The Genomics Organization for Academic Laboratories (GOAL): A vision for a genomics future for academic pathology

T cell lymphoma and secondary primary malignancy risk after commercial CAR T cell therapy

We report a T cell lymphoma (TCL) occurring 3 months after anti-CD19 chimeric antigen receptor (CAR) T cell immunotherapy for non-Hodgkin B cell lymphoma. The TCL was diagnosed from a thoracic lymph node upon surgery for lung cancer. The TCL exhibited CD8+ cytotoxic phenotype and a JAK3 variant, while the CAR transgene was very low. The T cell clone was identified at low levels in the blood before CAR T infusion and in lung cancer. To assess the overall risk of secondary primary malignancy after commercial CAR T (CD19, BCMA), we analyzed 449 patients treated at the University of Pennsylvania. At a median follow-up of 10.3 months, 16 patients (3.6%) had a secondary primary malignancy. The median onset time was 26.4 and 9.7 months for solid and hematological malignancies, respectively. The projected 5-year cumulative incidence is 15.2% for solid and 2.3% for hematological malignancies. Overall, one case of TCL was observed, suggesting a low risk of TCL after CAR T.

FindDNAFusion: An Analytical Pipeline with Multiple Software Tools Improves Detection of Cancer-Associated Gene Fusions from Genomic DNA

Detection of cancer-associated gene fusions is crucial for diagnosis, prognosis, and treatment selection. Many bioinformatics tools are available for the detection of fusion transcripts by RNA sequencing, but there are fewer well-validated software tools for DNA next-generation sequencing (NGS). A 542-gene solid tumor NGS panel was designed, with exonic probes supplemented with intronic bait probes against genes commonly involved in oncogenic fusions, with a focus on lung cancer. Three software tools for the detecting gene fusions in this DNA-NGS panel were selected and evaluated. The performance of these tools was compared after a pilot study, and each was configured for optimal batch analysis and detection rate. A blacklist for filtering common tool-specific artifacts, and criteria for selecting clinically reportable fusions, were established. Visualization tools for annotating and confirming somatic fusions were applied. Subsequently, a full clinical validation was used for comparing the results to those from in situ hybridization and/or RNA sequencing. With JuLI, Factera, and GeneFuse, 94.1%, 88.2%, and 66.7% of expected fusions were detected, respectively. With a combinatorial pipeline (termed FindDNAFusion), developed by integrating fusion-calling tools with methods for fusion filtering, annotating, and flagging reportable calls, the accuracy of detection of intron-tiled genes was improved to 98.0%. FindDNAFusion is an accurate and efficient tool in detecting somatic fusions in DNA-NGS panels with intron-tiled bait probes when RNA is unavailable.

Clinical Utility and Benefits of Comprehensive Genomic Profiling in Cancer

BACKGROUND

Comprehensive genomic profiling (CGP) with next-generation sequencing detects genetic alterations of hundreds of genes simultaneously and multiple molecular biomarkers with one test. In the personalized medicine era, CGP is increasingly used for cancer diagnosis, treatment selection, and prognosis prediction.

CONTENT

In this review, we summarize the benefits of CGP, clinical utility of CGP, and challenges of setting up CGP in the clinical laboratories. Besides the genetic alterations identified in the cancer-related genes, other biomarkers such as tumor mutational burden, microsatellite instability, and homologous recombination deficiency are critical for initiating targeted therapy. Compared with conventional tests, CGP uses less specimen and shortens the turnaround time if multiple biomarkers need to be tested. RNA fusion assay and liquid biopsy are helpful additions to DNA-based CGP by detecting fusions/splicing variants and complementing tissue-based CGP findings, respectively.

SUMMARY

Many previous hurdles for implementing CGP in the clinical laboratories have been gradually alleviated such as the decrease in sequencing cost, availability of both open-source and commercial bioinformatics tools, and improved reimbursement. These changes have helped to make CGP available to a greater population of cancer patients for improving characterization of their tumors and expanding their eligibility for clinical trials. Additionally, sequencing results of the hundreds of genes on CGP panels could be further analyzed to better understand the biology of various cancers and identify new biomarkers.