This site is intended for
U.S.
Healthcare Professionals only.

For Patients
 

Tumor Antigens

Tumor antigens are recognized as nonself or foreign by the host immune system.1 They can initiate the adaptive immune response by priming the immune system.1,2 Several Immuno-Oncology (I-O) biomarkers related to tumor antigens are currently under investigation:

Mutated DNA pathway expressed in a dying tumor cell diagram
 

Neoantigens

Neoantigens are newly formed antigens that arise from mutated tumor proteins. They can elicit an immune response and may help predict sensitivity to I-O therapy.

Click below to learn more about neoantigens as potential I-O biomarkers.
  • Neoantigens are newly formed antigens that have not been previously recognized by the immune system1,2
  • Neoantigens can arise from altered peptides formed as a result of tumor mutations or viral proteins1,2
  • High tumor mutational burden (TMB), microsatellite instability-high (MSI-H), mismatch repair deficient (dMMR) status, or MGMT methylation may be associated with increased neoantigen production3-7
Neoantigens and Total Mutations
  • Neoantigens can be recognized by the immune system as nonself and, as such, can elicit an immune response2,3
  • Neoantigen-specific T cells have been identified in several human cancers8
  • Tumors with a high neoantigen burden may be more sensitive to immunotherapy, indicating that neoantigens may be a potential I-O biomarker9
   

Tumor Mutational Burden (TMB)

TMB is the amount of acquired mutations in the tumor genome, and may be a surrogate biomarker for neoantigens. It can vary across tumor types and may predict the likelihood of an immune response, and can be measured using next-generation sequencing.

Click below to learn more about TMB as a predictive I-O biomarker.
   

MSI-H/dMMR

Microsatellite instability (MSI), caused by deficiencies in mismatch repair (dMMR), can be an indicator of genomic instability. MSI-H/dMMR tumors correlate with increases in neonantigen production.

Click to learn more about research into the role of MSI-H/dMMR as I-O biomarkers.

Get I-O Resources

Order or download
educational tools for your
patients and practice

See all resources

Clinical Trials

Learn more about our
current clinical trials

Learn more

References–Tumor antigens

1. Schumacher TN, Schreiber RD. Neoantigens in cancer immunotherapy. Science. 2015;348(6230):69-74. 2. Eggermont LJ, Paulis LE, Tel J, Figdor CG. Towards efficient cancer immunotherapy: advances in developing artificial antigen-presenting cells. Trends Biotechnol. 2014; 32(9):456-465.

References–Neoantigens

1. Schumacher TN, Schreiber RD. Neoantigens in cancer immunotherapy. Science. 2015;348(6230):69-74. 2. Lu Y-C, Robbins PF. Cancer immunotherapy targeting neoantigens. Semin Immunol. 2016;28(1):22-27. 3. Hause RJ, Pritchard CC, Shendure J, Salipante SJ. Classification and characterization of microsatellite instability across 18 cancer types. Nat Med. 2016. doi:10.1038/nm.4191. 4. Bogaert J, Prenen H. Molecular genetics of colorectal cancer. Ann Gastroenterol. 2014;27(1):9-14. 5. Chalmers ZR, Connelly CF, Fabrizio D, et al. Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden. Genome Med. 2017;9(1):34. doi:10.1186//s13073-017-0424-2. 6. Kim JM, Chen DS. Immune escape to PD-L1/PD-1 blockade: seven steps to success (or failure). Ann Oncol. 2016;27(8):1492-1504. 7. Germano G, Lamba S, Rospo G, Barault L, Magrì A, Maione F, et al. Inactivation of DNA repair triggers neoantigen generation and impairs tumour growth. Nature. 2017;552:116-20. 8. Bobisse S, Foukas PG, Coukos G, Harari A. Neoantigen-based cancer immunotherapy. Ann Transl Med. 2016;4(14):262. 9. Efremova M, Finotello F, Rieder D, Trajanoski Z. Neoantigens generated by individual mutations and their role in cancer immunity and immunotherapy. Front Immunol. 2017;8:1679. doi:10.3389/fimmu.2017.01679. 10. Chabanon RM, Pedrero M, Lefebvre C, Marabelle A, Soria JC, Postel-Vinay S. Mutational landscape and sensitivity to immune checkpoint blockers. Clin Cancer Res. 2016;22(17):4309-4321. 11. Yuan J, Hegde PS, Clynes R, et al. Novel technologies and emerging biomarkers for personalized cancer immunotherapy. J Immunother Cancer. 2016;4:3. doi:10.1186/s40425-016-0107-3.

References–Tumor mutational burden

1. Chalmers ZR, Connelly CF, Fabrizio D, et al. Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden. Genome Med. 2017;9(1):34. doi:10.1186/s13073-017-0424-2. 2. Stratton MR, Campbell PJ, Futreal PA. The cancer genome. Nature. 2009;458(7239):719-724. 3. Rooney MS, Shukla SA, Wu CJ, Getz G, Hacohen N. Molecular and genetic properties of tumors associated with local immune cytolytic activity. Cell. 2015;160(1-2):48-61. 4. Chabanon RM, Pedrero M, Lefebvre C, Marabelle A, Soria JC, Postel-Vinay S. Mutational landscape and sensitivity to immune checkpoint blockers. Clin Cancer Res. 2016;22(17):4309-4321. 5. Kim JM, Chen DS. Immune escape to PD-L1/PD-1 blockade: seven steps to success (or failure). Ann Oncol. 2016;27(8):1492-1504. 6. Giannakis M, Mu XJ, Shukla SA, et al. Genomic correlates of immune-cell infiltrates in colorectal carcinoma. Cell Rep. 2016;15(4):857-865. 7. Brown SD, Warren RL, Gibb EA, et al. Neo-antigens predicted by tumor genome meta-analysis correlate with increased patient survival. Genome Res. 2014;24(5):743-750. 8. Alexandrov LB, Nik-Zainal S, Wedge DC, et al. Signatures of mutational processes in human cancer. Nature. 2013;500:415-421. 9. Rizvi NA, Hellmann MD, Snyder A, et al. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer. Science. 2015;348(6230):124-128. 10. Johnson BE, Mazor T, Hong C, Barnes M, et al. Mutational analysis reveals the origin and therapy-driven evolution of recurrent glioma. Science. 2014;343(6167):189-93. 11. Wang J, Cazzato E, Ladewig E, et al. Clonal evolution of glioblastoma under therapy. Nat Genet. 2016;48(7):768. 12. Yuan J, Hegde PS, Clynes R, et al. Novel technologies and emerging biomarkers for personalized cancer immunotherapy. J Immunother Cancer. 2016;4:3. doi:10.1186/s40425-016-0107-3. 13. Frampton GM, Fichtenholtz A, Otto GA, et al. Development and validation of a clinical cancer genomic profiling test based on massively parallel DNA sequencing. Nat Biotechnol. 2013;31(11):1023-1031. 14. Meyerson M, Gabriel S, Getz G. Advances in understanding cancer genomes through second-generation sequencing. Nat Rev Genet. 2010;11(10):685-696. 15. Ng SB, Turner EH, Robertson PD, et al. Targeted capture and massively parallel sequencing of twelve human exomes. Nature. 2009;461(7261):272-276. 16. Behjati S, Tarpey PS. What is next generation sequencing? Arch Dis Child Educ Pract Ed. 2013;98(6):236-238. 17. Drilon A, Wang L, Arcila ME, et al. Broad, hybrid capture-based next-generation sequencing identifies actionable genomic alterations in lung adenocarcinomas otherwise negative for such alterations by other genomic testing approaches. Clin Cancer Res. 2015;21(16):3631-3639. 18. Garofalo A, Sholl L, Reardon B, et al. The impact of tumor profiling approaches and genomic data strategies for cancer precision medicine. Genome Med. 2016;8:79. doi:10.1186/s13073-016-0333-9. 19. Roszik J, Haydu LE, Hess KR, et al. Novel algorithmic approach predicts tumor mutation load and correlates with immunotherapy clinical outcomes using a defined gene mutation set. BMC Med. 2016;14(1):168. doi:10.1186/s12916-016-0705-4.

References–MSI-H/dMMR

1. National Cancer Institute. Microsatellite instability. www.cancer.gov/publications/dictionaries/cancer-terms?cdrid=285933. Accessed January 7, 2019. 2. Vilar E, Gruber SB. Microsatellite instability in colorectal cancer—the stable evidence. Nat Rev Clin Oncol. 2010;7(3):153-162. 3. Hause RJ, Pritchard CC, Shendure J, Salipante SJ. Classification and characterization of microsatellite instability across 18 cancer types. Nat Med. 2016;22(11):1-9. 4. Bogaert J, Prenen H. Molecular genetics of colorectal cancer. Ann Gastroenterol. 2014;27(1):9-14. 5. Giannakis M, Mu XJ, Shukla SA, et al. Genomic correlates of immune-cell infiltrates in colorectal carcinoma. Cell Rep. 2016;15(4):857-865. 6. McGranahan N, Furness AJ, Rosenthal R, et al. Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade. Science. 2016;351(6280):1463-1469. 7. Chalmers ZR, Connelly CF, Fabrizio D, et al. Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden. Genome Med. 2017;9(1):34. doi:10.1186/s13073-017-0424-2. 8. Le DT, Durham JN, Smith KN, et al. Mismatch repair deficiency predicts response of solid tumors to PD-1 blockade. Science. 2017;357(6349):409-413. 9. Lee V, Murphy A, Le DT, Diaz LA. Mismatch repair deficiency and response to immune checkpoint blockade. Oncologist. 2016;21(10):1200-1211. 10. Popat S, Hubner R, Houlston RS. Systematic review of microsatellite instability and colorectal cancer prognosis. J Clin Oncol. 2005;23(3):609-618. 11. Cortes-Ciriano I, Lee S, Park WY, Kim TM, Park PJ. A molecular portrait of microsatellite instability across multiple cancers. Nat Commun. 2017;8:15180. 12. Goldstein J, Tran B, Ensor J, et al. Multicenter retrospective analysis of metastatic colorectal cancer (CRC) with high-level microsatellite instability (MSI-H). Ann Oncol. 2014;25(5):1032-1038. 13. Koopman M, Kortman GA, Mekenkamp L, et al. Deficient mismatch repair system in patients with sporadic advanced colorectal cancer. Br J Cancer. 2009;100(2):266-273. 14. Kawakami H, Zaanan A, Sinicrope FA. Implications of mismatch repair-deficient status on management of early stage colorectal cancer. J Gastrointest Oncol. 2015;6(6):676-684. 15. Richman S. Deficient mismatch repair: read all about it. Int J Oncol. 2015;47(4):1189-1202.