Supplementary Figure S4. Characterization of additional cell lines. A. Immunofluorescence for DAPI (blue) and CGA (red) on murine NEPC cells (TC566 and TC411K). B. Immunofluorescence for DAPI (blue) and OPN (red) on HMC-1 cells. C. Western blot for OPN in HMC-1 cells treated or not with Brefeldin A (BFA; 5 g/ml). Vinculin was evaluated as housekeeping control. D. Gating strategy applied to distinguish human NEPC cells (CD49f+c-Kit-) from HMC-1 MCs (CD49f-c-Kit+) by flow cytometry. E. OPN evaluation by ELISA (left panel) or real time PCR (the Spp1 transcript; right panel) in WT and OPN−/− MCs, and in MC/9, T23, and ST4787 cells. F. Elisa for OPN in parental MC/9 cells and in MC/9-CTR, MC/9-OPNf, MC/9-iOPN cells. T23 cells were used as control.

Supplementary table 1 - list of antibodies used in the study

Supplementary Figure S1. Flow cytometry evaluation of murine MC purity and maturation in vitro. A. Gating strategy used to evaluate the purity and maturation of WT, OPN-/-, MyD88-/- and TNFa-/-MCs by flow cytometry. Mature MC population is identified as c-Kit+FceRI+.

Supplementary Figure S5. Expression of OPN in MC/9 cells and effect on T23 cell proliferation. A. Separate channels of immunofluorescence for DAPI (cyan), OPN (red) and WGA (blue) of MC/9, MC/9-CTR, MC/9-OPNf, and MC/9-iOPN cells showed in Fig. 2E. B. Quantification of A as percentage of OPN positive cells. C. Murine adenocarcinoma (T23) cells (50.000/well) were cultured either alone or with MC/9, MC/9-CTR, MC/9-OPNf or MC/9-iOPN cells (tumor cell:MC ratio 1:1). After 4 days the growth rate of cancer cells was evaluated through trypan blue count. Cancer cells and MC/9 could be distinguished thanks to their grown in adhesion or suspension, respectively. All histograms depict mean ± SD of biological replicates (represented by dots). One-way ANOVA followed by Tukey’s multiple comparison test was used: *, P < 0.05; **, P <0.01. Where P-value is not indicated, the comparison between groups is not statistically significant.

Supplementary table 3 - List of putative NEPC-specific surface TLR ligands

Supplementary Figure S2. OPN evaluation in bone marrow-derived MCs. A. Separate channels of immunofluorescence for DAPI (cyan), OPN (red) and WGA (blue) of WT and OPN-/- MCs showed in Fig. 1A B. Representative images of 3 different biological replicates of immunofluorescence for DAPI (cyan), OPN (red) and WGA (blue), in WT and OPN-/- MCs. These pictures were used for the quantification reported in Fig. 1B.

Supplementary Figure S8. Hematoxylin and eosin staining in TRAMP mice. A. Hematoxylin and eosin staining in serial slides of tumors reported in Fig. 5A, showing an untreated TRAMP mouse with adenocarcinoma (ADENO) and a TRAMP mouse subjected to surgical castration showing a focal t-NEPC area.

Supplementary table 4 - transcript levels of the 29 TLR ligands measured by high throughput customized Taqman assay

Supplementary Figure S9. Expression and silencing of putative TLR ligands in NEPC cells. A. Venn diagrams show a list of 29 genes (List 3; Supplementary Table S3) extrapolated from the intersection between genes found up-regulated in TRAMP-derived incipient NEPC (a data set generated in this study, GSE242811; List 1; Supplementary Table S3) and a list of surface TLR2/TLR4 ligands identified from a ligand-receptor pairs repository (LewisLabUCSD, ref. (Armingol et al., 2021) List 2; Table S3). B. Real Time-PCR for Cd14, Sdc1, Hspa2 and Anxa2 on lysates from T23 and ST4787 cells. Technical replicates are indicated by dots (n=2). C. Quantification of the western blot for HSPA2 and ANXA2 in T23 and ST4787 showed in Fig. 6B. D. Expression of CD14 and SDC1 in ST4787 silenced with two different siRNA specific for Cd14 (ST4787-siCD14- 1 and ST4787-siCD14-2) or Sdc1 (ST4787-siSDC1-1 and ST4787-siSDC1-2), or in scramble control cells (ST4787-scramble), evaluated by flow cytometry 72 hours post-silencing. E. HSPA2 and ANXA2 expression in ST4787 silenced with two different siRNA specific for Hspa2 (ST4787- siHSPA2-1 and ST4787- siHSPA2-2) or Anxa2 (ST4787-siANXA2-1 and ST4787-siANXA2-2), or in scramble control cells (ST4787-scramble) evaluated by western blot analysis 72 hours post- silencing. F. Quantification of E. Western blot was validated twice. G. ST4787-scramble or silenced with two different siRNA specific for Cd14 were cultured with WT or OPN−/− MCs (ratio 1:1). After 16 hours the percentage of TNF positive MCs was evaluated by intracellular flow cytometry in WT or OPN-/-MCs. Gating strategy is reported in Fig. S4D. H. Flow cytometry evaluation of CD14 on adenocarcinoma (22Rv1 human) and NEPC (TC411K murine, and NCI-H660 human) cells. All histograms depict mean ± SD of biological replicates (represented by dots). T test (B) or One-way ANOVA followed by Tukey’s multiple comparison test (G) were used for the analysis of significance between samples. P-values are reported as: *, P < 0.05; **, P <0.01; ***, P <0.001. Where P-value is not indicated, the comparison between groups is not statistically significant.

Supplementary table 2 - list of siRNA and Taqman assays used in the study

Supplementary Figure S3. Toluidine blue for detection of MCs in mice. A. MC count reported as number of MCs/tumor area (cm2) in tumor samples from TRAMP mice with prostate intraepithelial neoplasia or adenocarcinoma (PIN/ADENO, n= 12), or TRAMP mice with NEPC (n= 3), as well as in prostatectomies from untreated patients with Gleason Score 7 (n= 10), Gleason Score 8 (n=10), or showing evidence of NEPC (n= 4). The histogram depict mean ± SD of biological replicates (represented by dots). B. Upper panels: representative images of toluidine blue staining in TRAMP, KitWsh-TRAMP, and OPN-/-TRAMP mice, or in KitWsh-TRAMP mice reconstituted with WT, OPN-/- or TNFa-/- MCs. Lower panels: representative images of toluidine blue staining in a prostate of a patient with adenocarcinoma. Scale bars indicate magnifications.

Supplementary Figure S7. Flow cytometry characterization of TNFa receptors and TNFa production. A. List of cytokines and chemokines tested through a multiplex immunoassay (Procarta-plex by Thermofisher) in the supernatants of ST4787 or T23 cells cultured either alone or in the presence of WT, OPN-/-, or MyD88-/- MCs. B.-C. Flow cytometry evaluation of TNFRs (CD120a and CD120b) on adenocarcinoma (T23 murine, 22Rv1 human) and NEPC (TC566 and TC411K murine, and LASCPC-01 human) cells. D. Gating strategy applied for intracellular detection of TNFa in MCs (CD49f-CD45+) by flow cytometry, in the co-cultures between MCs and tumor cells.

Supplementary Figure S6. Quantification of western blot. A. Quantification of western blot reported in Fig. 3G. Western blots were validated twice. All histograms depict mean ± SD of biological replicates (represented by dots). One-way ANOVA followed by Tukey’s multiple comparison test was used for the analysis of significance between samples. P-values are reported as: *, P < 0.05; **, P <0.01; ***, P <0.001; ****, P <0.0001. Where P-value is not indicated, the comparison between groups is not statistically significant.

This study investigated the interaction between apple juice (AJ) and acarbose (A) in modulating glycaemic responses, with the aim of validating in vivo results previously observed in vitro. When administered to rats, AJ alone reduced the glycemic curve, but the combination of AJ with increasing doses of A resulted in higher glycemic responses, suggesting an antagonistic interaction in alpha-glucosidase inhibition. To explore this mechanism, quercetin-3-glucoside (Q-3-G), a major phenolic compound in AJ, was tested for alpha-glucosidase inhibition in vitro. Q-3-G and A together showed reduced inhibitory efficacy compared to either compound alone, consistent with in vivo findings. Ex vivo studies in Caco-2 cells further supported this antagonism. Sucrose hydrolysis experiments showed that low concentrations of Q-3-G increased residual sucrose when combined with moderate concentrations of A, but higher concentrations of Q-3-G favoured sucrose hydrolysis regardless of A levels. The results highlight the antagonistic interaction between Q-3-G and A in inhibiting alpha-glucosidase and emphasise the need to combine in vitro, ex vivo and in vivo studies to evaluate food-drug interactions. This comprehensive approach is essential before advocating the use of functional foods alongside pharmacological therapies.

BACKGROUND:Ovarian cancer (OC) is one of the most aggressive tumors requiring new therapeutic approaches. Immunotherapy represents an opportunity, but to date, OC patients do not appear to benefit from current protocols. A better understanding of the composition of the tumor microenvironment (TME), especially in its immune components, could unveil mechanisms of immune suppression in a useful way to predict response to therapies and develop new therapeutic approaches. METHOD:The MICO (tumor MICroenvironment of Ovarian cancer) study is a single-center observational study. Starting from peritoneal biopsy of high-grade serous ovarian carcinoma (HGSOC), the purpose of the MICO study is to generate tumor patient-derived organoid (PDOs) cultures and evaluate the concordance between in vitro platinum-based chemotherapy sensitivity and in vivo sensitivity. Simultaneously, we will characterize through multiparameter cytofluorimetric analysis the composition of the OC TME, focusing on B lymphocytes and mast cells whose roles in ovarian cancer remain controversial and underinvestigated. Furthermore, patients experiencing recurrence will be longitudinally followed to monitor changes in the TME composition and the responsiveness of PDOs to in vitro stimulation with drugs. DISCUSSION:The association between the composition of the TME, the reactivity of the PDOs, and patients' disease progression will be analyzed to identify whether specific subpopulations of tumor-infiltrating immune cells could be predictive factors of the disease outcomes. The comparison of molecular profiles, in vitro response to drugs, and clinical-pathological data will allow the definition of a pattern capable of predicting the response of the primary tumor for the identification of those patients who may benefit from specific treatment. STRENGTHS AND LIMITATIONS:The results of our study could help to better understand the OC behavior, may have implications for the development of effective immunotherapy and targeted pharmacological therapies for epithelial OC in a personalized medicine perspective. This will be a monocentric trial with an involvement of only 43 patients, so further studies will need to confirm our results. TRIAL REGISTRATION:The clinical trial has been registered at Clinical-Trials.gov with the identifier NCT06272240 on 02/14/2024.

Background: Recently, research on the pathogenesis of multiple sclerosis (MS) has focused on the role of B lymphocytes and the possibility of using specific drugs, such as Ocrelizumab and Rituximab, directed toward these cells to reduce inflammation and to slow disease progression. Objective: We aimed to evaluate the effect of Ocrelizumab/Rituximab on laboratory immune parameters and identify the predictors of treatment responses. Methods: A retrospective single-center study was conducted among patients who received infusion therapy with an anti-CD20 drug to treat MS. Results: A total of 64 patients met the inclusion criteria, with 277 total cycles of therapy studied. Compared with the baseline values, anti-CD20 infusions resulted in absolute-value and percentage decreases in B lymphocyte levels and increased the absolute and percentage levels of NK cells 3 and 5 months after therapy (p < 0.001). After multivariate logistic regression analysis, a reduced percentage level of NK cells 3 months after infusion could predict disease activity 6 months after Ocrelizumab/Rituximab administration (p = 0.041). Conclusions: Lower percentage levels of NK cells 3 months after anti-CD20 infusion correlate with the presence of disease activity 6 months after therapy, confirming a possible protective role of NK cells in MS.