IL-10 Signaling Elicited by Nivolumab-Induced Activation of the MAP Kinase Pathway Does Not Fully Contribute to Nivolumab-Modulated Heterogeneous T Cell Responses

Toripalimab, a therapeutic monoclonal anti-PD-1 antibody with high binding affinity to PD-1 and enhanced potency to activate human T cells

Over the past decade, US Food and Drug Administration (FDA)-approved immune checkpoint inhibitors that target programmed death-1 (PD-1) have demonstrated significant clinical benefit particularly in patients with PD-L1 expressing tumors. Toripalimab is a humanized anti-PD-1 antibody, approved by FDA for first-line treatment of nasopharyngeal carcinoma in combination with chemotherapy. In a post hoc analysis of phase 3 studies, toripalimab in combination with chemotherapy improved overall survival irrespective of PD-L1 status in nasopharyngeal carcinoma (JUPITER-02), advanced non-small cell lung cancer (CHOICE-01) and advanced esophageal squamous cell carcinoma (JUPITER-06). On further characterization, we determined that toripalimab is molecularly and functionally differentiated from pembrolizumab, an anti-PD-1 mAb approved previously for treating a wide spectrum of tumors. Toripalimab, which binds the FG loop of PD-1, has 12-fold higher binding affinity to PD-1 than pembrolizumab and promotes significantly more Th1- and myeloid-derived inflammatory cytokine responses in healthy human PBMCs in vitro. In an ex vivo system employing dissociated tumor cells from treatment naïve non-small cell lung cancer patients, toripalimab induced several unique genes in IFN-γ and immune cell pathways, showed different kinetics of activation and significantly enhanced IFN-γ signature. Additionally, binding of toripalimab to PD-1 induced lower levels of SHP1 and SHP2 recruitment, the negative regulators of T cell activation, in Jurkat T cells ectopically expressing PD-1. Taken together, these data demonstrate that toripalimab is a potent anti-PD-1 antibody with high affinity PD-1 binding, strong functional attributes and demonstrated clinical activity that encourage its continued clinical investigation in several types of cancer.

Identification of immune-related and autophagy-related genes for the prediction of survival in bladder cancer

Background

Bladder cancer has the characteristics of high morbidity and mortality, and the prevalence of bladder cancer has been increasing in recent years. Immune and autophagy related genes play important roles in cancer, but there are few studies on their effects on the prognosis of bladder cancer patients.

Methods

Using gene expression data from the TCGA-BLCA database, we clustered bladder cancer samples into 6 immune-related and autophagy-related molecular subtypes with different prognostic outcomes based on 2208 immune-related and autophagy-related genes. Six subtypes were divided into two groups which had significantly different prognosis. Differential expression analysis was used to explore genes closely related to the progression of bladder cancer. Then we used Cox stepwise regression to define a combination of gene expression levels and immune infiltration indexes to construct the risk model. Finally, we built a Nomogram which consist of risk score and several other prognosis-related clinical indicators.

Results

The risk model suggested that high expression of C5AR2, CSF3R, FBXW10, FCAR, GHR, OLR1, PGLYRP3, RASGRP4, S100A12 was associated with poor prognosis, while high expression level of CD96, IL10, MEFV pointed to a better prognosis. Validation by internal and external dataset suggested that our risk model had a high ability to discriminate between the outcomes of patients with bladder cancer. The immunohistochemical results basically confirmed our results. The C-Index value and Calibration curves verified the robustness of Nomogram.

Conclusions

Our study constructed a model that included a risk score for patients with bladder cancer, which provided a lot of helps to predict the prognosis of patients with bladder cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12863-022-01073-7.

Identification of an endogenous retroviral signature to predict anti-PD1 response in advanced clear cell renal cell carcinoma: an integrated analysis of three clinical trials

Background

Endogenous retrovirus (ERV) elements are genomic footprints of ancestral retroviral infections within the human genome. Previous studies have demonstrated that dysregulated ERV transcription level is associated with immune cell infiltration in cancers, but the association between ERV expression and programmed cell death protein 1 (PD-1) blockade response is currently unraveled for solid cancers, such as advanced clear cell renal cell carcinoma (ccRCC).

Methods

ERV mRNA profiles were obtained from three clinical trials of ccRCC where the patients were treated with anti-PD-1 (CM-009, CM-010, CM-025, and TCGA-KIRC data). Patients treated with nivolumab were divided into training and test cohort, while the TCGA-KIRC cohort was used as an external validation. Univariate Cox regression analysis and least absolute shrinkage and selection operator regression were used to establish the signature. Immune cell infiltration analysis and gene set enrichment analysis were performed to explore potential biological mechanisms.

Results

An ERV signature was established based on nine ERV expression patterns. In the training cohort, the median overall survival in the low- and high-risk group was 45.2 and 19.6 months [hazard ratio (HR) = 0.49, 0.32-0.75, p < 0.001], respectively. The results were confirmed in the test (HR = 0.41, 0.20-0.83, p = 0.013), and in the TCGA-KIRC cohort (HR = 0.55, 0.34-0.90, p = 0.017). Moreover, in the CM-025 cohort, the low-risk group that received nivolumab had a more favorable survival compared with those that received the mTOR inhibitor everolimus, while no significant differences were observed in the high-risk group. CD8+ T cells were enriched in the low-risk group, while immune suppressive pathways were suppressed.

Conclusion

The newly identified ERV signature is not only a prognostic, but also a predictive biomarker for advanced ccRCC patients who received anti-PD-1 therapy, which can guide personalized treatment in cancer patients in the future.