Copy number variation (CNV) refers to the variation in the number of copies of a DNA segment in the genome, which can influence regions of one or a few genes up to a whole chromosome. CNVs which provide cells with survival and growth advantages are retained through natural selection and are frequently observed across various types or subtypes of cancer. These CNVs can serve as important clinical biomarkers for cancer stratification.
Different techniques, including karyotyping, fluorescence in situ hybridization, array comparative genomic hybridization, single nucleotide polymorphism array, and next-generation sequencing, have been used to characterize CNV profiles. The resolution of CNV detection has increased from chromosomal-level in karyotyping to kilobase pair level in next-generation sequencing. CNV biomarkers are identified after analyzing samples of the same cancer type or subtype. The identified CNV biomarkers reciprocally provide advanced guidelines of cancer classification, enhance the diagnostic accuracy, and improve treatment of patients.
However, the application of these CNV biomarkers to rapid, particularly intraoperative, tumor assessments within the timeframe of neurosurgical procedures has remained elusive due to the protracted duration of conventional CNV characterization methods. The recent development of nanopore sequencing has enabled the real-time interpretation of the nucleotides and methylation status of DNA and RNA molecules. However, it is still a challenge to obtain the real-time CNV profiles that can improve diagnosis and treatment decisions in the operating room due to the lack of sensitive and reliable CNV detections.
In this thesis, we propose a statistical framework, called CNVisor, designed for rapid CNV detection from nanopore sequencing within one hour of biopsy to provide accurate CNV profiles and reliable CNV ranges, informing critical intraoperative decisions. The proposed method is applied to eight brain tumor patients during surgery and can enhance the current real-time glioma classifier based on methylation profiles. Moreover, CNVisor's compatibility with low sequencing coverage can facilitate non-invasive and precise cancer diagnostics through the CNV analysis of liquid biopsies from cerebrospinal fluid where only limited amount of DNA can be obtained. CNVs are also frequently observed in induced pluripotent stem cells (iPSCs) . We utilize the proposed method to evaluate the genome integrity of iPSCs obtained from the fibroblasts of northern white rhinos (\Ceratotherium simum cottoni), in which the iPSCs will be used for in vitro gametogenesis, i.e., an assisted reproductive technology with the potential to rescue this functionally extinct species.
