aCNViewer: Comprehensive genome-wide visualization of absolute copy number and copy neutral variations

Can a Liquid Biopsy Detect Circulating Tumor DNA With Low-passage Whole-genome Sequencing in Patients With a Sarcoma? A Pilot Evaluation

BACKGROUND

A liquid biopsy is a test that evaluates the status of a disease by analyzing a sample of bodily fluid, most commonly blood. In recent years, there has been progress in the development and clinical application of liquid biopsy methods to identify blood-based, tumor-specific biomarkers for many cancer types. However, the implementation of these technologies to aid in the treatment of patients who have a sarcoma remains behind other fields of cancer medicine. For this study, we chose to evaluate a sarcoma liquid biopsy based on circulating tumor DNA (ctDNA). All human beings have normal cell-free DNA (cfDNA) circulating in the blood. In contrast with cfDNA, ctDNA is genetic material present in the blood stream that is derived from a tumor. ctDNA carries the unique genomic fingerprint of the tumor with changes that are not present in normal circulating cfDNA. A successful ctDNA liquid biopsy must be able to target these tumor-specific genetic alterations. For instance, epidermal growth factor receptor (EGFR) mutations are common in lung cancers, and ctDNA liquid biopsies are currently in clinical use to evaluate the status of disease in patients who have a lung cancer by detecting EGFR mutations in the blood. As opposed to many carcinomas, sarcomas do not have common recurrent mutations that could serve as the foundation to a ctDNA liquid biopsy. However, many sarcomas have structural changes to their chromosomes, including gains and losses of portions or entire chromosomes, known as copy number alterations (CNAs), that could serve as a target for a ctDNA liquid biopsy. Murine double minute 2 (MDM2) amplification in select lipomatous tumors or parosteal osteosarcoma is an example of a CNA due to the presence of extra copies of a segment of the long arm of chromosome 12. Since a majority of sarcomas demonstrate a complex karyotype with numerous CNAs, a blood-based liquid biopsy strategy that searches for these CNAs may be able to detect the presence of sarcoma ctDNA. Whole-genome sequencing (WGS) is a next-generation sequencing technique that evaluates the entire genome. The depth of coverage of WGS refers to how detailed the sequencing is, like higher versus lower power on a microscope. WGS can be performed with high-depth sequencing (that is, > 60×), which can detect individual point mutations, or low-depth sequencing (that is, 0.1× to 5×), referred to as low-passage whole-genome sequencing (LP-WGS), which may not detect individual mutations but can detect structural chromosomal changes including gains and losses (that is, CNAs). While similar strategies have shown favorable early results for specific sarcoma subtypes, LP-WGS has not been evaluated for applicability to the broader population of patients who have a sarcoma.

QUESTIONS/PURPOSES

Does an LP-WGS liquid biopsy evaluating for CNAs detect ctDNA in plasma samples from patients who have sarcomas representing a variety of histologic subtypes?

METHODS

This was a retrospective study conducted at a community-based, tertiary referral center. Nine paired (plasma and formalin-fixed paraffin-embedded [FFPE] tissue) and four unpaired (plasma) specimens from patients who had a sarcoma were obtained from a commercial biospecimen bank. Three control specimens from individuals who did not have cancer were also obtained. The paired and unpaired specimens from patients who had a sarcoma represented a variety of sarcoma histologic subtypes. cfDNA was extracted, amplified, and quantified. Libraries were prepared, and LP-WGS was performed using a NextSeq 500 next-generation sequencing machine at a low depth of sequencing coverage (∼1×). The ichorCNA bioinformatics algorithm, which was designed to detect CNAs from low-depth genomic sequencing data, was used to analyze the data. In contrast with the gold standard for diagnosis in the form of histopathologic analysis of a tissue sample, this test does not discriminate between sarcoma subtypes but detects the presence of tumor-derived CNAs within the ctDNA in the blood that should not be present in a patient who does not have cancer. The liquid biopsy was positive for the detection of cancer if the ichorCNA algorithm detected the presence of ctDNA. The algorithm was also used to quantitatively estimate the percent ctDNA within the cfDNA. The concentration of ctDNA was then calculated from the percent ctDNA relative to the total concentration of cfDNA. The CNAs of the paired FFPE tissue and plasma samples were graphically visualized using aCNViewer software.

RESULTS

This LP-WGS liquid biopsy detected ctDNA in 9 of 13 of the plasma specimens from patients with a sarcoma. The other four samples from patients with a sarcoma and all serum specimens from patients without cancer had no detectable ctDNA. Of those 9 patients with positive liquid biopsy results, the percent ctDNA ranged from 6% to 11%, and calculated ctDNA quantities were 0.04 to 5.6 ng/mL, which are levels to be expected when ctDNA is detectable.

CONCLUSION

In this small pilot study, we were able to detect sarcoma ctDNA with an LP-WGS liquid biopsy searching for CNAs in the plasma of most patients who had a sarcoma representing a variety of histologic subtypes.

CLINICAL RELEVANCE

These results suggest that an LP-WGS liquid biopsy evaluating for CNAs to identify ctDNA may be more broadly applicable to the population of patients who have a sarcoma than previously reported in studies focusing on specific subtypes. Large prospective clinical trials that gather samples at multiple time points during the process of diagnosis, treatment, and surveillance will be needed to further assess whether this technique can be clinically useful. At our institution, we are in the process of developing a large prospective clinical trial for this purpose.

Unravelling the Genetic Landscape of Hemiplegic Migraine: Exploring Innovative Strategies and Emerging Approaches

Migraine is a severe, debilitating neurovascular disorder. Hemiplegic migraine (HM) is a rare and debilitating neurological condition with a strong genetic basis. Sequencing technologies have improved the diagnosis and our understanding of the molecular pathophysiology of HM. Linkage analysis and sequencing studies in HM families have identified pathogenic variants in ion channels and related genes, including CACNA1A, ATP1A2, and SCN1A, that cause HM. However, approximately 75% of HM patients are negative for these mutations, indicating there are other genes involved in disease causation. In this review, we explored our current understanding of the genetics of HM. The evidence presented herein summarises the current knowledge of the genetics of HM, which can be expanded further to explain the remaining heritability of this debilitating condition. Innovative bioinformatics and computational strategies to cover the entire genetic spectrum of HM are also discussed in this review.

Control-FREEC viewer: a tool for the visualization and exploration of copy number variation data

BACKGROUND

Copy number alterations (CNAs) are genetic changes commonly found in cancer that involve different regions of the genome and impact cancer progression by affecting gene expression and genomic stability. Computational techniques can analyze copy number data obtained from high-throughput sequencing platforms, and various tools visualize and analyze CNAs in cancer genomes, providing insights into genetic mechanisms driving cancer development and progression. However, tools for visualizing copy number data in cancer research have some limitations. In fact, they can be complex to use and require expertise in bioinformatics or computational biology. While copy number data analysis and visualization provide insights into cancer biology, interpreting results can be challenging, and there may be multiple explanations for observed patterns of copy number alterations.

RESULTS

We created Control-FREEC Viewer, a tool that facilitates effective visualization and exploration of copy number data. With Control-FREEC Viewer, experimental data can be easily loaded by the user. After choosing the reference genome, copy number data are displayed in whole genome or single chromosome view. Gain or loss on a specific gene can be found and visualized on each chromosome. Analysis parameters for subsequent sessions can be stored and images can be exported in raster and vector formats.

CONCLUSIONS

Control-FREEC Viewer enables users to import and visualize data analyzed by the Control-FREEC tool, as well as by other tools sharing a similar tabular output, providing a comprehensive and intuitive graphical user interface for data visualization.

A molecular phenotypic map of malignant pleural mesothelioma

BACKGROUND

Malignant pleural mesothelioma (MPM) is a rare understudied cancer associated with exposure to asbestos. So far, MPM patients have benefited marginally from the genomics medicine revolution due to the limited size or breadth of existing molecular studies. In the context of the MESOMICS project, we have performed the most comprehensive molecular characterization of MPM to date, with the underlying dataset made of the largest whole-genome sequencing series yet reported, together with transcriptome sequencing and methylation arrays for 120 MPM patients.

RESULTS

We first provide comprehensive quality controls for all samples, of both raw and processed data. Due to the difficulty in collecting specimens from such rare tumors, a part of the cohort does not include matched normal material. We provide a detailed analysis of data processing of these tumor-only samples, showing that all somatic alteration calls match very stringent criteria of precision and recall. Finally, integrating our data with previously published multiomic MPM datasets (n = 374 in total), we provide an extensive molecular phenotype map of MPM based on the multitask theory. The generated map can be interactively explored and interrogated on the UCSC TumorMap portal (https://tumormap.ucsc.edu/?p=RCG_MESOMICS/MPM_Archetypes ).

CONCLUSIONS

This new high-quality MPM multiomics dataset, together with the state-of-art bioinformatics and interactive visualization tools we provide, will support the development of precision medicine in MPM that is particularly challenging to implement in rare cancers due to limited molecular studies.

Clonal and subclonal TP53 molecular impairment is associated with prognosis and progression in multiple myeloma

Aberrations on TP53, either as deletions of chromosome 17p (del17p) or mutations, are associated with poor outcome in multiple myeloma (MM), but conventional detection methods currently in use underestimate their incidence, hindering an optimal risk assessment and prognostication of MM patients. We have investigated the altered status of TP53 gene by SNPs array and sequencing techniques in a homogenous cohort of 143 newly diagnosed MM patients, evaluated both at diagnosis and at first relapse: single-hit on TP53 gene, either deletion or mutation, detected both at clonal and sub-clonal level, had a minor effect on outcomes. Conversely, the coexistence of both TP53 deletion and mutation, which defined the so-called double-hit patients, was associated with the worst clinical outcome (PFS: HR 3.34 [95% CI: 1.37–8.12] p = 0.008; OS: HR 3.47 [95% CI: 1.18–10.24] p = 0.02). Moreover, the analysis of longitudinal samples pointed out that TP53 allelic status might increase during the disease course. Notably, the acquisition of TP53 alterations at relapse dramatically worsened the clinical course of patients. Overall, our analyses showed these techniques to be highly sensitive to identify TP53 aberrations at sub-clonal level, emphasizing the poor prognosis associated with double-hit MM patients.

BPG: Seamless, automated and interactive visualization of scientific data

BACKGROUND

We introduce BPG, a framework for generating publication-quality, highly-customizable plots in the R statistical environment.

RESULTS

This open-source package includes multiple methods of displaying high-dimensional datasets and facilitates generation of complex multi-panel figures, making it suitable for complex datasets. A web-based interactive tool allows online figure customization, from which R code can be downloaded for integration with computational pipelines.

CONCLUSION

BPG provides a new approach for linking interactive and scripted data visualization and is available at http://labs.oicr.on.ca/boutros-lab/software/bpg or via CRAN at https://cran.r-project.org/web/packages/BoutrosLab.plotting.general.