Unknown,Transcriptomics,Genomics,Proteomics

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A high dimensional deep sequencing study of non-small cell lung adenocarcinoma in never-smoker Korean females [Seq]

ABSTRACT: One of the most fertile applications of next generation sequencing will be in the field of cancer genomics. Here, we report a high-throughput multi-dimensional sequencing study of primary non-small cell lung adenocarcinoma tumors and adjacent normal tissues of 6 never-smoker Korean female patients. Our data encompass results from exome-seq, RNA-seq, small RNA-seq, and MeDIP-seq. We identified and validated novel genetic aberrations including 47 somatic mutations and 20 fusion transcripts. We also characterized gene expression profiles which we sought to integrate with genomic aberrations and epigenetic regulations into functional networks. Importantly, among others the gene network module governing G2/M cell check point emerged as the primary source of disturbance in these patients. In addition, our study strongly suggests that microRNAs make key regulatory inputs into this gene network module. Our study offers a paradigm for integrative genomics analysis and proposes potential target pathways for the control of non-small cell lung adenocarcinoma. Study of primary non-small cell lung adenocarcinoma tumors and normal tissues of 6 patients.

ORGANISM(S): Homo sapiens

SUBMITTER: Sanghyuk Lee

PROVIDER: E-GEOD-37764 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

A high-dimensional, deep-sequencing study of lung adenocarcinoma in female never-smokers.

Kim Sang Cheol SC Jung Yeonjoo Y Park Jinah J Cho Sooyoung S Seo Chaehwa C Kim Jaesang J Kim Pora P Park Jehwan J Seo Jihae J Kim Jiwoong J Park Seongjin S Jang Insu I Kim Namshin N Yang Jin Ok JO Lee Byungwook B Rho Kyoohyoung K Jung Yeonhwa Y Keum Juhee J Lee Jinseon J Han Jungho J Kang Sangeun S Bae Sujin S Choi So-Jung SJ Kim Sujin S Lee Jong-Eun JE Kim Wankyu W Kim Jhingook J Lee Sanghyuk S

PloS one 20130206 2

<h4>Background</h4>Deep sequencing techniques provide a remarkable opportunity for comprehensive understanding of tumorigenesis at the molecular level. As omics studies become popular, integrative approaches need to be developed to move from a simple cataloguing of mutations and changes in gene expression to dissecting the molecular nature of carcinogenesis at the systemic level and understanding the complex networks that lead to cancer development.<h4>Results</h4>Here, we describe a high-throug ...[more]

PMID: 23405175

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Project description:Clear cell renal cell carcinoma (ccRCC) initiated from the renal epithelium is the most prevalent histological type of adult kidney cancers. Dissecting intratumoral heterogeneity (ITH) of ccRCC has leveraged to extend our knowledge on how primary tumors harboring driver mutations evolve and spread to other sites. The cellular fractions within and across the primary (pRCC) and metastatic RCC (mRCC) are heterogeneous in both their genetic and biological features determining the variability in clinical aggressiveness and sensitivity to the therapy. To achieve sustainable therapeutic benefit with targeted agents in mRCC, the effective target should focus on signaling pathways that are related to driver mutations occurred early in the clonal evolution of the disease and thus should be common to primary tumor and metastatic sites. Considering that extensive genetic heterogeneity may result in drug response variability among patients and treatment resistance, the tailored strategies for metastatic RCC is urgently needed. Here, we analyze single-cell RNA-seq (scRNA-seq) data from a matched primary RCC (pRCC) and lung metastasis (mRCC) to dissect ITH at the highest resolution to date with the objective of discovering the better therapeutic regimen. In order to identify successful clonal propagation from patient to PDX samples and understand pathogenesis from primary to metastatic RCC, we performed whole-exome sequencing (WES, n=4) and matched aCGH (n=4) on bulk tumor samples. And we utilized single-cell RNA sequencing (scRNA-seq) to model and dissect functional heterogeneity acroass primary and metastatic RCC tumors. We checked whether of capturing live one cell, not more cells, in microfluidics by fluorescent microscopic observation. To construct RNA sequencing libraries, we performed further quality controls including adequate quantities and qualities of amplified transcriptomes respectively from single cells. Tumor cells from the parental mRCC (n=34), PDX-mRCC (n=36) and PDX-pRCC (n=46) were finally analyzed in this study after filtering out poor quality cells.

Dataset Information

A high dimensional deep sequencing study of non-small cell lung adenocarcinoma in never-smoker Korean females [Seq]

Publications

A high-dimensional, deep-sequencing study of lung adenocarcinoma in female never-smokers.

Similar Datasets

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