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Melanoma pp 223–233Cite as

PD-L1 Detection on Circulating Melanoma Cells

Part of the Methods in Molecular Biology book series (MIMB,volume 2265)

Abstract

The advent of personalized medicines targeting cell signaling pathways has radically improved melanoma patient outcomes. More recently, immune-modulating therapies disrupting the PD-1/PD-L1 axis have become a powerful tool in the treatment of a range of melanoma, showing a profound improvement in the overall survival outcomes. However, immune checkpoint inhibitors (ICIs) are associated with considerable toxicities and appear to only be efficacious in a subset of melanoma patients. Therefore, there is an urgent need to identify biomarkers that can determine if patients will or will not respond to ICI therapy. Here, we describe an optimized method for analyzing PD-L1 expression on circulating melanoma cells following immunomagnetic enrichment from patient blood samples.

Key words

  • Circulating tumor cells (CTC)
  • Melanoma
  • PD-L1
  • Immunotherapy
  • Liquid biopsy

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References

  1. Ding PN, Becker TM, Bray VJ, Chua W, Ma YF, Lynch D, Po J, Luk AWS, Caixeiro N, de Souza P, Roberts TL (2019) The predictive and prognostic significance of liquid biopsy in advanced epidermal growth factor receptor-mutated non-small cell lung cancer: a prospective study. Lung Cancer 134:187–193. https://doi.org/10.1016/j.lungcan.2019.06.021

    CAS  CrossRef  PubMed  Google Scholar 

  2. Lim M, Kim CJ, Sunkara V, Kim MH, Cho YK (2018) Liquid biopsy in lung cancer: clinical applications of circulating biomarkers (CTCs and ctDNA). Micromachines (Basel) 9(3):100. https://doi.org/10.3390/mi9030100

    CrossRef  Google Scholar 

  3. Alix-Panabieres C, Pantel K (2016) Clinical applications of circulating tumor cells and circulating tumor DNA as liquid biopsy. Cancer Discov 6(5):479–491. https://doi.org/10.1158/2159-8290.CD-15-1483

    CAS  CrossRef  PubMed  Google Scholar 

  4. Becker TM, Caixeiro NJ, Lim SH, Tognela A, Kienzle N, Scott KF, Spring KJ, de Souza P (2014) New frontiers in circulating tumor cell analysis: a reference guide for biomolecular profiling toward translational clinical use. Int J Cancer 134(11):2523–2533. https://doi.org/10.1002/ijc.28516

    CAS  CrossRef  PubMed  Google Scholar 

  5. Hwang WL, Pleskow HM, Miyamoto DT (2018) Molecular analysis of circulating tumors cells: biomarkers beyond enumeration. Adv Drug Deliv Rev 125:122–131. https://doi.org/10.1016/j.addr.2018.01.003

    CAS  CrossRef  PubMed  Google Scholar 

  6. Zhang S, Li L, Wang T, Bian L, Hu H, Xu C, Liu B, Liu Y, Cristofanilli M, Jiang Z (2016) Real-time HER2 status detected on circulating tumor cells predicts different outcomes of anti-HER2 therapy in histologically HER2-positive metastatic breast cancer patients. BMC Cancer 16:526. https://doi.org/10.1186/s12885-016-2578-5

    CAS  CrossRef  PubMed  PubMed Central  Google Scholar 

  7. Gray ES, Rizos H, Reid AL, Boyd SC, Pereira MR, Lo J, Tembe V, Freeman J, Lee JH, Scolyer RA, Siew K, Lomma C, Cooper A, Khattak MA, Meniawy TM, Long GV, Carlino MS, Millward M, Ziman M (2015) Circulating tumor DNA to monitor treatment response and detect acquired resistance in patients with metastatic melanoma. Oncotarget 6(39):42008–42018. https://doi.org/10.18632/oncotarget.5788

    CrossRef  PubMed  PubMed Central  Google Scholar 

  8. Lee M, Kim EJ, Cho Y, Kim S, Chung HH, Park NH, Song YS (2017) Predictive value of circulating tumor cells (CTCs) captured by microfluidic device in patients with epithelial ovarian cancer. Gynecol Oncol 145(2):361–365. https://doi.org/10.1016/j.ygyno.2017.02.042

    CrossRef  PubMed  Google Scholar 

  9. Koyanagi K, Mori T, O’Day SJ, Martinez SR, Wang HJ, Hoon DS (2006) Association of circulating tumor cells with serum tumor-related methylated DNA in peripheral blood of melanoma patients. Cancer Res 66(12):6111–6117. https://doi.org/10.1158/0008-5472.CAN-05-4198

    CAS  CrossRef  PubMed  PubMed Central  Google Scholar 

  10. Aya-Bonilla CA, Marsavela G, Freeman JB, Lomma C, Frank MH, Khattak MA, Meniawy TM, Millward M, Warkiani ME, Gray ES, Ziman M (2017) Isolation and detection of circulating tumour cells from metastatic melanoma patients using a slanted spiral microfluidic device. Oncotarget 8(40):67355–67368. https://doi.org/10.18632/oncotarget.18641

    CrossRef  PubMed  PubMed Central  Google Scholar 

  11. Banko P, Lee SY, Nagygyorgy V, Zrinyi M, Chae CH, Cho DH, Telekes A (2019) Technologies for circulating tumor cell separation from whole blood. J Hematol Oncol 12(1):48. https://doi.org/10.1186/s13045-019-0735-4

    CrossRef  PubMed  PubMed Central  Google Scholar 

  12. Alix-Panabieres C, Pantel K (2013) Circulating tumor cells: liquid biopsy of cancer. Clin Chem 59(1):110–118. https://doi.org/10.1373/clinchem.2012.194258

    CAS  CrossRef  PubMed  Google Scholar 

  13. Satelli A, Mitra A, Cutrera JJ, Devarie M, Xia X, Ingram DR, Dibra D, Somaiah N, Torres KE, Ravi V, Ludwig JA, Kleinerman ES, Li S (2014) Universal marker and detection tool for human sarcoma circulating tumor cells. Cancer Res 74(6):1645–1650. https://doi.org/10.1158/0008-5472.CAN-13-1739

    CAS  CrossRef  PubMed  PubMed Central  Google Scholar 

  14. Sullivan JP, Nahed BV, Madden MW, Oliveira SM, Springer S, Bhere D, Chi AS, Wakimoto H, Rothenberg SM, Sequist LV, Kapur R, Shah K, Iafrate AJ, Curry WT, Loeffler JS, Batchelor TT, Louis DN, Toner M, Maheswaran S, Haber DA (2014) Brain tumor cells in circulation are enriched for mesenchymal gene expression. Cancer Discov 4(11):1299–1309. https://doi.org/10.1158/2159-8290.CD-14-0471

    CAS  CrossRef  PubMed  PubMed Central  Google Scholar 

  15. Salvianti F, Orlando C, Massi D, De Giorgi V, Grazzini M, Pazzagli M, Pinzani P (2015) Tumor-related methylated cell-free DNA and circulating tumor cells in melanoma. Front Mol Biosci 2:76. https://doi.org/10.3389/fmolb.2015.00076

    CAS  CrossRef  PubMed  Google Scholar 

  16. Ben-Izhak O, Stark P, Levy R, Bergman R, Lichtig C (1994) Epithelial markers in malignant melanoma. A study of primary lesions and their metastases. Am J Dermatopathol 16(3):241–246. https://doi.org/10.1097/00000372-199406000-00003

    CAS  CrossRef  PubMed  Google Scholar 

  17. Grzywa TM, Paskal W, Wlodarski PK (2017) Intratumor and intertumor heterogeneity in melanoma. Transl Oncol 10(6):956–975. https://doi.org/10.1016/j.tranon.2017.09.007

    CrossRef  PubMed  PubMed Central  Google Scholar 

  18. Gray ES, Reid AL, Bowyer S, Calapre L, Siew K, Pearce R, Cowell L, Frank MH, Millward M, Ziman M (2015) Circulating melanoma cell subpopulations: their heterogeneity and differential responses to treatment. J Invest Dermatol 135(8):2040–2048. https://doi.org/10.1038/jid.2015.127

    CAS  CrossRef  PubMed  PubMed Central  Google Scholar 

  19. Vanella V, Festino L, Trojaniello C, Vitale MG, Sorrentino A, Paone M, Ascierto PA (2019) The role of BRAF-targeted therapy for advanced melanoma in the immunotherapy era. Curr Oncol Rep 21(9):76. https://doi.org/10.1007/s11912-019-0827-x

    CrossRef  PubMed  Google Scholar 

  20. Mackiewicz J, Mackiewicz A (2018) BRAF and MEK inhibitors in the era of immunotherapy in melanoma patients. Contemp Oncol (Pozn) 22(1A):68–72. https://doi.org/10.5114/wo.2018.73890

    CrossRef  Google Scholar 

  21. Johnson DB, Estrada MV, Salgado R, Sanchez V, Doxie DB, Opalenik SR, Vilgelm AE, Feld E, Johnson AS, Greenplate AR, Sanders ME, Lovly CM, Frederick DT, Kelley MC, Richmond A, Irish JM, Shyr Y, Sullivan RJ, Puzanov I, Sosman JA, Balko JM (2016) Melanoma-specific MHC-II expression represents a tumour-autonomous phenotype and predicts response to anti-PD-1/PD-L1 therapy. Nat Commun 7:10582. https://doi.org/10.1038/ncomms10582

    CAS  CrossRef  PubMed  PubMed Central  Google Scholar 

  22. Gowrishankar K, Snoyman S, Pupo GM, Becker TM, Kefford RF, Rizos H (2012) Acquired resistance to BRAF inhibition can confer cross-resistance to combined BRAF/MEK inhibition. J Invest Dermatol 132(7):1850–1859. https://doi.org/10.1038/jid.2012.63

    CAS  CrossRef  PubMed  Google Scholar 

  23. Wyluda EJ, Cheng J, Schell TD, Haley JS, Mallon C, Neves RI, Robertson G, Sivik J, Mackley H, Talamo G, Drabick JJ (2015) Durable complete responses off all treatment in patients with metastatic malignant melanoma after sequential immunotherapy followed by a finite course of BRAF inhibitor therapy. Cancer Biol Ther 16(5):662–670. https://doi.org/10.1080/15384047.2015.1026507

    CAS  CrossRef  PubMed  PubMed Central  Google Scholar 

  24. Domingues B, Lopes JM, Soares P, Populo H (2018) Melanoma treatment in review. Immunotargets Ther 7:35–49. https://doi.org/10.2147/ITT.S134842

    CAS  CrossRef  PubMed  PubMed Central  Google Scholar 

  25. Quandt D, Dieter Zucht H, Amann A, Wulf-Goldenberg A, Borrebaeck C, Cannarile M, Lambrechts D, Oberacher H, Garrett J, Nayak T, Kazinski M, Massie C, Schwarzenbach H, Maio M, Prins R, Wendik B, Hockett R, Enderle D, Noerholm M, Hendriks H, Zwierzina H, Seliger B (2017) Implementing liquid biopsies into clinical decision making for cancer immunotherapy. Oncotarget 8(29):48507–48520. https://doi.org/10.18632/oncotarget.17397

    CrossRef  PubMed  PubMed Central  Google Scholar 

  26. Havel JJ, Chowell D, Chan TA (2019) The evolving landscape of biomarkers for checkpoint inhibitor immunotherapy. Nat Rev Cancer 19(3):133–150. https://doi.org/10.1038/s41568-019-0116-x

    CAS  CrossRef  PubMed  PubMed Central  Google Scholar 

  27. Bajwa R, Cheema A, Khan T, Amirpour A, Paul A, Chaughtai S, Patel S, Patel T, Bramson J, Gupta V, Levitt M, Asif A, Hossain MA (2019) Adverse effects of immune checkpoint inhibitors (programmed death-1 inhibitors and cytotoxic t-lymphocyte-associated protein-4 inhibitors): results of a retrospective study. J Clin Med Res 11(4):225–236. https://doi.org/10.14740/jocmr3750

    CAS  CrossRef  PubMed  PubMed Central  Google Scholar 

  28. Davis AA, Patel VG (2019) The role of PD-L1 expression as a predictive biomarker: an analysis of all US Food and Drug Administration (FDA) approvals of immune checkpoint inhibitors. J Immunother Cancer 7(1):278. https://doi.org/10.1186/s40425-019-0768-9

    CrossRef  PubMed  PubMed Central  Google Scholar 

  29. Maleki Vareki S, Garrigos C, Duran I (2017) Biomarkers of response to PD-1/PD-L1 inhibition. Crit Rev Oncol Hematol 116:116–124. https://doi.org/10.1016/j.critrevonc.2017.06.001

    CrossRef  PubMed  Google Scholar 

  30. Gibney GT, Weiner LM, Atkins MB (2016) Predictive biomarkers for checkpoint inhibitor-based immunotherapy. Lancet Oncol 17(12):e542–e551. https://doi.org/10.1016/S1470-2045(16)30406-5

    CAS  CrossRef  PubMed  PubMed Central  Google Scholar 

  31. Kee D, McArthur G (2017) Immunotherapy of melanoma. Eur J Surg Oncol 43(3):594–603. https://doi.org/10.1016/j.ejso.2016.07.014

    CAS  CrossRef  PubMed  Google Scholar 

  32. Herbst RS, Soria JC, Kowanetz M, Fine GD, Hamid O, Gordon MS, Sosman JA, McDermott DF, Powderly JD, Gettinger SN, Kohrt HE, Horn L, Lawrence DP, Rost S, Leabman M, Xiao Y, Mokatrin A, Koeppen H, Hegde PS, Mellman I, Chen DS, Hodi FS (2014) Predictive correlates of response to the anti-PD-L1 antibody MPDL3280A in cancer patients. Nature 515(7528):563–567. https://doi.org/10.1038/nature14011

    CAS  CrossRef  PubMed  PubMed Central  Google Scholar 

  33. Freeman JB, Gray ES, Millward M, Pearce R, Ziman M (2012) Evaluation of a multi-marker immunomagnetic enrichment assay for the quantification of circulating melanoma cells. J Transl Med 10:192. https://doi.org/10.1186/1479-5876-10-192

    CrossRef  PubMed  PubMed Central  Google Scholar 

  34. Sunshine JC, Nguyen PL, Kaunitz GJ, Cottrell TR, Berry S, Esandrio J, Xu H, Ogurtsova A, Bleich KB, Cornish TC, Lipson EJ, Anders RA, Taube JM (2017) PD-L1 expression in melanoma: a quantitative immunohistochemical antibody comparison. Clin Cancer Res 23(16):4938–4944. https://doi.org/10.1158/1078-0432.CCR-16-1821

    CAS  CrossRef  PubMed  PubMed Central  Google Scholar 

  35. Kaunitz GJ, Cottrell TR, Lilo M, Muthappan V, Esandrio J, Berry S, Xu H, Ogurtsova A, Anders RA, Fischer AH, Kraft S, Gerstenblith MR, Thompson CL, Honda K, Cuda JD, Eberhart CG, Handa JT, Lipson EJ, Taube JM (2017) Melanoma subtypes demonstrate distinct PD-L1 expression profiles. Lab Investig 97(9):1063–1071. https://doi.org/10.1038/labinvest.2017.64

    CAS  CrossRef  PubMed  Google Scholar 

  36. Parra ER, Villalobos P, Mino B, Rodriguez-Canales J (2018) Comparison of different antibody clones for immunohistochemistry detection of programmed cell death ligand 1 (PD-L1) on non-small cell lung carcinoma. Appl Immunohistochem Mol Morphol 26(2):83–93. https://doi.org/10.1097/PAI.0000000000000531

    CAS  CrossRef  PubMed  Google Scholar 

  37. Anantharaman A, Friedlander T, Lu D, Krupa R, Premasekharan G, Hough J, Edwards M, Paz R, Lindquist K, Graf R, Jendrisak A, Louw J, Dugan L, Baird S, Wang Y, Dittamore R, Paris PL (2016) Programmed death-ligand 1 (PD-L1) characterization of circulating tumor cells (CTCs) in muscle invasive and metastatic bladder cancer patients. BMC Cancer 16(1):744. https://doi.org/10.1186/s12885-016-2758-3

    CAS  CrossRef  PubMed  PubMed Central  Google Scholar 

  38. Mimura K, Teh JL, Okayama H, Shiraishi K, Kua LF, Koh V, Smoot DT, Ashktorab H, Oike T, Suzuki Y, Fazreen Z, Asuncion BR, Shabbir A, Yong WP, So J, Soong R, Kono K (2018) PD-L1 expression is mainly regulated by interferon gamma associated with JAK-STAT pathway in gastric cancer. Cancer Sci 109(1):43–53. https://doi.org/10.1111/cas.13424

    CAS  CrossRef  PubMed  Google Scholar 

  39. Castro F, Cardoso AP, Goncalves RM, Serre K, Oliveira MJ (2018) Interferon-gamma at the crossroads of tumor immune surveillance or evasion. Front Immunol 9:847. https://doi.org/10.3389/fimmu.2018.00847

    CAS  CrossRef  PubMed  PubMed Central  Google Scholar 

  40. Po JW, Ma Y, Balakrishna B, Brungs D, Azimi F, de Souza P, Becker TM (2019) Immunomagnetic isolation of circulating melanoma cells and detection of PD-L1 status. PLoS One 14(2):e0211866. https://doi.org/10.1371/journal.pone.0211866

    CAS  CrossRef  PubMed  PubMed Central  Google Scholar 

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Acknowledgments

This work was supported by the Cancer Institute New South Wales through the Centre for Oncology Education and Research Translation (CONCERT, grant ID: 13/TRC/1-01). Human ethics approval, HREC/13/LPOOL/158, was obtained and managed by the CONCERT Biobank.

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Po, J.W. et al. (2021). PD-L1 Detection on Circulating Melanoma Cells. In: Hargadon, K.M. (eds) Melanoma. Methods in Molecular Biology, vol 2265. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1205-7_17

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  • DOI: https://doi.org/10.1007/978-1-0716-1205-7_17

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