BACKGROUND-AIM: Although a particular subset of patients treated with immune-checkpoint inhibitors (ICIs) consistently shows long-term survival, the immune mechanisms behind such phenomena remain largely unknown. We propose a network medicine framework that reliably uncovers non-obvious patterns among target T-cell subgroups in flow-cytometric data. Our objective is to investigate the topological rewiring of T-cell response in long survivors (LS) across different solid tumor cohorts, with the aim of uncovering a tumor-agnostic immune signature. METHODS: Peripheral blood mononuclear cells were collected from 93 patients with distinct solid tumors undergoing ICI therapy and 52 healthy donors and then analyzed using multiparametric flow-cytometry for a total of 31 T-cell populations. Patients were divided in LS (Overall-Survival>18/24 months) and Early Progressors (EP) (Progression-Free-Survival (PFS)≤3 months). To investigate immune signatures among subgroups, we implemented a differential overlay pipeline: network edges were first validated for stability via bootstrap resampling, followed by permutation testing to assess significant rewiring across clinical outcomes. Stable edges were then topologically classified (conserved, specific, or inverted). RESULTS: The EP network is highly centralized around activation compartments (CD3+PD1+Effector, degree=11). Interestingly, the LS network undergoes extensive structural rewiring to establish a costimulatory, memory-driven topology. Here, the central hub is represented by CD3+CD137+Central memory (degree=12). This node-centric divergence is driven by statistically robust edge inversions, prominently the interactions between CD3+CD137+Effector memory RA+ and CD3+PD1+Naive (p=0.0015 in EPvsLS), and between CD3+Central memory and CD3+Effector memory (p=0.0065 in EP vs LS), proving that long-term survival relies on reversing specific immunological axes rather than global immune restoration. CONCLUSION: From our results, long-term survival seems supported by rewired CD137+ memory T-cell networks. Our framework demonstrates that integrating edge inversions and nodal metrics from flow-cytometry data provides deep biological insights invisible to standard univariate analyses.
A tumor-agnostic network medicine framework reveals topological rewiring of systemic T-cell immunity in long-surviving cancer patients / Capozzi, D., Valentino, F., Tuosto, L., Asquino, A., Pace, A., Cirillo, A., Gelibter, A., Botticelli, A., Zizzari, I.G., Napoletano, C., Paci, P., Rughetti, A.. - (2026). (Congresso SIPMeT 2026 Napoli ).
A tumor-agnostic network medicine framework reveals topological rewiring of systemic T-cell immunity in long-surviving cancer patients
D. Capozzi;F. Valentino;L. Tuosto;A. Asquino;A. Pace;A. Cirillo;A. Gelibter;A. Botticelli;I. G. Zizzari;C. Napoletano;P. Paci;A. Rughetti
2026
Abstract
BACKGROUND-AIM: Although a particular subset of patients treated with immune-checkpoint inhibitors (ICIs) consistently shows long-term survival, the immune mechanisms behind such phenomena remain largely unknown. We propose a network medicine framework that reliably uncovers non-obvious patterns among target T-cell subgroups in flow-cytometric data. Our objective is to investigate the topological rewiring of T-cell response in long survivors (LS) across different solid tumor cohorts, with the aim of uncovering a tumor-agnostic immune signature. METHODS: Peripheral blood mononuclear cells were collected from 93 patients with distinct solid tumors undergoing ICI therapy and 52 healthy donors and then analyzed using multiparametric flow-cytometry for a total of 31 T-cell populations. Patients were divided in LS (Overall-Survival>18/24 months) and Early Progressors (EP) (Progression-Free-Survival (PFS)≤3 months). To investigate immune signatures among subgroups, we implemented a differential overlay pipeline: network edges were first validated for stability via bootstrap resampling, followed by permutation testing to assess significant rewiring across clinical outcomes. Stable edges were then topologically classified (conserved, specific, or inverted). RESULTS: The EP network is highly centralized around activation compartments (CD3+PD1+Effector, degree=11). Interestingly, the LS network undergoes extensive structural rewiring to establish a costimulatory, memory-driven topology. Here, the central hub is represented by CD3+CD137+Central memory (degree=12). This node-centric divergence is driven by statistically robust edge inversions, prominently the interactions between CD3+CD137+Effector memory RA+ and CD3+PD1+Naive (p=0.0015 in EPvsLS), and between CD3+Central memory and CD3+Effector memory (p=0.0065 in EP vs LS), proving that long-term survival relies on reversing specific immunological axes rather than global immune restoration. CONCLUSION: From our results, long-term survival seems supported by rewired CD137+ memory T-cell networks. Our framework demonstrates that integrating edge inversions and nodal metrics from flow-cytometry data provides deep biological insights invisible to standard univariate analyses.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
