BACKGROUND: Patients with early-stage non-small-cell lung carcinoma (NSCLC) may benefit from treatments based on more accurate prognosis. A 15-gene prognostic classifier for NSCLC was identified from mRNA expression profiling of tumor samples from the NCIC CTG JBR.10 trial. In this study, we assessed its value in an independent set of cases. METHODS: Expression profiling was performed on RNA from frozen, resected tumor tissues corresponding to 181 stage I and II NSCLC cases collected at University Health Network (UHN181). Kaplan-Meier methodology was used to estimate 5-year overall survival probabilities, and the prognostic effect of the classifier was assessed using the log-rank test. A Cox proportional hazards model evaluated the signature's effect adjusting for clinical prognostic factors. RESULTS: Expression data of the 15-gene classifier stratified UHN181 cases into high- and low-risk subgroups with significantly different overall survival (hazard ratio [HR] = 1.92; 95% confidence interval [CI], 1.15-3.23; p = 0.012). In a subgroup analysis, this classifier predicted survival in 127 stage I patients (HR = 2.17; 95% CI, 1.12-4.20; p = 0.018) and the smaller subgroup of 48 stage IA patients (HR = 5.61; 95% CI, 1.19-26.45; p = 0.014). The signature was prognostic for both adenocarcinoma and squamous cell carcinoma cases (HR = 1.76, p = 0.058; HR = 4.19, p = 0.045, respectively). CONCLUSION: The prognostic accuracy of a 15-gene classifier was validated in an independent cohort of 181 early-stage NSCLC samples including stage IA cases and in different NSCLC histologic subtypes.
BACKGROUND:Patients with early-stage non-small-cell lung carcinoma (NSCLC) may benefit from treatments based on more accurate prognosis. A 15-gene prognostic classifier for NSCLC was identified from mRNA expression profiling of tumor samples from the NCIC CTG JBR.10 trial. In this study, we assessed its value in an independent set of cases. METHODS: Expression profiling was performed on RNA from frozen, resected tumor tissues corresponding to 181 stage I and II NSCLC cases collected at University Health Network (UHN181). Kaplan-Meier methodology was used to estimate 5-year overall survival probabilities, and the prognostic effect of the classifier was assessed using the log-rank test. A Cox proportional hazards model evaluated the signature's effect adjusting for clinical prognostic factors. RESULTS: Expression data of the 15-gene classifier stratified UHN181 cases into high- and low-risk subgroups with significantly different overall survival (hazard ratio [HR] = 1.92; 95% confidence interval [CI], 1.15-3.23; p = 0.012). In a subgroup analysis, this classifier predicted survival in 127 stage I patients (HR = 2.17; 95% CI, 1.12-4.20; p = 0.018) and the smaller subgroup of 48 stage IApatients (HR = 5.61; 95% CI, 1.19-26.45; p = 0.014). The signature was prognostic for both adenocarcinoma and squamous cell carcinoma cases (HR = 1.76, p = 0.058; HR = 4.19, p = 0.045, respectively). CONCLUSION: The prognostic accuracy of a 15-gene classifier was validated in an independent cohort of 181 early-stage NSCLC samples including stage IA cases and in different NSCLC histologic subtypes.
Authors: Dijana Djureinovic; Björn M Hallström; Masafumi Horie; Johanna Sofia Margareta Mattsson; Linnea La Fleur; Linn Fagerberg; Hans Brunnström; Cecilia Lindskog; Katrin Madjar; Jörg Rahnenführer; Simon Ekman; Elisabeth Ståhle; Hirsh Koyi; Eva Brandén; Karolina Edlund; Jan G Hengstler; Mats Lambe; Akira Saito; Johan Botling; Fredrik Pontén; Mathias Uhlén; Patrick Micke Journal: JCI Insight Date: 2016-07-07
Authors: Marianna Grinberg; Dijana Djureinovic; Hans Rr Brunnström; Johanna Sm Mattsson; Karolina Edlund; Jan G Hengstler; Linnea La Fleur; Simon Ekman; Hirsh Koyi; Eva Branden; Elisabeth Ståhle; Karin Jirström; Derek K Tracy; Fredrik Pontén; Johan Botling; Jörg Rahnenführer; Patrick Micke Journal: Mod Pathol Date: 2017-03-10 Impact factor: 7.842
Authors: Dhruva Biswas; Nicolai J Birkbak; Rachel Rosenthal; Crispin T Hiley; Emilia L Lim; Krisztian Papp; Stefan Boeing; Marcin Krzystanek; Dijana Djureinovic; Linnea La Fleur; Maria Greco; Balázs Döme; János Fillinger; Hans Brunnström; Yin Wu; David A Moore; Marcin Skrzypski; Christopher Abbosh; Kevin Litchfield; Maise Al Bakir; Thomas B K Watkins; Selvaraju Veeriah; Gareth A Wilson; Mariam Jamal-Hanjani; Judit Moldvay; Johan Botling; Arul M Chinnaiyan; Patrick Micke; Allan Hackshaw; Jiri Bartek; Istvan Csabai; Zoltan Szallasi; Javier Herrero; Nicholas McGranahan; Charles Swanton Journal: Nat Med Date: 2019-10-07 Impact factor: 53.440