Multicenter Study

. 2023 Jul 7:14:1199089.

doi: 10.3389/fimmu.2023.1199089. eCollection 2023.

A network approach to define the predictive role of immune profile on tumor response and toxicity of anti PD-1 single agent immunotherapy in patients with solid tumors

Silvia Mezi¹, Giulia Pomati², Giulia Fiscon³, Sasan Amirhassankhani⁴, Ilaria Grazia Zizzari⁵, Chiara Napoletano⁵, Aurelia Rughetti⁵, Ernesto Rossi⁶, Giovanni Schinzari^{6

7}, Giampaolo Tortora^{6

7}, Gaetano Lanzetta⁸, Giulia D'Amati¹, Marianna Nuti⁵, Daniele Santini⁹, Andrea Botticelli¹

Affiliations

¹ Department of Radiological, Oncological and Pathological Science, Sapienza University of Rome, Rome, Italy.
² Department of Molecular Medicine, Sapienza University of Rome, Rome, Italy.
³ Department of Computer, Control, and Management Engineering "Antonio Ruberti", "Sapienza" University of Rome, Rome, Italy.
⁴ Department of Urology, S. Orsola-Malpighi Hospital University of Bologna, Bologna, Italy.
⁵ Laboratory of Tumor Immunology and Cell Therapy, Department of Experimental Medicine, Policlinico Umberto I, University of Rome "Sapienza", Rome, Italy.
⁶ Medical Oncology, Fondazione Policlinico Universitario Agostino Gemelli Istituti di Ricovero e Cura a Carattere Scientifico (IRCCS), Rome, Italy.
⁷ Medical Oncology, Universitá Cattolica del Sacro Cuore, Rome, Italy.
⁸ Clinical Oncology Unit, Istituto Neurotraumatologico Italiano (I.N.I.) Grottaferrata, via di S.Anna snc, Grottaferrata, Italy.
⁹ Department of Medico-Surgical Sciences and Biotechnology, Polo Pontino, Sapienza University of Rome, Rome, Italy.

PMID: 37483633
PMCID: PMC10361061
DOI: 10.3389/fimmu.2023.1199089

Multicenter Study

A network approach to define the predictive role of immune profile on tumor response and toxicity of anti PD-1 single agent immunotherapy in patients with solid tumors

Silvia Mezi et al. Front Immunol. 2023.

. 2023 Jul 7:14:1199089.

doi: 10.3389/fimmu.2023.1199089. eCollection 2023.

Authors

Affiliations

¹ Department of Radiological, Oncological and Pathological Science, Sapienza University of Rome, Rome, Italy.
² Department of Molecular Medicine, Sapienza University of Rome, Rome, Italy.
³ Department of Computer, Control, and Management Engineering "Antonio Ruberti", "Sapienza" University of Rome, Rome, Italy.
⁴ Department of Urology, S. Orsola-Malpighi Hospital University of Bologna, Bologna, Italy.
⁵ Laboratory of Tumor Immunology and Cell Therapy, Department of Experimental Medicine, Policlinico Umberto I, University of Rome "Sapienza", Rome, Italy.
⁶ Medical Oncology, Fondazione Policlinico Universitario Agostino Gemelli Istituti di Ricovero e Cura a Carattere Scientifico (IRCCS), Rome, Italy.
⁷ Medical Oncology, Universitá Cattolica del Sacro Cuore, Rome, Italy.
⁸ Clinical Oncology Unit, Istituto Neurotraumatologico Italiano (I.N.I.) Grottaferrata, via di S.Anna snc, Grottaferrata, Italy.
⁹ Department of Medico-Surgical Sciences and Biotechnology, Polo Pontino, Sapienza University of Rome, Rome, Italy.

PMID: 37483633
PMCID: PMC10361061
DOI: 10.3389/fimmu.2023.1199089

Abstract

Background: The immune profile of each patient could be considered as a portrait of the fitness of his/her own immune system. The predictive role of the immune profile in immune-related toxicities (irAEs) development and tumour response to treatment was investigated.

Methods: A prospective, multicenter study evaluating, through a multiplex assay, the soluble immune profile at the baseline of 53 patients with advanced cancer, treated with immunotherapy as single agent was performed. Four connectivity heat maps and networks were obtained by calculating the Spearman correlation coefficients for each group: responder patients who developed cumulative toxicity (R-T), responders who did not develop cumulative toxicity (R-NT), non-responders who developed cumulative toxicity (NR-T), non-responders who did not develop cumulative toxicity (NR-NT).

Results: A statistically significant up-regulation of IL-17A, sCTLA4, sCD80, I-CAM-1, sP-Selectin and sEselectin in NR-T was detected. A clear loss of connectivity of most of the soluble immune checkpoints and cytokines characterized the immune profile of patients with toxicity, while an inversion of the correlation for ICAM-1 and sP-selectin was observed in NR-T. Four connectivity networks were built for each group. The highest number of connections characterized the NR-T.

Conclusions: A connectivity network of immune dysregulation was defined for each subgroup of patients, regardless of tumor type. In patients with the worst prognosis (NR-T) the peculiar connectivity model could facilitate their early and timely identification, as well as the design of a personalized treatment approach to improve outcomes or prevent irAEs.

Keywords: chemokine; cytokine; immune-related toxicity; network analysis; soluble adhesion molecules; soluble immune checkpoints; soluble immune profile.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

**Figure 1**
Statistical analysis at T0. Heatmap of expression levels of immune mediators (base-2 loga-rithmic scale) at T0 across 53 patients grouped by R-T (violet bars), R-NT (water blue bars), NR-NT (orange bars), NR-T (blue bars). A z-score normalization was applied and colors represent different expression levels increasing from blue to yellow. The distribution of primary tumours in each subgroup is indicated at the bottom of the heatmap.

**Figure 2**
Statistical analysis at T0. Boxplot of molecules expression level (base-2 logarithmic scale) in 7 R-T (violet box), 12 R-NT (water blue box), 23 NR-NT (orange box) and 11 NR-T (blue box) at T0. Pairwise p-values (p) were obtained employing a Mann-Whitney test for unpaired samples, while overall p-value was obtained via Kruskal-Wallis test. Only molecules showing an overall statistically significant difference among all groups and a pairwise statistical difference in at least one comparison are shown. Legend: * p-value ≤ 0.05; ** p-value ≤ 0.01; *** p-value ≤ 0.001.

**Figure 3**
Statistical analysis at T0 for sICs. Boxplot of sICs expression level (base 2 logarithmic scale) in 7 R-T (violet box), 12 R-NT (water blue box), 23 NR-NT (orange box) and 11 NR-T (blue box) at T0. Pairwise p-values (p) were obtained emplying the Mann-Whitney test for unpaired samples, overall p-value was obtained via Kruskal-Wallis test. Legend: * p-value ≤ 0.05.

**Figure 4**
Connectivity map between molecules in R-NT **(A)**, R-T **(B)**, NR-NT **(C)**, NR-T **(D)** at T0. Statistically significant Spearman correlations (p-value ≤ 0.05) are reported. In the plot, circles are scaled and coloured according to the correlation values, increasing from red (negative correlation) to blue (positive correlation). Molecules are grouped and ordered according to the functional group reported in the legend.

**Figure 5**
Connectivity network between molecules in R-NT **(A)**, R-T **(B)**, NR-NT **(C)**, NR-T **(D)** at T0. In each network, nodes represent molecule and a link occurs between two nodes if the absolute value of Spearman correlation between their expression levels is statistically significant (p-value ≤ 0.05) and greater than a selected threshold (i.e., the 80th percentile of the overall distribution corresponding to 0.7). Nodes are colored according to the functional groups reported in the legend; whereas edge colour indicates positive (blue) or negative (red) correlation values.

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A network approach to define the predictive role of immune profile on tumor response and toxicity of anti PD-1 single agent immunotherapy in patients with solid tumors

Affiliations

A network approach to define the predictive role of immune profile on tumor response and toxicity of anti PD-1 single agent immunotherapy in patients with solid tumors

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

References

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MeSH terms

Substances

LinkOut - more resources

Full Text Sources

Medical

Research Materials

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