Preferable background filtering for next-generation sequencing analysis in non-small cell lung cancer: pericarcinomatous tissues or peripheral blood lymphocytes?
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non-small-cell lung cancer
epidermal growth factor receptor
kirsten rat sarcoma viral oncogene
The Cancer Genome Atlas
tumor suppressor gene
v-Raf murine sarcoma viral oncogene homolog B
Lung cancer is the leading cause of cancer-related death worldwide, with the predominant pathological type being non-small cell lung cancer (NSCLC) [1, 2]. Next-generation sequencing (NGS) analysis is increasingly used to help clinicians select appropriate target therapies, such as epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) for EGFR-mutant patients . Both pericarcinomatous tissues and peripheral blood lymphocytes are widely used as normal control for NGS analysis. However, whether pericarcinomatous tissue is suitable for background filtering in mutation analysis remains controversial. According to the whole-genome sequencing data from The Cancer Genome Atlas (TCGA) database, there were some genomic variations in pericarcinomatous tissue from NSCLC patients, but no driver gene mutation was detected [4, 5]. Therefore, deep sequencing of pericarcinomatous and tumor tissues is necessary to confirm whether pericarcinomatous tissue harbors low-frequency mutations.
Genotyping with NGS has been demonstrated to be clinically effective in guiding NSCLC treatment. It helps oncologists to find druggable mutations for targeted therapy [6, 7] and potential targetable genomic alterations for drug development [8, 9]. Previous studies reported the detection of genomic alterations in pericarcinomatous tissues from NSCLC patients [4, 5], but the significance of these mutations in lung carcinogenesis remains unclear. Moreover, it is important to determine whether pericarcinomatous tissue from NSCLC patients can serve as background sample for genomic filtering for germline mutations to increase the accuracy of NGS results.
Thus, we performed deep targeted capture sequencing with pericarcinomatous and tumor tissues. We found that tumor-derived mutations indeed existed in nearly 20% of pericarcinomatous tissues from NSCLC patients, which indicated that pericarcinomatous tissue might not be recommended as background filter for genomic analysis in NSCLC. Neither EGFR nor KRAS was detected in pericarcinomatous tissues, whereas BRAF and RET were detected. This result suggests that matched pericarcinomatous tissue might not act as normal control for detecting oncogenes. Remarkably, mutations in androgen receptor (AR), serine/threonine kinase 11 (STK11), TP53, neurofibromin 1 (NF1), BRAF, and neurogenic locus notch homolog protein 2 (NOTCH2) genes were detected in pericarcinomatous tissues, and these genes are associated with epithelial–mesenchymal transition (EMT). However, EMT is a complex process which is regulated by a multi-level molecular signalling pathway, instead of a single gene mutation. Some mutations of tumor-derived genes detected in pericarcinomatous tissues are related to EMT. However, their roles in EMT formation should be further explored and validated.
Although the present study showed several interesting findings, our conclusions may be affected by several limitations. First, the small cohort size was a limitation. Further study enrolling more patients is needed. Second, we did not measure and record the exact distance between the pericarcinomatous site and the primary tumor location. During the sample collection, the pericarcinomatous tissue was collected at the furthest distance (visible to the naked eyes) from the tumor in resected specimen (at least 5 cm from the tumor). As a result, it is not possible to evaluate whether those mutation-negative pericarcinomatous samples were further away from the primary tumor sites as compared with mutation-positive ones. Future studies are warranted to address this issue. Additionally, we used panel target capture sequencing instead of whole exome or genome sequencing for analyses, which might have resulted in some missing data, especially in passenger gene regions. However, we used a pan-cancer panel that included 1021 genes related to solid tumor carcinogenesis for sequencing analyses, and this panel showed a significant consistency with exome sequencing for detecting mutation number using the Pearson correlation analysis. Although we cannot rule out missing data entirely, panel sequencing may be a more applicable and cost-effective method for such analyses.
Tumor-derived mutations exist in pericarcinomatous tissues from patients with NSCLC, mostly enriched in trunk mutations and TSGs. Neither EGFR nor KRAS mutations were detected in pericarcinomatous tissues, whereas BRAF and RET were detected. It suggests that pericarcinomatous tissue should be neither recommended as filtering background for genomics analysis nor suitable for detecting druggable oncogenes of NSCLC.
YZ and LZ designed this study. YZ, WF and YY collected clinical data. YZ, LZ, SH and HZ collected samples. LC, YG and XY made sequencing and statistical analysis. All authors wrote the manuscript. All authors read and approved the final manuscript.
This work was supported by the National Key R&D Program of China (Grant No. 2016YFC0905500, 2016YFC0905503), Science and Technology Program of Guangdong (Grant No. 2017B020227001, 2016A020215084), Science and Technology Program of Guangzhou (Grant No. 201607020031, 201400000001-2), Chinese National Natural Science Foundation Project (Grant No. 81772476, 81572659, 81602011), Pearl River Nova Program of Guangzhou (Grant No. 201610010048), and National Natural Science Funds for Young Scholars of China (Grant No. 81502355).
Ethics approval and consent to participate
This study was approved by the Institutional Review Board (IRB) of Sun Yat-sen University Cancer Center (IRB number B2017-067-01).
Consent for publication
All patients provided written informed consent.
The authors declare that they have no competing interests.
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