Literature DB >> 27660711

Biomarkers immune monitoring technology primer: Immunoscore® Colon.

Fabienne Hermitte1.   

Abstract

Entities:  

Year:  2016        PMID: 27660711      PMCID: PMC5029002          DOI: 10.1186/s40425-016-0161-x

Source DB:  PubMed          Journal:  J Immunother Cancer        ISSN: 2051-1426            Impact factor:   13.751


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Description of the technology

The Immunoscore® assay for Colon Cancer (IS Colon) is the first standardized immune-based assay for the classification of cancer. It assesses the host immune response to Colon Cancer (CC) by measuring intra- and peri-tumoral T cell infiltration in formalin-fixed paraffin-embedded (FFPE) tissue sections. For each tumor sample, 2 slides are stained using an automated immunohistochemistry (IHC) staining instrument (BenchMark XT, Ventana): one with CD3 and one with CD8 ready-to-use monoclonal antibodies (HalioDx). Detection is performed with the ultraView Universal DAB Detection Kit (Ventana), followed by counterstaining in order to visualize nuclei (Bluing Reagent, Ventana). Stained slides are then washed, dehydrated, mounted and coverslipped. Digital images of stained slides are obtained using a whole slide scanner (Nanozoomer XR, Hamamatsu), and analyzed by a software program (Immunoscore® Analyzer, HalioDx) if staining and image quality is validated by the operator. One separate control slide with 3 external controls −1 negative tissue (placenta) and 2 positive (1 tissue: tonsil and a cell line pellet) - is processed identically in each IHC run, and allows monitoring of the staining and scanning steps.

Image processing

Digital images are imported into the Immunoscore® Analyzer software and automatically processed for tissue detection (core of the tumor (CT), healthy non-epithelial tissue, and epithelium) and CD3 and CD8 positive lymphocytes quantification. The histotechnician reviews the region annotations and modifies them if required; the invasive margin (IM) is subsequently displayed automatically. Its width spans 360 μm into the healthy tissue and 360 μm into the tumor from the frontier between these two tissue types.

Density and score calculation

After image processing validation by an independent reviewer, densities of CD3 and CD8 positive lymphocytes in the 2 regions of interest (ROIs) CT or IM regions are reported. The best performing algorithm to compute the Immunoscore has been defined in the large international SITC -led retrospective validation study [1, 2] conducted on more than 3800 St I-III colon cancer patients, Briefly, for each marker (CD3 & CD8) and each zone (CT & IM), densities distributions have been established on the study training set; for each parameter of a tested sample (CD3, CD8, CT, IM), a percentile is derived from these distributions. An average percentile is calculated based on these 4 values. The Immunoscore® is reported as IS-0, 1 – 2 – 3 – 4 based on the following average percentile classes respectively: [0 %; 10 %] - [>10 %; 25 %] - [>25 %; 70 %] - [>70 %; 95 %] - [>95 %; 100 %].

Reported prognostic information

Statistically significant prognostic groups have been defined in the SITC study [2], with the Immunoscore® categories 0 and 1 indicating a bad prognosis (high risk of relapse), while the Immunoscore® categories 3 and 4 indicate a good prognosis (low risk of relapse), and patients with an Immunoscore® 2 have an intermediate risk of relapse.

Type of data obtained/readout

The Immunoscore® Analyzer generates a printable report. This report contains a capture of all quality control results as well as the analysis result.

Limitations of the approach

In order to get an accurate assessment of intra- and peri-tumoral T-cell infiltration, the tumor specimen must be selected from the block the most infiltrated by immune cells and must contain both the core of the tumor and the invasive margin. Pathologist review is mandatory to qualify the selection of the specimen according to those criteria prior to the testing. The image analysis is a critical step in the process, and digital pathology expertise is required. The Immunoscore® assay is offered through HalioDx service laboratory and will be initially implemented in expert centers only. Finally Immunoscore® optimal performance were validated on a specific platform combining validated instruments (autostainer and scanner) and qualified reagents. Future equivalency studies will be conducted to qualify additional platforms.

Types of samples needed and special issues pertaining to samples

Starting material is a FFPE tissue block from a surgical section of colon cancer. The block must contain the core of the tumor (CT) and the invasive margin (IM) (tumor and healthy tissue present in the sample). Samples must have been fixed with 10 % buffered formalin. Slides must be prepared less than 4 months before testing; 2 slides are required (one for CD3, one for CD8) from adjacent 4 μm slices. Slices should be mounted on positively charged glass slides (Superfrost™ Plus or equivalent).

Level of evidence

The role of adaptive immune response in controlling tumor progression in colorectal cancer was first evidenced by Galon et al. in 2006 [3]. In a comprehensive analysis of the tumor microenvironment, they showed that the type, density and location of immune cells within tumor regions predicted clinical outcome of the patients. In particular, the combined analysis of immune cells density in both tumor regions (CT and IM) was shown to improve the accuracy of survival prediction as compared to single-region analysis. It is based on those observations that the Immunoscore® was established and its prognostic power has been shown to surpass that of the conventional TNM staging and clinicopathological factors [3-6]. Notably, when Immunoscore® was applied on two large independent cohorts of early-stage colorectal cancer (n = 602), only 4.8 % of patients with a high Immunoscore relapsed after 5 years as opposed to 72 % of patients with a low IS indicating that these patients could potentially have benefited from adjuvant therapy. Recent data in large cohorts of CRC patients further demonstrated the critical importance of IS over tumor-related features in the mechanism of dissemination to distant metastasis [7]. Immunoscore® was shown to be a stronger predictor of survival than microsatellite instability status [8]. Microsatellite instable (MSI) tumors often contain intra-epithelial T cells in response to the expression of neo-antigens on the cell surface and this probably contributes to the better prognosis of patients with MSI tumors. Although patients with IS-High tumors are overrepresented in the MSI group compared to the microsatellite stable (MSS) group, there is a substantial number of IS-High cases in the MSS group, indicating that there is a good number of MSS cases that are immunogenic. Patients with IS-High tumors had statistically significant prolonged survival than patients with IS-Low tumors despite their microsatellite status. The last major Immunoscore® study conducted by the Immunoscore® worldwide consortium, and led by the Society for Immunotherapy of Cancer (SITC) involved 23 pathology centers from 17 countries. This international study including more than 3800 stage I/II/III colon cancer patients aimed at promoting the Immunoscore® in routine clinical setting [1,2]. Although CD45RO was one of the markers used for Immunoscore assessment in previous studies, because of background staining and loss of antigenicity in stored sections, it was agreed to employ the combination of the two easiest membrane stains, CD3 and CD8 in two regions (CT and IM) for validation in standard clinical practice [9]. The primary endpoint of the study was reached, with significantly longer TTR for patients classified as IS-High in the training set (HR = 0.41 (CI95 %, [0.28–0.61]; p < 0.0001) and two independent validation sets. Importantly, Immunoscore® discriminated a subgroup of high-risk stage II patients. Immunoscore® was also able to predict DFS and OS. Those major results, beyond further validating Immunoscore® as a strong prognostic marker also demonstrated that the assay was quantitative, reproducible and robust through this multicentric study. Altogether, those results might lead the introduction of Immunoscore® into the cancer classification designated “TNM-I” (for TNM-Immune) and thereby help with therapeutic decision in clinical routine [9]. Immunoscore® Colon is available through HalioDx service laboratory, for research use only (RUO). By the end of the year, pathologists will have access to an in vitro diagnostic (IVD) assay in Europe, while a RUO solution will also be available in the rest of the World.
  8 in total

1.  The tumor microenvironment and Immunoscore are critical determinants of dissemination to distant metastasis.

Authors:  Bernhard Mlecnik; Gabriela Bindea; Amos Kirilovsky; Helen K Angell; Anna C Obenauf; Marie Tosolini; Sarah E Church; Pauline Maby; Angela Vasaturo; Mihaela Angelova; Tessa Fredriksen; Stéphanie Mauger; Maximilian Waldner; Anne Berger; Michael R Speicher; Franck Pagès; Viia Valge-Archer; Jérôme Galon
Journal:  Sci Transl Med       Date:  2016-02-24       Impact factor: 17.956

2.  Integrative Analyses of Colorectal Cancer Show Immunoscore Is a Stronger Predictor of Patient Survival Than Microsatellite Instability.

Authors:  Bernhard Mlecnik; Gabriela Bindea; Helen K Angell; Pauline Maby; Mihaela Angelova; David Tougeron; Sarah E Church; Lucie Lafontaine; Maria Fischer; Tessa Fredriksen; Maristella Sasso; Amélie M Bilocq; Amos Kirilovsky; Anna C Obenauf; Mohamad Hamieh; Anne Berger; Patrick Bruneval; Jean-Jacques Tuech; Jean-Christophe Sabourin; Florence Le Pessot; Jacques Mauillon; Arash Rafii; Pierre Laurent-Puig; Michael R Speicher; Zlatko Trajanoski; Pierre Michel; Richard Sesboüe; Thierry Frebourg; Franck Pagès; Viia Valge-Archer; Jean-Baptiste Latouche; Jérôme Galon
Journal:  Immunity       Date:  2016-03-15       Impact factor: 31.745

3.  Type, density, and location of immune cells within human colorectal tumors predict clinical outcome.

Authors:  Jérôme Galon; Anne Costes; Fatima Sanchez-Cabo; Amos Kirilovsky; Bernhard Mlecnik; Christine Lagorce-Pagès; Marie Tosolini; Matthieu Camus; Anne Berger; Philippe Wind; Franck Zinzindohoué; Patrick Bruneval; Paul-Henri Cugnenc; Zlatko Trajanoski; Wolf-Herman Fridman; Franck Pagès
Journal:  Science       Date:  2006-09-29       Impact factor: 47.728

Review 4.  The adaptive immunologic microenvironment in colorectal cancer: a novel perspective.

Authors:  Jérôme Galon; Wolf-Herman Fridman; Franck Pagès
Journal:  Cancer Res       Date:  2007-03-01       Impact factor: 12.701

5.  Histopathologic-based prognostic factors of colorectal cancers are associated with the state of the local immune reaction.

Authors:  Bernhard Mlecnik; Marie Tosolini; Amos Kirilovsky; Anne Berger; Gabriela Bindea; Tchao Meatchi; Patrick Bruneval; Zlatko Trajanoski; Wolf-Herman Fridman; Franck Pagès; Jérôme Galon
Journal:  J Clin Oncol       Date:  2011-01-18       Impact factor: 44.544

6.  In situ cytotoxic and memory T cells predict outcome in patients with early-stage colorectal cancer.

Authors:  Franck Pagès; Amos Kirilovsky; Bernhard Mlecnik; Martin Asslaber; Marie Tosolini; Gabriela Bindea; Christine Lagorce; Philippe Wind; Florence Marliot; Patrick Bruneval; Kurt Zatloukal; Zlatko Trajanoski; Anne Berger; Wolf-Herman Fridman; Jérôme Galon
Journal:  J Clin Oncol       Date:  2009-10-26       Impact factor: 44.544

Review 7.  Cancer classification using the Immunoscore: a worldwide task force.

Authors:  Jérôme Galon; Franck Pagès; Francesco M Marincola; Helen K Angell; Magdalena Thurin; Alessandro Lugli; Inti Zlobec; Anne Berger; Carlo Bifulco; Gerardo Botti; Fabiana Tatangelo; Cedrik M Britten; Sebastian Kreiter; Lotfi Chouchane; Paolo Delrio; Hartmann Arndt; Martin Asslaber; Michele Maio; Giuseppe V Masucci; Martin Mihm; Fernando Vidal-Vanaclocha; James P Allison; Sacha Gnjatic; Leif Hakansson; Christoph Huber; Harpreet Singh-Jasuja; Christian Ottensmeier; Heinz Zwierzina; Luigi Laghi; Fabio Grizzi; Pamela S Ohashi; Patricia A Shaw; Blaise A Clarke; Bradly G Wouters; Yutaka Kawakami; Shoichi Hazama; Kiyotaka Okuno; Ena Wang; Jill O'Donnell-Tormey; Christine Lagorce; Graham Pawelec; Michael I Nishimura; Robert Hawkins; Réjean Lapointe; Andreas Lundqvist; Samir N Khleif; Shuji Ogino; Peter Gibbs; Paul Waring; Noriyuki Sato; Toshihiko Torigoe; Kyogo Itoh; Prabhu S Patel; Shilin N Shukla; Richard Palmqvist; Iris D Nagtegaal; Yili Wang; Corrado D'Arrigo; Scott Kopetz; Frank A Sinicrope; Giorgio Trinchieri; Thomas F Gajewski; Paolo A Ascierto; Bernard A Fox
Journal:  J Transl Med       Date:  2012-10-03       Impact factor: 5.531

Review 8.  Towards the introduction of the 'Immunoscore' in the classification of malignant tumours.

Authors:  Jérôme Galon; Bernhard Mlecnik; Gabriela Bindea; Helen K Angell; Anne Berger; Christine Lagorce; Alessandro Lugli; Inti Zlobec; Arndt Hartmann; Carlo Bifulco; Iris D Nagtegaal; Richard Palmqvist; Giuseppe V Masucci; Gerardo Botti; Fabiana Tatangelo; Paolo Delrio; Michele Maio; Luigi Laghi; Fabio Grizzi; Martin Asslaber; Corrado D'Arrigo; Fernando Vidal-Vanaclocha; Eva Zavadova; Lotfi Chouchane; Pamela S Ohashi; Sara Hafezi-Bakhtiari; Bradly G Wouters; Michael Roehrl; Linh Nguyen; Yutaka Kawakami; Shoichi Hazama; Kiyotaka Okuno; Shuji Ogino; Peter Gibbs; Paul Waring; Noriyuki Sato; Toshihiko Torigoe; Kyogo Itoh; Prabhu S Patel; Shilin N Shukla; Yili Wang; Scott Kopetz; Frank A Sinicrope; Viorel Scripcariu; Paolo A Ascierto; Francesco M Marincola; Bernard A Fox; Franck Pagès
Journal:  J Pathol       Date:  2014-01       Impact factor: 7.996

  8 in total
  13 in total

Review 1.  Assessing Tumor-Infiltrating Lymphocytes in Solid Tumors: A Practical Review for Pathologists and Proposal for a Standardized Method from the International Immuno-Oncology Biomarkers Working Group: Part 2: TILs in Melanoma, Gastrointestinal Tract Carcinomas, Non-Small Cell Lung Carcinoma and Mesothelioma, Endometrial and Ovarian Carcinomas, Squamous Cell Carcinoma of the Head and Neck, Genitourinary Carcinomas, and Primary Brain Tumors.

Authors:  Shona Hendry; Roberto Salgado; Thomas Gevaert; Prudence A Russell; Tom John; Bibhusal Thapa; Michael Christie; Koen van de Vijver; M V Estrada; Paula I Gonzalez-Ericsson; Melinda Sanders; Benjamin Solomon; Cinzia Solinas; Gert G G M Van den Eynden; Yves Allory; Matthias Preusser; Johannes Hainfellner; Giancarlo Pruneri; Andrea Vingiani; Sandra Demaria; Fraser Symmans; Paolo Nuciforo; Laura Comerma; E A Thompson; Sunil Lakhani; Seong-Rim Kim; Stuart Schnitt; Cecile Colpaert; Christos Sotiriou; Stefan J Scherer; Michail Ignatiadis; Sunil Badve; Robert H Pierce; Giuseppe Viale; Nicolas Sirtaine; Frederique Penault-Llorca; Tomohagu Sugie; Susan Fineberg; Soonmyung Paik; Ashok Srinivasan; Andrea Richardson; Yihong Wang; Ewa Chmielik; Jane Brock; Douglas B Johnson; Justin Balko; Stephan Wienert; Veerle Bossuyt; Stefan Michiels; Nils Ternes; Nicole Burchardi; Stephen J Luen; Peter Savas; Frederick Klauschen; Peter H Watson; Brad H Nelson; Carmen Criscitiello; Sandra O'Toole; Denis Larsimont; Roland de Wind; Giuseppe Curigliano; Fabrice André; Magali Lacroix-Triki; Mark van de Vijver; Federico Rojo; Giuseppe Floris; Shahinaz Bedri; Joseph Sparano; David Rimm; Torsten Nielsen; Zuzana Kos; Stephen Hewitt; Baljit Singh; Gelareh Farshid; Sibylle Loibl; Kimberly H Allison; Nadine Tung; Sylvia Adams; Karen Willard-Gallo; Hugo M Horlings; Leena Gandhi; Andre Moreira; Fred Hirsch; Maria V Dieci; Maria Urbanowicz; Iva Brcic; Konstanty Korski; Fabien Gaire; Hartmut Koeppen; Amy Lo; Jennifer Giltnane; Marlon C Rebelatto; Keith E Steele; Jiping Zha; Kenneth Emancipator; Jonathan W Juco; Carsten Denkert; Jorge Reis-Filho; Sherene Loi; Stephen B Fox
Journal:  Adv Anat Pathol       Date:  2017-11       Impact factor: 3.875

2.  SITC cancer immunotherapy resource document: a compass in the land of biomarker discovery.

Authors:  Siwen Hu-Lieskovan; Srabani Bhaumik; Kavita Dhodapkar; Jean-Charles J B Grivel; Sumati Gupta; Brent A Hanks; Sylvia Janetzki; Thomas O Kleen; Yoshinobu Koguchi; Amanda W Lund; Cristina Maccalli; Yolanda D Mahnke; Ruslan D Novosiadly; Senthamil R Selvan; Tasha Sims; Yingdong Zhao; Holden T Maecker
Journal:  J Immunother Cancer       Date:  2020-12       Impact factor: 13.751

Review 3.  The Society for Immunotherapy of Cancer Biomarkers Task Force recommendations review.

Authors:  Lisa H Butterfield
Journal:  Semin Cancer Biol       Date:  2017-09-22       Impact factor: 15.707

Review 4.  Clinical correlates for immune checkpoint therapy: significance for CNS malignancies.

Authors:  Nivedita M Ratnam; Stephen C Frederico; Javier A Gonzalez; Mark R Gilbert
Journal:  Neurooncol Adv       Date:  2020-11-27

Review 5.  Beyond PD-L1 testing-emerging biomarkers for immunotherapy in non-small cell lung cancer.

Authors:  Khinh Ranh Voong; Josephine Feliciano; Daniel Becker; Benjamin Levy
Journal:  Ann Transl Med       Date:  2017-09

6.  A template to quantify the location and density of CD3 + and CD8 + tumor-infiltrating lymphocytes in colon cancer by digital pathology on whole slides for an objective, standardized immune score assessment.

Authors:  Dordi Lea; Martin Watson; Ivar Skaland; Hanne R Hagland; Melinda Lillesand; Einar Gudlaugsson; Kjetil Søreide
Journal:  Cancer Immunol Immunother       Date:  2021-01-13       Impact factor: 6.968

7.  Cancer Immunotherapy and Personalized Medicine: Emerging Technologies and Biomarker-Based Approaches.

Authors:  Laura Maciejko; Munisha Smalley; Aaron Goldman
Journal:  J Mol Biomark Diagn       Date:  2017-06-28

8.  Immunotherapy biomarkers 2016: overcoming the barriers.

Authors:  James L Gulley; Jay A Berzofsky; Marcus O Butler; Alessandra Cesano; Bernard A Fox; Sacha Gnjatic; Sylvia Janetzki; Shyam Kalavar; Vaios Karanikas; Samir N Khleif; Ilan Kirsch; Peter P Lee; Cristina Maccalli; Holden Maecker; Jeffrey Schlom; Barbara Seliger; Janet Siebert; David F Stroncek; Magdalena Thurin; Jianda Yuan; Lisa H Butterfield
Journal:  J Immunother Cancer       Date:  2017-03-21       Impact factor: 13.751

9.  Automatic discovery of image-based signatures for ipilimumab response prediction in malignant melanoma.

Authors:  Nathalie Harder; Ralf Schönmeyer; Katharina Nekolla; Armin Meier; Nicolas Brieu; Carolina Vanegas; Gabriele Madonna; Mariaelena Capone; Gerardo Botti; Paolo A Ascierto; Günter Schmidt
Journal:  Sci Rep       Date:  2019-05-15       Impact factor: 4.379

10.  Exome and immune cell score analyses reveal great variation within synchronous primary colorectal cancers.

Authors:  Ulrika A Hänninen; Erkki-Ville Wirta; Riku Katainen; Tomas Tanskanen; Jiri Hamberg; Minna Taipale; Jan Böhm; Laura Renkonen-Sinisalo; Anna Lepistö; Linda M Forsström; Esa Pitkänen; Kimmo Palin; Toni T Seppälä; Netta Mäkinen; Jukka-Pekka Mecklin; Lauri A Aaltonen
Journal:  Br J Cancer       Date:  2019-03-21       Impact factor: 7.640

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