Chromosomal copy number variation analysis by next generation sequencing confirms ploidy stability in Trypanosoma brucei subspecies

AbstractCopy number variation (CNV) is a common type of mutation that often drives cancer progression. With advances in next-generation sequencing (NGS), CNVs can be detected in a detailed manner via newly developed computational tools but quality of such CNV calls has not been carefully evaluated. We analyzed CNV calls reported by 6 cutting-edge callers for 91 samples which were derived from the same cancer cell line, prepared and sequenced by varying the following factors: type of tissue sample (Fresh vs. Formalin Fixed Paraffin Embedded (FFPE)), library DNA amount, tumor purity, sequencing platform (Whole-Genome Sequencing (WGS) versus Whole-Exome Sequencing (WES)), and sequencing coverage. We found that callers greatly determined the pattern of CNV calls. Calling quality was drastically impaired by low purity (<50%) and became variable when WES, FFPE, and medium purity (50%-75%) were applied. Effects of low DNA amount and low coverage were relatively minor. Our analysis demonstrates the limitation of benchmarking somatic CNV callers when the real ground truth is not available. Our comprehensive analysis has further characterized each caller with respect to confounding factors and examined the consistency of CNV calls, thereby providing guidelines for conducting somatic CNV analysis.

Download Full-text

EPCO-28. SINGLE-CELL RNA SEQUENCING IDENTIFIES INTRATUMORAL HETEROGENEITY AND ACTIVATION OF PRO-INVASIVE PATHWAYS IN NON-FUNCTIONING PITUITARY ADENOMAS

Neuro-Oncology ◽

10.1093/neuonc/noab196.027 ◽

2021 ◽

Vol 23 (Supplement_6) ◽

pp. vi8-vi8

Author(s):

Saket Jain ◽

Elaina Wang ◽

Husam Babikir ◽

Karin Shamardani ◽

Aaron Diaz ◽

...

Keyword(s):

Copy Number Variation ◽

Wnt Signaling ◽

Single Cell ◽

Rna Sequencing ◽

Pituitary Adenomas ◽

Copy Number ◽

Variation Analysis ◽

Copy Number Variation Analysis ◽

Single Cell Rna Sequencing ◽

Number Variation

Abstract Pituitary adenomas (PA) are one of the most common primary brain tumors and comprise 15% of brain neoplasms. Most PAs are histologically benign but can cause significant morbidity. The genetic profile of PAs is poorly understood. We used single-cell RNA sequencing using the 10X genomic platform to investigate cellular heterogeneity in twelve non-functioning pituitary adenoma samples from nine patients including site-specific (core vs edge) samples from three patients. Our analysis identified discrete clusters of cells associated with activation of specific functional pathways including lipid metabolism, angiogenic, and antigen presentation and processing pathways regardless of location within the tumor. MALT1, a lncRNA associated with increased proliferation and metastasis was ubiquitously expressed amongst these samples. Analysis of the core vs edge samples showed two specific clusters with activated invasion-promoting pathways including PI3k/AKT signaling, Wnt signaling (Wnt6 and FZD4), and epithelial-mesenchymal transition (TGFB1, SMAD1, ZEB1, and SNAI2) in the edge of the tumors. The activated Wnt signaling cascade drove a proinflammatory tumor microenvironment induced by the expression of IL-1, IL-17, and Toll-like receptors (TLR6 and TLR7/8) resulting in suppression of Tregs. Copy number variation analysis using the CONICS-CNV algorithm highlighted distinct chromosomal alterations within our samples that led to insight into clonal variations within each tumor with loss of chromosome 2 an early event in tumorigenesis and gain/loss of chromosome 19 as late events. Mapping the copy number variation analysis with the somatic variant analysis using the Vartrix algorithm identified novel driver mutations within these tumors. These findings help define the molecular fingerprint of pituitary adenomas and provide insights which could be utilized for better management of these tumors.

Download Full-text