molecular diagnostic tool. In this review, we focus on the cfDNA fragment characteristics and its potential application, such as fragment length, end motifs, jagged ends, preferred end coordinates, as well as nucleosome footprints, open chromatin region, and gene expression inferred by the cfDNA fragmentation pattern across the genome. Furthermore, we summarize the methods for deducing the tissue of origin by cfDNA fragmentomics.

Real-world analysis of the prognostic value of EGFR mutation detection in plasma ctDNA from patients with advanced non-small cell lung cancer

BACKGROUND

The plasma sample has emerged as a promising surrogate sample for EGFR mutation detection in advanced non-small cell lung cancer (NSCLC). In clinical practice, whether EGFR variants in baseline plasma ctDNA of advanced NSCLC can predict prognosis in addition to guiding targeted therapy remains to be further explored.

MATERIAL AND METHODS

In total, 315 NSCLC patients were retrospectively enrolled. EGFR mutation data from tissue detected by ARMS-PCR and paired plasma samples within 1 month of admission detected by SuperARMS or ARMS-PCR were collected. The correlation between baseline plasma ctDNA EGFR mutation status and survival was compared.

RESULTS

EGFR mutation detection rates in tumor samples and plasma samples were 65.1% (205/315) and 43.8% (138/315). Referred to tissue results, the consistent rate of test ctDNA EGFR alteration by SuperARMS was higher than that detected by ARMS (79.5% vs. 69.0%, p = 0.04), either in stage I-IIIA patients (85.7% vs. 50.0%, p = 0.4) or stage IIIB-IV patients (79.1% vs. 69.4%, p = 0.04). Patients' treatment status and pathological subtype were the two factors that affected plasma ctDNA EGFR alteration detection accuracy. The concordance in non-adenocarcinoma patients was obviously higher than that in adenocarcinoma (p = 0.02), and the concordance in treatment naïve patients was significantly higher than that in relapse patients (p = 0.047). In treatment naïve patients, the median PFS (mPFS) in plasma ctDNA EGFR-positive patients was shorter than that in plasma ctDNA EGFR negative patients (7.0 vs. 10.0 months, p = 0.01). In relapsed patients, the mPFS in plasma ctDNA EGFR-positive patients was 9.0 months versus 11.0 months in plasma ctDNA EGFR negative patients (p = 0.1).

CONCLUSIONS

A plasma sample could be an alternative for a molecular test when tissue samples was unavailable. The SuperARMS-PCR detection method has high sensitivity in real-world clinical practice. Furthermore, in patients with stage IIIB-IV, baseline plasma ctDNA EGFR mutation positivity not only guides targeted therapy but also predicts a worse prognosis.

Liquid biopsy approaches to capture tumor evolution and clinical outcomes during cancer immunotherapy

Circulating cell-free tumor DNA (ctDNA) can serve as a real-time biomarker of tumor burden and provide unique insights into the evolving molecular landscape of cancers under the selective pressure of immunotherapy. Tracking the landscape of genomic alterations detected in ctDNA may reveal the clonal architecture of the metastatic cascade and thus improve our understanding of the molecular wiring of therapeutic responses. While liquid biopsies may provide a rapid and accurate evaluation of tumor burden dynamics during immunotherapy, the complexity of antitumor immune responses is not fully captured through single-feature ctDNA analyses. This underscores a need for integrative studies modeling the tumor and the immune compartment to understand the kinetics of tumor clearance in association with the quality of antitumor immune responses. Clinical applications of ctDNA testing in patients treated with immune checkpoint inhibitors have shown both predictive and prognostic value through the detection of genomic biomarkers, such as tumor mutational burden and microsatellite instability, as well as allowing for real-time monitoring of circulating tumor burden and the assessment of early on-therapy responses. These efforts highlight the emerging role of liquid biopsies in selecting patients for cancer immunotherapy, monitoring therapeutic efficacy, determining the optimal duration of treatment and ultimately guiding treatment selection and sequencing. The clinical translation of liquid biopsies is propelled by the increasing number of ctDNA-directed interventional clinical trials in the immuno-oncology space, signifying a critical step towards implementation of liquid biopsies in precision immuno-oncology.

Minimal Residual Disease Monitoring in Radically Treated Non-Small Cell Lung Cancer: Challenges and Future Directions

Circulating tumor DNA (ctDNA) analysis can identify patients with residual disease before it is clinically or radiologically evident. Minimal residual disease (MRD) is an advancing area in the management of radically treated solid tumors. Which MRD assay is optimum and when it should be used is still not defined. Whilst promising, the clinical utility of this technology to guide patient care is still investigational in non-small cell lung cancer (NSCLC) and has not entered routine care. Once technically and clinically optimized, MRD may be utilized to personalize adjuvant therapy, detect disease relapse earlier and improve cure rates. In this review, we discuss the current status of MRD monitoring in NSCLC by summarizing frequently used MRD assays and their associated evidence in NSCLC. We discuss the potential applications of these technologies and the challenge of demonstrating MRD clinical utility in trials.