End Motif Research Articles

Abstract 6371: Deep learning algorithm for multi-cancer detection and classification using cf-WGS

Abstract Purpose: Several cell-free DNA (cf-DNA) features, such as genome-wide coverage, fragment size, and fragment end motif frequency, have shown their potentials for cancer detection. In this study, we developed two independent models, GC (gross chromatin), and FEMS (fragment end motif frequency and size). Each model uses images generated from genome-wide normalized sequencing coverage and cf-DNA fragment end motif frequencies according to the different cf-DNA size profiles. Then we integrated them into a single ensemble model to improve cancer detection and multi-cancer type classification accuracy. Methods: Low depth cf-WGS data was generated from 1,396 patients (stage I: 14.9%, stage II: 35.6%, stage III: 24.9%, stage IV: 24.2%, unknown: 0.4%) with breast (n=702), liver (n=213), esophageal (n=155), ovarian (n=151), pancreatic (n=85), lung (n=53), head and neck (n=16), biliary tract (n=15), and colon cancer (n=6) and 417 healthy individuals. Samples were randomly split into training, validation, and test set stratifying cancer type and stages. Cancer types with a small number of samples (<20) were excluded for multi-cancer type classification. Each model was trained using a convolutional neural network, then integrated into a single ensemble model by averaging the predicted probabilities calculated from each model. Results: For cancer detection, the ensemble model achieved sensitivities of 85.2% [95% confidence interval (CI): 71.8% to 94.5%], 74.9% (CI: 68.0% to 88.0%), 73.2% (CI: 66.7% to 85.9%) at a specificity of 95%, 98% and 99% and the AUC value of 0.97(CI: 0.95-0.99) in the test dataset. By the cancer stages, sensitivity was 62.8% (CI: 48.8% to 83.7%) in stage I, 66.3% (CI: 57.7% to 82.7%) in stage II, 85.9% (CI: 77.5% to 94.4%) in stage III, and 76.1% (CI: 63.4% to 87.3%) in stage IV at 99% specificity. For multi-cancer classification, the overall accuracy of 85.1% (CI: 80.4% to 89.3%) was achieved including 6 cancer types. Conclusions: Highly sensitive and accurate deep learning model for cancer detection and multi-cancer classification was generated by combining different types of cf-DNA features. This result provides the opportunity for general population multi-cancer screening using various cf-DNA features. Citation Format: Tae-Rim Lee, Jin Mo Ahn, Joo Hyuk Sohn, Sook Ryun Park, Min Hwan Kim, Gun Min Kim, Ki-Byung Song, Eunsung Jun, Dongryul Oh, Jeong-Won Lee, Joseph J Noh, Young Sik Park, Sun-Young Kong, Sang Myung Woo, Bo Hyun Kim, Eui Kyu Chie, Hyun-Cheol Kang, Youn Jin Choi, Ki-Won Song, Jeong-Sik Byeon, Junnam Lee, Dasom Kim, Chang-Seok Ki, Eunhae Cho. Deep learning algorithm for multi-cancer detection and classification using cf-WGS [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6371.

Abstract 5150: Multimodal analysis of plasma cell-free DNA methylome for sensitive multi-cancer detection

Abstract Introduction: Genomic scale copy number, methylation, and fragmentation aberrations are proven genetic and epigenetic biomarkers of circulating tumor DNA (ctDNA). We developed a novel cell-free DNA (cfDNA) methylome sequencing assay that allows for integrative analysis of these genomic features for sensitive detection of multiple types of cancer. Methods: Whole methylome sequencing (WMS) libraries were generated from enzymatically converted cfDNA. Low-pass (~2X) paired-end NGS sequencing was performed on WMS libraries and paired whole genome sequencing (WGS) libraries of unconverted cfDNA for technical comparison and analytical validation. For development of cancer detection models, we profiled the genome-wide methylation density (MD), fragment size index (FSI), fragment end motif (motif) and chromosome instability (CIN) based on WMS data from a discovery cohort of 352 healthy controls and 559 newly diagnosed cancer patients (45 breast, 105 colorectal, 44 esophageal, 79 gastric, 79 liver, 110 lung, 83 pancreatic, and 14 others), 34.5% of which were at stage I or II. Machine learning models, including KNN, SVM, LR, GBDT, and random forest were trained and tested for individual biomarker types, with a final ensemble classifier to integrate all biomarkers. Performance of the predictive model was confirmed on an independent validation cohort consisting of 145 healthy controls and 236 cancer patients (21 breast, 45 colorectal, 18 esophageal, 35 gastric, 34 liver, 47 lung, and 36 pancreatic), among which 31.8% were at early stages (I or II). Results: WMS and WGS data from 512 cfDNA samples showed high concordance in CIN (R=0.988, 95% CI: 0.986-0.990) and FSI (R=0.961, 0.954-0.967) profiles. On the independent validation cohort, the optimal model selected for each of individual genomic features achieved following area under the ROC curve (AUC) values for cancer detection: MD-KNN, 0.830 (0.789-0.870); FSI-SVM, 0.904 (0.874-0.933); motif-SVM, 0.943 (0.920-0.966); and CIN-PAscore, 0.812 (0.770-0.854). The ensemble classifier based on linear SVM outperformed individual biomarkers, with an AUC value of 0.952 (0.934-0.971), which translated to, at 95% specificity, detection sensitivity of 66.7% for breast, 77.8% for colorectal, 83.3% for esophageal, 62.9% for gastric, 82.4% for liver, 66.0% for lung, and 77.8% for pancreatic cancers. Noteworthily, the overall sensitivity on early-stage cancer was 74.7%. Conclusions: These results demonstrate the first proof of principle on the feasibility of integrating multiple genomic cancer markers on the same WMS technical platform. Low-pass WMS on plasma cfDNA from 10ml of blood with integrative multimodal analysis of methylation, fragmentation, and CNV profiles yields in satisfactory sensitivity and specificity for detection of multiple types of cancer, warranting a forthcoming prospective study to further assess its clinical performance in a larger cohort. Citation Format: Yulong Li, Fenglong Bie, Fengwei Tan, Tiancheng Han, Shunli Yang, Fang Lv, Peiyao Nie, Qi Zhang, Yuanyuan Hong, Zhijie Wang, Ji He, Weizhi Chen, Liang Zhao, Shugeng Gao. Multimodal analysis of plasma cell-free DNA methylome for sensitive multi-cancer detection [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5150.

Abstract 1912: A versatile computational pipeline for the preprocessing of cell-free DNA fragmentation data

Abstract Cell-free DNA (cfDNA) emerges as a promising liquid biopsy biomarker for cancer diagnosis and patient monitoring. Complementing mutation-based assays, cfDNA carries information about epigenetic modifications from decaying cells. This information is encoded in the shape of the cfDNA fragments. Specifically, fragments from cancer tend to be shorter than those originating from other adult cells, enabling a distinction between cancer patients and healthy individuals. Additional cfDNA features such as fragment end motifs and information on nucleosome positioning provide further insight into cancer biology. These cfDNA measures are typically inferred from low-pass whole genome sequencing and subsequent bioinformatics processing. A key bioinformatics step is the alignment of DNA sequencing reads to the reference genome, which critically depends on preprocessing steps such as read trimming and alignment filters. A good understanding of preprocessing settings is thus crucial to derive accurate information from cfDNA. We therefore investigated to what extent preprocessing choices affect cfDNA analysis. To this end, we have built a robust bioinformatics pipeline that evaluates a range of possible preprocessing settings. The pipeline is implemented in a bioinformatics workflow engine, enabling a scalable and reproducible workflow. We are currently evaluating the effect of preprocessing on global and regional fragmentation patterns, detection of nucleosome positioning and identification of fragment end motifs. The different preprocessing settings are also evaluated for their ability to distinguish cancer from control samples using cfDNA fragmentation information. We are benchmarking the pipeline using cfDNA datasets from multiple centres to ensure our findings are generalizable over different platforms and experimental procedures. Our investigations will allow us to build a versatile bioinformatics preprocessing pipeline for the analysis of cell-free DNA fragmentation data. Citation Format: Ivna Ivankovic, Zsolt Balázs, Todor Gitchev, Daniel Trejo Banos, Norbert Moldovan, Panagiotis Balermpas, Jonas Willmann, Nicolaus Andratschke, Florent Moulière, Michael Krauthammer. A versatile computational pipeline for the preprocessing of cell-free DNA fragmentation data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1912.

Cell-Free DNA Fragmentomics in Liquid Biopsy.

Cell-free DNA (cfDNA) in bodily fluids has rapidly transformed the development of noninvasive prenatal testing, cancer liquid biopsy, and transplantation monitoring. Plasma cfDNA consists of a mixture of molecules originating from various bodily tissues. The study of the fragmentation patterns of cfDNA, also referred to as ‘fragmentomics’, is now an actively pursued area of biomarker research. Clues that cfDNA fragmentation patterns might carry information concerning the tissue of origin of cfDNA molecules have come from works demonstrating that circulating fetal, tumor-derived, and transplanted liver-derived cfDNA molecules have a shorter size distribution than the background mainly of hematopoietic origin. More recently, an improved understanding of cfDNA fragmentation has provided many emerging fragmentomic markers, including fragment sizes, preferred ends, end motifs, single-stranded jagged ends, and nucleosomal footprints. The intrinsic biological link between activities of various DNA nucleases and characteristic fragmentations has been demonstrated. In this review, we focus on the biological properties of cell-free DNA unveiled recently and their potential clinical applications.

Refined characterization of circulating tumor DNA through biological feature integration

Circulating tumor DNA (ctDNA) in blood plasma is present at very low concentrations compared to cell-free DNA (cfDNA) of non-tumor origin. To enhance ctDNA detection, recent studies have been focused on understanding the non-random fragmentation pattern of cfDNA. These studies have investigated fragment sizes, genomic position of fragment end points, and fragment end motifs. Although these features have been described and shown to be aberrant in cancer patients, there is a lack of understanding of how the individual and integrated analysis of these features enrich ctDNA fraction and enhance ctDNA detection. Using whole genome sequencing and copy number analysis of plasma samples from 5 high grade serious ovarian cancer patients, we observed that (1) ctDNA is enriched not only in fragments shorter than mono-nucleosomes (~ 167 bp), but also in those shorter than di-nucleosomes (~ 240–330 bp) (28–159% enrichment). (2) fragments that start and end at the border or within the nucleosome core are enriched in ctDNA (5–46% enrichment). (3) certain DNA motifs conserved in regions 10 bp up- and down- stream of fragment ends (i.e. cleavage sites) could be used to detect tumor-derived fragments (10–44% enrichment). We further show that the integrated analysis of these three features resulted in a higher enrichment of ctDNA when compared to using fragment size alone (additional 7–25% enrichment after fragment size selection). We believe these genome wide features, which are independent of genetic mutational changes, could allow new ways to analyze and interpret cfDNA data, as significant aberrations of these features from a healthy state could improve its utility as a diagnostic biomarker.

Emerging frontiers of cell-free DNA fragmentomics

Analysis of cell-free DNA (cfDNA) in the blood has shown promise for monitoring a variety of biological processes. Plasma cfDNA is a mixture comprising DNA molecules released from various bodily tissues, mediated by characteristic DNA fragmentations occurring during cell death. Fragmentation of cfDNA is non-random and contains tissue-of-origin information, which has been demonstrated in circulating fetal, tumoral, and transplanted organ-derived cfDNA molecules. Many studies have elucidated a plurality of fragmentomic markers for noninvasive prenatal, cancer, and organ transplantation assessment, such as fragment sizes, fragment ends, end motifs, and nucleosome footprints. Recently, researchers have further revealed the large population of previously unidentified long cfDNA molecules (kilobases in size) in the plasma DNA pool. This review focuses on the emerging biological properties of cfDNA, together with a discussion on its potential clinical implications.

Single-molecule sequencing reveals a large population of long cell-free DNA molecules in maternal plasma

In the field of circulating cell-free DNA, most of the studies have focused on short DNA molecules (e.g., <500 bp). The existence of long cell-free DNA molecules has been poorly explored. In this study, we demonstrated that single-molecule real-time sequencing allowed us to detect and analyze a substantial proportion of long DNA molecules from both fetal and maternal sources in maternal plasma. Such molecules were beyond the size detection limits of short-read sequencing technologies. The proportions of long cell-free DNA molecules in maternal plasma over 500 bp were 15.5%, 19.8%, and 32.3% for the first, second, and third trimesters, respectively. The longest fetal-derived plasma DNA molecule observed was 23,635 bp. Long plasma DNA molecules demonstrated predominance of A or G 5' fragment ends. Pregnancies with preeclampsia demonstrated a reduction in long maternal plasma DNA molecules, reduced frequencies for selected 5' 4-mer end motifs ending with G or A, and increased frequencies for selected motifs ending with T or C. Finally, we have developed an approach that employs the analysis of methylation patterns of the series of CpG sites on a long DNA molecule for determining its tissue origin. This approach achieved an area under the curve of 0.88 in differentiating between fetal and maternal plasma DNA molecules, enabling the determination of maternal inheritance and recombination events in the fetal genome. This work opens up potential clinical utilities of long cell-free DNA analysis in maternal plasma including noninvasive prenatal testing of monogenic diseases and detection/monitoring of pregnancy-associated disorders such as preeclampsia.

451P Utility of circulating free DNA 5’-end motif profile in the prediction of pathological response after neoadjuvant chemoradiotherapy in patients with locally advanced rectal cancer

For locally advanced rectal cancer (LARC) patients who achieved complete clinical response (cCR) after neoadjuvant chemoradiotherapy (nCRT), a “Watch & Wait” (W&W) approach is adopted to improve quality of life. However, W&W may increase the recurrence risk of those who are not pathological complete response (non-pCR). Cell-free DNA (cfDNA) end motifs have been used in cancer detection. But its utility in predicting pCR status has not been reported. In this study, we explored the potential of cfDNA end motif profile in the prediction of pathological response in LARC patients.

Characterization of fragment sizes, copy number aberrations and 4-mer end motifs in cell-free DNA of hepatocellular carcinoma for enhanced liquid biopsy-based cancer detection.

Circulating cell‐free DNA (cfDNA) fragmentomics, which encompasses the measurement of cfDNA length and short nucleotide motifs at the ends of cfDNA molecules, is an emerging field for cancer diagnosis. The utilization of cfDNA fragmentomics for the diagnosis of patients with hepatocellular carcinoma (HCC) caused by hepatitis B virus (HBV) is currently limited. In this study, we utilized whole‐genome sequencing data of cfDNA in samples from patients with HCC (n = 197) and HBV (n = 187) to analyze the association of fragment size selection (< 150 bp) with tumor fraction (TF), copy number variation (CNV) alterations and the change in the proportion of 4‐mer end motifs in HCC and HBV samples. Our analyses identified five typical CNV markers (i.e. loss in chr1p, chr4q and chr8p, and gain in chr1q and chr8q) in cfDNA with a cumulatively positive rate of ˜ 95% in HCC samples. Size selection (< 150 bp) significantly enhanced TF and CNV signals in HCC samples. Additionally, three 4‐mer end motifs (CCCA, CCTG and CCAG) were identified as preferred end motifs in HCC samples. We identified 139 end motifs significantly associated with fragment size that showed similar patterns of associations between patients with HCC and HBV, suggesting that end motifs might be inherently coupled with fragment size by a ubiquitous mechanism. Here we conclude that CNV markers, fragment size selection and end‐motif pattern in cfDNA have potential for effective detection of patients with HCC.

Plasma DNA Profile Associated with DNASE1L3 Gene Mutations: Clinical Observations, Relationships to Nuclease Substrate Preference, and In Vivo Correction

SummaryPlasma DNA fragmentomics is an emerging area in cell-free DNA diagnostics and research. In murine models, it has been shown that the extracellular DNase, DNASE1L3, plays a role in the fragmentation of plasma DNA. In humans, DNASE1L3 deficiency causes familial monogenic systemic lupus erythematosus with childhood onset and anti-dsDNA reactivity. In this study, we found that human patients with DNASE1L3 disease-associated gene variations showed aberrations in size and a reduction of a “CC” end motif of plasma DNA. Furthermore, we demonstrated that DNA from DNASE1L3-digested cell nuclei showed a median length of 153 bp with CC motif frequencies resembling plasma DNA from healthy individuals. Adeno-associated virus-based transduction of Dnase1l3 into Dnase1l3-deficient mice restored the end motif profiles to those seen in the plasma DNA of wild-type mice. Our findings demonstrate that DNASE1L3 is an important player in the fragmentation of plasma DNA, which appears to act in a cell-extrinsic manner to regulate plasma DNA size and motif frequency.

Abstract IA01: Plasma DNA-based molecular diagnostics: Fragments, circles and beyond

Abstract My group has a longstanding interest in the diagnostic applications of cell-free DNA in plasma. For example, we have pioneered noninvasive prenatal testing (NIPT) and the use of plasma DNA for cancer screening. We believe that understanding the fundamental biology of circulating DNA is essential to further advance the field. In this regard, we have been particularly interested in the fragmentation patterns of cell-free DNA in plasma. We have shown that cell-free fetal DNA molecules in the plasma of pregnant women are shorter than those of maternal origin. The differential size profiles between circulating fetal and maternal DNA have enabled the use of plasma DNA size as an independent metric for NIPT. In the area of cancer liquid biopsy, we have used circulating Epstein-Barr virus (EBV) DNA as an example of tumor-derived DNA in plasma. Hence, circulating EBV DNA molecules are also short fragments of DNA. In another example, we have used hepatocellular carcinoma as a model system and have found that circulating tumor-derived DNA molecules have a shorter size profile than those of nontumoral origin. We are exploring enzymes that might be involved in the fragmentation of plasma DNA. We have shown that mice in which both copies of the Dnase1l3 gene have been knocked out have a larger size profile of circulating DNA. We have also developed a plasma DNA end motif metric to measure the effect of disruption of this nuclease system. In addition to the fragmentation of linear DNA in plasma, my group is also interested in exploring the presence of nonlinear DNA in plasma. Hence, we have used mitochondrial DNA (mtDNA) as a model system as mtDNA exists as a circular molecule inside mitochondria. Interestingly, we have observed the existence of both linear and circular mtDNA in plasma. Using liver and bone marrow transplantation models, we have shown that the circular form is predominantly of hematopoietic origin while the linear form is predominantly from the liver. Plasma mtDNA topologics thus holds information on the origin of circulating DNA. These studies therefore demonstrate some of the exciting findings that can be revealed through the study of plasma DNA fragmentomics and topologics. We believe that such new biologic understandings will drive new diagnostic applications. Citation Format: Yuk Ming Dennis Lo. Plasma DNA-based molecular diagnostics: Fragments, circles and beyond [abstract]. In: Proceedings of the AACR Special Conference on Advances in Liquid Biopsies; Jan 13-16, 2020; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(11_Suppl):Abstract nr IA01.

Plasma DNA End-Motif Profiling as a Fragmentomic Marker in Cancer, Pregnancy, and Transplantation.

Plasma DNA fragmentomics is an emerging area of research covering plasma DNA sizes, end points, and nucleosome footprints. In the present study, we found a significant increase in the diversity of plasma DNA end motifs in patients with hepatocellular carcinoma (HCC). Compared with patients without HCC, patients with HCC showed a preferential pattern of 4-mer end motifs. In particular, the abundance of plasma DNA motif CCCA was much lower in patients with HCC than in subjects without HCC. The aberrant end motifs were also observed in patients with other cancer types, including colorectal cancer, lung cancer, nasopharyngeal carcinoma, and head and neck squamous cell carcinoma. We further observed that the profile of plasma DNA end motifs originating from the same organ, such as the liver, placenta, and hematopoietic cells, generally clustered together. The profile of end motifs may therefore serve as a class of biomarkers for liquid biopsy in oncology, noninvasive prenatal testing, and transplantation monitoring. SIGNIFICANCE: Plasma DNA molecules originating from the liver, HCC and other cancers, placenta, and hematopoietic cells each harbor a set of characteristic plasma DNA end motifs. Such markers carry tissue-of-origin information and represent a new class of biomarkers in the nascent field of fragmentomics.This article is highlighted in the In This Issue feature, p. 627.

RNA Circularization Diminishes Immunogenicity and Can Extend Translation Duration InVivo.

Circular RNAs (circRNAs) are a class of single-stranded RNAs with a contiguous structure that have enhanced stability and a lack of end motifs necessary for interaction with various cellular proteins. Here, we show that unmodified exogenous circRNA is able to bypass cellular RNA sensors and thereby avoid provoking an immune response in RIG-I and Toll-like receptor (TLR) competent cells and in mice. The immunogenicity and protein expression stability of circRNA preparations are found to be dependent on purity, with small amounts of contaminating linear RNA leading to robust cellular immune responses. Unmodified circRNA is less immunogenic than unmodified linear mRNA invitro, in part due to theevasion of TLR sensing. Finally, we provide the first demonstration to our knowledge of exogenous circRNA delivery and translation invivo, and we show that circRNA translation is extended in adipose tissue in comparison to unmodified and uridine-modified linear mRNAs.

Dnase1l3 deletion causes aberrations in length and end-motif frequencies in plasma DNA

Circulating DNA in plasma consists of short DNA fragments. The biological processes generating such fragments are not well understood. DNASE1L3 is a secreted DNASE1-like nuclease capable of digesting DNA in chromatin, and its absence causes anti-DNA responses and autoimmunity in humans and mice. We found that the deletion of Dnase1l3 in mice resulted in aberrations in the fragmentation of plasma DNA. Such aberrations included an increase in short DNA molecules below 120 bp, which was positively correlated with anti-DNA antibody levels. We also observed an increase in long, multinucleosomal DNA molecules and decreased frequencies of the most common end motifs found in plasma DNA. These aberrations were independent of anti-DNA response, suggesting that they represented a primary effect of DNASE1L3 loss. Pregnant Dnase1l3-/- mice carrying Dnase1l3+/- fetuses showed a partial restoration of normal frequencies of plasma DNA end motifs, suggesting that DNASE1L3 from Dnase1l3-proficient fetuses could enter maternal systemic circulation and affect both fetal and maternal DNA fragmentation in a systemic as well as local manner. However, the observed shortening of circulating fetal DNA relative to maternal DNA was not affected by the deletion of Dnase1l3 Collectively, our findings demonstrate that DNASE1L3 plays a role in circulating plasma DNA homeostasis by enhancing fragmentation and influencing end-motif frequencies. These results support a distinct role of DNASE1L3 as a regulator of the physical form and availability of cell-free DNA and may have important implications for the mechanism whereby this enzyme prevents autoimmunity.

Shiga Toxin Subtypes and Virulence Genes in Escherichia coli Isolated from Cattle.

Subtypes of stx1 and stx2 in 45 Shiga toxin-producing Escherichia coli (STEC) strains isolated from cattle were investigated by PCR. Only subtype stx1a was detected among all the stx1-positive strains. The major stx2 subtype was stx2a followed by stx2d, stx2c, stx2b, and stx2g in decreasing order of frequency. stx2c was found in strains of serotypes O157 and O174. stx2d was found in 11 strains. These strains were confirmed by DNA sequencing to carry both the activatable tail and the END motif; all were eae-negative, and 3 contained stx2d as the only stx. stx2g was found in 2 strains in association with stx2a, estA1, and astA. In addition, 7 hybrid strains of shigatoxigenic and enterotoxigenic E. coli (STEC/ETEC) were found to harbor one or both of stx1a and stx2a (stx1a/stx2a) and estA1. Among 27 serotypes of STEC strains isolated from cattle, O157:H7 and O109:H- strains were eae-positive. Other putative adhesin genes, such as saa, iha, espP, and lpfAO113 were detected in more than 12 serotypes.

A supramolecular DNA self-assembly based on β-cyclodextrin–adamantane complexation as a bioorthogonal sticky end motif

We propose linear end-to-end assemblies of short DNA duplexes based on β-cyclodextrin-adamantane complexation. The assembled duplexes exhibited increased Tm values compared with those of the corresponding natural hybrids. Competition experiments with external guest molecules showed a substantial decrease in Tm of the terminal modified duplexes, suggesting the viability of inter-duplex complexation.

Next Generation Sequencing Spectratyping (NGS-S) Comprehensively Monitors T Cell Receptor Diversity in Children with T Cell Abnormalities

Abstract▪2173▪This icon denotes a clinically relevant abstractThe adaptive arm of the immune system - the T-cell compartment – may become compromised by inherited or acquired defects resulting in cancer, autoimmunity, or increased susceptibility to microbial infectious agents. A normal polyclonal T cell compartment comprises an estimated number of 2.5 × 10E7 individual T cell clones each expressing a unique antigen recognizing T cell receptor (TCR). The functionality of the T cell compartment is thus – at least partly - reflected by TCR sequence diversity. There is a medical need for rapid and robust diagnostic approaches that accurately monitor TCR diversity in patient samples, e.g. after bone marrow transplantation (BMT).Previously, complementarity determining region 3 (CDR3) size spectratyping in TCR β-chain subfamilies (Vβ), an immunoscopic technique, was employed for the analysis of T cell diversity. However, spectratyping is limited to the analysis of CDR3 length polymorphisms only. Underlying diversity of TCR Vβ sequences of equal length remain undetected. Furthermore, spectratyping is time consuming and consequently data can only be interpreted with a delay of weeks.To determine TCR diversity fast and accurately we developed next-generation-sequencing spectratyping (NGS-S), which employs high coverage, massive parallel Roche/454-sequencing of TCR Vβ-chain amplicons.Three different sample groups were analyzed in parallel by spectratyping and NGS-S: T cells from (1) healthy children (n=6), (2) children at diagnosis of severe aplastic anemia (n=7), and (3) children who underwent haploidentical BMT (n=7). In brief, RNA was extracted from bone marrow derived CD8+ cells and transcribed to cDNA. Amplicon libraries were generated by PCR employing two degenerated wobble primers (VP1, VP2), designed to cover most of the known TCR Vβ gene segments and a universal reverse primer (CP1) located in the conserved TCR region (Figure 1). The mean overall coverage of the CDR3 region achieved was 23.133 per patient. [Display omitted] For simultaneous characterization of these individual amplicons we generated the TCR Profiler (Figure 2). This new software tool automatically preprocessed raw sequencing data using a threshold quality value (q=30) to trim the 3’ end of the TCR β-chain sequences. Rearranged germline TCR Vβ and Jβ genes were identified by Smith-Waterman local alignment against each human TCR β-chain germline gene of the IMGT/GENE-DB reference directory. Base call reliability was assured by incorporating phred-like quality values provided by the sequencer into the Smith-Waterman local alignment routine. A quality value, q, was computed for each base as the log-transformation of the probability p of a base being incorrectly called, q = − 10 x log10(p). Transformed into a reliability measure, r = 1- (1/10^(q/10)), q-values indicated the probability for each base to be correctly called. CDR3 regions were delimited using specific flanking amino acid sequence motifs. The 5’ end motif varies dependently on the rearranged TCR Vβ gene and was identified using the IMGT/GENE-DB reference directory sequence set, whereas the 3’ end motif [W/F]GXG (IUPAC code) is conserved in all TCR β-chains. CDR3 length was calculated including all amino acids between the two motifs. Screening for in-frame stop codons was done to exclude non-functional TCR β-chain transcripts. [Display omitted] The TCR profiler identified on average 16165 of the input sequences as unique CDR3 sequences. Of these a mean of 9840 were predicted to be functionally rearranged.Whereas spectratyping gave a rough estimate of CDR3 size and allowed T cell deficient samples to be identified, NGS-S determined the exact length and sequence composition of the CDR3, identified the rearranged TCR Vβ and Jβ genes and the specific recombination (Figure 3A). [Display omitted] Utilization of specific genes, the resulting amino acid composition of the CDR3 region as well as its length and overall diversity were integrated into a novel NGS-S score.This score reliably differentiated not only between normal and T cell deficient samples, but also between the different T cell deficient groups (SAA and BMT) (Figure 3B). We conclude that NGS-S allows rapid and precise determination of TCR diversity in clinical samples. Disclosures:No relevant conflicts of interest to declare.

Synthesis of Biantennary Complex-Type Nonasaccharyl Asn Building Blocks for Solid-Phase Glycopeptide Synthesis

The biantennary complex-type N-glycans bearing LacNAc and LacdiNAc as the nonreducing end motif were synthesized in a protected form suitable to use in the Fmoc solid-phase peptide synthesis studies. Two approaches for the nonasaccharide synthesis were examined by taking advantage of the highly β-selective glycosylation with GlcNTCA (N-phenyl)trifluoroacetimidate. An earlier approach, which involved the reaction of the trisaccharide donor (Gal-GlcNTCA-Man) and trisaccharide acceptor (Man-GlcNPhth(2)-N(3)), produced a mixture of nonasaccharide isomers. On the other hand, mannosylation of the trisaccharide acceptor (Man-GlcNPhth(2)-N(3)) stereoselectively afforded the known pentasaccharide (Man(3)-GlcNPhth(2)-N(3)), which was reacted with the disaccharyl glycosyl donor (Gal-GlcNTCA or GalNTCA-GlcNTCA) to produce the desired nonasaccharide as a single stereoisomer. Selective dephthaloylation followed by N-acetylation furnished the GlcNAc(2) functionality. The resulting nonasaccharyl azides were condensed with Fmoc-Asp(OPfp)-OBu(t) or Fmoc-Asp(OPfp)-OPac in the presence of Ph(CH(3))(2)P and HOOBt. Finally, the Zn reduction and cleavage of the tert-butyl ester or Zn reduction alone produced the targeted nonasaccharyl Asn building blocks.

Mint-3 Regulates the Retrieval of the Internalized Membrane-type Matrix Metalloproteinase, MT5-MMP, to the Plasma Membrane by Binding to Its Carboxyl End Motif EWV

Membrane type matrix metalloproteinases (MT-MMPs) play a critical role in promoting cell growth and migration within the extracellular matrix by trafficking to specialized areas. Here we show that the carboxyl EWV motif of MT5-MMP serves as a retrieval signal for internalized MT5-MMP by interacting with Mint-3, a protein with two type III PDZ domains. Deletion of the EWV signal impairs the recycling of MT5-MMP without affecting its internalization, leading to decreased activity on the cell surface. A yeast two-hybrid screening identified Mint-3 as the EWV-binding protein. Mint-3 stimulates MT5-MMP activity when expressed at low levels in an EWV-dependent fashion, but inhibits its activity at higher levels independent of the EWV motif. siRNA-mediated knockdown of endogenous Mint-3 decreased MT5-MMP activity. Furthermore, Mint-3 significantly increased the level of MT5-MMP on the cell surface without affecting its synthesis and internalization. Therefore, Mints may be the adaptor proteins that regulate the trafficking of MT-MMPs.

Recombination signal sequence variations and the mechanism of patterned T-cell receptor-β locus rearrangement

Rearrangement of antigen receptor genes is controlled at multiple levels. One important regulation is achieved through variation in the recombination signals (RS) that flank the rearranging variable (V), diversity (D), and joining (J) gene segments. Several functional and biochemical studies have confirmed the importance of RS variations in gene rearrangement but very few molecular analyses has been reported with known, endogenous RS motifs. We have shown previously that rearrangement of the murine T-cell receptor (TCR)-B, D, and J genes follows a stereotypical pattern determined largely by the BJ genes and their flanking RS. Therefore, we studied the mechanism by which the endogenous BJ RS determine patterned gene rearrangement. We have compared the activity of three representative RS in transfection and in vitro DNA cleavage assays. Mutagenesis studies identified residues in various components of the RS and flanking coding ends that cooperate to determine the ultimate efficiency of recombination. Surprisingly, we find that changes in one component of the RS can be compensated by other elements to restore functional activity. DNA electrophoretic mobility shift assays (EMSA) show that a combinatorial effect of various higher order protein/RS complexes can, in part, control the efficiency of recombination. We propose that evolution of a patterned primary antigen receptor repertoire reflects the delicate interplay between various components of the RS and flanking coding end motifs resulting from the highly flexible interactions of the recombinase with its target DNA.