Clinical and Translational Oncology

, Volume 17, Issue 4, pp 330–338 | Cite as

A 50-gene signature is a novel scoring system for tumor-infiltrating immune cells with strong correlation with clinical outcome of stage I/II non-small cell lung cancer

  • S. Hernández-Prieto
  • A. Romera
  • M. Ferrer
  • J. L. Subiza
  • J. A. López-Asenjo
  • J. R. Jarabo
  • A. M. Gómez
  • Elena M. Molina
  • J. Puente
  • J. L. González-Larriba
  • F. Hernando
  • B. Pérez-VillamilEmail author
  • E. Díaz-Rubio
  • J. Sanz-OrtegaEmail author
Research Article



To identify a novel system for scoring intratumoral immune response that can improve prognosis and therapy decisions in early stage non-small cell lung cancer (NSCLC).


Eighty-four completely resected stage I/II NSCLC without adjuvant therapy were classified by expression profiling using whole genome microarrays. An external cohort of 162 tumors was used to validate the results. Immune cells present in tumor microenvironment were evaluated semiquantitatively by CD20, CD79, CD3, CD8, CD4 and CD57 immunostaining. Univariate and multivariate analyses of variables associated with recurrence-free survival were performed.


Initial molecular classification identified three clusters, one with significantly better RFS. A reduced two-subgroup classification and a 50-gene predictor were built and validated in an external dataset: high and low risk of recurrence patients (HR = 3.44; p = 0.001). Analysis of the predictor´s genes showed that the vast majority were related to a B/plasma cell immune response overexpressed in the low-risk subgroup. The predictor includes genes coding for unique B lineage-specific genes, functional elements or other genes that, although non-restricted to this lineage, have strong influence on B-cell homeostasis. Immunostains confirmed increased B-cells in the low-risk subgroup. Gene signature (p < 0.0001) and CD20 (p < 0.05) were predictors for RFS, while CD79 and K-RAS mutations showed a tendency.


Favorable prognosis in completely resected NSCLC is determined by a B-cell-mediated immune response. It can be differently scored by a 50-gene expression profile or by CD20 immunostaining. That prognosis information not reflected by traditional classifications may become a new tool for determining individualized adjuvant therapies.


Gene expression Molecular classification Immune response Non-small cell lung cancer Early stages Relapse-free survival 



We thank Dr. Richard Simon for his kind suggestions. We thank Dr. Paul Roepman and Nico van Zandwijk for gently providing us with their microarray and patient’s data. We thank Biobank of IDISSC as a sample bio-repository. This study has been funded by FIS, INMUNOTHERCAN-CM, S2010/BMD-2326 and RTICC-Instituto Salud Carlos III ref 06/0020/0021.

Conflict of interest

All authors state that there is no conflict of interest.

Supplementary material

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Supplementary material 1 (PPT 93 kb)
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Supplementary material 4 (PDF 47 kb)
12094_2014_1235_MOESM5_ESM.xls (20 kb)
Supplementary material 5 (XLS 20 kb)


  1. 1.
    Siegel R, Naishadham D, Jemal A. Cancer statistics, 2012. CA Cancer J Clin. 2012;62(1):10–29.CrossRefPubMedGoogle Scholar
  2. 2.
    Vallières E, Shepherd FA, Crowley J, Van Houtte P, Postmus PE, Carney D, et al. The IASLC Lung cancer staging project: proposals regarding the relevance of TNM in the pathologic staging of NSCLC in the forthcoming (seventh) edition of the TNM classification for lung cancer. J Thorac Oncol. 2009;4(9):1049–59.CrossRefPubMedGoogle Scholar
  3. 3.
    Edge SB, Byrd DR, Compton CC, Fritz AG, Greene FL, Trotti A et al. eds.: AJCC cancer staging manual. 7th ed. New York: Springer; 2010. p. 253–704.Google Scholar
  4. 4.
    Agulló-Ortuño MT, López-Ríos F, Paz-Ares L. Lung cancer genomic signatures. J Thorac Oncol. 2010;5(10):1673–91.CrossRefPubMedGoogle Scholar
  5. 5.
    Takeuchi T, Tomida S, Yatabe Y, Kosaka T, Osada H, Yanagisawa K, et al. Expression profile-defined classification of lung adenocarcinoma shows close relationship with underlying major genetic changes and clinicopathologic behaviors. J Clin Oncol. 2006;24:1679–88.CrossRefPubMedGoogle Scholar
  6. 6.
    Sun Z, Wigle DA, Yang P. Non-overlapping and non-cell-type-specific gene expression signatures predict lung cancer survival. J Clin Oncol. 2008;26(6):877–83.CrossRefPubMedGoogle Scholar
  7. 7.
    Zhu CQ, Ding K, Strumpf D, Weir BA, Meyerson M, Pennell N, et al. Prognostic and predictive gene signature for adjuvant chemotherapy in resected NSCLC. J Clin Oncol. 2010;28(29):4417–24.CrossRefPubMedCentralPubMedGoogle Scholar
  8. 8.
    Lu Y, Lemon W, Liu P-Y, Yi Y, Morrison C, Yang P, et al. A gene expression signature predicts survival of patients with stage I NSCLC. PLoS Med. 2006;3(12):e467.CrossRefPubMedCentralPubMedGoogle Scholar
  9. 9.
    Roepman P, Jassem J, Smit EF, Muley T, Niklinski J, van de Velde T, et al. An immune response enriched 72-gene prognostic profile for early-stage NSCLC. Clin Cancer Res. 2009;15(1):284–90.CrossRefPubMedGoogle Scholar
  10. 10.
    Zhu CQ, Pintilie M, John T, Strumpf D, Shepherd FA, Der SD, et al. Understanding prognostic gene expression signatures in lung cancer. Clin Lung Cancer. 2009;10(5):331–40.CrossRefPubMedGoogle Scholar
  11. 11.
    Lau SK, Boutros PC, Pintilie M, Blackhall FH, Zhu CQ, Strumpf D, et al. Three-gene prognostic classifier for early-stage NSCLC. J Clin Oncol. 2007;25:5562–9.CrossRefPubMedGoogle Scholar
  12. 12.
    Neumann J, Feuerhake F, Kayser G, Wiech T, Aumann K, Passlick B, et al. Gene expression profiles of lung adenocarcinoma linked to histopathological grading and survival but not to EGF-R status: a microarray study. BMC Cancer. 2010;10:77.CrossRefPubMedCentralPubMedGoogle Scholar
  13. 13.
    Hou J, Aerts J, den Hamer B, van Ijcken W, den Bakker M, Riegmanet P et al. Gene expression-based classification of NSCLC and survival prediction. PloS One 2010; 5(4): e10312.Google Scholar
  14. 14.
    Bryant CM, Albertus DL, Kim S, Chen G, Brambilla C, Guedj M et al. Clinically relevant characterization of lung adenocarcinoma subtypes based on cellular pathways: an international validation study. PLoS One 2010;22; 5(7):e11712.Google Scholar
  15. 15.
    Wan YW, Sabbagh E, Raese R, Qian Y, Luo D, Denvir J et al. Hybrid models identified a 12-gene signature for lung cancer prognosis and chemoresponse prediction. PLoS One 2010;17;5(8):e12222.Google Scholar
  16. 16.
    Zhu CQ, Strumpf D, Li CY, Li Q, Liu N, Der S, et al. Prognostic gene expression signature for SCC of lung. Clin Cancer Res. 2010;16:5038.CrossRefPubMedGoogle Scholar
  17. 17.
    Kratz JR, He J, Van Den Eeden SK, Zhu ZH, Gao W, Pham PT, et al. A practical molecular assay to predict survival in resected non-squamous, NSCLC: development and international validation studies. Lancet. 2012;379:823–32.CrossRefPubMedCentralPubMedGoogle Scholar
  18. 18.
    Perez-Villamil B, Romera-Lopez A, Hernandez-Prieto S, Lopez Campos G, Calles A, Sanz-Ortega J, et al. Colon cancer molecular subtypes identified by expression profiling and associated to stroma, mucinous type and different clinical behavior. BMC Cancer. 2012;12:260.CrossRefPubMedCentralPubMedGoogle Scholar
  19. 19.
    Benito M, Parker J, Du Q, Wu J, Xiang D, Perou CM, et al. Adjustment of systematic microarray data bases. Bioinformatics. 2003;20(1):105–14.CrossRefGoogle Scholar
  20. 20.
    Tibshirani R, Hastie T, Narasimhan B, Chu G. Diagnosis of multiple cancer types by shrunken centroids of gene expression. Proc Natl Acad Sci USA. 2002;99(10):6567–72.CrossRefPubMedCentralPubMedGoogle Scholar
  21. 21.
    Mascaux C, Iannino N, Martin B, Paesmans M, Berghmans T, Dusart M et al. The role of RAS oncogene in survival of patients with lung cancer: a systematic review of the literature with meta-analysis. Br J Cancer 2005;92:131–135.Google Scholar
  22. 22.
    Subramanian J, Simon R. Gene expression-based prognostic signatures in lung cancer: ready for clinical use? J Natl Cancer Inst. 2010;102:464–74.CrossRefPubMedCentralPubMedGoogle Scholar
  23. 23.
    Dupuy A, Simon RM. Critical review of published microarray studies for cancer outcome and guidelines on statistical analysis and reporting. J Natl Cancer Inst. 2007;99(2):147–57.CrossRefPubMedGoogle Scholar
  24. 24.
    Perez-Andres M, Paiva B, Nieto WG, Caraux J, Schmitz CA, Almeida J, et al. Human peripheral blood B-cell compartments: a crossroad in B-cell traffic. Cytometry B Clin Cytom. 2010;78B(Suppl. 1):S47–60.CrossRefGoogle Scholar
  25. 25.
    Tangye SG, Good KL. Human IgM+ CD27+ B cells: memory B cells or “memory” B cells? J Immunol. 2007;179(1):13–9.CrossRefPubMedGoogle Scholar
  26. 26.
    White E. The pims and outs of survival signaling: role for the Pim-2 protein kinase in the suppression of apoptosis by cytokines. Genes Dev. 2003;17(15):1813–6.CrossRefPubMedGoogle Scholar
  27. 27.
    Asano J, Nakano A, Oda A, Amou H, Hiasa M, Takeuchi K et al. The serine/threonine kinase Pim-2 is a novel anti-apoptotic mediator in myeloma cells. Leukemia 2011;25(7):1182–8.Google Scholar
  28. 28.
    Trinidad EM, Ballesteros M, Zuloaga J, Zapata A, Alonso-Colmenar LM. An impaired transendothelial migration potential of chronic lymphocytic leukemia (CLL) cells can be linked to ephrin-A4 expression. Blood. 2009;114(24):5081–90.CrossRefPubMedGoogle Scholar
  29. 29.
    Shapiro MJ, Nguyen CT, Aghajanian H, Zhang W, Shapiro VS. Negative regulation of TCR signaling by linker for activation of X cells via phosphotyrosine-dependent and -independent mechanisms. J Immunology. 2008;181:7055–61.CrossRefGoogle Scholar
  30. 30.
    Zikos AD, Donnenberg RJ, Landreneau JD, Luketich JD, Donnenberg VS. Lung T-cell subset composition at the time of surgical resection is a prognostic indicator in NSCLC. Cancer Immunol Immunother. 2011;60:819–27.CrossRefPubMedCentralPubMedGoogle Scholar
  31. 31.
    Hagn M, Sontheimer K, Dahlke K, Brueggemann S, Kaltenmeier C, Beyer T, et al. Human B cells differentiate into granzyme B-secreting cytotoxic B lymphocytes upon incomplete T-cell help. Immunol Cell Biol. 2012;90(4):457–67.CrossRefPubMedGoogle Scholar
  32. 32.
    Chen H-Y, Yu S-L, Chen C-H, Chang GC, Chen CY, Yuan A, et al. A five gene signature and clinical outcome in NSCLC. N Engl J Med. 2007;356:11–20.CrossRefPubMedGoogle Scholar
  33. 33.
    Mahabeleshwar GH, Das R, Kundu GC. Tyrosine kinase, p56lck-induced cell motility, and urokinase-type plasminogen activator secretion involve activation of EGFR/extracellular signal regulated kinase pathways. J BiolChem. 2004;279:9733–42.Google Scholar
  34. 34.
    Majolini MB, D’Elios MM, Galieni P, Boncristiano F, Lauria G, Del Prete JL, et al. Expression of the T-cell-specific tyrosine kinase lck in normal B-1 cells and in chronic lymphocytic leukemia B cells. Blood. 1998;91:3390–6.PubMedGoogle Scholar
  35. 35.
    Ascierto ML, Kmieciak M, Idowu MO, Manjili R, Zhao Y, Grimes M, et al. A signature of immune function genes associated with recurrence-free survival in breast cancer patients. Breast Cancer Res Treat. 2012;131(3):871–80.CrossRefPubMedCentralPubMedGoogle Scholar
  36. 36.
    Coronella JA, Telleman P, Kingsbury GA, Truong TD, Hays S, Junghans RP, et al. Evidence for an antigen-driven humoral immune response in medullary ductal breast cancer. Cancer Res. 2001;61(21):7889–99.PubMedGoogle Scholar
  37. 37.
    Kotlan B, Simsa P, Teillaud JL, Fridman WH, Toth J, McKnight M, et al. Novel ganglioside antigen identified by B cells in human medullary breast carcinomas: the proof of principle concerning the tumor-infiltrating B lymphocytes. J Immunol. 2005;175(4):2278–85.CrossRefPubMedGoogle Scholar
  38. 38.
    Galon J, Pagès F, Marincola FM, Thurin M, Trinchieri G, Fox BA, et al. The immune score as a new possible approach for the classification of cancer. J Transl Med. 2012;10:1–4.CrossRefPubMedCentralPubMedGoogle Scholar
  39. 39.
    Suzuki K, Kachala SS, Kadota K, Shen R, Mo Q, Beer DG, et al. Prognostic immune markers in NSCLC. Clin Cancer Res. 2011;17(16):5247–56.CrossRefPubMedGoogle Scholar
  40. 40.
    Hernando F, Sanz J, Jarabo JR, et al. A new genetic signature defining two prognostic groups among patients with completely resected early non-small cell lung cancer. J Thor Oncol. 2012;7(6):S59.Google Scholar
  41. 41.
    Sanz J, Hernandez S, Hernando F, Larriba JLG, Puente J, Ferrer M, et al. An intratumoral B-cell immune response determines favorable prognosis for early stage lung cancer and can be assessed by different immunoscores. Modern Pathol. 2013;26:466A.Google Scholar

Copyright information

© Federación de Sociedades Españolas de Oncología (FESEO) 2014

Authors and Affiliations

  • S. Hernández-Prieto
    • 2
  • A. Romera
    • 1
  • M. Ferrer
    • 2
  • J. L. Subiza
    • 4
  • J. A. López-Asenjo
    • 2
  • J. R. Jarabo
    • 3
  • A. M. Gómez
    • 3
  • Elena M. Molina
    • 2
  • J. Puente
    • 1
  • J. L. González-Larriba
    • 1
  • F. Hernando
    • 3
  • B. Pérez-Villamil
    • 1
    Email author
  • E. Díaz-Rubio
    • 1
  • J. Sanz-Ortega
    • 2
    Email author
  1. 1.Departamento de Oncología, Laboratorio de Genómica y Microarrays, Laboratorio de Oncología MolecularInstituto de Investigación Sanitaria San Carlos (IdISSC), Hospital Clinico San Carlos (HCSC)MadridSpain
  2. 2.Departamento de AnatomiaPatologicaInstituto de Investigación Sanitaria San Carlos (IdISSC), Hospital Clinico San Carlos (HCSC)MadridSpain
  3. 3.Unidad de CirugiaToracica, HCSCInstituto de Investigación Sanitaria San Carlos (IdISSC), Hospital Clinico San Carlos (HCSC)MadridSpain
  4. 4.Departamento de InmunologíaInstituto de Investigación Sanitaria San Carlos (IdISSC), Hospital Clinico San Carlos (HCSC)MadridSpain

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