Skip to main content

Genetic Instability Markers in Cancer

  • Protocol
  • First Online:
Book cover Biomarkers for Immunotherapy of Cancer

Abstract

High frequency of mutations seems to determine a higher occurrence of neoepitope formation and, thus, tumor immunogenicity. A somatic hypermutated status could thus act as a predictive biomarker of responsiveness to immunotherapy with recent immune checkpoint inhibitors. Among several factors involved in determining the hypermutated status, such as inactivating mutations in the DNA polymerases as well as exposure to external (cigarette smoke, UV radiation, chemicals) and endogenous (reactive oxygen species) mutagens, a defective DNA mismatch repair system may give rise to genetic instability and, particularly, to microsatellite instability (MSI). The occurrence of MSI has been associated with increased load of mutations and expression of abundant peptides that serve as neoantigens to elicit an immune response within a context of a favorable tumor microenvironment. Here we describe methodological strategies to investigate for the presence of the MSI phenotype in cancer samples, through a combination of molecular approaches performed on paraffin-embedded tissues.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 249.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Cancer Genome Atlas Network (2012) Comprehensive molecular characterization of human colon and rectal cancer. Nature 487:330–337

    Article  Google Scholar 

  2. Guinney J, Dienstmann R, Wang X et al (2015) The consensus molecular subtypes of colorectal cancer. Nat Med 21:1350–1356

    Article  CAS  Google Scholar 

  3. Toth G, Gaspari Z, Jurka J (2000) Microsatellites in different eukaryotic genomes: survey and analysis. Genome Res 10:967–981

    Article  CAS  Google Scholar 

  4. Schlotterer C (2000) Evolutionary dynamics of microsatellite DNA. Chromosoma 109:365–371

    Article  CAS  Google Scholar 

  5. van Eyk CL, Richards RI (2012) Dynamic mutations: where are they now? Adv Exp Med Biol 769:55–77

    PubMed  Google Scholar 

  6. Schmidt MH, Pearson CE (2016) Disease-associated repeat instability and mismatch repair. DNA Repair (Amst) 38:117–126

    Article  CAS  Google Scholar 

  7. Dienstmann R, Vermeulen L, Guinney J et al (2017) Consensus molecular subtypes and the evolution of precision medicine in colorectal cancer. Nat Rev Cancer 17:79–92

    Article  CAS  Google Scholar 

  8. Lengauer C, Kinzier KW, Volgestein B (1998) Genetic instabilities in human cancers. Nature 396:643–649

    Article  CAS  Google Scholar 

  9. Muresu R, Sini MC, Cossu A et al (2002) Chromosomal abnormalities and microsatellite instability in sporadic endometrial cancer. Eur J Cancer 38:1802–1809

    Article  CAS  Google Scholar 

  10. Jasin M (2000) Chromosome breaks and genomic instability. Cancer Invest 18:78–86

    Article  CAS  Google Scholar 

  11. Sakofsky CJ, Malkova A (2017) Break induced replication in eukaryotes: mechanisms, functions, and consequences. Crit Rev Biochem Mol Biol 52:395–413

    Article  CAS  Google Scholar 

  12. Diaz-Padilla I, Romero N, Amir E et al (2013) Mismatch repair status and clinical outcome in endometrial cancer: a systematic review and meta-analysis. Crit Rev Oncol Hematol 88:154–167

    Article  Google Scholar 

  13. Richman S (2015) Deficient mismatch repair: read all about it. Int J Oncol 47:1189–1202

    Article  CAS  Google Scholar 

  14. Bardi G, Pandis N, Schousboe K et al (1995) Near-diploid karyotypes with recurrent chromosome abnormalities characterize early-stage endometrial cancer. Cancer Genet Cytogenet 80:110–114

    Article  CAS  Google Scholar 

  15. Giam M, Rancati G (2015) Aneuploidy and chromosomal instability in cancer: a jackpot to chaos. Cell Div 10:3

    Article  Google Scholar 

  16. Palmieri G, Colombino M, Cossu A et al (2017) Genetic instability and increased mutational load: which diagnostic tool best direct patients with cancer to immunotherapy? J Transl Med 15:17

    Article  Google Scholar 

  17. Chalmers ZR, Connelly CF, Fabrizio D et al (2017) Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden. Genome Med 9:34

    Article  Google Scholar 

  18. Jamieson NB, Maker AV (2017) Gene-expression profiling to predict responsiveness to immunotherapy. Cancer Gene Ther 24:134–140

    Article  CAS  Google Scholar 

  19. Le DT, Uram JN, Wang H et al (2015) PD-1 blockade in tumors with mismatch-repair deficiency. N Engl J Med 372:2509–2520

    Article  CAS  Google Scholar 

  20. Dudley JC, Lin MT, Le DT et al (2016) Microsatellite instability as a biomarker for PD-1 blockade. Clin Cancer Res 22:813–820

    Article  CAS  Google Scholar 

  21. Llosa NJ, Cruise M, Tam A et al (2015) The vigorous immune micro- environment of microsatellite instable colon cancer is balanced by multiple counter-inhibitory checkpoints. Cancer Discov 5:43–51

    Article  CAS  Google Scholar 

  22. Fridman WH, Zitvogel L, Sautès-Fridman C et al (2017) The immune contexture in cancer prognosis and treatment. Nat Rev Clin Oncol 14:717–734

    Article  CAS  Google Scholar 

  23. Shia J (2008) Immunohistochemistry versus microsatellite instability testing for screening colorectal cancer patients at risk for hereditary nonpolyposis colorectal cancer syndrome. Part I. The utility of immunohistochemistry. J Mol Diagn 10:293–300

    Article  Google Scholar 

  24. Chang L, Chang M, Chang HM et al (2018) Microsatellite instability: a predictive biomarker for cancer immunotherapy. Appl Immunohistochem Mol Morphol 26:e15–e21

    CAS  PubMed  Google Scholar 

  25. Colombino M, Cossu A, Manca A et al (2002) Prevalence and prognostic role of microsatellite instability in patients with rectal carcinoma. Ann Oncol 13:1447–1453

    Article  CAS  Google Scholar 

  26. Palmieri G, Ascierto PA, Cossu A et al (2003) Assessment of genetic instability in melanocytic skin lesions through microsatellite analysis of benign nevi, dysplastic nevi, and primary melanomas along with their metastases. Melanoma Res 13:167–170

    Article  CAS  Google Scholar 

  27. Colombino M, Cossu A, Arba A et al (2003) Microsatellite instability and mutation analysis among Southern Italian patients with colorectal carcinoma: detection of different alterations accounting for MLH1 and MSH2 inactivation in familial cases. Ann Oncol 14:1530–1536

    Article  CAS  Google Scholar 

  28. Paliogiannis P, Attene F, Cossu A et al (2015) Impact of tissue type and content of neoplastic cells of samples on the quality of epidermal growth factor receptor mutation analysis among patients with lung adenocarcinoma. Mol Med Rep 12:187–191

    Article  CAS  Google Scholar 

  29. Williams C, Ponten F, Moberg C et al (1999) A high frequency of sequence alterations is due to formalin fixation of archival specimens. Am J Pathol 155:1467–1471

    Article  CAS  Google Scholar 

  30. Srinivasan M, Sedmak D, Jewell S (2002) Effect of fixatives and tissue processing on the content and integrity of nucleic acids. Am J Pathol 161:1961–1971

    Article  CAS  Google Scholar 

  31. Apple S, Pucci R, Lowe AC et al (2011) The effect of delay in fixation, different fixatives, and duration of fixation in estrogen and progesterone receptor results in breast carcinoma. Am J Clin Pathol 135:592–598

    Article  Google Scholar 

  32. Palomaki GE, McClain MR, Melillo S (2009) EGAPP supplementary evidence review: DNA testing strategies aimed at reducing morbidity and mortality from lynch syndrome. Genet Med 11:42–65

    Article  Google Scholar 

  33. Pinol V, Castells A, Andreu M et al (2005) Accuracy of revised Bethesda guidelines, microsatellite instability, and immunohistochemistry for the identification of patients with hereditary nonpolyposis colorectal cancer. JAMA 293:1986–1994

    Article  CAS  Google Scholar 

  34. Förster I, Brockmann M, Schildgen O et al (2018) Microsatellite instability testing in colorectal cancer using the QiaXcel advanced platform. BMC Cancer 18:484

    Article  Google Scholar 

  35. Zhao H, Thienpont B, Yesilyurt BT et al (2014) Mismatch repair deficiency endows tumors with a unique mutation signature and sensitivity to DNA double-strand breaks. Elife 3:e02725

    Article  Google Scholar 

  36. Hampel H, Frankel WL, Martin E et al (2008) Feasibility of screening for Lynch syndrome among patients with colorectal cancer. J Clin Oncol 26:5783–5788

    Article  Google Scholar 

Download references

Acknowledgments

This work was partially supported by Associazione Italiana per la Ricerca sul Cancro (AIRC) “Programma di ricerca 5 per Mille 2018—Id.21073.”

Conflict of Interest: The authors have no conflict of interest to declare.

Author Contributions: GiP: Conception and design, acquisition of protocol data, drafting the manuscript. MiC, AM, GrP, MCS: Analysis and interpretation of molecular protocols, revising the manuscript. VD, AC: Analysis and interpretation of pathology aspects, revising the manuscript. MaC: Conception and design, contributed unpublished essential data or protocols, revising the manuscript.

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Science+Business Media, LLC, part of Springer Nature

About this protocol

Check for updates. Verify currency and authenticity via CrossMark

Cite this protocol

Palmieri, G. et al. (2020). Genetic Instability Markers in Cancer. In: Thurin, M., Cesano, A., Marincola, F. (eds) Biomarkers for Immunotherapy of Cancer. Methods in Molecular Biology, vol 2055. Humana, New York, NY. https://doi.org/10.1007/978-1-4939-9773-2_6

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-9773-2_6

  • Published:

  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-4939-9772-5

  • Online ISBN: 978-1-4939-9773-2

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics