Search Results - EGA European Genome-Phenome Archive

Machine learning guided signal enrichment for ultrasensitive plasma tumor burden monitoring

In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS ctDNA single nucleotide variant (SNV) and copy number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by 300X compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, thereby expanding its applicability to a wider range of solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in tumor burden in response to neoadjuvant immunotherapy in non-small cell lung cancer (NSCLC) and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables de novo mutation calling in melanoma and small cell lung cancer (SCLC) without matched tumor, yielding clinically informative TF monitoring for patients on immune checkpoint inhibition (ICI).

Study EGAS00001007545

This study generated Oxford Nanopore long read sequencing data of cancer cell line mixtures for validating long-read variant calls in cancer genomics

Long-read sequencing (LRS) improves genome alignment and facilitates resolving variants in complex genomic regions, making it a promising approach for cancer variant detection and biomarker discovery. Here, we evaluate the performance of LRS to detect somatic variants across different tumour purities and sequencing depths by comparing to somatic variants from short-read sequencing. We generated experimental mixtures of cancer cell lines and matched normal cell lines to simulate 10 tumour purities (ranging from 0 to 100% tumour content). This resulted in 22 samples which were sequenced using whole genome LRS to a targeted depth of 60x and somatic variants were identified. We downsampled sequencing data to explore the optimal read depth for somatic variant detection. Our results show that long-read variant calling tools achieve recall rates comparable to short-read gold standards. While a tumour sequencing depth of 30x to 60× is generally sufficient for detecting common variants, particularly structural variants (SVs), sequencing the matched normal sample at adequate depth is crucial for accuracy. Notably, we found variants unique to LRS that may represent real and previously undetected events. This study highlights key factors for optimising cancer genome sequencing with LRS and provides a comprehensive dataset of cell line mixtures for future research and tool development.

Study EGAS00001008107

PD-L1 blockade immunotherapy rewires cancer-induced emergency myelopoiesis

Introduction Immune checkpoint blockade (ICB) immunotherapy has revolutionized cancer treatment, demonstrating exceptional clinical responses in a wide range of cancers. Despite the success, a significant proportion of patients still fail to respond, highlighting the existence of unappreciated mechanisms of immunotherapy resistance. Delineating such mechanisms is paramount to minimize immunotherapy failures and optimize the clinical benefit. Methods In this study, we treated tumour-bearing mice with PD-L1 blockage antibody (aPD-L1) immunotherapy, to investigate its effects on cancer-induced emergency myelopoiesis, focusing on bone marrow HSPCs. We examined the impact of aPD-L1 treatment on HSPC quiescence, proliferation, transcriptomic profile, and functionality. Results Herein, we reveal that aPD-L1 in tumour-bearing mice targets the hematopoietic stem and progenitor cells (HSPCs) in the bone marrow (ΒΜ), mediating their exit from quiescence and promoting their proliferation. Notably, disruption of the PDL1/PD1 axis induces transcriptomic reprogramming in HSPCs, observed in both individuals with Hodgkin lymphoma (HL) and tumour-bearing mice, shifting towards an inflammatory state. Furthermore, HSPCs from aPDL1-treated mice demonstrated resistance to cancer-induced emergency myelopoiesis, evidenced by a lower generation of MDSCs compared to control-treated mice. Discussion: Our findings shed light on unrecognized mechanisms of action of ICB immunotherapy in cancer, which involves targeting of BM-driven HSPCs and reprogramming of cancer-induced emergency myelopoiesis.

Study EGAS00001007873

WES of 2 human osteosarcoma and corresponding cell lines

Progress in the systemic control of osteosarcoma has been limited over the past decades thus indicating the urgent clinical need for the development of novel treatment strategies. Therefore, we have recently developed new preclinical models to study promising novel agents for the treatment of pediatric osteosarcoma. The checkpoint kinase (chk) inhibitor prexasertib (LY2606368) and its salt form (LSN2940930) have recently been shown to be active in adult and pediatric malignancies, including sarcoma. We have now tested the potency of prexasertib in clonogenic survival assays in two new lines of primary patient-derived osteosarcoma cells and in two established osteosarcoma cell lines as a single agent and in combination with cisplatin and the poly ADP-ribose polymerase (PARP) inhibitor talazoparib. Prexasertib alone results in strongly reduced clonogenic survival at low nanomolar concentrations and acts by affecting cell cycle progression, induction of apoptosis and induction of double-stranded DNA breakage at concentrations that are well below clinically tolerable and safe plasma concentrations. In combination with cisplatin and talazoparib, prexasertib acts in a synergistic fashion. Chk1 inhibition by prexasertib and its combination with the DNA damaging agent cisplatin and the PARP-inhibitor talazoparib thus emerges as a potential new treatment option for pediatric osteosarcoma which will now have to be tested in preclinical primary patient derived in vivo models and clinical studies.

Study EGAS00001003923

Double mutant DNMT3A AML: a unique subtype

Mutation of DNMT3A, encoding a de novo methyltransferase essential for cytosine methylation, is a common early event in clonal hematopoiesis (CH) and adult acute myeloid leukemia (AML). Spontaneous deamination of methylated cytosines damages DNA, which is repaired by the base excision repair (BER) enzymes MBD4 and TDG. Congenital MBD4-deficiency has been linked to early-onset CH and AML, and is marked by exceedingly high levels of DNA damage and mutation of DNMT3A. Strikingly, wildtype (WT) DNMT3A binds TDG, thereby potentiating its repair activity. Since TDG is the only remaining BER enzyme in MBD4-deficient AML patients capable of repairing methylation damage, we investigated whether mutant DNMT3A negatively affects the repair function of TDG. We found that, whereas WT DNMT3A stimulates TDG function, mutant DNMT3A impairs TDG-mediated repair of DNA damage in vitro. In light of this finding and to extrapolate our observations to the broader AML patient population, we investigate here the genetic profiles and survival outcomes of AML patients with single (SM) versus double mutant (DM) DNMT3A. DM DNMT3A AML patients show a characteristic driver mutation landscape and reduced overall survival when compared to SM DNMT3A AML patients. Importantly, whole-genome sequencing showed a trend for increased DNA damage in primary DM DNMT3A AML samples, especially when DNMT3A mutations are located at the DNMT3A-TDG interaction interface.

Study EGAS00001007966

deep-learning-powered tissue deconvolution for cfDNA

Plasma cell-free DNA (cfDNA) is a noninvasive biomarker for cell death of all organs. Deciphering the tissue origin of cfDNA can reveal abnormal cell death because of diseases, which has great clinical potential in disease detection and monitoring. Despite the great promise, the sensitive and accurate quantification of tissue-derived cfDNA remains challenging to existing methods due to the limited characterization of tissue methylation and the reliance on unsupervised methods. To fully exploit the clinical potential of tissue-derived cfDNA, here we present one of the largest comprehensive and high-resolution methylation atlas based on 521 noncancer tissue samples spanning 29 major types of human tissues. We systematically identified fragment-level tissue-specific methylation patterns and extensively validated them in orthogonal datasets. Based on the rich tissue methylation atlas, we develop the first supervised tissue deconvolution approach, a deep-learning-powered model, cfSort, for sensitive and accurate tissue deconvolution in cfDNA. On the benchmarking data, cfSort showed superior sensitivity and accuracy compared to the existing methods. We further demonstrated the clinical utilities of cfSort with two potential applications: aiding disease diagnosis and monitoring treatment side effects. The tissue-derived cfDNA fraction estimated from cfSort reflected the clinical outcomes of the patients. In summary, the tissue methylation atlas and cfSort enhanced the performance of tissue deconvolution in cfDNA, thus facilitating cfDNA-based disease detection and longitudinal treatment monitoring.

Study EGAS00001007213

Spatial concordance of DNA methylation classification in diffuse glioma

Background: Intratumoral heterogeneity is a hallmark of diffuse gliomas. DNA methylation profiling is an emerging approach in the clinical classification of brain tumors. The goal of this study is to investigate the effects of intratumoral heterogeneity on classification confidence. Methods: We used neuronavigation to acquire 133 image-guided and spatially-separated stereotactic biopsy samples from 16 adult patients with a diffuse glioma (7 IDH-wildtype and 2 IDH-mutant glioblastoma, 6 diffuse astrocytoma, IDH-mutant and 1 oligodendroglioma, IDH-mutant and 1p19q codeleted), which we characterized using DNA methylation arrays. Samples were obtained from regions with and without abnormalities on contrast enhanced T1 weighted and fluid-attenuated inversion recovery MRI. Methylation profiles were analyzed to devise a three-dimensional reconstruction of (epi)genetic heterogeneity. Tumor purity was assessed from clonal methylation sites. Results: Molecular aberrations indicated that tumor was found outside imaging abnormalities, underlining the infiltrative nature of this tumor and the limitations of current routine imaging modalities. We demonstrate that tumor purity is highly variable between samples and explains a substantial part of apparent epigenetic spatial heterogeneity. We observed that DNA methylation subtypes are often, but not always, conserved in space taking tumor purity and prediction accuracy into account. Conclusion: Our results underscore the infiltrative nature of diffuse gliomas and suggest that DNA methylation subtypes are relatively concordant in this tumor type, although some heterogeneity exists.

Study EGAS00001005434

Unraveling the transcriptomic profile of utero-tubal lavage fluid of ovarian cancer patients

The majority of ovarian cancers are diagnosed at an advanced stage and have a high mortality rate. Current screening strategies fail to improve prognosis because markers of early stage disease are lacking. This medical need justifies the search for biomarkers enabling early detection of ovarian cancer. In this study, we explore the extracellular transcriptome of utero-tubal lavage fluid obtained from 26 ovarian cancer patients and 48 controls using messenger RNA (mRNA) capture and small RNA sequencing. Because of its contact with the fallopian tube and the ovaries, collection of utero-tubal lavage might be the preferred non-invasive method to identify localized lesions compared with analyses based on peripheral blood samples. We observed an enrichment of ovarian and fallopian tube specific messenger RNAs in utero-tubal lavage fluid compared to other human biofluids. Over 300 mRNAs and 41 miRNAs were upregulated in ovarian cancer samples compared with controls. Upregulated genes were enriched for genes involved in cell cycle activation and proliferation, hinting at a tumor derived signal. In conclusion, we provide proof-of-principle that mRNA capture sequencing of utero-tubal lavage fluid is technically feasible, and that the extracellular transcriptome of utero-tubal lavage should be further explored in larger cohorts to assess the diagnostic value of the biomarkers identified in this study.

Study EGAS00001005498

Intratumoural heterogeneity and immune modulation in lung adenocarcinoma of female smokers and never smokers

Lung cancer is still the leading cause of cancer death worldwide despite declining smoking prevalence in industrialised countries. Although lung cancer is highly associated with smoking status, a significant proportion of lung cancer cases develop in patients who never smoked, with an observable bias towards female never smokers. A better understanding of lung cancer heterogeneity and immune system involvement during tumour evolution and progression in never smokers is therefore highly warranted. We employed single nucleus transcriptomics of surgical lung adenocarcinoma (LADC) and normal lung tissue samples from patients with or without smoking history. Immune cells as well as fibroblasts and endothelial cells respond to tobacco smoke exposure by inducing a highly inflammatory state in normal lung tissue. In the presence of LADC, we identified differentially expressed transcriptional programmes in macrophages and cancer-associated fibroblasts, providing insight into how the niche favours tumour progression. Within tumours, we distinguished eight subpopulations of neoplastic cells in female smokers and never smokers. Through pseudotemporal ordering, we inferred a trajectory towards two differentiated tumour cell states implicated in cancer progression and invasiveness. A proliferating cell population sustaining tumour growth exhibits differential immune modulating signatures in both patient groups. Our results resolve cellular heterogeneity and immune interactions in LADC, with a special emphasis on female never smokers and implications for the design of therapeutic approaches.

Study EGAS00001006331

Target gene sequencing for human normal endometrial glands

The raw fastq files target sequencing of 112 genes for 1,298 endometrial glands and matched blood samples. The paired-end sequencing data sets (R1 and R2) are deposited. ABCC1, ACRC, ANK3, ARHGAP35, ARID1A, ARID5B, ATCAY, ATM, ATR, BARD1, BCOR, BRCA1, BRCA2, BRD4, BRIP1, CAMTA1, CDC23, CDYL, CFAP54, CHD4, CHEK1, CHEK2, CTCF, CTNNB1, CUX1, DGKA, DISP2, DYNC2H1, EMSY, FAAP24, FAM135B, FAM175A, FAM65C, FANCA, FANCB, FANCC, FANCD2, FANCE, FANCF, FANCG, FANCI, FANCL, FANCM, FAT1, FAT3, FBN2, FBXW7, FGFR2, FRG1, GPR50, HEATR1, HIST1H4B, HNRNPCL1, HOOK3, KIAA1109, KIF26A, KMT2B, KMT2C, KRAS, LAMA2, LRP1B, MLH1, MON2, MRE11A, MSH2, MSH6, MTOR, NBN, PALB2, PHEX, PIK3CA, PIK3R1, PLXNB2, PLXND1, PMS2, POLE, POLR3B, PPP2R1A, PTEN, PTPN13, RAD50, RAD51, RAD51B, RAD51C, RAD51D, RAD52, RAD54B, RAD54L, RICTOR, SACS, SIGLEC9, SLC19A1, SLX4, SPEG, STT3A, TAF1, TAF2, TAS2R31, TFAP2C, TNC, TONSL, TP53, TTC6, UBA7, VNN1, WT1, XIRP2, ZBED6, ZC3H13, ZFHX3, ZFHX4, ZMYM4.

Dataset EGAD00001008465

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