5 protein-based signature for resectable lung squamous cell carcinoma improves the prognostic performance of the TNM staging

Elena Martínez-Terroba, Maria del Carmen Behrens, Jackeline Agorreta, Eduard Monsó, Laura Millares, Enriqueta Felip, Rafael Rosell, José Luis Ramirez, Ana Remirez, Wenceslao Torre, Ignacio Gil-Bazo, Miguel A. Idoate, Juan P. De-Torres, Ruben Pio, Ignacio Ivan Wistuba, María J. Pajares, Luis M. Montuenga

Research output: Contribution to journalArticle

Abstract

Introduction: Prognostic biomarkers have been very elusive in the lung squamous cell carcinoma (SCC) and none is currently being used in the clinical setting. We aimed to identify and validate the clinical utility of a protein-based prognostic signature to stratify patients with early lung SCC according to their risk of recurrence or death. Methods: Patients were staged following the new International Association for the Study of Lung Cancer (IASLC) staging criteria (eighth edition, 2018). Three independent retrospective cohorts of 117, 96 and 105 patients with lung SCC were analysed to develop and validate a prognostic signature based on immunohistochemistry for five proteins. Results: We identified a five protein-based signature whose prognostic index (PI) was an independent and significant predictor of disease-free survival (DFS) (p<0.001; HR=4.06, 95% CI 2.18 to 7.56) and overall survival (OS) (p=0.004; HR=2.38, 95% CI 1.32 to 4.31). The prognostic capability of PI was confirmed in an external multi-institutional cohort for DFS (p=0.042; HR=2.01, 95% CI 1.03 to 3.94) and for OS (p=0.031; HR=2.29, 95% CI 1.08 to 4.86). Moreover, PI added complementary information to the newly established IASLC TNM 8th edition staging system. A combined prognostic model including both molecular and anatomical (TNM) criteria improved the risk stratification in both cohorts (p<0.05). Conclusion: We have identified and validated a clinically feasible protein-based prognostic model that complements the updated TNM system allowing more accurate risk stratification. This signature may be used as an advantageous tool to improve the clinical management of the patients, allowing the reduction of lung SCC mortality through a more accurate knowledge of the patient's potential outcome.

Original languageEnglish (US)
Pages (from-to)371-379
Number of pages9
JournalThorax
Volume74
Issue number4
DOIs
StatePublished - Apr 1 2019

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Neoplasm Staging
Squamous Cell Carcinoma
Lung
Proteins
Disease-Free Survival
Survival
Lung Neoplasms
Biomarkers
Immunohistochemistry
Recurrence
Mortality

Keywords

  • clinical utility
  • disease-free survival
  • immunohistochemistry
  • overall survival
  • prognosis
  • signature
  • squamous cell carcinoma

ASJC Scopus subject areas

  • Pulmonary and Respiratory Medicine

Cite this

5 protein-based signature for resectable lung squamous cell carcinoma improves the prognostic performance of the TNM staging. / Martínez-Terroba, Elena; Behrens, Maria del Carmen; Agorreta, Jackeline; Monsó, Eduard; Millares, Laura; Felip, Enriqueta; Rosell, Rafael; Ramirez, José Luis; Remirez, Ana; Torre, Wenceslao; Gil-Bazo, Ignacio; Idoate, Miguel A.; De-Torres, Juan P.; Pio, Ruben; Wistuba, Ignacio Ivan; Pajares, María J.; Montuenga, Luis M.

In: Thorax, Vol. 74, No. 4, 01.04.2019, p. 371-379.

Research output: Contribution to journalArticle

Martínez-Terroba, E, Behrens, MDC, Agorreta, J, Monsó, E, Millares, L, Felip, E, Rosell, R, Ramirez, JL, Remirez, A, Torre, W, Gil-Bazo, I, Idoate, MA, De-Torres, JP, Pio, R, Wistuba, II, Pajares, MJ & Montuenga, LM 2019, '5 protein-based signature for resectable lung squamous cell carcinoma improves the prognostic performance of the TNM staging' Thorax, vol. 74, no. 4, pp. 371-379. https://doi.org/10.1136/thoraxjnl-2018-212194
Martínez-Terroba, Elena ; Behrens, Maria del Carmen ; Agorreta, Jackeline ; Monsó, Eduard ; Millares, Laura ; Felip, Enriqueta ; Rosell, Rafael ; Ramirez, José Luis ; Remirez, Ana ; Torre, Wenceslao ; Gil-Bazo, Ignacio ; Idoate, Miguel A. ; De-Torres, Juan P. ; Pio, Ruben ; Wistuba, Ignacio Ivan ; Pajares, María J. ; Montuenga, Luis M. / 5 protein-based signature for resectable lung squamous cell carcinoma improves the prognostic performance of the TNM staging. In: Thorax. 2019 ; Vol. 74, No. 4. pp. 371-379.
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abstract = "Introduction: Prognostic biomarkers have been very elusive in the lung squamous cell carcinoma (SCC) and none is currently being used in the clinical setting. We aimed to identify and validate the clinical utility of a protein-based prognostic signature to stratify patients with early lung SCC according to their risk of recurrence or death. Methods: Patients were staged following the new International Association for the Study of Lung Cancer (IASLC) staging criteria (eighth edition, 2018). Three independent retrospective cohorts of 117, 96 and 105 patients with lung SCC were analysed to develop and validate a prognostic signature based on immunohistochemistry for five proteins. Results: We identified a five protein-based signature whose prognostic index (PI) was an independent and significant predictor of disease-free survival (DFS) (p<0.001; HR=4.06, 95{\%} CI 2.18 to 7.56) and overall survival (OS) (p=0.004; HR=2.38, 95{\%} CI 1.32 to 4.31). The prognostic capability of PI was confirmed in an external multi-institutional cohort for DFS (p=0.042; HR=2.01, 95{\%} CI 1.03 to 3.94) and for OS (p=0.031; HR=2.29, 95{\%} CI 1.08 to 4.86). Moreover, PI added complementary information to the newly established IASLC TNM 8th edition staging system. A combined prognostic model including both molecular and anatomical (TNM) criteria improved the risk stratification in both cohorts (p<0.05). Conclusion: We have identified and validated a clinically feasible protein-based prognostic model that complements the updated TNM system allowing more accurate risk stratification. This signature may be used as an advantageous tool to improve the clinical management of the patients, allowing the reduction of lung SCC mortality through a more accurate knowledge of the patient's potential outcome.",
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T1 - 5 protein-based signature for resectable lung squamous cell carcinoma improves the prognostic performance of the TNM staging

AU - Martínez-Terroba, Elena

AU - Behrens, Maria del Carmen

AU - Agorreta, Jackeline

AU - Monsó, Eduard

AU - Millares, Laura

AU - Felip, Enriqueta

AU - Rosell, Rafael

AU - Ramirez, José Luis

AU - Remirez, Ana

AU - Torre, Wenceslao

AU - Gil-Bazo, Ignacio

AU - Idoate, Miguel A.

AU - De-Torres, Juan P.

AU - Pio, Ruben

AU - Wistuba, Ignacio Ivan

AU - Pajares, María J.

AU - Montuenga, Luis M.

PY - 2019/4/1

Y1 - 2019/4/1

N2 - Introduction: Prognostic biomarkers have been very elusive in the lung squamous cell carcinoma (SCC) and none is currently being used in the clinical setting. We aimed to identify and validate the clinical utility of a protein-based prognostic signature to stratify patients with early lung SCC according to their risk of recurrence or death. Methods: Patients were staged following the new International Association for the Study of Lung Cancer (IASLC) staging criteria (eighth edition, 2018). Three independent retrospective cohorts of 117, 96 and 105 patients with lung SCC were analysed to develop and validate a prognostic signature based on immunohistochemistry for five proteins. Results: We identified a five protein-based signature whose prognostic index (PI) was an independent and significant predictor of disease-free survival (DFS) (p<0.001; HR=4.06, 95% CI 2.18 to 7.56) and overall survival (OS) (p=0.004; HR=2.38, 95% CI 1.32 to 4.31). The prognostic capability of PI was confirmed in an external multi-institutional cohort for DFS (p=0.042; HR=2.01, 95% CI 1.03 to 3.94) and for OS (p=0.031; HR=2.29, 95% CI 1.08 to 4.86). Moreover, PI added complementary information to the newly established IASLC TNM 8th edition staging system. A combined prognostic model including both molecular and anatomical (TNM) criteria improved the risk stratification in both cohorts (p<0.05). Conclusion: We have identified and validated a clinically feasible protein-based prognostic model that complements the updated TNM system allowing more accurate risk stratification. This signature may be used as an advantageous tool to improve the clinical management of the patients, allowing the reduction of lung SCC mortality through a more accurate knowledge of the patient's potential outcome.

AB - Introduction: Prognostic biomarkers have been very elusive in the lung squamous cell carcinoma (SCC) and none is currently being used in the clinical setting. We aimed to identify and validate the clinical utility of a protein-based prognostic signature to stratify patients with early lung SCC according to their risk of recurrence or death. Methods: Patients were staged following the new International Association for the Study of Lung Cancer (IASLC) staging criteria (eighth edition, 2018). Three independent retrospective cohorts of 117, 96 and 105 patients with lung SCC were analysed to develop and validate a prognostic signature based on immunohistochemistry for five proteins. Results: We identified a five protein-based signature whose prognostic index (PI) was an independent and significant predictor of disease-free survival (DFS) (p<0.001; HR=4.06, 95% CI 2.18 to 7.56) and overall survival (OS) (p=0.004; HR=2.38, 95% CI 1.32 to 4.31). The prognostic capability of PI was confirmed in an external multi-institutional cohort for DFS (p=0.042; HR=2.01, 95% CI 1.03 to 3.94) and for OS (p=0.031; HR=2.29, 95% CI 1.08 to 4.86). Moreover, PI added complementary information to the newly established IASLC TNM 8th edition staging system. A combined prognostic model including both molecular and anatomical (TNM) criteria improved the risk stratification in both cohorts (p<0.05). Conclusion: We have identified and validated a clinically feasible protein-based prognostic model that complements the updated TNM system allowing more accurate risk stratification. This signature may be used as an advantageous tool to improve the clinical management of the patients, allowing the reduction of lung SCC mortality through a more accurate knowledge of the patient's potential outcome.

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