Search Results - EGA European Genome-Phenome Archive

WES analysis of a mixed cohort of pituitary tumors

BACKGROUND: Sporadic pituitary adenomas are the second most common primary brain tumor, but their genetics remains incompletely understood. We performed deep DNA sequencing of 42 pituitary macroadenomas, including hormonally active and atypical adenomas. METHODS: Pituitary adenomas representative of a spectrum of histopathologic subtypes, primary and recurrent tumors, and MIB-1 proliferative indices were profiled. Whole-exome sequencing was performed on tumors and paired blood followed by analysis of somatic copy number alteration and mutation. RESULTS: On the whole, the tumors harbored a low rate of mutations, similar to other benign brain tumors. However, almost one-third (29%) exhibited somatic copy-number alterations across large fractions of the genome (up to 99%). Despite such widespread genomic disruption, these tumors had few focal events, which is atypical among highly-disrupted cancers. The other 71% of tumors formed a distinct molecular class, with somatic copy-number alterations involving less than 6% of the genome. Among the highly-disrupted group, 92% were functional or atypical null-cell adenomas, whereas 87% of the less-disrupted group were clinically non-functional adenomas. The only significantly recurrent events were arm-level losses of chromosomes 1, 2, 11, and 18. No significantly recurrent mutations or insertion/deletion events were identified, suggesting no genes are altered by exomic mutations in >15% of pituitary tumors. CONCLUSIONS: Genomic characterization of a large series of sporadic pituitary adenomas reveals two classes of tumor, based on genomic disruption from arm-level copy-number alterations, which associate with hormonal and histologic subtypes.

Study EGAS00001001714

mRNA capture sequencing and RT-qPCR for the detection of pathognomonic, novel and secondary fusion transcripts in formalin-fixed paraffin-embedded tissue: a sarcoma showcase

RNA sequencing is widely used to study gene abundance patterns, but less frequently to assess structural alterations such as fusion transcripts. In this study, we assess the performance of messenger RNA (mRNA) capture sequencing to identify fusion transcripts in formalin-fixed paraffin-embedded (FFPE) tissue of different types of sarcoma, followed by orthogonal confirmation using RT-qPCR. To validate our workflow, we used the TruSight RNA Pan-Cancer Panel to analyze a first cohort of 6 positive control tumors for which the diagnostic workup demonstrated the presence of a specific chromosomal rearrangement. Fusion transcript calling by FusionCatcher confirmed all known aberrations and enabled the identification of both fusion gene partners and breakpoints. Next, whole transcriptome TruSeq RNA Exome sequencing was applied to a second cohort of 17 patients, diagnosed with fusion gene-negative alveolar rhabdomyosarcoma (ARMS) or undifferentiated round cell sarcoma (URCS), for whom fluorescence in situ hybridization (FISH) did not identify the classical pathognomonic rearrangements. Remarkably, for 6 out of 17 patients, mRNA capture sequencing readily detected a pathognomonic fusion transcript, i.e. PAX3-FOXO1 in 2 ARMS patients, and EWSR1-FLI1, EWSR1-ERG or EWSR1-NFATC2 in 4 URCS patients. These data show that RNA capture sequencing may enhance the detection rate of pathognomonic fusion genes in sarcoma. For the 11 patients with no known pathognomonic fusion transcript, 11 newly identified fusion transcripts were confirmed by RT-qPCR, including COPS3-TOM1L2, NCOA1-DTNB, WWTR1-LINC01986, PLAA-MOB3B, AP1B1-CHEK2 and BRD4-LEUTX fusion transcripts in ARMS patients. Additionally, recurrently detected secondary fusion transcripts in two patients diagnosed with EWSR1-NFATC2-positive sarcoma were confirmed (COPS4-TBC1D9, PICALM-SYTL2, SMG6-VPS53 and UBE2F-ALS2). Our results provide new insights into the underlying genetic causes of these malignancies.

Study EGAS00001005202

Pancreatic Cancer Sequencing Initiative

Pancreatic Cancer Sequencing Initiative for the International Cancer Genome Consortium at the Ontario Institute for Cancer Research.

Study EGAS00001000343

RRBS data from TRACERx non-small cell lung cancer (NSCLC) tumours and matched normal adjacent tissue.

TRACERx (TRAcking Cancer Evolution through therapy (Rx)) is a prospective cohort study designed to investigate intratumor heterogeneity (ITH) in relation to clinical outcome, and to determine the clonal nature of driver events and evolutionary processes in early stage non-small cell lung cancer (NSCLC).

Study EGAS00001008071

Multiple_myeloma_precursor_genomics

Whole genome sequencing of up to 45 multiple myeloma precursor samples and matched normals pairs.

Study EGAS00001006312

High-Resolution Spatial Transcriptomics Uncover Epidermal-Dermal Divergences in Merkel Cell Carcinoma: Spatial Context Reshapes the Gene Expression Landscape

Merkel cell carcinoma (MCC) is an aggressive malignancy with neuroendocrine differentiation marked by high plasticity, often manifesting as rapid therapy resistance. Although the cell-of-origin is presumed to be epithelial, epidermal localization of MCC is rarely observed, largely because in situ MCC is typically an incidental finding. Nevertheless, a subset of MCC tumors exhibits epidermotropism, wherein tumor cells are present in the epidermis. The behavior of cancer cells is profoundly influenced by the tumor microenvironment and interactions with neighboring cells. Notably, the normal counterparts of the cancer’s cell-of-origin have been shown to attenuate tumor aggressiveness. Thus, epidermotropic MCC presents a unique opportunity to explore the potential role of surrounding keratinocytes in modulating tumor cell behavior. While the epidermotropic tumor nests share histological resemblance with their dermal counterparts, their transcriptomic profiles remain unexplored. Here, we employed high-definition spatial and single cell transcriptomics to dissect the gene expression profiles of epidermotropic MCC cells, comparing them to MCC cells in the tumor core and those adjacent to blood vessels. Notably, epidermotropic MCC cells exhibit a transcriptomic signature reminiscent of cutaneous squamous cell carcinoma, characterized by upregulation of genes encoding keratins, S100A proteins, as well as calmodulin-like proteins 3 and 5. Mechanistically, this keratinocytic differentiation is associated with enhanced p63 activity, leading to the upregulation of PERP. Collectively, our study demonstrates that MCC cells can adopt a keratinocytic differentiation program in response to microenvironmental cues, underscoring the remarkable phenotypic plasticity of this malignancy and the importance of the tumor microenvironment for tumor characteristics.

Study EGAS00001008157

Spatio-temporal Profiling of a Rhabdoid Tumor Case Study

Background Immune checkpoint inhibition (ICI) has revolutionized oncology, offering extended survival and long-term remission in previously incurable cancers. While highly effective in tumors with high mutational burden, lowly mutated cancers, including pediatric malignancies, present low response rate and limited predictive biomarkers. Patients and methods We present a framework for the identification and validation of tumor-reactive T cells as a biomarker to quantify ICI efficacy and as candidates for a personalized TCR-T cell therapy. Therefore, we profiled a pediatric malignant rhabdoid tumor patient with complete remission after ICI therapy using deep single-cell T cell receptor (TCR) repertoire sequencing of the tumor microenvironment (TME) and the peripheral blood. Results Tracking T cell dynamics longitudinally from the tumor to cells in circulation over a time course of 12 months revealed a systemic response and durable clonal expansion of tumor-resident and ICI-induced TCR clonotypes. We functionally validated tumor reactivity of TCRs identified from the TME and the blood by co-culturing patient-derived tumor cells with TCR-engineered autologous T cells. Here, we observed unexpectedly high frequencies of tumor-reactive TCR clonotypes in the TME and confirmed T cell dynamics in the blood post-ICI to predict tumor-reactivity. Conclusion These findings strongly support spatio-temporal tracking of T cell activity in response to ICI to inform therapy efficacy and to serve as a source of tumor-reactive TCRs for personalized TCR-T designs.

Study EGAS00001008174

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