Next-generation sequencing identifies novel microRNAs in peripheral blood of lung cancer patients

Keller, Andreas; Backes, Christina; Leidinger, Petra; Kefer, Nathalie; Boisguérin, Valesca; Bárbácioru, Cátálin; Vogel, Britta; Matzas, Mark; Huwer, Hanno; Katus, Hugo A.; Stähler, Cord; Meder, Benjamin; Meese, Eckart

doi:10.1039/c1mb05353a

Cited by 56 publications

(42 citation statements)

References 36 publications

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“…The standard protocol for NGS experiments has helped us uncover the potential of several sncRNAs such as piRNAs18 and miRNAs3041. tRNAs, however posed challenges even in high-throughput sequencing platforms, mainly due to their compact tertiary structure and the presence of post-transcriptional modifications.…”

Section: Discussionmentioning

confidence: 99%

Genome-wide profiling of transfer RNAs and their role as novel prognostic markers for breast cancer

Krishnan

Ghosh

Wang

et al. 2016

Sci Rep

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Transfer RNAs (tRNAs, key molecules in protein synthesis) have not been investigated as potential prognostic markers in breast cancer (BC), despite early findings of their dysregulation and diagnostic potential. We aim to comprehensively profile tRNAs from breast tissues and to evaluate their role as prognostic markers (Overall Survival, OS and Recurrence Free Survival, RFS). tRNAs were profiled from 11 normal breast and 104 breast tumor tissues using next generation sequencing. We adopted a Case-control (CC) and Case-Only (CO) association study designs. Risk scores constructed from tRNAs were subjected to univariate and multivariate Cox-proportional hazards regression to investigate their prognostic value. Of the 571 tRNAs profiled, 76 were differentially expressed (DE) and three were significant for OS in the CC approach. We identified an additional 11 tRNAs associated with OS and 14 tRNAs as significant for RFS in the CO approach, indicating that CC alone may not capture all discriminatory tRNAs in prognoses. In both the approaches, the risk scores were significant in the multivariate analysis as independent prognostic factors, and patients belonging to high-risk group were associated with poor prognosis. Our results confirmed global up-regulation of tRNAs in BC and identified tRNAs as potential novel prognostic markers for BC.

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Section: Discussionmentioning

confidence: 99%

Genome-wide profiling of transfer RNAs and their role as novel prognostic markers for breast cancer

Krishnan

Ghosh

Wang

et al. 2016

Sci Rep

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“…A substantial part of small RNA sequencing data has been obtained using HiSeq and MiSeq platforms (Illumina) based on stepwise sequencing by polymerase on DNA microarrays prepared by bridge PCR [8], as well as the IonTorrent systems from Thermo Fisher Scientific using a different type of polymerase-based stepwise sequencing on micro-bead arrays generated by emulsion PCR, the first method proposed for making microarrays for massively parallel sequencing [9]. Another approach is the ligase-based stepwise sequencing also using micro-bead arrays, applied for example by ThermoFisher Scientific’s SOLiD sequencing platform, and which has also been used to analyze and present novel miRNAs [10]. …”

Section: Introductionmentioning

confidence: 99%

cPAS-based sequencing on the BGISEQ-500 to explore small non-coding RNAs

et al. 2016

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BackgroundWe present the first sequencing data using the combinatorial probe-anchor synthesis (cPAS)-based BGISEQ-500 sequencer. Applying cPAS, we investigated the repertoire of human small non-coding RNAs and compared it to other techniques.ResultsStarting with repeated measurements of different specimens including solid tissues (brain and heart) and blood, we generated a median of 30.1 million reads per sample. 24.1 million mapped to the human genome and 23.3 million to the miRBase. Among six technical replicates of brain samples, we observed a median correlation of 0.98. Comparing BGISEQ-500 to HiSeq, we calculated a correlation of 0.75. The comparability to microarrays was similar for both BGISEQ-500 and HiSeq with the first one showing a correlation of 0.58 and the latter one correlation of 0.6. As for a potential bias in the detected expression distribution in blood cells, 98.6% of HiSeq reads versus 93.1% of BGISEQ-500 reads match to the 10 miRNAs with highest read count. After using miRDeep2 and employing stringent selection criteria for predicting new miRNAs, we detected 74 high-likely candidates in the cPAS sequencing reads prevalent in solid tissues and 36 candidates prevalent in blood.ConclusionsWhile there is apparently no ideal platform for all challenges of miRNome analyses, cPAS shows high technical reproducibility and supplements the hitherto available platforms.Electronic supplementary materialThe online version of this article (doi:10.1186/s13148-016-0287-1) contains supplementary material, which is available to authorized users.

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“…The same analysis was performed with deregulated miRNAs identified in other studies on lung cancer either on whole blood samples or on tissue specimen. We have to point out that the studies on whole blood were mostly based on the identification of deregulated miRNAs between blood from lung cancer patients and blood from healthy controls or patients with other lung diseases and not on the differentiation of the different histological lung cancer subtypes [22, 26, 28, 29]. Studies that compared miRNAs between histological subgroups of lung cancer did not use whole blood as source of the miRNA but are based on the analysis of FFPE, biopsies, brushing specimens, fine needle aspirations etc.…”

Section: Resultsmentioning

confidence: 99%

The blood-borne miRNA signature of lung cancer patients is independent of histology but influenced by metastases

et al. 2014

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ObjectivesIn our previous studies we reported a panel of 24 miRNAs that allowed discrimination between blood of lung tumor patients independent of the histological subtype and blood of healthy controls with an accuracy of 95.4% [94.9%-95.9%]. Here, we now separately analyzed the miRNA expression in blood of non-small cell lung cancer (NSCLC), including squamous cell lung cancer and adenocarcinoma, and small cell lung cancer (SCLC) patients.Patients and methodsIn total, we examined the expression levels of 1,205 miRNAs in blood samples from 20 patients from each of the three histological groups and determined differentially expressed miRNAs between histological subtypes and metastatic and non-metastatic lung cancer. We further determined the overlap of miRNAs expressed in each subgroup with the 24-miRNA signature of lung tumor patients.ResultsBased on a raw p-value < 0.05, only 18 blood-borne miRNAs were differentially expressed between patients with adenocarcinoma and with squamous cell lung carcinoma, 11 miRNAs between adenocarcinoma and SCLC, and 2 between squamous cell lung carcinoma and SCLC. Likewise, the comparison based on a fold change of 1.5 did not reveal major differences of the blood-borne miRNA expression pattern between NSCLC and SCLC. In addition, we found a large overlap between the blood-borne miRNAs detected in the three histological subgroups and the previously described 24-miRNA signature that separates lung cancer patients form controls. We identified several miRNAs that allowed differentiating between metastatic and non-metastatic tumors both in blood of patients with adenocarcinoma and in blood of patients with SCLC.ConclusionThere is a common miRNA expression pattern in blood of lung cancer patients that does not allow a reliable further subtyping into NSCLC or SCLC, or into adenocarcinoma and squamous cell lung cancer. The previously described 24-miRNA signature for lung cancer appears not primarily dependent on histological subtypes. However, metastatic adenocarcinoma and SCLC can be predicted with 75% accuracy.Electronic supplementary materialThe online version of this article (doi:10.1186/1476-4598-13-202) contains supplementary material, which is available to authorized users.

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Next-generation sequencing identifies novel microRNAs in peripheral blood of lung cancer patients

Cited by 56 publications

References 36 publications

Genome-wide profiling of transfer RNAs and their role as novel prognostic markers for breast cancer

Genome-wide profiling of transfer RNAs and their role as novel prognostic markers for breast cancer

cPAS-based sequencing on the BGISEQ-500 to explore small non-coding RNAs

The blood-borne miRNA signature of lung cancer patients is independent of histology but influenced by metastases

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