High efficiency error suppression for accurate detection of low-frequency variants

Systematic Review of Cerebrospinal Fluid Biomarker Discovery in Neuro-Oncology: A Roadmap to Standardization and Clinical Application

Effective diagnosis, prognostication, and management of CNS malignancies traditionally involves invasive brain biopsies that pose significant risk to the patient. Sampling and molecular profiling of cerebrospinal fluid (CSF) is a safer, rapid, and noninvasive alternative that offers a snapshot of the intracranial milieu while overcoming the challenge of sampling error that plagues conventional brain biopsy. Although numerous biomarkers have been identified, translational challenges remain, and standardization of protocols is necessary. Here, we systematically reviewed 141 studies (Medline, SCOPUS, and Biosis databases; between January 2000 and September 29, 2022) that molecularly profiled CSF from adults with brain malignancies including glioma, brain metastasis, and primary and secondary CNS lymphomas. We provide an overview of promising CSF biomarkers, propose CSF reporting guidelines, and discuss the various considerations that go into biomarker discovery, including the influence of blood-brain barrier disruption, cell of origin, and site of CSF acquisition (eg, lumbar and ventricular). We also performed a meta-analysis of proteomic data sets, identifying biomarkers in CNS malignancies and establishing a resource for the research community.

Transcriptomic and epigenomic insights into pectoral muscle fiber formation at the late embryonic development in pure chicken lines

Long-term intensive genetic selection has led to significant differences between broiler and layer chickens, which are evident during the embryonic period. Despite this, there is a paucity of research on the genetic regulation of the initial formation of muscle fiber morphology in chick embryos. Embryonic d 17 (E17) is the key time point for myoblast fusion completion and muscle fiber morphology formation in chickens. This study aimed to explore the genetic regulatory mechanisms underlying the early muscle fiber morphology establishment in broiler chickens of Cornish (CC) and White Plymouth Rock (RR) and layer chickens of White Leghorn (WW) at E17 using the transcriptomic and chromatin accessibility sequencing of pectoral major muscles. The results showed that broiler chickens exhibited significant higher embryo weight and pectoral major muscle weight at E17 compared to layer chickens (P = 0.000). A total of 1,278, 1,248, and 892 differentially expressed genes (DEGs) of RNA-seq data were identified between CC vs. WW, RR vs. WW, and CC vs. RR, separately. All DEGs were combined for cluster analysis and they were divided into 6 clusters, including cluster 1 with higher expression in broilers and cluster 6 with higher expression in layers. DEGs in cluster 1 were enriched in terms related to macrophage activation (P = 0.002) and defense response to bacteria (P = 0.002), while DEGs in cluster 6 showed enrichment in protein-DNA complex (P = 0.003) and monooxygenase activity (P = 0.000). ATAC-seq data analysis identified a total of 38,603 peaks, with 13,051 peaks for CC, 18,780 peaks for RR, and 6,772 peaks for WW. Integrative analysis of transcriptomic and chromatin accessibility data revealed GOLM1, ISLR2, and TOPAZ1 were commonly upregulated genes in CC and RR. Furthermore, screening of all upregulated DEGs in cluster 1 from CC and RR identified GOLM1, ISLR2, and HNMT genes associated with neuroimmune functions and MYOM3 linked to muscle morphology development, showing significantly elevated expression in broiler chickens compared to layer chickens. These findings suggest active neural system connectivity during the initial formation of muscle fiber morphology in embryonic period, highlighting the early interaction between muscle fiber formation morphology and the nervous system. This study provides novel insights into late chick embryo development and lays a deeper foundation for further research.

Clinical Practice Guideline for Blood-based Circulating Tumor DNA Assays

Circulating tumor DNA (ctDNA) has emerged as a promising tool for various clinical applications, including early diagnosis, therapeutic target identification, treatment response monitoring, prognosis evaluation, and minimal residual disease detection. Consequently, ctDNA assays have been incorporated into clinical practice. In this review, we offer an in-depth exploration of the clinical implementation of ctDNA assays. Notably, we examined existing evidence related to pre-analytical procedures, analytical components in current technologies, and result interpretation and reporting processes. The primary objective of this guidelines is to provide recommendations for the clinical utilization of ctDNA assays.

Digital RNA sequencing using unique molecular identifiers enables ultrasensitive RNA mutation analysis

Mutation analysis is typically performed at the DNA level since most technical approaches are developed for DNA analysis. However, some applications, like transcriptional mutagenesis, RNA editing and gene expression analysis, require RNA analysis. Here, we combine reverse transcription and digital DNA sequencing to enable low error digital RNA sequencing. We evaluate yield, reproducibility, dynamic range and error correction rate for seven different reverse transcription conditions using multiplexed assays. The yield, reproducibility and error rate vary substantially between the specific conditions, where the yield differs 9.9-fold between the best and worst performing condition. Next, we show that error rates similar to DNA sequencing can be achieved for RNA using appropriate reverse transcription conditions, enabling detection of mutant allele frequencies <0.1% at RNA level. We also detect mutations at both DNA and RNA levels in tumor tissue using a breast cancer panel. Finally, we demonstrate that digital RNA sequencing can be applied to liquid biopsies, analyzing cell-free gene transcripts. In conclusion, we demonstrate that digital RNA sequencing is suitable for ultrasensitive RNA mutation analysis, enabling several basic research and clinical applications.

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 molecular residual disease (MRD) detection, 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. When applied to MRD detection, AccuScan demonstrated analytical sensitivity down to 10 -6 circulating tumor allele fraction at 99% sample level specificity. In colorectal cancer, AccuScan showed 90% landmark sensitivity for predicting relapse. It also showed robust MRD performance with esophageal cancer using samples collected as early as 1 week after surgery, and predictive value for immunotherapy monitoring with melanoma patients. Overall, AccuScan provides a highly accurate WGS solution for MRD, empowering circulating tumor DNA detection at parts per million range without high sample input nor personalized reagents.

One Sentence Summary

AccuScan showed remarkable ultra-low limit of detection with a short turnaround time, low sample requirement and a simple workflow for MRD detection.

Early Cancer Detection in Li-Fraumeni Syndrome with Cell-Free DNA

People with Li-Fraumeni syndrome (LFS) harbor a germline pathogenic variant in the TP53 tumor suppressor gene, face a near 100% lifetime risk of cancer, and routinely undergo intensive surveillance protocols. Liquid biopsy has become an attractive tool for a range of clinical applications, including early cancer detection. Here, we provide a proof-of-principle for a multimodal liquid biopsy assay that integrates a targeted gene panel, shallow whole-genome, and cell-free methylated DNA immunoprecipitation sequencing for the early detection of cancer in a longitudinal cohort of 89 LFS patients. Multimodal analysis increased our detection rate in patients with an active cancer diagnosis over uni-modal analysis and was able to detect cancer-associated signal(s) in carriers prior to diagnosis with conventional screening (positive predictive value = 67.6%, negative predictive value = 96.5%). Although adoption of liquid biopsy into current surveillance will require further clinical validation, this study provides a framework for individuals with LFS.

SIGNIFICANCE

By utilizing an integrated cell-free DNA approach, liquid biopsy shows earlier detection of cancer in patients with LFS compared with current clinical surveillance methods such as imaging. Liquid biopsy provides improved accessibility and sensitivity, complementing current clinical surveillance methods to provide better care for these patients. See related commentary by Latham et al., p. 23. This article is featured in Selected Articles from This Issue, p. 5.

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.

Identification of tumor mutations in plasma based on mutation variant frequency change (MVFC)

To overcome the dependency of strategies utilizing cell-free DNA (cfDNA) on tissue sampling, the emergence of sequencing panels for non-invasive mutation screening was promoted. However, cfDNA sequencing with panels still suffers from either inaccuracy or omission, and novel approaches for accurately screening tumor mutations solely based on plasma without gene panel restriction are urgently needed. We performed unique molecular identifier (UMI) target sequencing on plasma samples and peripheral blood mononuclear cells (PBMCs) from 85 hepatocellular carcinoma (HCC) patients receiving surgical resection, which were divided into an exploration dataset (20 patients) or an evaluation dataset (65 patients). Plasma mutations were identified in pre-operative plasma, and the mutation variant frequency change (MVFC) between post- and pre-operative plasma was then calculated. In the exploration dataset, we observed that plasma mutations with MVFC < 0.2 were enriched for tumor mutations identified in tumor tissues and had frequency changes that correlated with tumor burden; these plasma mutations were therefore defined as MVFC-identified tumor mutations. The presence of MVFC-identified tumor mutations after surgery was related to shorter relapse-free survival (RFS) in both datasets and thus indicated minimum residual disease (MRD). The combination of MVFC-identified tumor mutations and Alpha Fetoprotein (AFP) could further improve MRD detection (P < 0.0001). Identification of tumor mutations based on MVFC was also confirmed to be applicable with a different gene panel. Overall, we proposed a novel strategy for non-invasive tumor mutation screening using solely plasma that could be utilized in HCC tumor-burden monitoring and MRD detection.

Circulating tumour DNA kinetics in recurrent/metastatic head and neck squamous cell cancer patients

PURPOSE

Immune checkpoint blockade (ICB) has become a standard of care in the treatment of recurrent/metastatic head and neck squamous cell cancer (R/M HNSCC). However, only a subset of patients benefit from treatment. Quantification of plasma circulating tumour DNA (ctDNA) levels and on-treatment kinetics may permit real-time assessment of disease burden under selective pressures of treatment.

PATIENTS AND METHODS

R/M HNSCC patients treated with systemic therapy, platinum-based chemotherapy (CT) or ICB, underwent serial liquid biopsy sampling. Biomarkers tested included ctDNA measured by CAncer Personalized Profiling by deep Sequencing (CAPP-Seq) and markers of host inflammation measured by neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR).

RESULTS

Among 53 eligible patients, 16 (30%) received CT, 30 (57%) ICB [anti-PD1/L1] monotherapy and 7 (13%) combination immunotherapy (IO). Median progression-free survival (PFS) and overall survival (OS) were 2.8 months (95% CI, 1.3-4.3) and 8.2 months (95% CI, 5.6-10.8), respectively. Seven (13%) patients experienced a partial response and 21 (40%) derived clinical benefit. At baseline, median ctDNA variant allele frequency (VAF) was 4.3%. Baseline ctDNA abundance was not associated with OS (p = 0.56) nor PFS (p = 0.54). However, a change in ctDNA VAF after one cycle of treatment (ΔVAF (T1-2)) was predictive of both PFS (p< 0.01) and OS (p< 0.01). Additionally, decrease in ΔVAF identified patients with longer OS despite early radiological progression, 8.2 vs 4.6 months, hazard ratio 0.44 (95% CI, 0.19-0.87) p = 0.03. After incorporating NLR and PLR into multivariable Cox models, ctDNA ∆VAF retained an association with OS.

CONCLUSIONS

Early dynamic changes in ctDNA abundance, after one cycle of treatment, compared to baseline predicted both OS and PFS in R/M HNSCC patients on systemic therapy.

Multimodal immunogenomic biomarker analysis of tumors from pediatric patients enrolled to a phase 1-2 study of single-agent atezolizumab

We report herein an exploratory biomarker analysis of refractory tumors collected from pediatric patients before atezolizumab therapy (iMATRIX-atezolizumab, NCT02541604 ). Elevated levels of CD8⁺ T cells and PD-L1 were associated with progression-free survival and a diverse baseline infiltrating T-cell receptor repertoire was prognostic. Differential gene expression analysis revealed elevated expression of CALCA (preprocalcitonin) and CCDC183 (highly expressed in testes) in patients who experienced clinical activity, suggesting that tumor neoantigens from these genes may contribute to immune response. In patients who experienced partial response or stable disease, elevated Igα2 expression correlated with T- and B-cell infiltration, suggesting that tertiary lymphoid structures existed in these patients' tumors. Consensus gene co-expression network analysis identified core cellular pathways that may play a role in antitumor immunity. Our study uncovers features associated with response to immune-checkpoint inhibition in pediatric patients with cancer and provides biological and translational insights to guide prospective biomarker profiling in future clinical trials.

Therapy-Acquired Clonal Mutations in Thiopurine Drug-Response Genes Drive Majority of Early Relapses in Pediatric B-Cell Precursor Acute Lymphoblastic Leukemia

METHODS

Forty pediatric (0-12 years) B-ALL DNA samples (20 paired Diagnosis-Relapse) and an additional six B-ALL DNA samples (without relapse at 3 years post treatment), as the non-relapse arm, were retrieved from the biobank for advanced genomic analysis. Deep sequencing (1050-5000X; mean 1600X) was performed using a custom NGS panel of 74 genes incorporating unique molecular barcodes.

RESULTS

A total 47 major clones (>25% VAF) and 188 minor clones were noted in 40 cases after bioinformatic data filtering. Of the forty-seven major clones, eight (17%) were diagnosis-specific, seventeen (36%) were relapse-specific and 11 (23%) were shared. In the control arm, no pathogenic major clone was noted in any of the six samples. The most common clonal evolution pattern observed was therapy-acquired (TA), with 9/20 (45%), followed by M-M, with 5/20 (25%), m-M, with 4/20 (20%) and unclassified (UNC) 2/20 (10%). The TA clonal pattern was predominant in early relapses 7/12 (58%), with 71% (5/7) having major clonal mutations in the NT5C2 or PMS2 gene related to thiopurine-dose response. In addition, 60% (3/5) of these cases were preceded by an initial hit in the epigenetic regulator, KMT2D. Mutations in common relapse-enriched genes comprised 33% of the very early relapses, 50% of the early and 40% of the late relapses. Overall, 14/46 (30%) of the samples showed the hypermutation phenotype, of which the majority (50%) had a TA pattern of relapse.

CONCLUSIONS

Our study highlights the high frequency of early relapses driven by TA clones, demonstrating the need to identify their early rise during chemotherapy by digital PCR.

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.

Myeloma immunoglobulin rearrangement and translocation detection through targeted capture sequencing

Multiple myeloma is a plasma cell neoplasm characterized by clonal immunoglobulin V(D)J signatures and oncogenic immunoglobulin gene translocations. Additional subclonal genomic changes are acquired with myeloma progression and therapeutic selection. PCR-based methods to detect V(D)J rearrangements can have biases introduced by highly multiplexed reactions and primers undermined by somatic hypermutation, and are not readily extended to include mutation detection. Here, we report a hybrid-capture approach (CapIG-seq) targeting the 3' and 5' ends of the V and J segments of all immunoglobulin loci that enable the efficient detection of V(D)J rearrangements. We also included baits for oncogenic translocations and mutation detection. We demonstrate complete concordance with matched whole-genome sequencing and/or PCR clonotyping of 24 cell lines and report the clonal sequences for 41 uncharacterized cell lines. We also demonstrate the application to patient specimens, including 29 bone marrow and 39 cell-free DNA samples. CapIG-seq shows concordance between bone marrow and cfDNA blood samples (both contemporaneous and follow-up) with regard to the somatic variant, V(D)J, and translocation detection. CapIG-seq is a novel, efficient approach to examining genomic alterations in myeloma.

Sensitive and reproducible cell-free methylome quantification with synthetic spike-in controls

Cell-free methylated DNA immunoprecipitation sequencing (cfMeDIP-seq) identifies genomic regions with DNA methylation, using a protocol adapted to work with low-input DNA samples and with cell-free DNA (cfDNA). We developed a set of synthetic spike-in DNA controls for cfMeDIP-seq to provide a simple and inexpensive reference for quantitative normalization. We designed 54 DNA fragments with combinations of methylation status (methylated and unmethylated), fragment length (80 bp, 160 bp, 320 bp), G + C content (35%, 50%, 65%), and fraction of CpG dinucleotides within the fragment (1/80 bp, 1/40 bp, 1/20 bp). Using 0.01 ng of spike-in controls enables training a generalized linear model that absolutely quantifies methylated cfDNA in MeDIP-seq experiments. It mitigates batch effects and corrects for biases in enrichment due to known biophysical properties of DNA fragments and other technical biases.

Heterogeneity and transcriptome changes of human CD8+ T cells across nine decades of life

The decline of CD8⁺ T cell functions contributes to deteriorating health with aging, but the mechanisms that underlie this phenomenon are not well understood. We use single-cell RNA sequencing with both cross-sectional and longitudinal samples to assess how human CD8⁺ T cell heterogeneity and transcriptomes change over nine decades of life. Eleven subpopulations of CD8⁺ T cells and their dynamic changes with age are identified. Age-related changes in gene expression result from changes in the percentage of cells expressing a given transcript, quantitative changes in the transcript level, or a combination of these two. We develop a machine learning model capable of predicting the age of individual cells based on their transcriptomic features, which are closely associated with their differentiation and mutation burden. Finally, we validate this model in two separate contexts of CD8⁺ T cell aging: HIV infection and CAR T cell expansion in vivo.

The characterisation of T cells during aging is important to predict functional outcomes in vaccination or infection. Here the authors use flow cytometry and scRNA sequencing to transcriptionally age CD8 T cells and then use a machine learning model to interpret cell age from transcriptional profiles.

Circulating Exosome Cargoes Contain Functionally Diverse Cancer Biomarkers: From Biogenesis and Function to Purification and Potential Translational Utility

Although diagnostic and therapeutic treatments of cancer have tremendously improved over the past two decades, the indolent nature of its symptoms has made early detection challenging. Thus, inter-disciplinary (genomic, transcriptomic, proteomic, and lipidomic) research efforts have been focused on the non-invasive identification of unique "silver bullet" cancer biomarkers for the design of ultra-sensitive molecular diagnostic assays. Circulating tumor biomarkers, such as CTCs and ctDNAs, which are released by tumors in the circulation, have already demonstrated their clinical utility for the non-invasive detection of certain solid tumors. Considering that exosomes are actively produced by all cells, including tumor cells, and can be found in the circulation, they have been extensively assessed for their potential as a source of circulating cell-specific biomarkers. Exosomes are particularly appealing because they represent a stable and encapsulated reservoir of active biological compounds that may be useful for the non-invasive detection of cancer. T biogenesis of these extracellular vesicles is profoundly altered during carcinogenesis, but because they harbor unique or uniquely combined surface proteins, cancer biomarker studies have been focused on their purification from biofluids, for the analysis of their RNA, DNA, protein, and lipid cargoes. In this review, we evaluate the biogenesis of normal and cancer exosomes, provide extensive information on the state of the art, the current purification methods, and the technologies employed for genomic, transcriptomic, proteomic, and lipidomic evaluation of their cargoes. Our thorough examination of the literature highlights the current limitations and promising future of exosomes as a liquid biopsy for the identification of circulating tumor biomarkers.

MicroRNAs Promote the Progression of Sepsis-Induced Cardiomyopathy and Neurovascular Dysfunction Through Upregulation of NF-kappaB Signaling Pathway-Associated HDAC7/ACTN4

Introduction

The objective of this study was to determine the NF-kappaB pathway, hub genes, and transcription factors (TFs) in monocytes implicated in the progression of neurovascular-related sepsis-induced cardiomyopathy (SIC) as well as potential miRNAs with regulatory functions.

Methods

: Sepsis-induced cardiomyopathy—and heart failure (HF)-related differentially expressed genes (DEGs) between SIC and HF groups were identified separately by differential analysis. In addition, DEGs and differentially expressed miRNAs (DEmiRNAs) in monocytes between sepsis and the HC group were identified. Then, common DEGs in SIC, HF, and monocyte groups were identified by intersection analysis. Based on the functional pathways enriched by these DEGs, genes related to the NF-kB-inducing kinase (NIK)/NF-kappaB signaling pathway were selected for further intersection analysis to obtain hub genes. These common DEGs, together with sepsis-related DEmiRNAs, were used to construct a molecular interplay network and to identify core TFs in the network.

Results

: A total of 153 upregulated genes and 25 downregulated genes were obtained from SIC-, HF-, and monocyte-related DEGs. Functional pathway analysis revealed that the upregulated genes were enriched in NF-κB signaling pathway. A total of eight genes associated with NF-κB signaling pathway were then further identified from the 178 DEGs. In combination with sepsis-related DEmiRNAs, HDAC7/ACTN4 was identified as a key transcriptional regulatory pair in the progression of SIC and in monocyte regulation. hsa-miR-23a-3p, hsa-miR-3175, and hsa-miR-23b-3p can regulate the progression of SIC through the regulation of HDAC7/ACTN4. Finally, gene set enrichment analysis (GSEA) suggested that HDAC7/ACTN4 may be associated with apoptosis in addition to the inflammatory response.

Conclusion

: hsa-miR-23a-3p, hsa-miR-3175, and hsa-miR-23b-3p are involved in SIC progression by regulating NF-κB signaling signaling pathway-related HDAC7/ACTN4 in monocytes and cardiac tissue cells. These mechanisms may contribute to sepsis-induced neurovascular damage.

OPUSeq simplifies detection of low-frequency DNA variants and uncovers fragmentase-associated artifacts

Detection of low-frequency DNA variants (below 1%) is becoming increasingly important in biomedical research and clinical practice, but is challenging to do with standard sequencing approaches due to high error rates. The use of double-stranded unique molecular identifiers (dsUMIs) allows correction of errors by comparing reads arising from the same original DNA duplex. However, the implementation of such approaches is still challenging. Here, we present a novel method, one-pot dsUMI sequencing (OPUSeq), which allows incorporation of dsUMIs in the same reaction as the library PCR. This obviates the need for adapter pre-synthesis or additional enzymatic steps. OPUSeq can be incorporated into standard DNA library preparation approaches and coupled with hybridization target capture. We demonstrate successful error correction and detection of variants down to allele frequency of 0.01%. Using OPUSeq, we also show that the use of enzymatic fragmentation can lead to the appearance of spurious double-stranded variants, interfering with detection of variant fractions below 0.1%.

Circulating Tumor DNA: An Emerging Tool in Gastrointestinal Cancers

Circulating tumor DNA (ctDNA) is tumor-derived fragmented DNA in the bloodstream that has come from primary or metastatic cancer sites. Neoplasm-specific genetic and epigenetic abnormalities are increasingly being identified through liquid biopsy: a novel, minimally invasive technique used to isolate and analyze ctDNA in the peripheral circulation. Liquid biopsy and other emerging ctDNA technologies represent a paradigm shift in cancer diagnostics because they allow for the detection of minimal residual disease in patients with early-stage disease, improve risk stratification, capture tumor heterogeneity and genomic evolution, and enhance ctDNA-guided adjuvant and palliative cancer therapy. Moreover, ctDNA can be used to monitor the tumor response to neoadjuvant and postoperative therapy in patients with metastatic disease. Using clearance of ctDNA as an endpoint for escalation/de-escalation of adjuvant chemotherapy for patients considered to have high-risk disease has become an important area of research. The possibility of using ctDNA as a surrogate for treatment response-including for overall survival, progression-free survival, and disease-free survival-is an attractive concept; this surrogate will arguably reduce study duration and expedite the development of new therapies. In this review, we summarize the current evidence on the applications of ctDNA for the diagnosis and management of gastrointestinal tumors. Gastrointestinal cancers-including tumors of the esophagus, stomach, colon, liver, and pancreas-account for one-quarter of global cancer diagnoses and contribute to more than one-third of cancer-related deaths. Given the prevalence of gastrointestinal malignancies, ctDNA technology represents a powerful tool to reduce the global burden of disease.

Physiological magnesium concentrations increase fidelity of diverse reverse transcriptases from HIV-1, HIV-2, and foamy virus, but not MuLV or AMV

Reverse transcriptases (RTs) are typically assayed using optimized Mg²⁺ concentrations (~5-10 mM) several-fold higher than physiological cellular free Mg²⁺ (~0.5 mM). Recent analyses demonstrated that HIV-1, but not Moloney murine leukaemia (MuLV) or avain myeloblastosis (AMV) virus RTs has higher fidelity in low Mg²⁺. In the current report, lacZα-based α-complementation assays were used to measure the fidelity of several RTs including HIV-1 (subtype B and A/E), several drug-resistant HIV-1 derivatives, HIV-2, and prototype foamy virus (PFV), all which showed higher fidelity using physiological Mg²⁺, while MuLV and AMV RTs demonstrated equivalent fidelity in low and high Mg²⁺. In 0.5 mM Mg²⁺, all RTs demonstrated approximately equal fidelity, except for PFV which showed higher fidelity. A Next Generation Sequencing (NGS) approach that used barcoding to determine mutation profiles was used to examine the types of mutations made by HIV-1 RT (type B) in low (0.5 mM) and high (6 mM) Mg²⁺ on a lacZα template. Unlike α-complementation assays which are dependent on LacZα activity, the NGS assay scores mutations at all positions and of every type. Consistent with α-complementation assays, a ~four-fold increase in mutations was observed in high Mg²⁺. These findings help explain why HIV-1 RT displays lower fidelity in vitro (with high Mg²⁺ concentrations) than other RTs (e.g. MuLV and AMV), yet cellular fidelity for these viruses is comparable. Establishing in vitro conditions that accurately represent RT's activity in cells is pivotal to determining the contribution of RT and other factors to the mutation profile observed with HIV-1.

HPV Sequencing Facilitates Ultrasensitive Detection of HPV Circulating Tumor DNA

PURPOSE

Human papillomavirus (HPV) DNA offers a convenient circulating tumor DNA (ctDNA) marker for HPV-associated malignancies, but current methods, such as digital PCR (dPCR), provide insufficient accuracy for clinical applications in patients with low disease burden. We asked whether a next-generation sequencing approach, HPV sequencing (HPV-seq), could provide quantitative and qualitative assessment of HPV ctDNA in low disease burden settings.

EXPERIMENTAL DESIGN

We conducted preclinical technical validation studies on HPV-seq and applied it retrospectively to a prospective multicenter cohort of patients with locally advanced cervix cancer (NCT02388698) and a cohort of patients with oropharynx cancer. HPV-seq results were compared with dPCR. The primary outcome was progression-free survival (PFS) according to end-of-treatment HPV ctDNA detectability.

RESULTS

HPV-seq achieved reproducible detection of HPV DNA at levels less than 0.6 copies in cell line data. HPV-seq and dPCR results for patients were highly correlated (R ² = 0.95, P = 1.9 × 10^-29) with HPV-seq detecting ctDNA at levels down to 0.03 copies/mL plasma in dPCR-negative posttreatment samples. Detectable HPV ctDNA at end-of-treatment was associated with inferior PFS with 100% sensitivity and 67% specificity for recurrence. Accurate HPV genotyping was successful from 100% of pretreatment samples. HPV ctDNA fragment sizes were consistently shorter than non-cancer-derived cell-free DNA (cfDNA) fragments, and stereotyped cfDNA fragmentomic patterns were observed across HPV genomes.

CONCLUSIONS

HPV-seq is a quantitative method for ctDNA detection that outperforms dPCR and reveals qualitative information about ctDNA. Our findings in this proof-of-principle study could have implications for treatment monitoring of disease burden in HPV-related cancers. Future prospective studies are needed to confirm that patients with undetectable HPV ctDNA following chemoradiotherapy have exceptionally high cure rates.

Minimal Residual Disease in Myeloma: Application for Clinical Care and New Drug Registration

The development of novel agents has transformed the treatment paradigm for multiple myeloma, with minimal residual disease (MRD) negativity now achievable across the entire disease spectrum. Bone marrow-based technologies to assess MRD, including approaches using next-generation flow and next-generation sequencing, have provided real-time clinical tools for the sensitive detection and monitoring of MRD in patients with multiple myeloma. Complementary liquid biopsy-based assays are now quickly progressing with some, such as mass spectrometry methods, being very close to clinical use, while others utilizing nucleic acid-based technologies are still developing and will prove important to further our understanding of the biology of MRD. On the regulatory front, multiple retrospective individual patient and clinical trial level meta-analyses have already shown and will continue to assess the potential of MRD as a surrogate for patient outcome. Given all this progress, it is not surprising that a number of clinicians are now considering using MRD to inform real-world clinical care of patients across the spectrum from smoldering myeloma to relapsed refractory multiple myeloma, with each disease setting presenting key challenges and questions that will need to be addressed through clinical trials. The pace of advances in targeted and immune therapies in multiple myeloma is unprecedented, and novel MRD-driven biomarker strategies are essential to accelerate innovative clinical trials leading to regulatory approval of novel treatments and continued improvement in patient outcomes.

Tumor-Naïve Multimodal Profiling of Circulating Tumor DNA in Head and Neck Squamous Cell Carcinoma

PURPOSE

Circulating tumor DNA (ctDNA) enables personalized treatment strategies in oncology by providing a noninvasive source of clinical biomarkers. In patients with low ctDNA abundance, tumor-naïve methods are needed to facilitate clinical implementation. Here, using locoregionally confined head and neck squamous cell carcinoma (HNSCC) as an example, we demonstrate tumor-naïve detection of ctDNA by simultaneous profiling of mutations and methylation.

EXPERIMENTAL DESIGN

We conducted CAncer Personalized Profiling by deep Sequencing (CAPP-seq) and cell-free Methylated DNA ImmunoPrecipitation and high-throughput sequencing (cfMeDIP-seq) for detection of ctDNA-derived somatic mutations and aberrant methylation, respectively. We analyzed 77 plasma samples from 30 patients with stage I-IVA human papillomavirus-negative HNSCC as well as plasma samples from 20 risk-matched healthy controls. In addition, we analyzed leukocytes from patients and controls.

RESULTS

CAPP-seq identified mutations in 20 of 30 patients at frequencies similar to that of The Tumor Genome Atlas (TCGA). Differential methylation analysis of cfMeDIP-seq profiles identified 941 ctDNA-derived hypermethylated regions enriched for CpG islands and HNSCC-specific methylation patterns. Both methods demonstrated an association between ctDNA abundance and shorter fragment lengths. In addition, mutation- and methylation-based ctDNA abundance was highly correlated (r > 0.85). Patients with detectable pretreatment ctDNA by both methods demonstrated significantly worse overall survival (HR = 7.5; P = 0.025) independent of clinical stage, with lack of ctDNA clearance post-treatment strongly correlating with recurrence. We further leveraged cfMeDIP-seq profiles to validate a prognostic signature identified from TCGA samples.

CONCLUSIONS

Tumor-naïve detection of ctDNA by multimodal profiling may facilitate biomarker discovery and clinical use in low ctDNA abundance applications.

Single-Cell Transcriptome Profiling Simulation Reveals the Impact of Sequencing Parameters and Algorithms on Clustering

Despite the scRNA-seq analytic algorithms developed, their performance for cell clustering cannot be quantified due to the unknown "true" clusters. Referencing the transcriptomic heterogeneity of cell clusters, a "true" mRNA number matrix of cell individuals was defined as ground truth. Based on the matrix and the actual data generation procedure, a simulation program (SSCRNA) for raw data was developed. Subsequently, the consistency between simulated data and real data was evaluated. Furthermore, the impact of sequencing depth and algorithms for analyses on cluster accuracy was quantified. As a result, the simulation result was highly consistent with that of the actual data. Among the clustering algorithms, the Gaussian normalization method was the more recommended. As for the clustering algorithms, the K-means clustering method was more stable than K-means plus Louvain clustering. In conclusion, the scRNA simulation algorithm developed restores the actual data generation process, discovers the impact of parameters on classification, compares the normalization/clustering algorithms, and provides novel insight into scRNA analyses.

CRISPAltRations: a validated cloud-based approach for interrogation of double-strand break repair mediated by CRISPR genome editing

CRISPR systems enable targeted genome editing in a wide variety of organisms by introducing single- or double-strand DNA breaks, which are repaired using endogenous molecular pathways. Characterization of on- and off-target editing events from CRISPR proteins can be evaluated using targeted genome resequencing. We characterized DNA repair fingerprints that result from non-homologous end joining (NHEJ) after double-stranded breaks (DSBs) were introduced by Cas9 or Cas12a for >500 paired treatment/control experiments. We found that building biological understanding of the repair into a novel analysis tool (CRISPAltRations) improved the quality of the results. We validated our software using simulated, targeted amplicon sequencing data (11 guide RNAs [gRNAs] and 603 on- and off-target locations) and demonstrated that CRISPAltRations outperforms other publicly available software tools in accurately annotating CRISPR-associated indels and homology-directed repair (HDR) events. We enable non-bioinformaticians to use CRISPAltRations by developing a web-accessible, cloud-hosted deployment, which allows rapid batch processing of samples in a graphical user interface (GUI) and complies with HIPAA security standards. By ensuring that our software is thoroughly tested, version controlled, and supported with a user interface (UI), we enable resequencing analysis of CRISPR genome editing experiments to researchers no matter their skill in bioinformatics.

Accelerating SARS-CoV-2 low frequency variant calling on ultra deep sequencing datasets

With recent advances in sequencing technology it has become affordable and practical to sequence genomes to very high depth-of-coverage, allowing researchers to discover low-frequency variants in the genome. However, due to the errors in sequencing it is an active area of research to develop algorithms that can separate noise from the true variants. LoFreq is a state of the art algorithm for low-frequency variant detection but has a relatively long runtime compared to other tools. In addition to this, the interface for running in parallel could be simplified, allowing for multithreading as well as distributing jobs to a cluster. In this work we describe some specific contributions to LoFreq that remedy these issues.

Liquid biopsy enters the clinic - implementation issues and future challenges

Historically, studies of disseminated tumour cells in bone marrow and circulating tumour cells in peripheral blood have provided crucial insights into cancer biology and the metastatic process. More recently, advances in the detection and characterization of circulating tumour DNA (ctDNA) have finally enabled the introduction of liquid biopsy assays into clinical practice. The FDA has already approved several single-gene assays and, more recently, multigene assays to detect genetic alterations in plasma cell-free DNA (cfDNA) for use as companion diagnostics matched to specific molecularly targeted therapies for cancer. These approvals mark a tipping point for the widespread use of liquid biopsy in the clinic, and mostly in patients with advanced-stage cancer. The next frontier for the clinical application of liquid biopsy is likely to be the systemic treatment of patients with 'ctDNA relapse', a term we introduce for ctDNA detection prior to imaging-detected relapse after curative-intent therapy for early stage disease. Cancer screening and diagnosis are other potential future applications. In this Perspective, we discuss key issues and gaps in technology, clinical trial methodologies and logistics for the eventual integration of liquid biopsy into the clinical workflow.

Integration of intra-sample contextual error modeling for improved detection of somatic mutations from deep sequencing

Sensitive mutation detection by next-generation sequencing is critical for early cancer detection, monitoring minimal/measurable residual disease (MRD), and guiding precision oncology. Nevertheless, because of artifacts introduced during library preparation and sequencing, the detection of low-frequency variants at high specificity is problematic. Here, we present Espresso, an error suppression method that considers local sequence features to accurately detect single-nucleotide variants (SNVs). Compared to other advanced error suppression techniques, Espresso consistently demonstrated lower numbers of false-positive mutation calls and greater sensitivity. We demonstrated Espresso's superior performance in detecting MRD in the peripheral blood of patients with acute myeloid leukemia (AML) throughout their treatment course. Furthermore, we showed that accurate mutation calling in a small number of informative genomic loci might provide a cost-efficient strategy for pragmatic risk prediction of AML development in healthy individuals. More broadly, we aim for Espresso to aid with accurate mutation detection in many other research and clinical settings.

Liquid biopsy as a perioperative biomarker of digestive tract cancers: review of the literature

Tissue biopsies are the gold-standard for investigating the molecular characterization of tumors. However, a "solid" biopsy is an invasive procedure that cannot capture real-time tumor dynamics and may yield inaccurate information because of intratumoral heterogeneity. In this review, we summarize the current state of knowledge about surgical treatment-associated "liquid" biopsy for patients with digestive organ tumors. A liquid biopsy is a technique involving the sampling and testing of non-solid biological materials, including blood, urine, saliva, and ascites. Previous studies have reported the potential value of blood-based biomarkers, circulating tumor cells, and cell-free nucleic acids as facilitators of cancer treatment. The applications of a liquid biopsy in a cancer treatment setting include screening and early diagnosis, prognostication, and outcome and recurrence monitoring of cancer. This technique has also been suggested as a useful tool in personalized medicine. The transition to precision medicine is still in its early stages. Soon, however, liquid biopsy is likely to form the basis of patient selection for molecular targeted therapies, predictions regarding chemotherapy sensitivity, and real-time evaluations of therapeutic effects.

Precision medicine in non-small cell lung cancer: Current applications and future directions

Advances in biomarkers, targeted therapies, and immuno-oncology have transformed the clinical management of patients with advanced NSCLC. For oncogene-driven tumors, there are highly effective targeted therapies against EGFR, ALK, ROS1, BRAF, TRK, RET, and MET. In addition, investigational therapies for KRAS, NRG1, and HER2 have shown promising results and may become standard-of-care in the near future. In parallel, immune-checkpoint therapy has emerged as an indispensable treatment modality, especially for patients lacking actionable oncogenic drivers. While PD-L1 expression has shown modest predictive utility, biomarkers for immune-checkpoint inhibition in NSCLC have remained elusive and represent an area of active investigation. Given the growing importance of biomarkers, optimal utilization of small tissue biopsies and alternative genotyping methods using circulating cell-free DNA have become increasingly integrated into clinical practice. In this review, we will summarize the current landscape and emerging trends in precision medicine for patients with advanced NSCLC with a special focus on predictive biomarker testing.