Novel modes of MPL activation in triple-negative myeloproliferative neoplasms.

The identification of a somatic mutation associated with myeloid malignancy is of diagnostic importance in myeloproliferative neoplasms (MPNs). Individuals with no mutation detected in common screening tests for variants in JAK2, CALR, and MPL are described as 'triple-negative' and pose a diagnostic challenge if there is no other evidence of a clonal disorder. To identify potential drivers that might explain the clinical phenotype, we used an extended sequencing panel to characterise a cohort of 44 previously diagnosed triple-negative MPN patients for canonical mutations in JAK2, MPL and CALR at low variant allele frequency (found in 4/44 patients), less common variants in the JAK-STAT signalling pathway (12 patients), or other variants in recurrently mutated genes from myeloid malignancies (18 patients), including hotspot variants of potential clinical relevance in eight patients. In one patient with thrombocytosis we identified biallelic germline MPL variants. Neither MPL variant was activating in cell proliferation assays, and one of the variants was not expressed on the cell surface, yet co-expression of both variants led to thrombopoietin hypersensitivity. Our results highlight the clinical value of extended sequencing including germline variant analysis and illustrate the need for detailed functional assays to determine whether rare variants in JAK2 or MPL are pathogenic.

Targeted gene panels identify a high frequency of pathogenic germline variants in patients diagnosed with a hematological malignancy and at least one other independent cancer.

The majority of studies assessing the contribution of pathogenic germline variants (PGVs) to cancer predisposition have focused on patients with single cancers. We analyzed 45 known cancer predisposition genes (CPGs) in germline samples of 202 patients with hematological malignancies (HMs) plus one or more other independent cancer managed at major tertiary medical centers on two different continents. This included 120 patients with therapy-related myeloid neoplasms (t-MNs), where the HM occurred after cytotoxic treatment for a first malignancy, and 82 patients with multiple cancers in which the HM was not preceded by cytotoxic therapy (MC-HM). Using American College of Medical Genetics/Association for Molecular Pathology variant classification guidelines, 13% of patients had PGVs, most frequently identified in CHEK2 (17% of PGVs), BRCA1 (13%), DDX41 (13%), and TP53 (7%). The frequency of PGVs in MC-HM was higher than in t-MN, although not statistically significant (18 vs. 9%; p = 0.085). The frequency of PGVs in lymphoid and myeloid HM patients was similar (19 vs. 17.5%; p > 0.9). Critically, patients with PGVs in BRCA1, BRCA2 or TP53 did not satisfy current clinical phenotypic criteria for germline testing. Our data suggest that a personal history of multiple cancers, one being a HM, should trigger screening for PGVs.

The mutational burden of therapy-related myeloid neoplasms is similar to primary myelodysplastic syndrome but has a distinctive distribution.

Therapy-related myeloid neoplasms (T-MN) are poorly characterized secondary hematological malignancies following chemotherapy/radiotherapy exposure. We compared the clinical and mutational characteristics of T-MN (n = 129) and primary myelodysplastic syndrome (P-MDS, n = 108) patients. Although the somatic mutation frequency was similar between T-MN and P-MDS patients (93% in both groups), the pattern was distinct. TP53 mutations were more frequent in T-MN (29.5 vs. 7%), while spliceosomal complex mutations were more common in P-MDS (56.5 vs. 25.6%). In contrast to P-MDS, the ring sideroblasts (RS) phenotype was not associated with better survival in T-MN, most probably due to genetic association with TP53 mutations. SF3B1 was mutated in 96% of P-MDS with ≥15% RS, but in only 32% T-MN. TP53 mutations were detected in 92% T-MN with ≥15% RS and SF3B1 wild-type cases. Interestingly, T-MN and P-MDS patients with "Very low" or "Low" Revised International Prognostic Scoring System (IPSS-R) showed similar biological and clinical characteristics. In a Cox regression analysis, TP53 mutation was a poor prognostic factor in T-MN, independent of IPSS-R cytogenetics, disease-modifying therapy, and NRAS mutation. Our data have direct implications for T-MN management and provide evidence that, in addition to conventional disease parameters, mutational analysis should be incorporated in T-MN risk stratification.

Integrative genomic analysis reveals cancer-associated mutations at diagnosis of CML in patients with high-risk disease.

Genomic events associated with poor outcome in chronic myeloid leukemia (CML) are poorly understood. We performed whole-exome sequencing, copy-number variation, and/or RNA sequencing for 65 patients to discover mutations at diagnosis and blast crisis (BC). Forty-six patients with chronic-phase disease with the extremes of outcome were studied at diagnosis. Cancer gene variants were detected in 15 (56%) of 27 patients with subsequent BC or poor outcome and in 3 (16%) of 19 optimal responders (P = .007). Frequently mutated genes at diagnosis were ASXL1, IKZF1, and RUNX1 The methyltransferase SETD1B was a novel recurrently mutated gene. A novel class of variant associated with the Philadelphia (Ph) translocation was detected at diagnosis in 11 (24%) of 46 patients comprising fusions and/or rearrangement of genes on the translocated chromosomes, with evidence of fragmentation, inversion, and imperfect sequence reassembly. These were more frequent at diagnosis in patients with poor outcome: 9 (33%) of 27 vs 2 (11%) of 19 optimal responders (P = .07). Thirty-nine patients were tested at BC, and all had cancer gene variants, including ABL1 kinase domain mutations in 58%. However, ABL1 mutations cooccurred with other mutated cancer genes in 89% of cases, and these predated ABL1 mutations in 62% of evaluable patients. Gene fusions not associated with the Ph translocation occurred in 42% of patients at BC and commonly involved fusion partners that were known cancer genes (78%). Genomic analysis revealed numerous relevant variants at diagnosis in patients with poor outcome and all patients at BC. Future refined biomarker testing of specific variants will likely provide prognostic information to facilitate a risk-adapted therapeutic approach.

ASXL1 and BIM germ line variants predict response and identify CML patients with the greatest risk of imatinib failure.

Scoring systems used at diagnosis of chronic myeloid leukemia (CML), such as Sokal risk, provide important response prediction for patients treated with imatinib. However, the sensitivity and specificity of scoring systems could be enhanced for improved identification of patients with the highest risk. We aimed to identify genomic predictive biomarkers of imatinib response at diagnosis to aid selection of first-line therapy. Targeted amplicon sequencing was performed to determine the germ line variant profile in 517 and 79 patients treated with first-line imatinib and nilotinib, respectively. The Sokal score and ASXL1 rs4911231 and BIM rs686952 variants were independent predictors of early molecular response (MR), major MR, deep MRs (MR4 and MR4.5), and failure-free survival (FFS) with imatinib treatment. In contrast, the ASXL1 and BIM variants did not consistently predict MR or FFS with nilotinib treatment. In the imatinib-treated cohort, neither Sokal or the ASXL1 and BIM variants predicted overall survival (OS) or progression to accelerated phase or blast crisis (AP/BC). The Sokal risk score was combined with the ASXL1 and BIM variants in a classification tree model to predict imatinib response. The model distinguished an ultra-high-risk group, representing 10% of patients, that predicted inferior OS (88% vs 97%; P = .041), progression to AP/BC (12% vs 1%; P = .034), FFS (P < .001), and MRs (P < .001). The ultra-high-risk patients may be candidates for more potent or combination first-line therapy. These data suggest that germ line genetic variation contributes to the heterogeneity of response to imatinib and may contribute to a prognostic risk score that allows early optimization of therapy.

BAM-matcher: a tool for rapid NGS sample matching.

UNLABELLED: The standard method used by high-throughput genome sequencing facilities for detecting mislabelled samples is to use independently generated high-density SNP data to determine sample identity. However, as it has now become commonplace to have multiple samples sequenced from the same source, such as for analysis of somatic variants using matched tumour and normal samples, we can directly use the genotype information inherent in the sequence data to match samples and thus bypass the need for additional laboratory testing. Here we present BAM-matcher, a tool that can rapidly determine whether two BAM files represent samples from the same biological source by comparing their genotypes. BAM-matcher is designed to be simple to use, provides easily interpretable results, and is suitable for deployment at early stages of data processing pipelines. AVAILABILITY AND IMPLEMENTATION: BAM-matcher is licensed under the Creative Commons by Attribution license, and is available from: https://bitbucket.org/sacgf/bam-matcher SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. CONTACT: paul.wang@sa.gov.au.

The impact of multiple low-level BCR-ABL1 mutations on response to ponatinib.

The third-generation tyrosine kinase inhibitor (TKI) ponatinib shows activity against all common BCR-ABL1 single mutants, including the highly resistant BCR-ABL1-T315I mutant, improving outcome for patients with refractory chronic myeloid leukemia (CML). However, responses are variable, and causal baseline factors have not been well-studied. The type and number of low-level BCR-ABL1 mutations present after imatinib resistance has prognostic significance for subsequent treatment with nilotinib or dasatinib as second-line therapy. We therefore investigated the impact of low-level mutations detected by sensitive mass-spectrometry before ponatinib initiation (baseline) on treatment response in 363 TKI-resistant patients enrolled in the PONATINIB for Chronic Myeloid Leukemia Evaluation and Ph(+)Acute Lymphoblastic Leukemia trial, including 231 patients in chronic phase (CP-CML). Low-level mutations were detected in 53 patients (15%, including low-level T315I in 14 patients); most, however, did not undergo clonal expansion during ponatinib treatment and, moreover, no specific individual mutations were associated with inferior outcome. We demonstrate however, that the number of mutations detectable by mass spectrometry after TKI resistance is associated with response to ponatinib treatment and could be used to refine the therapeutic approach. Although CP-CML patients with T315I (63/231, 27%) had superior responses overall, those with multiple mutations detectable by mass spectrometry (20, 32%) had substantially inferior responses compared with those with T315I as the sole mutation detected (43, 68%). In contrast, for CP-CML patients without T315I, the inferior responses previously observed with nilotinib/dasatinib therapy for imatinib-resistant patients with multiple mutations were not seen with ponatinib treatment, suggesting that ponatinib may prove to be particularly advantageous for patients with multiple mutations detectable by mass spectrometry after TKI resistance.

Compound mutations in BCR-ABL1 are not major drivers of primary or secondary resistance to ponatinib in CP-CML patients.

BCR-ABL1 kinase domain mutations can confer resistance to first- and second-generation tyrosine kinase inhibitors (TKIs) in chronic myeloid leukemia (CML). In preclinical studies, clinically achievable concentrations of the third-generation BCR-ABL1 TKI ponatinib inhibit T315I and all other single BCR-ABL1 mutants except T315M, which generates a single amino acid exchange, but requires 2 sequential nucleotide exchanges. In addition, certain compound mutants (containing ≥2 mutations in cis) confer resistance. Initial analyses based largely on conventional Sanger sequencing (SS) have suggested that the preclinical relationship between BCR-ABL1 mutation status and ponatinib efficacy is generally recapitulated in patients receiving therapy. Thus far, however, such analyses have been limited by the inability of SS to definitively identify compound mutations or mutations representing less than ~20% of total alleles (referred to as "low-level mutations"), as well as limited patient follow-up. Here we used next-generation sequencing (NGS) to define the baseline BCR-ABL1 mutation status of 267 heavily pretreated chronic phase (CP)-CML patients from the PACE trial, and used SS to identify clonally dominant mutants that may have developed on ponatinib therapy (30.1 months median follow-up). Durable cytogenetic and molecular responses were observed irrespective of baseline mutation status and included patients with compound mutations. No single or compound mutation was identified that consistently conferred primary and/or secondary resistance to ponatinib in CP-CML patients. Ponatinib is effective in CP-CML irrespective of baseline mutation status.

Prognosis for patients with CML and >10% BCR-ABL1 after 3 months of imatinib depends on the rate of BCR-ABL1 decline.

In chronic myeloid leukemia (CML) patients, a breakpoint cluster region-Abelson (BCR-ABL1) value >10% at 3 months of therapy is statistically associated with poorer outcome, yet many of these patients still achieve satisfactory outcomes. We investigated 528 first-line imatinib-treated patients to determine whether patients with the poorest outcome can be better discriminated at 3 months. All outcomes were significantly superior for the 410 patients with BCR-ABL1 ≤10% at 3 months (P < .001). However, the poorest outcomes among the 95 evaluable patients with BCR-ABL1 >10% at 3 months were identified by the rate of BCR-ABL1 decline from baseline, assessed by estimating the number of days over which BCR-ABL1 halved. Patients with BCR-ABL1 halving time <76 days (n = 74) had significantly superior outcomes compared with patients whose BCR-ABL1 values did not halve by 76 days (n = 21; 4-year overall survival, 95% vs 58%, P = .0002; progression-free survival, 92% vs 63%, P = .008; failure-free survival, 59% vs 6%, P < .0001; and major molecular response, 54% vs 5%, P = .008). By multivariate analysis, the halving time was an independent predictor of outcome in this poor risk group. Our study highlighted that the rate of BCR-ABL1 decline may be a critical prognostic discriminator of the patients with very poor outcome among those >10% at 3 months. The International Randomized IFN vs STI571 (IRIS) trial was registered at http://www.clinicaltrials.gov as #NCT00006343. The Tyrosine Kinase Inhibitor Optimization and Selectivity (TOPS) trial was registered at http://www.clinicaltrials.gov as #NCT00124748. The Therapeutic Intensification in DE-novo Leukaemia (TIDEL) I trial was registered at http://www.ANZCTR.org.au as #ACTRN12607000614493. The TIDEL II trial was registered at http://www.ANZCTR.org.au as #ACTRN12607000325404.

A comparative analysis of algorithms for somatic SNV detection in cancer.

MOTIVATION: With the advent of relatively affordable high-throughput technologies, DNA sequencing of cancers is now common practice in cancer research projects and will be increasingly used in clinical practice to inform diagnosis and treatment. Somatic (cancer-only) single nucleotide variants (SNVs) are the simplest class of mutation, yet their identification in DNA sequencing data is confounded by germline polymorphisms, tumour heterogeneity and sequencing and analysis errors. Four recently published algorithms for the detection of somatic SNV sites in matched cancer-normal sequencing datasets are VarScan, SomaticSniper, JointSNVMix and Strelka. In this analysis, we apply these four SNV calling algorithms to cancer-normal Illumina exome sequencing of a chronic myeloid leukaemia (CML) patient. The candidate SNV sites returned by each algorithm are filtered to remove likely false positives, then characterized and compared to investigate the strengths and weaknesses of each SNV calling algorithm. RESULTS: Comparing the candidate SNV sets returned by VarScan, SomaticSniper, JointSNVMix2 and Strelka revealed substantial differences with respect to the number and character of sites returned; the somatic probability scores assigned to the same sites; their susceptibility to various sources of noise; and their sensitivities to low-allelic-fraction candidates. AVAILABILITY: Data accession number SRA081939, code at http://code.google.com/p/snv-caller-review/ CONTACT: david.adelson@adelaide.edu.au SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Poor response to second-line kinase inhibitors in chronic myeloid leukemia patients with multiple low-level mutations, irrespective of their resistance profile.

Specific imatinib-resistant BCR-ABL1 mutations (Y253H, E255K/V, T315I, F317L, and F359V/C) predict failure of second-line nilotinib or dasatinib therapy in patients with chronic myeloid leukemia; however, such therapy also fails in approximately 40% of patients in the chronic phase of this disease who do not have these resistant mutations. We investigated whether sensitive mutation analysis could identify other poor-risk subgroups. Analysis was performed by direct sequencing and sensitive mass spectrometry on 220 imatinib-resistant patients before they began nilotinib or dasatinib therapy. Patients with resistant mutations by either method (n = 45) were excluded because inferior response was known. Of the remaining 175 patients, 19% had multiple mutations by mass spectrometry versus 9% by sequencing. Compared with 0 or 1 mutation, the presence of multiple mutations was associated with lower rates of complete cytogenetic response (50% vs 21%, P = .003) and major molecular response (31% vs 6%, P = .005) and a higher rate of new resistant mutations (25% vs 56%, P = .0009). Sensitive mutation analysis identified a poor-risk subgroup (15.5% of all patients) with multiple mutations not identified by standard screening.

Sensitive detection of BCR-ABL1 mutations in patients with chronic myeloid leukemia after imatinib resistance is predictive of outcome during subsequent therapy.

PURPOSE: BCR-ABL1 mutation analysis is recommended to facilitate selection of appropriate therapy for patients with chronic myeloid leukemia after treatment with imatinib has failed, since some frequently occurring mutations confer clinical resistance to nilotinib and/or dasatinib. However, mutations could be present below the detection limit of conventional direct sequencing. We developed a sensitive, multiplexed mass spectrometry assay (detection limit, 0.05% to 0.5%) to determine the impact of low-level mutations after imatinib treatment has failed. PATIENTS AND METHODS: Mutation status was assessed in 220 patients treated with nilotinib or dasatinib after they experienced resistance to imatinib. RESULTS: Mutations were detected by sequencing in 128 patients before commencing nilotinib or dasatinib therapy (switchover). In 64 patients, 132 additional low-level mutations were detected by mass spectrometry alone (50 of 132 mutations were resistant to nilotinib and/or dasatinib). When patients received the inhibitor for which the mutation confers resistance, 84% of the low-level resistant mutations rapidly became dominant clones detectable by sequencing, including 11 of 12 T315I mutations. Subsequent complete cytogenetic response rates were lower for patients with resistant mutations at switchover detected by sequencing (0%) or mass spectrometry alone (16%) compared with patients with other mutations or no mutations (41% and 49%, respectively; P < .001). Failure-free survival among the 100 patients with chronic phase chronic myeloid leukemia when resistant mutations were detected at switchover by sequencing or mass spectrometry alone was 0% and 0% compared with 51% and 45% for patients with other mutations or no mutations (P = .003). CONCLUSION: Detection of low-level mutations after imatinib resistance offers critical information to guide subsequent therapy selection. If an inappropriate kinase inhibitor is selected, there is a high risk of treatment failure with clonal expansion of the resistant mutant.

Molecular methods in diagnosis and monitoring of haematological malignancies.

The use of the polymerase chain reaction (PCR) was a revolutionary step in molecular biology, allowing for small amounts of genetic material to be amplified and studied. The advent of real-time PCR was a further refinement that led to reliable quantification of RNA and DNA. This allowed response monitoring and the detection of minimal residual disease, which proved to have important correlations with outcome in certain malignancies. The technology is indispensable for physicians and pathologists caring for oncology patients. In this article we will review the applications of molecular technology in the diagnosis and management of malignancies. Using chronic myeloid leukaemia (CML) as an example, technical aspects and clinical correlations will be discussed, with emphasis on the importance of quality assurance and standardisation to allow for comparability of results across laboratories. We will also examine emerging technologies that allow for high throughput and rapid turnaround of specimens and speculate how these would affect outcomes in future health care. The established and emerging molecular technologies have applications in many fields of oncology.

Tyrosine kinase inhibitor resistance in chronic myeloid leukemia cell lines: investigating resistance pathways.

There are three currently identified secondary resistance mechanisms observed in patients with chronic myeloid leukemia (CML) receiving tyrosine kinase inhibitors (TKIs). These are BCR-ABL kinase domain (KD) mutations, increased BCR-ABL expression, and overexpression of drug-efflux proteins (ABCB1 and ABCG2). To investigate the interplay between these three modes of resistance, three CML blast crisis cell lines (K562, its ABCB1-overexpressing variant K562 Dox, and KU812) were cultured in gradually increasing concentrations of imatinib to 2 µM, or dasatinib to 200 nM. Eight imatinib- and two dasatinib-resistant cell lines were established. Two imatinib-resistant K562 lines both had increased BCR-ABL expression as the apparent mode of resistance. However, when a dasatinib-resistant K562 culture was generated we observed gradually increasing BCR-ABL expression which peaked prior to identification of the T315I mutation. BCR-ABL overexpression followed by mutation development was observed in a further 4/10 cell lines, each with different KD mutations. In contrast, three imatinib-resistant K562 Dox lines exhibited only a further increase in ABCB1 expression. All TKI-resistant cell lines generated had increased IC(50) (dose of drug required to reduce phosphorylation of the adaptor protein p-Crkl by 50%) to imatinib, dasatinib, and nilotinib, regardless of which TKI was used to induce resistance. This suggests that currently available TKIs share the same susceptibilities to drug resistance.