7790 results for "canc*"

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• Genome and transcriptome sequence data from a metastatic breast ductal carcinoma patient

  Genome and transcriptome sequence data from a metastatic breast ductal carcinoma patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001011021

• Genome and transcriptome sequence data from a neuroendocrine tumor patient

  Genome and transcriptome sequence data from a neuroendocrine tumor patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001011024

• Genome and transcriptome sequence data from a metastatic thymic carcinoma patient

  Genome and transcriptome sequence data from a metastatic thymic carcinoma patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001011025

• Genome and transcriptome sequence data from a small cell lung carcinoma patient

  Genome and transcriptome sequence data from a small cell lung carcinoma patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001011026

• Genome and transcriptome sequence data from a nasopharyngeal carcinoma patient

  Genome and transcriptome sequence data from a nasopharyngeal carcinoma patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001011028

• Genome and transcriptome sequence data from a colorectal carcinoma patient

  Genome and transcriptome sequence data from a colorectal carcinoma patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001011029

• Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

  Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001011035

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001011036

• Genome and transcriptome sequence data from a papillary thyroid carcinoma patient

  Genome and transcriptome sequence data from a papillary thyroid carcinoma patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001011038

• GBM-Space: Spatial Transcriptomic Profiling of Glioblastoma (10x Genomics - Visium)

  Cancer cells display heterogeneous and dynamic states in glioblastoma, but how these malignant states arise and whether they follow a tractable cellular trajectory across tumours is poorly understood. Here, we generate a deep single cell and spatial multi-region atlas of 12 isocitrate dehydrogenase wild-type (IDH-wt) primary glioblastomas that integrates transcriptomic, epigenomic and genomic analysis to comprehensively characterise their tumour heterogeneity. The datasets in this study include sequencing data from Visium spatial transcriptomic (10x Genomics) profiling of these tumours. Note: 2 new samples were added to the dataset on 2026-05-19.

  Dataset EGAD00001015527

• Genome and transcriptome sequence data from a metastatic follicular hurtle cell carcinoma patient

  Genome and transcriptome sequence data from a metastatic follicular hurtle cell carcinoma patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001015550

• Genome and transcriptome sequence data from a esophageal squamous cell carcinoma patient

  Genome and transcriptome sequence data from a esophageal squamous cell carcinoma patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001015556

• Genome and transcriptome sequence data from a metastatic rectal cancer patient

  Genome and transcriptome sequence data from a metastatic rectal cancer patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001015557

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001015560

• Genome and transcriptome sequence data from a metastatic acinic cell carcinoma patient

  Genome and transcriptome sequence data from a metastatic acinic cell carcinoma patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001015564

• DAC for Early detection of ovarian cancer using cell-free DNA fragmentomes and protein biomarkers

  Ovarian cancer is a leading cause of death from gynecological malignancies worldwide. No effective screening methods exist resulting in tumor detection at advanced stages where treatment is less effective. In this study, we used whole-genome cell-free DNA (cfDNA) fragmentome and protein biomarker (CA-125 and HE4) analyses to evaluate 591 women, mostly post-menopausal, from the European Union or the United States with ovarian cancer, benign adnexal masses, or without ovarian lesions. Using a machine learning model that incorporated multi-analyte fragmentome data and protein measurements, we evaluated the detection of ovarian cancer in two clinical settings, detection of ovarian cancers among a healthy population, and classification of adnexal masses as benign or malignant. The combined approach detected ovarian cancer with specificity >99% and sensitivity of 72%, 69%, 87%, and 100% for stages I–IV, respectively (AUC=0.96, 95% CI: 0.94-0.99), including 90% of high grade serous ovarian cancers. At the same specificity, CA-125 alone detected 34%, 62%, 63%, and 100% of ovarian cancers for stages I–IV (p=0.001, two-sided test of equal proportions). Additionally, our approach differentiated benign masses from ovarian cancers with high accuracy (AUC of 0.88, 95% CI=0.83-0.92). These results were validated in an independent population. These findings show that integrated cfDNA fragmentome and protein analyses detect ovarian cancers with high performance, enabling a new accessible approach for noninvasive ovarian cancer screening and diagnostic evaluation.

  Dac EGAC50000000332

• Colorectal cancer sequencing project of Cancer Institute of Zhejiang University (China)

  We performed whole genome sequencing for 10 pairs tumor samples and exome sequencing for 72 pairs tumor samples of colorectal cancer patients.

  Study EGAS00001001269

• Colorectal cancer sequencing project of Cancer Institute of Zhejiang University (China)

  We performed whole genome sequencing for 10 pairs tumor samples and exome sequencing for 72 pairs tumor samples of colorectal cancer patients.

  Dataset EGAD00001001877

• Genome and transcriptome sequence data from a metastatic pancreatobiliary adenocarcinoma patient

  Genome and transcriptome sequence data from a metastatic pancreatobiliary adenocarcinoma patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001015565

• Genome and transcriptome sequence data from a metastatic breast carcinoma (ductal) patient

  Genome and transcriptome sequence data from a metastatic breast carcinoma (ductal) patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001015570

• Genome and transcriptome sequence data from a squamous cell carcinoma left base tongue patient

  Genome and transcriptome sequence data from a squamous cell carcinoma left base tongue patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001015576

• Genome and transcriptome sequence data from a pancreatic neuroendocrine tumour patient

  Genome and transcriptome sequence data from a pancreatic neuroendocrine tumour patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001015588

• MethylScan data from tissue samples

  Raw data (fastq files) for tumor/normal paired samples (378 samples in total; 78, 58, 29, 24 pairs from liver, lung, ovary, and stomach cancer patients, respectively) profiled with the MethylScan assay, a low cost assay for profiling methylation. The MethylScan assay is designed for cfDNA methylome sequencing that enriches for the disease-associated DNA by depleting background signal. For solid tissues, the assay was performed without the MSRE digestion step.

  Dataset EGAD00001015685

• MethylScan data from plasma

  Raw data (fastq files) from 1061 plasma samples profiled with the MethylScan assay, a highly cost-effective approach for cfDNA methylome sequencing. MethylScan is a cost-efficient cfDNA methylome sequencing method that enriches methylation-informative fragments while actively depleting abundant background DNA derived from blood cells. By reducing this background noise, it improves the detection sensitivity for disease-associated cfDNA, such as tumor-derived DNA.The plasma samples (n = 1,061) were from 460 cancer patients (covering 4 major cancers: liver, lung, ovarian, and stomach cancer) and 601 noncancer individuals. The noncancer individuals (n = 601) can be further categorized into three groups: noncancer patients at high-risk of liver cancer who have chronic liver diseases (n = 157), noncancer patients at high-risk of lung cancer who have benign lung nodules (n = 43), and general noncancer hospital visitors (n = 401).

  Dataset EGAD00001015686

• Genome and transcriptome sequence data from a suspected radiation induced retroperitoneal sarcoma patient

  Genome and transcriptome sequence data from a suspected radiation induced retroperitoneal sarcoma patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001015854

• GBM-Space: Transcriptomic Profiling of Patient-Derived Glioblastoma Cell Lines (Parse Biosciences - Evercode WT)

  Cancer cells display heterogeneous and dynamic states in glioblastoma, but how these malignant states arise and whether they follow a tractable cellular trajectory across tumours is poorly understood. Here, we generate a deep single cell and spatial multi-region atlas of 12 isocitrate dehydrogenase wild-type (IDH-wt) primary glioblastomas that integrates transcriptomic, epigenomic and genomic analysis to comprehensively characterise their tumour heterogeneity. This dataset comprises sequencing data from single-cell transcriptomic profiles of patient-derived glioblastoma cell lines (Parse Biosciences Evercode WT v3), towards experimentally validating the malignant cell trajectory from developmental-like to gliosis-hypoxia states.

  Dataset EGAD00001016126

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__clear_cell_renal_cell_carcinoma

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute. Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001002608

• TCR β-chain repertoire characterization of regulatory and conventional T cells in peripheral blood from breast cancer patients and healthy individuals.

  Identification of tumor-specific effects on peripheral TCRβ repertoire formation in humans, investigation of the clonal origin of regulatory T cells in breast cancer patients and impact analysis of the tumor-specific conversion of conventional T cells into induced regulatory T cells on the peripheral Treg repertoire in humans.

  Study EGAS00001002699

• Preferential infiltration of distinct Vγ9δ2 T cells into Glioblastoma multiforme

  Glioblastoma multiforme (GBM), the most fatal CNS cancer, is highly infiltrative as a result of phenotypic alteration of cancer cells mainly driven by a mutual interaction among cancer cells, tumor-associated macrophages (TAMs) and other stromal cells. This work aims at characterizing GBM-infiltrating γδ T cells that may regulate the GBM tumor microenvironment and cancer cell gene expression. V(D)J repertoires of tumor-infiltrating and blood circulating γδ T cells from 4 patients were analyzed by NGS-based TCR sequencing. RNA gene expression profiling and immunostaining of cancer tissues were performed as well.

  Study EGAS00001002790

• Sensitive and Frequent Identification of High Avidity Neo-epitope Specific CD8 + T-cells in Immunotherapy-naïve Ovarian Cancer

  Immunotherapy directed against private tumor neo-antigens derived from non-synonymous somatic mutations is a promising strategy of personalized cancer immunotherapy. However, feasibility in low mutational load tumor types remains unknown. Comprehensive and deep analysis of circulating and tumor-infiltrating lymphocytes (TILs) for neo-epitope specific CD8 + T cells allowed prompt identification of oligoclonal and polyfunctional such cells from most immunotherapy-naïve patients with advanced epithelial ovarian cancer studied. Neo-epitope recognition was discordant between circulating T cells and TILs, and was more likely to be found among TILs, which displayed higher functionalavidity and unique TCRs with higher predicted affinity than their blood counterparts. Our results imply that identification of neo-epitope specific CD8 + T cells is achievable even in tumors with relatively low number of somatic mutations, and neo-epitope validation in TILs extends opportunities for mutanome-based personalized immunotherapies to such tumors.

  Study EGAS00001002803

• “Castration-persistence” is a distinct state of tolerance to androgen receptor targeting therapies in prostate cancer

  Androgen receptor (AR) signalling is important in prostate cancer progression, and therapies that specifically target this pathway are the mainstay of treatment for advanced disease. Treatment however is non-curative, and resistance develops inevitably with time. Although the mechanisms that drive progressive ‘castration resistant’ disease are reasonably well characterized, how tumours survive acute pathway inhibition is unclear. We performed a neo-adjuvant study of a novel combination of AR targeting therapies, and noted that the objective response to treatment was highly variable. To determine what was driving tumour persistence in poorly responding patients, we comprehensively characterised pre- and post-treatment samples were using both whole genome and RNA-sequencing. We find that ‘castration-persistence’ is a distinct state from ‘castration-resistance’, and is mediated by global transcriptional reprogramming leading to transitional EMT state, which is shared with benign luminal epithelial cells. This appears to be AP-1 and KLF driven, and represents and integration of multiple signalling pathways, particularly IGF2, offering a number of tractable strategies to improve clinical response to AR targeting therapies.

  Study EGAS00001003172

• Genome and transcriptome sequence data from a primary of unknown origin patient

  Genome and transcriptome sequence data from a primary of unknown origin patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001016185

• Lindsey E. Jones et al. Patient-derived cells from recurrent tumors that model the evolution of IDH-mutant glioma. Neuro-Oncology Advances, 2020. We established robust, versatile, and well-characterized Patient Derived Cells (PDC) of an IDH1-mutant astrocytoma and an IDH1-mutant oligodendroglioma that represents defined evolutionary stages of chemotherapy-induced hypermutation. The PDCs retain tumor subtype defining features over time as well as classic hallmarks of cancer, including anchorage independent growth and cell immortality. The integrated phylogenies composed of PDCs,single-cell-derived PDCs, patient-derived xenografts, and corresponding spatiotemporal tumor tissue samples also provide new insight into the clonality, evolutionary pattern, and immense mutational load of hypermutated IDH mutant gliomas.

  IDH-mutant lower-grade gliomas can undergo malignant progression via temozolomide-driven hypermutation. Patient-derived cells (PDC) that model the genetically distinct hypermutated (HM) tumor subgroup are generally lacking, and few if any human brain tumor cell models are from defined evolutionary time points. Here, we characterize multiple PDC derived from independent surgical specimens of IDH1-mutant recurrences, including an ATRX and TP53-mutant astrocytoma and a 1p/19q co-deleted and TERT promoter-mutant oligodendroglioma. We determined the evolutionary time points represented by each PDC using exome sequencing and phylogenetic reconstruction, comparing the PDC and single cell clones of the PDC (scPDC) to multiple spatiotemporal tumor tissue samples, PDC-derived xenografts (PDX) and patient-matched blood. The tumor samples exhibited TMZ-induced mutagenesis and a branching pattern of evolution. We found clear evidence of two fully independent founder HM clones in the tumor tissue that are faithfully represented by independent PDC. The PDC, scPDC and PDX also shared the mutagenesis signature and represent the mid and later evolutionary time points of their corresponding tumors. The PDC maintained the tumor subtype-defining features over many passages, including heterozygosity of the IDH1 R132H mutation, production of 2-hydroxyglutarate (2-HG), and subtype-specific telomere maintenance mechanisms. The PDC from both tumors exhibited anchorage-independent growth in soft agar. The oligodendroglioma PDC formed infiltrative intracranial tumors with characteristic oligodendroglioma histology, initially with a long period to tumor formation. We conclude that the PDC, scPDC and PDX faithfully model the heterogeneous clonal origins of the corresponding tumor tissue. The multilevel analysis also provides new insight into the intratumoral heterogeneity and vast mutational load of HM glioma. The PDC from multiple evolutionary time points presented in the context of full clinical timelines may be useful to model evolution and intratumoral heterogeneity, important sources of therapeutic failure.

  Study EGAS00001003992

• Chemotherapy induces canalization of cell state in childhood B-cell precursor acute lymphoblastic leukemia

  Comparison of intratumor genetic heterogeneity in cancer at diagnosis and relapse suggests that chemotherapy induces bottleneck selection of subclonal genotypes. However, evolutionary events subsequent to chemotherapy could also explain changes in clonal dominance seen at relapse. We therefore investigated the mechanisms of selection in childhood B-cell precursor acute lymphoblastic leukemia (BCP-ALL) during induction chemotherapy where maximal cytoreduction occurs. To distinguish stochastic versus deterministic events, individual leukemias were transplanted into multiple xenografts and chemotherapy administered. Analyses of the immediate post-treatment leukemic residuum at single-cell resolution revealed that chemotherapy has little impact on genetic heterogeneity. Rather, it acts on extensive, previously unappreciated, transcriptional and epigenetic heterogeneity in BCP-ALL, dramatically reducing the spectrum of cell states represented, leaving a genetically polyclonal but phenotypically uniform population, with hallmark signatures relating to developmental stage, cell cycle and metabolism. Hence, canalization of the cell state accounts for a significant component of bottleneck selection during induction chemotherapy.

  Study EGAS00001004407

• FOXM1 is a biomarker of resistance to PI3Kα inhibition in ER+ breast cancer that is detectable using metabolic imaging (RNA-seq data)

  PIK3CA, encoding the PI3Kα isoform, is the most frequently mutated oncogene in estrogen receptor-positive breast cancer. Isoform-selective PI3K inhibitors are used clinically but intrinsic and acquired resistance limits their utility. Improved selection of patients that will benefit from these drugs requires novel predictive biomarkers. We show here that persistent FOXM1 expression following drug treatment is a biomarker of resistance to PI3Kα inhibition in ER+ breast cancer. Since the transcription factor drives expression of lactate dehydrogenase (LDH) but not hexokinase 2 (HK-II), changes in FOXM1 expression can be detected using magnetic resonance imaging of LDH-catalyzed hyperpolarized 13C label exchange between pyruvate and lactate but not by PET measurements of HK-II-mediated trapping of the glucose analog 2-deoxy-2-[18F]fluorodeoxyglucose.

  Study EGAS00001004452

• Clinical relevance of somatic copy-number alterations in plasma circulating tumor DNA from advanced EGFR-mutated NSCLC patients treated with osimertinib

  Background: Somatic copy-number alterations (SCNAs) are associated with drug resistance in patients with advanced epidermal growth factor receptor (EGFR)-mutated non-small cell lung cancer (NSCLC) treated with EGFR-tyrosine kinase inhibitors (TKIs). The purpose of our study was to assess the clinical relevance and development of genome-wide SCNAs in plasma circulating tumor DNA (ctDNA) under osimertinib therapy.Methods: We included 43 patients with advanced EGFR T790M-positive lung adenocarcinoma who were treated with osimertinib after progression under previous EGFR-TKI therapy. We performed genomic profiling of ctDNA in plasma samples from each patient obtained pre-osimertinib and after patients developed resistance to osimertinib. SCNAs were detected by shallow whole-genome plasma sequencing and EGFR mutations were assessed by droplet digital PCR.Results: SCNAs in resistance-related genes (rrSCNAs) were detected in 10 out of 39 (25.6%) evaluable patients before start of osimertinib. The presence of rrSCNAs in plasma before initiation of osimertinib therapy was associated with a lower response rate to osimertinib (50% versus 86%, p=0.02) and was an independent predictor for shorter progression-free survival (adjusted HR 3.26, 95% CI 1.37-7.75, p=0.008) and overall survival (adjusted HR 2.41, 95% CI 1.09-5.34, p=0.03).Conclusions: Genomic profiling of plasma ctDNA is clinically relevant and affects the efficacy and clinical outcome of osimertinib. Our approach allows comprehensive assessment of SCNAs in plasma samples of lung adenocarcinoma patients and may help to guide genotype-specific therapeutic strategies in the future.

  Study EGAS00001004539

• TCR β-chain repertoire characterization of regulatory and conventional T cells in breast tumors from breast cancer patients.

  Identification of tumor-specific effects on peripheral TCRβ repertoire formation in humans, investigation of the clonal origin of regulatory T cells in breast cancer patients and impact analysis of the tumor-specific conversion of conventional T cells into induced regulatory T cells on the peripheral Treg repertoire in humans.

  Study EGAS00001004671

• Assessment of cannabidiol and Δ9-tetrahydrocannabiol in mouse models of medulloblastoma

  Phytocannabinoids Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD) have been demonstrated to exhibit anti-cancer activity in preclinical models of brain cancer leading to new clinical trials for adults with glioblastoma. We describe here the first report that has investigated a role for THC and CBD in paediatric brain cancer. Cannabinoids had cytotoxic activity against medulloblastoma and ependymoma cells in vitro, functioning in part through the inhibition of cell cycle progression and the induction of autophagy. Despite these effects in vitro, when tested in orthotopic mouse models of medulloblastoma or ependymoma, no impact on animal survival was observed. Furthermore, cannabinoids neither enhanced nor impaired conventional chemotherapy in a medulloblastoma mouse model. These data show that while THC and CBD do have some effects on medulloblastoma and ependymoma cells, are well tolerated and have minimal adverse effects, they do not appear to elicit any survival benefit in preclinical models of paediatric brain cancer.

  Study EGAS00001004963

• Genome and transcriptome sequence data from a metastatic ​adenocarcinoma of breast (ductal) patient

  Genome and transcriptome sequence data from a metastatic ​adenocarcinoma of breast (ductal) patient,generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010976

• Identification of biomarkers of response to preoperative talazoparib monotherapy in treatment naïve gBRCA+ breast cancers

  Germline mutations in BRCA1 or BRCA2 exist in ~2-7% of breast cancer patients, which has led to the approval of PARP inhibitors in the advanced setting. We have previously reported a phase II neoadjuvant trial of single agent talazoparib for patients with germline BRCA pathogenic variants with a pathologic complete response (pCR) rate of 53%. As nearly half of the patients treated did not have pCR, better strategies are needed to overcome treatment resistance. To this end, we conducted multi-omic analysis of 13 treatment naïve breast cancer tumors from patients that went on to receive single-agent neoadjuvant talazoparib. We looked for biomarkers that were predictive of response (assessed by residual cancer burden) after 6 months of therapy. We found that all resistant tumors exhibited either the loss of SHLD2, expression of a hypoxia signature, or expression of a stem cell signature. These results indicate that the deep analysis of pre-treatment tumors can identify biomarkers that are predictive of response to talazoparib and potentially other PARP inhibitors, and provides a framework that will allow for better selection of patients for treatment, as well as a roadmap for the development of novel combination therapies to prevent emergence of resistance.

  Study EGAS00001005676

• Single-cell profiling of neoantigen-specific T cells in lung cancers treated with neoadjuvant PD-1 blockade

  We study the expression profile of MANA-specific T cells, we used the MANA functional expansion of specific T cells (MANAFEST) assay in neoadjuvant anti-PD-1-treated lung cancers and applied their T cell receptor’s (TCR) complementarity-determining region 3 (CDR3) as a “barcode” to track and analyze their transcriptional programs in the tumor microenvironment using single cell TCR sequencing coupled with single cell RNA sequencing. We revealed distinct phenotype for MANA- and virus-specific clones in TIL and adjacent normal lung, regardless of response. MANA-specific T cells show features that drive the differences between responders and non-responders.

  Study EGAS00001005343

• RNA-sequencing of tumors from 45 patients with recurrent or metastatic gastric cancer treated with immune checkpoint inhibitors

  Genomic profiling can provide prognostic and predictive information to guide clinical care. Biomarkers that reliably predict patient response to chemotherapy and immune checkpoint inhibition in gastric cancer are lacking. In this work, we used our machine learning algorithm NTriPath to identify a gastric-cancer specific 32-gene signature. Using unsupervised clustering on expression levels of these 32 genes in tumors from 567 patients, we identified four molecular subtypes that were prognostic for survival. We then built a support vector machine with linear kernel and the binary classifier to generate a risk score that is prognostic for 5-year overall survival and validated the risk score using three independent datasets. We also found that the molecular subtypes predicted response to adjuvant 5-fluorouracil and platinum after gastrectomy and immune checkpoint inhibitors in patients with metastatic or recurrent disease. The 32-gene signature is a promising prognostic and predictive biomarker to guide the clinical care of gastric cancer patients and should be validated in a prospective manner. This EGA archive includes both St.Mary hospital cohort samples (n=28) and Yonsei immunotherapy patient samples (n=17).

  Study EGAS00001005588

• Mult-omics Palbociclib Resistance Study in HR+/HER2– Metastatic Breast Cancer

  Resistance to CDK4/6 inhibitors and endocrine therapy (ET) are common and poorly understood since they have been real game changer in patients with HR-positive and HER2-negative MBC. A comprehensive genomic and transcriptomic analysis of pre-treatment and post-treatment tumors from patients treated with palbociclib plus ET identified novel markers associated with poor prognosis such as genomic scar features caused by homologous repair deficiency (HRD), estrogen response signatures, and four unique prognostic clusters with distinct molecular features. Tumors with TP53 mutations co-occurring with a unique HRD-high cluster responded poorly. By comparing genomic and transciptomic profiles of paired samples, tumors were found to be further enriched in HRD genomic scars and many had switched to aggressive molecular subtypes. Furthermore, we identified high frequencies of acquired genomic alterations upon disease progression in RB1, ESR1, PTEN, and KMT2C. Our findings provide new insight into potential predictive biomarkers that could be targeted to overcome resistance. (NCT03401359)

  Study EGAS00001005736

• Genome-wide cell-free DNA termini in patients with cancer

  The structure, fragmentation pattern, length and terminal sequence of cell-free DNA (cfDNA) is under the influence of nucleases present in the blood. We hypothesized that differences in the diversity of bases at the end of cfDNA fragments can be leveraged on a genome-wide scale to enhance the sensitivity for detecting the presence of tumor signals in plasma. We surveyed the cfDNA termini in 72 plasma samples from 319 patients with 18 different cancer types using low-coverage whole genome sequencing. The fragment-end sequence and diversity were altered in all cancer types in comparison to 76 healthy controls. We converted the fragment end sequences into a quantitative metric and observed that this correlates with circulating tumor DNA tumor fraction (R = 0.58, p < 0.001, Spearman). Using these metrics, we were able to classify cancer samples from control at a low tumor content (AUROC of 91% at 1% tumor fraction) and shallow sequencing coverage (mean AUROC = 0.99 at >1M fragments). Combining fragment-end sequences and diversity using machine learning, we classified cancer from healthy controls (mean AUROC = 0.99, SD = 0.01). Using unsupervised clustering we showed that early-stage lung cancer can be classified from control or later stages based on fragment-end sequences. We observed that fragment-end sequences can be used for prognostication (hazard ratio: 0.49) and residual disease detection inresectable esophageal adenocarcinoma patients, moving fragmentomics toward a greater clinical implementation.

  Study EGAS00001005738

• Genome-wide cell-free DNA termini in patients with cancer

  The structure, fragmentation pattern, length and terminal sequence of cell-free DNA (cfDNA) is under the influence of nucleases present in the blood. We hypothesized that differences in the diversity of bases at the end of cfDNA fragments can be leveraged on a genome-wide scale to enhance the sensitivity for detecting the presence of tumor signals in plasma. We surveyed the cfDNA termini in 72 plasma samples from 319 patients with 18 different cancer types using low-coverage whole genome sequencing. The fragment-end sequence and diversity were altered in all cancer types in comparison to 76 healthy controls. We converted the fragment end sequences into a quantitative metric and observed that this correlates with circulating tumor DNA tumor fraction (R = 0.58, p < 0.001, Spearman). Using these metrics, we were able to classify cancer samples from control at a low tumor content (AUROC of 91% at 1% tumor fraction) and shallow sequencing coverage (mean AUROC = 0.99 at >1M fragments). Combining fragment-end sequences and diversity using machine learning, we classified cancer from healthy controls (mean AUROC = 0.99, SD = 0.01). Using unsupervised clustering we showed that early-stage lung cancer can be classified from control or later stages based on fragment-end sequences. We observed that fragment-end sequences can be used for prognostication (hazard ratio: 0.49) and residual disease detection inresectable esophageal adenocarcinoma patients, moving fragmentomics toward a greater clinical implementation.

  Study EGAS00001005747

• Accumulation of copy number alterations and clinical progression across advanced prostate cancer

  The burden of copy number alterations positively associated with radiologically-evident distant metastases at diagnosis (P=0.00006) and showed a non-linear relationship with clinical outcome on univariable and multivariable analysis, characterised by a sharp increase in the relative risk of progression (P=0.003) and death (P=0.045) for each unit increase, stabilising into more modest increases with higher burdens. This association between copy number burden and outcome was similar in each of the four metastatic states. Copy number loss occurred significantly more frequently than gain at the lowest copy number burden quartile (q=4.1X10-6). Loss of segments in chromosome 5q21-22 and gains at 8q21-24, respectively including CHD1 and cMYC, occurred more frequently in cases with higher copy number alteration (for either region: Kolmogorov–Smirnov distance, 0.5; adjusted P<0.0001). Copy number alterations showed variability across tumor regions in the same prostate. This variance associated with increased risk of distant metastases (Kruskal-Wallis test P=0.037).

  Study EGAS00001006251

• early-stage ESCC sequencing study

  We performed a comprehensive multi-omics analysis of 786 trace-tumor-samples from 154 esophageal squamous cell carcinoma phase (ESCC) patients, covering 9 histopathological stages in 3 phases as nontumor phase (NT phase), intraepithelial neoplasia phase (IEN phase), and ESCC phase. Proteogenomics elucidated the stage-specific molecular characterization and defined the cancer-driving waves along with the mutation accumulation in EC progression. The integrated multi-omics uncovered the chromosome 3q gain was the key event in the transmit from the NT to IEN phase, disclosed the top mutation of TP53 enhanced cell cycle and DNA replication in the IEN phase, and revealed the ESCC phase mutations of AKAP9 and MCAF1 elevated glycolysis and Wnt signaling, respectively. Furthermore, the trajectory analysis identified 6 major tracks related to different clinical features during ESCC progression. Growingly enhanced and hyperphosphorylated phosphoglycerate kinase 1 (PGK1, S203) was detected and considered as a drug target in ESCC progression. Collectively, this study provides insight into the understanding of ESCC molecular mechanism and a valuable resource for the development of therapeutic targets.

  Study EGAS00001006126

• Genome-wide cell-free DNA termini in patients with cancer

  The structure, fragmentation patterns and terminal sequences of cell-free DNA (cfDNA) are altered by nucleases and biological mechanisms in the blood of cancer patients. The cfDNA fragment-end composition recovered from low coverage WGS (<1 fold coverage) using a bespoke software (FrEIA) is aberrant in the plasma from cancer patient (n = 418, 655 samples) compared to controls (n = 117). As a standalone test FrEIA allows detection down to ~0.2% tumor fraction in vitro and in silico at 95% specificity, leading to a sensitivity of ~71% for detecting lung cancer (14/22 stage I-II, 27/38 stage III, 92/127 stage IV) and ~68% for detecting esophageal adenocarcinoma (26/44 stage II, 46/62 stage III). Additional cfDNA biological patterns can be combined with FrEIA increasing the diagnostic potential of low coverage WGS at minimal cost (mean AUROC = 0.96). Integrating multiple cfDNA biological signal augments the diagnostic performance of liquid biopsy.

  Study EGAS00001006142

• Intratumoral Heterogeneity and Clonal Evolution Induced by HPV Integration.

  The human papillomavirus (HPV) genome is integrated into host DNA in most HPV-positive cancers, but the consequences for chromosomal integrity are unknown. Continuous long-read sequencing of oropharyngeal cancers and cancer cell lines revealed a unique form of structural variation, termed heterocateny here, characterized by heterogeneous, interrelated, and repetative patterns of concatemerized virus and host DNA segments. Evidence of heterocateny was detected in extrachromosomal and/or intrachromosomal DNA in all cases. Unique breakpoint sequences shared across structurally heterogeneous virus-host concatemers within each cancer facilitated stepwise reconstruction of their evolution from a common molecular ancestor. This analysis revealed that unstable virus and virus-host concatemers in ecDNA or integrated form mediate insertion into and excision from chromosomes, capture, rearrangement, and rolling-circle amplification of host DNA, and chromosomal rearrangements. The data indicate that heterocatena is driven by the dynamic, aberrant replication and recombination of an oncogenic DNA virus, thereby extending known consequences of HPV integration to include promotion of intra-tumoral heterogeneity and clonal evolution.

  Study EGAS00001006652

• RNA-seq of DF149 cells – a patient-derived xenograft model of ascites-derived, homologous recombination repair-proficient, high-grade serous ovarian carcinoma – cultured in vitro and isolated after 8 hours treatment with DMSO control (3 x biological replicates) and 2.5 µM CBL0137 (3 x biological replicates)

  Background: High-grade serous ovarian carcinomas (HGSCs) are a heterogeneous subtype of epithelial ovarian cancers and include serous cancers arising in the fallopian tube and peritoneum. These cancers are now subdivided into homologous recombination repair (HR)-deficient and proficient subgroups as this classification impacts on management and prognosis. PARP inhibitors (PARPi) have shown significant clinical efficacy, particularly as maintenance therapy following response to platinum based chemotherapy in BRCA-mutant or homologous recombination (HR)-deficient HGSCs in both the 1st and 2nd line settings. However, PARPi have limited clinical benefit in HR-proficient HGSCs which make up almost 50% of HGSC and improving outcomes in these patients is now a high priority due to the poor prognosis with current standard of care. There are a number of potential lines of investigation including efforts in sensitizing HR-proficient tumors to PARPi. Herein, we aimed to develop a novel combination therapy by targeting SSRP1 using a small molecule inhibitor CBL0137 with PARPi in HR-proficient HGSOCs. Experimental design: We tested anti-cancer activity of CBL0137 monotherapy using a panel of HGSOC cell lines and patient-derived tumor cells in vitro. RNA sequencing was used to map global transcriptomic changes in CBL0137-treated patient-derived HR-proficient HGSOC cells. We tested efficacy of CBL0137 in combination with PARPi using HGSOC cell lines and patient-derived tumor cells in vitro and in vivo. Results: We show that SSRP1 inhibition using a small molecule, CBL0137, that traps SSRP1 onto chromatin, exerts a significant anti-growth activity in vitro against HGSC cell lines and patient-derived tumor cells, and also reduces tumor burden in vivo. CBL0137 induced DNA repair deficiency via inhibition of the HR repair pathway and sensitized SSRP1-high HR-proficient HGSC cell lines and patient-derived tumor cells/xenografts to the PARPi, Olaparib in vitro and in vivo. CBL0137 also enhanced the efficacy of DNA damaging platinum-based chemotherapy in HGSC patient-derived xenografts. Conclusion: Our findings strongly suggest that combination of CBL0137 and PARP inhibition represents a novel therapeutic strategy for HR-proficient HGSCs that express high levels of SSRP1 and should be investigated in the clinic.

  Study EGAS00001006662