Contribution of Immunoscore and Molecular Features to Survival Prediction in Stage III Colon Cancer

Abstract Background The American Joint Committee on Cancer staging and other prognostic tools fail to account for stage-independent variability in outcome. We developed a prognostic classifier adding Immunoscore to clinicopathological and molecular features in patients with stage III colon cancer. Methods Patient (n = 559) data from the FOLFOX arm of adjuvant trial NCCTG N0147 were used to construct Cox models for predicting disease-free survival (DFS). Variables included age, sex, T stage, positive lymph nodes (+LNs), N stage, performance status, histologic grade, sidedness, KRAS/BRAF, mismatch repair, and Immunoscore (CD3+, CD8+ T-cell densities). After determining optimal functional form (continuous or categorical) and within Cox models, backward selection was performed to analyze all variables as candidate predictors. All statistical tests were two-sided. Results Poorer DFS was found for tumors that were T4 vs T3 (hazard ratio [HR] = 1.76, 95% confidence interval [CI] = 1.19 to 2.60; P = .004), right- vs left-sided (HR = 1.52, 95% CI = 1.14 to 2.04; P = .005), BRAF V600E (HR = 1.74, 95% CI = 1.26 to 2.40; P < .001), mutant KRAS (HR = 1.66, 95% CI = 1.08 to 2.55; P = .02), and low vs high Immunoscore (HR = 1.69, 95% CI = 1.22 to 2.33; P = .001) (all P < .02). Increasing numbers of +LNs and lower continuous Immunoscore were associated with poorer DFS that achieved significance (both Ps< .0001). After number of +LNs, T stage, and BRAF/KRAS, Immunoscore was the most informative predictor of DFS shown multivariately. Among T1–3 N1 tumors, Immunoscore was the only variable associated with DFS that achieved statistical significance. A nomogram was generated to determine the likelihood of being recurrence-free at 3 years. Conclusions The Immunoscore can enhance the accuracy of survival prediction among patients with stage III colon cancer.

[1]  A. Jemal,et al.  Cancer statistics, 2019 , 2019, CA: a cancer journal for clinicians.

[2]  F. Marincola,et al.  International validation of the consensus Immunoscore for the classification of colon cancer: a prognostic and accuracy study , 2018, The Lancet.

[3]  M. Weiser,et al.  AJCC 8th Edition: Colorectal Cancer , 2018, Annals of Surgical Oncology.

[4]  J. Meyerhardt,et al.  NCCN Guidelines Insights: Colon Cancer, Version 2.2018. , 2018, Journal of the National Comprehensive Cancer Network : JNCCN.

[5]  R. Labianca,et al.  Duration of Adjuvant Chemotherapy for Stage III Colon Cancer , 2018, The New England journal of medicine.

[6]  G. Maddern,et al.  Outcomes for metastatic colorectal cancer (mCRC) based on microsatellite instability. , 2018 .

[7]  Shu Zheng,et al.  Multi-omics Approach Reveals Distinct Differences in Left- and Right-Sided Colon Cancer , 2017, Molecular Cancer Research.

[8]  N. Kemeny,et al.  Clinical Features and Outcomes of Patients with Colorectal Cancers Harboring NRAS Mutations , 2017, Clinical Cancer Research.

[9]  Stephen B Gruber,et al.  Tumor-Infiltrating Lymphocytes, Crohn's-Like Lymphoid Reaction, and Survival From Colorectal Cancer. , 2016, Journal of the National Cancer Institute.

[10]  R. Maruyama,et al.  Association of Fusobacterium nucleatum with immunity and molecular alterations in colorectal cancer. , 2016, World journal of gastroenterology.

[11]  C. Huttenhower,et al.  Fusobacterium nucleatum and T Cells in Colorectal Carcinoma. , 2015, JAMA oncology.

[12]  Daniel J Sargent,et al.  ACCENT-based web calculators to predict recurrence and overall survival in stage III colon cancer. , 2014, Journal of the National Cancer Institute.

[13]  F. Marincola,et al.  Towards the introduction of the ‘Immunoscore’ in the classification of malignant tumours , 2013, The Journal of pathology.

[14]  Z. Trajanoski,et al.  Spatiotemporal dynamics of intratumoral immune cells reveal the immune landscape in human cancer. , 2013, Immunity.

[15]  D. Sargent,et al.  Prognostic impact of deficient DNA mismatch repair in patients with stage III colon cancer from a randomized trial of FOLFOX-based adjuvant chemotherapy. , 2013, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[16]  R W Wilkinson,et al.  Digital pattern recognition-based image analysis quantifies immune infiltrates in distinct tissue regions of colorectal cancer and identifies a metastatic phenotype , 2013, British Journal of Cancer.

[17]  F. Marincola,et al.  The continuum of cancer immunosurveillance: prognostic, predictive, and mechanistic signatures. , 2013, Immunity.

[18]  D. Sargent,et al.  Effect of oxaliplatin, fluorouracil, and leucovorin with or without cetuximab on survival among patients with resected stage III colon cancer: a randomized trial. , 2012, JAMA.

[19]  I. Nagtegaal,et al.  Has the new TNM classification for colorectal cancer improved care? , 2012, Nature Reviews Clinical Oncology.

[20]  M Buyse,et al.  Two or three year disease-free survival (DFS) as a primary end-point in stage III adjuvant colon cancer trials with fluoropyrimidines with or without oxaliplatin or irinotecan: data from 12,676 patients from MOSAIC, X-ACT, PETACC-3, C-06, C-07 and C89803. , 2011, European journal of cancer.

[21]  J. Vincent,et al.  5-Fluorouracil selectively kills tumor-associated myeloid-derived suppressor cells resulting in enhanced T cell-dependent antitumor immunity. , 2010, Cancer research.

[22]  Z. Trajanoski,et al.  Biomolecular network reconstruction identifies T-cell homing factors associated with survival in colorectal cancer. , 2010, Gastroenterology.

[23]  Daniel J Sargent,et al.  End points for colon cancer adjuvant trials: observations and recommendations based on individual patient data from 20,898 patients enrolled onto 18 randomized trials from the ACCENT Group. , 2007, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[24]  Z. Trajanoski,et al.  Type, Density, and Location of Immune Cells Within Human Colorectal Tumors Predict Clinical Outcome , 2006, Science.

[25]  Z. Trajanoski,et al.  Effector memory T cells, early metastasis, and survival in colorectal cancer. , 2005, The New England journal of medicine.

[26]  C. Ostwald,et al.  Prognostic role of CD8+ tumor-infiltrating lymphocytes in stage III colorectal cancer with and without microsatellite instability. , 2004, Human pathology.

[27]  Sunil J Rao,et al.  Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis , 2003 .

[28]  K. Kinzler,et al.  Tumorigenesis: RAF/RAS oncogenes and mismatch-repair status , 2002, Nature.

[29]  H Nagura,et al.  CD8+ T cells infiltrated within cancer cell nests as a prognostic factor in human colorectal cancer. , 1998, Cancer research.

[30]  J. Meyerhardt,et al.  Colon Cancer , Version 2 . 2018 Featured Updates to the NCCN Guidelines , 2018 .

[31]  P. Grambsch,et al.  Goodness-of-fit and diagnostics for proportional hazards regression models. , 1995, Cancer treatment and research.

[32]  N. Dubrawsky Cancer statistics , 1989, CA: a cancer journal for clinicians.