Local Inflammatory Response Can Predict Clinical Outcome in Patients with Curatively Resected Stage-IIB Colon Cancer: An Advanced Methodological Study

  • Mehmet ZenginEmail author
Original Article



Although local inflammatory response (LIR) is a reliable survival marker in colon cancers (CCs), there is no consensus on its use in daily practice. We investigated the prognostic value of LIR in a highly homogeneous population with a well-designed methodology.


Eighty stage-IIB CC patients operated between 2002 and 2012 were included in the study. Standardization was investigated for extra-biopsy evaluation methods (magnification, staining, and counting). Model A was used for intra-biopsy evaluation methods (block, section, and focus). So, this study makes important contributions to the standardization of pathological evaluations.


In method 1, the following analyzes showed more successful results for LIR: relationship with prognostic factors [tumour deposits (p=0.017), Crohn’s-like reaction (p=0.019), advanced grade, (p=0.012), positive surgical margin (p=0.019), perineural invasion (p=0.025), mismatch repair proteins-proficiency (p=0.031)], reproducibility of the study (Kappa=0.49–0.73, Intra-class correlation=0.442–0.724), and correlation of estimates (r=0.704). The cut-off value was also quite useful (area of under ROC=0.820 [0.694-0.920]). In univariate analysis, low LIR was related to poor overall survival (OS; p<0.001) and poor relapse-free survival (RFS, p=0.001) . Multivariate analysis confirmed that low LIR is an independent poor survival marker for OS (Hazard Ratio [HR]=1.32 [1.08-1.61, p=0.005) and RFS (HR=1.50 [1.22-1.85], p<0.001).


Our results showed that low LIR had an independent prognostic significance in stage -IIB CCs. We also recommend using model A and method 1 for successful results and standardization.


Local inflammatory response tumour biomarkers colon cancers stage -IIB 



We would like to thank the members of Kırıkkale University, Department of Pathology and Internal Medicine for their support and participation. All persons who have contributed to the paper approves for publication of this research.


AJCC: American Joint Cancer Committee,LIR: Local inflammatory response, CC: Colorectal cancer, H&E: Hematoxylin and eosin, HPF: High-power field,SD: Standard deviation, IHC: Immunohistochemistry,CI: Confidence interval, SD: Standard deviation, ICC: Intra-Class Correlation Coefficient, HR: Hazard ratio, K: Kappa, OS: Overall survival, RFS: Relapse-free survival, MSI: Microsatellite instability, MMR: Mismatch repair proteins, Method 1: Using the ‘x20 objektive&IHC&quantitative’, Model A: Using the ‘deeply invasive blocks&hot-spot area&invasive margin’.


The author is not associated with any organization or financial involvement that has a financial interest in the issue of the material discussed in the article.

Compliance with Ethical Standard

Conflicts of Interest

The author does not report a conflict of interest.

Supplementary material

12253_2019_758_Fig4_ESM.png (4.5 mb)
Supplementary Fig. S1

(PNG 4644 kb)

12253_2019_758_MOESM1_ESM.tif (4.2 mb)
Hıgh Resolutıon İmage (TIF 4290 kb)
12253_2019_758_MOESM2_ESM.pdf (429 kb)
Supplementary Table S1 (PDF 429 kb)


  1. 1.
    Karim S, Brennan K, Nanji S et al (2017). Association between prognosis and tumor laterality in early-stage colon cancer. JAMA Oncol 2017; 3: 1386-92CrossRefGoogle Scholar
  2. 2.
    Cunningham D, Atkin W, Lenz HJ et al (2010) Colorectal cancer. Lancet 375:1030–1047CrossRefGoogle Scholar
  3. 3.
    Quasar Collaborative Group, Gray R, Barnwell J et al (2007) Adjuvant chemotherapy versus observation in patients with colorectal cancer: a randomised study. Lancet 370:2020–2029CrossRefGoogle Scholar
  4. 4.
    Benson AB 3rd, Schrag D, Somerfield MR et al (2004) American Society of Clinical Oncology recommendations on adjuvant chemotherapy for stage II colon cancer. J Clin Oncol 22:3408–3419CrossRefGoogle Scholar
  5. 5.
    Colotta F, Allavena P, Sica A et al (2009). Cancer-related inflammation, the seventh hallmark of cancer: links to genetic instability. Carcinogenesis 30:1073–1081CrossRefGoogle Scholar
  6. 6.
    Roxburgh CS, McMillan DC (2010) Role of systemic inflammatory response in predicting survival in patients with primary operable cancer. Future Oncol 6:149–163CrossRefGoogle Scholar
  7. 7.
    Mei Z, Liu Y, Liu C et al (2014) Tumour-infiltrating inflammation and prognosis in colorectal cancer: systematic review and meta-analysis. Br J Cancer 110:1595–1605CrossRefGoogle Scholar
  8. 8.
    Leitch EF, Chakrabarti M, Crozier JE et al (2007) Comparison of the prognostic value of selected markers of the systemic inflammatory response in patients with colorectal cancer. Br J Cancer 97:1266–1270CrossRefGoogle Scholar
  9. 9.
    Menon AG, Janssen-van Rhijn CM, Morreau H et al (2004) Immune system and prognosis in colorectal cancer: a detailed immunohistochemical analysis. Lab Invest 84:493–501CrossRefGoogle Scholar
  10. 10.
    Ishizuka M, Nagata H, Takagi K et al (2009) Influence of inflammation-based prognostic score on mortality of patients undergoing chemotherapy for far advanced or recurrent unresectable colorectal cancer. Ann Surg 250:268–272CrossRefGoogle Scholar
  11. 11.
    Dong ZY, Wu SP, Liao RQ et al (2016) Potential biomarker for checkpoint blockade immunotherapy and treatment strategy. Tumour Biol 37:4251–4261CrossRefGoogle Scholar
  12. 12.
    Zengin M (2019) Prognostic role of Tumor-infiltrating T lymphocytes in stage IIA (T3N0) colon cancer: A broad methodological study in a fairly homogeneous population. Annals of Diagnostic Pathology 41:69–78CrossRefGoogle Scholar
  13. 13.
    McShane LM, Altman DG, Sauerbrei W et al (2005) REporting recommendations for tumour MARKer prognostic studies (REMARK). Br J Cancer 93:387–391CrossRefGoogle Scholar
  14. 14.
    Sobin LH, Compton CC (2010). TNM seventh edition: what's new, what's changed: communication from the International Union Against Cancer and the American Joint Committee on Cancer. Cancer 116: 5336-9.CrossRefGoogle Scholar
  15. 15.
    Kamarudin AN, Cox T, Kolamunnage-Dona R (2017) Time-dependent ROC curve analysis in medical research: current methods and applications. BMC Med Res Methodol 17:53CrossRefGoogle Scholar
  16. 16.
    McGraw KO, Wong SP (1996) Forming inferences about some intraclass correlation coefficients. Psychol Methods 1:30–46CrossRefGoogle Scholar
  17. 17.
    Landis JR, Koch GG (1977) The measurement of observer agreement for categorical data. Biometrics 33:159–174CrossRefGoogle Scholar
  18. 18.
    Nosho K, Baba Y, Tanaka N et al (2010) Tumour-infiltrating T-cell subsets, molecular changes in colorectal cancer, and prognosis: cohort study and literature review. J Pathol 222:350–366CrossRefGoogle Scholar
  19. 19.
    Galon J, Costes A, Sanchez-Cabo F et al (2006) Type, density, and location of immune cells within human colorectal tumors predict clinical outcome. Science 313:1960–1964CrossRefGoogle Scholar
  20. 20.
    Ropponen KM, Eskelinen MJ, Lipponen PK et al (1997) Prognostic value of tumour-infiltrating lymphocytes (TILs) in colorectal cancer. J Pathol 182:318–324CrossRefGoogle Scholar
  21. 21.
    Pages F, Berger A, Camus M et al (2005) Effector memory T cells, early metastasis, and survival in colorectal cancer. N Engl J Med 353:2654–2666CrossRefGoogle Scholar
  22. 22.
    Laghi L, Bianchi P, Miranda E et al (2009) CD3+ cells at the invasive margin of deeply invading (pT3-T4) colorectal cancer and risk of post-surgical metastasis: a longitudinal study. Lancet Oncol 10:877–884CrossRefGoogle Scholar
  23. 23.
    Dahlin AM, Henriksson ML, Van Guelpen B et al (2011) Colorectal cancer prognosis depends on T-cell infiltration and molecular characteristics of the tumor. Mod Pathol 24:671–682CrossRefGoogle Scholar
  24. 24.
    Foxtrot CG (2012) Feasibility of preoperative chemotherapy for locally advanced, operable colon cancer: the pilot phase of a randomised controlled trial. Lancet Oncol 13:1152–1160CrossRefGoogle Scholar
  25. 25.
    Prall F, Duhrkop T, Weirich V et al (2004) Prognostic role of CD8+ tumor-infiltrating lymphocytes in stage III colorectal cancer with and without microsatellite instability. Hum Pathol 35:808–816CrossRefGoogle Scholar
  26. 26.
    Klintrup K, Makinen JM, Kauppila S et al (2005) Inflammation and prognosis in colorectal cancer. Eur J Cancer 41:2645–2654CrossRefGoogle Scholar
  27. 27.
    Nagtegaal ID, Marijnen CA, Kranenbarg EK et al (2001) Local and distant recurrences in rectal cancer patients are predicted by the nonspecific immune response; specific immune response has only a systemic effect: a histopathological and immunohistochemical study. BMC Cancer 1:7CrossRefGoogle Scholar
  28. 28.
    Berntsson J, Nodin B, Eberhard J et al (2016) Prognostic impact of tumour-infiltrating B cells and plasma cells in colorectal cancer. Int J Cancer. 139(5):1129–1139CrossRefGoogle Scholar
  29. 29.
    Guidoboni M, Gafa R, Viel A et al (2001) Microsatellite instability and high content of activated cytotoxic lymphocytes identify colon cancer patients with a favorable prognosis. Am J Pathol 159:297–304CrossRefGoogle Scholar
  30. 30.
    Turksma AW, Coupe VM, Shamier MC et al (2016) Extent and location of tumor-infiltrating lymphocytes in microsatellite-stable colon cancer predict outcome to adjuvant active specific immunotherapy. Clin Cancer Res 22:346–356CrossRefGoogle Scholar
  31. 31.
    Galon J, Pages F, Marincola FM et al (2012) Cancer classification using the Immunoscore: a worldwide task force. J Transl Med 10:205CrossRefGoogle Scholar

Copyright information

© Arányi Lajos Foundation 2019

Authors and Affiliations

  1. 1.Kırıkkale UniversityDepartment of PathologyKırıkkaleTurkey

Personalised recommendations