The UCSF500 service is provided by the Clinical Cancer Genomic Lab (CCGL). This group is directed by Dr. Boris C. Bastian, and the informatics group, where I work, is led by Dr. Iwei Yeh. The pilot program from 2014 to 2016 focused on local patients with metastatic disease, including children and patients with rare or poorly understood cancer types.
Several published studies from this program have already given us insight into cancer mechanisms and treatment options:
- Childhood gliomas and other brain tumors
- Malignant phyllodes tumors of the breast
- Peritoneal mesothelioma, a rare cancer of the abdomen
- Anaplastic pleomorphic xanthoastrocytoma (PXA), a rare neurological tumor
Targeted sequencing
The UCSF500 assay is a targeted panel of approximately 500 genes and other genomic regions relevant to cancer diagnosis, prognosis and treatment.The sequenced tissue samples are typically a solid tumor biopsy and a matched normal sample, either blood draw or buccal swab. The matched normal is optional, and hematologic (blood) tumors such as leukemia and lymphoma can also be sequenced. In cases of tumor recurrence a previously sequenced normal sample's results will be reused in the new analysis to save time and cost.
CCGL staff perform DNA extraction, library preparation and hybridization on-site at UCSF. The custom target panel consists of:
- Exonic regions of about 500 (initially 510, now 480) cancer-associated genes;
- Selected introns of about 40 genes;
- Microsatellite sequences, for detecting microsatellite instability (MSI);
- Scattered SNP sites ("CGH probes") to detect loss of heterozygosity and mutation burden -- these probes are more concentrated near genes where copy number status is known to be actionable.
The target panel and analysis approach originated in the Bastian lab at UCSF. Elements of this approach can be seen in published papers on melanoma progression, the genetic drivers of desmoplastic melanoma, and our copy number caller CNVkit.
Analysis on the cloud
CCGL's custom-built pipeline for variant detection and analysis runs on the DNAnexus platform. Analysis of a typical sequencing run -- 14 patient samples, sequenced to an on-target coverage depth of 400x, plus 2 control samples -- takes about 4.5 hours.The pipeline detects:
- Small/single nucleotide variants (SNV): GATK HaplotypeCaller and UnifiedGenotyper, FreeBayes, Mutect -- combined into a single "unified" VCF for annotation
- Structural variants (SV): Pindel, DELLY -- run independently to detect potential gene fusions; small indels from Pindel are also included in the SNV VCF
- Copy number variants (CNV): CNVkit
- MSI detection: MSIsensor
- Various validity checks and quality metrics.
Reporting to the oncologist
The completed analysis results are automatically pulled to an on-site server hosting the signout software. This server and software is used by CCGL staff to review and approve each run's final QC metrics, and by CCGL clinical geneticists (mainly UCSF pathologists) to review the results and generate a PDF report to be entered in the patient's medical record and returned to the ordering oncologist.The UCSF500 report highlights clinically relevant genomic features:
- Somatic SNVs annotated as "Pathogenic" or "Likely Pathogenic" in ClinVar
- Copy number alterations
- Fusion genes
- Microsatellite stability/instability status
- Pathogenic germline variants relevant to oncology (incidental)
Finally, the clinical geneticist responsible for the report and the ordering oncologist responsible for the patient discuss therapeutic strategies at the next molecular tumor board meeting.
This is the UCSF500's key advantage, and the reason this service can only be offered by a medical center, not a startup: CCGL clinical geneticists continue to work with oncologists after delivering the final report so that the patient's medical history and treatment plan can be considered together with genetics and other diagnostic tests. This approach allows us to not only identify relevant therapies and clinical trials, but also to reconsider the initial diagnosis, quickly order follow-up lab tests, and consider germline findings that may affect the patient's family members.
6 comments:
Very nice initiative and something that should, in fact, drive the approach of NGS in a more revolutionizing and targetted way. I enjoyed how the approach of variants are done and that entire breakup of SNV, INDELS, CNVs, LOH are done. I hope then also once these 500 genes are checked for all the alterations at the genome level, the molecular profiles of these patients are also checked to understand the expression read out for these genes. The only thing which I am curious as of now is , do you also try to score from among this 500 genes if there are certain drivers are not based on statistical models of Bayesian classifiers or even functional impacts or consequences clustering? I believe not all 500 will be relevant or sometimes might also be that you have more than a considerable number of variants from among these 500 genes so a scoring metric for prioritization might be needed. Nonetheless, this work is indeed pretty transforming and am glad we are moving in such direction.
That is fantastic!
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