Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2020 Jun;9(3):670-681.
doi: 10.21037/tlcr-19-401.

Integrated analysis of optical mapping and whole-genome sequencing reveals intratumoral genetic heterogeneity in metastatic lung squamous cell carcinoma

Yizhou Peng  1   2 , Chongze Yuan  1   2 , Xiaoting Tao  1   2 , Yue Zhao  1   2 , Xingxin Yao  1   2 , Lingdun Zhuge  1   2 , Jianwei Huang  3 , Qiang Zheng  2   4 , Yue Zhang  3 , Hui Hong  1   2 , Haiquan Chen  1   2 , Yihua Sun  1   2
Affiliations

Integrated analysis of optical mapping and whole-genome sequencing reveals intratumoral genetic heterogeneity in metastatic lung squamous cell carcinoma

Yizhou Peng et al. Transl Lung Cancer Res. 2020 Jun.

Abstract

Background: Intratumoral heterogeneity is a crucial factor to the outcome of patients and resistance to therapies, in which structural variants play an indispensable but undiscovered role.

Methods: We performed an integrated analysis of optical mapping and whole-genome sequencing on a primary tumor (PT) and matched metastases including lymph node metastasis (LNM) and tumor thrombus in the pulmonary vein (TPV). Single nucleotide variants, indels and structural variants were analyzed to reveal intratumoral genetic heterogeneity among tumor cells in different sites.

Results: Our results demonstrated there were less nonsynonymous somatic variants shared with PT in LNM than in TPV, while there were more structural variants shared with PT in LNM than in TPV. More private variants and its affected genes associated with tumorigenesis and progression were identified in TPV than in LNM. It should be noticed that optical mapping detected an average of 77.1% (74.5-78.5%) large structural variants (>5,000 bp) not detected by whole-genome sequencing and identified several structural variants private to metastases.

Conclusions: Our study does demonstrate structural variants, especially large structural variants play a crucial role in intratumoral genetic heterogeneity and optical mapping could make up for the deficiency of whole-genome sequencing to identify structural variants.

Keywords: Heterogeneity; lung squamous cell carcinoma (LUSC); metastasis; optical mapping; structural variants.

PubMed Disclaimer

Conflict of interest statement

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/tlcr-19-401). The authors have no conflicts of interest to declare.

Figures

Figure 1
Figure 1
Clinical and histological diagnostic results of a patient with LUSC. (A) Schematic diagram of the primary tumors (PT) and lymph node metastases (LNM) and tumor thrombus in pulmonary vein (TPV). (B) Preoperative enhanced computerized tomography (enhanced-CT) scanning showed the PT (upper), LNM (middle) and TPV (lower). (C) Postoperative paraffin section and hematoxylin and eosin (H&E) staining image based on 400× magnification. Tumor cells in PT, LNM and TPV were moderately or poorly differentiated. PT, primary tumor; LNM, lymph node metastases; TPV, tumor thrombus in pulmonary vein.
Figure 2
Figure 2
Exonic somatic variants identified in PT, LNM and TPV. The exonic somatic variants were classified as shared or private variants. Red color represent genes contain different variants among different tumors. PT, primary tumor; LNM, lymph node metastases; TPV, tumor thrombus in pulmonary vein.
Figure 3
Figure 3
Intratumoral genetic heterogeneity in form of SNVs and indels. (A) The number of exonic somatic variants (SNVs and indels) and nonsynonymous somatic variants in each of tumors. (B) The mutation spectrum of SNVs in PT, LNM and TPV. (C) Mutational signatures of all tumor sample. (D) Two mutational signatures (S1, S2) extracted from all tumors. (E) Cluster analysis of S1, S2 and 30 COSMIC mutational signature based on the cosine similarity. (F) The proportion of S1 and S2 in PT, LNM and TPV. PT, primary tumor; LNM, lymph node metastases; TPV, tumor thrombus in pulmonary vein.
Figure 4
Figure 4
Workflow for detection of structural variants. The workflow for extracting structural variants from a combination of whole-genome sequencing and optical mapping. Detail explanation seen in Methods.
Figure 5
Figure 5
Comparison of structural variants detected by WGS and optical mapping. (A) The number of structural variants detected by whole-genome sequencing and optical mapping. (B) The number of different types of structural variants detected by whole-genome sequencing and optical mapping in TPV. (C) Size distribution of deletions in TPV. (D) The number of large structural variants (>5,000 bp) detected by whole-genome sequencing and optical mapping in TPV. TPV, tumor thrombus in pulmonary vein.
Figure 6
Figure 6
Intratumoral genetic heterogeneity in form of structural variants. (A) Overlap of structural variants detected by whole-genome sequencing (upper) and optical mapping (lower) among PT, LNM and TPV. (B) Genes associated with tumorigenesis and progression affected by structural variants detected by whole-genome sequencing and optical mapping in PT, LNM and TPV. (C) Genes associated with prognosis of lung cancer affected by structural variants detected by whole-genome sequencing and optical mapping. (Red dotted line represents P value >0.05) (D) KEGG enrichment of genes only affected by metastases-specific structural variants. (Red dotted line represents adjusted P value >0.05). PT, primary tumor; LNM, lymph node metastases; TPV, tumor thrombus in pulmonary vein.
Figure S1
Figure S1
Postoperative paraffin section and hematoxylin and eosin (H&E) staining image for PT (A and B), LNM (C) and TPV (D) based on 40–100× magnification. PT, primary tumor; LNM, lymph node metastases; TPV, tumor thrombus in pulmonary vein.
Figure S2
Figure S2
The proportions of different types of SVs detected by whole-genome sequencing (left) or optical mapping (right) in PT (upper), LNM (middle) and TPV (lower). PT, primary tumor; LNM, lymph node metastases; TPV, tumor thrombus in pulmonary vein.
Figure S3
Figure S3
The number of different types of structural variants detected by whole-genome sequencing and optical mapping in PT (A) and LNM (C), of which size distribution of deletions in PT (B) and LNM (D). PT, primary tumor; LNM, lymph node metastases.
See this image and copyright information in PMC

References

    1. Bray F, Ferlay J, Soerjomataram I, et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2018;68:394-424. 10.3322/caac.21492 - DOI - PubMed
    1. Campbell JD, Alexandrov A, Kim J, et al. Distinct patterns of somatic genome alterations in lung adenocarcinomas and squamous cell carcinomas. Nat Genet 2016;48:607-16. 10.1038/ng.3564 - DOI - PMC - PubMed
    1. Meng F, Zhang L, Ren Y, et al. The genomic alterations of lung adenocarcinoma and lung squamous cell carcinoma can explain the differences of their overall survival rates. J Cell Physiol 2019;234:10918-25. 10.1002/jcp.27917 - DOI - PubMed
    1. Langer CJ, Obasaju C, Bunn P, et al. Incremental Innovation and Progress in Advanced Squamous Cell Lung Cancer: Current Status and Future Impact of Treatment. J Thorac Oncol 2016;11:2066-81. 10.1016/j.jtho.2016.08.138 - DOI - PubMed
    1. Gandara DR, Hammerman PS, Sos ML, et al. Squamous cell lung cancer: from tumor genomics to cancer therapeutics. Clin Cancer Res 2015;21:2236-43. 10.1158/1078-0432.CCR-14-3039 - DOI - PMC - PubMed