Viviana Vallacchi

Desmoid fibromatosis (DF) is a rare mesenchymal neoplasm with an unpredictable clinical course, where spontaneous regression or progression occurs in a significant subset of patients through largely undefined mechanisms. The use of active surveillance (AS) offers the opportunity to investigate whether tumor- or host-driven systemic and local immune features may explain these divergent outcomes, improving patient management. A prospective observational study enrolled 55 patients with primary sporadic DF managed with AS. Clinical evolution was categorized as progression, regression, or stable disease according to RECIST 1.1. Immunomonitoring with multicolor flow cytometry identified distinct systemic T-helper polarization states stratifying clinical trajectories: regressors showed a Th2-skewed profile, while progressors displayed activated T-helper cells and Th1/Th9/Th17 subsets. Higher baseline Th2 levels associated with regression and longer progression-free survival. Plasma proteomic and whole-blood transcriptomic analyses confirmed coordinated IL-4/IL-13-linked pro-resolving programs in regressors and inflammatory, early T-cell activation signatures in progressors. Tumor transcriptomics revealed adaptive, antigen-presentation and restrained immune programs in regressing lesions versus innate inflammatory, interferon and TGF-β-driven fibrotic pathways in progressing tumors. These findings identify systemic T-helper polarization as a biomarker of DF behavior and highlight coordinated systemic-tumoral immune programs underlying clinical outcomes, supporting more precise clinical management.

Supplementary Tables S1-S6_S17-S18

In tumor-bearing mice, cyclic fasting or fasting-mimicking diets (FMD) enhance the activity of antineoplastic treatments by modulating systemic metabolism and boosting antitumor immunity. Here we conducted a clinical trial to investigate the safety and biological effects of cyclic, five-day FMD in combination with standard antitumor therapies. In 101 patients, the FMD was safe, feasible, and resulted in a consistent decrease of blood glucose and growth factor concentration, thus recapitulating metabolic changes that mediate fasting/FMD anticancer effects in preclinical experiments. Integrated transcriptomic and deep-phenotyping analyses revealed that FMD profoundly reshapes anticancer immunity by inducing the contraction of peripheral blood immunosuppressive myeloid and regulatory T-cell compartments, paralleled by enhanced intratumor Th1/cytotoxic responses and an enrichment of IFNγ and other immune signatures associated with better clinical outcomes in patients with cancer. Our findings lay the foundations for phase II/III clinical trials aimed at investigating FMD antitumor efficacy in combination with standard antineoplastic treatments.Significance:Cyclic FMD is well tolerated and causes remarkable systemic metabolic changes in patients with different tumor types and treated with concomitant antitumor therapies. In addition, the FMD reshapes systemic and intratumor immunity, finally activating several antitumor immune programs. Phase II/III clinical trials are needed to investigate FMD antitumor activity/efficacy.This article is highlighted in the In This Issue feature, p. 1

Supplementary Data from Development of a Molecular Blood-Based Immune Signature Classifier as Biomarker for Risks Assessment in Lung Cancer Screening

Background:Low-dose CT (LDCT) screening trials have shown that lung cancer early detection saves lives. However, a better stratification of the screening population is still needed. In this respect, we generated and prospectively validated a plasma miRNA signature classifier (MSC) able to categorize screening participants according to lung cancer risk. Here, we aimed to deeply characterize the peripheral immune profile and develop a diagnostic immune signature classifier to further implement blood testing in lung cancer screening.Methods:Peripheral blood mononuclear cell (PBMC) samples collected from 20 patients with LDCT-detected lung cancer and 20 matched cancer-free screening volunteers were analyzed by flow cytometry using multiplex panels characterizing both lymphoid and myeloid immune subsets. Data were validated in PBMC from 40 patients with lung cancer and 40 matched controls and in a lung cancer specificity set including 27 subjects with suspicious lung nodules. A qPCR-based gene expression signature was generated resembling selected immune subsets.Results:Monocytic myeloid-derived suppressor cell (MDSC), polymorphonuclear MDSC, intermediate monocytes and CD8+PD-1+ T cells distinguished patients with lung cancer from controls with AUCs values of 0.94/0.72/0.88 in the training, validation, and lung cancer specificity set, respectively. AUCs raised up to 1.00/0.84/0.92 in subgroup analysis considering only MSC-negative subjects. A 14-immune genes expression signature distinguished patients from controls with AUC values of 0.76 in the validation set and 0.83 in MSC-negative subjects.Conclusions:An immune-based classifier can enhance the accuracy of blood testing, thus supporting the contribution of systemic immunity to lung carcinogenesis.Impact:Implementing LDCT screening trials with minimally invasive blood tests could help reduce unnecessary procedures and optimize cost-effectiveness.

Supplementary Figure from Development of a Molecular Blood-Based Immune Signature Classifier as Biomarker for Risks Assessment in Lung Cancer Screening