DNA Fragmentation Research Articles

Ameliorative impacts of carvacrol on DNA integrity, oxidative stress, and sperm quality in asthenozoospermic infertile individuals during cryopreservation.

Nowadays, the cryopreservation process can produce reactive oxygen species (ROS), which cause damage to the motility, cell membrane, and DNA integrity of sperm. This study is aimed at evaluating the impact of carvacrol, as a powerful antioxidant, on sperm features and improving oxidative stress throughout the cryopreservation procedure. In this prospective study, semen samples from 25 patients with asthenozoospermia were separated into three groups: fresh, freezing, and freezing + carvacrol (a dose of 100µM). The subsequent parameters were evaluated using standard methods in all three groups: sperm motility according to WHO criteria, sperm morphology using Papanicolaou staining, sperm viability with eosin-nigrosin staining, DNA integrity with acridine orange staining, levels of antioxidant enzymes (catalase, glutathione, and superoxide dismutase), total antioxidant capacity (TAC), and malondialdehyde (MDA) using ELISA. Also, DNA fragmentation was analyzed by the SDFA kit, and mitochondrial membrane potential (MMP) was assessed by rhodamine staining. Average sperm viability, motility, mitochondrial membrane potentiality, integrity of sperm membrane, and antioxidant enzyme levels are meaningfully reduced in the freezing group in contrast to the control group. The freezing group showed a meaningful rise in the mean MDA levels and DNA fragmentation compared to the control group. In the freezing group supplemented with carvacrol, a meaningful rise could be visible in mean percentages of viability, motility, and antioxidant enzyme levels, whereas mean levels of MDA and DNA fragmentation meaningfully declined in contrast to the freezing group. The results demonstrate that carvacrol, a potent antioxidant, offers significant protection against the loss generated by the freeze-thaw procedure, thereby improving sperm quality.

Characterization of poly(A) and poly(T) tail lengths in plasmid DNA by liquid chromatography high-resolution mass spectrometry.

Rapid advances in messenger RNA (mRNA) technology necessitate effective analytical methods. This study describes the development of a novel in vitro method using ion-pair reversed-phase liquid chromatography coupled to high-resolution mass spectrometry (IP-RP-LC-HRMS) for assessing the poly(A) and complementary poly(T) tail lengths directly into the DNA template used to manufacture mRNA. Briefly, after the validation of poly(A) tail length in the plasmid by Sanger sequencing, double-stranded DNA fragments containing these tails in the plasmid of interest were amplified by thepolymerase chain reaction (PCR), purified on silica column, and digested with restriction enzymes ClaI and HindIII. Gel or capillary electrophoresis confirmed sample quality and enzymatic digestion efficiency. Subsequently, poly(A) and complementary poly(T) tails were extracted and analyzed by LC-MS to determine their length and heterogeneity at a single-nucleotide resolution. Three DNA templates containing poly(A) tail lengths of 60A-G, 95A, or 108A were studied. LC-MS results correlated well with Sanger sequencing, identifying major populations of 60A-G, 95A, or 108A. Surprisingly, unlike Sanger sequencing, LC-MS analysis revealed minor poly(A) populations with lengths longer or shorter than the theoretically encoded poly(A) tail length. This finding could be explained by (i) the slippage of bacterial DNA polymerase I during plasmid replication in bacterial culture, which occurs on repeat mononucleotide sequences, or (ii) the slippage of Q5® High-Fidelity DNA Polymerase during PCR amplification. In conclusion, the method is easy, rapid, and accurate and could replace Sanger sequencing to assess the poly(A) and complementary poly(T) tail lengths in plasmid DNA.

Evaluation of spermatic DNA fragmentation in smoking normospermic infertile individuals

Aim: In approximately 20% of infertile couples, the male factor is the only main cause. In recent years, it has been hypothesized that sperm DNA integrity may be a better indicator than routine semen analysis. Although the effects of smoking on male infertility have not yet been proven, smoking is considered a reasonable risk factor for infertility. In our study, we aimed to evaluate DNA damage in normospermic infertile men who smoke and do not smoke using the acridine orange method. Material and Methods: This study was conducted on semen samples from 50 male cases, 25 of whom were smokers and non-smokers, who met the infertility criteria and applied to the urology clinic of Dicle University Medical Faculty Hospital. Microscopic examinations and morphological evaluations were performed in accordance with the WHO 2010 criteria. The acridine orange method was applied to evaluate DNA fragmentation and DNA fragmentations were calculated. Statistical analysis of the obtained data was performed using the Mann-Whitney U Test. Results: In our study, in the smoking group, age was significantly associated with the duration of infertility, concentration with total motile sperm count, total sperm count with total motile sperm count, and amorphous head anomaly (p<0.01). In the non-smoking group, age and infertility were significantly associated with the duration, volume and total count, concentration and total count, total motile sperm count, and DNA fragmentation (p<0.01). However, there was no statistical difference between the smoking and non-smoking groups in terms of semen parameters and DNA fragmentation (p>0.05). Conclusion: In order to obtain more reliable results, it is thought that large-scale studies are needed in the same groups and in the general population. Keywords: sperm, infertility, DNA fragmentation, smoking

Participation of retroelements in chromoanagenesis in cancer development

Purpose of the study: to determine the role of retroelements in chromoanagenesis mechanisms in cancer etiopathogenesis.Material and Methods. The search for relevant sources was carried out in the Scopus, Web of Science, PubMed, Elibrary systems, including publications from February 2002 to December 2023. Of the 864 scientifc articles found, 60 were used to write a systematic review.Results. According to original works and meta-analyses results, the cause of complex chromosomal rearrangements during cancer development may be retroelement pathological activation. Chromoanagenesis involves LINE1, SVA, Alu, HERV, which cause double-stranded DNA breaks, insertions in tumor suppressor genes region, the formation of chimeric oncogenes due to retroelement use as new promoters, and function as molecular “band-aids” in non-homologous end junctions and form bridges of distal DNA fragments. Global structural rearrangements of chromosomes observed during chromoanagenesis may be consequences of retroelements activation, which participate in non-allelic homologous recombination and in microhomology-mediated joining of ends characteristic. Certain types of neoplasms, such as colon cancer, are characterized by both high levels of chromothripsis and retroelement activity. In head and neck squamous cell carcinoma, chromoplexy is specifc, the sources of sequences at the breakpoints of which are retroelements. During chromoanagenesis, activation of proto-oncogenes and inactivation of tumor suppressor genes are observed, which is also a consequence of retroelement activation. This is due to the presence of retroelement sequences in proto-oncogenes promoter regions and introns (which become the basis for chimeric oncogene formation) and hot spots of insertional mutagenesis in tumor suppressor genes (transpositions into these regions inactivate these genes).Conclusion. The results obtained on the driver effect of retroelements in chromothripsis, chromoplexy and chromoanasynthesis mechanisms, which are the basis for the formation of clonal evolution of tumors, indicate promise of targeted therapy aimed at silencing the activity of retroelements in cancer patients treatment. For this purpose, it is possible to use microRNAs complementary to retroelements, which are also involved in tumor development, as tools.

Comparison of androgen receptor mutation detection between plasma extracellular vesicle DNA and cell-free DNA and its relationship to prostate cancer prognosis

Background In liquid biopsy, mutation detection is primarily performed using cell-free DNA (cfDNA). However, the numerous advantages of extracellular vesicle (EV) DNA for mutation detection have gradually garnered the attention of researchers in recent years. This study aimed to compare the differences between EV DNA and cfDNA in mutation detection and explore the role of plasma androgen receptor (AR) mutations in the prognosis of prostate cancer (PCa). Methods We compared the biological characteristics of plasma extracellular vesicle DNA (p-EV DNA) and cfDNA by capillary electrophoresis and concentration detection. Subsequently, we performed pan-oncogene-targeted sequencing in paired tissue and plasma samples from five patients with PCa to verify the feasibility of mutation detection using p-EV DNA and cfDNA. Further, we conducted AR mutation detection in expanded samples to compare the differences between EV DNA and cfDNA in mutation detection and to analyse their role in PCa. Results p-EV DNA fragments were larger than plasma cell-free DNA (p-cfDNA) fragments; however, there was no significant difference in their concentrations in the plasma of patients with PCa. Feasibility analysis revealed that major mutations associated with PCa detected in tissue samples could be identified in both p-EV DNA and p-cfDNA. Advantage comparison found that, although cfDNA could detect more mutations, AR mutations in EV DNA were more strongly associated with a poor prognosis of PCa than cfDNA. Conclusion Mutation detection using either EV DNA or cfDNA is both feasible in PCa liquid biopsies, and EV DNA AR mutations have an advantage in prognostic assessment for PCa. This study lays the foundation for future research on EV DNA-related biomarkers.

Abstract B068: Inferring enhancer activity from cell-free DNA fragmentation patterns

Abstract We present a framework for inferring enhancer activity from cell-free DNA (cfDNA) fragmentation patterns, offering a novel feature set for cfDNA analysis that reflects gene regulation. Enhancers are promoter-distal regulatory elements that regulate gene expression programs that define cell types and cellular states. Despite advances in inferring gene regulation in cancer using liquid biopsy, it remains challenging to identify signals of enhancer activity from cell-free DNA (cfDNA). Active enhancers are characterized by transcription of short enhancer RNAs (eRNAs). Recent studies demonstrated that cfDNA from promoters of transcribed genes demonstrates high variation in DNA fragment length, or “fragmentation entropy”. We tested whether eRNA transcription can be inferred based on cfDNA fragmentation entropy. We quantified “enhancer fragmentation entropy” (EFE) to profile enhancer activity in plasma by measuring Shannon entropy of cfDNA fragments around enhancer transcription start sites (TSS). Using PRO-cap data from lymphoblastoid cell lines, we analyzed EFE signals at 70,000 transcribed enhancers and observed distinct patterns between active (expressed) and inactive enhancers in cfDNA from healthy individuals. cfDNA from patients with prostate cancer showed elevated EFE at enhancers activated in prostate cancer. EFE at these sites correlated with circulating tumor DNA (ctDNA) levels in a published cfDNA dataset of 41 prostate cancer plasma samples. Lower-dimensional projections of the entropy signals across 300 “modules” of co-regulated enhancers revealed tighter clustering of samples within the same cancer type, suggesting that these entropy patterns capture cell-type specific enhancer activity. Our findings suggest that enhancer fragmentation entropy captures cell-type specific signals and, when measured at cancer-specific enhancers in cfDNA, could serve as a promising biomarker for cancer detection and monitoring. Ongoing work is focused on validating these findings in larger cohorts and applying EFE to cancer monitoring and clinical subtyping. Citation Format: Alexis Yang. Inferring enhancer activity from cell-free DNA fragmentation patterns [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B068.

Abstract IA021: Plasma-only ultrasensitive liquid biopsy to monitor tumor burden and clonal evolution

Abstract Individual bulk tumor biopsies are invasive and may fail to capture clonal heterogeneity within primary tumors and metastatic sites of disease. Further, analyses of subclonal variants are often hindered by background error rates related to tissue preservation methods (e.g. FFPE) and sequencing artifact. Use of plasma-only ultrasensitive liquid biopsy approaches may allow for noninvasive inference of clonality and dynamically track changes in tumor burden. We previously developed MRD-EDGE, a tumor-informed machine learning classifier for ultrasensitive liquid biopsy monitoring of single nucleotide variants (SNVs) and copy number variants (CNVs) using standard plasma whole genome sequencing. For SNVs, MRD- EDGE uses a novel machine learning framework to classify individual cell free DNA (cfDNA) fragments as circulating tumor DNA or cfDNA sequencing artifact. We demonstrated the potential of plasma-only MRD-EDGE to identify SNVs in advanced melanoma and monitor tumor burden throughout treatment with immune checkpoint inhibiton. In tumor-informed settings, MRD-EDGE was used to identify minimal residual disease at tumor fractions (TFs) of 1:100,000 and below. Accurate SNV classification is a function of classifier performance and background error rate. To reduce error rates, we combined MRD-EDGE SNV with paired plus- minus sequencing (ppmSeq) from Ultima Genomics. ppmSeq is a PCR-free approach that leverages the hydrogen bonds of complementary DNA to carry matched native strands directly into sequencing, enabling scalable duplex sequencing. Use of MRD-EDGE SNV together with ppmSeq enables ultrasensitive tracking of early-stage non-small cell lung cancer throughout neoadjuvant immunotherapy. Plasma-only MRD-EDGE is therefore poised to enable dynamic monitoring of tumor burden and clonal composition outside the scope of tumor-informed approaches, including the comparison of SNV composition in cancer recurrence with preoperative disease. Citation Format: Adam Widman, Alexandre P. Cheng, John Zinno, Srinivas Rajagopalan, Ashish Saxena, Nasser Altorki, Dan A. Landau. Plasma-only ultrasensitive liquid biopsy to monitor tumor burden and clonal evolution [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr IA021.

Abstract B058: Novel machine learning lung cancer classifier shows significant correlation with cancer-specific fragmentomics features

Abstract Lung cancer is the second most prevalent cancer, and the leading cause of cancer-related deaths, in the US. Since the survival rate of patients diagnosed with lung cancer at earlier stages is dramatically higher than those diagnosed at later stages, technologies that shift lung cancer diagnosis to an earlier stage would be expected to improve survival rates. Fragmentomics, the study of short circulating cell-free DNA (cfDNA) fragments in the blood, is an emerging field in cancer diagnostics that has the potential to catalyze such a shift. Studies have shown that fragmentomics features, such as fragment sizes and end motifs, can be used to discriminate normal cfDNA from circulating tumor DNA (ctDNA) generated through tumor necrosis and apoptosis. Using this knowledge, machine learning tools, trained to identify ctDNA-specific features, are being leveraged in novel liquid biopsy assays to improve early-stage lung cancer detection. To create a machine learning classifier that detects discrete signals of ctDNA in individuals with lung cancer, Genece Health utilized low pass (∼3x coverage) whole genome sequencing (Illumina) of plasma extracted cfDNA from >400 lung cancer samples and >1,000 negative controls. This data was used to generate our novel FEMS (Fragment End Motifs and Sizes) dataframe, containing >30,000 features, by combining fragment lengths with their corresponding 5’ 4bp end motifs. The FEMS dataframe was then used to train a neural network machine learning classifier. To evaluate the performance of our machine learning classifier, we investigated whether the classifier scores correlated with well-known hallmarks of ctDNA. First, consistent with published ctDNA characteristics, we observed significant (p<0.01) enrichment of fragment sizes ≤167bp in lung cancer samples. Concordantly, our classifier scores are significantly correlated with this fragment size enrichment. Also, both fragment size enrichment and our classifier scores are correlated with lung cancer stage, with higher enrichment and higher scores observed in later stages. Next, we show that our classifier scores are correlated with specific end motif enrichments or depletions in lung cancer samples. For example, in lung cancer samples, CCCA end motifs were significantly enriched (p<0.01) in fragment sizes 120-140bp (max at 128bp), while significantly depleted in fragment sizes 190-210bp (min at 204bp). Once again, our classifier scores were significantly correlated with both the enrichment of this end motif in short fragments and its depletion in long fragments. Last, we assessed the classifier’s performance in an independent cohort (46 lung cancer and 132 non-cancer samples) and show 89.2% sensitivity with 90.4% specificity (auROC=0.957). The correlation observed between our classifier scores and published ctDNA characteristics, combined with the strong performance in an independent cohort, suggests that Genece’s novel machine learning classifier is effectively leveraging ctDNA-specific fragmentomics features for the identification of lung cancer in patient samples. Citation Format: Carlos Guzman, Michael L Salmans, Mengchi Wang, Byung In Lee, Andrew R Carson. Novel machine learning lung cancer classifier shows significant correlation with cancer-specific fragmentomics features [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B058.

Abstract A050: Early detection of liver cancer from diverse populations using cfDNA fragmentome and protein biomarkers

Abstract Hepatocellular carcinoma (HCC) is a leading cause of cancer death world-wide. In the US, liver cancer has increased in incidence and mortality due to a growing population from South and Central America, which faces higher risk of disease in part due to aflatoxin exposure. Recently, we showed that the DELFI (DNA evaluation of fragments for early interception) approach using genome-wide cell free DNA (cfDNA) fragmentation profiles and machine learning can be used for detection of liver and other cancers. Having previously demonstrated that a DELFI classifier accurately detects HCC in populations from the US and Hong Kong, we evaluated the classifier in other clinically relevant cohorts worldwide. Here we show that approach generalizes to diverse populations, and that including other genomic and protein features from the same blood draw improves performance. We examined plasma samples from 377 individuals, including 244 individuals with HCC and 133 without cancer, including 85 with cirrhosis. Plasma samples were collected from individuals with or without HCC in a case-control study in Guatemala (n=203) and from a prospective collection in Romania (n=174) and cfDNA was analyzed by whole- genome sequencing at ∼10x coverage. The median DELFI scores using a locked classifier (Foda et al., Cancer Discovery, 2023) were higher in both cohorts for patients with cancer across all stages compared to individuals without cancer, regardless of the presence of cirrhosis. Using the locked model with a threshold that corresponded to 80% specificity in prior work, DELFI detected individuals with HCC with sensitivities of 90% and 69% in the two cohorts at specificities of 92% and 86%, respectively. For early-stage HCC within Milan Criteria for liver transplantation, sensitivities were 85% in the case-control cohort and 64% in the prospective cohort. In these cohorts, the fixed DELFI model outperformed AFP at the clinically used threshold of 20 ng/mL with a sensitivity in the combined cohorts of 78% at 91% specificity, compared to 63% sensitivity at 91% specificity for AFP. A combined approach using either DELFI at a threshold that corresponded to a 90% specificity in our previous study or AFP at the clinical threshold resulted in 82% sensitivity (74% in early stage) at 92% specificity and was superior to estimates of AFP and ultrasound for early-stage disease (63% sensitivity at 84% specificity). Individuals who tested positive with DELFI had a significantly shorter overall survival (p=0.002, log rank test), even amongst individuals at the earliest stage, while AFP alone did not stratify survival for patients with early-stage disease. Single-molecule analyses from low coverage WGS of cfDNA revealed genome-wide mutational profiles that were similar to those of HCC and in individuals from Guatemala that were characteristic of aflatoxin exposure. Overall, this work provides insight into the origins of cfDNA in populations at risk for HCC and validates our genome-wide fragmentome approach for non-invasive cancer detection that may facilitate liver cancer screening. Citation Format: Zachariah H Foda, Daniel Bruhm C Bruhm, Akshaya V Annapragada, Shashikant Koul, Sarah Short, Keerti Boyapati, Adrianna Bartolomucci, Vilmos Adleff, Nicholas A Vulpescu, Hope Orjuela, Andrei Sorop, Razvan Iacob, Liana Gheorghe, Simona Dima, Katherine A McGlynn, Manuel Ramírez-Zea, Jillian Phallen, John Groopman, Robert B Sharpf, Victor E Velculescu. Early detection of liver cancer from diverse populations using cfDNA fragmentome and protein biomarkers [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr A050.

Preclinical delayed toxicity studies of BCMA CAR T-cell injection in B-NDG mice with multiple myeloma

PurposeBased on the efficacy data from the previous study of B-cell maturation antigen (BCMA) chimeric antigen receptor (CAR) T-cell injection, we further examined the delayed toxicity for 8 weeks after a single dose of BCMA CAR T-cell injection to observe possible toxic reactions.MethodsB-NDG mice transplanted with multiple myeloma (MM) cells were given a single dose of BCMA CAR T-cell injection at two dosages or human normal T cells and then subjected to examinations including clinical signs, weight and food intake measurements, haematology, blood biochemical analysis, cytokine assay, T-lymphocyte subpopulation quantification and histopathology on days 28 and 56 after dosing. In addition, quantitative polymerase chain reaction (qPCR) was used to quantify DNA fragments in different tissues to assess the tissue distribution of CAR and provide a basis for its preclinical safety evaluation and clinical dosing.ResultsIn the delayed toxicity study, no mortality or significant toxic effects such as reductions in food intake, body weight, relevant biochemical parameters and target organ weights were observed in the BCMA CAR T-cell-treated groups. Compared to the model group, restorative changes in clinical signs and clinicopathology indicating therapeutic effects were seen in the BCMA CAR T-cell-treated groups. Human-derived cytokines interleukin-2 (IL-2), IL-4, IL-6, IL-12, IL-10, tumor necrosis factor α (TNF-α), and interferon-γ (IFN-γ) could be detected in all cancer cell–bearing mice by cytokine level measurement. IFN-γ levels showed a geometric increase due to the graft versus host disease (GVHD) response induced in the mice, while the levels of the other cytokines did not show significant changes. Histopathological examination indicated that the BCMA CAR T-cell treatment groups showed mixed cellular infiltration of human-derived T cells, cancer cells, and inflammatory cells in several target organs including the liver, spleen, lung, and kidney, and some of them showed mild tissue damage, but the number of the animals and the severity of damage were significantly less than those of the T-cell control group as well as the model group. The results of the tissue distribution study showed that BCMA CAR T cells were mainly concentrated in the kidney, lung, bone marrow and the related immune organs/tissues, and the distribution of BCMA CAR T cells was highly consistent with that of MM cells, suggesting that BCMA CAR T cells could follow the cancer cells during metastatic targeting of the tissues.ConclusionsThe present study demonstrated a low toxicity of BCMA CAR T-cell injection, with manageable side effects and good anticancer activity and without observable adverse effects. This study provides data to support future clinical studies of BCMA CAR T-cell injection for MM.

Whole genome sequencing of CRISPR/Cas9-engineered NF-κB reporter mice for validation and variant discovery.

Targeted knockout, mutations, or knock-in of genomic DNA fragments in model organisms have been used widely for functional and cell-tracking studies. The desired genetic perturbation is often accomplished by recombination-based or CRISPR/Cas9-based genome engineering. For validating the intended genetic modification, a local region surrounding the targeted locus is typically examined based on enzymatic cleavage and consequent length patterns, e.g. in a Southern analysis. Despite its wide use, this approach is open to incomplete and ambiguous readouts. With decreasing costs of high-throughput sequencing, it is becoming feasible to consider a large-scale validation of a new strain after a targeted genetic perturbation. Here we describe a dataset of whole-genome sequences and the variant analysis results from four novel reporter mouse strains. This served to validate the strains and identified all the off-target effects on the genome, thereby increasing the genetic diversity of genomic sequences over those represented in the public databases for inbred mice.

Abstract B067: Dynamic chromatin landscapes of colorectal cancer development and cell-free DNA fragmentation

Abstract This abstract is being presented as a short talk in the scientific program. A full abstract is printed in the Proffered Abstracts section (PR016) of the Conference Program/Proceedings. Citation Format: Nicholas A. Vulpescu, Zachariah H. Foda, Pieter H.A. Wisse, Christopher Cherry, Jaime E. Medina, Vilmos Adleff, Remond J.A. Fijneman, Robert B. Scharpf, Gerrit A. Meijer, Beatriz Carvalho, Victor E. Velculescu. Dynamic chromatin landscapes of colorectal cancer development and cell-free DNA fragmentation [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B067.

Abstract A014: A methylation state specific targeted background depletion technique for enrichment of ctDNA fraction

Abstract Liquid biopsy continues to be a focus of the cancer diagnostics industry, primarily due to the non-invasive nature of sample collection, however the low levels of circulating tumor DNA (ctDNA) remain a challenge. Methylation has emerged as a promising biomarker for detecting ctDNA, yet detecting the cancerous signal in an excess of non-cancerous, unmethylated cfDNA in the background has been proven difficult. Harbinger Health has developed a novel method that depletes unmethylated background at the CpG-level from specific genomic regions of interest, resulting in an enrichment of the ctDNA fraction. We developed a background cfDNA depletion method that utilizes the endonuclease activity and the specificity of CRISPR/Cas12a to remove unmethylated DNA fragments at ctDNA methylation biomarker sites. First, we identified cancer-informative regions that showed consistent contiguous elevated methylation states in cancer compared to normal samples. We then designed guide RNAs that specifically bind and cut unmethylated CpG sites within the target regions. Cas depletion of bisulfite-converted DNA enriches cancer informative signal for bioanalysis. To test validity of our Cas complex designs, we created model samples that mimic fully unmethylated and fully methylated species. We spiked these cfDNA models into a background of genomic DNA from 5% to 0.01%. In triplicate, we examined cutting efficiency, multiplexing and specificity of Cas to unmethylated species of model DNA. Results were assessed using qPCR by comparing differences in Ct with and without Cas treatment. Additionally, we applied this depletion step during our library preparation process to show utility in methylation analysis of low tumor content liquid biopsy samples. Using both the model sample dilution series and bisulfite converted cfDNA samples, which represent a range of cancerous and background methylation signal, we deplete unmethylated targets using Cas prior to indexing PCR. This rendered unmethylated targets non-amplifiable, removing them from analysis. Results were assessed using both qPCR and sequencing data, such as methylated read counts over the target region. We demonstrated our analytical approach efficiently depletes non-cancer cfDNA by on average 9-fold, which increases the fraction of ctDNA signal and can be multiplexed. This background signal depletion driven by CRISPR is sensitive and specific, maintaining methylated DNA signal detection down to 0.01% at inputs of 10ng DNA. Our Cas-mediated depletion of background signal method has proven useful for enriching rare methylated fragments over background by improving the signal to noise ratio. This technique is novel by harnessing the specificity of CRISPR to target DNA in both a sequence and methylation state specific manner. The depletion of precise methylation states at the CpG-level make it suitable for use in multiple bioassays. Citation Format: Caitlin Gilley, Miguel Williams, Emily Neaga, Sarah Falotico, Kade Pettie, Anthony Shuber. A methylation state specific targeted background depletion technique for enrichment of ctDNA fraction [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr A014.

Abstract A035: A real-time PCR method for the detection of cancer-specific methylation patterns in cfDNA

Abstract Non-invasive liquid biopsy tests are proving to be the next frontier in cancer diagnostics with methylation emerging as a reliable biomarker for low levels of circulating tumor DNA (ctDNA). There is a rising interest in sensitive, low-cost liquid biopsy assays to detect low copies of hypermethylated ctDNA in an excess background of non-cancer-associated hypomethylated cell- free DNA (cfDNA). Real-time quantitative methylation-specific PCR (qMSP) allows for the detection of low abundance methylated fragments. qMSP approaches have previously been developed but are predominantly designed to target a specific CpG site. To date we are not aware of any qMSP approaches that target pan-cancer-associated methylation patterns across multiple CpG sites. Harbinger Health has developed a qMSP method with locked nucleic acid (LNA) blockers that target methylation haplotypes, allowing for multiplex enrichment and quantification of cancer-specific methylation patterns. Using targeted bisulfite sequencing, we identified ten pan-cancer-informative CpG-dense regions which showed consistent contiguous elevated methylation states in cancer cfDNA and low levels of methylation in non-cancer cfDNA. We designed qMSP assays for these regions and LNA blockers which bind to unmethylated target CpG sites, outcompeting the hydrolysis probe through a high Tm differential. This prevented non-specific probe hybridization. The qMSP-LNA assays were evaluated in simplex and multiplex using cell line DNA in a titration of hypermethylated “ctDNA” spiked into hypomethylated “cfDNA” to simulate varying ctDNA levels, and then validated with cancer and non-cancer cfDNA samples at 5 ng input, equivalent to 1450 haploid copies. The percentage of methylated DNA was estimated by the ratio of methylated copies (qMSP-LNA) to total copies (internal reference), which were quantified by standard curves. The qMSP-LNA assays detected low abundance methylated DNA fragments down to 23 target copies. LNA blockers completely depleted background signal originating from unmethylated DNA with high specificity, showing no inhibition of methylated DNA detection. When tested in cfDNA samples which varied in conversion efficiency, discordant methylation states, and methylation abundance, the assays reproducibly amplified and detected highly methylated fragments which correspond to cancer signal. Harbinger Health has developed qMSP-LNA assays for contiguous CpG biomarkers which differentiate cancer and non-cancer samples from only ten pan-cancer-informative regions. The qMSP-LNA method detected low abundance fragments with specific methylation patterns with high specificity and sensitivity. The assay reproducibly detected methylated DNA in cfDNA samples that represent a clinically relevant range of methylation signal and will be further validated in a larger cohort of cancer and non-cancer cfDNA samples. Due to the high specificity and sensitivity, this cost-effective PCR method may provide utility and improve access for early cancer detection and monitoring. Citation Format: Emily Neaga, Caitlin Gilley, Sarah Falotico, Mayur Gurnani, Zhenyu Zhang, Jocelyn Charlton, Miguel Williams, Anthony Shuber. A real-time PCR method for the detection of cancer-specific methylation patterns in cfDNA [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr A035.

Abstract PR016: Dynamic chromatin landscapes of colorectal cancer development and cell-free DNA fragmentation

Abstract The stepwise progression of colorectal cancer (CRC) from healthy epithelium, to premalignant adenoma, to cancer is accompanied by genome-wide epigenetic reprogramming which may be reflected in circulating cell-free DNA (cfDNA). However, current analyses of these processes have been hampered by complex mixtures of cells in normal, adenoma and cancer tissue samples, as well as absence of suitable adenoma model systems. Cultured colorectal organoids, comprised of pure epithelial cells, could enable insights on the epigenetic changes leading to progression from healthy tissue to cancer. Such features could be instrumental in the early cancer detection using genome-wide analyses of cfDNA fragmentation. Using 43 patient-derived colorectal organoids derived from healthy, adenoma, and cancer tissues, as well as 10 freshly collected peripheral blood mononuclear cell (PBMC) control samples, we examined the chromatin landscape of tumor progression using transposase accessible chromatin analyses with next-generation sequencing. We defined a consensus set of nucleosome depleted regions for each disease state and identified loci with differential accessibility between PBMCs, colon healthy, colon adenoma, and colon cancer tissues. We analyzed these differential loci for fragmentation characteristics in the circulating cfDNA of 250 healthy individuals and 51 patients with metastatic CRC. Across all organoid samples, we identified >35 million nucleosome depleted regions that we coalesced into a consensus set of 62,708 regions. As 78% of these regions could be linked to genes, we assessed whether these signatures identify known pathways involved in colorectal cancer. Within these regions, we identified unique colon tumor-related signatures comprising genes of known and novel pathways, including those involved in WNT, hippo, and RAS signaling. While the majority of chromatin accessibility differences were shared between adenomas and cancers, we identified 895 chromatin changes in adenomas that were not present in either healthy or malignant tissues. In healthy individuals, we found that the cfDNA coverage was negatively correlated with accessibility of white blood cell accessibility loci (Spearman ρ= - 0.60) while in individuals with cancer, changes in chromatin accessibility were associated with independent circulating tumor DNA abundance by droplet digital PCR (R2=0.69, p<0.001). Chromatin accessibility profiles were correlated with genome-wide cell-free DNA fragmentation features and could be used to distinguish healthy individuals from those with colorectal cancer (AUC=0.97). These analyses are consistent with dynamic chromatin remodeling during colorectal tumor development and may provide an avenue for evaluating these through genome-wide analyses of cfDNA fragmentation. Citation Format: Nicholas A. Vulpescu, Zachariah H. Foda, Pieter H.A. Wisse, Christopher Cherry, Jaime E. Medina, Vilmos Adleff, Remond J.A. Fijneman, Robert B. Scharpf, Gerrit A. Meijer, Beatriz Carvalho, Victor E. Velculescu. Dynamic chromatin landscapes of colorectal cancer development and cell-free DNA fragmentation [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr PR016.

Abstract PR020: A novel framework for epigenome-dependent multimodal fragment-signature analysis reveals insights into cell-free DNA generation in cancer

Abstract Background: The genome-wide pattern of cell-free DNA (cfDNA) is influenced by fragmentation enzymes, nucleosome occupancy, and epigenetic factors, as well as cell death mechanisms. Better modeling of these factors and their interactions will be essential for more sensitive detection of tumor-specific features and tissue-of-origin. Methods: To obtain mechanistic insights into cfDNA fragmentation, we developed a fragmentomics signature analysis framework. Our fragmenTopics algorithm (i) decomposes contributions of different fragment lengths and end-motif signatures using topic modeling and (ii) learns the dependencies of signature rates on the epigenome. The second component utilizes gradient boosting, enabling the modeling of non-linear dependencies and feature interactions. Both large-scale features, such as histone marks and DNase activity, and meso-scale features, such as transcription start sites (TSSs), nucleosome positions, and secondary DNA structures, are included in the model. Results: Using de novo signature discovery from 726 samples across five datasets, we built a comprehensive catalog of fragment length and end-motif signatures and studied determinants of their activity across the genome. The most common length and end-motif signatures reflected the mononucleosomal fragmentation by DNASE1L3. These signatures, as well as the dinucleotide length signature and motif signatures associated with known motifs of DNase enzymes, such as DFFB, showed lower abundance in cancer and further decreased with increasing tumor fraction. Instead, cancer samples manifested a higher diversity of processes, many of which are of unknown origin. Notably, two cancer-enriched length signatures were, on average, 20 bp shorter fragments with respect to mono- and di-nucleosome peaks. These signatures correlated with H3K4me1 and the compartment eigenvector, and may be linked to tighter nucleosome wrapping in euchromatin. Two cancer-enriched signatures (190-240 bp and 240-300 bp) had higher rates in TSSs; in addition to the two tight mono- and di-nucleosomal signatures, which were also enriched. Cancer-enriched end-motifs were A/T-rich, and these did not correspond to known DNase motifs. The increased diversity in end-motifs may be due to non-apoptotic cell death or tissue- or cancer-specific activity of less-studied cleavage enzymes; our results on their epigenome correlations can inform further investigations into their etiology. Conclusion: Our signature-based fragmentomics framework, which decouples the contributions of distinct processes while identifying the epigenomic determinants of their genome-wide rates, can improve our understanding of cell-free DNA fragmentation in cancer. Citation Format: Yoo-Na Kim, Sangmi Lee, Allen Lynch, Tae Hee Kim, Peter J Park, Doga Gulhan. A novel framework for epigenome-dependent multimodal fragment-signature analysis reveals insights into cell-free DNA generation in cancer [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr PR020.

Abstract B063: DiMMER: A robust computational pipeline for differential methylation marker evaluation in R of cell-free DNA fragments

Abstract Background: Decoding the origins of cell-free DNA (cfDNA) released from dying cells in a liquid biopsy sample offers the potential to provide insight into the dynamic, organism-wide changes reflective of health and disease, making cfDNA an ideal target for serial, minimally invasive monitoring of disease-related changes. To this end, cell-type specific DNA methylation patterns offer a promising target to facilitate tissue of origin analysis, yet limited methods exist to identify differentially methylated regions that distinguish cell-types. Methods: We develop a robust differentially methylated marker region identification pipeline, DiMMER, that leverages cfDNA fragment level information of neighboring, co-regulated CpG sites on methylome-wide sequencing reads. Compared to prior methods that utilize simple heuristics in one-vs-all average methylation rate comparisons, we implement an individual pairwise statistical test procedure across all cell-types or groups under consideration. We assess the cell-specific nature of identified differentially methylated marker regions by generating in-silico mixtures from known cell-type of origin at each region, and calculating the area under the receiver operating characteristic curve (AUROC). We utilize our differentially methylated marker finding pipeline to identify melanocyte specific methylation marker regions and assess their functional role through annotations. We show these cell-specific regions are conserved in melanoma cell-lines and are distinct from the aberrant changes in a cancer context. Results: We identified the most cell-type specific differentially methylated marker regions across 24 distinct cell-type groups using our pipeline. Compared to a simpler one-vs-all heuristic, we demonstrate improved cell-type specificity evidenced by a higher AUROC on average. Using our pipeline we identified melanocyte-specific marker regions, which were commonly found in intronic and promoter regions of genes related to melanocyte development and differentiation. When comparing methylation patterns between melanocytes and melanoma cell-lines, we demonstrate melanocyte specific methylation marks are conserved through the transformation to malignant melanoma. Conclusion: As methylome-wide sequencing methods continue to rapidly develop and more cell-specific methylation data is generated, there is unmet need for more statistically robust differentially methylated marker finding tools. Here we present one such tool, DiMMER, and demonstrate the potential utility of identifying such regions to be used to assess organ-specific load as a measure of residual disease, as opposed to traditional circulating tumor DNA quanitification. Citation Format: Arthur P McDeed, Sidharth S Jain, Megan E McNamara, Amber Alley, Anton Wellstein, Jaeil Ahn. DiMMER: A robust computational pipeline for differential methylation marker evaluation in R of cell-free DNA fragments [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B063.

Abstract 4132149: Elevated Levels of Plasma Mitochondrial DNA Damage-Associated Molecular Patterns (DAMPS) in Humans and Dogs with Heart Failure and Reduced Ejection Fraction

Background: Heart failure (HF) with reduced ejection fraction (HFrEF) is associated with increased inflammatory response that contributes to progressive worsening of the HF state. Potential endogenous triggers of this process include damage-associated molecular patterns (DAMPs). DAMPs originate from within cells following tissue stress or injury and activate pattern recognition receptors of the immune system, triggering an inflammatory response. Mitochondria are the major cell organelles that release DAMPs into the circulation. Chronic HF is associated with multi-organ mitochondrial dysfunction and cell injury and death. Purpose: The present study sought to quantify differences in mitochondrial DNA (mtDNA) DAMPs in the setting of HFrEF in humans and dogs compared to normal humans and dogs. Methods: Plasma samples were obtained from 9 HFrEF patients with left ventricular ejection fraction (LVEF) ≤35% and 9 age-matched healthy subjects, and from 6 dogs with coronary microembolization-induced HF (LVEF ≤35%) and 6 normal dogs. DNA fragments were isolated from 1 ml of plasma using a commercially available kit. Quantitative PCR and specifically designed primers were used to measure the amount of DNA in plasma from COX1 (cytochrome c oxidase subunit 1), ND1 (NADH dehydrogenase subunit 1) and ND6 (NADH dehydrogenase subunit 6) using an Applied Biosystems 7500 Fast-PCR unit. The relative abundances of plasma mtDNA DAMPs were expressed as threshold cycles (C T ). Results: Compared to normal human subjects, mtDNA DAMPs levels of COX1 , ND1 and ND6 in plasma of HFrEF patients was 4-fold, 9-fold and 8-fold greater, respectively. Similarly, compared to normal dogs, mtDNA DAMPs levels of COX1 , ND1 and ND6 in plasma of HFrEF dogs was increased 48-fold, 12-fold and 4-fold, respectively. Conclusions: These findings indicate a marked increase of mtDNA DAMPs in plasma of humans and dogs with HFrEF. The increase of mtDNA DAMPs is consistent with the elevated systemic inflammatory state of HFrEF. The results underscore mitochondrial abnormalities as integral players in the progressive worsening of HFrEF.

Stabilization of a single-stranded DNA of adeno-associated virus by inverted terminal repeats.

Parvoviruses have evolved to possess a linear single-stranded DNA (ssDNA) genome ranging from 4 to 6.3kb. Adeno-associated virus (AAV), a member of the Parvoviridae family, contains approximately 5kb of linear ssDNA within its capsid. This ssDNA features two 145-base inverted terminal repeats (ITRs) positioned at each end. ITRs have a T-shaped hairpin secondary structure, which plays a crucial role in viral replication. To investigate the impact of ITRs on ssDNA stability, we conducted a DNA denaturation-reannealing assay in 10 mM magnesium acetate, 50 mM potassium acetate, and 20 mM Tris-acetate buffer at pH7.9. Conventional double-stranded DNA (dsDNA) fragments retain a reannealing capability of over 50% for sizes under 8.8kb, gradually losing this capability as sizes increase; however, dsDNA fragments in rAAV ranging from 0.7 to 6.3kb did not exhibit a reannealing profile. This suggests that the presence of ITRs at both ends hinders annealing between the complementary strands. These results indicate that ITR structures preferentially induce an ssDNA conformation less than 6.3kb in size, and that the stability of AAV ssDNA contributes to the viral life cycle, including processes such as infection, replication, and packaging. Considering the size of parvovirus genomes, it appears that their genomes require reversible flexibility in complementary DNA strands; simultaneously, this adaptability needs to be regulated by specific palindromic ITRs at both ends.

Abstract 4146302: NETosis Attenuating Nanoprobe Improves Survival after Cardiac Arrest

NETosis, the process of neutrophil cell death due to the formation and release of neutrophil extracellular traps (NETs) has been implicated in the pathogenesis of heart disease. NETs are composed of immunogenic DNA fragments and citrullinated histones. The role of NETosis in the context of cardiac arrest and resuscitation (CA/R) is however unknown. We previously reported the development of a Dextran-Thiazole Orange (DTO) nanoprobe, with nanomolar affinity for nucleic acids, that exerts acute anti-inflammatory effects and reduces ischemia-reperfusion injury in mice. We aimed here to determine whether the DTO nanoprobe would also bind to the nucleic acid in NETS, whether DTO could attenuate the intensity of NETosis, and whether this would improve outcomes and survival after cardiac arrest. C57Bl6 mice were arrested for 8 minutes before resuscitation. DTO or unmodified dextran (vehicle control) was injected at the time of resuscitation, and again 4 hours later (n=38 mice). Survival and neurological function were scored daily. Time-domain resolved (lifetime) and conventional fluorescence imaging was performed at 4 hours after resuscitation in 6 additional mice injected with DTO. NETosis was evaluated by protein blot in the hearts of cardiac arrest mice injected with DTO or control. DTO significantly (p<0.05) improved 10-day survival (Fig. A), mean survival (from 4 to 7 days, Fig. B), and neurological function (Fig. C) following CA/R. Lifetime imaging (Fig. D), but not conventional fluorescence imaging (Fig. E) revealed the presence of DTO in the injured heart, liver and kidneys. In the heart, DTO signal was significantly increased in CA/R compared to sham mice injected with DTO or CA/R mice injected with control dextran (Fig. F). Citrullinated H3 and HMGB-1 (High mobility group box 1, a chromatin protein) were both upregulated in CA/R, and were significantly attenuated by DTO injection (Fig. G-I). We show for the first time that NETosis plays a key role in cardiac arrest and resuscitation. DTO is capable of detecting NETosis as well as attenuating it, likely via a reduction in HMGB-1 activity. The modulation of NETosis may provide a new avenue to improve survival after cardiac arrest.