scholarly journals Epidemiologic and Clinical Analysis of Tumor Mutational Burden (TMB) in Acute Myeloid Leukemia (AML): Exome Sequencing Study of the Mayo Clinic AML Epidemiology Cohort (MCAEC)

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 3437-3437
Author(s):  
James M. Foran ◽  
Michael G. Heckman ◽  
Yesesri Cherukuri ◽  
Mikolaj Wieczorek ◽  
Zaid Abdel Rahman ◽  
...  
Keyword(s):  
Risk Factors ◽  
Exome Sequencing ◽  
Mayo Clinic ◽  
Research Funding ◽  
Regression Models ◽  
Risk Group ◽  
Risk Genes ◽  
Poor Risk ◽  
Whole Exome ◽  
Epidemiologic Risk

Abstract TMB is used to guide PD-1-directed immunotherapy in solid tumor Oncology. However, it has not been systematically studied in AML, where the focus has been on cytogenetic risk and individual driver gene mutations (GM's). TMB contribution to AML epidemiology is also uncertain. We therefore studied its association with epidemiologic risk factors; driver GM's and somatic mutations (SM's) in AML risk genes which we recently demonstrated (ABCB1; CYP1A1; CYP2B6; EPHX1; ERCC1,2,& 5; MEFV; MTRR; and TERT); clinical and cytogenetic features; and outcome after therapy in the MCAEC, a highly annotated clinical epidemiology cohort of consecutive AML pts [Finn, Cancer Epidemiol 39:1084, 2015]. Methods: We obtained somatic leukemia DNA from remnant diagnostic cytogenetic pellets in 98 MCAEC patients (pts), as previously described [Foran, Blood (2017) 130:570a]. Whole exome sequencing (WES) was performed at depth of ~100 million paired end 100bp reads using Agilent SureSelectXT Human All Exon V5 + UTRs target enrichment kit. Reads were mapped to human genome build hg19 using BWA-MEM. Single nucleotide variants (SNVs) and small INDELs were identified using Mayo Clinic (MC) analytic pipeline GenomeGPS 4.0.1 following Broad GATK variant discovery best practices of alignment, realignment and recalibration, and multi-sample joint genotyping; and filtered using both germline whole exome and genome sequencing of ~1200 MC Biobank samples and public germline variant databases of 1000 genome project, 6500 individuals in exome sequencing project, and HapMap phase 3. Remaining variants were annotated using ANNOVAR, and functional variants of non-synonymous, truncating, frame-shift, and splice-sites were used in the statistical association analyses. TMB was defined as the number of functional mutations per Mb of coding region, heterozygous or homozygous. TMB associations with epidemiologic risk, clinical characteristics, and SM's in AML risk genes (listed above) or driver GM's (occurring in 5 or more pts: ASXL1, BCOR, CEBPA, DNMT3A, FLT3, IDH2, KRAS, MLL2-5, NF1, NPM1, NRAS, PHF6, RUNX1, SF3B1, STAG2, TET2, TP53, U2AF1) were evaluated using linear regression models; a rank transformation of TMB was utilized due to its skewed distribution. Multivariable analysis (MVA) models were adjusted for variables with p-value <0.05 in unadjusted analysis. Regression coefficients ("β") were estimated, interpreted as change in mean TMB rank for specified variables or characteristic. Associations with outcomes were examined using logistic regression or Cox proportional hazards regression models. All statistical tests were two-sided (version 3.6.2; R Foundation for Statistical Computing, Vienna, Austria). Results Median age at AML diagnosis was 70 yrs (Range: 19-94 yrs), and 67 pts were male. Cytogenetic risk group was favorable (7%), intermediate-normal (46%) or abnormal (20%), and poor risk (27%). 40/61 pts (66%) achieved complete remission (CR). With a median follow-up of 8.0 months (Range: 0.1 - 186), 80 pts (82%) died and 20 (20%) underwent allogeneic transplantation (AlloBMT). Median TMB was 18.2 (Range: 15.0-70.1). In MVA, significant associations with increased TMB were observed in pts with history of prior immunosuppressive therapy or solid organ transplantation (β=19.48, P=0.015), and with FLT3 (β=21.12, P=0.015), MLL2 (β=20.91, P=0.001), and MLL3 (β=11.31, P=0.031) GM's. A borderline association was observed for U2AF1 (β=16.14, P=0.057). TMB was also associated with SM's in TERT (β=25.13, P=0.028); a borderline association with SM's in ABCB1 was not confirmed in MVA (β=-17.98, P=0.069). Additionally, cytogenetic risk group was associated with TMB in MVA (P=0.005), being highest in intermediate-normal and lowest in poor risk groups. Body Mass Index was inversely associated with TMB (unadjusted β=-16.99, P=0.005), but unconfirmed in MVA (β=-8.29, P=0.12). There was no association with CR (OR=0.93, P=0.46), use of (HR=0.96, P=0.64) or relapse risk (HR=1.00, P=0.98) following AlloBMT, or survival (HR=0.97, P=0.56) (Figure). Conclusions Measurement of TMB is feasible in this AML epidemiologic cohort, and we observed important associations with AML risk factors, risk gene SM's, cytogenetic risk group, and driver GM's. We acknowledge the relatively small sample size and possibility of type II error, and therefore these observations require validation in a large prospective cohort which is planned. Figure 1 Figure 1. Disclosures Foran: OncLive: Honoraria; certara: Honoraria; actinium: Research Funding; boehringer ingelheim: Research Funding; novartis: Honoraria; abbvie: Research Funding; servier: Honoraria; taiho: Honoraria; pfizer: Honoraria; revolution medicine: Honoraria; gamida: Honoraria; takeda: Research Funding; sanofi aventis: Honoraria; trillium: Research Funding; syros: Honoraria; aptose: Research Funding; bms: Honoraria; kura: Research Funding; h3bioscience: Research Funding; aprea: Research Funding; sellas: Research Funding; stemline: Research Funding. Murthy: CRISPR Therapeutics: Research Funding. Finn: Jazz: Consultancy, Speakers Bureau; BMS: Consultancy, Speakers Bureau; BeiGene: Consultancy, Speakers Bureau; ADC Therapeutics: Consultancy, Speakers Bureau. Badar: Pfizer Hematology-Oncology: Membership on an entity's Board of Directors or advisory committees. Cerhan: Celgene/BMS: Other: Connect Lymphoma Scientific Steering Committee, Research Funding; Genentech: Research Funding; NanoString: Research Funding; Regeneron Genetics Center: Other: Research Collaboration.

scholarly journals Whole-exome sequencing identified genetic risk factors for asparaginase-related complications in childhood ALL patients

Oncotarget ◽  
2017 ◽  
Vol 8 (27) ◽  
pp. 43752-43767 ◽  
Author(s):  
Rachid Abaji ◽  
Vincent Gagné ◽  
Chang Jiang Xu ◽  
Jean-François Spinella ◽  
Francesco Ceppi ◽  
...  
Keyword(s):  
Risk Factors ◽  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Genetic Risk ◽  
Genetic Risk Factors ◽  
Childhood All ◽  
Whole Exome

Genetic risk factors for VIPN in childhood acute lymphoblastic leukemia patients identified using whole-exome sequencing

2018 ◽  
Vol 19 (15) ◽  
pp. 1181-1193 ◽  
Author(s):  
Rachid Abaji ◽  
Francesco Ceppi ◽  
Swati Patel ◽  
Vincent Gagné ◽  
Chang J Xu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Acute Lymphoblastic Leukemia ◽  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Genetic Risk ◽  
Lymphoblastic Leukemia ◽  
Genetic Risk Factors ◽  
Childhood Acute Lymphoblastic Leukemia ◽  
Whole Exome

Perspectives on facilitating whole exome sequencing for international patients at Mayo Clinic

2019 ◽  
Vol 28 (2) ◽  
pp. 398-406
Author(s):  
Nicole Bertsch ◽  
Katherine Agre ◽  
Sarah Ewing ◽  
Lauren Gunderson ◽  
Jennifer Kemppainen ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Mayo Clinic ◽  
Whole Exome

Whole Exome Sequencing of a Patient with Atypical Congenital Pure Red Cell Aplasia Has Enabled the Identification of a Novel Key Actor of Erythropoiesis That May be Involved in CDAI Physiopathology

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 3-4
Author(s):  
Elia Colin ◽  
Genevieve Courtois ◽  
Lydie Da Costa ◽  
Carine Lefevre ◽  
Michael Dussiot ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Homologous Recombination ◽  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Research Funding ◽  
Pure Red Cell Aplasia ◽  
Red Cell ◽  
Whole Exome

Background: The development of next generation sequencing techniques has brought important insights into the molecular mechanisms of erythropoiesis and how these processes can be perturbed in human diseases. This strategy may be valuable in some hereditary erythroid disorders where a subset of patients does not carry any mutations in the supposed causal gene and for which transgenic mouse models do not recapitulate the phenotype, suggesting that additional genetic events may be involved in pathogenesis. Here, we report the case of an adult patient presenting with atypical pure red cell aplasia associated with facial dysmorphy and chronic leg ulcers. Whole exome sequencing revealed a heterozygous missense mutation (R725W) in the CDAN1 gene, which has been previously reported in congenital dyserythropoietic anemia type I (CDAI). However, this mutation was also detected in her healthy brother, suggesting that this event alone was not sufficient to explain her phenotype. According to this hypothesis, we found an additional germline heterozygous nonsense mutation (Q732X) in the MMS22L gene, which was not shared by her unaffected relatives. MMS22L is a protein involved in homologous recombination-dependent repair of stalled or collapsed replication forks. Additionally, MMS22L is able to bind newly synthesized soluble histones H3 and H4 and exhibits a histone chaperone activity. MMS22L loading onto ssDNA during homologous recombination is promoted by the histone chaperone ASF1. Interestingly, CDAN1 acts as a negative regulator of ASF1 by mediating its sequestration in the cytoplasm, which results in the blocking of histone delivery. Aims: As MMS22L has never been reported in erythropoiesis before, we aimed to investigate the role of MMS22L in human erythropoiesis. Based on the data summarized above, the purpose of this study was also to determine the effect of combined inactivation of MMS22L and CDAN1 on in vivo erythropoiesis, while exploring the functional cooperation between both proteins. Results: To decipher the role of MMS22L in human erythropoiesis, we assessed the consequences of complete MMS22L inactivation in human cord blood CD34+ progenitors as well as in CD36+ immature erythroblasts using shRNA lentiviruses. This resulted in a severe decrease of cell proliferation and differentiation due to G1 cell cycle arrest, with a slight increase of apoptosis. Interestingly, this phenotype was not observed when MMS22L was inactivated in the granulo-monocytic lineage, in which differentiation was maintained, suggesting that erythroid cells, that are highly proliferative, are more sensitive to MMS22L inactivation. To better understand the effect of combined CDAN1 and MMS22L haploinsufficiency observed in the proband, we used zebrafish as an in vivo model. Mms22l and cdan1 expression were simultaneously or separately downregulated by about 50% using antisens morpholino oligomers. 48 hours later, zebrafish embryos were stained with o-dianisidine to detect hemoglobin-containing cells. We found that combined knock-down of mms22l and cdan1 resulted in severe anemia, while knock-down of mms22l or cdan1 alone did not lead to any erythroid disorder. This experiment provides a proof-of-concept, indicating that the phenotype of the proband is indeed caused by the combination of both MMS22L and CDAN1 mutations. Finally, in order to decipher the cooperation between MMS22L and CDAN1 we used the human erythroid UT-7 cell line. We found that CDAN1 inactivation resulted in a severe decrease in MMS22L expression within the nucleus, suggesting that CDAN1 may regulate MMS22L expression or localization. We therefore wanted to confirm these results by assessing MMS22L expression in B-EBV cell lines established from two CDAI patients with CDAN1 compound heterozygous mutations. We found a great decrease in MMS22L expression within the nucleus of the CDAI patients' cells when compared to three control B-EBV cell lines. Based on these results, we suggest that impairment of MMS22L trafficking to the nucleus could be involved in CDA1 physiopathology. Conclusion: Through comprehensive genetic analysis of a single case with atypical congenital anemia, we demonstrated for the first time that MMS22L, a cell cycle regulator, is essential for the process of erythropoiesis. The crosstalk between MMS22L and CDAN1 is currently under investigation and could bring important new insights into the physiopathology of CDAI. Disclosures Hermine: Novartis: Research Funding; Alexion: Research Funding; AB Science: Consultancy, Current equity holder in publicly-traded company, Honoraria, Patents & Royalties, Research Funding; Celgene BMS: Consultancy, Research Funding; Roche: Consultancy.

Whole-Exome Sequencing Identifies a Somatic Cell Mutation Signature That Predicts Relapse Risk and Survival Probability in Multiple Myeloma

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 5-5
Author(s):  
Ehsan Malek ◽  
E. Ricky Chan ◽  
Daniel Qu ◽  
Jane Reese ◽  
Robert Fox ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Signaling Pathways ◽  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Research Funding ◽  
Advisory Board ◽  
High Burden ◽  
Signature Genes ◽  
Whole Exome ◽  
Relapse Group

Introduction: Multiple myeloma (MM) is a plasma cell neoplasm associated with heterogeneous somatic alterations. Despite the development of novel anti-myeloma agents that have significantly prolonged patient survival, disease relapse remains a daunting problem. Our goal was to employ whole-exome sequencing (WES) to better describe the mutational landscape in MM beyond the tumor cell and identify genomic factors that might predict relapse. WES was performed using autograft samples obtained from MM patients that were then treated with high dose melphalan and autologous hematopoietic cell transplant (HCT). We identified a panel of genes that were most frequently mutated in all patients and then identified those genes mutated with greater frequency in patients that relapsed. A relapse burden signature was generated based upon the genes that were most frequently mutated genes in relapsed patients. Finally, the relapse burden signature was correlated with patient progression-free survival (PFS) and overall survival (OS) following autologous HCT. Methods. DNA was extracted from one ml of cryopreserved, mobilized hematopoietic cell product obtained from patients (N=93) that underwent HCT and was provided by the Case Comprehensive Cancer Center Hematopoietic Biorepository Core. Targeted sequencing was performed using the Tempus xE whole exome platform (Tempus, Chicago, IL). Variants were identified using a variant allele frequency (VAF) ≥0.1 for each sample. Variants were tabulated for each gene in each patient. Patients were grouped according to their relapse status; "No Relapse" (N=39) and "Relapse" (N=54) which corresponded to their post-HCT outcome. Relapse time was defined as time from transplant to event. Variants identified in each gene and patient group were counted and ranked. A relapse burden signature was defined and included twenty-two genes over-represented in the relapse group compared to the non-relapse group by > 10%. Genes in the relapse burden signature were subjected to gene set enrichment analysis (GSEA) and cross referenced against Gene Ontology (GO) categories. PFS and OS were defined as the time from transplant until the event of interest, with censoring at time of last follow up. Patients were regrouped according to their mutation burden in the relapse signature genes ("High burden" defined as >=six signature genes with variants) and their OS and PFS were analyzed with an R package (survival) to generate Kaplan-Meier curves and statistical significance based on a Chi-square test between low and high burden patients. Results: In total, 3,523 genes were identified as containing variants. Table 1 lists the top thirty genes that were identified and ranked based upon total number of mutations (mutational count) and most frequently mutated in relapsed and non-relapsed patients (sample count). We then identified those genes that were more frequently mutated by at least 10% in relapsed patients compared to non-relapsed patients (Fig. 1A). GSEA revealed that the relapse burden gene signature was associated with protein O-linked glycosylation, glycan processing, Golgi lumen and innate immune response activating cell surface receptor signaling pathways (Table 2). Interestingly, multiple mucin family members (Muc2, Muc3A, Muc12 and Muc19) were represented in the relapse burden signature. GO analysis indicated that the individual mucin genes were associated with the same signaling pathways that had been associated with the relapse burden signature by GSEA (Table 3). Importantly, a high relapse burden signature was correlated with a statistically significant reduction in both PFS and OS (Fig. 1B, C). Conclusion: Taken together, our results support the feasibility of WES to generate a relapse burden signature that predicts the risk of MM patients for relapse following HCT. Moreover, the mutational landscape associated with relapse, i.e. the specific genes mutated, has provided insights on the mechanisms of relapse. It is noteworthy that the relapse burden signature genes identified here were mutated at a much greater frequency than genes associated with clonal hematopoiesis of indeterminate potential (CHIP). The identification of patient subgroups at heightened risk of relapse can better guide treatment decisions. Future studies will be conducted to evaluate the effect of pathways identified here on myeloma cell survival and to validate actionable therapeutic targets. Disclosures Malek: Bluespark: Research Funding; Takeda: Other: Advisory board , Speakers Bureau; Medpacto: Research Funding; Janssen: Other: Advisory board, Speakers Bureau; Sanofi: Other: Advisory board; Clegene: Other: Advisory board , Speakers Bureau; Amgen: Honoraria; Cumberland: Research Funding. Caimi:Amgen: Other: Advisory Board; Bayer: Other: Advisory Board; Verastem: Other: Advisory Board; Kite pharmaceuticals: Other: Advisory Board; Celgene: Speakers Bureau; ADC therapeutics: Other: Advisory Board, Research Funding. de Lima:Celgene: Research Funding; BMS: Other: Personal Fees, advisory board; Incyte: Other: Personal Fees, advisory board; Kadmon: Other: Personal Fees, Advisory board; Pfizer: Other: Personal fees, advisory board, Research Funding.

Whole Exome Sequencing to Predict Response to Hypomethylating Agents in MDS

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 1698-1698 ◽  
Author(s):  
Holleh D Husseinzadeh ◽  
Edward P Evans ◽  
Kenichi Yoshida ◽  
Hideki Makishima ◽  
Andres Jerez ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Research Funding ◽  
Somatic Mutations ◽  
Prolonged Exposure ◽  
Mutational Analysis ◽  
Outcome Analysis ◽  
Individual Treatment ◽  
Hypomethylating Agents ◽  
Whole Exome

Abstract Abstract 1698 Hypomethylating agents decitabine and azacitidine are standard treatments for myelodysplastic syndromes (MDS). In their use, one hopes to rectify cytopenias and prolong survival by retarding further disease progression. However, individual treatment responses vary from complete remission (CR) to complete refractoriness. In general, at least 4 cycles of therapy are administered prior to assessing response. Thus, patients may have prolonged exposure to ineffective therapy, suffering toxicities without clinical benefit, while alternative and potentially more effective treatments are delayed. Currently, there are no reliable phenotypic or mutational markers for predicting response to hypomethylating agents. Once whole exome sequencing (WES) became available for more routine analysis, we theorized that somatic mutational patterns may help identify patients who would most benefit from these drugs, thereby maximizing response rate by rational patient selection. To pursue this hypothesis, we screened a cohort of 168 patients with MDS who received either azacitidine or decitabine for the presence of somatic mutations. Only those who received sufficient therapy, i.e., completed at least 4 cycles, were selected for outcome analysis. Targeted Sanger sequencing, including a panel of up to 19 genes frequently affected by somatic mutations was performed. For a representative subset of 26 patients (this subset is expanding) of whom there were 15 responders and 11 non-responders, mutational analysis was performed by WES to select target genes for further analysis. WES utilizes paired DNA (tumor vs. CD3+ lymphocytes) to produce raw sequence reads aligned using Burrows-Wheeler Aligner (BWA). Variants are detected using the Broad Institute's Best Practice Variant Detection GATK toolkit. Median age was 68 years (range, 55–85), 50% were female, and MDS subtypes were as follows: RA/RCUD/RARS 13%, RCMD 16%, RAEB-1/2 20%, MDS/MPN & CMML-1/2 31%, and sAML 20%. Response was assessed using IWG 2006 criteria at 4 and 7 months after therapy initiation. Overall response was 48%; rate of CR (including marrow/cytogenetic CR) was 28%, any HI 20%, SD 22%, and no response 29%. The cohort was then dichotomized into “responders” and “non-responders,” with responders classified as those achieving CR or any HI. Baseline patient characteristics were similar between both groups, including average age at treatment initiation, disease subtypes, proportion of abnormal/complex karyotypes, and presence of common cytogenetic aberrations. Overall, the most frequently mutated genes include TET2/IDH1/IDH2, SRSF2, ASXL1, SF3B1, RUNX1, EZH2/EED/SUZ12, SETBP1, CBL, and PPIAF2. The highest rate of refractoriness was noted in mutants of TET2/IDH1/IDH2 (67%), SF3B1 (67%), U2AF1/2 (67%). We also identified several genes whose mutants were few but associated exclusively with refractory disease (100%), including KIT, ZRSR2, PRPF8, LUC7L2. We next applied a recursive partitioning algorithm to construct a decision tree for identifying the most pivotal mutations associated with response: we found mutant CBL and PPFIA2 to be strongly associated with response, whereas mutant U2AF1/2, SF3B1 and PRPF8 were strongly associated with refractoriness. Our final approach was to dichotomize the cohort by the presence/absence of each mutation/group of mutations, and response within mutant vs. wild type cases was compared. Among refractory cases, TET2/IDH1/IDH2 (26%) and SF3B1 (17%) were most frequently mutated; among responders, mutations in RUNX1 (19% vs. 4%]), CBL (14% vs. 0%), SRSF2 (23% vs. 9%), and SETBP1 (18% vs. 4%) were most frequent. When multiple genes were combined in “either-or” fashion, mutation in TET2, SF3B1, PRPF8, or LUCL71 was significantly associated with refractoriness (52%, p=.0287), whereas mutations of RUNX1, CBL, SRSF2, SETBP1, or PPFIA2 mutation was significantly associated with response (86%, p=.0001). Mutational patterns appear to predict response to standard hypomethylating agents. Identification of the most predictive genes could guide development of molecular maker-based selection of patients for hypomethylating agent therapy, but will require ongoing analysis and additional prospective testing for validation. Disclosures: Advani: Genzyme: Honoraria, Research Funding; Immunomedics: Research Funding. Maciejewski:NIH: Research Funding; Aplastic Anemia&MDS International Foundation: Research Funding.

Driver Mutation in Waldenstrom's Macroglobullinemia and Their Clonal Heterogeneity during Progression and Relapse

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 1092-1092 ◽  
Author(s):  
Jihye Park ◽  
Antonio Sacco ◽  
Salomon Manier ◽  
Karma Salem ◽  
Mira Mashood ◽  
...  
Keyword(s):  
New York ◽  
Disease Progression ◽  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Copy Number ◽  
Research Funding ◽  
Targeted Sequencing ◽  
Whole Exome ◽  
Btk Inhibitor ◽  
Serial Samples

Abstract Background: Whole genome sequencing has recently shown the presence of recurrent mutations, such as MYD88, CXCR4 and ARID1A, in patients with Waldenstrom's Macroglobulinemia (WM) at diagnosis. Nevertheless, the contribution of each genomic aberration within the clonal evolution of the tumor during WM progression has not been reported. We therefore aimed to investigate whether sequential genomic events sustain WM disease progression by using whole exome sequencing (WES) and targeted sequencing of serial samples. In addition, we investigated if specific genomic alterations can change in response to treatment with samples before and after proteasome or BTK inhibitor treatments. Methods: We have sequenced 74 samples from 32 patients using WES or targeted sequencing technology. DNA was collected from bone marrow CD19-selected cells that were isolated from 6 patients with WM at different stages of disease (2-3 serial samples per patient, total 15 samples), and was subjected to library construction, followed by Agilent Sure-Select Human All Exon v2.0-based hybrid selection. Germline DNA was isolated from matched CD19-depleted peripheral blood samples. All libraries were sequenced with Illumina Hiseq 2500 instrument (New York Genome Center, Rockefeller University, New York, NY). Reads were aligned to GRCh37, and quality control, mutation calling, insertion and deletion identification, copy number variation detection, coverage calculations were accomplished via Firehose at Broad. Somatic Single Nucleotide Variations (SSNVs) were identified and annotated using MuTect and Oncotator, respectively. Insertions and deletions were detected using Strelka. In addition, the deep targeted sequencing was done with a customized bait set in 59 independent serial samples obtained from 26 patients who were treated with either proteasome inhibitor (Pi)- or BTK inhibitor (BTKi)-based therapies in 12 and 14 cases, respectively. Results: Whole exome sequencing, performed at a total average depth of 83X for germline and 85X for tumor samples, led to the identification of average of 14 non-silent mutations per sample (range 2-60). Base conversion signature showed dominant A>C/G transitions. Copy number analysis showed 6q deletion being the most prevalent one. MYD88 was the most recurrent somatic variants in WM patients (>93%), followed by several genes including IRS4, VCAN, CXCR4 and ALDH2, being detected in ~20-30% of the samples. Specifically, changes in the Cancer Cell Fraction (CCF) of these mutations, such as MYD88 and CXCR4, occurred in the serial samples depending on progression and response to therapy. The mutated genes mentioned above, including MYD88, CXCR4, LRG1 and VCAN, were also observed in targeted sequencing of 59 independent serial samples (mean target coverage 434X). CXCR4 was linked to disease progression exposed to Pi or BTK; but not detected in patients responding to therapies. MYD88 was present in patients with either progressive disease or PR/VGPRs. Specifically, different frequencies of MYD88 mutations were identified in patients with progression or PR/VGPR to BTKi-based therapies compared to Pi-based therapies. LRG1 was detected in a patient in response to Pi, while VCAN was observed in both patients showing progression or response to Pi regimens only. Conclusion: These findings reveal the occurrence of clonal variations in patients with WM during disease progression and response to therapies. MYD88 was confirmed to be the most prevalent somatic aberration, and was present in post-treatment samples of progressors and responders to Pi- or BTKi-based regimens. In contrast, mutations in CXCR4 were enriched in patients with WM progressing to either Pi or BTKi therapies. This study demonstrates that WES and targeted sequencing of serial samples of WM patients can detect clonal variations during disease progression. Disclosures Ghobrial: Celgene: Honoraria, Research Funding; Noxxon: Honoraria; Amgen: Honoraria; BMS: Honoraria, Research Funding; Novartis: Honoraria; Takeda: Honoraria. Roccaro:Takeda Pharmaceutical Company Limited: Honoraria.

Cancer-specific survival in patients with urothelial carcinoma of the bladder with recurrence after radical cystectomy: External validation of the prognostic risk stratification model.

2014 ◽  
Vol 32 (4_suppl) ◽  
pp. 325-325 ◽  
Author(s):  
Tohru Nakagawa ◽  
Haruki Kume ◽  
Atsushi Kanatani ◽  
Masaomi Ikeda ◽  
Akihiko Matsumoto ◽  
...  
Keyword(s):  
Risk Factors ◽  
Urothelial Carcinoma ◽  
Radical Cystectomy ◽  
Median Survival ◽  
Prognostic Value ◽  
Risk Group ◽  
Cancer Specific Survival ◽  
Poor Risk ◽  
Carcinoma Of The Bladder ◽  
Metastatic Sites

325 Background: Prognosis of the patients with urothelial carcinoma of the bladder (UCB) who developed recurrence after radical cystectomy (RC) is generally poor, but can be variable. We previously showed that shorter time to recurrence (TTR) after RC, presence of symptoms on recurrence, more than one metastatic sites (organs), high serum C-reactive protein (CRP) level were associated with decreased survival in those patients, and proposed a model to stratify patients into 3 separate risk groups (Nakagawa et al. J Urol. 2013; 189:1275). The aim of this study was to evaluate the prognostic value of this model in a multi-institutional cohort of patients. Methods: We identified 267 patients who experienced disease recurrence after RC for UCB from 9 academic and community hospitals. Patients were categorized into three groups based on the presence of four risk factors, TTR of <1 year, presence of symptoms on recurrence, more than one metastatic sites (organs), and CRP level of ≥0.5 mg/dl: the favourable risk group included patients with none or one of these risk factors; the intermediate risk group with 2 risk factors; and those with 3 or 4 risk factors were assigned to the poor risk group. Results: Overall, median survival time (MST) of the entire cohort was 8.3 months (95%CI, 6.4-9.1). Two hundred and nineteen patients died of their disease with a median survival of 5.9 months. In a multivariate analysis, all of the 4 risk factors were statistically significant for the cancer-specific survival. Sixty-five (27.4%), 84 (35.4%), and 88 (37.1%) patients were in the favorable, intermediate and poor risk group, respectively. Thirty patients were excluded because CRP value was not obtained. MSTs of the patients in the favorable, intermediate and poor risk group were 22.2 (95% CI 16.1-28.3), 7.6 (95% CI 6.3-9.5), and 3.6 (95% CI 2.6-4.4) months, respectively, and the difference was statistically significant (p<0.001, log-rank test). Conclusions: We confirmed the prognostic value of our previous criteria based on the four variables in patients with recurrence after RC for UCB. This criteria would help in patient counseling and clinical trial design.

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