STAT3 Knockdown in B16 Melanoma by siRNA Lipopolyplexes Induces Bystander Immune Response In Vitro and In Vivo

Abstract

Persistent activation of STAT3 plays a major role in cancer progression and immune escape. Therefore, targeting STAT3 in tumors is essential to enhance/reactivate antitumor immune response. In our previous studies, we demonstrated the efficacy of stearic acid-modified polyethylenimine (PEI-StA) in promoting small interfering RNA (siRNA) silencing of STAT3 in B16.F10 melanoma in vitro and in vivo. In the current study, we examine the immunologic impact of this intervention. Toward this goal, the infiltration and activation of lymphocytes and dendritic cells (DCs) in the tumor mass were assessed using flow cytometry. Moreover, the levels of IFN-γ, IL-12, and TNF-α in homogenized tumor supernatants were determined. Moreover, mixed lymphocytes reaction using splenocytes of tumor-bearing mice was used to assess DC functionality on siRNA/lipopolyplexes intervention. Our results demonstrated up to an approximately fivefold induction in the infiltration of CD3(+) cells in tumor mass on STAT3 knockdown with high levels of CD4(+), CD8(+), and NKT cells. Consistently, DC infiltration in tumor milieu increased up to approximately fourfold. Those DCs were activated, in an otherwise suppressive microenvironment, as evidenced by a high expression of costimulatory molecules CD86 and CD40. ELISA analysis revealed a significant increase in IFN-γ, IL-12, and TNF-α. Moreover, mixed lymphocytes reaction demonstrated alloreactivity of these DCs as assessed by high T-cell proliferation and IL-2 production. Our results suggest a bystander immune response after local STAT3 silencing by siRNA. This strategy could be beneficial as an adjuvant therapy along with current cancer vaccine formulations.

Figure 1

B16.F10 cell death after STAT3 knockdown by anti-STAT3 siRNA complexes in vitro. (A) Confluent B16 cells were incubated for 36 hours with titrated doses of anti-STAT3 siRNA (6.25–400 nM) delivered by PEI or PEI-StA complexes. The cells were then lysed, and p-STAT3 levels were detected by Western blot as explained in details in the Materials and Methods section. Percentage of p-STAT3 silencing was calculated at each dose by comparing level of STAT3 of test group versus level of STAT3 in the untreated cells (considered as 100%). The dose-response curve of p-STAT3 silencing percentage was plotted against anti-STAT3 siRNA concentration using a four-parameter logistic function. (B) A representative Western blot analysis of B16 cells when treated with 50 nm of anti-STAT3 siRNA delivered by PEI or PEI-StA complexes. Identical complexes of NT siRNA as well as untreated B16 cells were used as controls. Bands' optical intensities of p-STAT3 (black bars) and STAT3 (gray bars) were quantified and normalized to actin bands using the ImageJ software. Data are shown as mean ± SD of four experiments. Statistical significance was determined compared with control (*P < .05) and PEI-treated (^aP < .05) groups. (C) Cell viability as well as apoptosis after 600 designated treatment were assessed by MTT assay (top) and caspase 3 activity assay (bottom), respectively. Caspase 3 activity after the designated treatment was calculated as the difference in the rates of substrate cleavage in the samples with and without specific caspase 3 inhibitor and expressed as nanomoles per minute per 10⁴ cells. Data are shown as mean ± SD of seven to eight replicates for each sample. Statistical significance was determined compared with control (*P < .05) and PEI-treated (^aP < .05) groups.

Figure 2

Restoration of DC phenotypic maturation in vitro. Primary DC cultures in day 7 were incubated with B16-CM of B16 culture that was treated with anti-STAT3 siRNA or NT siRNA complexes of PEI or PEI-StA for 24 hours. (A, B) FCM analysis of CD86 and CD40 expression on the DC surface, respectively. In histograms (left), black lines indicate DCs exposed to B16-CM from siRNA-treated groups (whether anti-STAT3 or s.c.), whereas gray shade indicates DCs exposed to untreated B16-CM control. Bar graphs (right) shows MFI values after each treatment. Data are presented as a mean of three different measurements (±SD). (C) STAT3 knockdown in DCs restores the capability of DCs to stimulate allogenic T-cell responses. Bars represent the level of T-cell proliferation (left) and IL-2 levels detected in the culture supernatant (right). All data are shown as mean ± SD of at least triplicates for each sample. Statistical significance was determined compared with control (*P < .05) and PEI-treated (^aP < .05) groups.

Figure 3

Tumor regression after STAT3 knockdown by anti-STAT3 siRNA complexes. B16 cells were inoculated subcutaneously (0.75 x 10⁶ cells per mice). NT or anti-STAT3 siRNA were administered daily by i.t. route from day 10 to day 13. At day 14, tumor dimensions were obtained, and tumor volume was calculated accordingly for each subject. Isolated tumors from each group were then lysed for Western blot analysis. (A) The value of tumor volume was plotted for each subject and presented as closed circles (top). Western blot analysis (bottom) shows the expression level of p-STAT3, STAT3, and actin loading control. Bands' optical intensities of p-STAT3 (black bars) and STAT3 (gray bars) were quantified and normalized to actin bands using ImageJ software. Data are shown as mean ± SD of four experiments. Statistical significance was determined compared with control (*P < .05) and PEI-treated (^aP < .05) groups. (B) Pictures of three representative mice per treatment group at the end point of the study (24 hours after last dose).

Figure 4

Activation of tumor-infiltrating DCs in vivo. At the end point of siRNA treatment (as described in Figure 3), tumor samples were isolated and crushed between two slides into uniform cell suspensions. Cellular component as well as supernatant of each group was analyzed by FCM and ELISA, respectively. (A) Bar graph (top) represents the fold increase of CD11c⁺ cells in the tumor cell suspensions of different treatment groups (compared with saline-treated group). Data are shown as mean ± SD of three measurements. Statistical significance was determined compared with control (*P < .05). Histograms (bottom) show the expression pattern of DC activation markers CD86 and CD40 in the tumor cell suspensions obtained from different treatment groups. The percentage of cells of the gated population is indicated in the upper right corner of each histogram, whereas the populations of cells in-gate and out-of-gate were separated by the vertical line in each histogram. (B) Cytokine levels measured in tumor sample supernatants by ELISA were plotted in bar graphs for IL-12 (top) and TNF-α (bottom). Data are shown as mean ± SD of three measurements. Statistical significance was determined compared with control (*P < .05) and PEI-treated (^aP < .05) groups. (C) Allogenic MLR after STAT3 silencing in vivo. Splenocytes from tumor-bearing mice were collected, irradiated, and cocultured with allogenic T cells. Bars represent the level of T-cell proliferation (top), and IL-2 levels were detected in the supernatant (bottom). All data are shown as mean ± SD of five replicates for each sample. Statistical significance was determined compared with control (*P < .05) and PEI (^aP < .05).

Figure 5

Activation of tumor-infiltrating lymphocytes in vivo. Tumor samples from different treatment groups were isolated (as described in Figure 4) and analyzed for the presence and activation of tumor-infiltrating lymphocytes. Bar graphs (left) represent percentages of cells positive for CD3 (T-cell marker) (top) and the amount of IFN-γ detected in the tumor supernatants from different treatment groups (bottom). Data are shown as mean ± SD of three measurements. Statistical significance was determined compared with control (*P < .05) and PEI (^aP < .05). Histograms (right) show the differential lymphocyte population markers CD4, CD8, and NK1.1 for the designated treatment groups. Percentage of cells of the gated population is indicated in the upper right corner of each histogram, whereas the populations of cells in-gate and out-of-gate were separated by the vertical line in each histogram.