Usefulness and robustness of Immunoscore for personalized management of cancer patients

Marliot, Florence; Pagès, Franck; Galon, Jérôme

doi:10.1080/2162402x.2020.1832324

Cited by 18 publications

(14 citation statements)

References 17 publications

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“…The analytical validation of IS has been demonstrated previously [ 20 , 25 ]. Immunoscore ® was deemed to be a robust, reproducible, quantitative, and standardized immune assay, with a high prognostic performance, independent of all of the prognostic markers currently used in clinical practice.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Immune Response Assessment in Colon Cancer by Immunoscore (Automated Digital Pathology) and Pathologist Visual Scoring

Boquet¹,

Kassambara²,

Lui³

et al. 2022

Cancers

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Adjunction of immune response into the TNM classification system improves the prediction of colon cancer (CC) prognosis. However, immune response measurements have not been used as robust biomarkers of pathology in clinical practice until the introduction of Immunoscore (IS), a standardized assay based on automated artificial intelligence assisted digital pathology. The strong prognostic impact of the immune response, as assessed by IS, has been widely validated and IS can help to refine treatment decision making in early CC. In this study, we compared pathologist visual scoring to IS. Four pathologists evaluated tumor specimens from 50 early-stage CC patients and classified the CD3+ and CD8+ T-cell densities at the tumor site (T-score) into 2 (High/Low) categories. Individual and overall pathologist scoring of immune response (before and after training for immune response assessment) were compared to the reference IS (High/Low). Pathologists’ disagreement with the reference IS was observed in almost half of the cases (48%) and training only slightly improved the accuracy of pathologists’ classification. Agreement among pathologists was minimal with a Kappa of 0.34 and 0.57 before and after training, respectively. The standardized IS assay outperformed expert pathologist assessment in the clinical setting.

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Section: Introductionmentioning

confidence: 99%

Comparison of Immune Response Assessment in Colon Cancer by Immunoscore (Automated Digital Pathology) and Pathologist Visual Scoring

Boquet¹,

Kassambara²,

Lui³

et al. 2022

Cancers

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“…Tumor immune microenvironment is one of the research hotspots in recent years ( 28 , 29 ). The concept of Immunoscore provides a new direction and a strong guarantee for the evaluation of various tumors ( 30 – 33 ). Increasing studies have shown that the density of CD3 + and CD8 + lymphocyte populations in the tumor microenvironment could effectively predict the recurrence and metastasis of GC and complement the TNM staging system ( 34 , 35 ).…”

Section: Discussionmentioning

confidence: 99%

Construction and Validation of Convenient Clinicopathologic Signatures for Predicting the Prognosis of Stage I-III Gastric Cancer

et al. 2022

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BackgroundPatients with stage I-III gastric cancer (GC) undergoing R0 radical resection display extremely different prognoses. How to discriminate high-risk patients with poor survival conveniently is a clinical conundrum to be solved urgently.MethodsPatients with stage I-III GC from 2010 to 2016 were included in our study. The associations of clinicopathological features with disease-free survival (DFS) and overall survival (OS) were examined via Cox proportional hazard model. Nomograms were developed which systematically integrated prognosis-related features. Kaplan–Meier survival analysis was performed to compare DFS and OS among groups. The results were then externally validated by The Sixth Affiliated Hospital, Sun Yat-sen University.ResultsA total of 585 and 410 patients were included in the discovery cohort and the validation cohort, respectively. T stage, N stage, lymphatic/vascular/nerve infiltration, preoperative CEA, and CA19-9 were independent prognostic factors (P < 0.05). Two prognostic signatures with a concordance index (C-index) of 0.7502 for DFS and 0.7341 for OS were developed based on the nomograms. The 3-year and 5-year calibration curves showed a perfect correlation between predicted and observed outcomes. Patients were divided into three risk groups (low, intermediate, high), and distinct differences were noticed (p < 0.001). Similar results were achieved in the validation cohort. Notably, a free website was constructed based on our signatures to predict the recurrence risk and survival time of patients with stage I-III GC.ConclusionsThe signatures demonstrate the powerful ability to conveniently identify distinct subpopulations, which may provide significant suggestions for individual follow-up and adjuvant therapy.

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“…Tumor immune microenvironment is one of the research hotspots in recent years (28,29). The concept of immunoscore provides a new direction and a strong guarantee for the evaluation of various tumors (30)(31)(32)(33). Increasing studies have shown that the density of CD3 + and CD8 + lymphocyte populations in the tumor microenvironment could effectively predict the recurrence and metastasis of GC and complemented the TNM staging system (34,35).…”

Section: Discussionmentioning

confidence: 99%

Construction and Validation of Convenient Clinicopathologic Signatures for Predicting the Prognosis of Stage I-III Gastric Cancer

You¹,

Cai²,

Sheng³

et al. 2021

Preprint

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BackgroundPatients with stage I-III gastric cancer (GC) undergoing R0 radical resection display extremely different prognosis. How to discriminate high-risk patients with poor survival conveniently is a clinical conundrum to be solved urgently.MethodsPatients with stage I-III GC from 2010 to 2016 at Shanghai Jiao Tong University Affiliated Sixth People’s Hospital were included in our study. The associations of clinicopathological features with disease-free survival (DFS) and overall survival (OS) were examined via Cox proportional hazard model. Nomograms were developed which systematically integrated prognosis-related features. Kaplan–Meier survival analysis was performed to compare DFS and OS among groups. The results were then externally validated by The Sixth Affiliated Hospital, Sun Yat-sen University.ResultsA total of 585 and 410 patients were included in the discovery cohort and in the validation cohort. Multivariable analysis demonstrated that T stage, N stage, lymphatic/vascular/nerve infiltration, preoperative CEA and CA199 were independent prognostic factors (P < 0.05). The 3-year and 5-year calibration curves based on the nomograms showed perfect correlation between predicted and observed outcomes. Distinct differences were noticed in the survival of different risk groups (p < 0.001). Patients with low risk signature had a 5-year rate of 84.0% for DFS and 83.0% for OS, whereas high risk signature had the worst 5-year rate (only 35.0% for DFS and 24.0% for OS). Similar results were achieved in validation cohort.ConclusionsThe signatures based on clinicopathologic features demonstrate the powerful ability to conveniently identify distinct subpopulations, which may provide significant suggestions for individual follow-up and adjuvant therapy.

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Usefulness and robustness of Immunoscore for personalized management of cancer patients

Cited by 18 publications

References 17 publications

Comparison of Immune Response Assessment in Colon Cancer by Immunoscore (Automated Digital Pathology) and Pathologist Visual Scoring

Comparison of Immune Response Assessment in Colon Cancer by Immunoscore (Automated Digital Pathology) and Pathologist Visual Scoring

Construction and Validation of Convenient Clinicopathologic Signatures for Predicting the Prognosis of Stage I-III Gastric Cancer

Construction and Validation of Convenient Clinicopathologic Signatures for Predicting the Prognosis of Stage I-III Gastric Cancer

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