Maintaining a methods database to optimize solid tumor tissue culture: Review of a 15-year database from a single institution

Evaluation of Hi-C sequencing for the detection of gene fusions in hematologic and solid pediatric cancer samples

HiC sequencing is a DNA-based next-generation sequencing method that preserves the 3D conformation of the genome and has shown promise in detecting genomic rearrangements in translational research studies. To evaluate HiC as a potential clinical diagnostic platform, analytical concordance with routine laboratory testing was assessed using primary pediatric leukemia and sarcoma specimens previously positive for clinically significant genomic rearrangements. Archived specimen types tested included viable and nonviable frozen leukemic cells, as well as formalin-fixed paraffin-embedded (FFPE) tumor tissues. Initially, pediatric acute myeloid leukemia (AML) and alveolar rhabdomyosarcoma (A-RMS) specimens with known genomic rearrangements were subjected to HiC analysis to assess analytical concordance. Subsequently, a discovery cohort consisting of AML and acute lymphoblastic leukemia (ALL) cases with no known genomic rearrangements based on prior clinical diagnostic testing were evaluated to determine whether HiC could detect rearrangements. Using a standard sequencing depth of 50 million raw read-pairs per sample, or approximately 5X raw genomic coverage, 100% concordance was observed between HiC and previous clinical cytogenetic and molecular testing. In the discovery cohort, a clinically relevant gene fusion was detected in 45% of leukemia cases (5/11). This study demonstrates the value of HiC sequencing to medical diagnostic testing as it identified several clinically significant rearrangements, including those that might have been missed by current clinical testing workflows.

Key points

HiC sequencing is a DNA-based next-generation sequencing method that preserves the 3D conformation of the genome, facilitating detection of genomic rearrangements.HiC was 100% concordant with clinical diagnostic testing workflows for detecting clinically significant genomic rearrangements in pediatric leukemia and rhabdomyosarcoma specimens.HiC detected clinically significant genomic rearrangements not previously detected by prior clinical cytogenetic and molecular testing.HiC performed well with archived non-viable and viable frozen leukemic cell samples, as well as archived formalin-fixed paraffin-embedded tumor tissue specimens.

Optical genome mapping reveals balanced and unbalanced genetic changes associated with tumor-forming potential in an early-stage prostate cancer epithelial subline (M2205)

BACKGROUND

Identifying cytogenetic changes in tumors can aid in diagnosis/prognosis and disease management. Complete cytogenetic characterization has historically required a multimethod/time-consuming approach. Optical genome mapping (OGM) offers a potential solution to this challenge by detecting both balanced and unbalanced abnormalities in a single assay.

METHODS

Genetic changes acquired with tumor-forming potential in a prostate xenograft subline [M2205] (derived from a Black male) that were detected using cytogenetic versus OGM analyses were compared to assess the utility of OGM for analyzing solid tumors.

RESULTS

Cytogenetic/OGM concordance was noted for (a) copy number gains (16, 1p, 3q, 5q, 7p, 8q, 9q, 11p, 11q, 15q, 20q), (b) copy number losses (Y, 3p, 4p, 6p, 7p, 9p, 11q), and (c) structural changes, including multibreak rearrangements. Discordance was noted for two structural findings, both of which had breakpoints localized to repetitive sequences. The OGM studies identified new findings and confirmed/further characterized 8q24 structural abnormalities. It also detected genes gained/disrupted in the 8q24 region (e.g., MYC, DEPTOR, and EXT1); but recognizing a jumping translocation required cytogenetic analyses.

CONCLUSION

These results support using OGM as a tool to analyze solid tumors in clinical/research settings. Moreover, this OGM analysis expanded the characterization of cytogenetic changes present in the M2205 subline, including alterations associated with tumors from Black males diagnosed with prostate cancer.

Clinical Validation of Somatic Mutation Detection by the OncoScan CNV Plus Assay

The OncoScan CNV Plus Assay (OS+) is a single-nucleotide polymorphism microarray platform that can detect 74 hotspot somatic mutations (SMs) in nine genes via molecular inversion probes. We report validation of the SM component of OS+ using a cohort of pediatric high-grade brain tumor specimens. SM calls were generated from 46 brain tumor cases, most tested orthogonally via bidirectional Sanger sequencing. The initial calling algorithm result showed that 31 tumors were positive and 15 were negative for SM, with a total of 71 OS+ SM calls [28 high-confidence (HC) and 43 low-confidence (LC)]. Sanger sequencing was performed for 54 of the 71 calls (27 HC and 27 LC), as well as for 21 randomly selected hotspots across the 15 OS+ negative cases. HC calls (except EGFR) Sanger sequencing confirmed positive, negative calls confirmed negative, but none of the LC calls were Sanger-confirmed positive. An update of the OS+ algorithm resolved the LC calls, but of the 11 HC SM EGFR calls, Sanger sequencing confirmed only one. Two PTEN SM calls by OS+ in two separate cases were also negative per Sanger sequencing. We conclude that a majority of HC OS+ SM calls were accurate, except calls identified in EGFR and PTEN. Clinically, we report SMs identified by OS+ only after Sanger sequencing verification.

From Banding to BAM Files: Genomics Informs Diagnosis and Precision Medicine for Brain Tumors

Tumors of the central nervous system (CNS) have been historically classified according to their morphologic and immunohistochemical features. In 2016, updates to the classification of tumors of the CNS by the World Health Organization revolutionized this paradigm. For the first time, genomic findings, whether whole-arm chromosomal aberrations or single nucleotide variants, represent a necessary and critical component of diagnosis, contributing or superseding histologic findings. These updates stem from decades of technical innovation and genomic discovery. During this time, there has been a dramatic expansion and evolution in clinical genomic assays for these tumors, informing diagnosis and guiding therapeutic management.