Clinical characteristics and whole exome/transcriptome sequencing of coexisting chronic myeloid leukemia and myelofibrosis

Myeloproliferative neoplasms (MPNs) are clonal hematopoietic stem cell (HSC) disorders that can be classified on the basis of genetic, clinical, phenotypic features. Genetic lesions such as JAK2 mutations and BCRâ ABL translocation are often mutually exclusive in MPN patients and lead to essential thrombocythemia, polycythemia vera, or myelofibrosis or chronic myeloid leukemia, respectively. Nevertheless, coexistence of these genetic aberrations in the same patient has been reported. Whether these aberrations occur in the same stem cell or a different cell is unclear, but an unstable genome in the HSCs seems to be the common antecedent. In an effort to characterize the underlying genetic events that might contribute to the appearance of more than one MPN in a patient, we studied neoplastic cells from patients with dual MPNs by nextâ generation sequencing. We observed that most patients with two MPNs harbored mutations in genes known to contribute to clonal hematopoiesis through altered epigenetic regulation such as TET2, ASXL1/2, SRSF2, and IDH2 at varying frequencies (1%â 47%). In addition, we found that some patients also harbored oncogenic mutations in N/KRAS, TP53, BRAF, EZH2, and GNAS at low frequencies, which probably represent clonal evolution. These findings support the hypothesis that hematopoietic cells from MPN patients harbor multiple genetic aberrations, some of which can contribute to clonal dominance. Acquiring mutations in JAK2/CALR/MPL or the BCRâ ABL translocation probably drive the oncogenic phenotype towards a specific MPN. Further, we propose that the acquisition of BCRâ ABL in these patients is frequently a secondary event resulting from an unstable genome.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/136751/1/ajh24728.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136751/2/ajh24728_am.pd

Perifosine plus lenalidomide and dexamethasone in relapsed and relapsed/refractory multiple myeloma: a Phase I Multiple Myeloma Research Consortium study

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/92443/1/bjh9173.pd

Rapid, ultra low coverage copy number profiling of cell-free DNA as a precision oncology screening strategy.

Current cell-free DNA (cfDNA) next generation sequencing (NGS) precision oncology workflows are typically limited to targeted and/or disease-specific applications. In advanced cancer, disease burden and cfDNA tumor content are often elevated, yielding unique precision oncology opportunities. We sought to demonstrate the utility of a pan-cancer, rapid, inexpensive, whole genome NGS of cfDNA approach (PRINCe) as a precision oncology screening strategy via ultra-low coverage (~0.01x) tumor content determination through genome-wide copy number alteration (CNA) profiling. We applied PRINCe to a retrospective cohort of 124 cfDNA samples from 100 patients with advanced cancers, including 76 men with metastatic castration-resistant prostate cancer (mCRPC), enabling cfDNA tumor content approximation and actionable focal CNA detection, while facilitating concordance analyses between cfDNA and tissue-based NGS profiles and assessment of cfDNA alteration associations with mCRPC treatment outcomes. Therapeutically relevant focal CNAs were present in 42 (34%) cfDNA samples, including 36 of 93 (39%) mCRPC patient samples harboring AR amplification. PRINCe identified pre-treatment cfDNA CNA profiles facilitating disease monitoring. Combining PRINCe with routine targeted NGS of cfDNA enabled mutation and CNA assessment with coverages tuned to cfDNA tumor content. In mCRPC, genome-wide PRINCe cfDNA and matched tissue CNA profiles showed high concordance (median Pearson correlation = 0.87), and PRINCe detectable AR amplifications predicted reduced time on therapy, independent of therapy type (Kaplan-Meier log-rank test, chi-square = 24.9, p < 0.0001). Our screening approach enables robust, broadly applicable cfDNA-based precision oncology for patients with advanced cancer through scalable identification of therapeutically relevant CNAs and pre-/post-treatment genomic profiles, enabling cfDNA- or tissue-based precision oncology workflow optimization

Rapid, ultra low coverage copy number profiling of cell-free DNA as a precision oncology screening strategy.

Current cell-free DNA (cfDNA) next generation sequencing (NGS) precision oncology workflows are typically limited to targeted and/or disease-specific applications. In advanced cancer, disease burden and cfDNA tumor content are often elevated, yielding unique precision oncology opportunities. We sought to demonstrate the utility of a pan-cancer, rapid, inexpensive, whole genome NGS of cfDNA approach (PRINCe) as a precision oncology screening strategy via ultra-low coverage (~0.01x) tumor content determination through genome-wide copy number alteration (CNA) profiling. We applied PRINCe to a retrospective cohort of 124 cfDNA samples from 100 patients with advanced cancers, including 76 men with metastatic castration-resistant prostate cancer (mCRPC), enabling cfDNA tumor content approximation and actionable focal CNA detection, while facilitating concordance analyses between cfDNA and tissue-based NGS profiles and assessment of cfDNA alteration associations with mCRPC treatment outcomes. Therapeutically relevant focal CNAs were present in 42 (34%) cfDNA samples, including 36 of 93 (39%) mCRPC patient samples harboring AR amplification. PRINCe identified pre-treatment cfDNA CNA profiles facilitating disease monitoring. Combining PRINCe with routine targeted NGS of cfDNA enabled mutation and CNA assessment with coverages tuned to cfDNA tumor content. In mCRPC, genome-wide PRINCe cfDNA and matched tissue CNA profiles showed high concordance (median Pearson correlation = 0.87), and PRINCe detectable AR amplifications predicted reduced time on therapy, independent of therapy type (Kaplan-Meier log-rank test, chi-square = 24.9, p < 0.0001). Our screening approach enables robust, broadly applicable cfDNA-based precision oncology for patients with advanced cancer through scalable identification of therapeutically relevant CNAs and pre-/post-treatment genomic profiles, enabling cfDNA- or tissue-based precision oncology workflow optimization