Comprehensive Immune Profiling via 5 Test Modes

RNA-Seq

to semi-quantitatively measure transcript levels of 43 genes related to T-cell receptor signaling (TCRS) and other components of the immune cycle, as well as 11 genes associated with tumor infiltrating lymphocytes (TILs)

  • Next Generation Sequencing (NGS) Assay
  • Amplicon-based targeted NGS for digital gene expression detection
  • 395 genes representing immune-related gene functions.
  • 54 of these 395 genes that can be divided into multiple functional Immune Phenotypes
    • T-cell Receptor Signaling (TCRS)
    • Tumor Infiltrating Lymphocytes (TILs)
  • 10 genes are used as control genes
  • Remaining genes in the assay have not been fully validated and are not included in IRC results

MSI-PCR

to assess microsatellite instability (MSI)

  • 5 markers
    • 2 mononucleotide repeat markers (BAT-25, BAT-26)
    • 3 dinucleotide repeat markers (D2S123, D5S346 and D17S250)
  • Reported as
    • MSI-high
    • MSI-low
    • MSS (microsatellite stable)
  • MSI typically used as a prognostic marker of survival in the setting of Lynch syndrome/hereditary nonpolyposis colorectal cancer (HNPCC)
  • Marker of response to CPIs in colorectal cancer (Le, PMID:26028255 – 2016)

IHC

Immunohistochemistry (IHC) to measure PD-L1 protein expression and patterns of lymphocyte infiltration. 

  • Uses automated stainer platforms and commercially available antibodies
    • PD-L1 (22C3, 28-8, SP142, all FDA-approved)
    • CD3 (Laboratory Developed Test)
    • CD8 (Laboratory Developed Test)
  • PD-L1 scoring follows FDA guidelines for:
    • Non-small cell lung cancer
    • Stomach and gastroesophageal junction adenocarcinoma
    • Melanoma
    • Head and neck squamous cell carcinoma
    • Urothelial carcinoma
  • CD3 and CD8 scoring pattern:
    • Infiltrating pattern
      • TILs within groups of neoplastic cells
    • Non-infiltrating
      • TILs present but no consistent pattern of infiltrating groups of neoplastic cells
      • includes cases with an abundance of TILs at the advancing edge of the tumor, but without infiltration of the neoplastic cells
    • Minimal to Absent
      • minimal to no TILs present within any part of the tumor

FISH

to detect copy number gain of PD-L1 and PD-L2

  • Measures copy number of PD-L1 (CD274) & PD-L2 (PDCD1LG2):
    • PD-1 ligands that when amplified are associated with PD-L1 expression
    • Located 40kb apart on 9p24.1
    • Detected using a pool of fluorescently labeled BAC clones that map to the gene region
  • Reported using ASCO–CAP HER2 Test Guideline Recommendations for determining copy number:
    • Amplified
      • Ratio of PD-L1/2 to CEP9 is equal to or greater than 2.0 for any copy number value of PD-L1/2
      • Ratio of PD-L1/2 to CEP9 is less than 2.0 and the copy number value of PD-L1/2 is equal to or greater than 6.0
    • Equivocal
      • Ratio of PD-L1/2 to CEP9 is less than 2.0 and copy number value of PD-L1/2 is equal to or greater than 4.0 and less than 6.0
    • Not Amplified
      • Ratio of PD-L1/2 to CEP9 is less than 2.0 and the copy number value of PD-L1/2 is less than 4.0.

DNA-Seq

to estimate mutational burden (MuB)

  • 1.16 Mb AmpliSeq capture of 6,602 exons
  • 409 oncogenes
  • Full exon coverage
  • Reported as mutational burden (MuB), mutations per Mb exonic sequence
  • Specific mutations are not reported

3 Legs of the Stool

Mutational Burden (MuB)

  • MuB is reported as number of mutations per megabase (Mb) of exonic DNA
  • MuB was calibrated against 4 clinically relevant peer-reviewed publications reporting a correlation of high mutational burden with response to checkpoint inhibitors:
    • Melanoma
      • Snyder, PMID:25409260 – 2016
      • Van Allen, PMID:26359337 – 2015
    • NSCLC
      • Rizvi, PMID:25765070 – 2016
    • Bladder (urothelial) cancer
      • Rosenberg, PMID:26952546 – 2016
  • Using an equivalent whole exome and these 4 references as a calibrator the cut-off values for MuB as measured by number of mutations per Mb DNA was established using an internal reference population of 167 subjects.
  • MuB is classified as “very high”, “high”, “intermediate”, “low”, and “very low”.

T Cell Receptor Signaling (TCRS)

  • May be expressed on:
    • Immune infiltrating cells
    • Neoplastic cells
    • Other cells of the tumor microenvironment
  • Further subdivided by multiple immune phenotypes.
  • Directly involved in checkpoint blockade
  • Functions that relate to TCRS

Tumor Infiltrating Lymphocytes (TILs)

  • 11 genes to classify subsets of infiltrating immune cells
    • Galon et. al. (Galon, PMID:24122236 – 2014)
    • Emphasis on CD3 and CD8
      • Associated IHC patterns of expression
  • TILs as a predictive immune biomarker/prognostic marker of survival/associated response to CPIs:
    • Positive
      • CD3+CD8+ cytotoxic lymphocytes
    • Negative
      • FOXP3+ Tregs

Publications 

  1. Ansell SM, Lesokhin AM, Borrello I, Halwani A, Scott EC, Gutierrez M, et al. PD-1 Blockade with Nivolumab in Relapsed or Refractory Hodgkin’s Lymphoma. N Engl J Med. 2015;372:311–9. doi:10.1056/NEJMoa1411087.  http://www.nejm.org/doi/full/10.1056/NEJMoa1411087
  2. Ascierto PA, Capone M, Urba WJ, Bifulco CB, Botti G, Lugli A, et al. The additional facet of immunoscore: immunoprofiling as a possible predictive tool for cancer treatment. J Transl Med. 2013;11:54. doi:10.1186/1479-5876-11-54.  https://translational-medicine.biomedcentral.com/articles/10.1186/1479-5876-11-54
  3. Baine MK, Turcu G, Zito CR, Adeniran AJ, Camp RL, Chen L, et al. Characterization of tumor infiltrating lymphocytes in paired primary and metastatic renal cell carcinoma specimens. Oncotarget. 2015;6:24990–5002.doi:10.18632/oncotarget.4572.  http://www.impactjournals.com/oncotarget/index.php?journal=oncotarget&page=article&op=view&path%5B%5D=4572
  4. Besser MJ, Shapira-Frommer R, Treves AJ, Zippel D, Itzhaki O, Hershkovitz L, et al. Clinical responses in a phase II study using adoptive transfer of short-term cultured tumor infiltration lymphocytes in metastatic melanoma patients. Clin Cancer Res. 2010;16:2646–55. doi:10.1158/1078-0432.CCR-10-0041.a.  http://clincancerres.aacrjournals.org/content/16/9/2646.long
  5. Brahmer J, Reckamp KL, Baas P, Crinò L, Eberhardt WEE, Poddubskaya E, et al. Nivolumab versus Docetaxel in Advanced Squamous-Cell Non–Small-Cell Lung Cancer. N Engl J Med. 2015;373:123–35. doi:10.1056/NEJMoa1504627.a.  http://www.nejm.org/doi/full/10.1056/NEJMoa1504627#t=article
  6. Budczies J, Bockmayr M, Denkert C, Klauschen F, Gröschel S, Darb-Esfahani S, et al. Pan-cancer analysis of copy number changes in programmed death-ligand 1 (PD-L1, CD274) – associations with gene expression, mutational load, and survival. Genes, Chromosom Cancer. 2016;55:626–39. doi:10.1002/gcc.22365. http://onlinelibrary.wiley.com/doi/10.1002/gcc.22365/abstract;jsessionid=9EB1D60F4EE5B578236FF56C6FF57C1E.f04t01
  7. Chen DS, Mellman I. Elements of cancer immunity and the cancer–immune set point. Nature. 2017;541:321–30. doi:10.1038/nature21349.  https://www.nature.com/nature/journal/v541/n7637/abs/nature21349.html
  8. Daud AI, Wolchok JD, Robert C, Hwu W-J, Weber JS, Ribas A, et al. Programmed Death-Ligand 1 Expression and Response to the Anti–Programmed Death 1 Antibody Pembrolizumab in Melanoma. J Clin Oncol. 2016;34:4102–9. doi:10.1200/JCO.2016.67.2477.  http://ascopubs.org/doi/abs/10.1200/JCO.2016.67.2477?url_ver=Z39.88-2003&rfr_id=ori:rid:crossref.org&rfr_dat=cr_pub%3dpubmed
  9. Diggs LP, Hsueh EC. Utility of PD-L1 immunohistochemistry assays for predicting PD-1/PD-L1 inhibitor response. Biomark Res. 2017;5:12. doi:10.1186/s40364-017-0093-8.a.  https://biomarkerres.biomedcentral.com/articles/10.1186/s40364-017-0093-8
  10. Galon J, Mlecnik B, Bindea G, Angell HK, Berger A, Lagorce C, et al. Towards the introduction of the “Immunoscore” in the classification of malignant tumours. J Pathol. 2014;232:199–209. doi:10.1002/path.4287.a.  http://onlinelibrary.wiley.com/doi/10.1002/path.4287/abstract
  11. Garber K. Oncologists await historic first: a pan-tumor predictive marker, for immunotherapy. Nat Biotechnol. 2017;35:297–8. doi:10.1038/nbt0417-297a.a.http://www.nature.com/nbt/journal/v35/n4/full/nbt0417-297a.html?WT.ec_id=NBT-201704&spMailingID=53829868&spUserID=NjUwMzkwMjAzNjgS1&spJobID=1141825855&spReportId=MTE0MTgyNTg1NQS2
  12. Gros A, Robbins PF, Yao X, Li YF, Turcotte S, Tran E, et al. PD-1 identifies the patient-specific CD8+ tumor-reactive repertoire infiltrating human tumors. J Clin Invest. 2014;124:2246–59. doi:10.1172/JCI73639.a.https://www.jci.org/articles/view/73639
  13. Herbst RS, Baas P, Kim D-W, Felip E, Pérez-Gracia JL, Han J-Y, et al. Pembrolizumab versus docetaxel for previously treated, PD-L1-positive, advanced non-small-cell lung cancer (KEYNOTE-010): a randomised controlled trial. Lancet (London, England). 2016;387:1540–50. doi:10.1016/S0140-6736(15)01281-7.  http://www.thelancet.com/journals/lancet/article/PIIS0140-6736(15)01281-7/supplemental
  14. Inoue Y, Osman M, Suda T, Sugimura H. PD-L1 copy number gains: a predictive biomarker for PD-1/PD-L1 blockade therapy? Transl Cancer Res. 2016;5:S199–202. doi:10.21037/tcr.2016.07.47.  http://tcr.amegroups.com/article/view/8810/html
  15. Inoue Y, Yoshimura K, Mori K, Kurabe N, Kahyo T, Mori H, et al. Clinical significance of PD-L1 and PD-L2 copy number gains in non-small-cell lung cancer. Oncotarget. 2016;7:32113–28. doi:10.18632/oncotarget.8528.  http://www.impactjournals.com/oncotarget/index.php?journal=oncotarget&page=article&op=view&path%5B%5D=8528
  16. Le DT, Uram JN, Wang H, Bartlett BR, Kemberling H, Eyring AD, et al. PD-1 Blockade in Tumors with Mismatch-Repair Deficiency. N Engl J Med. 2015;372:2509–20. doi:10.1056/NEJMoa1500596.  http://www.nejm.org/doi/full/10.1056/NEJMoa1500596
  17. Motzer RJ, Escudier B, McDermott DF, George S, Hammers HJ, Srinivas S, et al. Nivolumab versus Everolimus in Advanced Renal-Cell Carcinoma. N Engl J Med. 2015;373:1803–13. oi:10.1056/NEJMoa1510665.  http://www.nejm.org/doi/full/10.1056/NEJMoa1510665#t=article
  18. Müller P, Rothschild SI, Arnold W, Hirschmann P, Horvath L, Bubendorf L, et al. Metastatic spread in patients with non-small cell lung cancer is associated with a reduced density of tumor-infiltrating T cells. Cancer Immunol Immunother. 2016;65:1–11. doi:10.1007/s00262-015-1768-3.  https://link.springer.com/article/10.1007%2Fs00262-015-1768-3
  19. Reck M, Rodríguez-Abreu D, Robinson AG, Hui R, Csőszi T, Fülöp A, et al. Pembrolizumab versus Chemotherapy for PD-L1–Positive Non–Small-Cell Lung Cancer. N Engl J Med. 2016;375:1823–33. doi:10.1056/NEJMoa1606774.  http://www.nejm.org/doi/full/10.1056/NEJMoa1606774#t=article
  20. Rizvi NA, Hellmann MD, Snyder A, Kvistborg P, Makarov V, Havel JJ, et al. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer. Science (80- ). 2015;348:124–8. doi:10.1126/science.aaa1348.  http://science.sciencemag.org/content/348/6230/124.long
  21. Rosenberg JE, Hoffman-Censits J, Powles T, Van Der Heijden MS, Balar A V., Necchi A, et al. Atezolizumab in patients with locally advanced and metastatic urothelial carcinoma who have progressed following treatment with platinum-based chemotherapy: A single-arm, multicentre, phase 2 trial. Lancet. 2016;387:1909–20. doi:10.1016/S0140-6736(16)00561-4.  http://www.thelancet.com/journals/lancet/article/PIIS0140-6736(16)00561-4/supplemental
  22. Snyder A, Makarov V, Merghoub T, Yuan J, Zaretsky JM, Desrichard A, et al. Genetic Basis for Clinical Response to CTLA-4 Blockade in Melanoma. N Engl J Med. 2014;:2189–99. doi:10.1056/NEJMoa1406498.  http://www.nejm.org/doi/full/10.1056/NEJMoa1406498#t=article
  23. Van Allen EM, Miao D, Schilling B, Shukla SA, Blank C, Zimmer L, et al. Genomic correlates of response to CTLA-4 blockade in metastatic melanoma. Science (80- ). 2015;350:207–11. doi:10.1126/science.aad0095.  http://science.sciencemag.org/content/350/6257/207.long
  24. Zhou J, Nagarkatti P, Zhong Y, Nagarkatti M. Characterization of T-cell memory phenotype after in vitro expansion of tumor-infiltrating lymphocytes from melanoma patients. Anticancer Res. 2011;31:4099–109. doi:10.1016/j.jaac.2013.12.025.  http://ar.iiarjournals.org/cgi/pmidlookup?view=long&pmid=22199267