CNVIntegrate: the first multi-ethnic database for identifying copy number variations associated with cancer

Copy number variations and their effect on the plasma proteome

Structural variations, including copy number variations (CNVs), affect around 20 million bases in the human genome and are common causes of rare conditions. CNVs are rarely investigated in complex disease research because most CNVs are not targeted on the genotyping arrays or the reference panels for genetic imputation. In this study, we characterize CNVs in a Swedish cohort (N = 1,021) using short-read whole-genome sequencing (WGS) and use long-read WGS for validation in a subcohort (N = 15), and explore their effect on 438 plasma proteins. We detected 184,182 polymorphic CNVs and identified 15 CNVs to be associated with 16 proteins (P < 8.22×10-10). Of these, 5 CNVs could be perfectly validated using long-read sequencing, including a CNV which was associated with measurements of the osteoclast-associated immunoglobulin-like receptor (OSCAR) and located upstream of OSCAR, a gene important for bone health. Two other CNVs were identified to be clusters of many short repetitive elements and another represented a complex rearrangement including an inversion. Our findings provide insights into the structure of common CNVs and their effects on the plasma proteome, and highlights the importance of investigating common CNVs, also in relation to complex diseases.

Novel RICTOR amplification harbouring entities: FISH validation of RICTOR amplification in tumour tissue after next-generation sequencing

Alterations in mTOR signalling molecules, including RICTOR amplification, have been previously described in many cancers, particularly associated with poor prognosis. In this study, RICTOR copy number variation (CNV) results of diagnostic next-generation sequencing (NGS) were analysed in 420 various human malignant tissues. RICTOR amplification was tested by Droplet Digital PCR (ddPCR) and validated using the "gold standard" fluorescence in situ hybridisation (FISH). Additionally, the consequences of Rictor protein expression were also studied by immunohistochemistry. RICTOR amplification was presumed in 37 cases with CNV ≥ 3 by NGS, among these, 16 cases (16/420; 3.8%) could be validated by FISH, however, ddPCR confirmed only 11 RICTOR-amplified cases with lower sensitivity. Based on these, neither NGS nor ddPCR could replace traditional FISH in proof of RICTOR amplification. However, NGS could be beneficial to highlight potential RICTOR-amplified cases. The obtained results of the 14 different tumour types with FISH-validated RICTOR amplification demonstrate the importance of RICTOR amplification in a broad spectrum of tumours. The newly described RICTOR-amplified entities could initiate further collaborative studies with larger cohorts to analyse the prevalence of RICTOR amplification in rare diseases. Finally, our and further work could help to improve and expand future therapeutic opportunities for mTOR-targeted therapies.

Necroptosis-Related Modification Patterns Depict the Tumor Microenvironment, Redox Stress Landscape, and Prognosis of Ovarian Cancer

Necroptosis is one of programmed cell death discovered recently, which involves in tumorigenesis, cancer metastasis, and immune reaction. We studied the necroptosis-related genes (NRGs) in ovarian cancer (OV) tissues using data from public databases, which separated into two NRGclusters. Patients in cluster A would have severe clinical characteristics, poor prognosis, and worse tumor microenvironment infiltration characteristics. The NRG score was achieved through the Cox analysis, along with a construction of a prognostic model. People with lower risk score would have better prognosis, lower expression of redox related genes, higher immunogenicity, and better effect on immunotherapy. In addition, the NRG score was closely related to cancer stem cell index, copy number variations, tumor mutation load, and chemosensitivity. We built a nomogram to enhance clinical application of the signature. These outcomes can help use know the function of NRGs in OV and provide new ideas for evaluating clinical outcome and developing more effective treatment protocols.

Integrated Workflow for the Label-Free Isolation and Genomic Analysis of Single Circulating Tumor Cells in Pancreatic Cancer

As pancreatic cancer is the third deadliest cancer in the U.S., the ability to study genetic alterations is necessary to provide further insight into potentially targetable regions for cancer treatment. Circulating tumor cells (CTCs) represent an especially aggressive subset of cancer cells, capable of causing metastasis and progressing the disease. Here, we present the Labyrinth-DEPArray pipeline for the isolation and analysis of single CTCs. Established cell lines, patient-derived CTC cell lines and freshly isolated CTCs were recovered and sequenced to reveal single-cell copy number variations (CNVs). The resulting CNV profiles of established cell lines showed concordance with previously reported data and highlight several gains and losses of cancer-related genes such as FGFR3 and GNAS. The novel sequencing of patient-derived CTC cell lines showed gains in chromosome 8q, 10q and 17q across both CTC cell lines. The pipeline was used to process and isolate single cells from a metastatic pancreatic cancer patient revealing a gain of chromosome 1q and a loss of chromosome 5q. Overall, the Labyrinth-DEPArray pipeline offers a validated workflow combining the benefits of antigen-free CTC isolation with single cell genomic analysis.