Background Over the past decade, the number of elderly cancer patients has increased, including those with NSCLCs, most of whom are over 60 years old. NSCLC patients receive anti-PD1-based therapies. These therapies directly target the immune system by activating T cells. However, older patients exhibit several baseline immune system changes compared to their younger counterparts, which could affect treatment effectiveness. This study aims to assess the immune systems of younger (<65) and older (>65) NSCLC patients at baseline to determine whether immune aging may alter the efficacy of immune treatments. ACCEPTED MANUSCRIPT ARTICLE IN PRESS ARTICLE IN PRESS 2 Methods Seventy-eight NSCLC patients were enrolled in this study and divided into two groups on an age basis: younger (26 pts, <65 years; young-pts) and older (52 pts, >65 years; old-pts). The patient's immune profile was assessed before therapy by evaluating circulating immune cell subsets and soluble immune mediators using flow cytometry and a Luminex assay, respectively. Immune populations and soluble factors were correlated with treatment response and survival outcomes. A cohort of 27 healthy donors (HDs) served as the control group. Results Cancer patients (CPs) exhibited higher levels of CD8 (p<0.001), Ki67 (p<0.001), effector (p<0.0075), and regulatory T cells (p<0.001) than HDs. These differences remained consistent across age groups, except for effector cells, which showed a slight increase (p=0.0932) in young CPs compared with young-HDs. Moreover, CD3 (p<0.001), CD4 (p<0.001), PD1 (p<0.001), and naïve T cells (p=0.0144) were significantly lower in CPs than in HDs, with a similar trend across age groups, except for naïve T cells (p=0.0748). The OS data showed no differences between the young and old groups when analyzing the entire population and the responder patients (R). However, young non-responders (NR) experienced longer survival than older NRs. Multivariate analysis identified PMN (Lox1 + )-MDSCs, Ki67, and response to therapy as independent predictors in NRs. The ROC curve established the cutoff for distinguishing the high-risk group, characterized by worse outcomes with elevated levels of PMN (Lox1 + )-MDSCs and Ki67 + cells, from the lowrisk group (log-rank p=0.0093). Moreover, old-NRs showed significantly higher levels of PMN (Lox1 + )-MDSCs than old-Rs, and a higher percentage of CD137 + PD1 + (p=0.05) and central memory T cells (p=0.09). Conclusion The combined index of PMN(Lox1+)-MDSCs and Ki67T cells offers a practical tool for assessing immunological fitness in the NR setting, thereby enhancing patient stratification
The immunological fitness of NSCLC patients drives the response to anti-PD1-based immunotherapy regardless of age / Tuosto, Lucrezia; Gelibter, Alain; Strigari, Lidia; Asquino, Angela; Siringo, Marco; Pace, Angelica; Valentino, Flavio; Capozzi, Davide; Bianchini, Serena; Bellati, Filippo; Santini, Daniele; Nuti, Marianna; Zizzari, Ilaria Grazia; Rughetti, Aurelia; Napoletano, Chiara. - In: JOURNAL OF TRANSLATIONAL MEDICINE. - ISSN 1479-5876. - (2026). [10.1186/s12967-026-07719-9]
The immunological fitness of NSCLC patients drives the response to anti-PD1-based immunotherapy regardless of age
Lucrezia TuostoPrimo
;Alain Gelibter
Secondo
;Lidia Strigari;Angela Asquino;Marco Siringo;Angelica Pace;Flavio Valentino;Davide Capozzi;Serena Bianchini;Filippo Bellati;Daniele Santini;Marianna Nuti;Ilaria Grazia Zizzari;Aurelia Rughetti
Penultimo
;Chiara Napoletano
Ultimo
2026
Abstract
Background Over the past decade, the number of elderly cancer patients has increased, including those with NSCLCs, most of whom are over 60 years old. NSCLC patients receive anti-PD1-based therapies. These therapies directly target the immune system by activating T cells. However, older patients exhibit several baseline immune system changes compared to their younger counterparts, which could affect treatment effectiveness. This study aims to assess the immune systems of younger (<65) and older (>65) NSCLC patients at baseline to determine whether immune aging may alter the efficacy of immune treatments. ACCEPTED MANUSCRIPT ARTICLE IN PRESS ARTICLE IN PRESS 2 Methods Seventy-eight NSCLC patients were enrolled in this study and divided into two groups on an age basis: younger (26 pts, <65 years; young-pts) and older (52 pts, >65 years; old-pts). The patient's immune profile was assessed before therapy by evaluating circulating immune cell subsets and soluble immune mediators using flow cytometry and a Luminex assay, respectively. Immune populations and soluble factors were correlated with treatment response and survival outcomes. A cohort of 27 healthy donors (HDs) served as the control group. Results Cancer patients (CPs) exhibited higher levels of CD8 (p<0.001), Ki67 (p<0.001), effector (p<0.0075), and regulatory T cells (p<0.001) than HDs. These differences remained consistent across age groups, except for effector cells, which showed a slight increase (p=0.0932) in young CPs compared with young-HDs. Moreover, CD3 (p<0.001), CD4 (p<0.001), PD1 (p<0.001), and naïve T cells (p=0.0144) were significantly lower in CPs than in HDs, with a similar trend across age groups, except for naïve T cells (p=0.0748). The OS data showed no differences between the young and old groups when analyzing the entire population and the responder patients (R). However, young non-responders (NR) experienced longer survival than older NRs. Multivariate analysis identified PMN (Lox1 + )-MDSCs, Ki67, and response to therapy as independent predictors in NRs. The ROC curve established the cutoff for distinguishing the high-risk group, characterized by worse outcomes with elevated levels of PMN (Lox1 + )-MDSCs and Ki67 + cells, from the lowrisk group (log-rank p=0.0093). Moreover, old-NRs showed significantly higher levels of PMN (Lox1 + )-MDSCs than old-Rs, and a higher percentage of CD137 + PD1 + (p=0.05) and central memory T cells (p=0.09). Conclusion The combined index of PMN(Lox1+)-MDSCs and Ki67T cells offers a practical tool for assessing immunological fitness in the NR setting, thereby enhancing patient stratification| File | Dimensione | Formato | |
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