Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT): A Hybridization Capture-Based Next-Generation Sequencing Clinical Assay for Solid Tumor Molecular Oncology

The identification of specific genetic alterations as key oncogenic drivers and the development of targeted therapies are together transforming clinical oncology and creating a pressing need for increased breadth and throughput of clinical genotyping. Next-generation sequencing assays allow the efficient and unbiased detection of clinically actionable mutations. To enable precision oncology in patients with solid tumors, we developed Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT), a hybridization capture-based next-generation sequencing assay for targeted deep sequencing of all exons and selected introns of 341 key cancer genes in formalin-fixed, paraffin-embedded tumors. Barcoded libraries from patient-matched tumor and normal samples were captured, sequenced, and subjected to a custom analysis pipeline to identify somatic mutations. Sensitivity, specificity, reproducibility of MSK-IMPACT were assessed through extensive analytical validation. We tested 284 tumor samples with previously known point mutations and insertions/deletions in 47 exons of 19 cancer genes. All known variants were accurately detected, and there was high reproducibility of inter- and intrarun replicates. The detection limit for low-frequency variants was approximately 2% for hotspot mutations and 5% for nonhotspot mutations. Copy number alterations and structural rearrangements were also reliably detected. MSK-IMPACT profiles oncogenic DNA alterations in clinical solid tumor samples with high accuracy and sensitivity. Paired analysis of tumors and patient-matched normal samples enables unambiguous detection of somatic mutations to guide treatment decisions.

Additional Primary Malignancies in Patients with Gastrointestinal Stromal Tumor (GIST): A Clinicopathologic Study of 260 Patients with Molecular Analysis and Review of the Literature

BACKGROUND

The incidence of other primary neoplasms in gastrointestinal stromal tumor (GIST) patients is relatively high. Our aim was to better characterize the clinicopathologic and molecular relationships in a cohort of GIST patients.

METHODS

All GIST patients with tumor samples sent for molecular testing were identified via electronic medical records. Clinicopathologic characteristics of GIST and additional primary malignancies were analyzed.

RESULTS

Of 260 patients, 50 (19 %) had at least one additional primary malignancy. In 33 patients, separate primary neoplasms predated their GIST diagnosis and most commonly included: prostate (n = 9), breast (n = 8), and hematologic (n = 5). Renal (n = 4) and hematologic (n = 3) malignancies were the most frequent cancers identified after GIST diagnosis. The majority (8 of 12, 66 %) of malignancies diagnosed after GIST were found incidentally. Patients who developed other malignancies after GIST more often had KIT exon 11 mutations (100 vs. 66 %, P = 0.01). In comparison to patients with only GIST, patients with a second primary neoplasm of any chronology had GISTs with increased mitotic rate (≥5 per 50 high-power fields) (P = 0.0006). Literature review revealed colorectal cancer, gastric, prostate, renal, leukemia, and desmoid-type fibromatosis as the most common secondary neoplasms.

CONCLUSIONS

Nineteen percent of GIST patients develop other malignancies. This is the first report to describe a relationship between additional primary malignancy and both mutation and mitotic rate of GIST. Although the basis of these relationships remains to be investigated, caution in the clinical management of GIST patients with additional lesions is warranted.

Novel oncogene and tumor suppressor mutations in KIT and PDGFRA wild type gastrointestinal stromal tumors revealed by next generation sequencing

Among gastrointestinal stromal tumors (GISTs) of 10-15% are negative for KIT and PDGFRA, and most of these cases are SDH deficient. Recent studies have provided data on additional molecular alterations such as KRAS in KIT mutant GISTs. We aimed to assess the frequency and spectrum of somatic mutations in common oncogenes as well as copy number variations in GISTs negative for KIT and PDGFRA mutations. GISTs with wild type KIT/PDGFRA were tested via next generation sequencing for somatic mutations in 341 genes. SDHB immunohistochemistry to evaluate for SDH deficiency was also performed. Of 267 GISTs tested for KIT and PDGFRA mutations, 15 were wild type, of which eight cases had material available for further testing. All eight cases had loss of SDHB expression and had various molecular alterations involving ARID1A, TP53, and other genes. One case had a KRAS G12V (c.35G>T) mutation in both the primary gastric tumor and a post-imatinib recurrence. This tumor had anaplastic features and was resistant to multiple tyrosine kinase inhibitors, ultimately resulting in cancer-related mortality within 2 years of diagnosis. In conclusion, KRAS mutations occur in rare GISTs with wild type KIT and PDGFRA. These tumors may display immunohistochemical positivity for KIT and primary resistance to tyrosine kinase inhibitors.

Detection of mutations in myeloid malignancies through paired-sample analysis of microdroplet-PCR deep sequencing data

Amplicon-based methods for targeted resequencing of cancer genes have gained traction in the clinic as a strategy for molecular diagnostic testing. An 847-amplicon panel was designed with the RainDance DeepSeq system, covering most exons of 28 genes relevant to acute myeloid leukemia and myeloproliferative neoplasms. We developed a paired-sample analysis pipeline for variant calling and sought to assess its sensitivity and specificity relative to a set of samples with previously identified mutations. Thirty samples with known mutations in JAK2, NPM1, DNMT3A, MPL, IDH1, IDH2, CEBPA, and FLT3, were profiled and sequenced to high depth. Variant calling using an unmatched Hapmap DNA control removed a substantial number of artifactual calls regardless of algorithm used or variant class. The removed calls were nonunique, had lower variant frequencies, and tended to recur in multiple unrelated samples. Analysis of sample replicates revealed that reproducible calls had distinctly higher variant allele depths and frequencies compared to nonreproducible calls. On the basis of these differences, filters on variant frequency were chosen to select for reproducible calls. The analysis pipeline successfully retrieved the associated known variant in all tested samples and uncovered additional mutations in some samples corresponding to well-characterized hotspot mutations in acute myeloid leukemia. We have developed a paired-sample analysis pipeline capable of robust identification of mutations from microdroplet-PCR sequencing data with high sensitivity and specificity.