RNA-Based Next-Generation Sequencing Approach to Non-Small Cell Lung Cancer: A Single-Center Experience in Turkey

The Catalogue Of Somatic Mutations In Cancer (COSMIC) [1] is one of the largest repositories of information on somatic mutations in human cancer. The project has been running for more than ten years as part of the Cancer Genome Project (CGP) at the Wellcome Trust Sanger Institute in the UK. The data in COSMIC are curated from a variety of sources, primarily the scientific literature and large international consortia. The project includes information from the CGP, along with data from other consortia such as the International Cancer Genome Consortium and The Cancer Genome Atlas. In addition, COSMIC is regularly updated with the genes highlighted in the Cancer Gene Census, which curates the scientific literature for known cancer genes [2]. With the advent of whole exome and genome sequencing technology, the amount of data in COSMIC is increasing rapidly. The recent COSMIC release (version 53; 18 May 2011) contains 608,042 tumor and cell line samples, annotating 176,856 mutations across 19,439 genes, with 352 full exomes, 43 whole genome rearrangement screens and 4 full genomes now available. The data are updated regularly, with new releases scheduled every two months. COSMIC provides a large number of graphical and tabular views for interpreting and mining the large quantity of information, as well as the facility to export the relevant data in various formats. The website can be navigated in many ways to examine mutation patterns on the basis of genes, samples and phenotypes, which are the main entry points to COSMIC. COSMIC also provides various options to browse the data in a genomic context. Integration with the Ensembl genome browser allows the visualization of full genome annotations, together with COSMIC data, on the GRCh37 genome coordinates. COSMIC also contains its own genome browser, which facilitates data analysis by combining genome-wide gene structures and sequences with rearrangement breakpoints, copy number variations and all somatic substitutions, deletions, insertions and complex gene mutations. The main COSMIC website [1] encompasses all of the available data. However, within COSMIC, the Cancer Cell Line Project [3] is a specialized component, which provides details of the genotyping of almost 800 commonly used cancer cell lines, through the set of known cancer genes. Its focus is to identify driver mutations, or those likely to be implicated in the oncogenesis of each tumor. This information forms the basis for integrating COSMIC with the Genomics of Drug Sensitivity in Cancer project [4], which is a joint effort with the Massachusetts General Hospital [5] to screen this panel of cancer cell lines against potential anticancer therapeutic compounds to investigate correlations between somatic mutations and drug sensitivity. Data on somatic mutations in cancer are being produced at a rapidly increasing rate, and the combined analysis of large distributed datasets is becoming ever more difficult. However, COSMIC curates and standardizes this information in a single database, providing user-friendly browsing tools and analytical functions, thus ensuring its role as a key resource in human cancer genetics.

The catalogue of Somatic Mutations in Cancer (COSMIC) (http://www.sanger.ac.uk/cosmic/) is the largest public resource for information on somatically acquired mutations in human cancer and is available freely without restrictions. Currently (v43, August 2009), COSMIC contains details of 1.5-million experiments performed through 13 423 genes in almost 370 000 tumours, describing over 90 000 individual mutations. Data are gathered from two sources, publications in the scientific literature, (v43 contains 7797 curated articles) and the full output of the genome-wide screens from the Cancer Genome Project (CGP) at the Sanger Institute, UK. Most of the world’s literature on point mutations in human cancer has now been curated into COSMIC and while this is continually updated, a greater emphasis on curating fusion gene mutations is driving the expansion of this information; over 2700 fusion gene mutations are now described. Whole-genome sequencing screens are now identifying large numbers of genomic rearrangements in cancer and COSMIC is now displaying details of these analyses also. Examination of COSMIC’s data is primarily web-driven, focused on providing mutation range and frequency statistics based upon a choice of gene and/or cancer phenotype. Graphical views provide easily interpretable summaries of large quantities of data, and export functions can provide precise details of user-selected data.

"COSMIC, the Catalogue Of Somatic Mutations In Cancer":http://www.sanger.ac.uk/cosmic is designed to store and display somatic mutation information relating to human cancers, combining detailed information on publications, samples and mutation types. The information is curated both from the primary literature and the laboratories at the Cancer Genome Project, Sanger Institute, UK, and then semi-automatically entered into the COSMIC database. The v47 release (May 2010) contained the curation of 9202 papers describing 116,977 mutations across 466,851 samples. In order to provide consistent annotation of the data, COSMIC has developed a classification system for cancer histology and tissue ontology, and adapted HGVS mutation nomenclature recommendations to describe the multiple mutation types involved in cancer.Cancer genetics is moving from systematic screens of candidate gene sets to whole genome sequencing analyses, and COSMIC displays and navigates this new data; we have recently included systematic gene screens and whole genome sequencing studies. COSMIC will annotate and display somatic mutation data that will be emerging from the "International Cancer Genome Consortium (ICGC)":http://www.icgc.org/ and "The Cancer Genome Atlas (TCGA)":http://cancergenome.nih.gov/ projects. New tools are being developed to interpret this genomic data with coding mutation annotations. In addition COSMIC will be expanded to curate and display data from mouse insertional mutagenesis screening and mouse cancer model exome/genome sequencing in the future. The data within COSMIC is freely available without restriction via a website, in datasheets on the "FTP site":ftp://ftp.sanger.ac.uk/pub/CGP/cosmic and through the "COSMIC Biomart":http://www.sanger.ac.uk/genetics/CGP/cosmic/biomart/martview/, available from the "COSMIC homepage":http://www.sanger.ac.uk/cosmic

Abstract"COSMIC, the Catalogue Of Somatic Mutations In Cancer":http://www.sanger.ac.uk/cosmic is designed to store and display somatic mutation information relating to human cancers, combining detailed information on publications, samples and mutation types. The information is curated both from the primary literature and the laboratories at the Cancer Genome Project, Sanger Institute, UK, and then semi-automatically entered into the COSMIC database. The v47 release (May 2010) contained the curation of 9202 papers describing 116,977 mutations across 466,851 samples. In order to provide consistent annotation of the data, COSMIC has developed a classification system for cancer histology and tissue ontology, and adapted HGVS mutation nomenclature recommendations to describe the multiple mutation types involved in cancer.Cancer genetics is moving from systematic screens of candidate gene sets to whole genome sequencing analyses, and COSMIC displays and navigates this new data; we have recently included systematic gene screens and whole genome sequencing studies. COSMIC will annotate and display somatic mutation data that will be emerging from the "International Cancer Genome Consortium (ICGC)":http://www.icgc.org/ and "The Cancer Genome Atlas (TCGA)":http://cancergenome.nih.gov/ projects. New tools are being developed to interpret this genomic data with coding mutation annotations. In addition COSMIC will be expanded to curate and display data from mouse insertional mutagenesis screening and mouse cancer model exome/genome sequencing in the future. The data within COSMIC is freely available without restriction via a website, in datasheets on the "FTP site":ftp://ftp.sanger.ac.uk/pub/CGP/cosmic and through the "COSMIC Biomart":http://www.sanger.ac.uk/genetics/CGP/cosmic/biomart/martview/, available from the "COSMIC homepage":http://www.sanger.ac.uk/cosmic

All advanced-stage lung adenocarcinoma patients should be tested for EGF receptor (EGFR) mutations and for EML4–ALK translocations as a guide for selecting them for tyrosine kinase inhibitor (TKI) therapy. The new EGFR and ALK guideline provides useful recommendations for appropriate testing [1]. Lung tumors are the leading cause of cancerrelated mortality worldwide [2]. Almost 80% of cases are non-small-cell lung cancer (NSCLC) and extensive disease is present at the time of diagnosis in the majority of patients. Systemic treatment with chemotherapy has reached a plateau of 10–20% response rates and 4–5 months of progression-free survival (PFS), and has not improved in more than a decade [3–5]. A first milestone in a new era of targeted therapy for this disease was reached with the discovery of a subset of tumors carrying activating mutations of EGFR, which can be selectively blocked with TKIs such as erlotinib and gefitinib. Numerous clinical studies have demonstrated the efficacy of these TKIs in the treatment of EGFR-mutated lung tumors, with 55–83% response rates and 9–13 month PFS [6,7]. A second milestone was the discovery, in 2007, of the EML4–ALK translocation in 6.7% of Japanese NSCLC patients [8]. The translocation was later found in 4–7% of Chinese [9], European [10] and US patients [11]. When treated with a novel ALK inhibitor, crizotinib, these patients showed response rates of 57% with a PFS greater than 6 months [12]. As a result of these new developments, many laboratories worldwide are currently testing lung tumor samples for EGFR mutations and EML4–ALK fusions. In an effort to standardize testing practices, the College of American Pathologists, the International Association for the Study of Lung Cancer and the Association for Molecular Pathology constituted writing and advisory panels, presided by three cochairs, to

Objective Ferroptosis is a type of programmed cell death dependent on iron and characterized by the accumulation of lipid peroxides, which was involved in the progression of malignant tumors including non-small cell lung cancer (NSCLC). Material/methods Ferroptosis inhibiting gene solute carrier family 7 member 11 (SLC7A11) mRNA expression was investigated in the database of TCGA and Oncomine and compared between the cancer tissue and the normal corresponding tissue of NSCLC patients. SLC7A11 gene mutation of NSCLC was investigated in the TCGA database by the online data analysis tool of Catalog of Somatic Mutations in Cancer (COSMIC) and cBioPortal. The protein–protein interaction (PPI) network of SLC7A11 and associated genes were constructed with the STRING database. Gene ontology (GO) and the KEGG pathway of genes involved in the PPI network were explored and demonstrated by a bubble plot. Progression-free survival (PFS), overall survival (OS) and postprogression survival (PPS) between SLC7A11high and SLC7A11low expression groups were compared and demonstrated by the survival curve. Results SLC7A11 mRNA was upregulated in cancer tissues compared to paired normal tissues in colorectal adenocarcinoma, esophageal squamous cell carcinoma, lung squamous cell carcinoma rectum adenocarcinoma and uterine corpus endometrial carcinoma. Missense and synonymous substitutions were 66.67% and 16.67% for lung squamous cell carcinoma. For lung adenocarcinoma, the missense and synonymous substitutions were 66.67% and 33.33% respectively. In the case of single nucleotide mutation, A>T, C>G, G>A, G>T for lung squamous cell carcinoma and G>T, C>A, G>A, T> for lung adenocarcinoma were the most common mutations in the SLC7A11 coding strand. Fifty-one genes were included in the PPI network with an edge number of 287, average node degree of 11.3 and local clustering coefficient of 0.694, which demonstrated that the PPI network was enriched significantly (p = 1.0 × 10−16). In terms of the KEGG pathway, the SLC7A11 and PPI-involved genes were mainly enriched in ferroptosis, NSCLC, pathways in cancer, tp53 signaling pathway, etc. The overall survival (OS) in the SLC7A11high group was significantly lower than those of SLC7A11low groups in NSCLC (HR = 1.15, 95% CI: 1.02–1.31, p = 0.027). However, the progression-free survival (PFS) (HR = 1.17, 95% CI: 0.97–1.42, p = 0.098) and postprogression survival (PPS) (HR = 1.00, 95% CI: 0.78–1.29, p = 0.97) between SLC7A11high and SLC7A11low expression groups were not statistically different. Conclusion SLC7A11 was upregulated in NSCLC and correlated with the patient’s poor overall survival. SLC7A11 may be a potential target for NSCLC treatment through the ferroptosis pathway.

Lung cancers represent the second most common cancer and Non-Small Cell Lung Cancer (NSCLC) constitutes 80-85% of all lung cancers. Genes within several cellular pathways have been previously evaluated for their clinical impact in NSCLC. In this investigation, we evaluate genetic mutations found in 50 cancer-critical genes implicated in the signaling pathways RTK/RAS/MAP, TGFβ, PI3K, Wnt, GPCR, p53, JAK/STAT, Notch, and the cell cycle pathway. Some of these mutations have not yet been described or have not been described in NSCLC. The intent of our study is to evaluate these mutations and allow further research into their impact, specifically highlighting mutations that are involved in clinically important pathways. We evaluated mutations found in 59 NSCLC patients at the Prisma Health Cancer Institute. These mutations are part of 2,800 COSMIC (Catalogue of Somatic Mutations in Cancer) hotspot mutations in 50 cancer-critical genes. Each mutation was investigated further using the ClinVar database to identify whether it had been described in NSCLC or other cancers/conditions, its genetic consequence, pathogenesis, possible variations, and origin. A total of 73 unique mutations in 59 NSCLC patients were evaluated. Of the 73 mutations, 17 had not been described at all, 40 had been described in other cancers/conditions, and 16 had been previously described in NSCLC. The known mutations’ effects in other cancers/conditions were categorized as pathogenic, likely pathogenic, likely benign, benign, or uncertain. Novel mutations were found in genes that provide a druggable target, help predict treatment response, are under investigation for their ability to predict treatment response or confer additional clinical utility. Medical management of cancer has benefitted greatly from studies of genetic mutations. Most mutations identified in our patient population had not been described in NSCLC, and a smaller number of those had not been described at all. Further elucidation of these mutations may lead to additional discoveries relevant to NSCLC prognostication and treatment. Citation Format: Miles Rothstein, Phillip Broughton, Ella Markalunas, Avery Funkhouser, Lorie Allen, Julie Martin, W. Jeffery Edenfield, Anna V. Blenda. Evaluation of genetic mutations in non-small cell lung cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5062.

7532 Background: We sought to determine the frequency and clinical characteristics of patients with non-small cell lung cancers (NSCLCs) harboring NRAS mutations. We used preclinical models to identify targeted therapies likely to be of benefit against NRAS mutant lung cancer cells. Methods: We reviewed data in the Catalogue of Somatic Mutations in Cancer (COSMIC) and clinical history from patients with NSCLC whose tumors underwent systematic screening for driver mutations including NRAS. Patient characteristics examined included age, gender, race, smoking history, disease stage, treatment history, and overall survival (OS). 6 NSCLC cell lines with NRAS mutations were screened for sensitivity against multiple targeted agents. Gene expression was profiled using Affymetrix U133A arrays in 5 NRAS mutant NSCLC cell lines, 8 with EGFR mutations and 17 with KRAS mutations. Results: Among 4524 patients with NSCLC tested, NRAS mutations were present in 29 (0.64%). The types of substitutions found were Q61H/K/L/R and G12A/C/D/R/S, with NRAS Q61L the most common (n=14; 48%). One tumor had a concurrent KRAS mutation. 83% had adenocarcinoma histology, with no significant differences in gender. While 90% of patients were former or current smokers, smoking-related G:C>T:A transversions were significantly less frequent in NRAS than in KRAS-mutant NSCLC (KRAS: 66%, NRAS: 13%, p<0.05). Systemic chemotherapy showed limited efficacy in 7 patients with metastatic disease (median OS 7 mos). 5 of 6 NRAS mutant lung cancer cell lines were sensitive to the MEK inhibitors, AZD6244 and GSK1120212, while other targeted agents (against EGFR, ALK, MET, IGF-1R, PIK3CA, BRAF) were minimally effective. Gene expression profiles of NRAS mutant cell lines were distinct from those with KRAS or EGFR mutations. Conclusions: NRAS mutations define a distinct subset of NSCLCs (~1%) with potential sensitivity to MEK inhibitors. While NRAS gene mutations are more common in current/former smokers, the types of mutations are not those classically associated with smoking.

e18547 Background: Even though local and regional controls have been substantially improved in nasopharyngeal carcinoma (NPC) in the contemporary era of intensity-modulated radiotherapy with extensive use of combined chemotherapy, the distant metastasis becomes the major cause of treatment failure and cancer-related death. To date, the genes contributed to metastasis of NPC is still unclear. The aim of this study was to identify the genes which lead to distant metastasis. Methods: A total of forty primary nonkeratinizing NPC patients were diagnosed at Shandong Cancer Hospital in this study. The formaldehyde-fixed paraffin embedded (FFPE) taken from primary sites or metastatic lymph nodes were performed next-generation sequencing (NGS) panel (Shanghai OrigiMed Co., Ltd.) to determine variated genes, such as single nucleotide variants (SNV), copy number variants (CNV) and rearrangement. These patients were followed up until Febr. 8, 2020. The genes related to distant metastasis were identified by logistic regression. Moreover, this study compared the frequency of mutated gene between our data and Catalog of Somatic Mutations in Cancer (COSMIC) database by the Chi-square test or Fisher’s exact test. Results: The study included 31 men and 9 women. The median age of the patients at diagnosis was 47 years (range 15–71 years). With the median follow-up of 10.6 months (range 16.8–72.3 months), 7 patients had distant metastasis and 1 undergone recurrent. Notably, EMSY and MCL1 variants were contributed to NPC distant metastasis (OR = 31, P = 0.049). The top eight SNV of genes in our study were CYLD, KMT2D, BAP1, EP300, TP53, ATM, NFKBIA and SPEN. When compared to COSMIC database, the mutant frequencies of CYLD, EP300 and BAP1 in our study were significantly higher than that of COSMIC database. However, the mutant frequencies of IDH2 and KMT2C were significantly lower than COSMIC database. Conclusions: This is the first study which suggests that EMSY and MCL1 variants were involved in the metastasis of NPC. The study identified 5 genes, which mutation frequency is significantly different from the COSMIC database. The study provided a molecular basis for a comprehensive understanding of, and exploring targeted therapies for nasopharyngeal carcinoma.

The discovery of mutations in cancer genes has advanced our understanding of cancer. These results are dispersed across the scientific literature and with the availability of the human genome sequence will continue to accrue. The COSMIC (Catalogue of Somatic Mutations in Cancer) database and website have been developed to store somatic mutation data in a single location and display the data and other information related to human cancer. To populate this resource, data has currently been extracted from reports in the scientific literature for somatic mutations in four genes, BRAF, HRAS, KRAS2 and NRAS. At present, the database holds information on 66 634 samples and reports a total of 10 647 mutations. Through the web pages, these data can be queried, displayed as figures or tables and exported in a number of formats. COSMIC is an ongoing project that will continue to curate somatic mutation data and release it through the website.

The Catalogue Of Somatic Mutations In Cancer (COSMIC), https://cancer.sanger.ac.uk/cosmic, is an expert-curated knowledgebase providing data on somatic variants in cancer, supported by a comprehensive suite of tools for interpreting genomic data, discerning the impact of somatic alterations on disease, and facilitating translational research. The catalogue is accessed and used by thousands of cancer researchers and clinicians daily, allowing them to quickly access information from an immense pool of data curated from over 29 thousand scientific publications and large studies. Within the last 4 years, COSMIC has substantially expanded its utility by adding new resources: the Mutational Signatures catalogue, the Cancer Mutation Census, and Actionability. To improve data accessibility and interoperability, somatic variants have received stable genomic identifiers that are associated with their genomic coordinates in GRCh37 and GRCh38, and new export files with reduced data redundancy have been made available for download.

Evolution of the Genomic Landscape in Non-Small Cell Lung Cancer

Introduction In non-small cell lung cancer (NSCLC), chromosomal translocation events that result in overactivation of the anaplastic lymphoma kinase (ALK) have been identified and shown to play a key role in tumorigenesis. Inhibitors of the ALK kinase, such as the FDA-approved crizotinib, are effective in treating ALK-fusion-positive non-small cell lung cancer. Molecular studies have identified many ALK fusion variants in various cancer types, encompassing a combination of 22 different gene partners as well as various break points within the partner genes. The most common fusion events in non-small cell lung cancer are between the echinoderm microtubule associated protein like 4 (EML4) gene and the ALK gene. Fusion events between the Kinesin Family Member 5B (KIF5B) gene and ALK have also been identified. Existing assays for ALK fusion detection include the time-consuming, costly, and challenging fluorescence in situ hybridization (FISH) method, which is the current gold standard. Next generation sequencing approaches are also available, which are also costly to implement, difficult to interpret, and have lengthy workflows. Reverse-transcriptase PCR methods are ideal, as they are cost-effective, sensitive, rapid, and require little interpretation expertise. Methodology We designed a multiplexed real-time RT-PCR method to enable indiscriminate detection of ten EML4-ALK and three KIF5B-ALK fusion variants (encompassing approximately 95% of EML4-ALK and 90% of KIF5B-ALK characterized fusion variants, based on the Catalogue of Somatic Mutations in Cancer (COSMIC) database). The assay uses standard real-time PCR instrumentation and was characterized using the Bio-Rad CFX384™, Roche LightCycler® 96, and Roche LightCycler® 480 II instruments. Assay preparation and run time requires 2 hours or less. Sensitivity testing showed that for the Roche LightCycler® 480 II and Bio-Rad CFX384™, 100% detection was achieved for 50 copies of fusion template for each of the 13 targeted variants. The Roche LightCycler® 96 showed slightly poorer sensitivity, with 100% detection observed at 50 copies for 9 fusion variants and 100 copies for the remaining four variants. Inter- and intra-run precision testing demonstrated good reproducibility and repeatability, with a coefficient of variation of less than 10% for all targeted fusion variants. Using ALK-positive and ALK-negative FFPE reference materials, it was demonstrated that 50 ng of total FFPE RNA was sufficient and up to approximately 200 ng showed good performance. Conclusion In summary, we have developed a rapid, precise, and sensitive assay for the detection of thirteen EML4-ALK and KIF5B-ALK fusion events to enable molecular characterization of non-small cell lung cancer tumors. Citation Format: Mona D. Shahbazian, Yulei Shang, Maidar Jamba, Michael J. Powell. Development of a rapid, precise, and sensitive molecular assay for ALK fusion detection [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 4648. doi:10.1158/1538-7445.AM2017-4648

Databases used for clinical interpretation in oncology rely on genetic data derived primarily from patients of European ancestry, leading to biases in cancer genetics research and clinical practice. One practical issue that arises in this context is the potential misclassification of multi-ancestral population variants as tumor-associated because they are not represented in reference genomes against which tumor sequencing data is aligned. To systematically find misclassified variants, we compared somatic variants in census genes from the Catalogue of Somatic Mutations in Cancer (COSMIC) V99 with multi-ancestral population variants from the Genome Aggregation Databases' Linkage Disequilibrium (GnomAD). By comparing genomic coordinates, reference, and alternate alleles, we could identify misclassified variants in genes associated with cancer. We found 192 of 208 genes in COSMIC's cancer-associated census genes (92.31%) to be associated with variant misclassifications. Among the 1,906,732 variants in COSMIC, 6,957 variants (0.36%) aligned with normal population variants in GnomAD, concerning for misclassification. The African / African American ancestral population included the greatest number of misclassified variants and also had the greatest number of unique misclassified variants. The direct, systematic comparison of variants from COSMIC for co-occurrence in GnomAD supports a more accurate interpretation of tumor sequencing data and reduces bias related to genomic ancestry.

226 Background: Biphenotypic (combined HCC/Cholangiocarcinoma) tumors represent a minority of primary liver cancers. While databases such as the Catalog of Somatic Mutations in Cancer (COSMIC) have genetic information on a large number of cases of HCC and Cholangiocarcinoma, there is little known about rarer Biphenotypic tumors. In this analysis we examine the results of targeted next-generation sequencing to assess genomic differences between these tumors. We utilize the COSMIC database for comparison. Methods: The database of theIRB-approved Washington University Hepatobiliary Registry identified patients with HCC, cholangiocarcinoma and biphenotypic tumors with specimens evaluated utilizing next generation sequencing via a Comprehensive Cancer Gene Set. Further data on corresponding genes was collected from the COSMIC database (v66) for comparison. Results: In this descriptive analysis 15 patients with biphenotypic tumors, 7 patients with HCC and 6 patients with cholangiocarcinoma are presented. The percent of samples with corresponding genetic mutations are outlined (table). These are compared to existing COSMIC data. Conclusions: Biphenotypic tumors had high levels of mutations in EGFR, P53 and Flt3. Mutations in MET, BRAF, CSF1, and MAPK1 were largely isolated to biphenotypic tumors. Mutations in CTNBB1 were isolated to cases of HCC. Notably, mutations in EGFR, Flt3 and FGFR4 were found in all three tumors in higher numbers than seen via review of COSMIC data. Overall, Biphenotypic tumors are genetically complex tumors that share many features of HCC and cholangiocarcinoma. [Table: see text]