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Identification of mRNAs and lincRNAs associated with lung cancer progression using next-generation RNA sequencing from laser micro-dissected archival FFPE tissue specimens

ABSTRACT: Adenocarcinoma in situ (AIS) is considered an intermediate step in the progression of normal lung tissue to invasive adenocarcinoma. However, the molecular mechanisms underlying this progression remain to be fully elucidated due to difficulties in obtaining and preserving clinical samples for downstream analyses. Formalin fixation and paraffin embedding (FFPE) is a tissue preservation system that is widely used as a means for long-term storage. Until now, challenges in working with FFPE have precluded using new RNA sequencing technologies (RNA-seq), which would help clarify some of the key pathways affected in the transition from normal to AIS to invasive adenocarcinoma. Recent technological advances have made it possible to sequence RNA from archival tissues. 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. Utilizing these technologies and new alignment tools we examined differential expression of long intergenic non-coding RNAs and mRNAs across normal, AIS and invasive adenocarcinoma samples from six patients to identify possible markers of lung cancer progression. RNA 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. Our findings indicate a potential role of not only mRNAs, but also lincRNAs in invasive adenocarcinoma. We anticipate that our current findings will lay the groundwork for future experimental studies of candidate RNAs from FFPE samples to identify their functional roles in lung cancer.

ORGANISM(S): Homo sapiens

PROVIDER: GSE52248 | GEO | 2014/12/01

SECONDARY ACCESSION(S): PRJNA227275

REPOSITORIES: GEO

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Project description:Background: The differential abundance of cell-free RNAs in bodily fluids is emerging as a promising tool for the non-invasive molecular diagnosis of cancer. Human saliva is considered a promising source of non-invasive biomarkers of diagnostic value for oral cancer detection. This study aims to identify diagnostic potent salivary RNAs in oral squamous cell carcinoma (OSCC)-patients by RNA-Sequencing. Method: Unstimulated saliva was collected from 5 normal control (NC) individuals and 9 OSCC patients (PS) with prior consent and ethical committee approvals. Total RNA isolated from cell-free saliva (CFS) supernatant was used to prepare small RNA libraries and sequenced on the Ion Torrent S5 platform. The sequencing reads were aligned to the human genome (hg19) using Bowtie 2, and the differential expression analysis was performed using RUVSeq and DESeq2. Mapped reads were screened across miRBase (v22) annotations for miRNAs and Gencode (v19) annotation for other RNAs. Reads were quantified by the Featurecount (v1.4.6) module of the R-package. The microbial-RNA enrichment analysis was determined using the One Codex platform. Result: RNA-sequencing detected protein-coding transcripts (PCTs), long-intergenic RNAs (lincRNAs), microRNAs (miRNAs), small nuclear RNAs (snRNAs), transfer RNAs (tRNAs) and pseudogenes from the saliva of PS and HC samples. Transcriptome analyses revealed 89 PCTs, 18 lincRNAs and 6 miRNAs differentially expressed between PS and HC with a log2fold change ≥ 1 or ≤ -1 and p-value < 0.05. Gene ontology and pathway enrichment analyses indicated a significant correlation of the identified PCTs and miRNAs to various cancer-related pathways that may have implications in the pathogenesis of OSCC. Interestingly, unmapped non-human reads aligned to the microbial reference genomes. Further analyses of these microbial sequence reads revealed a significant microbial dysbiosis differentiating PS from HC. Metabolic pathways and functional analysis of the identified microbial phylotypes showed gene ontologies associated with inflammation, cell proliferation, ROS generation, and a range of metabolic processes. Conclusion: We report novel panels of differentially expressed PCTs, miRNAs and lincRNAs distinguishing PS from HC. Importantly, our results also provide evidence for oral microbial dysbiosis that appears to have pathological implications in OSCC. Summarily, this study provides a comprehensive landscape of salivary RNAs that can be exploited as non-invasive biomarkers for OSCC detection.

Project description:Advantages of RNA-Seq over array based platforms are quantitative gene expression and discovery of expressed single nucleotide variants (eSNVs) and fusion transcripts from a single platform, but the sensitivity for each of these characteristics is unknown. We measured gene expression in a set of manually degraded RNAs, nine pairs of matched fresh-frozen, and FFPE RNA isolated from breast tumor with the hybridization based, NanoString nCounter, (226 gene panel) and with whole transcriptome RNA-Seq using RiboZeroGold ScriptSeq V2 library preparation kits. We performed correlation analyses of gene expression between samples and across platforms. We then specifically assessed whole transcriptome expression of lincRNA and discovery of eSNVs and fusion transcripts in the FFPE RNA-Seq data. For gene expression in the manually degraded samples, we observed Pearson correlation of >0.94 and >0.80 with NanoString and ScriptSeq protocols respectively. Gene expression data for matched fresh-frozen and FFPE samples yielded mean Pearson correlations of 0.874 and 0.783 for NanoString (226 genes) and ScriptSeq whole transcriptome protocols respectively. Specifically for lincRNAs, we observed superb Pearson correlation (0.988) between matched fresh-frozen and FFPE pairs. FFPE samples across NanoString and RNA-Seq platforms gave a mean Pearson correlation of 0.838. In FFPE libraries, we detected 53.4% of high confidence SNVs and 24% of high confidence fusion transcripts. Sensitivity of fusion transcript detection was not overcome by an increase in depth of sequencing up to 3-fold (increase from ~56 to ~159 million reads). Both NanoString and ScriptSeq RNA-Seq technologies yield reliable gene expression data for degraded and FFPE material. The high degree of correlation between NanoString and RNA-Seq platforms suggests discovery based whole transciptome studies from FFPE material will produce reliable expression data. The RiboZeroGold ScriptSeq protocol performed particularly well for lincRNA expression from FFPE libraries but detection of eSNV and fusion transcripts was less sensitive.

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Identification of mRNAs and lincRNAs associated with lung cancer progression using next-generation RNA sequencing from laser micro-dissected archival FFPE tissue specimens

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