Types Of Genomic Alterations Research Articles

Removal of the catalytic subunit of DNA-protein kinase in the proximal tubules promotes DNA and tubular damage during kidney injury.

Tubular epithelial cell damage can be repaired through a series of complex signaling pathways. An early event in many forms of tubular damage is the observation of DNA damage, which can be repaired by specific pathways depending upon the type of genomic alteration.. In this study, we report that the catalytic subunit of DNA protein kinase (DNA-PKcs), a central DNA repair enzyme involved in sensing DNA damage and performing double stranded DNA break repair, plays an important role in the extent of tubular epithelial cell damage following exposure to injurious acute and chronic stimuli. Selective loss of DNA-PKcs in the proximal tubules led to increased markers of kidney dysfunction, DNA damage, and tubular epithelial cell injury in multiple models of acute kidney injury, specifically bilateral renal ischemia-reperfusion injury and single dose of cisplatin (15 mg/kg IP). In contrast, in a mouse model of kidney fibrosis and chronic kidney disease (UUO),the protective effects of DNA-PKcs was not as obvious histologically from the tissue sections. In the absence of proximal tubular DNA-PKcs, there was reduced levels of fibrotic markers, α-SMA and fibronectin, which suggests that there may be a biphasic role of DNA-PKcs depending upon the conditions exerted upon the kidney. In conclusion, this study demonstrates that the catalytic subunit of DNA-PKcs plays a context-dependent role in the kidney to reduce DNA damage during exposure to various types of acute, but not chronic forms of injurious stimuli.

SNP-SVant: A Computational Workflow to Predict and Annotate Genomic Variants in Organisms Lacking Benchmarked Variants.

Whole-genome sequencing is widely used to investigate population genomic variation in organisms of interest. Assorted tools have been independently developed to call variants from short-read sequencing data aligned to a reference genome, including single nucleotide polymorphisms (SNPs) and structural variations (SVs). We developed SNP-SVant, an integrated, flexible, and computationally efficient bioinformatic workflow that predicts high-confidence SNPs and SVs in organisms without benchmarked variants, which are traditionally used for distinguishing sequencing errors from real variants. In the absence of these benchmarked datasets, we leverage multiple rounds of statistical recalibration to increase the precision of variant prediction. The SNP-SVant workflow is flexible, with user options to tradeoff accuracy for sensitivity. The workflow predicts SNPs and small insertions and deletions using the Genome Analysis ToolKit (GATK) and predicts SVs using the Genome Rearrangement IDentification Software Suite (GRIDSS), and it culminates in variant annotation using custom scripts. A key utility of SNP-SVant is its scalability. Variant calling is a computationally expensive procedure, and thus, SNP-SVant uses a workflow management system with intermediary checkpoint steps to ensure efficient use of resources by minimizing redundant computations and omitting steps where dependent files are available. SNP-SVant also provides metrics to assess the quality of called variants and converts between VCF and aligned FASTA format outputs to ensure compatibility with downstream tools to calculate selection statistics, which are commonplace in population genomics studies. By accounting for both small and large structural variants, users of this workflow can obtain a wide-ranging view of genomic alterations in an organism of interest. Overall, this workflow advances our capabilities in assessing the functional consequences of different types of genomic alterations, ultimately improving our ability to associate genotypes with phenotypes. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol: Predicting single nucleotide polymorphisms and structural variations Support Protocol 1: Downloading publicly available sequencing data Support Protocol 2: Visualizing variant loci using Integrated Genome Viewer Support Protocol 3: Converting between VCF and aligned FASTA formats.

A Novel Alu Element Insertion in ATM Induces Exon Skipping in Suspected HBOC Patients

The vast majority of patients at risk of hereditary breast and/or ovarian cancer (HBOC) syndrome remain without a molecular diagnosis after routine genetic testing. One type of genomic alteration that is commonly missed by diagnostic pipelines is mobile element insertions (MEIs). Here, we reanalyzed multigene panel data from suspected HBOC patients using the MEI detection tool Mobster. A novel Alu element insertion in ATM intron 54 (ATM:c.8010+30_8010+31insAluYa5) was identified as a potential contributing factor in seven patients. Transcript analysis of patient-derived RNA from three heterozygous carriers revealed exon 54 skipping in 38% of total ATM transcripts. To manifest the direct association between the Alu element insertion and the aberrant splice pattern, HEK293T and MCF7 cells were transfected with wild-type or Alu element-carrying minigene constructs. On average, 77% of plasmid-derived transcripts lacked exon 54 in the presence of the Alu element insertion compared to only 4.7% of transcripts expressed by the wild-type minigene. These results strongly suggest ATM:c.8010+30_8010+31insAluYa5 as the main driver of ATM exon 54 skipping. Since this exon loss is predicted to cause a frameshift and a premature stop codon, mutant transcripts are unlikely to translate into functional proteins. Based on its estimated frequency of up to 0.05% in control populations, we propose to consider ATM:c.8010+30_8010+31insAluYa5 in suspected HBOC patients and to clarify its role in carcinogenesis through future epidemiological and functional analyses. Generally, the implementation of MEI detection tools in diagnostic sequencing pipelines could increase the diagnostic yield, as MEIs are likely underestimated contributors to genetic diseases.

An absolute approach to using whole exome DNA and RNA workflow for cancer biomarker testing.

The concept of personalized medicine in cancer has emerged rapidly with the advancement of genome sequencing and the identification of clinically relevant variants that contribute to disease prognosis and facilitates targeted therapy options. In this study, we propose to validate a whole exome-based tumor molecular profiling for DNA and RNA from formalin-fixed paraffin-embedded (FFPE) tumor tissue. The study included 166 patients across 17 different cancer types. The scope of this study includes the identification of single-nucleotide variants (SNVs), insertions/deletions (INDELS), copy number alterations (CNAs), gene fusions, tumor mutational burden (TMB), and microsatellite instability (MSI). The assay yielded a mean read depth of 200×, with >80% of on-target reads and a mean uniformity of >90%. Clinical maturation of whole exome sequencing (WES) (DNA and RNA)- based assay was achieved by analytical and clinical validations for all the types of genomic alterations in multiple cancers. We here demonstrate a limit of detection (LOD) of 5% for SNVs and 10% for INDELS with 97.5% specificity, 100% sensitivity, and 100% reproducibility. The results were >98% concordant with other orthogonal techniques and appeared to be more robust and comprehensive in detecting all the clinically relevant alterations. Our study demonstrates the clinical utility of the exome-based approach of comprehensive genomic profiling (CGP) for cancer patients at diagnosis and disease progression. The assay provides a consolidated picture of tumor heterogeneity and prognostic and predictive biomarkers, thus helping in precision oncology practice. The primary intended use of WES (DNA+RNA) assay would be for patients with rare cancers as well as for patients with unknown primary tumors, and this category constitutes nearly 20-30% of all cancers. The WES approach may also help us understand the clonal evolution during disease progression to precisely plan the treatment in advanced stage disease.

Whole-Genome Sequencing Reveals Mutational Signatures Related to Radiation-Induced Sarcomas and DNA-Damage-Repair Pathways

Radiation-induced sarcoma (RIS) is a rare but serious late complication arising from radiotherapy. Despite unfavorable clinical outcomes, the genomic footprints of ionizing radiation in RIS development remain largely unknown. Hence, this study aimed to characterize RIS genomes and the genomic alterations in them. We analyzed whole-genome sequencing in 11 RIS genomes matched with normal genomes to identify somatic alterations potentially associated with RIS development. Furthermore, the abundance of mutations, mutation signatures, and structural variants in RIS were compared with those in radiation-naïve spontaneous sarcomas. The mutation abundance in RIS genomes, including one hypermutated genome, was variable. Cancer-related genes might show different types of genomic alterations. For instance, NF1, NF2, NOTCH1, NOTCH2, PIK3CA, RB1, and TP53 showed singleton somatic mutations; MYC, CDKN2A, RB1, and NF1 showed recurrent copy number alterations; and NF2, ARID1B, and RAD51B showed recurrent structural variations. The genomic footprints of nonhomologous end joining are prevalent at indels of RIS genomes compared with those in spontaneous sarcoma genomes, representing the genomic hallmark of RIS genomes. In addition, frequent chromothripsis was identified along with predisposing germline variants in the DNA-damage–repair pathways in RIS genomes. The characterization of RIS genomes on a whole-genome sequencing scale highlighted that the nonhomologous end joining pathway was associated with tumorigenesis, and it might pave the way for the development of advanced diagnostic and therapeutic strategies for RIS.

Clinical and Genomic Analysis of Patients with Short Survival after Surgery for Esophageal Squamous Cell Carcinoma

Background: This study aimed to investigate the prognosis of Chinese patients with esophageal squamous cell carcinoma (ESCC) after surgery and its correlation with genomic alterations (GAs) to identify potential prognostic markers. Methods: The clinical information, pathological specimens, and follow-up information of 50 patients with stage II and III primary ESCC who were surgically resected in the Fourth Hospital of Hebei Medical University from January 2011 to December 2015 were collected in the present study. Based on overall survival (OS), these patients were divided into the short OS group (<3 years) and the long OS group (>4 years). GA detection was performed in patients with ESCC using next-generation sequencing. All categories of GAs were evaluated; the landscape of GAs in patients with ESCC was mapped; and the correlations between clinical characteristics, prognosis, and GAs were analyzed. Results: There was no skew in the distribution of gender, smoking, and adjuvant therapy between the long OS group and the short OS group. A total of 372 GAs were detected in the 50 patients with ESCC, with 7 types of GAs, including insertions, deletions, and copy number variations, and missense mutations occurred most frequently, with a frequency of >50.0%. Tumor protein 53 (TP53; 50/50, 100%) was the most commonly mutated gene in the entire cohort followed by cyclin D1, cyclin-dependent kinase inhibitor 2A (CDKN2A), and fibroblast growth factor 19. More CDKN2A loss (p = 0.098) was detected in the short OS group than in the long OS group. The results of the multivariate analysis after adjustment for clinical factors showed a statistically significant difference in the CDKN2A loss between the two groups. Data obtained from The Cancer Genome Atlas for surgical ESCC revealed that the CDKN2A loss may be responsible for the poorer prognosis in postoperative patients with ESCC. Conclusion: In patients with progressive primary ESCC, the poor postoperative prognosis may be epiphenomenally associated with the CDKN2A loss.

GIP: an open-source computational pipeline for mapping genomic instability from protists to cancer cells.

Genome instability has been recognized as a key driver for microbial and cancer adaptation and thus plays a central role in many diseases. Genome instability encompasses different types of genomic alterations, yet most available genome analysis software are limited to just one type of mutation. To overcome this limitation and better understand the role of genetic changes in enhancing pathogenicity we established GIP, a novel, powerful bioinformatic pipeline for comparative genome analysis. Here, we show its application to whole genome sequencing datasets of Leishmania, Plasmodium, Candida and cancer. Applying GIP on available data sets validated our pipeline and demonstrated the power of our tool to drive biological discovery. Applied to Plasmodium vivax genomes, our pipeline uncovered the convergent amplification of erythrocyte binding proteins and identified a nullisomic strain. Re-analyzing genomes of drug adapted Candida albicans strains revealed correlated copy number variations of functionally related genes, strongly supporting a mechanism of epistatic adaptation through interacting gene-dosage changes. Our results illustrate how GIP can be used for the identification of aneuploidy, gene copy number variations, changes in nucleic acid sequences, and chromosomal rearrangements. Altogether, GIP can shed light on the genetic bases of cell adaptation and drive disease biomarker discovery.

Whole-Genome Sequencing Reveals Comprehensive Genomic Profiles of Radiation-Induced Sarcomas

<h3>Purpose/Objective(s)</h3> Radiation-induced sarcoma (RIS) is a rare secondary malignancy resulting from ionizing radiation-related treatment after a long latency period. Despite the unfavorable clinical outcomes, the genomic footprints of ionizing radiation in RIS development remain largely unknown. Hence, this study aimed to characterize RIS genomes and the genomic alterations in them. <h3>Materials/Methods</h3> We performed whole-genome sequencing (WGS) of 11 cases of RIS matched with normal genomes to identify somatic alterations potentially associated with RIS development. <h3>Results</h3> The mutation abundance of RIS genomes including one hypermutated genome was variable. Cancer-related genes might show different types of genomic alterations. For instance, NF1, NF2, NOTCH1, NOTCH2, PIK3CA, RB1, and TP53 showed singleton somatic mutations; MYC, CDKN2A, RB1, and NF1 showed recurrent copy number alterations; and NF2, ARID1B, and RAD51B showed recurrent structural variations (SVs). The effects of non-homologous end joining on short insertions-deletions and SVs were substantial in RIS genomes, compared with in spontaneous osteosarcoma genomes, representing the genomic hallmark of RIS genomes. In addition, frequent chromothripsis and predisposing germline variants in DNA damage-repair pathways were identified. <h3>Conclusion</h3> Taken together, WGS-scale characterization of RIS genomes may pave the way for advanced diagnostic and therapeutic strategies for RIS.

Development and Analytical Validation of a Targeted Next-Generation Sequencing Panel to Detect Actionable Mutations for Targeted Therapy.

BackgroundThe ability to rapidly, inexpensively, and accurately identify cancer patients based on actionable genomic mutations in tumour specimens is becoming critically important in routine clinical diagnostics. Targeted panel sequencing is becoming popular because it enables comprehensive and cost-effective diagnosis. However, the implementation of a next-generation sequencing (NGS) assay in clinical settings requires careful analytical validation to demonstrate its ability to detect multiple genomic variants.Materials and MethodsHere, we developed a custom-targeted NGS panel to identify actionable variants, including single nucleotide variants, insertions, and deletions; copy number variants; and gene fusions, across 73 genes for targeted cancer therapy. We implemented a practical validation strategy with diluted samples and reference standard samples that modelled key determinants of accuracy, including mutant allele frequency, insertion/deletion length, amplitude of copy number, and hotspot gene fusions.ResultsThe analytical validation results demonstrated that our panel can identify different types of genomic alterations in these test samples with high levels of accuracy, sensitivity, and reproducibility.ConclusionOur panel could be deployed as a routine clinical test to comprehensively detect actionable variants in cancer patients to guide targeted therapy decisions.

MYC Activity Inference Captures Diverse Mechanisms of Aberrant MYC Pathway Activation in Human Cancers.

c-MYC (MYC) is deregulated in more than 50% of all cancers. While MYC amplification is the most common MYC-deregulating event, many other alterations can increase MYC activity. We thus systematically investigated MYC pathway activity across different tumor types. Using a logistic regression framework, we established tumor type-specific, transcriptomic-based MYC activity scores that can accurately capture MYC activity. We show that MYC activity scores reflect a variety of MYC-regulating mechanisms, including MYCL and/or MYCN amplification, MYC promoter methylation, MYC mRNA expression, lncRNA PVT1 expression, MYC mutations, and viral integrations near the MYC locus. Our MYC activity score incorporates all of these mechanisms, resulting in better prognostic predictions compared with MYC amplification status, MYC promoter methylation, and MYC mRNA expression in several cancer types. In addition, we show that tumor proliferation and immune evasion are likely contributors to this reduction in survival. Finally, we developed a MYC activity signature for liquid tumors in which MYC translocation is commonly observed, suggesting that our approach can be applied to different types of genomic alterations. In conclusion, we developed a MYC activity score that captures MYC pathway activity and is clinically relevant. IMPLICATIONS: By using cancer type-specific MYC activity profiles, we were able to assess MYC activity across many more tumor types than previously investigated. The range of different MYC-related alterations captured by our MYC activity score can be used to facilitate the application of future MYC inhibitors and aid physicians to preselect patients for targeted therapy.

Abstract 789: Development and validation of a capture based NGS assay that enables the detection of Epstein Barr virus from gastric cancer patients' tumor tissues

Abstract Background: Gastric cancer patients with positive test for Epstein Barr virus (EBV) in their tumors have been reported to benefit significantly from anti-PD-1 therapy. Current clinical testing relies on fluorescent in situ hybridization of EBV-encoded small RNA (EBER). NGS assays have been increasingly used in the clinical settings to make therapeutic recommendations to cancer patients due to its versatility in detecting various types of genomic alterations. Detecting EBV by NGS is highly desired. Method: DNA was extracted from the FFPE samples of 214 gastric cancer patients' tumors, and profiled by the comprehensive NGS assay. A classification algorithm was developed using 131 gastric cancer samples (EBV Pos, n = 31; EBV Neg, n = 100) with known EBV status derived from EBER. The algorithm and the predetermined cutoff was then applied to an independent sample set (EBV Pos, n = 30; EBV Neg, n = 53) to evaluate the test performance. Results: In the training set, we achieved a sensitivity of 93.5% at a specificity of 100%. In the validation set, we achieved a sensitivity of 93.3% at a specificity of 100%. Using the same algorithm and cutoff, in the patients with tumor content above 20%, we achieve a sensitivity of 97.9% at a specificity of 100%. Conclusion: We developed a method to detect EBV in gastric tumors' FFPE samples through a capture-based NGS assay. We also demonstrated strong concordance with an orthogonal assay (EBER) in detecting EBV. Citation Format: Yajie Hu, Bo Yang, Lei Wang, Shiyi Liu, Lei Liang, Jie Wang, Fugen Li, Yu Sun. Development and validation of a capture based NGS assay that enables the detection of Epstein Barr virus from gastric cancer patients' tumor tissues [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 789.

Abstract P5-01-08: Landscape of circulating tumor DNA (ctDNA) in metastatic breast cancer

Abstract Background: The clinical utility of routine clinical assessment of ctDNA in metastatic breast cancer (MBC) has not been clearly established. Recently, the Food and Drug Administration approved alpelisib (Piqray®) with a ctDNA-based companion diagnostic. Therefore, there is significant interest in describing the landscape of ctDNA alterations and establishing further clinical utility of this assessment. Methods: We retrospectively identified ctDNA data from a single institution (Northwestern University). All patients had next-generation sequencing performed by Guardant Health (Redwood City, CA) from 2015-2019 for clinical evaluation, and patients were consented for participation in a prospective registry study. Reports were evaluated for type of genomic alterations, number of alterations, and mutant allele frequency (MAF) of the dominant clone. Clinical information including demographics, pathology, imaging, treatment, and response data were collected via patient chart review. Associations were tested through Fisher’s exact test or Kruskal-Wallis test as statistically appropriate. Matched paired samples were investigated through McNemar test. Results: The cohort consisted of 255 patients with MBC. In total, 371 ctDNA reports were reviewed, including 116 patients with serial assessments. Baseline ctDNA evaluation occurred at a median of 3 lines of therapy (interquartile range (IQR): 1 - 5). Median number of alterations was 4 (IQR: 2-7), while median MAF was 4% (IQR: 0.6% - 17.9%). Across the entire cohort, PIK3CA and TP53 were the most commonly detected mutations, while MYC, FGFR1, PIK3CA, and ERBB2 were the most commonly detected amplifications. 40% of patients had PIK3CA aberrations observed in the analyzed plasma samples (28% amplification, 22% H1047R, 11% E542K), which was independent of breast cancer subtype. In the subset of patients with hormone-receptor positive (HR+) breast cancer, 30% of patients had ESR1 mutations (27% D538G, 19% Y537S, 12% Y537N, 11% E380Q). Patients with triple negative breast cancer (TNBC) had statistically higher MAF compared to HR+ or HER2+ breast cancer (P&amp;lt;0.05). However, there were no differences in the number of alterations observed in each subtype. When examining the mutational profile of subtypes across lines of therapy, only ESR1 and FGFR1 were associated with collection beyond the first line of therapy for HR+ patients (P=0.003 and P&amp;lt;0.025, respectively). The mutational profiles of TNBC and HER2+ subtypes did not vary by lines of therapy at baseline blood collection. Number of genomic alterations detected increased incrementally with increasing lines of therapy (P&amp;lt;0.01), with specific genes more likely to be altered beyond the first line (ESR1, FGFR1, NF1). Higher MAF and number of genomic alterations were also significantly associated with number of metastatic sites on imaging (both P&amp;lt;0.001). In the subset of patients with serial blood collections, across all patients, the following genomic alterations were significantly more likely to emerge over time in paired samples: APC, BRAF, CCNE1, ERBB2, MET, MYC, NF1 (all P&amp;lt;0.05 with Q values corrected for multiplicity). Conclusion: Liquid biopsy evaluation using ctDNA identified clinically meaningful genomic alterations at high frequency. In addition, our data indicate the potential clinical utility of ctDNA as a surrogate for tumor burden on imaging based on the observed correlation with lines of therapy received and sites of disease. Serial assessment of ctDNA demonstrated clonal evolution, particularly in the HR+ cohort, and identified resistant clones. Validation with an independent cohort is warranted. Citation Format: Andrew A Davis, Saya Jacob, Lorenzo Gerratana, Ami N Shah, Firas Wehbe, Neelima Katam, Qiang Zhang, Lisa Flaum, Kalliopi Siziopikou, Leonidas C Platanias, William J Gradishar, Amir Behdad, Massimo Cristofanilli. Landscape of circulating tumor DNA (ctDNA) in metastatic breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P5-01-08.

Abstract B141: Landscape of circulating tumor DNA (ctDNA) in refractory metastatic breast cancer: Real-time evaluation of treatment-resistance

Abstract Background: Liquid biopsy is among the most important technological innovations in oncology in the past few years with the ability to provide real-time prognostic and predictive information. Circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA) contain genetic information released by the tumor of origin or metastasis in the bloodstream. Therefore, genetic alterations occurring in the tumor at the time of diagnoses or after treatment failure, can be detected with a simple blood sample. The efforts are now focused on demonstrating the clinical value of this assessment to improve treatment outcomes. Metastatic breast cancer (MBC) is a heterogeneous disease showing molecular evolution over time representing a challenge for selection of appropriate palliative treatment without longitudinal use of a sensitive diagnostic method. Methods: We retrospectively identified ctDNA data from a single institution (Northwestern University). All patients had next-generation sequencing performed by Guardant Health (Redwood City, CA) from 2015-2019 for clinical evaluation, and patients were consented for participation in a prospective registry study. Reports were evaluated for type of genomic alterations, number of alterations, and mutant allele frequency (MAF) of the dominant clone. Clinical information including demographics, pathology, imaging, treatment, and response data were collected via patient chart review. Associations were tested through Fisher’s exact test or Kruskal-Wallis test as statistically appropriate. Matched paired samples were investigated through McNemar test. Results: We evaluated a cohort of 255 patients with MBC. In total, 371 ctDNA reports were reviewed, including 116 patients with serial assessments. Baseline ctDNA evaluation occurred at a median of 3 lines of therapy (interquartile range (IQR): 1 – 5). Median number of detected alterations was 4 (IQR: 2-7), while median MAF was 4% (IQR: 0.6% - 17.9%). The most frequent mutations detected across the entire cohort, were PIK3CA and TP53, while MYC, FGFR1, PIK3CA, and ERBB2 were the most commonly detected amplifications. 40% of patients had PIK3CA aberrations observed in the analyzed plasma samples (28% amplification, 22% H1047R, 11% E542K), which was independent of breast cancer subtype. Particularly, interesting and with clinical relevance were the results from the hormone-receptor positive (HR+) breast cancer cohort. In this subset, 30% of patients had ESR1 mutations (27% D538G, 19% Y537S, 12% Y537N, 11% E380Q)which was associated with resistance to endocrine therapy. When examining the correlation with treatment lines, only ESR1 and FGFR1 were associated with collection beyond the first line of therapy for HR+ patients (P=0.003 and P&amp;lt;0.025, respectively). Conclusion: Liquid biopsy evaluation using ctDNA identified clinically meaningful genomic alterations in treatment-refractory MBC. Serial assessment of ctDNA demonstrated clonal evolution, particularly in the HR+ cohort, and identified resistant clones. Validation with an independent cohort is warranted. Citation Format: ELENA VAGIA, Andrew Adam Davis, Lorenzo Gerratana, Ami Shah, Amir Behdad, William Gradishar, Firas Wehbe, Massimo Cristofanilli. Landscape of circulating tumor DNA (ctDNA) in refractory metastatic breast cancer: Real-time evaluation of treatment-resistance [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; 2019 Oct 26-30; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2019;18(12 Suppl):Abstract nr B141. doi:10.1158/1535-7163.TARG-19-B141

1583P - SMARCA4 deficient non-small cell lung cancer (NSCLC): A comprehensive genomic profiling (CGP) study

BackgroundThe SMARCA4 catalytic ATPase, can be inactivated by several types of genomic alterations (GA) in NSCLC. SMARCA4 deficient (d) NSCLC is an aggressive subtype of primary lung adenocarcinoma that is often confused with metastatic disease to the lung. MethodsFrom a series of 40,319 clinically advanced NSCLC, 2,840 (7%) SMARCA4d and 37,479 (93%) SMARCA4i cases underwent hybrid capture-based CGP using FFPE material. Microsatellite instability (MSI) was determined on 114 loci and tumor mutational burden (TMB) and (mutations (mut) per/ Mb) was determined on 1.1 Mbp of sequenced DNA. PD-L1 expression was measured by IHC (Dako 22C3). ResultsSMARCA4d was inactivated by short variant base substitutions and truncations (88%), deletions (9%), duplications (1%), rearrangement/fusions (1%). SMARCA4d patients were slightly younger and featured significantly fewer females (Table). At 3.2 vs 5.6 GA/tumor, SMARCA4d tumors had significantly fewer driver-type GA than SMARCAi tumors. Although non-targetable GA in TP53 and KRAS were similar, SMARCA4d cases features significantly lower frequencies of the EGFR and PIK3CA SV targets and fusions in ALK, ROS1 and NTRK1-3 genes. In contrast, SMARCA4d tumors had a significantly higher frequency of STK11 mutations while also having a higher median TMB and greater proportion of cases with > 10 and > 20 mut/Mb. CDK4/6 GA were more frequent in the SMARCA4i cases.Table1583PTableSMARCA4 Deficient NSCLCSMARCA4 Intact NSCLCSignificanceCases2,84037,479% Male/female57/4349/51P<0.0001Median age6467NSGA/tumor3.25.6P<0.0001TP5370%64%NSKRAS28%30%NSEGFR7%18%P<0.0001STK1134%13%P<0.0001PIK3CA5%10%P<0.0001RB16%8%NSMET4%5%NSBRAF4%5%NSERBB26%4%NSCDK42%4%P<0.0001CDK 62%2%NSALK ROS1 NTRK1/32%5%P<0.0001PD-L1 (CD274) amp1%1%NSPD-L1 Low26%27%NSPD-L1 High18%29%P<0.0001Median TMB (mut/Mb)12.26.1P<0.0001TMB > 10 mut/Mb60%35%P<0.0001TMB > 20 mut/Mb27%10%P<0.0001MSI High0.8%0.2%NS ConclusionsSMARCA4d NSCLC is characterized by pleomorphic histology, TTF1- IHC and significant reduction in targetable driver mutations in genes such as EGFR, ALK, ROS1 and NTRK1-3. Despite new evidence that SMARCA4d tumors can respond to cell cycle inhibitors such as palbociclib, the CDK4/6 mutation frequencies is not increased in this tumor subset. Higher TMB levels in SMARCA4d NSCLC suggests strong potential for immunotherapy benefit, but the significantly enriched STK11 GA frequency may reduce overall response rates to checkpoint inhibitors. Legal entity responsible for the studyFoundation Medicine. FundingFoundation Medicine. DisclosureD. Lin: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. J.A. Elvin: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. J. Vergilio: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. J.K. Killian: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. N. Ngo: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. S. Ramkissoon: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. E. Severson: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. A. Hemmerich: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. D. Duncan: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. C. Edgerly: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. S.M. Ali: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. A.B. Schrock: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. J. Chung: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. E.S. Sokol: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. P. Reddy: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. K. McGregor: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. V.A. Miller: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. B.M. Alexander: Leadership role, Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. J.S. Ross: Leadership role, Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. All other authors have declared no conflicts of interest.

An enhanced genetic model of colorectal cancer progression history

BackgroundThe classical genetic model of colorectal cancer presents APC mutations as the earliest genomic alterations, followed by KRAS and TP53 mutations. However, the timing and relative order of clonal expansion and other types of genomic alterations, such as genomic rearrangements, are still unclear.ResultsHere, we perform comprehensive bioinformatic analysis to dissect the relative timing of somatic genetic alterations in 63 colorectal cancers with whole-genome sequencing data. Utilizing allele fractions of somatic single nucleotide variants as molecular clocks while accounting for the presence of copy number changes and structural alterations, we identify key events in the evolution of colorectal tumors. We find that driver point mutations, gene fusions, and arm-level copy losses typically arise early in tumorigenesis; different mechanisms act on distinct genomic regions to drive DNA copy changes; and chromothripsis—clustered rearrangements previously thought to occur as a single catastrophic event—is frequent and may occur multiple times independently in the same tumor through different mechanisms. Furthermore, our computational approach reveals that, in contrast to recent studies, selection is often present on subclones and that multiple evolutionary models can operate in a single tumor at different stages.ConclusionCombining these results, we present a refined tumor progression model which significantly expands our understanding of the tumorigenic process of human colorectal cancer.

Molecular underpinnings of clinical disparity patterns in African American vs. Caucasian American multiple myeloma patients

Caucasian Americans (CA) compared with African Americans (AA) have a twofold increased incidence of multiple myeloma (MM) and have an earlier age of diagnosis. However, there is sparse information regarding underlying biological differences across racial/ethnic groups. We characterized genetic alterations using a targeted next-generation sequencing assay called myTYPE, developed at MSKCC, allowing capture of somatic mutations, IgH translocations, gains/losses, and hyperdiploidy. Samples were obtained from the NIH Plasma Cell Dyscrasia Racial Disparity Cohort. In total, 68 patient samples were successfully sequenced and manually curated based on well-established databases. Of the 68 patient samples (47 CA, 21 AA), 84% had at least one type of genomic alteration. Importantly, the IgH translocation, t(11;14), was observed more frequently in the AA group (0 vs. 29%, p = 0.001). Known oncogenic somatic non-synonymous mutations were found in 18 genes and indels in 2 genes. KRAS mutations were the most common mutation found in 16% of patients followed by NRAS and BRAF mutations. TP53 somatic mutations appeared to be more common in CA but lacked significance. This proof-of-principle study indicates the presence of varying underlying tumor biology between racial groups and supports the need of future prospective trials to capture these molecular characteristics.

Identification of Genomic Alterations Through Multilevel DNA Structural Analysis.

Current methods to identify genomic alterations using whole-genome sequencing (WGS) data are often limited to single nucleotide polymorphisms and insertions and deletions that are less than 10bp in length. These limitations are largely due to challenges in accurately mapping short sequencing reads that significantly diverge from the reference genome. Newer sequencing-based methods have been developed to define and characterize larger DNA structural elements. This is achieved by enriching for and sequencing regions of the genome that contain a specific element, followed by identifying genomic regions with high densities of mapped short reads that designate the location of these elements. This process essentially aggregates short read data into larger structural units for further characterization. Here, we describe protocols for identifying various types of genomic alterations using differential analysis of these structural units. We focus on changes in DNA accessibility, protein-DNA interactions, and chromosomal contacts as measured by ATAC-Seq, ChIP-Seq, and Hi-C respectively. As many protocols have been published describing the generation and processing of these data, we focus on simple methods that can be used to identify mutations in these data, and can be executed by someone with limited computational expertise.

Abstract 5357: OncoGxSelectTM - a beneficial supplement to comprehensive cancer genetic test

Abstract Genetic profiling of tumor has been widely accepted both in oncology research and clinical field. However, clinical doctors are sometimes overwhelmed by tremendous and complicated information provided by comprehensive genetic tests, although they are welcomed by research-oriented oncologists. In order to provide accurate key findings to aid diagnosis and treatment in clinical practice, a careful tailored NGS based test - OncoGxSelectTM was developed and validated. Targeting 7 popular cancer types (NSCLC, Colorectal cancer, Breast cancer, Melanoma, Thyroid cancer, Esophageal and GIST cancer), OncoGxSelectTM detects all 4 types of genomic alterations including single nucleotide mutation, insertion/deletion, copy number variation and gene rearrangement in tumor tissue for 12 well-characterized clinical actionable genes strictly following NCCN (National Comprehensive Cancer Network) guidelines. OncoGxSelectTM offers high sensitivity and specificity greater than 99%, low cost and fast turnaround time using both DNA and RNA as starting material from FFPE samples with as low as 10% tumor cell content. This CLIA certified and CAP accredited genetic test panel is a valuable supplement to clinical oncologists to further facilitate diagnosis and treatment choosing. Citation Format: Yang Han, Pengfei Yu, Qingxuan Song, Min Wei, Guanghui Hu. OncoGxSelectTM - a beneficial supplement to comprehensive cancer genetic test [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5357. doi:10.1158/1538-7445.AM2017-5357

Aneuploidy meets network analysis: leveraging copy number alterations to identify molecular pathways disrupted in high-grade serous ovarian carcinomas

Cancer is a genomic disorder that often involves the accumulation of various types of genomic alterations that play roles in disease development and progression (1,2). In solid tumors, somatic mutations (herein, point mutations and short indels) and SCNAs (somatic copy number alterations as chromosomal amplifications/deletions) comprise the majority of the genomic alterations in cancer genomes in terms of abundance and genomic fraction, respectively; several to tens of thousands of somatic mutations and SCNAs occupying >50% of the genome have been observed in solid tumor genomes. Aneuploidy is defined as the presence of an abnormal number of chromosomes, and this chromosome-level SCNA has long been recognized as a hallmark of cancer genomes (3).

Correlation of genomic alterations assessed by next-generation sequencing (NGS) of tumor tissue DNA and circulating tumor DNA (ctDNA) in metastatic renal cell carcinoma (mRCC): potential clinical implications.

IntroductionTumor tissue and circulating tumor DNA (ctDNA) next-generation sequencing (NGS) testing are frequently performed to detect genomic alterations (GAs) to help guide treatment in metastatic renal cell carcinoma (mRCC), especially after progression on standard systemic therapy. Our objective was to assess if GAs detected by ctDNA NGS are different from those detected by tumor tissue NGS, specifically in patients with mRCC, and if these platforms are interchangeable or complimentary.ResultsWhen controlling for genes tested by both platforms, the median mutation rate for ctDNA was similar to tissue (median 3.0 vs. 1.0, p = 0.14). However, the concordance rate between the two platforms was only 8.6%. When comparing GAs by molecular pathway, GAs in tumor tissue were more common for the DNA repair and epigenetic pathways.Materials and MethodsResults of NGS testing from tumor tissue and ctDNA from 19 sequential mRCC patients were compared. GAs in each were statistically evaluated using the Wilcoxon signed-rank test. The Fischer's exact test was used to compare the incidence of mutations in selected molecular pathways.ConclusionsWhen controlling for genes tested by both platforms, similar number of GAs were detected by both tissue and ctDNA based NGS. However, there was discordance in the type of GAs detected suggesting that ctDNA NGS may be more reflective of dynamic tumor genomic heterogeneity. Hence, these two platforms may be considered complementary to each other, rather than interchangeable, for assessment of tumor GAs to guide selection of targeted clinical trial therapies.