Background: The recent advances in molecular techniques and the adaptation of next generation sequencing (NGS) in routine clinical testing increased our ability to use molecular approaches in the ...diagnosis and classification of most hematologic diseases. Bone marrow aspiration and biopsy remains necessary for initial confirmation of diagnosis of neoplastic processes in bone marrow, but significant literature suggests that screening or monitoring patients by testing peripheral bloodcfDNAmight be a reliable alternative to marrow biopsy and might reduce the need for a painful bone marrow procedure. Here we report the results of routine clinical testing ofcfDNAthat is ordered by practicing hematologist in the context of the presence or the suspicion of the presence of hematologic neoplasm.
Methods: A total of 227 peripheral blood samples were submitted for screeningcfDNAfor mutations in a 54 gene focusedMyeloidpanel using NGS sequencing. DNA was extracted from plasma usingNucliSenSEasyMAGautomated platform and then assayed using theTruSightMyeloid Sequencing Panel (Illumina; San Diego, CA) with an average sequencing depth of 10,000X. The average age patients was 71 (18-96) years. The reason for submitting samples wasruling out MDS in 199 and ruling out AML or other hematologic neoplasms in 28 samples. Of these samples, 12 patients had a follow up testing of bone marrow aspiration sample.
Results: Of the 227 tested samples (Figure 1), 126 (55%) showed no evidence of mutation in any of the tested genes. Based on our previous data (see ASH abstract by Albitar et al, 2016), this suggested that MDS can be ruled out in these patients and bone marrow biopsy could be avoided and not recommended. In contrast, 101 (45%) had mutations in one or more genes. Twenty-nine (~12.8%) contained a mutation in a single gene with variant allele frequency (VAF) <20% in one gene and were considered not diagnostic for the presence of clinically significant hematologic neoplasm, but follow up was recommended. Of these patients, one had a mutation in JAK2 at VAF of 6% and a second had a mutation in CALR gene at VAF of 7%, which most likely suggest the presence of early evolvingmyeloproliferativeneoplasms. Seventy-four patients (33%) had mutations in two or more genes or in one gene but with VAF≥20% and considered diagnostic for the presence of hematologic neoplasm and bone marrow morphologic evaluation was recommended. The most commonly mutated gene in these patents was TET2, detected in 30 samples, of which 8 also showed a second mutation in TET2, followed by ASXL1, and DNMT3A mutated in 24 and 26 samples, respectively. Samples containing a TET2 mutation were more likely to have a second mutation in TET2 or another gene, in contrast other genes that were frequently mutated did not show this trend (see Figure). TP53 gene was mutated in 16 samples, 7 of which as a single abnormality with VAF <20% therefore was reported as of unknown significance and recommended ruling out neoplasms in hematologic (lymphoid and myeloid) as well as solid tumors. SF3B1 gene mutations were detected in 19 samples and recommended ruling out refractory anemia with ringsideroblasts(RARS). Despite the small sampling (12 samples), follow up usingcfDNAtesting reliably recapitulated original bone marrow Biopsy’s findings. In one patient, additionalsubcloneswere detected incfDNAthat were not detected in the bone marrow aspirate.
Conclusions:cfDNAtesting is reliable approach to screen for the presence of Hematologic neoplasm and potentially could avoid the need for bone marrow biopsy in almost half the patients expected to have MDS or otherhematopoeticneoplasms. Positive diagnosis can be confirmed in additional 45% of patients and only 12.8% of patients will be reported with questionable results. Except for those with TP53 mutations, the rest of the 12.8% cases can be classified as Clonal Hematopoiesis of Indeterminate Potential (CHIP). While bone marrow is still the gold standard, our real world experience shows liquid biopsies can be sensitive and non-invasive approach to rule out MDS or other hematological diseases.
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Funari:NeoGenomics Laboratories: Employment. Ma:Neogenomics Laboratories: Employment. Thangavelu:Neogenomics Laboratories: Employment. De Dios:Neogenomics Laboratories: Employment. Albitar:Neogenomics Laboratories: Employment, Equity Ownership.
Background:We have reported that peripheral blood cell-free DNA (cfDNA) is reliable for detecting bone marrow molecular abnormalities in patients with hematologic neoplasms. However, not clear is ...whether cfDNA is sufficient to detect mutations present at low variant allele frequency (VAF). Since patients with aplastic anemia (AA usually have relatively small clones in blood and bone marrow (BM), we compared mutations detected in BM cells with those detected in peripheral blood cfDNA from patientswith this disease.
Methods: A total of 120 paired BM aspirate and PB plasma samples were tested by the commercially available TruSight Myeloid Sequencing Panel (Illumina; San Diego, CA). We extracted DNA from bone marrow aspirate using the QIAamp DNA Mini Kit. We used NucliSenS EasyMAG automated platform for extracting total nucleic acid from PB plasma collected in EDTA. All paired BM and plasma samples were tested by the commercially available TruSight Myeloid Sequencing Panel (Illumina; San Diego, CA), which covers hot spot mutations in 54 genes. The average depth of sequencing was 10,000X.
Results: One hundred twenty paired BM and cfDNA samples from 96 patients with aplastic anemia were tested. Of the 96 patients, 33 (34%; equivalent to 48 samples, 40%) had one or more mutations. We identified 54 different somatic mutations in these patients, of which 45 were unique. There was no significant difference (P=0.71, Sign test) in allele frequency between cfDNA and BM. The median mutant allele frequency was 10.9% in cfDNA and 12.6% in BM cells, and 40 of the 54 mutations had allele frequency ≤20% in BM cells, while 45 samples had allele frequency ≤20 in cfDNA. Six of the 33 patients with somatic mutations (18%) showed mutations in plasma cfDNA but not in BM. In contrast, 2 patients (6%) showed mutations in BM cells and not in cfDNA. One of these two patients had a mutation in ASXL1 gene detected in BM cells but not in cfDNA and a subsequent sample showed the same ASXL1mutation in BM cells and not in cfDNA, and a second clone with a different ASXL1 mutation detected in both BM cells and cfDNA. Overall concordance between BM cells and cfDNA in the 120 samples was 92% and there was no statistically significant difference between the two sample types (P=0.6).
Summary and Conclusions: Seven samples (from 7 patients) of the 120 tested samples showed mutations in cfDNA and not in BM cells while 3 samples (from 2 patients) showed mutations in BM and not in cfDNA. VAF of mutations in cfDNA were similar to those in BM cells. Therefore, peripheral blood cfDNA should be tested in addition to BM cells for detecting mutations in patients with AA. Peripheral blood cfDNA can be used as a reliable means for monitoring patients with AA. cfDNA testing can be used as an alternative testing to bone marrow even when mutant allele frequency in bone marrow is <20%. cfDNA may be an especially valuable source of mutation detection in marrow failure, in which marrow aspirates may not contain sufficient cells for accurate mutation analysis.
Albitar:Neogenomics Laboratories: Employment. Townsley:Novartis: Research Funding. Ma:Neogenomics Laboratories: Employment. De Dios:Neogenomics Laboratories: Employment. Funari:Neogenomics Laboratories: Employment. Young:GSK/Novartis: Research Funding. Albitar:Neogenomics Laboratories: Employment, Equity Ownership.
Introduction: Clonal hematopoiesis, as determined by the presence of TET2, ASXL1, and DNMT3 mutation, is believed to be increasingly common in normal individuals as they age. This phenomenon is ...currently referred to as clonal hematopoiesis of indeterminate potential (CHIP). It has been reported that a few of these patients will develop myeloid neoplasms that begin as MDS and may evolve into AML. However, the clinical relevance of this particular subset of gene mutations (TET2, ASXL1, and DNMT3A) in healthy individuals is unclear as there are more than 50 genes that have been reported to be involved in myeloid neoplasms.
FLT3 and NPM1 mutations have been reported in de novo AML patients and may occur as a secondary mutations on an MDS background. In order to clarify the significance of TET2, ASXL1, and DNMT3 in CHIP and their relationship to MDS and AML, we assessed the prevalence of TET2, ASXL1, and DNMT3 genes in patients with NPM1 and FLT3 mutations. In addition, since IDH1/2 gene are rarely mutated with TET2, we also studied the frequency of mutations of various myeloid genes in this group of patients.
Methods: A total of 6390 consecutive bone marrow aspirate samples or peripheral blood samples submitted with clinical impression of AML, MDS, or MPN between January 2014 and mid 2017 were tested for mutations in myeloid genes using NGS. We used the TruSight Myeloid Panel (Illumina, San Diego, CA) for detecting missense mutations and fragment length analysis (FLA) for detecting ITD in FLT3 and large indels in CALR . DNA was extracted from samples using the QIAamp DNA Mini Kit. This NGS testing covers mutations in 54 myeloid-related genes. The average depth of sequencing was 10,000x.
Results: In our database of consecutively tested patients, there were 311 patients with FLT3 mutations, 318 patients with NPM1 mutation, and 467 patients with IDH1/2 mutation. In addition, there were 308 patients diagnosed as MDS. All these patients tested for mutations in all 54 myeloid-related genes. The median age of patients in FLT3, MDS, IDH1/2, and NPM1 groups was 65, 75, 69, and 66, respectively. The top 4 most frequently mutated in genes in the FLT3 -positive patients, which present AML, were NPM1, DNMT3, WT1, and RUNX1 . In patients with NPM1 mutations, also representing AML, the top 4 most mutated genes were FLT3, IDH2, NRAS, and PTPN11 . In the IDH1/2 mutated patients, the top 4 mutated genes were DNMT3A, SRSF2, ASXL1, and NPM1 . As expected in the MDS group, the top 4 mutated genes were TET2, DNMT3A, ASXL1, and SRSF2 .
Conclusions: The demonstration that mutations in TET2, DNMT3A, and ASXL1 are most common in patients presenting with MDS, as well as in CHIP, but not in patients presenting with acute myeloid neoplasms, suggests that CHIP likely represents early MDS. It is possible that mutations in these genes in few hematopoietic cells may not be adequate for manifestation of clinical MDS, but the presence of these mutations in large number of cells (high VAF) or the accumulation of mutations in additional genes is necessary for clinical disease. Therefore the clinical relevance of CHIP should always be considered in conjunction with other mutations and with VAF.
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Ma:NeoGenomics: Employment. De Dios:NeoGenomics: Employment. Funari:NeoGenomics: Employment. Sudarsanam:NeoGenomics: Employment. Jiang:NeoGenomics: Employment. Agersborg:NeoGenomics: Employment. Hummel:NeoGenomics: Employment. Blocker:NeoGenomics: Employment. Albitar:NeoGenomics: Employment.
Cytopenia is common in cause for considering the diagnosis of myelodysplastic syndrome (MDS), especially in the elderly population. To diagnose the presence or absence of MDS, bone marrow biopsy is ...performed on most patients with cytopenia. Performing bone marrow biopsy is a painful procedure and can be associated with bleeding and other complications. Moreover, bone marrow morphology is unreliable for the diagnosis of MDS. Cytogenetics and molecular studies can provide conclusive evidence for the diagnosis of MDS. Liquid biopsy and testing for molecular abnormalities in cfDNA in peripheral blood plasma is significantly less invasive than traditional bone marrow testing. We evaluated the diagnostic value of liquid biopsy in determining the presence of MDS in 640 patients presented in community setting practice with cytopenia.
Methodology: A total of 640 peripheral blood samples from patients with cytopenia were submitted for cfDNA testing. We used the TruSight Myeloid panel (Illumina, San Diego, CA) for detecting missense mutations and fragment length analysis (FLA) for detecting ITD in FLT3 and large indels in CALR . DNA was extracted from samples using the QIAamp DNA Mini Kit. This next generation sequencing (NGS) testing covers mutations in 54 myeloid-related genes. The average depth of sequencing was 10,000x.
Results: Of the 640 tested patients, 310 (48.4%) showed mutations in one or more genes: 38% of these had mutations in one gene, 25.5% had mutations in two genes, and 36.5% had mutations in more than two genes. However, 14% of cases with mutation in one gene had two or more mutant subclones. The median age of all patients was 69 (range: 15-99) and 55% were males. Patients with mutations were significantly older (75 vs. 66 years old, P<0.0001) and more likely to be males (60% vs. 46% males, P=0.004). The most commonly mutated genes were TET2, DNMT3A, ASXL1, SRSF2, SF3B1, and RUNX1 detected in 31%, 28%, 25%, 17%, 15%, and 10% of the patients with mutations, respectively. Interestingly, 32 patients (10% of patients with any mutation) had mutations in TP53, 3% had mutations in FLT3, and 4% had mutations in NPM1 genes, indicating aggressive or acute disease. The average variant allele frequency (VAF) was <10% in 22% of cases with any mutation, between 10-20% in 19% of cases, between 20-30% in 16% of cases, and >40% in 43% of the cases. There was a significantly higher number of mutated genes in patients with average VAF >20% (P<0.0001). The combination of VAF, type of mutated gene, and number of mutated genes were considered in determining the significance of abnormal neoplastic clone and recommendation for management. The presence of mutations in NPM1, FLT3, TP53 as well as SF3B1 were considered diagnostic irrespective of the VAF. For patients with VAF at <20% in genes such as TET2, DNMT3A, and ASXL1 were not considered diagnostic for clinically significant myeloid neoplasm.
Conclusions: Liquid biopsy for evaluating patients with pancytopenia can be used to evaluate the presence of abnormal hematopoietic neoplasm clones and the severity of the disease. Liquid biopsy can reduce the need for bone marrow biopsy in more than 50% of patients presenting with cytopenia. VAF, mutated gene types, and the combination of mutated genes should be considered for making management decisions based on liquid biopsy.
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Ma:NeoGenomics: Employment. De Dios:NeoGenomics: Employment. Funari:NeoGenomics: Employment. Jiang:NeoGenomics: Employment. Agersborg:NeoGenomics: Employment. Hummel:NeoGenomics: Employment. Blocker:NeoGenomics: Employment. Albitar:NeoGenomics: Employment.
IDH1/2 genes normally regulate cellular metabolism and epigenetic expression. Mutations in IDH1/2 are believed to play a significant part in leukemogenesis, and inhibitors are in active development. ...IDH1/2 mutations are rarely the sole mutation in myeloid neoplasms and are frequently found with co-mutations in other genes. However, it is not clear if the IDH1/2 mutations are founder or progressor mutations. Determining whether an IDH1/2 mutation is a founder or progressor may have significant impact on therapy outcome. As founding mutations persist in subclones, targeting founding mutations is likely to result in the eradication of the leukemic clone, whereas targeting progressor mutations can only destroy the subclone and progeny. We used variant allele frequency (VAF) and next generation sequencing (NGS) to determine if IDH1/2 mutations are founding or progressor mutations and to characterize the co-mutational background for 6390 patients who presented with a clinical impression of myeloid neoplasm.
Methods: A total of 6390 consecutive bone marrow aspirate samples or peripheral blood samples submitted with clinical impression of AML, MDS, or MPN between January 2014 and mid 2017 were tested for mutations in myeloid genes using NGS. We used the TruSight Myeloid Panel (Illumina, San Diego, CA) for detecting missense mutations and fragment length analysis (FLA) for detecting ITD in FLT3 and large indels in CALR . DNA was extracted from samples using the QIAamp DNA Mini Kit. This NGS testing covers mutations in 54 myeloid-related genes. The average depth of sequencing was 10,000x.
Results: A total of 2670 (42%) of the tested samples showed a mutation in one or more of the tested genes. Of the samples with mutations 467 patients (17.5%) patients showed mutations in either IDH1 or IDH2 genes. IDH1 mutations were detected 185 (40%) and IDH2 was detected in 291 (62%) of these patients. Nine patients (2%) had mutations in both IDH1 and IDH2. To distinguish patients with IDH1/2 as a founder mutation vs. subsequent (progressor) mutation, we used a lower VAF of a 10% in IDH1 or IDH2 as compared with the average VAF of all genes as a cut-off. Using this criteria, we found patients 35 patients (19%) as a progressor in the IDH1 mutated group and 48 (16.5%) in the IDH2 mutated group as progressors. Only 12 patients (6.5%) of the IDH1 mutated patients and 11 (4%) of the IDH2 mutated patients had IDH1 or IDH2 as the sole mutated gene.
The most commonly co-mutated genes with IDH1/2 were DNMT3A, SRSF2, NPM1, ASXL1, and RUNX1 detected in 34%, 28%, 22%, 22%, and 20%, respectively. Mutations in TP53 and FLT3, which may have significant impact on therapy and outcome, were detected in 7% and 12% of patients, respectively. In patients with an IDH1/2 progressor mutation, there was significantly higher relative mutations in TP53 (P=0.03) and FLT-ITD (P=0.0001). The presence of mutations in TP53 and FLT-3 -ITD signify significantly more aggressive myeloid neoplasm or acute leukemia. In addition to the typical mutations in codon 132 of IDH1 and codons 140 and 132 in IDH2, we detected mutations by NGS in codons 100, 103, 109, and 183 in IDH1 and codon 173 in IDH2 .
Conclusion: IDH1/2 mutations are founding mutations in most myeloid neoplasms. However, 19% of patients with IDH1/2 mutations may have acquired their IDH1/2 mutations in a subclone. Majority of these patients have mutations in FLT-3-ITD and TP53 and may represent significantly more aggressive disease. Clinical studies are needed to determine the pattern of response to IDH1/2 inhibitors in patients with subclonal (progressor) mutation in IDH1/2 . The potential of selecting for the leukemic clone that lack IDH1/2 mutation should be considered. Complete molecular profiling rather than testing for mutations in IDH1/2 alone provides important information in the management and therapy of myeloid neoplasms.
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Ma:NeoGenomics: Employment. De Dios:NeoGenomics: Employment. Funari:NeoGenomics: Employment. Sudarsanam:NeoGenomics: Employment. Jiang:NeoGenomics: Employment. Agersborg:NeoGenomics: Employment. Hummel:NeoGenomics: Employment. Blocker:NeoGenomics: Employment. Albitar:NeoGenomics: Employment.
The receptor tyrosine kinase FLT3 gene is commonly mutated in acute myeloid leukemia (AML) and its mutation is associated with significantly more aggressive disease and poor outcome. However, in the ...co-presence of NPM1 mutation, the disease is less aggressive and is associated with better outcome. FLT3 inhibitor midostaurin (Rydapt; Novartis Pharmaceuticals, Inc.) was recently approved for patients with FLT3 mutations. While the presence ofa FLT3 mutation is commonly associated with AML,it can develop in less acute myeloid neoplasms, such as MDS and CMML, and implies transformation into more acute phase. In this context, the FLT3 mutation is typically detected in a subclone of the original chronic myeloid clone. The prevalence of subclonal FLT3 mutations is unknown, as is the clinical relevance of subclonal FLT3, especially when treated with FLT3 inhibitors. We used variant allele frequency (VAF) and next generation sequencing (NGS) to determine if FLT3 mutations are founding or secondary mutations and to characterize the co-mutational background in large number of consecutive patients who presented with a clinical impression of myeloid neoplasm.
Methods: A total of 6390 consecutive bone marrow aspirate samples or peripheral blood samples were submitted with clinical impression of AML, MDS, or MPN between January 2014 and mid 2017 were tested for mutations in myeloid genes using NGS. We used the TruSight Myeloid panel (Illumina, San Diego, CA) for detecting missense mutations and fragment length analysis (FLA) for detecting internal tandem repeat (ITD) in FLT3 . DNA was extracted from samples using the QIAamp DNA Mini Kit. This NGS testing covers mutations in 54 myeloid-related genes. The average depth of sequencing was 10,000x.
Results: A total of 2670 (42%) of the samples showed a mutation in one or more of the tested genes. Of the samples with mutations, FLT3 ITD and kinase domain (KD) mutations were detected in 313 (12%) patients. Of these patients, 208 (66.5%) had ITD and 117 (37.4%) had KD mutations. Twelve patients (3.8%) had both ITD and KD mutations. NPM1 mutation was detected in 138 (44%) of the patients. Most of FLT3 -KD mutations were in codon 835, but mutations in codons 836, 839, 842 and 845 were also found. Additionally, missense mutations in codons 576, 592, and 593 at the site of ITD were detected. To distinguish a FLT3 mutation as a founding mutation rather than a secondary mutation, we used a lower VAF of 10% as a cut-off. Using this approach, we found that 27% (115/313) of patients had secondary FLT3 mutations. Of these subclonal FLT3 mutants, NPM1 co-mutation was detected in 61 (53%) patients, but was not statistically significant (P=0.06). Patients with FLT3 mutation as a subclone had a significantly higher number of co-mutated genes (P-value <0.0001). This group of patients had higher (P≤0.01) mutations in TET2, DNMT3A, NRAS, IDH2, EZH2, and BCOR, consistent with an MDS/CMML background. On the other hand, patients with both FLT3 and NPM1 mutations had a significantly lower number of co-mutant genes (P<0.0001) and particularly lower (P≤0.01) mutation rate in U2AF1, SF3B1, SRSF2, RUNX1, IDH1, BCOR, and AXL1 .
Conclusion: FLT3 mutations are frequently (27%) a secondary mutation in a subclone of the neoplastic founding mutations. This appears to be more common when FLT3 mutation is developing in a background of MDS/CMML. The co-presence of an NPM1 mutation is more commonly associated with fewer co-mutations in MDS-related genes. This data suggests that in addition to detecting ITD by FLA, using NGS for profiling mutations in FLT3 -KD and other myeloid genes should be considered whenever FLT3 mutations are evaluated. Further, the clinical decision for combination therapy should consider the entire mutation profile and not only mutations in FLT3 .
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Ma:NeoGenomics: Employment. De Dios:NeoGenomics: Employment. Funari:NeoGenomics: Employment. Sudarsanam:NeoGenomics: Employment. Jiang:NeoGenomics: Employment. Agersborg:NeoGenomics: Employment. Hummel:NeoGenomics: Employment. Blocker:NeoGenomics: Employment. Albitar:NeoGenomics: Employment.
Introduction: The principle of precision cancer medicine is to customize therapy based on the genomic profiles of the cancer and the host constitution/response to the cancer. Since RNA expression is ...influence by many genetic mechanisms, RNA profiling may provide broader coverage of genomic changes and might be a better predictor of response to therapy. However, incorporating the many biological changes of the host and the cancer in the decision of selecting therapeutic approach is not practical without using computer-aided algorithms. This is particularly relevant when combination therapy is used. We explored the potential of developing algorithms for the prediction of complete response (CR) to novel combination therapy in patients with acute myeloid leukemia (AML) using targeted RNA expression profiling.
Methods: RNA was extracted from the peripheral blood (PB) and bone marrow (BM) samples from patients with AML being treated on two different protocols: FLAG-IDA+venetoclax (F-I-V)( Abou Dalle I et al, ASH 2019; the NCT # is NCT03214562) and ivosidenib+venetoclax (I-V). In the initial study, 22 samples (9 PB and 13 BM) were used as training set. Subsequently 16 PB samples from the F-I-V arm and 4 from the I-V arm were collected and tested blindly as testing set after the development and locking of the algorithm. RNA was sequenced using NGS panel composed on compared of 1408 genes. The RNA sequencing is based on hybrid capture and the number of reads ranged from 5 to 10 million. RNA quantification was performed using Cufflinks. The RNA levels were normalized to ABL1 mRNA levels. Each gene is normalized by the mean and standard deviation of the gene. To develop a model for predicting CR, we used the training set in each arm and first evaluated the performance of each of the 1408 genes using receiver operating characteristic (ROC) curve. Then used the following mathematical methods for developing algorithms for predicting CR: Support Vector machine (SVM), Bayesian modeling with Gaussian Processes (GP), and Naïve Bayesian (NB).
Results: In univariate analysis, multiple genes showed very high AUC. In the F-I-V arm, top genes in predicting CR were GLI3, SETBP1, SH3D19, ARHGAP20, ETS1, IKZF2, GNG4 and MAGEE1 with AUC ranged from 0.74 to 0.85. In the I-V arm, the top genes in predicting CR were STL, TNFRSF10D, PTGS2, RET, TFRC, NAV3, WSB1, and GAS1 with AUC varied from 0.91 to 0.96. Using the training samples we developed algorithms for predicting CR by SVM, NB and Bayesian GP. Upon testing these models using leave-one-out (LOO), the three algorithms performed similarly with AUC around 0.97 for the I-V arm and around 0.96 for the F-I-V arm. There was no difference between BM and PB in predicting CR. Therefore, we collected and sequenced only peripheral blood for blind testing. The three algorithms were tested using 16 PB samples from the F-I-V arm and 4 samples from the I-V arm. The SVM and NB algorithms predicted CR correctly in 15 of the 16 samples (94%) while Bayesian GP missed 4 of the 16 samples. As for the I-V arm, the NB predicted CR correctly in the 4 samples, while both SVM and Bayesian GP missed 3 of 4.
Conclusions: While the data is limited and further validation is need, algorithms using RNA expression profiling of peripheral blood using targeted RNA NGS may provide an excellent tool for customizing therapeutic approach, especially in the age of combination therapy when number of cases for training can be limited. Furthermore, this study suggests that modeling using Nave Bayesian is reliable approach in developing prediction algorithms.
Albitar:Genomic Testing Ccoperative: Employment, Equity Ownership. Konopleva:Reata Pharmaceuticals: Equity Ownership, Patents & Royalties; Ascentage: Research Funding; Kisoji: Consultancy, Honoraria; Ablynx: Research Funding; Agios: Research Funding; Amgen: Consultancy, Honoraria; F. Hoffman La-Roche: Consultancy, Honoraria, Research Funding; Genentech: Honoraria, Research Funding; Astra Zeneca: Research Funding; Calithera: Research Funding; Stemline Therapeutics: Consultancy, Honoraria, Research Funding; Forty-Seven: Consultancy, Honoraria; Eli Lilly: Research Funding; AbbVie: Consultancy, Honoraria, Research Funding; Cellectis: Research Funding. Loghavi:MDACC: Employment; AlphaSights: Consultancy; GLG Consultants: Consultancy. Takahashi:Symbio Pharmaceuticals: Consultancy. Kantarjian:Daiichi-Sankyo: Research Funding; Ariad: Research Funding; Cyclacel: Research Funding; AbbVie: Honoraria, Research Funding; Agios: Honoraria, Research Funding; Amgen: Honoraria, Research Funding; BMS: Research Funding; Jazz Pharma: Research Funding; Novartis: Research Funding; Takeda: Honoraria; Pfizer: Honoraria, Research Funding; Immunogen: Research Funding; Actinium: Honoraria, Membership on an entity's Board of Directors or advisory committees; Astex: Research Funding. DiNardo:syros: Honoraria; daiichi sankyo: Honoraria; celgene: Consultancy, Honoraria; jazz: Honoraria; abbvie: Consultancy, Honoraria; agios: Consultancy, Honoraria; medimmune: Honoraria; notable labs: Membership on an entity's Board of Directors or advisory committees.
Since the first novel gene discovery for a Mendelian condition was made via exome sequencing (ES), the rapid increase in the number of genes known to underlie Mendelian conditions coupled with the ...adoption of exome (and more recently, genome) sequencing by diagnostic testing labs has changed the landscape of genomic testing for rare disease. Specifically, many individuals suspected to have a Mendelian condition are now routinely offered clinical ES. This commonly results in a precise genetic diagnosis but frequently overlooks the identification of novel candidate genes. Such candidates are also less likely to be identified in the absence of large-scale gene discovery research programs. Accordingly, clinical laboratories have both the opportunity, and some might argue a responsibility, to contribute to novel gene discovery which should in turn increase the diagnostic yield for many conditions. However, clinical diagnostic laboratories must necessarily balance priorities for throughput, turnaround time, cost efficiency, clinician preferences, and regulatory constraints, and often do not have the infrastructure or resources to effectively participate in either clinical translational or basic genome science research efforts. For these and other reasons, many laboratories have historically refrained from broadly sharing potentially pathogenic variants in novel genes via networks like Matchmaker Exchange, much less reporting such results to ordering providers. Efforts to report such results are further complicated by a lack of guidelines for clinical reporting and interpretation of variants in novel candidate genes. Nevertheless, there are myriad benefits for many stakeholders, including patients/families, clinicians, researchers, if clinical laboratories systematically and routinely identify, share, and report novel candidate genes. To facilitate this change in practice, we developed criteria for triaging, sharing, and reporting novel candidate genes that are most likely to be promptly validated as underlying a Mendelian condition and translated to use in clinical settings.
Background:
Homologous recombination deficiency (HRD) is the hallmark of breast cancer gene 1/2 (BRCA1/2)-mutated tumors and the unique biomarker for predicting response to double-strand break ...(DSB)–inducing drugs. The demonstration of HRD in tumors with mutations in genes other than BRCA1/2 is considered the best biomarker of potential response to these DSB-inducer drugs.
Objectives:
We explored the potential of developing a practical approach to predict in any tumor the presence of HRD that is similar to that seen in tumors with BRCA1/2 mutations using next-generation sequencing (NGS) along with machine learning (ML).
Design:
We use copy number alteration (CNA) generated from routine-targeted NGS data along with a modified naïve Bayesian model for the prediction of the presence of HRD.
Methods:
The CNA from NGS of 434 targeted genes was analyzed using CNVkit software to calculate the log2 of CNA changes. The log2 values of various sequencing reads (bins) were used in ML to train the system on predicting tumors with BRCA1/2 mutations and tumors with abnormalities similar to those detected in BRCA1/2 mutations.
Results:
Using 31 breast or ovarian cancers with BRCA1/2 mutations and 84 tumors without mutations in any of 12 homologous recombination repair (HRR) genes, the ML demonstrated high sensitivity (90%, 95% confidence interval CI = 73%-97.5%) and specificity (98%, 95% CI = 90%-100%). Testing of 114 tumors with mutations in HRR genes other than BRCA1/2 showed 39% positivity for HRD similar to that seen in BRCA1/2. Testing 213 additional wild-type (WT) cancers showed HRD positivity similar to BRCA1/2 in 32% of cases. Correlation with proportional loss of heterozygosity (LOH) as determined using whole exome sequencing of 51 samples showed 90% (95% CI = 72%-97%) concordance. The approach was also validated in an independent set of 1312 consecutive tumor samples.
Conclusions:
These data demonstrate that CNA when combined with ML can reliably predict the presence of BRCA1/2 level HRD with high specificity. Using BRCA1/2 mutant cases as gold standard, this ML can be used to predict HRD in cancers with mutations in other HRR genes as well as in WT tumors.
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