Dataset Information

Identification of novel mutations in FFPE lung adenocarcinomas using DEPArray sorting technology and next-generation sequencing.

ABSTRACT: Formalin-fixed paraffin-embedded (FFPE) tissues are utilized as the standard diagnostic method in pathology laboratories. However, admixture of unwanted tissues and shortage of normal samples, which can be used to detect somatic mutation, are considered critical factors to accurately diagnose cancer. To explore these challenges, we sorted the pure tumor cells from 22 FFPE lung adenocarcinoma tissues via Di-Electro-Phoretic Array (DEPArray) technology, a new cell sorting technology, and analyzed the variants with next-generation sequencing (NGS) for the most accurate analysis. The allele frequencies of the all gene mutations were improved by 1.2 times in cells sorted via DEPArray (tumor suppressor genes, 1.3-10.1 times; oncogenes, 1.3-2.6 times). We identified 16 novel mutations using the sequencing from sorted cells via DEPArray technology, compared to detecting 4 novel mutation by the sequencing from unsorted cells. Using this analysis, we also revealed that five genes (TP53, EGFR, PTEN, RB1, KRAS, and CTNNB1) were somatically mutated in multiple homogeneous lung adenocarcinomas. Together, we sorted pure tumor cells from 22 FFPE lung adenocarcinomas by DEPArray technology and identified 16 novel somatic mutations. We also established the precise genomic landscape for more accurate diagnosis in 22 lung adenocarcinomas with mutations detected in pure tumor cells. The results obtained in this study could offer new avenues for the treatment and the diagnosis of squamous cell lung cancers.

SUBMITTER: Lee JW

PROVIDER: S-EPMC6060994 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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Identification of novel mutations in FFPE lung adenocarcinomas using DEPArray sorting technology and next-generation sequencing.

Lee Ji Won JW Shin Jong-Yeon JY Seo Jeong-Sun JS

Journal of applied genetics 20180310 3

Formalin-fixed paraffin-embedded (FFPE) tissues are utilized as the standard diagnostic method in pathology laboratories. However, admixture of unwanted tissues and shortage of normal samples, which can be used to detect somatic mutation, are considered critical factors to accurately diagnose cancer. To explore these challenges, we sorted the pure tumor cells from 22 FFPE lung adenocarcinoma tissues via Di-Electro-Phoretic Array (DEPArray) technology, a new cell sorting technology, and analyzed ...[more]

PMID: 29525983

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Project description:ObjectivesAdenocarcinoma in situ (AIS) is an intermediate step in the progression of normal lung tissue to invasive adenocarcinoma. However, molecular mechanisms underlying this progression remain to be fully elucidated due to challenges in obtaining fresh clinical samples for downstream analyses. Formalin fixation and paraffin embedding (FFPE) is a tissue preservation system widely used for long-term storage. Until recently, challenges in working with FFPE precluded using new RNA sequencing technologies (RNA-seq), which would help clarify key pathways in cancer progression. Also, isolation techniques including laser-capture micro-dissection provide the ability to select histopathologically distinct tissues, allowing researchers to study transcriptional variations between tightly juxtaposed cell and tissue types.Materials and methodsUtilizing these technologies and new alignment tools we examined differential expression of long intergenic non-coding RNAs (lincRNAs) and mRNAs across normal, AIS and invasive adenocarcinoma samples from six patients to identify possible markers of lung cancer progression.ResultsRNA extracted and sequenced from these 18 samples generated an average of 198 million reads per sample. After alignment and filtering, uniquely aligned reads represented an average 35% of the total reads. We detected differential expression of a number of lincRNAs and mRNAs when comparing normal to AIS, or AIS to invasive adenocarcinoma. Of these, 5 lincRNAs and 31 mRNAs were consistently up- or down-regulated from normal to AIS and more so to invasive carcinoma. We validated the up-regulation of two mRNAs and one lincRNA by RT-qPCR as proof of principle.ConclusionOur findings indicate a potential role of not only mRNAs, but also lincRNAs in the progression to invasive adenocarcinoma. We anticipate that these findings will lay the groundwork for future experimental studies of candidate RNAs from FFPE to identify their functional roles in lung cancer.

Project description:Although targeted therapy has emerged as an effective treatment strategy for non-small cell lung cancer (NSCLC), some patients cannot benefit from such therapy due to the limited number of therapeutic targets. The present study aimed to identify mutated genes associated with clinicopathological characteristics and prognosis and to screen for mutations that are not concurrent with applicable drug target sites in patients with NSCLC. Tumor tissue and blood samples were obtained from 97 patients with NSCLC. A lung cancer-specific panel of 55 genes was established and analyzed using next-generation sequencing (NGS). The results obtained from the clinical cohort were compared with the NSCLC dataset from The Cancer Genome Atlas (TCGA). Subsequently, 25 driver genes were identified by taking the intersection of the 55 lung-cancer-specific genes with three databases, namely, the Catalog of Somatic Mutations in Cancer database, the Network of Cancer Genes database and Vogelstein's list. Functional annotation and protein-protein interaction analysis were conducted on these 25 driver genes. The χ2 test and logistic regression were used to evaluate the association between mutations in the 25 driver genes and the clinicopathological characteristics of 97 patients, and phosphatase and tensin homolog (PTEN) and kirsten rat sarcoma viral oncogene homolog (KRAS) were associated with stage at diagnosis and sex, respectively, while epidermal growth factor receptor (EGFR) was associated with sex, stage at diagnosis, metastasis, CEA and CYFRA21-1. Moreover, the association between the 25 driver gene mutations and overall survival were examined using Cox regression analysis. Age and Notch homolog 2 (NOTCH2) mutations were independent prognostic factors in TCGA dataset. The correlations between statistically significant mutations in EGFR, KRAS, PTEN and NOTCH2 were further examined, both in the clinical data and TCGA dataset. There was a negative correlation between EGFR and NOTCH2 mutations (correlation coefficient, -0.078; P=0.027). Thus, the present study highlights the importance of NOTCH2 mutations and might provide novel therapeutic options for patients with NSCLC who do not harbor EGFR mutations.

Dataset Information

Identification of novel mutations in FFPE lung adenocarcinomas using DEPArray sorting technology and next-generation sequencing.

Publications

Identification of novel mutations in FFPE lung adenocarcinomas using DEPArray sorting technology and next-generation sequencing.

Similar Datasets

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