Loss of Chromatin-Remodeling Proteins and/or CDKN2A Associates With Metastasis of Pancreatic Neuroendocrine Tumors and Reduced Patient Survival Times
2018; Elsevier BV; Volume: 154; Issue: 8 Linguagem: Inglês
10.1053/j.gastro.2018.02.026
ISSN1528-0012
AutoresSomak Roy, William A. LaFramboise, Ta‐Chiang Liu, Dengfeng Cao, Alyssa Luvison, Caitlyn Miller, Maureen A. Lyons, Roderick J. O’Sullivan, Amer H. Zureikat, Melissa E. Hogg, Allan Tsung, Kenneth K. Lee, Nathan Bahary, Randall E. Brand, Jennifer Chennat, Kenneth Fasanella, Kevin McGrath, Marina N. Nikiforova, Georgios I. Papachristou, Adam Slivka, Herbert J. Zeh, Aatur D. Singhi,
Tópico(s)Neuroblastoma Research and Treatments
ResumoDespite prognostic grading and staging systems, it is a challenge to predict outcomes for patients with pancreatic neuroendocrine tumors (PanNETs). Sequencing studies of PanNETs have identified alterations in death domain-associated protein (DAXX) and alpha-thalassemia/mental retardation X-linked chromatin remodeler (ATRX). In tumors, mutations in DAXX or ATRX and corresponding loss of protein expression correlate with shorter times of disease-free survival and disease-specific survival of patients. However, DAXX or ATRX proteins were lost in only 50% of distant metastases analyzed. We performed whole-exome sequencing analyses of 20 distant metastases from 20 patients with a single nonsyndrome, nonfunctional PanNET. We found distant metastases contained alterations in multiple endocrine neoplasia type 1 (MEN1) (n = 8), ATRX (n = 5), DAXX (n = 5), TSC2 (n = 3), and DEP domain containing 5 (DEPDC5) (n = 3). We found copy number loss of cyclin dependent kinase inhibitor 2A (CDKN2A) in 15 metastases (75%) and alterations in genes that regulate chromatin remodeling, including set domain containing 2 (SETD2) (n = 4), AT-rich interaction domain 1A (ARID1A) (n = 2), chromodomain helicase DNA binding protein 8 (CHD8) (n = 2), and DNA methyl transferase 1 (DNMT1) (n = 2). In a separate analysis of 347 primary PanNETs, we found loss or deletion of DAXX and ATRX, disruption of SETD2 function (based on loss of H3 lysine 36 trimethylation), loss of ARID1A expression or deletions in CDKN2A in 81% of primary PanNETs with distant metastases. Among patients with loss or deletion of at least 1 of these proteins or genes, 39% survived disease-free for 5 years and 44% had disease-specific survival times of 10 years. Among patients without any of these alterations, 98% survived disease-free for 5 years and 95% had disease-specific survival times of 10 years. Therefore, primary PanNETs with loss of DAXX, ATRX, H3 lysine 36 trimethylation, ARID1A, and/or CDKN2A associate with shorter survival times of patients. Our findings indicate that alterations in chromatin-remodeling genes and CDKN2A contribute to metastasis of PanNETs. Despite prognostic grading and staging systems, it is a challenge to predict outcomes for patients with pancreatic neuroendocrine tumors (PanNETs). Sequencing studies of PanNETs have identified alterations in death domain-associated protein (DAXX) and alpha-thalassemia/mental retardation X-linked chromatin remodeler (ATRX). In tumors, mutations in DAXX or ATRX and corresponding loss of protein expression correlate with shorter times of disease-free survival and disease-specific survival of patients. However, DAXX or ATRX proteins were lost in only 50% of distant metastases analyzed. We performed whole-exome sequencing analyses of 20 distant metastases from 20 patients with a single nonsyndrome, nonfunctional PanNET. We found distant metastases contained alterations in multiple endocrine neoplasia type 1 (MEN1) (n = 8), ATRX (n = 5), DAXX (n = 5), TSC2 (n = 3), and DEP domain containing 5 (DEPDC5) (n = 3). We found copy number loss of cyclin dependent kinase inhibitor 2A (CDKN2A) in 15 metastases (75%) and alterations in genes that regulate chromatin remodeling, including set domain containing 2 (SETD2) (n = 4), AT-rich interaction domain 1A (ARID1A) (n = 2), chromodomain helicase DNA binding protein 8 (CHD8) (n = 2), and DNA methyl transferase 1 (DNMT1) (n = 2). In a separate analysis of 347 primary PanNETs, we found loss or deletion of DAXX and ATRX, disruption of SETD2 function (based on loss of H3 lysine 36 trimethylation), loss of ARID1A expression or deletions in CDKN2A in 81% of primary PanNETs with distant metastases. Among patients with loss or deletion of at least 1 of these proteins or genes, 39% survived disease-free for 5 years and 44% had disease-specific survival times of 10 years. Among patients without any of these alterations, 98% survived disease-free for 5 years and 95% had disease-specific survival times of 10 years. Therefore, primary PanNETs with loss of DAXX, ATRX, H3 lysine 36 trimethylation, ARID1A, and/or CDKN2A associate with shorter survival times of patients. Our findings indicate that alterations in chromatin-remodeling genes and CDKN2A contribute to metastasis of PanNETs. Editor's NotesBackground and ContextCurrent grading and staging systems are suboptimal in predicting the clinical behavior of pancreatic neuroendocrine tumors (PanNETs), underscoring the need for identification of novel prognostic biomarkers.New FindingsThe authors found that loss or deletion of either DAXX, ATRX, H3K36me3/SETD2, ARID1A or CDKN2A in primary PanNETs was associated with significantly shorter patient disease-free survival and disease-specific survival.LimitationsAdditional studies are required to determine the prognostic and treatment ramifications of these markers in preoperative clinical specimens.ImpactThese observations highlight the potential role of chromatin remodeling genes (DAXX, ATRX, H3K36me3/SETD2 and ARID1A) and CDKN2A in the metastatic progression of PanNETs. Current grading and staging systems are suboptimal in predicting the clinical behavior of pancreatic neuroendocrine tumors (PanNETs), underscoring the need for identification of novel prognostic biomarkers. The authors found that loss or deletion of either DAXX, ATRX, H3K36me3/SETD2, ARID1A or CDKN2A in primary PanNETs was associated with significantly shorter patient disease-free survival and disease-specific survival. Additional studies are required to determine the prognostic and treatment ramifications of these markers in preoperative clinical specimens. These observations highlight the potential role of chromatin remodeling genes (DAXX, ATRX, H3K36me3/SETD2 and ARID1A) and CDKN2A in the metastatic progression of PanNETs. Pancreatic neuroendocrine tumors (PanNETs) are a heterogeneous group of neoplasms with increasing incidence and ill-defined pathobiology. Although most PanNETs are indolent and remain stable for years, a subset may behave aggressively and metastasize widely. Thus, the frequent detection of PanNETs presents a treatment dilemma. Current prognostic parameters and systems, such as tumor size and World Health Organization (WHO) grade, are susceptible to interpretation errors, sampling issues, and, in a subset of PanNETs, do not accurately reflect the clinical behavior of these neoplasms.1Reid M.D. et al.Mod Pathol. 2016; 29: 93Crossref Scopus (15) Google Scholar, 2Kuo E.J. et al.Ann Surg Oncol. 2013; 20: 2815-2821Crossref PubMed Scopus (151) Google Scholar, 3Haynes A.B. et al.Arch Surg. 2011; 146: 534-538Crossref PubMed Scopus (175) Google Scholar, 4Diaz Del Arco C. et al.Diagn Cytopathol. 2017; 45: 29-35Crossref PubMed Scopus (17) Google Scholar Hence, additional markers are needed to improve the prognostic classification of PanNETs. Recently, whole-exome and whole-genome sequencing studies have focused on identifying recurrent genetic alterations in primary PanNETs.5Jiao Y. et al.Science. 2011; 331: 1199-1203Crossref PubMed Scopus (1282) Google Scholar, 6Scarpa A. et al.Nature. 2017; 543: 65-71Crossref PubMed Scopus (53) Google Scholar Among these alterations, the most commonly mutated genes are multiple endocrine neoplasia type 1 (MEN1), death domain-associated protein (DAXX), and alpha-thalassemia/mental retardation X-linked (ATRX). DAXX and ATRX genes encode for proteins that participate in chromatin remodeling at telomeres. Mutations in these genes are associated with loss of nuclear expression of their respective proteins by immunohistochemistry and correlate with alternative lengthening of telomeres, a telomerase-independent telomere maintenance mechanism.7Heaphy C.M. et al.Science. 2011; 333: 425Crossref PubMed Scopus (758) Google Scholar In addition, loss of DAXX and/or ATRX is associated with shorter times of disease-free survival (DFS) and disease-specific survival (DSS).8Singhi A.D. et al.Clin Cancer Res. 2017; 23: 600-609Crossref PubMed Scopus (13) Google Scholar, 9Kim J.Y. et al.Clin Cancer Res. 2017; 23: 1598-1606Crossref PubMed Scopus (86) Google Scholar, 10Marinoni I. et al.Gastroenterology. 2014; 146: 453-460.e5Abstract Full Text Full Text PDF PubMed Scopus (299) Google Scholar Consequently, DAXX and/or ATRX loss is considered to be a driver of metastasis. However, only 50% of distant metastases demonstrate loss of DAXX and/or ATRX. In contrast to primary PanNETs, the genetic landscape of metastatic PanNETs remains relatively unknown and, therefore, we hypothesized that additional genetic alterations other than those involving DAXX and ATRX account for the metastatic progression of PanNETs and may serve as useful prognostic markers. Thus, we performed whole-exome sequencing of 20 distant metastases from 20 patients with a solitary, nonsyndrome, and nonfunctional PanNET (Supplementary Materials and Methods). Similar to sequencing studies of primary PanNETs, whole-exome sequencing of metastatic PanNETs revealed frequent genomic alterations in MEN1 (n = 8), ATRX (n = 5), DAXX (n = 5), TSC2 (n = 3), and DEP domain containing 5 (DEPDC5) (n = 3) (Supplementary Table 1 and Supplementary Figure 1).5Jiao Y. et al.Science. 2011; 331: 1199-1203Crossref PubMed Scopus (1282) Google Scholar, 6Scarpa A. et al.Nature. 2017; 543: 65-71Crossref PubMed Scopus (53) Google Scholar Inactivating mutations in DAXX and ATRX were mutually exclusive and correlated with loss of corresponding protein expression and the presence of alternative lengthening of telomeres by telomere fluorescence in situ hybridization (FISH). In addition, as described by Heaphy et al,7Heaphy C.M. et al.Science. 2011; 333: 425Crossref PubMed Scopus (758) Google Scholar 2 DAXX-negative and 2 ATRX-negative metastatic PanNETs lacked mutations in DAXX and ATRX, respectively. In contrast to primary PanNETs, MEN1 was not the most commonly altered gene in metastatic PanNETs. Cyclin dependent kinase inhibitor 2A (CDKN2A) copy number loss was found in 15 (75%) cases. Furthermore, genomic alterations in chromatin-remodeling genes, such as set domain containing 2 (SETD2) (n = 4), AT-rich interaction domain 1A (ARID1A) (n = 2), chromodomain helicase DNA binding protein 8 (CHD8) (n = 2), and DNA methyl transferase 1 (DNMT1) (n = 2), were seen in 10 (50%) metastatic PanNETs. Considering genomic alterations in SETD2, ARID1A, and CDKN2A were previously described in primary PanNETs, but at a significantly lower prevalence than in metastatic PanNETs, the status of SETD2, ARID1A, and CDKN2A was reevaluated using orthogonal methods. The SETD2 gene encodes for a histone methyltransferase that is specific for H3 lysine 36 trimethylation (H3K36me3) and loss-of-function mutations result in the absence of H3K36me3 expression by immunohistochemistry.11Ho T.H. et al.Oncogene. 2016; 35: 1565-1574Crossref PubMed Scopus (50) Google Scholar ARID1A inactivating mutations are associated with loss of the corresponding protein.12Gibson W.J. et al.Nat Genet. 2016; 48: 848-855Crossref PubMed Scopus (143) Google Scholar Genomic deletions in CDKN2A can be assayed using dual-color FISH.13Singhi A.D. et al.Mod Pathol. 2016; 29: 14-24Crossref PubMed Scopus (24) Google Scholar An analysis of the sequenced metastatic PanNETs revealed loss of H3K36me3 and ARID1A by immunohistochemistry and deletions for CDKN2A by dual-color FISH had a 100% concordance with alterations in their respective genes (Supplementary Figure 2). To determine the prognostic significance of SETD2, ARID1A, and CDKN2A alterations in relationship to DAXX/ATRX loss, the status of DAXX, ATRX, H3K36me3, ARID1A, and CDKN2A was evaluated in 347 solitary, nonsyndromic, primary PanNETs (Supplementary Tables 2 and 3). Loss or deletion of DAXX/ATRX, H3K36me3, ARID1A, and CDKN2A was identified in 80 (23%), 28 (8%), 10 (3%), and 25 (7%) of primary PanNETs, respectively, and associated with larger mean tumor size, higher WHO grade, lymphovascular invasion, higher pathologic tumor stage, synchronous distant metastases, and metachronous distant metastases (P < .05). Of note, DAXX/ATRX loss correlated with deletion in CDKN2A, but not the absence of H3K36me3 or ARID1A. Overall, DAXX, ATRX, H3K36me3, ARID1A, and/or CDKN2A loss or deletion was identified in 112 (32%) PanNETs. Further, loss or deletion of at least 1 marker was detected in 81 (81%) primary PanNETs from patients who either had synchronous metastases (41 [75%] of 55) or developed metachronous metastases (without synchronous metastases) on follow-up (40 [89%] of 45). The DFS and DSS for patients with PanNETs demonstrating either loss or deletion in DAXX, ATRX, H3K36me3, ARID1A, and/or CDKN2A were 63% at 3 years and 39% at 5 years (P < .001, χ2 = 142.5), and 75% at 5 years and 44% at 10 years (P < .001, χ2 = 53.9), respectively (Figure 1 and Supplementary Figure 3). Conversely, patients with PanNETs that lacked alterations in DAXX, ATRX, H3K36me3, ARID1A, and CDKN2A had a DFS of 99% at 3 years and 98% at 5 years, and DSS of 96% at 5 years and 95% at 10 years. Univariate and multivariate Cox regression analyses were used to determine the prognostic significance of these 5 markers. Loss or deletion in any 1 marker was an independent prognostic factor for DFS with a hazard ratio of 14.44 (P < .001) and DSS with a hazard ratio of 3.12 (P = .006) (Table 1).Table 1Univariate and Multivariate Cox Regression Analysis for DFS and DSSPatient or tumor characteristicsUnivariate Cox regression analysisMultivariate Cox regression analysisDFS HR (95% CI)PDSS HR (95% CI)PDFS HR (95% CI)PDSS HR (95% CI)PSex, male vs female1.10 (0.61–1.99).7520.94 (0.52–1.68).824Age, y1.03 (1.01–1.06).0081.03 (1.00–1.05).038Tumor size, > 2.0 cm vs ≤ 2.0 cm37.79 (5.20–274.50)<.00127.57 (3.80–200.16).00110.30 (1.39–76.64).0235.21 (0.69–39.62).111Functional vs nonfunctional0.18 (0.02–1.28).0860.58 (0.18–1.89).584Location, head and uncinate vs body and tail1.25 (0.69–2.27).4591.67 (0.93–2.99).088WHO grade, G2 or G3 vs G14.74 (2.50–8.98)<.0015.79 (2.91–11.53)<.0011.54 (0.77–3.07).2152.05 (0.99–4.27).054Lymphovascular invasion, presence vs absence6.60 (3.38–12.90)<.00111.73 (4.91–28.00)<.001Perineural invasion, presence vs absence5.43 (2.95–9.98)<.0014.05 (2.23–7.35)<.001Tumor stage (pT), pT3 vs pT1 and pT25.51 (3.01–10.08)<.0018.60 (4.23–17.47)<.001Lymph node metastasis, presence vs absence5.31 (2.84–9.93)<.0015.21 (2.69–10.10)<.0011.56 (0.80–3.04).1902.12 (1.07–4.20).031Distant metastases at presentation, presence vs absence10.02 (5.43–18.49)<.0013.64 (1.91–6.91)<.001DAXX/ATRX/H3K36me3/ARID1A/CDKN2A, loss/deletion vs preserved/wild-type35.45 (13.91–90.34)<.0019.55 (4.58–19.91)<.00114.43 (5.37–38.75)<.0013.12 (1.39–7.00).030NOTE. Data in bold indicates statistical significance.CI, confidence interval; HR, hazard ratio; pT, pathologic tumor. Open table in a new tab NOTE. Data in bold indicates statistical significance. CI, confidence interval; HR, hazard ratio; pT, pathologic tumor. Notwithstanding, our study has a number of limitations. It is retrospective by design and not all patients received the same form of treatment. Among patients with primary PanNETs, 8% underwent enucleation or central pancreatectomy, and, as a result, regional lymphadenectomy may be suboptimal. Removing these patients from our analyses would have little impact on the statistical correlations associated with DAXX, ATRX, H3K36me3, ARID1A, and CDKN2A status. Of note, enucleation and central pancreatectomy are typically done in the setting of small PanNETs (≤2 cm) because they often have an indolent clinical course.14Kulke M.H. et al.J Natl Compr Canc Netw. 2015; 13: 78-108Crossref PubMed Scopus (258) Google Scholar However, studies suggest a subset of small PanNETs can behave aggressively.2Kuo E.J. et al.Ann Surg Oncol. 2013; 20: 2815-2821Crossref PubMed Scopus (151) Google Scholar, 3Haynes A.B. et al.Arch Surg. 2011; 146: 534-538Crossref PubMed Scopus (175) Google Scholar Within our cohort, 2% of small PanNETs developed distant metastases and in each case harbored loss or deletion of at least 1 marker. Although additional studies are necessary, loss or deletion in DAXX, ATRX, H3K36me3, ARID1A, and/or CDKN2A in preoperative biopsies may indicate an increased risk of developing metastatic disease and, in turn, prompt a change in surgical management to ensure complete regional lymph node dissection. In summary, metastatic PanNETs not only harbor frequent genetic alterations in MEN1, DAXX, and ATRX, but also in SETD2, ARID1A, and CDKN2A. Loss or deletion of DAXX/ATRX, H3K36me3 (as a surrogate for SETD2), ARID1A, and CDKN2A in primary PanNETs correlated with several adverse clinicopathologic features. In addition, loss or deletion of at least 1 marker was associated with shorter DFS and DSS times, and a negative, prognostic factor for DFS and DSS, independent of tumor size and WHO grade. Although further studies are required, the assessment of these 5 markers by immunohistochemistry and FISH offers an objective method of evaluating prognostic risk using pathologic specimens. Moreover, our observations highlight the potential role of chromatin-remodeling genes and CDKN2A in the metastatic progression of PanNETs. Author Contributions Study Concept and Design: Somak Roy, William A. LaFramboise, Herbert J. Zeh, and Aatur D. Singhi. Acquisition of Data: Somak Roy, William A. LaFramboise, Ta-Chiang Liu, Dengfeng Cao, Alyssa Luvison, Caitlyn Miller, Maureen A. Lyons, Roderick J. O’Sullivan, Amer H. Zureikat, Melissa E. Hogg, Allan Tsung, Kenneth K. Lee, Jennifer S. Chennat, Kenneth E. Fasanella, Georgios I. Papachristou, Nathan Bahary, Randall E. Brand, Kevin McGrath, Marina N. Nikiforova, Adam Slivka, Herbert J. Zeh, and Aatur D. Singhi. Analysis and Interpretation of Data: Somak Roy, William A. LaFramboise, Herbert J. Zeh, and Aatur D. Singhi. Drafting of the Manuscript: Somak Roy, William A. LaFramboise, Herbert J. Zeh, and Aatur D. Singhi. Study approval was obtained from the University of Pittsburgh (Institutional Review Board No. PRO13020493) and Washington University (201404143) institutional review boards. The surgical pathology archives from the Departments of Pathology at the University of Pittsburgh Medical Center and Barnes-Jewish Hospital were queried for neuroendocrine neoplasms of the pancreas between 1995 and 2014 that underwent enucleation, central pancreatectomy, pancreaticoduodenectomy, or distal pancreatectomy. Cases were cross-referenced with clinical and follow-up data obtained from patient paper and/or electronic medical records. The study inclusion criteria consisted of the following: a solitary, well-differentiated neuroendocrine tumor (confirmed with positive immunolabeling for neuroendocrine markers [eg, synaptophysin and chromogranin A]) centered within the pancreas, surveillance and survival data of >2 years, absence of a genetic syndrome associated with pancreatic neuroendocrine neoplasms (eg, multiple endocrine neoplasia type 1 syndrome, von Hippel-Lindau syndrome, neurofibromatosis type 1 syndrome, and tuberous sclerosis complex syndrome), and cases with sufficient material for ancillary studies. In total, 367 patients with a resected PanNET fulfilled the aforementioned criteria. In addition, the surgical pathology archives from the respective institutions were cross-referenced to identify corresponding distant metastases with sufficient pathologic material for ancillary studies. Among 120 patients with distant metastases, 72 patients had pathologic material available of the distant metastasis for ancillary studies. For whole-exome sequencing, 20 distant metastatic PanNETs from 20 patients were selected. Pathologic material of the surgically resected primary PanNET from the remaining 347 patients was used to create high-density tissue microarrays (TMAs), as previously described.1Singhi A.D. et al.Clin Cancer Res. 2017; 23: 600-609Crossref PubMed Scopus (132) Google Scholar High-density TMAs were constructed using archival formalin-fixed, paraffin-embedded (FFPE) tissue blocks. Three, 1.0-mm-sized cores were punched from representative areas of each patient’s tumor and collected into recipient blocks. Sufficient tissue for ancillary studies on cut sections was confirmed before immunohistochemical testing and FISH. Details of both whole-exome sequencing and PanNET cohorts are discussed in detail in the Supplementary Data section. Clinical and demographic data were reviewed for each case. Corresponding pathology gross reports and H&E-stained slides also were reviewed for the following pathologic features: tumor size, location, lymphovascular invasion, perineural invasion, extension outside of the pancreas, and regional lymph node metastasis. Each PanNET was graded using the 2010 WHO classification system for pancreatic neuroendocrine neoplasms.2Bosman F.T. et al.World Health Organization (WHO) Classification of Tumours of the Digestive System. IARC Press, Lyon, France2010Google Scholar Briefly, on the basis of mitotic rate and Ki-67 immunohistochemistry, the following criteria were used: grade 1 (G1), <2 mitoses/10 high-power fields (hpf) and Ki-67 of 20 mitoses/10 hpf or Ki-67 of >20%. The mitotic rate was derived from evaluation of multiple sections in 50 hpf (×400, field diameter 0.55 mm2) and expressed as mitoses/10 hpf. For Ki-67, at least 500 neoplastic nuclei were counted in the highest-staining region for each case with careful exclusion of non-neoplastic cells.3Reid M.D. et al.Mod Pathol. 2015; 28: 686-694Crossref PubMed Scopus (146) Google Scholar A labeling index was calculated and expressed as a percentage. For cases with discordant mitotic rate and Ki-67 measurements, the highest grade was assigned. Pathologic primary tumor classification was determined according to the American Joint Committee on Cancer (AJCC) Staging Manual, seventh edition.4Edge S.B. et al.Exocrine and endocrine pancreas. AJCC Cancer Staging Manual.7th ed. Springer, New York, NY2010: 241-249Google Scholar Follow-up information was extracted from the patient’s paper and electronic medical records to include data on surveillance, disease recurrence/distant metastasis, and survival. Whole-exome sequencing was performed in the University of Pittsburgh Cancer Institute, Cancer Genomics Facility. Ten, 5-μm unstained FFPE sections from both tumor and normal were used for sample and library preparation. Paraffin was melted in an air incubator (60°C, 30 minutes), removed by submerging in 100% xylene (5 minutes), and rinsing in 100% ethanol 3 times followed by centrifugation (1000g, 5 minutes; R5810; S4–104 rotor with slide adaptor; Eppendorf, Hamburg, Germany). Each unstained slide was aligned in register with its corresponding H&E and the demarcated tumor or normal phenotype domain was manually dissected with a sterile scalpel with substrate accumulated across serial slides in a 2.0-mL low-retention, nuclease-free tube in which the substrate underwent 2 additional xylene and ethanol washes. A stereomicroscope was used to assist manual microdissection (Olympus SZ61 microscope; Olympus Corp, Center Valley, PA) as needed. DNA purification was performed on all samples using the QiaAmp FFPE DNA extraction kit (Qiagen, Hilden, Germany) beginning with an overnight incubation in lysis buffer (Buffer ATL:Proteinase K; 300 μL:100 μL, 56°C, shaking at 600 rpm) followed by a 100-μL proteinase spike-in and a 24-hour lysis. After the second lysis regimen, the substrate was denatured (90°C; 60 minutes); subjected to ethanol precipitation (2× volume and buffer AL); and QIAamp column capture was performed using a 2-mL flow-through collection tube (6000g, 1 minute). The column was serially washed (buffer AW1, AW2; 6000g, 1 minute) and dried (20,000g, 3 minutes) and the DNA eluted in low TE buffer (53 μL Tris 10 mM; EDTA 0.1 mM, pH 8.0; 20,000g, 5 minutes). Quality assurance/quality control (QA/QC) analysis was performed using an established pipeline, including spectrophotometry for purity (NanoDrop 1000, OD 260/280 >1.8; Thermo Scientific, Grand Island, NY), quantitative fluorometry for double-stranded DNA yield (Qubit-High Sensitivity, >100 ng dsDNA; Thermo Scientific), and micro-capillary electrophoresis to determine DNA integrity (Bioanalyzer 2100, fragment size >500 bp; Agilent, Santa Clara, CA). The DNA samples were subjected to acoustical shearing (200 ng, 50 μL low TE) using a Covaris S1 (Covaris, Woburn, MA) to obtain a fragment size of 150 to 170 bp for processing with the SureSelectXT library Prep kit (SSXT: #G9611A; Agilent). End repair was performed on individual samples (10× End Repair Buffer: 10 μL, dNTP mix: 1.6 μL, DNA polymerase: 1 μL, Klenow DNA polymerase: 2 μL, T4 polynucleotide kinase: 2.2 μL, nuclease-free H2O: 33.2 μL; 60 minutes, 20°C) and the DNA captured using Agencourt AMPure beads (#A63881; Beckman-Coulter, Indianapolis, IN) with elution in nuclear-free H2O. End-repaired DNA underwent 3ʹ adenylation (10× Klenow Polymerase Buffer: 5 μL, dATP: 1 μL, Exo (-) Klenow enzyme: 3 μL, NF H2O: 11 μL; 37°C, 30 minutes) followed by AMPure bead purification. Adapters were ligated to the paired ends (5× T4 DNA ligase buffer: 10 μL, T4 DNA ligase: 1.5 μL, undiluted Adaptor Oligo Mix: 10 μL, nuclease-free H2O: 15.5 μL; 20°C, 15 minutes), followed by AMPure bead purification and polymerase chain reaction (PCR) amplification was performed (98°C: 2 minutes, 10 cycles at 98°C: 30 seconds; 65°C: 30 seconds; 72°C: 1 minute; 72°C: 10 minutes) using SS primers (#G9611A) and the Herculase II Fusion DNA polymerase kit (#600679; Agilent). The DNA samples underwent QC to ensure adequate yield (>500 ng) of fragments 225 to 275 bp after PCR and AMPure bead purification. Hybridization (SS Human All Exon V6; Agilent) was performed on individual samples (500 ng DNA: 3.4 μL, SureSelect Block: 5.6 μL), which were then denatured at 95°C before mixing with capture baits (hyb buffer: 13 μL, baits: 5 μL, RNAse Block: 2 μL; 65°C, 24 hours). Hybridization products were then captured by incubation with streptavidin T1 beads (Dynabeads MyOne Streptavidin T1; Thermo Fisher, Waltham, MA) in SS binding buffer (room temperature, 30 minutes) followed by separation in a magnetic rack. Beads were washed (SS wash 2, 200 μL, 65°C, 10 minutes) and resuspended in H2O followed by amplification with indexing primers (Illumina, San Diego, CA) generating unique bar codes for each sample (H2O: 18.5 μL, 5× Herculase II reaction buffer: 10 μL, 100 mM dNTP: 0.5 μL, Herculase polymerase: 1 μL, indexing post-capture PCR primer: SSXT Index Reverse primers: 5 μL, DNA: 14 μL; 98°C: 2 minutes; 11 cycles 98°C: 30 seconds; 57°C: 30 seconds; 72°C: 1 minute). The DNA library was recovered using AMPure beads. Sequencing was performed using the NextSeq 500 (Illumina) high-output flow cell kit (2 × 76 paired end, 150 cycles) with samples concentrated (660 g/mol × bp fragment size × 1 × 106), pooled and titrated to 1.7 pM per sample to achieve an average base call target depth of 63× to 102×. Bioinformatics analysis was performed using a custom protocol developed for tumor and paired normal analysis. First, base call (BCL) files were converted to FASTQ files using bcltofastq (Illumina). Per lane FASTQ files were merged into FASTQ files for each read pair (R1 and R2), as per manufacturer’s recommendation. Each set of read pair FASTQs were aligned to the human reference genome (GRCh37.p13, hg19; GCF_000001405.25) using BWA MEM and encoded into a BAM (binary sequence alignment) format using Samtools.5Li H. arXiv 2013;1303.3997v1 [q-bio.GN].Google Scholar, 6Li H. et al.Bioinformatics. 2009; 25: 2078-2079Crossref PubMed Scopus (31884) Google Scholar RG (read group) tags for each sample were added at the time of sequence alignment. The raw BAM files were sorted, indexed, and PCR duplicates marked using Sambamba.7Tarasov A. et al.Bioinformatics. 2015; 31: 2032-2034Crossref PubMed Scopus (735) Google Scholar Prevariant calling processing included concurrent local realignment around regions of known indels (COSMIC v80, dbSNPv138, and Mills gold-standard Indel sets) for both tumor and normal-aligned reads using GATK.8Forbes S.A. et al.Nucleic Acids Res. 2015; 43: D805-D811Crossref PubMed Scopus (1766) Google Scholar, 9Sherry S.T. et al.Nucleic Acids Res. 2000; 29: 308-311Crossref Scopus (4865) Google Scholar, 10McKenna A. et al.Genome Res. 2010; 20: 1297-1303Crossref PubMed Scopus (14912) Google Scholar Subsequently, realigned BAMs were subjected to BQSR (Base Quality Score Recalibration) using GATK. Subsequently, variant calling was performed on the recalibrated BAMs using Varscan2 for SNV and short Indel detection and Scalpel for larger Indel detection.11Koboldt D.C. et al.Genome Res. 2012; 22: 568-576Crossref PubMed Scopus (2966) Google Scholar, 12Fang H. et al.Nat Protoc. 2016; 11: 2529-2548Crossref PubMed Scopus (66) Google Scholar Briefly for Varscan2, recalibrated BAM files for both tumor and normal were used to generate a paired tumor-normal sequence mpileup, which was used for calling variants using Varscan2 in somatic mode. Potential false positives were marked in the VCF files using Varscan2’s fpfilter based on specific parameters. Variants marked as somatic and high confidence by the variant caller were prioritized. For large Indel detection, Scalpel was used in somatic (paired tumor-normal) mode. Variants were represented using VCF format v4.2 (https://samtools.github.io/hts-specs/VCFv4.2.pdf). Variant calls from both callers were integrated, normalized, and annotated using custom python modules with dependencies on ANNOVAR and HGVS python package.13Wang K. et al.Nucleic Acids Res. 2010; 38: e164Crossref PubMed Scopus (7948) Google Scholar, 14Hart R.K. et al.Bioinformatics. 2014; 31: 268-270Crossref PubMed Scopus (26) Google Scholar For FASTQ and BAM files,
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