LAG-3 Expression Predicts Outcome in Stage II Colon Cancer
Abstract
:1. Introduction
2. Patients and Methods
2.1. Patient Cohort
2.2. Next-Generation Tissue Microarray (ngTMA®) Construction
2.3. Immunohistochemistry
2.4. Evaluation of Immunohistochemistry
2.5. Statistical Analysis
3. Results
3.1. Patients Characteristics
3.2. LAG-3 Expression on TILs and Its Correlation with Clinicopathological Characteristics
3.3. LAG-3 Expression on TILs and Its Association with DFS
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Bray, F.; Me, J.F.; Soerjomataram, I.; Siegel, R.L.; Torre, L.A.; Jemal, A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA A Cancer J. Clin. 2018, 68, 394–424. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Berger, M.D.; Ning, Y.; Stintzing, S.; Heinemann, V.; Cao, S.; Zhang, W.; Yang, D.; Miyamoto, Y.; Suenaga, M.; Schirripa, M.; et al. A polymorphism within the R-spondin 2 gene predicts outcome in metastatic colorectal cancer patients treated with FOLFIRI/bevacizumab: Data from FIRE-3 and TRIBE trials. Eur. J. Cancer 2020, 131, 89–97. [Google Scholar] [CrossRef] [PubMed]
- Brenner, H.; Kloor, M.; Pox, C.P. Colorectal cancer. Lancet 2014, 383, 1490–1502. [Google Scholar] [CrossRef]
- Gunderson, L.L.; Jessup, J.M.; Sargent, D.J.; Greene, F.L.; Stewart, A. Revised Tumor and Node Categorization for Rectal Cancer Based on Surveillance, Epidemiology, and End Results and Rectal Pooled Analysis Outcomes. J. Clin. Oncol. 2010, 28, 256–263. [Google Scholar] [CrossRef] [PubMed]
- Tomlinson, J.S.; Jarnagin, W.R.; DeMatteo, R.P.; Fong, Y.; Kornprat, P.; Gonen, M.; Kemeny, N.; Brennan, M.F.; Blumgart, L.H.; D’Angelica, M. Actual 10-Year Survival After Resection of Colorectal Liver Metastases Defines Cure. J. Clin. Oncol. 2007, 25, 4575–4580. [Google Scholar] [CrossRef] [PubMed]
- Argilés, G.; Tabernero, J.; Labianca, R.; Hochhauser, D.; Salazar, R.; Ivenson, T.; Laurent-Puig, P.; Quirke, P.; Yoshino, T.; Taieb, J.; et al. Localised colon cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann. Oncol. 2020, 31, 1291–1305. [Google Scholar] [CrossRef] [PubMed]
- Shields, A.F. What is the optimal duration of adjuvant therapy in colon cancer? Clin. Adv. Hematol. Oncol. 2017, 15, 734–738. [Google Scholar]
- Wyss, J.; Dislich, B.; Koelzer, V.H.; Galvan, J.A.; Dawson, H.; Hädrich, M.; Inderbitzin, D.; Lugli, A.; Zlobec, I.; Berger, M.D. Stromal PD-1/PD-L1 Expression Predicts Outcome in Colon Cancer Patients. Clin. Color. Cancer 2019, 18, e20–e38. [Google Scholar] [CrossRef]
- Pagès, F.; Mlecnik, B.; Marliot, F.; Bindea, G.; Ou, F.S.; Bifulco, C.; Lugli, A.; Zlobec, I.; Rau, T.T.; Berger, M.D.; et al. International validation of the consensus Immunoscore for the classification of colon cancer: A prognostic and accuracy study. Lancet 2018, 391, 2128–2139. [Google Scholar] [CrossRef]
- Li, Y.; Liang, L.; Dai, W.; Cai, G.; Xu, Y.; Li, X.; Li, Q.; Cai, S. Prognostic impact of programed cell death-1 (PD-1) and PD-ligand 1 (PD-L1) expression in cancer cells and tumor infiltrating lymphocytes in colorectal cancer. Mol. Cancer 2016, 15, 1–15. [Google Scholar] [CrossRef] [Green Version]
- Andrews, L.P.; Marciscano, A.E.; Drake, C.G.; Vignali, D.A. LAG3 (CD223) as a cancer immunotherapy target. Immunol. Rev. 2017, 276, 80–96. [Google Scholar] [CrossRef] [PubMed]
- Woo, S.R.; Turnis, M.E.; Goldberg, M.V.; Bankoti, J.; Selby, M.; Nirschl, C.J.; Bettini, M.L.; Gravano, D.M.; Vogel, P.; Liu, C.L.; et al. Immune inhibitory molecules LAG-3 and PD-1 synergistically regulate T-cell function to promote tumoral immune escape. Cancer Res. 2012, 72, 917–927. [Google Scholar] [CrossRef] [Green Version]
- Kouo, T.; Huang, L.; Pucsek, A.B.; Cao, M.; Solt, S.; Amstrong, T.; Jaffee, E. Galectin-3 Shapes Antitumor Immune Responses by Suppressing CD8+ T Cells via LAG-3 and Inhibiting Expansion of Plasmacytoid Dendritic Cells. Cancer Immunol. Res. 2015, 3, 412–423. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Long, L.; Zhang, X.; Chen, F.; Pan, Q.; Phiphatwatchara, P.; Zeng, Y.; Chen, H. The promising immune checkpoint LAG-3: From tumor microenvironment to cancer immunotherapy. Genes Cancer 2018, 9, 176–189. [Google Scholar] [CrossRef] [Green Version]
- Xu, F.; Liu, J.; Liu, D.; Liu, B.; Wang, M.; Hu, Z.; Du, X.; Tang, L.; He, F. LSECtin Expressed on melanoma cells promotes tumor progression by inhibiting antitumor T-cell responses. Cancer Res. 2014, 74, 3418–3428. [Google Scholar] [CrossRef] [Green Version]
- He, Y.; Rivard, C.J.; Rozeboom, L.; Yu, H.; Ellison, K.; Kowalewski, A.; Zhou, C.; Hirsch, F.R. Lymphocyte-activation gene-3, an important immune checkpoint in cancer. Cancer Sci. 2016, 107, 1193–1197. [Google Scholar] [CrossRef] [PubMed]
- Ruffo, E.; Wu, R.C.; Bruno, T.C.; Workman, C.J.; Vignali, D.A.A. Lymphocyte-activation gene 3 (LAG3): The next immune checkpoint receptor. Semin. Immunol. 2019, 42, 101305. [Google Scholar] [CrossRef]
- Dawson, H.; Galuppini, F.; Träger, P.; Berger, M.D.; Studer, P.; Brügger, L.; Zlobec, I.; Inderbitzin, D.; Lugli, A. Validation of the International Tumor Budding Consensus Conference 2016 recommendations on tumor budding in stage I-IV colorectal cancer. Hum. Pathol. 2019, 85, 145–151. [Google Scholar] [CrossRef] [Green Version]
- Sobottka, B.; Moch, H.; Varga, Z. Differential PD-1/LAG-3 expression and immune phenotypes in metastatic sites of breast cancer. Breast Cancer Res. 2021, 23, 4. [Google Scholar] [CrossRef] [PubMed]
- Interpretation Guide for Staining of Colorectal Tissue. Available online: https://diagnostics.roche.com/content/dam/diagnostics/us/en/products/c/colorectal-ihc-portfolio/MMR-IHC-Panel-InterpretationGuide.pdf (accessed on 3 July 2021).
- Lee, S.J.; Jun, S.Y.; Lee, I.H.; Kang, B.W.; Park, S.Y.; Kim, H.J.; Park, J.S.; Choi, G.S.; Yoon, G.; Kim, J.G. CD274, LAG3, and IDO1 expressions in tumor-infiltrating immune cells as prognostic biomarker for patients with MSI-high colon cancer. J. Cancer Res. Clin. Oncol. 2018, 144, 1005–1014. [Google Scholar] [CrossRef] [PubMed]
- Mlecnik, B.; Bindea, G.; Angell, H.K.; Maby, P.; Angelova, M.; Tougeron, D.; Church, S.E.; Lafontaine, L.; Fischer, M.; Fredriksen, T.; et al. Integrative analyses of colorectal cancer show Immunoscore is a stronger predictor of patient survival than microsatellite instability. Immunity 2016, 44, 698–711. [Google Scholar] [CrossRef] [Green Version]
- Zhang, Y.; Liu, Y.; Luo, Y.; Liu, B.L.; Huang, Q.T.; Wang, F.; Zhong, Q. Prognostic value of Lymphocyte Activation Gene-3 (LAG-3) expression in esophageal squamous cell carcinoma. J. Cancer 2018, 9, 4287–4293. [Google Scholar] [CrossRef] [Green Version]
- Hald, S.M.; Rakaee, M.; Martinez, I.; Richardsen, E.; Al-Saad, S.; Paulsen, E.E.; Blix, E.S.; Kilvaer, T.; Andersen, S.; Busund, L.T.; et al. LAG-3 in non–small-cell lung cancer: Expression in primary tumors and metastatic lymph nodes is associated with improved survival. Clin. Lung Cancer 2018, 19, 249–259.e2. [Google Scholar] [CrossRef]
- Burugu, S.; Gao, D.; Leung, S.; Chia, S.K.; Nielsen, T.O. LAG-3+ tumor infiltrating lymphocytes in breast cancer: Clinical correlates and association with PD-1/PD-L1+ tumors. Ann. Oncol. 2017, 28, 2977–2984. [Google Scholar] [CrossRef] [PubMed]
- Chen, J.; Chen, Z. The effect of immune microenvironment on the progression and prognosis of colorectal cancer. Med. Oncol. 2014, 31, 82. [Google Scholar] [CrossRef] [PubMed]
- Saleh, R.; Taha, R.Z.; Toor, S.M.; Sasidharan Nair, V.; Murshed, K.; Khawar, M.; Al-Dhaheri, M.; Petkar, M.A.; Abu Nada, M.; Elkord, E. Expression of immune checkpoints and T cell exhaustion markers in early and advanced stages of colorectal cancer. Cancer Immunol. Immunother. 2020, 69, 1989–1999. [Google Scholar] [CrossRef]
- Toor, S.M.; Murshed, K.; Al-Dhaheri, M.; Khawar, M.; Abu Nada, M.; Elkord, E. Immune Checkpoints in Circulating and Tumor-Infiltrating CD4+ T Cell Subsets in Colorectal Cancer Patients. Front. Immunol. 2019, 10, 2936. [Google Scholar] [CrossRef] [PubMed]
- Larkin, J.; Chiarion-Sileni, V.; Gonzalez, R.; Grob, J.J.; Cowey, C.L.; Lao, C.D.; Schadendorf, D.; Dummer, R.; Smylie, M.; Rutkowski, P.; et al. Combined nivolumab and ipilimumab or monotherapy in untreated Melanoma. N. Engl. J. Med. 2015, 373, 23–34. [Google Scholar] [CrossRef] [Green Version]
- Brahmer, J.; Reckamp, K.L.; Baas, P.; Crinò, L.; Eberhardt, W.E.; Poddubskaya, E.; Antonia, S.; Pluzanski, A.; Vokes, E.E.; Holgado, E.; et al. Nivolumab versus docetaxel in advanced squamous-cell non–small-cell lung cancer. N. Engl. J. Med. 2015, 373, 123–135. [Google Scholar] [CrossRef] [Green Version]
- Motzer, R.J.; Escudier, B.; McDermott, D.F.; George, S.; Hammers, H.J.; Srinivas, S.; Tykodi, S.S.; Sosman, J.A.; Procopio, G.; Plimack, E.R.; et al. Nivolumab versus everolimus in advanced renal-cell carcinoma. N. Engl. J. Med. 2015, 373, 1803–1813. [Google Scholar] [CrossRef]
- Bellmunt, J.; de Wit, R.; Vaughn, D.J.; Fradet, Y.; Lee, J.L.; Fong, L.; Vogelzang, N.J.; Climent, M.A.; Petrylak, D.P.; Choueiri, T.K.; et al. Pembrolizumab as second-line therapy for advanced urothelial carcinoma. N. Engl. J. Med. 2017, 376, 1015–1026. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Ferris, R.L.; Blumenschein, G., Jr.; Fayette, J.; Guigay, J.; Colevas, A.D.; Licitra, L.; Harrington, K.; Kasper, S.; Vokes, E.E.; Even, C.; et al. Nivolumab for recurrent squamous-cell carcinoma of the head and neck. N. Engl. J. Med. 2016, 375, 1856–1867. [Google Scholar] [CrossRef] [PubMed]
- Younes, A.; Santoro, A.; Shipp, M.; Zinzani, P.L.; Timmerman, J.M.; Ansell, S.; Armand, P.; Fanale, M.; Ratanatharathorn, V.; Kuruvilla, J.; et al. Nivolumab for classical Hodgkin’s lymphoma after failure of both autologous stem-cell transplantation and brentuximab vedotin: A multicentre, multicohort, single-arm phase 2 trial. Lancet Oncol. 2016, 17, 1283–1294. [Google Scholar] [CrossRef] [Green Version]
- Maruhashi, T.; Sugiura, D.; Okazaki, I.M.; Okazaki, T. LAG-3: From molecular functions to clinical applications. J. Immunother. Cancer 2020, 8, e001014. [Google Scholar] [CrossRef] [PubMed]
- Lythgoe, M.P.; Liu, D.S.K.; Annels, N.E.; Krell, J.; Frampton, A.E. Gene of the month: Lymphocyte-activation gene 3 (LAG-3). J. Clin. Pathol. 2021, 28. [Google Scholar] [CrossRef]
- Overman, M.J.; McDermott, R.; Leach, J.L.; Lonardi, S.; Lenz, H.J.; Morse, M.A.; Desai, J.; Hill, A.; Axelson, M.; Moss, R.A.; et al. Nivolumab in patients with metastatic DNA mismatch repair-deficient or microsatellite instability-high colorectal cancer (CheckMate 142): An open-label, multicentre, phase 2 study. Lancet Oncol. 2017, 181182–181191. [Google Scholar] [CrossRef]
- André, T.; Shiu, K.K.; Kim, T.W.; Jensen, B.V.; Jensen, L.H.; Punt, C.; Smith, D.; Garcia-Carbonero, R.; Benavides, M.; Gibbs, P.; et al. Pembrolizumab in microsatellite instability-high advanced colorectal cancer. N. Engl. J. Med. 2020, 383, 2207–2218. [Google Scholar] [CrossRef]
- Eng, C.; Kim, T.W.; Bendell, J.; Argilés, G.; Tebbutt, N.C.; Di Bartolomeo, M.; Falcone, A.; Fakih, M.; Kozloff, M.; Segal, N.H.; et al. Atezolizumab with or without cobimetinib versus regorafenib in previously treated metastatic colorectal cancer (IMblaze370): A multicentre, open-label, phase 3, randomised, controlled trial. Lancet Oncol. 2019, 20, 849–861. [Google Scholar] [CrossRef]
- Combination Chemotherapy with or without Atezolizumab in Treating Patients with Stage III Colon Cancer and Deficient DNA Mismatch Repair. Available online: https://clinicaltrials.gov/ct2/show/NCT02912559 (accessed on 25 January 2021).
- Lau, D.; Kalaitzaki, E.; Church, D.N.; Pandha, H.; Tomlinson, I.; Annels, N.; Gerlinger, M.; Sclafani, F.; Smith, G.; Begum, R.; et al. Rationale and design of the POLEM trial: Avelumab plus fluoropyrimidine-based chemotherapy as adjuvant treatment for stage III mismatch repair deficient or POLE exonuclease domain mutant colon cancer: A phase III randomised study. ESMO Open 2020, 5, e000638. [Google Scholar] [CrossRef] [Green Version]
Feature | Combined | p-Value | ||
---|---|---|---|---|
Front and Center negative | Front or Center positive | |||
Age, years (n = 141) | Mean ± SD | 69.5 ± 13.8 | 67.5 ± 15.7 | 0.493 |
Gender (n = 142) | Male | 24 (52.2) | 58 (60.4) | 0.352 |
Female | 22 (47.8) | 38 (39.6) | ||
pT (n = 141) | pT3 | 40 (88.9) | 81 (84.4) | 0.474 |
pT4 | 5 (11.1) | 15 (15.6) | ||
Tumor grade (n = 134) | G1/G2 | 43 (97.8) | 79 (87.8) | 0.058 |
G3 | 1 (2.2) | 11 (12.2) | ||
EMVI (n = 135) | V0 | 37 (88.1) | 81 (87.1) | 0.871 |
V1 | 5 (11.9) | 12 (12.9) | ||
Tumor location (n = 139) | Left | 26 (59.1) | 47 (49.5) | 0.291 |
Right | 18 (40.9) | 48 (50.5) | ||
Tumor budding (ITBCC) (n = 142) | Mean ± SD | 11.1 ± 11.4 | 11.9 ± 10.8 | 0.408 |
MMR status (n = 134) | Proficient | 35 (87.5) | 66 (70.2) | 0.034 |
Deficient | 5 (12.5) | 28 (29.8) |
Feature | Front | Center | |||||
---|---|---|---|---|---|---|---|
Negative | Positive | p-value | Negative | Positive | p-value | ||
Age, years (n = 141) | Mean ± SD | 69.8 ± 13.9 | 67.1 ± 14.6 | 0.316 | 68.4 ± 14.0 | 67.7 ± 14.9 | 0.784 |
Gender (n = 142) | Male | 31 (54.4) | 51 (60.0) | 0.507 | 52 (56.5) | 28 (58.3) | 0.837 |
Female | 26 (45.6) | 34 (40.0) | 40 (43.5) | 20 (41.7) | |||
pT (n = 141) | pT3 | 48 (85.7) | 73 (85.9) | 0.978 | 78 (85.7) | 41 (85.4) | 0.962 |
pT4 | 8 (14.3) | 12 (14.1) | 13 (4.3) | 7 (14.6) | |||
Tumor grade (n = 134) | G1/G2 | 52 (96.3) | 70 (87.5) | 0.08 | 86 (95.6) | 36 (83.7) | 0.021 |
G3 | 2 (3.7) | 10 (12.5) | 4 (4.4) | 7 (16.3) | |||
EMVI (n = 135) | V0 | 46 (88.5) | 72 (86.8) | 1.0 | 75 (86.2) | 42 (91.3) | 0.39 |
V1 | 6 (11.5) | 11 (13.3) | 12 (13.8) | 4 (8.7) | |||
Tumor location (n = 139) | Left | 33 (60.0) | 40 (47.6) | 0.168 | 51 (57.3) | 21 (43.8) | 0.123 |
Right | 22 (40.0) | 44 (52.4) | 38 (42.7) | 27 (56.3) | |||
Tumor budding (ITBCC) (n = 142) | Mean ± SD | 11.2 ± 11.6 | 11.9 ± 10.5 | 0.227 | 12.5 ± 11.7 | 10.0 ± 9.3 | 0.142 |
MMR status (n = 134) | Proficient | 45 (86.5) | 56 (68.3) | 0.017 | 66 (75.0) | 35 (76.1) | 0.89 |
Deficient | 7 (13.5) | 26 (31.7) | 22 (25.0) | 11 (23.9) |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Rhyner Agocs, G.; Assarzadegan, N.; Kirsch, R.; Dawson, H.; Galván, J.A.; Lugli, A.; Zlobec, I.; Berger, M.D. LAG-3 Expression Predicts Outcome in Stage II Colon Cancer. J. Pers. Med. 2021, 11, 749. https://doi.org/10.3390/jpm11080749
Rhyner Agocs G, Assarzadegan N, Kirsch R, Dawson H, Galván JA, Lugli A, Zlobec I, Berger MD. LAG-3 Expression Predicts Outcome in Stage II Colon Cancer. Journal of Personalized Medicine. 2021; 11(8):749. https://doi.org/10.3390/jpm11080749
Chicago/Turabian StyleRhyner Agocs, Gaëlle, Naziheh Assarzadegan, Richard Kirsch, Heather Dawson, José A. Galván, Alessandro Lugli, Inti Zlobec, and Martin D. Berger. 2021. "LAG-3 Expression Predicts Outcome in Stage II Colon Cancer" Journal of Personalized Medicine 11, no. 8: 749. https://doi.org/10.3390/jpm11080749
APA StyleRhyner Agocs, G., Assarzadegan, N., Kirsch, R., Dawson, H., Galván, J. A., Lugli, A., Zlobec, I., & Berger, M. D. (2021). LAG-3 Expression Predicts Outcome in Stage II Colon Cancer. Journal of Personalized Medicine, 11(8), 749. https://doi.org/10.3390/jpm11080749