Correspondence to Professor Xiongbing Zu; [email protected] ; Professor Zefu Liu; [email protected] ; Professor Jinbo Chen; [email protected] ; Professor Jiao Hu; [email protected]
WHAT IS ALREADY KNOWN ON THIS TOPIC
Immune checkpoint inhibitors have shown limited response rates in bladder cancer. While RC48-antibody-drug conjugates (ADC) (a HER2-targeted ADC) show clinical efficacy alone and combined with immune checkpoint inhibitors, its mechanisms for overcoming immunotherapy resistance remain unclear.
WHAT THIS STUDY ADDS
RC48-ADC reactivates the tumor immune microenvironment by reducing PD-L1 transcription via Hippo pathway activation and inhibiting TAZ/TEAD4 activity. It also promotes the release of chemokines (CCL5, CXCL9, and CXCL14) and recruits cytotoxic T-lymphocytes. In preclinical mouse models, RC48-ADC synergized with CTLA-4 and PD-L1 antibodies.
HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY
These findings provide mechanistic rationale for prioritizing RC48-ADC and CTLA-4mAb combinations in HER2-positive bladder cancer, offering a strategy to overcome anti-PD-1 resistance. The Hippo-TAZ/PD-L1 axis and chemokine signatures may serve as biomarkers for immunotherapy response, guiding patient selection in clinical trials and future treatment guidelines.
Introduction
Bladder cancer (BCa) is the second most prevalent malignant tumor in the urinary system worldwide.1 Increasing clinical evidence suggests that immune checkpoint blockade (ICB) significantly improves BCa survival outcomes. Nivolumab has received FDA approval for the treatment of muscle-invasive bladder carcinoma (MIBC), while the phase III AMBASSADOR trial of pembrolizumab has also demonstrated positive results.2 3 However, the long-term clinical benefits of ICB are limited to a subset of patients4 5 with a low remission rate within 5 years.6 Thus, exploring the molecular mechanisms underlying ICB resistance is essential for developing effective combination therapeutic strategies.
Recently, antibody-drug conjugates (ADCs) have demonstrated convincing efficacy and survival advantages in patients with BCa compared with chemotherapy and immunotherapy.7 8 Disitamab vedotin, or RC48-ADC, is the inaugural domestically manufactured ADC medication sanctioned for commercial use in China. By targeting HER2, RC48-ADC delivers the cytotoxic payload, MMAE (Monomethyl auristatin E), with a killing effect.9 RC48-ADC has been clinically used to treat HER2+ in patients with advanced BCa, showing promising efficacy.10 11 Furthermore, combination therapy clinical trials exploring RC48-ADC with other drugs are ongoing.12–15 The pairing of a PD-1 blocker with RC48-ADC has shown improved effectiveness compared with monotherapy, with reliable safety in BCa.12 15
At the molecular level, HER2, a target of RC48-ADC, is highly expressed in various solid tumors, including bladder, breast, and gastric cancers. A recent large-scale study involving 37 992 patients revealed that the rate of HER2 overexpression in BCa (12.4%) exceeds that in breast cancer (10.5%).16 Overexpression of HER2 and gene amplification are strongly associated with higher risk classification and poor prognosis in metastatic BCa.17 Previous studies have revealed that HER2 expression is negatively correlated with immunotherapy efficacy in BCa.18 Therefore, blocking tumor HER2 with RC48-ADC may improve immunotherapy efficacy, as evidenced by improved RC48-ADC efficacy combined with ICBs in clinical applications. Our recent study has shown that RC48-ADC combined with immunotherapy is more effective than immunotherapy combined with chemotherapy or immunotherapy alone.19 Exploring the changes in the tumor immune microenvironment (TIME) and the molecular mechanisms of RC48-ADC treatment provides valuable cellular and molecular insights supporting the combined use of these therapies.
The Hippo pathway is essential in various biological processes, particularly in tumorigenesis and the development of drug resistance.20 Core proteins in this pathway comprise serine/threonine kinases, such as large tumor suppressors 1 and 2 (LATS1/2) and sterile 20-like kinases 1 and 2 (MST1/2). In addition, the pathway involves downstream effector proteins, including Yes-associated protein 1 (YAP1) and its paralog, transcriptional coactivator with a PDZ-binding motif (TAZ, also known as WWTR1).21 When the Hippo pathway is activated, YAP/TAZ is phosphorylated, leading to its subsequent degradation by the proteasome. This process restricts the nuclear accumulation of YAP/TAZ and prevents their interaction with transcription factors known as transcriptionally enhanced associated domain proteins 1–4 (TEAD1-4), thereby downregulating the transcriptional activity of downstream genes (eg, CTGF and CYR61).22 23
This study revealed the molecular mechanisms by which RC48-ADC regulates tumor PD-L1 expression through the Hippo-TAZ pathway and reinforces CD8+T cell-based immunity by comprehensively performing bioinformatics analysis, in vitro molecular experiments, in vivo functional characterization, and clinical trial validation. This study provides novel therapeutic strategies and molecular evidence for combining RC48-ADC with ICB.
Results
RC48-ADC therapy reshapes the TIME in BCa
To investigate whether RC48-ADC therapy is involved in the BCa anticancer immune process and its specific mechanisms, we used the Kaplan-Meier Plotter tool to analyze the relationship between ERBB2 (HER2 protein-coding gene, targeted by RC48-ADC) expression and anti-PD-1 therapy efficacy. The survival curve showed that ERBB2 expression was negatively correlated with immunotherapy efficacy (median survival time: ERBB2 high/low: 14.09/24.31 months, figure 1A). Similar findings were observed in the Xiangya immunotherapy cohort (figure 1B, online supplemental figure 1A,B). ERBB2 expression in The Cancer Genome Atlas (TCGA) cohorts showed a negative correlation with the three immune scores (figure 1C, online supplemental filgures 1B–E). In the TCGA-BLCA (bladder cancer) cohort, individuals were categorized into groups exhibiting high and low levels of ERBB2 expression, with the classification determined by the median expression value of ERBB2. Various chemokines, major histocompatibility complex (MHC)-related molecules, chemokine receptors, and immunostimulatory factors were downexpressed in the high-ERBB2 group and overexpressed in the low-ERBB2 group (online supplemental figure 1F). Similar results were observed in the cancer immune cycle, including several fundamental steps of immune cell recruitment and infiltration (figure 1D). Furthermore, immune cell infiltration levels (CD8+ T cells, natural killer (NK) cells, CD4+ T cells, and dendritic cells (DCs)) were significantly negatively correlated with ERBB2 expression in several independent algorithms (figure 1E). Similarly, in the Xiangya cohort, ERBB2 expression negatively correlated with tumor immune cycle activity and the infiltration levels of tumor-infiltrating immune cells (TIICs) (figure 1F). Compared with the low ERBB2 group, the high ERBB2 group exhibited lower expression levels of immune effector genes, including those associated with CD8+ T cells, T helper 1 (Th1) cells, NK cells, macrophages, and DCs (online supplemental figure 1G).
As a targeting HER2 ADC, RC48 has been used in multiple clinical studies focused on BCa10 11 and has received FDA (The U.S. Food and Drug Administration) breakthrough therapy designation.24 Furthermore, to explore how RC48-ADC transforms the TIME, we established a Xiangya BLCA RC48-ADC cohort treated with RC48-ADC, which included 7 and 18 treated-treatment and untreated-treatment samples, respectively. Compared with the untreated group, the treated group showed markedly increased expression levels of effector genes linked to NK cells, CD8+ T cells, Th1 cells, macrophages, and DCs. In addition, chemokine and cytokine receptors were significantly upregulated (figure 1G, online supplemental figure 2A). Analysis of the cancer immune cycle and immune cell infiltration revealed significant recruitment and increased infiltration of CD8+ T cells in the RC48-ADC treatment group (figure 1H,I, online supplemental figures 1H and I). To validate our hypothesis at the single-cell level, we performed single-cell transcriptome sequencing and classified cells into eight categories based on recognized biomarkers: epithelial cells, fibroblasts, myofibroblasts, T/NK cells, endothelial cells, B cells, myeloid cells, and plasma cells (figure 1J, online supplemental figures 2B–D). T/NK cells were further classified into NAIVE T, CD4 regulatory T, NK, cytotoxic CD8+ T, Exhausted CD4+ T, Exhausted CD8+ T, and TRM CD8+ cells (online supplemental figures 2E–G). Using the STARTRAC-dist index25 in our specific analysis of CD8+ T cell subgroups, we identified a significant increase in the proportion of cytotoxic CD8+ T cells in the RC48-ADC treatment group (figure 1K). Overall, as a therapeutic target for RC48-ADC cells, high ERBB2 expression indicates an immunosuppressive tumor microenvironment (TME) and resistance to immunotherapy. RC48-ADC treatment reversed the inhibitory TIME into an activated TIME by enhancing the immune capacity associated with CD8+ T cells in BCa. Therefore, we inferred that RC48-ADC not only exerts its own tumor-killing effect but also improves the immune therapy-insensitive TIME by recruiting and activating CD8+ T cells.
Establishment of in vivo and in vitro models of h-HER2-MB49 cells
To investigate the antitumor effect of RC48-ADC in vivo, the first step involved ensuring that RC48-ADC interacts specifically with human HER2 without cross-reacting with murine HER2. Drawing from similar studies,26–28 we established a murine BCa cell line overexpressing h-HER2 (h-HER2-MB49) by stably transfecting the vector or h-HER2 expression into the murine BCa cell line MB49 (online supplemental figure 3A and B). To validate the cytotoxicity mediated by RC48-ADC, we conducted cell proliferation experiments to measure the IC50 values of vector and OE-h-HER2 MB49 and found that the latter exhibited significantly enhanced sensitivity to RC48-induced cytotoxicity (online supplemental figure 3C). Simultaneously, flow cytometry was used to demonstrate the surface expression of h-HER2 in h-HER2-MB49 cells. (online supplemental figure 3D）Subsequently, subcutaneous tumor experiments were performed, the tumors were harvested, and immunofluorescence (IF) staining was conducted to further confirm the suitability of the model for subsequent in vivo studies (online supplemental figure 3E).
RC48-ADC inhibits tumor PD-L1 expression and increases CD8+ T cell infiltration and activity
To study the antitumor effect of RC48-ADC and its role in TIME remodeling, we treated h-HER2-MB49 tumor-bearing immunocompetent mice with RC48-ADC (figure 2A). Treatment with RC48 significantly reduced the tumor burden in mice. Compared with the low-dose group, the high-dose group showed a significantly increased antitumor capability (figure 2B–D). RC48-ADC treatment did not cause unusual changes in the body weight in tumor-bearing mice (online supplemental figure 4A). Based on our earlier analysis, a reliable correlation was established between RC48-ADC treatment and the TME, especially in increasing the immune response related to CD8+ T cells. To further investigate this, we employed flow cytometry to statistically analyze CD8+ T cell abundance and assessed their cytotoxic function indicators across the different treatment groups. The results showed that RC48-ADC treatment significantly increased CD8+ T cell infiltration (CD4-CD8+/CD3+, from 16.45% to 25.47% (RC48-LD), p<0.01; or to 41.53% (RC48-HD), p<0.001, figure 2E,F) and also increased the functional activation of CD8+ T cell groups compared with the vehicle group (figure 2G-I gating strategy is shown in online supplemental figure 4B). Given that immune checkpoints primarily regulate CD8+ T cell activity, we hypothesized that RC48-ADC influences cytotoxic T-lymphocytes (CTL) activity by modulating immune checkpoint levels.29 We detected changes in PD-L1 expression in non-immune cells and found that RC48-ADC treatment reduced PD-L1 expression in the tumor (PD-L1+/CD45_, from 63.73% to 36.91% (RC48-LD), p＜0.05; or to 4.58% (RC48-HD), p＜0.001 (figure 2J,K). The immunohistochemistry and IF results validated this conclusion (figure 2L –O). This relationship was also observed in patients with BCa, where RC48-ADC treatment led to decreased PD-L1 levels and induced activated CD8+ T cells (figure 2P,Q). These results suggested that the enhanced antitumor CTL activity of RC48-ADC may exert its effects by regulating PD-L1 expression.
RC48-ADC regulates tumor PD-L1 transcription levels through the Hippo-TAZ pathway
To further investigate whether RC48-ADC mediates the downregulation of PD-L1 in tumor cells, the transcription and post-transcriptional expression levels of HER2 were assessed in seven BCa cell lines, as well as their sensitivity to RC48-ADC (figure 3A, online supplemental figure 5 A–C). We found that under in vitro conditions, HER2 expression was positively correlated with the effectiveness of RC48-ADC (figure 3B), aligning with previous findings.30 Finally, we selected T24 and 5637, which had high HER2 expression and were sensitive to RC48-ADC, for further experiments based on RC48-ADC clinical guidelines.10 We pretreated BCa cells with IFN-γ to induce PD-L1 expression and subsequently treated them with or without RC48-ADC. Western blot and quantitative reverse transcription PCR (qRT-PCR) analyses revealed that both PD-L1 protein and mRNA levels were significantly reduced in a dose-dependent manner following RC48-ADC treatment (figure 3C-G). Flow cytometry analysis also showed a dose-dependent decrease in PD-L1 membrane levels (T24 from 94.07% to 35.30%, p<0.001; 5637 from 85.03% to 37.90%, p <0.001) (figure 3H–K). These findings suggest that RC48-ADC regulates tumor cell PD-L1 at the transcriptional level.
To investigate the specific molecular mechanism by which RC48-ADC regulates PD-L1 expression, we used RNA sequencing (RNA-seq) to identify the signaling pathways altered in T24 cells following RC48-ADC treatment. This analysis revealed that 2785 genes were significantly upregulated and 2989 were significantly downregulated genes. Key genes of the Hippo pathway (including LATS2, STK3, STK4, MOB1B, and SAV1) and their upstream activating genes (including LATS2, STK3, STK4, MOB1B, SAV1, NF2, and FAT4) were significantly upregulated, whereas the expression of upstream inhibitory genes of the Hippo pathway (AJUBA) was downregulated (figure 3L). Endocytosis and lysosomes, which are crucial for the pharmacological action of RC48-ADC, were significantly enriched in the RC48-ADC treated group, further indicating the effectiveness of RC48-ADC treatment. In addition, the upregulated genes were significantly enriched in the Hippo signaling pathway (figure 3M, top enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways for genes downregulated in online supplemental figure 5D). Activation of the Hippo pathway leads to the phosphorylation of YAP/TAZ, resulting in their degradation via the proteasome, thereby downregulating the transcriptional activity of downstream genes (figure 3N). Given the evidence that RC48-ADC regulates tumor PD-L1 at the transcriptional level, we investigated whether this regulation is mediated by the Hippo signaling pathway. First, we examined the changes in key molecules of the Hippo pathway in RC48-ADC-treated BCa cells (including LATS1/2, MST1/2, YAP/TAZ, and their phosphorylated protein levels) and found that the levels of p-MST, p-LATS, and p-TAZ significantly increased (figure 3O,P). Therefore, we believed that the RC48-ADC treatment was associated with the activation of the Hippo pathway. Based on the magnitude of the changes observed in several nodal molecules of the Hippo pathway, we hypothesized that the MST2-LATS2-TAZ axis was involved in the major change. Subsequently, we transiently knocked down the key upstream and downstream molecules, MST2 and LATS2 of the pathway, and the results showed that the elevated TAZ phosphorylation levels after RC48-ADC treatment were downregulated; moreover, PD-L1 levels were restored (figure 3Q–T), indicating that the Hippo pathway is indeed involved in the modulation of PD-L1 expression by RC48-ADC.
TAZ regulates gene expression by interacting with transcription factors, particularly members of the transcriptionally enhanced associated domain proteins, TEAD family (TEAD1-4).31 To investigate the specific molecular mechanism by which RC48-ADC regulates PD-L1 transcription level changes through the Hippo pathway, we overexpressed a constitutively active mutant TAZ (TAZ-S89A) and a TAZ mutant (TAZ-S89A-F52/53A) with abnormal binding to TEAD in T24 cells.23 Subsequently, we found that TAZ-S89A can significantly reverse the downregulation of PD-L1 induced by RC48-ADC, while TAZ-S89A-F52/53A structurally induces a weakened ability to induce PD-L1 expression (figure 4A–C). Similarly, knockdown of TEAD in T24-TAZ-S89A cells also reduced PD-L1 expression induced by TAZ-S89A (figure 4D,E). Therefore, RC48-ADC regulates PD-L1 expression by regulating the binding of TAZ to TEAD transcription factors. Similar results were also observed in 5637 BCa cells (online supplemental figure 5 E–I).
To further investigate the transcriptional control of PD-L1 by TAZ, we constructed a PD-L1 minimal promoter reporter using a luciferase system (nucleotides −221 to +21). We then cotransfected this reporter gene with TAZ-S89A and TEAD1-4 into T24 cells for analysis. The coexpression of TAZ-S89A and TEAD1-4 led to a significant increase in PD-L1 promoter activity, indicating that TAZ and TEAD1-4 play crucial roles in regulating PD-L1 expression at the transcriptional level (figure 4F). Mutant forms of TAZ, including the TAZ lacking its C-terminal transactivation domain (TAZ-Δ227), TEAD-interaction mutant TAZ (TAZ-F52/53A), and the TEAD-interaction mutant TEAD4 (TEAD4-Y429H),23 could not activate the PD-L1 promoter, indicating the necessity of these specific interactions for PD-L1 transcriptional regulation (figure 4G). We performed deletion scanning analysis to identify the specific PD-L1 promoter regions regulated by TEAD4 and TAZ-S89A. Deletion of nucleotides −100 to −40 prevented the activation by TAZ-S89A and TEAD4, indicating that this region is essential for their regulatory function in the PD-L1 promoter (figure 4H). Within this region, we detected a possible TEAD-responsive element positioned between −74 and −62 (figure 4I). Deleting this TEAD response element significantly diminished the TAZ-S89A-mediated and TEAD4-mediated activation of the PD-L1 promoter, highlighting its critical role in regulating PD-L1 expression (figure 4J). We confirmed TAZ binding to the PD-L1 promoter using the CUT&Tag (Cleavage Under Targets and Tagmentation) assay, detecting that a fragment from the proximal PD-L1 promoter along with the CTGF promoter coprecipitated with TAZ. In contrast, the more distal fragment of the PD-L1 promoter did not co-precipitate, suggesting that TAZ specifically interacts with the proximal promoter region to regulate PD-L1 expression (figure 4K). Collectively, these findings revealed that RC48-ADC regulated PD-L1 transcription levels through activation of the Hippo pathway. This process specifically involves the signaling axis MST2-LATS2-TAZ-TEAD4, which influences the transcriptional activity of PD-L1.
TAZ expression in patients with BCa is associated with the therapeutic effect of PD-1/PD-L1 blockade
To validate our findings specifically that RC48-ADC treatment reduced tumor PD-L1 levels by activating the Hippo pathway to promote TAZ phosphorylation and degradation, we analyzed the TAZ and PD-L1 levels in samples from patients with BCa, RC48-ADC treated and untreated using IF. Compared with samples without RC48-ADC treatment, we detected lower levels of TAZ and PD-L1 in treated samples (figure 5A–C). One factor that contributes to the limited efficacy of PD-1/PD-L1 blockade therapy in certain patients is the dependence of PD-1-related immune resistance on PD-L1 ligands availability within the TME. To further investigate this phenomenon, we analyzed TAZ and PD-L1 expression levels in biopsy samples from 20 patients with BCa treated with PD-1 monoclonal antibodies. As expected, nearly all samples demonstrated a positive correlation between TAZ and PD-L1 expression, and the non-responsive group exhibited lower levels of both TAZ and PD-L1 signals than the responsive group (figure 5D–G). In addition, we found that patients with elevated PD-L1 expression in the tumor region experienced better overall survival (OS) following PD-1/PD-L1 blockade therapy (median OS, 23.47 months vs 8.72 months, p<0.001, figure 5H). Consistent with previous studies, patients with high TAZ expression showed a significant benefit from PD-1/PD-L1 blockade immunotherapy, exhibiting a notably prolonged OS (median OS, 18.60 months vs 7.46 months, p<0.001, figure 5I). In summary, our study revealed that the Hippo-TAZ pathway is a novel molecular mechanism regulating PD-L1 expression, and we developed a potential treatment strategy for patients with BCa through combined RC48-ADC and PD-1/CTLA4 mAb treatment.
RC48-ADC promotes CD8+ T cell recruitment and activation by inducing the release of chemokines from tumors
The aforementioned RC48-ADC treatment in vivo experiments showed that changes in the number and activity of tumor-infiltrating CTLs correlated with RC48-ADC treatment. To verify that CTLs are directly involved in RC48-ADC killing of tumors, we designed in vivo experiments (figure 6A). After IF and flow cytometry validation of the spleen and tumor, we confirmed that CD8+ T cells have been depleted by CD8α antagonism (online supplemental figure 6 A-F). The antitumor effect of RC48-ADC decreased when CD8α was combined with RC48-ADC (tumor volume, RC48-ADC vs RC48-ADC+CD8α, 152.29 vs 646.71 mm3, p<0.01, figure 6B–D), indicating that CD8+T cells are indeed involved in the anti-tumor process of RC48-ADC. After isolating lymphocytes from human peripheral blood and purifying them successfully, we obtained a relatively homogeneous population of CD8+ T cells, which were subsequently used for the T-cell cytotoxicity assay and chemotaxis experiment (figure 6E,F). Next, we determined the effect of RC48-ADC on the inhibitory immune checkpoint PD-L1 and its impact on CTL activity through in vitro T-cell killing experiments. As expected, RC48-ADC treatment significantly enhanced T cell-killing activity (figure 6G–K). We further investigated the mechanisms underlying the increased number of tumor-infiltrating CTLs. The recruitment of CTLs is often mediated by cytokines. Our findings demonstrated that compared with the control group, the conditioned medium from RC48-ADC-treated cells displayed a significantly enhanced chemotactic effect on CTLs (figure 6L–M). RC48-ADC-treated BCa cells upregulated the cytokine-cytokine receptor-related pathway. From this pathway, we selected the upregulated chemokines CCL5 and CXCL14 (online supplemental figure 6G,Table 1). Previous studies, as well as our previous study, have also demonstrated that CXCL9 and CXCL10 are key chemokines for recruiting CD8+ T cells.32–35 We measured the transcription and protein secretion levels of these chemokines in both the control and RC48-ADC treatment groups. Our findings confirmed that CCL5, CXCL9, and CXCL14 were the main chemokines involved in the recruitment of CTLs by RC48-ADC treatment (figure 6N,O). When three neutralizing antibodies were used to individually block CCL5, CXCL9, and CXCL14, it was observed that the enhancement of CD8+ T cell chemotaxis was partially restored. This indicates that all three chemokines collectively contribute to the augmentation of CD8+ T cell chemotaxis mediated by RC48 (figure 6P,Q). In summary, RC48-ADC treatment mediated the downregulation of tumor cell membrane PD-L1 and promoted the secretion of chemokines CCL5, CXCL9, and CXCL14, thereby recruiting and activating CTLs.
Synergistic effect of RC48-ADC and CTLA-4/PD-1 mAb in treating BCa in immunocompetent mice
Phase II clinical studies on combination therapy using RC48-ADC with PD-1 or CTLA-4 for the treatment of urothelial carcinoma are currently underway,36 37 aiming to determine the efficacy of combination therapy and its broader applicability. Based on prior findings showing that RC48-ADC downregulates tumor PD-L1 expression to enhance antitumor immunity, we hypothesized that RC48-ADC may have an effect similar to that of the PD-L1 mAb, although their mechanisms of action are not exactly the same. To verify this, we treated h-HER2-MB49-bearing mouse models with RC48-ADC, CTLA-4 mAb, PD-1 mAb, RC48-ADC plus CTLA-4 mAb, RC48-ADC plus PD-1 mAb, or the control group (figure 7A). The results showed that in the h-HER2-MB49 BCa model, compared with the control group, RC48-ADC significantly reduced tumor growth on day 12 post-treatment (mean tumor size: 1350.50 mm3 vs 425.31 mm3; p<0.01). The combination of RC48-ADC with either CTLA-4 mAb or PD-1 mAb showed better therapeutic effects. Importantly, when combined with CTLA-4 mAb treatment, RC48-ADC exhibited the best tumor growth suppression (mean tumor size: 1350.50 vs 26.12 mm3; p<0.001, figure 7B–D). Consistent with our mechanistic findings, IF and flow cytometry analyses indicated that t RC48-ADC treatment, whether administered as monotherapy or in conjunction with PD-1/CTLA-4 monoclonal antibodies, significantly diminished tumor PD-L1 expression, increased CD8+ T cells population, and enhanced their activity within the TME in immunocompetent mice. Notably, combination therapy demonstrated a more pronounced effect (figure 7E–H). To further investigate whether PD-L1 expressed by tumor cells contributes to enhancing the efficacy of ICB mediated by RC48, we established PD-L1 knockout MB49 cell line and conducted corresponding in vivo experiments (online supplemental figure 7A-C). Our results demonstrated that the ability of RC48 to enhance ICB efficacy was significantly diminished following PD-L1 knockout (online supplemental figure 7 D-F). Additionally, we evaluated the functional state of CD8+ T cells across different experimental groups. In accordance with our findings, compared with the wild-type group, the cytotoxic activity and exhaustion reversal trends of CD8+ T cells were less pronounced after PD-L1 knockout (online supplemental figure 8A-C). These observations suggest that PD-L1 plays a critical role in augmenting the efficacy of RC48-mediated ICB. These results indicated that RC48-ADC could serve as a promising combinatorial agent to enhance the efficacy of ICB monotherapy in BCa.
Discussion
PD-L1-PD-1 binding on the surface of activated T cells is a key regulatory step in the transduction of inhibitory checkpoint signals in T cells.38 Numerous studies have confirmed that PD-L1 is rarely expressed in normal tissues, and elevated PD-L1 expression has been linked to unfavorable outcomes in numerous solid tumors.39–43 This suggests that PD-L1, with its selective expression characteristics, can serve as a target for tumor treatment. To some extent, the effectiveness of PD-1/PD-L1 inhibition therapy is related to tumor PD-L1 expression.44 Therefore, it is crucial to explore and understand the specific molecular mechanisms underlying changes in tumor PD-L1 levels. RC48-ADC has shown promising results in BCa treatment10 45 and demonstrated good synergy when combined with ICIs; however, its regulatory characteristics and mechanisms in the TIME remain unclear. This study is the first to provide a detailed report on the ability of RC48-ADC to reduce PD-L1 expression on the surface of tumor cells, recruit and reactivate CD8+ T cells, and thereby reshape the TIME. Mechanistically (online supplemental figure 9), this study confirmed through in vivo and in vitro experiments that RC48-ADC reduced the transcription level of PD-L1 by activating the Hippo pathway in tumor cells to inhibit the activity of TAZ/TEAD4 transcription factor. This regulation was verified in clinical samples obtained from patients with BCa. Simultaneously, RC48-ADC promoted the release of more cytokines, such as CCL5, CXCL9, and CXCL14, thereby recruiting more CTLs into the TME. Preclinical data indicated a significant synergistic effect when RC48-ADC was combined with PD-1 mAb for BCa treatment in immunocompetent mice, and this effect was even more significant when combined with CTLA4 mAb. Clinically, we observed that, compared with patients with BCa who responded to anti-PD-1 treatment, PD-L1 and TAZ levels in the tumor area of non-responders were lower. In summary, our study revealed a novel mechanism underlying PD-L1 regulation, identified potential prognostic markers for predicting the efficacy of anti-PD-1 therapy, and proposed new combination treatment strategies for BCa.
The results of the preclinical experiments indicated that RC48-ADC showed good synergistic effects when combined with either PD-1 or CTLA-4 mAb; however, the effect was superior with CTLA-4 mAb. Prior preclinical studies suggested that the combined use of anti-PD-1 and anti-PD-L1 antibodies promotes immunotherapy by targeting different qualitative CTLs and altering their phenotypes.46 Some clinical trials also combined the use of anti-PD-1 and anti-PD-L1; however, many combination therapy studies have been halted owing to significant adverse reactions. This outcome may stem from a nonspecific combination of these reactions, in which the use of two types of antibodies excessively activates the body’s immune system, leading to adverse reactions. Unlike PD-L1 mAb, which binds to PD-L1 on the cell surface, RC48-ADC specifically regulates the transcriptional activity of PD-L1 within tumor cells, thereby avoiding over-activation of the human immune system. Therefore, the combined use of RC48-ADC and PD-1 mAb did not produce the aforementioned strong adverse reactions, consistent with current clinical trial results.47 48 Blocking CTLA-4 primarily involves regulating T cell activation and suppressing DC activity through Treg cells in lymph nodes/tissues, whereas blocking PD-1 mainly involves inhibiting the activation of effector T cells and NK cells and inducing Treg cell differentiation in peripheral tissues.49–51 Meanwhile, many clinical studies on melanoma, lung cancer, gastric cancer, and prostate cancer have confirmed the effectiveness and safety of their combined use.52–56 In summary, we hypothesized that RC48-ADC has a synergistic effect when used with PD-1 or CTLA-4 mAb, and this has been validated in preclinical combination therapy experiments. The results showed that the combined use of RC48-ADC and CTLA-4 mAb outperforms that of PD-1 mAb, given that the synergistic effects are significantly greater than those of single-drug treatment. In conclusion, the combined use of RC48-ADC and PD-1 or CTLA-4 mAbs holds promise.
RC48-ADC, the first approved and marketed HER2-targeted ADC in China, has gradually been used for BCa treatment. Numerous clinical trials are currently investigating its therapeutic potential in combination with other drugs, with a primary focus on immunotherapeutic agents.14 47 48 57 Previous studies have identified a negative correlation between HER2 expression and the activation of the Hippo signaling pathway.58–60 In addition, reports have suggested that other ADCs can activate the Hippo pathway during treatment, thereby conferring drug resistance.61 62 After pathway enrichment analysis, we hypothesized that the Hippo pathway might serve as a regulatory mechanism by which RC48 modulates PD-L1 expression in tumor cells, and this has been rigorously demonstrated through a series of molecular experiments. A previous study reported that a novel ADC promoted the secretion of CXCL9 and CXCL10 in the TME.63 This finding aligns with the effects of RC48-ADC, which enhances the secretion of CCL5, CXCL9, and CXCL14 from tumor cells, thereby facilitating the recruitment of CTLs to the TME. The description of the molecular mechanism deepens our understanding of the characterization change; however, other possibilities worth exploration are as follows: the upstream mechanism by which RC48-ADC directly influences the Hippo pathway; the intracellular mechanism pathway of RC48-ADC affecting chemokine secretion; whether RC48-ADC may alter the TIME by inducing immunogenic cell death of tumor cells; drug safety verification in vivo experiment section; using a subcutaneous tumor model does not accurately represent how therapeutics traffic into the bladder as an orthotopic bladder tumor model would. However, these questions require further investigation.
In conclusion, through rigorous computational analysis, in vitro and in vivo functional characterization, and clinical validation, we identified a new molecular mechanism whereby RC48-ADC regulates PD-L1 through the Hippo-TAZ pathway and reactivates CD8+T cells, providing a new treatment strategy for combination therapy involving RC48-ADC and ICIs.
Methods
Cell culture and treatment
Human BCa cell lines (5637, UMUC3, J82, T24, RT4, RT112, and TCCSUP) and the mouse BCa cell line MB49 were acquired from Meisen CTCC (Jinhua, China) and Procell Life Science & Technology (Wuhan, China), respectively. The cells were cultured in media such as 1640, DMEM (dulbecco's modified eagle medium), or MEM (Eagle's Minimum Essential Medium)(BasalMedia, China) supplemented with 10% fetal bovine serum (Gibco, USA) and 1% penicillin-streptomycin (NCM Biotech, China). All cultures were kept in an incubator set to 37°C with a 5% CO2.
Cell transfection
Stable transfection: Lentiviral plasmids for HER2 overexpression and its negative control, PD-L1 Crispr/Cas9 are sourced from Shanghai GK Biotechnology. Detailed information on the sgRNA targeting sequences can be found in online supplemental Table 3. One day before transfection with the lentiviral vector, plate cells in a 6-well plate, ensuring that the cell confluence is 20%–30% on the second day for transfection. At this point, use the GK Gene Lentiviral Stable Transfection Reagent Kit. Add 1 mL of culture medium, 40 µL of infection reagent P solution, and 1×108 IU/µL of the target gene viral solution or the control group viral solution to each well. After 16 hours, replace the medium with 2 mL of complete culture medium per well. Start selecting with medium containing puromycin after 48–72 hours of transfection. Pass the cells 2–3 times, continuously selecting during the process. After the blank group cells have completely died, retain sufficient cells from each group for subsequent Western Blot and qRT-PCR verification of transfection efficiency.
Transient transfection:TAZ-S89A plasmid, TAZ-S89A-F52/53A plasmid, Luc-hPD-L1 promoter (−221 to +21) plasmid, TEAD1-4 plasmids, TAZ-A227 plasmid, TEAD4-Y429H plasmid, hPD-L1 promoter (−221 to +21)-del (−221 to −160) plasmid, hPD-L1 promoter (−221 to +21)-del (−160 to −100) plasmid, hPD-L1 promoter (−221 to +21)-del (−100 to −40) plasmid, TEAD response element (−74 to −62) deleted PD-L1 promoter plasmid, CV405 Renilla plasmid and siMST2, siLATS2, siTEAD RNA are sourced from Shanghai GK Biotechnology. Detailed information on the siRNA targeting sequences can be found in online supplemental Table 3. Seed cells to achieve 70%−90% confluence at the time of transfection. Dilute Lipofectamine 3000 Reagent in Opti-MEM Medium (2 tubes) and mix thoroughly. Prepare a DNA master mix by diluting the DNA in Opti-MEM Medium, then add P3000 Reagent and mix well. Combine the diluted DNA with the Lipofectamine 3000 Reagent in a 1:1 ratio and mix. Add the DNA-lipid complex to the cells.
Antibody
The antibodies used in the experiment for Western Blot, Immunofluorescence, Immunohistochemistry, CUT&Tag, flow cytometry analysis and neutralization antagonism are presented in online supplemental table 2.
RNA Isolation, qRT-PCR
Total RNA was isolated with the SteadyPure Universal RNA Extraction Kit (Accurate Biotechnology, China) and reconstituted in RNase-free water (Accurate Biotechnology, China). Total RNA was converted into cDNA using Evo M-MLV RT Premix for qPCR (Accurate Biotechnology, China). qRT-PCR was performed using a SYBR Green Premix Pro Taq HS qPCR Kit (Accurate Biotechnology, China). The procedures were performed based on the manufacturer’s guidelines. The primers used are listed in online supplemental Table 3.
Western blot
Protein samples were loaded onto a polyacrylamide gel for electrophoretic separation. Subsequently, the proteins were transferred onto polyvinylidene fluoride membranes. Skim milk or protein-free rapid blocking buffer (1×) (Epizyme Biotech, China) was used to block nonspecific binding sites. The membranes were subsequently incubated with a specific primary antibody to facilitate binding to the target protein. Next, the membrane was washed with buffer to eliminate any unbound primary antibodies and then incubated with a specific secondary antibody. Following an additional buffer wash to clear unbound secondary antibodies, the target protein was visualized using a chemiluminescent substrate. The primary antibodies used are detailed in online supplemental Table 2. The primary antibodies included HER2/ErbB2 Polyclonal antibody, Proteintech, 51105-1-AP; Anti-PD-L1 antibody (EPR19759), abcam, ab213524; Anti-PD-L1 antibody (EPR20529), abcam, ab213480; GAPDH Monoclonal antibody, Proteintech, 60004-1-Ig; YAP1 Rabbit Polyclonal Antibody, Proteintech, 13584-1-AP; TAZ Rabbit Polyclonal Antibody, Proteintech, 23306-1-AP; STK4/MST1 Rabbit Polyclonal Antibody, Proteintech, 22245-1-AP; STK3 Rabbit Polyclonal antibody, Proteintech, 12097-1-AP; LATS1 Rabbit Polyclonal Antibody, Proteintech, 17049-1-AP; LATS2-Specific Rabbit Polyclonal Antibody, Proteintech, 20276-1-AP; Phospho-YAP (Ser127) (D9W2I) Rabbit mAb, Cell Signaling Technology, #13008T; Phospho-TAZ (Ser89) (E1X9C) Rabbit mAb, Cell Signaling Technology, #59971; Anti-STK3/MST-2 (phospho T180)+MSP/MST1 (phospho T183) antibody, abcam, ab79199; Anti-LATS1/WARTS (phospho T1079)+LATS2 (phospho T1041) antibody (EPR27261-8), abcam, ab305029; Anti-PAN TEAD antibody (EPR15629), abcam, ab197589.
Immunofluorescence
Sample preparation: Tissue slices were treated with 4% paraformaldehyde for half an hour and subsequently rinsed with phosphate-buffered saline (PBS). Antigen retrieval: Specimens were heated in sodium citrate buffer (pH 6.0) and allowed to cool. Blocking: Specimens were exposed to 5% goat serum for 1 hour to prevent non-specific binding. Primary antibody: Primary antibodies were added and incubated overnight at 4°C, followed by washing with PBS. Secondary antibody: Fluorophore-conjugated secondary antibodies were then added and incubated for 1 hour in the dark, after which the samples were washed. Nuclear staining: Mounted with DAPI-containing medium. Microscopy: Observed and imaged using fluorescence microscopy. The primary antibodies included: Anti-PD-L1 antibody (EPR19759), abcam, ab213524; anti-PD-L1 antibody (EPR20529), abcam, ab213480; anti-CD8 alpha antibody (EPR21769), abcam, ab217344; anti-CD8 alpha antibody (CAL66), abcam, ab237709; Granzyme B Polyclonal antibody, Proteintech, 13588-1-AP; TAZ Rabbit Polyclonal Antibody, Proteintech, 23306-1-AP.
Immunohistochemistry
Antigen retrieval: Samples were heated in sodium citrate buffer (pH 6.0) for 10 min and then allowed to cool. Blocking: To prevent non-specific binding, the samples were incubated with 5% goat serum for 1 hour. Primary antibody: Primary antibodies were administered and incubated overnight at 4°C, followed by washing with PBS. Biotinylated secondary antibodies were incubated with the samples for 1 hour, samples were then washed. Color development: Incubation with streptavidin-biotin-peroxidase complex (ABC reagent) for 30 min, washing, and development with DAB substrate. Counterstaining sections were counterstained with hematoxylin, rinsed, dehydrated, and mounted. Microscopy: Observed and imaged using a light microscope.
Dual-luciferase reporter assay
Cell seeding: Cells were seeded into 24-well plates and cultured overnight until they reached 70%–80% confluency. Transfection: Cells were transfected with Renilla luciferase control plasmid, firefly luciferase reporter plasmid, and other required construct based on the manufacturer’s guidelines. Incubation: Cells were incubated for 24–48 hours at 37°C with 5% CO. Lysis: The cells were lysed with a passive lysis buffer for 15 min at room temperature with gentle shaking. Luciferase assay: The Dual-Luciferase Reporter Assay System (Promega, USA) was used following the manufacturer’s instructions. Data analysis relative luciferase activity was calculated and analyzed.
CUT&Tag assay
CUT&Tag analysis was conducted using the NovoNGS CUT&Tag 3.0 high-sensitivity reagent kit (Novoprotein Scientific, China), in accordance with the manufacturer’s instructions. Briefly, 1×105 T24 cells were harvested. A 37% formaldehyde solution was carefully added to the cells and incubated for 2 min. Crosslinking was stopped, and the samples were rinsed with a wash buffer. The cells were concentrated using ConA beads and subsequently resuspended in 50 µL of primary antibody buffer containing anti-TAZ antibody (Cat. 23306-1-AP, USA). The primary antibody buffer was then discarded, and 100 µL of anti-rabbit IgG antibody buffer, diluted at 1:100, was added and incubated for 1 h. The beads were then washed three times with the antibody buffer before incubation with protein A/G-Tn5 transposase for 1 hour. The cells were re-mixed in 50 µL of tagmentation solution (10 mM magnesium chloride within ChiTaq solution) and kept at 37℃ for 60 min. Tagged DNA extraction beads were used to extract DNA fragments for agarose gel electrophoresis. Primers used for PCR amplification of the PD-L1 promoter are shown in the supplemental data.
T cell-mediated cytotoxicity assay
Human peripheral blood lymphocyte isolation fluid was used to obtain lymphocytes (Yanjin Biological, China), which were cultured in CTS AIM V serum-free medium (SFM) (Gibco, USA) with ImmunoCult Human CD3/CD28/CD2 T cell activator (STEMCELL Technologies, USA) and interleukin-2 (IL-2) (PeproTech, USA) for 1 week, following the manufacturer’s protocol. Anti-CD3 antibody (eBioscience, USA) and IL-2 antibodies were used. CD8+ T cells were purified from PBMCs using the Human CD8+ T Cell Isolation Kit (BioLegend, USA). Cancer cells were plated in culture dishes and allowed to adhere overnight, then treated with RC48-ADC for 24 hours, followed by co-incubation with activated T cells for another 24 hours at a cancer cell-to-activated T cell ratio of 1:3. Quantitative analysis was performed using the CCK-8 assay, followed by crystal violet staining and photography. CD8T cells after different groups of cocultivation are used for dyeing the Live/Dead, CD45, CD3, CD4, CD8, GZMB, IFN-γ flow analysis to evaluate the function of the CD8T cells activity. (The specific color scheme can be found in Section Fluorescence-activated cell sorting analysis of tumor immune cell spectrum, and the detailed information of the antibody can be found in online supplemental Table 2).
Chemotaxis assay
Chemotaxis assay was conducted using a 24-well transwell plate with a 3 μm pore size (Corning, USA). Cancer cells were plated in culture dishes and allowed to adhere overnight, then treated with RC48-ADC for 24 hours, neutralizing antibodies against CCL5, CXCL9, or CXCL14 were administered to the respective treatment groups CD8+ T cells were purified from PBMCs using the Human CD8+ T Cell Isolation Kit (BioLegend, USA). Isolated cells (1×105) in 200 μL were placed in the upper chamber, while 600 μL of supernatant from various treated cell lines was added to the lower chamber. Following a 6-hour incubation at 37°C, the migrated cells in the lower chamber were collected and stain Live/Dead, CD45, CD3, CD4, CD8, and analyzed and quantified them by flow cytometry. The detailed information of the antibody can be found in online supplemental table 2.
ELISA
The concentrations of CXCL9, CXCL10, CCL5, and CXCL14 in the culture supernatants of human BCa cells were measured using human-specific ELISA kits (Proteintech, USA; CXCL14 from Abcam, USA). Assays were performed based on the manufacturer’s protocols, and optical density values were recorded (ThermoFisher Scientific, USA) to account for the diverse secretion levels of cytokines and chemokines. The data underwent log2 transformation for standardized analysis.
Fluorescence-activated cell sorting analysis of tumor immune cell spectrum
Single-cell suspensions of MB49 tumors from mouse samples were prepared by rapid and gentle dissociation using hyaluronidase (Cat: H3506, Sigma, USA), collagenase IV (Cat: C5138, Sigma, USA), and DNase I (Cat: DN25, Sigma, USA). The cell suspension was filtered through 70 μm cell strainers (BIOFIL, China) with physical grinding. Dead cells were eliminated using the Zombie Aqua Fixable Viability Kit after blocking with an anti-mouse CD16/CD32 antibody. The remaining cells were stained for 20 min with APC-Fire 750 anti-CD45, BV421 anti-CD3, BV605 anti-CD8a, and PerCP/Cyanine5.5 anti-mouse CD4, followed by staining for intracellular GZMB and IFN-γ using PE anti‐GZMB, PE‐Dazzle 594 anti‐IFN‐γ after fixation and permeabilization (BD Bioscience, USA). In order to simultaneously evaluate the killing activity and exhaustion indicators of CD8 T cells in different groups, use another color scheme (APC-Cy7 anti-CD45, PE-Cy7 anti-CD3, BV605 anti-CD8a, BV785 anti-CD11b, and PerCP/Cyanine5.5 anti-CD4) followed by staining FITC anti-GZMB, APC anti-PD-1, PE-Dazzle 594 anti-IFN-γ, BV421 anti-TCF, PE anti-TOX). To assess PD-L1 expression on the surface of human cell lines, the cells were stained with APC anti-CD274. Dead cells were removed using the Zombie Aqua Fixable Viability Kit. All antibodies used were acquired from BioLegends. The labeled cells were examined using an Aurora flow cytometer (Cytek, USA), and the resulting information was subsequently processed via the FlowJo software (V.10.0). Detailed antibody information is provided in online supplemental Table 2.
Mouse tumor generation and implantation
Female C57BL/6 mice aged 6–7 weeks were sourced from the Central South University Experimental Animal Center. All surgical procedures involving these mice received approval from the Animal Care and Use Committee at Xiangya Hospital, Central South University (Project No: CSU-2022-0647). h-HER2-MB49 cells (5×105) in a volume of 100 µL were subcutaneously injected into 6-week-old C57BL/6 female mice. Approximately 1 week later, once the tumor size reached 50–100 mm³, the mice were randomly allocated into several groups. These groups were established to evaluate the effectiveness of RC48-ADC as a standalone treatment, and the mice were administered RC48-ADC (5 or 10 mg/kg, intravenous) or the control drug every 3 days. Furthermore, to determine whether the killing of tumors by RC48-ADC depends on CD8+ T cells, InVivoPlus anti-mouse CD8α (Cat: BP0117, Bioxcell, USA) (100 µg/each/3 days) or an isotype control IgG2b (Cat: BP0090, Bioxcell, USA) were used to deplete CD8+ T cells in mice based on RC48-ADC treatment. In addition, the therapeutic effect of RC48-ADC combined with checkpoint blockade was evaluated. h-HER2-MB49 cells (5×10⁵) were subcutaneously injected into 6-week-old female C57BL/6 mice. The mice received RC48-ADC (10 mg/kg, administered intravenously), along with intraperitoneal injections of anti-mouse PD-1 (InVivo mAb, Bioxcell, USA) or CTLA-4 mAb (Bioxcell, USA) (100 µg per dose every 3 days). Mice were treated with either the combination therapy or monotherapy for 12 days. Afterward, tumors were harvested for fluorescence-activated cell sorting analysis, rapidly frozen in liquid nitrogen, and also processed for paraffin embedding for further histological analysis.
Clinical tissue samples
Paraffin sections of patients with BCa at Xiangya Hospital of Central South University before and after treatment with RC48-ADC were collected.
RNA-seq analysis
The BCa cell line T24 was classified into two groups (Control/RC48-ADC: 3 vs 3) based on whether it was treated with RC48-ADC. Total RNA was extracted, and RNA-seq was performed (BGI Co, Shenzhen, China). The Limma R toolkit combined with empirical Bayes techniques was used to detect differentially expressed genes (DEGs) from the RNA expression dataset of the two cohorts. Criteria for DEG selection were set at |log fold change (log FC) | > 1 and an adjusted p<0.05. KEGG analyses were conducted on identified DEGs by Cluster Profiler R package.
Data source and processing
Xiangya BLCA Cohort: Previous studies64 22 reported that 57 eligible patients with BLCA at Xiangya Hospital underwent surgical interventions, including transurethral bladder tumor resection and radical cystectomy. High-throughput RNA-seq was performed on all samples to obtain transcriptome information. The Xiangya BLCA cohort was constructed using RNA-seq data, clinicopathological features, and follow-up information from these patients (online supplemental Table 4).
Xiangya BLCA Immunotherapy Cohort: This cohort included 25 patients with MIBC were included. Prior to initiating neoadjuvant anti-PD-1 therapy, all tissue samples were collected through diagnostic transurethral resection of the bladder tumor, based on the patient’s treatment response and preference. The clinical and pathological details of these patients are provided in online supplemental table 5.
Xiangya BLCA RC48-ADC cohort: This cohort comprised 25 patients with MIBC in the Xiangya BLCA RC48-ADC queue, including 7 and 18 RC48-ADC treated and untreated patients, respectively. ADC-treated patients were administered RC48-ADC at a dose of 2.0 mg/kg, with a maximum dose of 120 mg, via intravenous infusion over 60–90 min every 2 weeks. After 2–6 cycles of treatment, the neoadjuvant treatment was discontinued and the surgical specimen was collected 2–4 weeks later. The Xiangya BLCA RC48-ADC cohort was then constructed using the RNA-seq data. Detailed clinical and pathological characteristics are listed in online supplemental Table 6.
TCGA database was used to obtain the BLCA RNA expression matrix from the UCSC Xena database. The RNA-seq data were normalized using Log2 transformation. To classify tumors as having high or low ERBB2 expression, we used the median TPM (Transcripts Per Million) value of ERBB2 from bulk RNA sequencing data across all tumor samples as the cut-off. Samples with ERBB2 TPM values above the median were classified as ‘high expression’, while those below the median were categorized as ‘low expression’.
Assessment of the immune characteristics of TME in BLCA
In our previous studies,33–35 64 65 we analyzed the immune characteristics of the TME in BLCA. Kaplan-Meier Plotter (https://kmplot.com/analysis/) was used to generate survival curves and assess the efficacy of immunotherapy. The data related to its immunotherapy include bladder (n=73), esophageal adeno (n=103), glioblastoma (n=28), hepatocellular carcinoma (n=22), and HNSCC (n=5), melanoma (n=423), NSCLC (n=21), NSLC (n=22), urothelial (n=348). The Tumor Immune Phenotype Tracking platform (http://biocc.hrbmu.edu.cn/TIP/) was employed to evaluate tumor immune cycle activity, providing insight into the effectiveness of antitumor immune responses. Five independent algorithms (TIMER, CIBERSORT, CIBERSORT-ABS, MCP-COUNTER, and XCELL) were used to estimate the infiltration levels of TIICs. The TIME was extensively assessed by examining the effector genes of immune cells, chemokine ligands, and their receptors, key histocompatibility complex (MHC) molecules, and immune-activating factors.
Single-cell RNA-sequencing
We conducted single-cell RNA sequencing (OE Biotech Co., Shanghai, China) on four treated and two untreated samples from the RC48-ADC cohort. Detailed procedures for sequencing, data preprocessing, and analysis have been described previously.33–35 64 65 Cellular subpopulation analysis was performed through the following workflow: Principal component analysis (PCA) was first executed using the RunPCA function, followed by application of t-distributed stochastic neighbor embedding (t-SNE) through the RunTSNE function based on PCA-reduced dimensions. Cell clusters were biologically annotated by integrating automated predictions from the SingleR package with canonical marker gene expression profiles documented in existing literature. Notably, the cellular population preliminarily identified as T lymphocytes underwent iterative subclustering for functional subset characterization. The Ro/e metric was used to assess tissue preference of T cell clusters, following the STARTRAC framework proposed by Zhang et al in Lineage tracking reveals dynamic relationships of T cells in colorectal cancer.25 Briefly, Ro (observed cell number) refers to the actual count of T cells belonging to a specific cluster-tissue combination derived from our scRNA-seq analysis pipeline. The expected number of cells (e) is calculated based on the χ2 test under the assumption of random distribution across tissues and clusters.
Specifically, for each combination of T cell cluster and tissue, the expected cell number (e) is determined by: e=(total cell number in the cluster)×(total cell number in the tissue)/(grand total cell number).
Statistical analysis
Data are presented as mean±SD. An independent sample Student’s t-test was used to compare the averages of two continuous variables with a normal distribution. For comparisons involving non-normally distributed data, the Mann-Whitney U test was applied for two groups, and the Kruskal-Wallis test was applied for three or more groups. Categorical variable frequencies were compared using Pearson’s χ² test or Fisher’s exact test, depending on suitability. To evaluate variations in continuous variables among multiple groups, a one-way analysis of variance was used, with the inclusion of Brown-Forsythe and Welch tests when necessary. Correlation strength between variables was assessed using Pearson or Spearman correlation coefficients. Kaplan-Meier survival curves were used for prognostic analysis of dichotomous variables, and the log-rank test was used to evaluate statistical differences. Statistical significance was set at p<0.05. Data analysis was performed using R software (V.4.0) and GraphPad Prism V.8.
This work was supported by the National Natural Science Foundation of China (82303760, 82373337), the China Postdoctoral Innovation Talents Support Program (BX20230431), the China Postdoctoral Science Foundation (2023M733951), Hunan Natural Science Foundation (2024JJ2093, 2023JJ40946, 2024JJ6647), and the Youth Science Foundation of Xiangya Hospital (2022Q20, 2023Q9).
Data availability statement
Data are available in a public, open access repository. Data are available on reasonable request. All data are available in the main text or the supplementary materials. Buk RNA-seq data for Xiangya BLCA Cohort can be accessed via the Gene Expression Omnibus under accession GSE18871 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE188715),64 TCGA database was used to obtain the BLCA RNA expression matrix from the UCSC Xena database.66 GEO-Pan cancer-Immunetherapy can be accessed via Kaplan-Meier Plotter (https://kmplot.com/analysis/)67 Further information and requests for resources (Buk RNA-seq data for Xiangya BLCA Immunotherapy Cohort, Xiangya BLCA RC48-ADC Cohort and Single-cell RNA-seq for RC48-ADC Cohort) should be directed to, and will be fulfilled by, the lead contact, Jiao Hu ([email protected]).
Ethics statements
Patient consent for publication
Not applicable.
Ethics approval
This study involves human participants, and paraffin sections of patients with Bca at Xiangya Hospital of Central South University before and after treatment with RC48-ADC were collected. The study protocol was approved by the Institutional Review Board at Xiangya Hospital, Central South University. (Project No: CSU-2022-0647). Participants gave informed consent to participate in the study before taking part.
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Abstract
Background
Immune checkpoint inhibitors have shown limited response rates in bladder cancer. RC48-antibody-drug conjugate (ADC) shows potential for combination with immune checkpoint inhibitors. This study aimed to elucidate RC48-ADC’s mechanism in sensitizing tumors to immunotherapy and identify optimal combination strategies.
Methods
Bioinformatics (The Cancer Genome Atlas, GEO, Xiangya cohorts) analyzed correlations between HER2, immune markers, and therapy response. The h-HER2-MB49 and sg-PD-L1-MB49 cell line was generated. In vitro/vivo models assessed RC48-ADC’s impact on the tumor immune microenvironment using flow cytometry, immunofluorescence, co-culture, chemotaxis, CUT&Tag assays, transcriptomics, and ELISA. Subcutaneous tumor models evaluated combination therapies. At the clinical level, bladder cancer immune therapy cohort tissue microarrays were used, and the aforementioned mechanisms were validated using immunohistochemistry and immunofluorescence.
Results
HER2 expression is associated with an inhibitory tumor immune microenvironment and resistance to immunotherapy. RC48-ADC treatment can reactivate this HER2-related inhibitory tumor immune microenvironment, thereby enhancing immunotherapy effectiveness. Mechanistically, RC48-ADC reactivates the tumor immune microenvironment by reducing PD-L1 transcription via Hippo pathway activation. It also promotes the release of chemokines (CCL5, CXCL9, and CXCL14) and recruits cytotoxic T-lymphocytes. In preclinical mouse models, RC48-ADC synergized with CTLA-4 and PD-L1 antibodies.
Conclusions
RC48-ADC enhances immunotherapy by regulating PD-L1 through the Hippo-TAZ pathway and reactivating CD8+T cells, offering a novel combination therapeutic strategy for bladder cancer.
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Details
; Hu, Jiao 1 1 Xiangya Hospital Central South University, Changsha, Hunan, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
2 Department of Urology, Huazhong University of Science and Technology, Wuhan, China
3 Department of Urology, The Second Affiliated Hospital, Guizhou Medical University, Kaili, China
4 Department of Urology, The First Affiliated Hospital of Hunan Normal University, Hunan Normal University, Changsha, Hunan, China