scholarly journals Additive effects of variants of unknown significance in replication repair-associated DNA polymerase genes on mutational burden and prognosis across diverse cancers

2021 ◽  
Vol 9 (9) ◽  
pp. e002336
Author(s):  
Jieer Ying ◽  
Lin Yang ◽  
Jiani C Yin ◽  
Guojie Xia ◽  
Minyan Xing ◽  
...  
Keyword(s):  
Hot Spot ◽  
The Cancer Genome Atlas ◽  
Driver Mutations ◽  
Cancer Type ◽  
Additive Effects ◽  
Variants Of Unknown Significance ◽  
Mutational Burden ◽  
Pathway Gene ◽  
Exonuclease Domain ◽  
Unknown Significance

BackgroundDefects in replication repair-associated DNA polymerases often manifest an ultra-high tumor mutational burden (TMB), which is associated with higher probabilities of response to immunotherapies. The functional and clinical implications of different polymerase variants remain unclear.MethodsTargeted next-generation sequencing using a 425-cancer gene panel, which covers all exonic regions of three polymerase genes (POLE, POLD1, and POLH), was conducted in a cohort of 12,266 patients across 16 different tumor types from January 2017 to January 2019. Prognostication of POL variant-positive patients was performed using a cohort of 4679 patients from the The Cancer Genome Atlas (TCGA) datasets.ResultsThe overall prevalence of somatic and germline polymerase variants was 4.2% (95% CI 3.8% to 4.5%) and 0.7% (95% CI 0.5% to 0.8%), respectively, with highest frequencies in endometrial, urinary, prostate, and colorectal cancers (CRCs). While most germline polymerase variants showed no clear functional consequences, we identified a candidate p.T466A affecting the exonuclease domain of POLE, which might be underlying the early onset in a case with childhood CRC. Low frequencies of known hot-spot somatic mutations in POLE were detected and were associated with younger age, the male sex, and microsatellite stability. In both the panel and TCGA cohorts, POLE drivers exhibited high frequencies of alterations in genes in the DNA damage and repair (DDR) pathways, including BRCA2, ATM, MSH6, and ATR. Variants of unknown significance (VUS) of different polymerase domains showed variable penetrance with those in the exonuclease domain of POLE and POLD1 displaying high TMB. VUS in POL genes exhibited an additive effect as carriers of multiple VUS had exponentially increased TMB and prolonged overall survival. Similar to cases with driver mutations, the TMB-high POL VUS samples showed DDR pathway involvement and polymerase hypermutation signatures. Combinatorial analysis of POL and DDR pathway status further supported the potential additive effects of POL VUS and DDR pathway genes and revealed distinct prognostic subclasses that were independent of cancer type and TMB.ConclusionsOur results demonstrate the pathogenicity and additive prognostic value of POL VUS and DDR pathway gene alterations and suggest that genetic testing may be warranted in patients with diverse solid tumors.

Genomic immunotherapy (IO) biomarkers detected on comprehensive genomic profiling (CGP) of tissue and circulating tumor DNA (ctDNA).

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 2541-2541
Author(s):  
Takayuki Yoshino ◽  
Hanna Tukachinsky ◽  
Jessica Kim Lee ◽  
Ethan Sokol ◽  
Dean C. Pavlick ◽  
...  
Keyword(s):  
Limit Of Detection ◽  
Predictive Biomarkers ◽  
Principal Component ◽  
Pathogenic Mutation ◽  
Circulating Tumor Dna ◽  
Driver Mutations ◽  
Cancer Type ◽  
Liquid Biopsies ◽  
Mutational Burden ◽  
Relative Prevalence

2541 Background: The dramatic impact of IO on treatment outcomes has heightened interest in predictive biomarkers, including genomic markers such as tumor mutational burden (TMB) and microsatellite instability (MSI). The recent FDA approval of pembrolizumab for previously treated advanced solid tumors with elevated TMB (≥10 mut/Mb on FoundationOne CDx, F1CDx) now requires a better understanding of the prevalence of this and other IO biomarkers detected on CGP, including differences between TMB detected in tissue and mutational burden detected in blood (bTMB). Methods: Tissue and plasma biopsies were profiled with two CGP panels of 324 genes with 0.8 Mb genome coverage (F1CDx and FoundationOne LiquidCDx). Mutational burden was calculated by counting somatic variants (single nucleotide and indels, including synonymous variants, excluding germline and driver mutations) with variant allele frequency (VAF) ≥5% in tissue (TMB) or ≥0.5% in ctDNA (bTMB). MSI score was assessed using 95 repetitive loci and principal component analysis (tissue) or >1,800 repetitive loci (plasma). ctDNA levels were estimated using composite tumor fraction (cTF), a metric based on aneuploidy and VAF. Results: Pan-cancer, TMB ≥10 was detected in 19% of tissue cases (29,238/156,294) and was common in melanoma (53%), small cell (41%), NSCLC (40%), bladder (39%), and endometrial (24%). bTMB ≥10 was detected in 13% of liquid biopsies (806/6,295); prevalence by cancer type was correlated with prevalence of elevated TMB (r = 0.81). Samples with bTMB ≥10 had an elevated cTF (median 13%, IQR 5 - 31%) as compared to samples with bTMB <10 (median 1.8%, IQR 0.6 - 7%, p < 0.001). Among 353 cases with both tissue and liquid CGP results (median 11 months apart), the relative prevalence of TMB ≥10 (12%) and bTMB ≥10 (13%) were similar, with concordant detection in 303 cases (86%). MSI-high (MSI-H) was seen in 2.2% of tissue CGP (3,461/156,294), most often in endometrial (19%), stomach (6.0%), and colorectal (5.3%) cancers, while MSI-H was detected in 0.68% of ctDNA specimens (43/6,295), which were also those with elevated cTF (median 11%, IQR 7 - 23%). Of 3,504 cases with MSI-H signature on tissue or liquid CGP, 1,619 (46%) had a pathogenic mutation detected in MLH1/MSH2/MSH6/PMS2 (15% predicted germline). CD274 amplification was detected in 1,207 cases (0.77%) of tissue CGP and 11 cases (0.17%) in ctDNA. Conclusions: Elevated bTMB is overall less prevalent than elevated tissue TMB, though these biomarkers are detected in similar cancer types. Detection of bTMB ≥10 and MSI-H in liquid biopsy was associated with elevated ctDNA levels, suggesting a limit of detection, and potentially indicating a more aggressive biology in samples positive for these biomarkers. Further investigation is needed to understand the utility of bTMB for identifying high TMB tumors that may benefit from IO.

Association of tumor mutational burden with smoking and mutation status in non-small cell lung cancer (NSCLC).

2017 ◽  
Vol 35 (7_suppl) ◽  
pp. 24-24 ◽  
Author(s):  
Andrew A. Davis ◽  
Young Kwang Chae ◽  
Sarita Agte ◽  
Alan Pan ◽  
Nisha Anjali Mohindra ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Genomic Instability ◽  
Smoking Status ◽  
Small Cell ◽  
Small Cell Lung ◽  
Variants Of Unknown Significance ◽  
Coding Regions ◽  
Mutational Burden ◽  
Unknown Significance ◽  
Tumor Mutational Burden

24 Background: Reponses to immunotherapy have been observed in multiple solid tumors including non-small cell lung cancer (NSCLC). Identifying optimal biomarkers for response to anti-PD-1/PD-L1 therapies remains critical. Tumor mutational burden (TMB) may indicate genomic instability and potential neoantigen binding sites to activated effector T cells. Methods: We retrospectively examined tumor mutational burden (TMB) using next-generation sequencing (Foundation Medicine) for 83 patients with NSCLC in our institution. TMB included both coding and non-coding regions, but excluded potentially functional mutations. We correlated TMB (mutations per megabase) with smoking history, number of potentially functional mutations, variants of unknown significance, and the driver mutations EGFR, ALK, and KRAS. TMB high versus low was stratified based on 15 mutations per megabase pair. Results: Our findings demonstrated that TMB was significantly associated with current/former smoking status (p = 0.01, Table 1). TMB was also significantly associated with number of potentially functional mutations, number of variants of unknown significance (VUS), and total reported mutations (p < 0.01). The absence of mutations in EGFR, ALK, or KRAS tended to be associated with higher TMB as well (p = 0.07). Conclusions: TMB was associated with smoking status, as well as potentially functional mutations, VUS, and total number of reported mutations. Our results indicate that number of coding region mutations predict genomic instability in non-coding regions. Future studies are needed to correlate this measure with other immune biomarkers and patient outcome in NSCLC. [Table: see text]

Detection of actionable BRAF missense mutations by ctDNA-based genomic analysis in prostate cancer.

2018 ◽  
Vol 36 (6_suppl) ◽  
pp. 306-306 ◽  
Author(s):  
Malshundria Prophet ◽  
Kun Xiao ◽  
Theodore Stewart Gourdin ◽  
Rebecca J Nagy ◽  
Lesli Ann Kiedrowski ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Genomic Analysis ◽  
Driver Mutations ◽  
Genomic Profiling ◽  
Missense Mutations ◽  
Braf Inhibitors ◽  
Braf Mutations ◽  
Variants Of Unknown Significance ◽  
Activating Mutations ◽  
Unknown Significance

306 Background: Activating BRAF fusion proteins are rare in prostate cancer (PCa) patients. Driver missense BRAF mutations have not been reported in detail in this population. Methods: We examined ctDNA-derived genomic profiles (Guardant 360) from 2,721 unique PCa patients, to identify BRAF genomic anomalies (SNVs, amplification). The ctDNA results were compared with PCa tissue-based genomics from the TCGA database (1,851 unique patients). Results: BRAF missense mutations were found in 76 ctDNA patients (2.8%) and were from all known mutation classes (I, II, III) as well as variants of unknown significance (VUSs). Only 4 patients had the V600E mutation. Multiple examples of known, autonomously active, non-canonical mutations were found (27), including K601E (12), G469A (5), D594G (2), and G466E (2). There were 45 VUSs. Mutations were primarily clonal but subclonal mutations were also found. In addition BRAF was commonly amplified, usually in the presence of multiple other amplified genes. BRAF missense mutations were more common with ctDNA than TCGA (2.8% vs 1.4%). Neither dataset identified frequent V600E mutations (ctDNA: 4/2,721; TCGA 1/1,851). However patients with the same non-canonical BRAF mutations were found in each dataset (K601E, G469A, G466E, D594G). Each dataset contained unique mutations found in only one patient. BRAF mutations potentially treatable with BRAF or MEK inhibitors (class I, II) were about half of all mutations (ctDNA 40.8%; TCGA 50%). We treated a PCa patient with a clonal BRAF(G469A) mutation with targeted therapy. The patient was resistant to multiple lines of hormonal and cytotoxic therapy. Trametinib produced a clinical and RECIST response. Conclusions: ctDNA-based genomic analysis identified multiple BRAF amplifications and missense SNVs in PCa patients. SNVs are largely non-canonical, but include known activating mutations that could act as drivers. The analysis also identified more BRAF missense mutations than did tissue genomic profiling, but the mutational landscape, overall frequency of mutations was similar with either method. ctDNA-based genomic profiling can identify actionable BRAF driver mutations that may respond to MEK and BRAF inhibitors.

Cutaneous melanoma mutation pathways and driver mutations as racially biased.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e22066-e22066
Author(s):  
Margaret I Sanchez ◽  
James Michael Grichnik
Keyword(s):  
Oxidative Damage ◽  
Racial Differences ◽  
Cutaneous Melanoma ◽  
The Cancer Genome Atlas ◽  
Driver Mutations ◽  
Racial Groups ◽  
Mutational Burden ◽  
Tumor Mutational Burden ◽  
Cancer Genome Atlas ◽  
Substitution Mutations

e22066 Background: Cutaneous melanoma (CM) demonstrates differences in its clinical prevalence in different racial groups. CM generally exhibits a high tumor mutational burden (TMB) and mutually exclusive driving mutations in NRAS, BRAF or KIT. TMB may be driven by different pathways including ultraviolet radiation (UVR), oxidation and deamination. UVR is the most common mutational signature found in CMs, but deamination and oxidation are also present. Methods: We analyzed 321 CMs exome data from The Cancer Genome Atlas network. BRAF, NRAS, KIT and those without (WT) were used to divide the melanomas. Germline SNPs with racial information (Caucasian, African and Asian) that were enriched in melanomas with a particular driving mutation were identified. Results: We compared the 3 racial groups across the 4 driving mutation types, Asian SNPs were significantly higher in KIT, African in WT and Caucasian in BRAF and NRAS. The melanomas were also evaluated by the type of substitution mutations including CC > TT for UV, G > T for oxidative damage and (G/A)C (G) > (G/A)T(G) for deamination. UV and deamination appeared inversely proportional, while oxidative damage appeared to be independent. UV signal was more prominent in BRAF and NRAS groups. KIT had a greater percentage of deamination while WT revealed more oxidative damage. We further compared UV and non-UV (CC > TT absence) KIT subgroups for racial differences. Asian SNPs were greatly increased in non-UV subgroup whereas Caucasian SNPs were in UV subgroup. Further, the non-UV KIT subgroup was divided into deamination and oxidative damage subgroups to compare racial differences. Deamination was significantly increased in Asians whereas oxidative damage was higher in Caucasians. In the case of the WT group, African SNPs were significantly higher in the non UV subgroup and were primarily correlated with oxidative damage. Conclusions: This study suggests that racial genetic background may predispose the distinctive mutational and genetic environments of melanoma development.

scholarly journals Identifying cancer type specific oncogenes and tumor suppressors using limited size data

2016 ◽  
Vol 14 (06) ◽  
pp. 1650031 ◽  
Author(s):  
Ana B. Pavel ◽  
Cristian I. Vasile
Keyword(s):  
Tumor Suppressors ◽  
Molecular Mechanisms ◽  
Lung Squamous Cell Carcinoma ◽  
The Cancer Genome Atlas ◽  
Driver Mutations ◽  
Cancer Type ◽  
Multiple Cancer ◽  
Driver Genes ◽  
Cancer Subtypes ◽  
Cancer Types

Cancer is a complex and heterogeneous genetic disease. Different mutations and dysregulated molecular mechanisms alter the pathways that lead to cell proliferation. In this paper, we explore a method which classifies genes into oncogenes (ONGs) and tumor suppressors. We optimize this method to identify specific (ONGs) and tumor suppressors for breast cancer, lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC) and colon adenocarcinoma (COAD), using data from the cancer genome atlas (TCGA). A set of genes were previously classified as ONGs and tumor suppressors across multiple cancer types (Science 2013). Each gene was assigned an ONG score and a tumor suppressor score based on the frequency of its driver mutations across all variants from the catalogue of somatic mutations in cancer (COSMIC). We evaluate and optimize this approach within different cancer types from TCGA. We are able to determine known driver genes for each of the four cancer types. After establishing the baseline parameters for each cancer type, we identify new driver genes for each cancer type, and the molecular pathways that are highly affected by them. Our methodology is general and can be applied to different cancer subtypes to identify specific driver genes and improve personalized therapy.

scholarly journals Construction of liver hepatocellular carcinoma-specific lncRNA-miRNA-mRNA network based on bioinformatics analysis

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0249881
Author(s):  
Ruifang Wang ◽  
Xiaobo Hu ◽  
Xiaorui Liu ◽  
Lu Bai ◽  
Junsheng Gu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Dna Replication ◽  
Metabolic Pathways ◽  
Molecular Mechanisms ◽  
Cox Proportional Hazards ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed ◽  
Driver Mutations ◽  
Pathway Gene ◽  
Liver Hepatocellular Carcinoma

Liver hepatocellular carcinoma (LIHC) is one of the major causes of cancer-related death worldwide with increasing incidences, however there are very few studies about the underlying mechanisms and pathways in the development of LIHC. We obtained LIHC samples from The Cancer Genome Atlas (TCGA) to screen differentially expressed mRNAs, lncRNAs, miRNAs and driver mutations. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, Gene ontology enrichment analyses and protein–protein interaction (PPI) network were performed. Moreover, we constructed a competing endogenous lncRNAs-miRNAs-mRNAs network. Finally, cox proportional hazards regression analysis was used to identify important prognostic differentially expressed genes. Total of 1284 mRNAs, 123 lncRNAs, 47 miRNAs were identified within different tissues of LIHC patients. GO analysis indicated that upregulated and downregulated differentially expressed mRNAs (DEmRNAs) were mainly associated with cell division, DNA replication, mitotic sister chromatid segregation and complement activation respectively. Meanwhile, KEGG terms revealed that upregulated and downregulated DEmRNAs were primarily involved in DNA replication, Metabolic pathways, cell cycle and Metabolic pathways, chemical carcinogenesis, retinol metabolism pathway respectively. Among the DERNAs, 542 lncRNAs-miRNAs-mRNAs pairs were predicted to construct a ceRNA regulatory network including 35 DElncRNAs, 26 DEmiRNAs and 112 DEmRNAs. In the Kaplan‐Meier analysis, total of 43 mRNAs, 14 lncRNAs and 3 miRNAs were screened out to be significantly correlated with overall survival of LIHC. The mutation signatures were analyzed and its correlation with immune infiltrates were evaluated using the TIMER in LIHC. Among the mutation genes, TTN mutation is often associated with poor immune infiltration and a worse prognosis in LIHC. This work conducted a novel lncRNAs-miRNAs-mRNAs network and mutation signatures for finding potential molecular mechanisms underlying the development of LIHC. The biomarkers also can be used for predicting prognosis of LIHC.

scholarly journals Truncation and Motif Based Pan-Cancer Analysis Highlights Novel Tumor Suppressing Kinases

2018 ◽  
Author(s):  
Andrew M. Hudson ◽  
Natalie L. Stephenson ◽  
Cynthia Li ◽  
Eleanor Trotter ◽  
Adam J. Fletcher ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Cancer Genomics ◽  
Cancer Cell Line ◽  
The Cancer Genome Atlas ◽  
Driver Mutations ◽  
Cancer Type ◽  
Loss Of Function ◽  
Gastric Cancer Cells ◽  
Jnk Pathway ◽  
Pan Cancer

AbstractA major challenge in cancer genomics is identifying driver mutations from the large number of neutral passenger mutations within a given tumor. Here, we utilize motifs critical for kinase activity to functionally filter genomic data to identify driver mutations that would otherwise be lost within mutational noise. In the first step of our screen, we define a putative tumor suppressing kinome by identifying kinases with truncation mutations occurring within or before the kinase domain. We aligned these kinase sequences and, utilizing data from the Cancer Cell Line Encyclopedia and The Cancer Genome Atlas databases, identified amino acids that represent predicted hotspots for loss-of-function mutations. The functional consequences of new LOF mutations were validated and the top 15 hotspot LOF residues were used in a pan-cancer analysis to define the tumor-suppressing kinome. A ranked list revealed MAP2K7 as a candidate tumor suppressor in gastric cancer, despite the mutational frequency of MAP2K7 falling within the mutational noise for this cancer type. The majority of mutations in MAP2K7 abolished catalytic activity compared to the wild type kinase, consistent with a tumor suppressive role for MAP2K7 in gastric cancer. Furthermore, reactivation of the JNK pathway in gastric cancer cells harboring LOF mutations in MAP2K7 or JNK1 suppresses clonogenicity and growth in soft agar, demonstrating the functional importance of inactivating the JNK pathway in gastric cancer. In summary, our data highlights a broadly applicable strategy to identify functional cancer driver mutations leading us to define the JNK pathway as tumor suppressive in gastric cancer.SummaryA unique computational pan-cancer analysis pinpoints novel tumor suppressing kinases, and highlights the power of functional genomics by defining the JNK pathway as tumor suppressive in gastric cancer.

scholarly journals CHASMplus reveals the scope of somatic missense mutations driving human cancers

2018 ◽  
Author(s):  
Collin Tokheim ◽  
Rachel Karchin
Keyword(s):  
Missense Mutation ◽  
Large Scale ◽  
Computational Method ◽  
The Cancer Genome Atlas ◽  
Superior Performance ◽  
Driver Mutations ◽  
Cancer Type ◽  
Missense Mutations ◽  
Driver Genes ◽  
Cancer Types

SummaryLarge-scale cancer sequencing studies of patient cohorts have statistically implicated many genes driving cancer growth and progression, and their identification has yielded substantial translational impact. However, a remaining challenge is to increase the resolution of driver prediction from the gene level to the mutation level, because mutation-level predictions are more closely aligned with the goal of precision cancer medicine. Here we present CHASMplus, a computational method, that is uniquely capable of identifying driver missense mutations, including those specific to a cancer type, as evidenced by significantly superior performance on diverse benchmarks. Applied to 8,657 tumor samples across 32 cancer types in The Cancer Genome Atlas, CHASMplus identifies over 4,000 unique driver missense mutations in 240 genes, supporting a prominent role for rare driver mutations. We show which TCGA cancer types are likely to yield discovery of new driver missense mutations by additional sequencing, which has important implications for public policy.SignificanceMissense mutations are the most frequent mutation type in cancers and the most difficult to interpret. While many computational methods have been developed to predict whether genes are cancer drivers or whether missense mutations are generally deleterious or pathogenic, there has not previously been a method to score the oncogenic impact of a missense mutation specifically by cancer type, limiting adoption of computational missense mutation predictors in the clinic. Cancer patients are routinely sequenced with targeted panels of cancer driver genes, but such genes contain a mixture of driver and passenger missense mutations which differ by cancer type. A patient’s therapeutic response to drugs and optimal assignment to a clinical trial depends on both the specific mutation in the gene of interest and cancer type. We present a new machine learning method honed for each TCGA cancer type, and a resource for fast lookup of the cancer-specific driver propensity of every possible missense mutation in the human exome.

Total number of circulating tumor DNA (ctDNA) genomic alterations and outcome after checkpoint inhibitor-based immunotherapy.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e14504-e14504
Author(s):  
Yulian Khagi ◽  
Aaron Goodman ◽  
Gregory A. Daniels ◽  
Sandip Pravin Patel ◽  
Lyudmila Bazhenova ◽  
...  
Keyword(s):  
Checkpoint Inhibitor ◽  
Predictive Biomarker ◽  
Circulating Tumor Dna ◽  
Genomic Alterations ◽  
Variants Of Unknown Significance ◽  
Non Invasive ◽  
Mutational Burden ◽  
Unknown Significance ◽  
Tumor Mutational Burden ◽  
Next Generation Sequencing Ngs

e14504 Background: High tumor mutational burden on tissue biopsy correlates with efficacy of checkpoint immunotherapy in cancers, such as non-small cell lung cancer and melanoma. However, the relationship between mutational burden detected in non-invasive surrogates, such as blood-derived ctDNA genomic alterations, and outcome after immunotherapy, has not been evaluated. Methods: We analyzed 69 patients with diverse malignancies whose plasma-derived ctDNA had undergone next generation sequencing (NGS) (54 to 70 genes: Guardant Health) and who had received checkpoint inhibitor-based immunotherapy. Data was assessed to correlate total number of alterations (characterized alterations and variants of unknown significance, VUS) in ctDNA and outcome: stable disease (SD) >6 months, complete or partial remission (CR or PR), progression-free and overall survival (PFS and OS), from date of immunotherapy initiation. Results: The69 patients had 23 different diagnoses. All individuals received checkpoint inhibitor-based immunotherapy, with the majority receiving anti-PD1/PD-L1 monotherapy. Evaluable patients with ≥6 vs. <6 total ctDNA alterations had significantly higher rates of SD≥6 months/CR/PR: 40.9% (9/22) vs. 15.9% (7/44) (p=0.035) (Table). Median PFS was 2.85 months vs. 2.1 months (p=0.046). OS was not statistically different. A landmark analysis at 2 months showed that median PFS in the ≥6 alterations group was 23.2 months for responders (CR/PR) vs. 2.3 months for non-responders (p=0.0006); for the group with <6 alterations, the median PFS was 12.6 vs. 3.3 months (p = 0.0006). Conclusions: Total number of ctDNA genomic alterations merits further exploration as a potential predictive biomarker for outcome with checkpoint inhibitor-based immunotherapy. Achieving response to checkpoint-based immunotherapy strongly predicts PFS from the 2-month mark. [Table: see text]

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