Abstract
Objectives
Copy number alterations (CNAs) are frequently found in malignant tissues. Different approaches have been used for CNA detection. However, it is not easy to detect a large panel of CNA targets in heterogenous tumors.
Methods
We have developed a CNAs detection approach through quantitatively analyzed allelic imbalance by allelotyping single nucleotide polymorphisms (SNPs) by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Furthermore, the copy number changes were quantified by real-competitive PCR (rcPCR) to distinguish loss of heterozygosity (LOH) and genomic amplification. The approach was used to validate the CNA regions detected by next generation sequencing (NGS) in early-stage lung carcinoma.
Results
CNAs were detected in heterogeneous DNA samples where tumor DNA is present at only 10% through the SNP based allelotyping. In addition, two different types of CNAs (loss of heterozygosity and chromosome amplification) were able to be distinguished quantitatively by rcPCR. Validation on a total of 41 SNPs from the selected CNA regions showed that copy number changes did occur, and the tissues from early-stage lung carcinoma were distinguished from normal.
Conclusions
CNA detection by MALDI-TOF MS can be used for validating potentially interesting genomic regions identified from next generation sequencing, and for detecting CNAs in tumor tissues consisting of a mixture of neoplastic and normal cells.
Funding source: High-Level Innovation Team of Universities in Zhejiang Province
Award Identifier / Grant number: 604090352/610
Funding source: Key Discipline of Zhejiang Province in Medical Technology (Fist Class, Category A)
Award Identifier / Grant number: 437601607
Funding source: Zhejiang Provincial Natural Science Foundation of China
Award Identifier / Grant number: LY19H160027
Acknowledgments
The authors thank all patients for participating in the study and the doctors and nurses for clinical support.
-
Research funding: This work was supported by Zhejiang Provincial Natural Science Foundation of China (DX: Grant No. LY19H160027), High-Level Innovation Team of Universities in Zhejiang Province (CD: Grant No. 604090352/610), and Key Discipline of Zhejiang Province in Medical Technology (Fist Class, Category A) (Grant No. 437601607).
-
Author contributions: Chunming Ding, Shengnan Jin and Deyao Xie design of the project, and led the writing of the manuscript. Chunming Ding, Shengnan Jin, Dan Huang, Weijiang Jin, Yourong Wang participated in study design and data interpretation; Hengrong Shao, Lisha Gong, Zhenni Luo, Zhengquan Yang, Ju Luan analyzed the data; Deyao Xie provided clinical expertise. All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
-
Competing interests: The authors declare no competing interests.
-
Informed consent: Informed consent was obtained from all individuals included in this study.
-
Ethical approval: The study was approved by the Clinical Research Ethics of the First Affiliated Hospital of Wenzhou Medical University (2019-ky-50).
References
1. Little, CD, Nau, MM, Carney, DN, Gazdar, AF, Minna, JD. Amplification and expression of the c-myc oncogene in human lung cancer cell lines. Nature 1983;306:194–6. https://doi.org/10.1038/306194a0.Search in Google Scholar PubMed
2. Vogelstein, B, Fearon, ER, Kern, SE, Hamilton, SR, Preisinger, AC, Nakamura, Y, et al.. Allelotype of colorectal carcinomas. Science 1989;244:207–11. https://doi.org/10.1126/science.2565047.Search in Google Scholar PubMed
3. Harbers, L, Agostini, F, Nicos, M, Poddighe, D, Bienko, M, Crosetto, N. Somatic copy number alterations in human cancers: an analysis of publicly available data from the cancer genome atlas. Front Oncol 2021;11:700568. https://doi.org/10.3389/fonc.2021.700568.Search in Google Scholar PubMed PubMed Central
4. Nahta, R. Molecular mechanisms of trastuzumab-based treatment in HER2-overexpressing breast cancer. ISRN Oncol 2012;2012:428062. https://doi.org/10.5402/2012/428062.Search in Google Scholar PubMed PubMed Central
5. Nielsen, DL, Kumler, I, Palshof, JA, Andersson, M. Efficacy of HER2-targeted therapy in metastatic breast cancer. Monoclonal antibodies and tyrosine kinase inhibitors. Breast 2013;22:1–12. https://doi.org/10.1016/j.breast.2012.09.008.Search in Google Scholar PubMed
6. Wang, Q, Yang, S, Wang, K, Sun, SY. MET inhibitors for targeted therapy of EGFR TKI-resistant lung cancer. J Hematol Oncol 2019;12:63. https://doi.org/10.1186/s13045-019-0759-9.Search in Google Scholar PubMed PubMed Central
7. Nemtsova, MV, Bykov, II, Udilova, AA, Zaletaev, DV, Khorobrykh, TV. Allelic imbalance of 17p13.1 (TP53), 1p36.1 (RUNX3), and 16p22 (CDH1) loci and microsatellite instability in gastric cancer. Mol Biol 2013;47:727–32. https://doi.org/10.1134/s0026893313050154.Search in Google Scholar
8. Kettunen, E, Aavikko, M, Nymark, P, Ruosaari, S, Wikman, H, Vanhala, E, et al.. DNA copy number loss and allelic imbalance at 2p16 in lung cancer associated with asbestos exposure. Br J Cancer 2009;100:1336–42. https://doi.org/10.1038/sj.bjc.6605012.Search in Google Scholar PubMed PubMed Central
9. Kallioniemi, A, Kallioniemi, OP, Sudar, D, Rutovitz, D, Gray, JW, Waldman, F, et al.. Comparative genomic hybridization for molecular cytogenetic analysis of solid tumors. Science 1992;258:818–21. https://doi.org/10.1126/science.1359641.Search in Google Scholar PubMed
10. Piazza, R, Magistroni, V, Pirola, A, Redaelli, S, Spinelli, R, Redaelli, S, et al.. CEQer: a graphical tool for copy number and allelic imbalance detection from whole-exome sequencing data. Plos One 2013;8:e74825. https://doi.org/10.1371/journal.pone.0074825.Search in Google Scholar PubMed PubMed Central
11. Lindblad-Toh, K, Tanenbaum, DM, Daly, MJ, Winchester, E, Lui, W, Villapakkam, A, et al.. Loss-of-heterozygosity analysis of small-cell lung carcinomas using single-nucleotide polymorphism arrays. Nat Biotechnol 2000;18:1001–5. https://doi.org/10.1038/79269.Search in Google Scholar PubMed
12. Mei, R, Galipeau, PC, Prass, C, Berno, A, Ghandour, G, Patil, N, et al.. Genome-wide detection of allelic imbalance using human SNPs and high-density DNA arrays. Genome Res 2000;10:1126–37. https://doi.org/10.1101/gr.10.8.1126.Search in Google Scholar PubMed PubMed Central
13. Staaf, J, Lindgren, D, Vallon-Christersson, J, Isaksson, A, Göransson, H, Juliusson, G, et al.. Segmentation-based detection of allelic imbalance and loss-of-heterozygosity in cancer cells using whole genome SNP arrays. Genome Biol 2008;9:R136. https://doi.org/10.1186/gb-2008-9-9-r136.Search in Google Scholar PubMed PubMed Central
14. Liu, Z, Li, A, Schulz, V, Chen, M, Tuck, D. MixHMM: inferring copy number variation and allelic imbalance using SNP arrays and tumor samples mixed with stromal cells. Plos One 2010;5:e10909. https://doi.org/10.1371/journal.pone.0010909.Search in Google Scholar PubMed PubMed Central
15. Bobach, IS, Stougaard, M. SNP-based detection of allelic imbalance: a novel approach for identifying KIAA1549-BRAF fusion in pilocytic astrocytoma using DNA sequencing. Exp Mol Pathol 2021;120:104621. https://doi.org/10.1016/j.yexmp.2021.104621.Search in Google Scholar PubMed
16. Assie, G, LaFramboise, T, Platzer, P, Bertherat, J, Stratakis, CA, Eng, C. SNP arrays in heterogeneous tissue: highly accurate collection of both germline and somatic genetic information from unpaired single tumor samples. Am J Hum Genet 2008;82:903–15. https://doi.org/10.1016/j.ajhg.2008.01.012.Search in Google Scholar PubMed PubMed Central
17. Silva, GO, Siegel, MB, Mose, LE, Parker, JS, Sun, W, Perou, CM, et al.. SynthEx: a synthetic-normal-based DNA sequencing tool for copy number alteration detection and tumor heterogeneity profiling. Genome Biol 2017;18:66. https://doi.org/10.1186/s13059-017-1193-3.Search in Google Scholar PubMed PubMed Central
18. Whale, AS, Huggett, JF, Cowen, S, Speirs, V, Shaw, J, Ellison, S, et al.. Comparison of microfluidic digital PCR and conventional quantitative PCR for measuring copy number variation. Nucleic Acids Res 2012;40:e82. https://doi.org/10.1093/nar/gks203.Search in Google Scholar PubMed PubMed Central
19. Ross, P, Hall, L, Haff, LA. Quantitative approach to single-nucleotide polymorphism analysis using MALDI-TOF mass spectrometry. Biotechniques 2000;29:620–9. https://doi.org/10.2144/00293rr05.Search in Google Scholar PubMed
20. Werner, M, Sych, M, Herbon, N, Illig, T, König, IR, Wjst, M. Large-scale determination of SNP allele frequencies in DNA pools using MALDI-TOF mass spectrometry. Hum Mutat 2002;20:57–64. https://doi.org/10.1002/humu.10094.Search in Google Scholar PubMed
21. Ding, C, Maier, E, Roscher, AA, Braun, A, Cantor, CR. Simultaneous quantitative and allele-specific expression analysis with real competitive PCR. BMC Genet 2004;5:8. https://doi.org/10.1186/1471-2156-5-8.Search in Google Scholar PubMed PubMed Central
22. Qiu, C, Kumar, S, Jia, G, Lu, J, Shi, S, Kalachikov, SM, et al.. Mitochondrial single nucleotide polymorphism genotyping by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry using cleavable biotinylated dideoxynucleotides – scienceDirect. Anal Biochem 2012;427:202–10. https://doi.org/10.1016/j.ab.2012.05.001.Search in Google Scholar PubMed
23. Ding, C, Cantor, CR. A high-throughput gene expression analysis technique using competitive PCR and matrix-assisted laser desorption ionization time-of-flight MS. Proc Natl Acad Sci U S A 2003;100:3059–64. https://doi.org/10.1073/pnas.0630494100.Search in Google Scholar PubMed PubMed Central
24. Bansal, A, van den Boom, D, Kammerer, S, Honisch, C, Adam, G, Cantor, CR, et al.. Association testing by DNA pooling: an effective initial screen. Proc Natl Acad Sci 2002;99:16871–4. https://doi.org/10.1073/pnas.262671399.Search in Google Scholar PubMed PubMed Central
25. Seymour, AB, Hruban, RH, Redston, M, Caldas, C, Powell, SM, Kiuzler, KW, et al.. Allelotype of pancreatic cancer using xenograft enrichment. Cancer Res 1995;55:4670–5.Search in Google Scholar
26. Xia, R, Vattathil, S, Scheet, P. Identification of allelic imbalance with a statistical model for subtle genomic mosaicism. PLoS Comput Biol 2014;10:e1003765. https://doi.org/10.1371/journal.pcbi.1003765.Search in Google Scholar PubMed PubMed Central
27. Lo, KW, Teo, PML, Hui, ABY, To, KF, Tsang, YS, Chan, SYY, et al.. High resolution allelotype of microdissected primary nasopharyngeal carcinoma. Cancer Res 2000;60:3348–53.Search in Google Scholar
28. Liu, A. Laser capture microdissection in the tissue biorepository. J Biomol Tech Jbt 2010;21:120–5.Search in Google Scholar
29. Lee, SH, Lee, NH, Jin, SM, Rho, YS, Jo, SJ. Loss of heterozygosity of tumor suppressor genes (p16, Rb, E-cadherin, p53) in hypopharynx squamous cell carcinoma. Otolaryngol Head Neck Surg 2011;145:64–70. https://doi.org/10.1177/0194599811401327.Search in Google Scholar PubMed
30. Schwarzenbach, H, Eichelser, C, Kropidlowski, J, Janni, W, Rack, B, Pantel, K. Loss of heterozygosity at tumor suppressor genes detectable on fractionated circulating cell-free tumor DNA as indicator of breast cancer progression. Clin Cancer Res 2012;18:5719–30. https://doi.org/10.1158/1078-0432.ccr-12-0142.Search in Google Scholar
31. Fiore, PPD, Pierce, JH, Kraus, MH, Segatto, O, King, CR, Aaronson, SA. erbB-2 is a potent oncogene when overexpressed in NIH/3T3 cells. Science 1987;237:178–82. https://doi.org/10.1126/science.2885917.Search in Google Scholar PubMed
32. Khaleghian, M, Jahanzad, I, Shakoori, A, Razavi, AE, Azimi, C. Association between amplification and expression of C-myc gene and clinicopathological characteristics of stomach cancer. Iran Red Crescent Med J 2016;18:e21221. https://doi.org/10.5812/ircmj.21221.Search in Google Scholar PubMed PubMed Central
33. Drost, J, Van Jaarsveld, RH, Ponsioen, B, Zimberlin, C, Van Boxtel, R, Buijs, A, et al.. Sequential cancer mutations in cultured human intestinal stem cells. Nature 2015;521:43–7. https://doi.org/10.1038/nature14415.Search in Google Scholar PubMed
34. Ried, T, Meijer, GA, Harrison, DJ, Grech, G, Camps, J. The landscape of genomic copy number alterations in colorectal cancer and their consequences on gene expression levels and disease outcome. Mol Aspect Med 2019;69:48–61. https://doi.org/10.1016/j.mam.2019.07.007.Search in Google Scholar
35. Friend, SH, Bernards, R, Rogelj, S, Weinberg, RA, Rapaport, JM, Albert, DM, et al.. A human DNA segment with properties of the gene that predisposes to retinoblastoma and osteosarcoma. Nature 1986;323:643–6. https://doi.org/10.1038/323643a0.Search in Google Scholar
36. Bièche, I, Lidereau, R. Loss of heterozygosity at 13q14 correlates with RB1 gene underexpression in human breast cancer. Mol Carcinog 2000;29:151–8. https://doi.org/10.1002/1098-2744(200011)29:3<151::aid-mc4>3.0.co;2-6.10.1002/1098-2744(200011)29:3<151::AID-MC4>3.0.CO;2-6Search in Google Scholar
37. Kamb, A, Gruis, NA, Weaver-Feldhaus, J, Liu, Q, Harshman, K, Tavtigian, SV, et al.. A cell cycle regulator potentially involved in genesis of many tumor types. Science 1994;264:436–40. https://doi.org/10.1126/science.8153634.Search in Google Scholar
38. Awaya, H, Takeshima, Y, Amatya, VJ, Furonaka, O, Tagawa, K, Kohno, N, et al.. Inactivation of the p16 gene by hypermethylation and loss of heterozygosity in adenocarcinoma of the lung. Pathol Int 2004;54:486–9. https://doi.org/10.1111/j.1440-1827.2004.01655.x.Search in Google Scholar
39. Sauter, G, Moch, H, Gasser, TC, Mihatsch, MJ, Waldman, FM. Heterogeneity of chromosome 17 and erbB-2 gene copy number in primary and metastatic bladder cancer. Cytometry 2010;21:40–6. https://doi.org/10.1002/cyto.990210109.Search in Google Scholar
40. Lieberfarb, ME, Lin, M, Lechpammer, M, Li, C, Tanenbaum, DM, Febbo, PG, et al.. Genome-wide loss of heterozygosity analysis from laser capture microdissected prostate cancer using single nucleotide polymorphic allele (SNP) arrays and a novel bioinformatics platform dChipSNP. Cancer Res 2003;63:4781–5.Search in Google Scholar
41. Hoque, MO, Lee, CR, Cairns, P, Schoenberg, M, Sidransky, D. Genome-wide genetic characterization of bladder cancer: a comparison of high-density single-nucleotide polymorphism arrays and PCR-based microsatellite analysis. Cancer Res 2003;63:2216–22.Search in Google Scholar
42. Zhou, X, Li, C, Mok, SC, Chen, Z, Wong, DTW. Whole genome loss of heterozygosity profiling on oral squamous cell carcinoma by high-density single nucleotide polymorphic allele (SNP) array. Cancer Genet Cytogenet 2004;151:82–4. https://doi.org/10.1016/j.cancergencyto.2003.11.010.Search in Google Scholar
43. Jänne, PA, Li, C, Zhao, X, Girard, L, Chen, TH, Minna, J, et al.. High-resolution single-nucleotide polymorphism array and clustering analysis of loss of heterozygosity in human lung cancer cell lines. Oncogene 2004;23:2716–26. https://doi.org/10.1038/sj.onc.1207329.Search in Google Scholar
44. Wong, KK, Tsang, YTM, Shen, J, Cheng, RS, Chang, YM, Man, TK, et al.. Allelic imbalance analysis by high-density single-nucleotide polymorphic allele (SNP) array with whole genome amplified DNA. Nucleic Acids Res 2004;32:e69. https://doi.org/10.1093/nar/gnh072.Search in Google Scholar
45. Savol, AJ, Wang, PI, Jeon, Y, Colognori, D, Yildirim, E, Pinter, SF, et al.. Genome-wide identification of autosomal genes with allelic imbalance of chromatin state. PLoS One 2017;12:e0182568. https://doi.org/10.1371/journal.pone.0182568.Search in Google Scholar
46. Shen, R, Seshan, VE. FACETS: allele-specific copy number and clonal heterogeneity analysis tool for high-throughput DNA sequencing. Nucleic Acids Res 2016;44:e131. https://doi.org/10.1093/nar/gkw520.Search in Google Scholar PubMed PubMed Central
47. Koumbaris, G, Achilleos, A, Nicolaou, M, Loizides, C, Tsangaras, K, Kypri, E, et al.. Targeted capture enrichment followed by NGS: development and validation of a single comprehensive NIPT for chromosomal aneuploidies, microdeletion syndromes and monogenic diseases. Mol Cytogenet 2019;12:48. https://doi.org/10.1186/s13039-019-0459-8.Search in Google Scholar PubMed PubMed Central
48. Tang, K, Fu, DJ, Julien, D, Braun, A, Cantor, CR, Köster, H. Chip-based genotyping by mass spectrometry. Proc Natl Acad Sci U S A 1999;96:10016–20. https://doi.org/10.1073/pnas.96.18.10016.Search in Google Scholar PubMed PubMed Central
49. Zhu, L, Yin, L, Xue, J, Wang, Z, Nie, Z. Mass spectrometry genotyping of human papillomavirus based on nano materials high-efficiency selective enrichment. ACS Appl Mater Interfaces 2018;10:41178–84. https://doi.org/10.1021/acsami.8b16694.Search in Google Scholar PubMed
Supplementary Material
The online version of this article offers supplementary material (https://doi.org/10.1515/cclm-2022-0511).
© 2022 Walter de Gruyter GmbH, Berlin/Boston