Henghui Zhang

Esophageal squamous cell carcinoma (ESCC) has limited treatment options post-immune checkpoint inhibitor (ICI) resistance. We developed IPM514, a universal multi-epitope mRNA lipid nanoparticle (LNP) vaccine targeting tumor-associated antigens identified via transcriptomic analysis of TCGA/GTEx datasets and validated in 132 ESCC patients. IPM514 contains 15 fragments from 9 antigens, covering most patients and over half of HLA subtypes. Peripheral blood mononuclear cells (PBMCs) from healthy donors and ESCC patients stimulated with IPM514 effectively expanded specific T cells that exhibited significant cytotoxic activity against ESCC and other squamous cell carcinomas with similar antigen profiles. In HLA-transgenic mouse models, IPM514 suppressed tumor growth, extended survival, and provided durable protection. Importantly, combination therapy with PD-1 blockade augmented antitumor efficacy by promoting immune cell infiltration, upregulating antigen presentation pathways, and reprogramming the tumor microenvironment toward an anti-tumorigenic state. These results demonstrate IPM514 represents a promising novel mRNA vaccine strategy for improving ESCC immunotherapy.

Background: Neoadjuvant immune checkpoint blockade (ICB) combined with chemotherapy has demonstrated higher response rates than chemotherapy alone in resectable esophageal squamous cell carcinoma (ESCC). Although tumor microenvironment (TME) features associated with treatment response have been studied in the contexts of both chemotherapy and immunotherapy, direct comparisons of these characteristics and their implications for novel therapeutic development remain largely unexplored. Methods: Paired pretreatment and post-treatment tumor samples were prospectively collected from 55 patients with locally advanced ESCC enrolled in a multicenter, phase 3 clinical trial (ChiCTR2000040034). Patients were randomized to receive neoadjuvant chemotherapy (paclitaxel with cisplatin, TP; n=14) or its combination with PD-1 blockade (camrelizumab, albumin-bound paclitaxel and cisplatin/paclitaxel and cisplatin, Cam+nab-TP/TP; n=41), followed by surgical resection. Pathological response was defined based on Mandard’s Tumor Regression Grade scoring system. Changes in immune cell populations and tumor-associated antigens (TAAs) within the TME in relation to response were characterized using single-cell RNA and T cell receptor sequencing. Results: Both chemotherapy and chemoimmunotherapy responders exhibited shared temporal dynamics including dendritic cell remodeling, cytotoxic CD8 ⁺ T cell contraction, and memory T cell expansion, with chemoimmunotherapy uniquely suppressing the clonal expansion of GZMB ⁺ TIGIT ⁺ T cells. In contrast, non-responders failed to elicit effective antitumor immunity and displayed persistent expression of targetable TAAs, fully preserved HLA machinery, and clonal expansion of dysfunctional GZMB ⁺ TIGIT ⁺ T cells. Conclusions: Our study identifies key immune contributors correlated with response to neoadjuvant therapies and a panel of TAAs in non-responders. These findings support the development of TAA-targeted therapeutic vaccines and combination strategies incorporating ICB to overcome resistance in non-responders.

Transarterial chemoembolization (TACE) has the potential to activate the immune system and regulate the tumor microenvironment. This study assesses the clinical response of patients with HBV-related hepatocellular carcinoma (HBV-HCC) after TACE treatment based on systemic immune classification (SIC). A total of 80 patients with HBV-HCC were assessed for the peripheral blood immune exhaustion phenotype and immune proteins through a combination of “Olink High Sensitivity Plasma Proteomics” and “Multicolor Flow Cytometry.” An unsupervised clustering algorithm was employed to classify various immune subtypes and identify core indicators that evaluate the response of SIC to TACE treatment. The application of these two technologies as novel approaches for detecting HBV-HCC provides synergistic insights into disease mechanisms and patient prognosis. Based on the combination of immune exhaustion phenotypes and immune proteins, we developed SIC that classified the subjects into three clusters: Cluster 1, Cluster 2, and Cluster 3. Cluster 3 was associated with poor clinical characteristics, unfavorable prognosis, and elevated levels of immune checkpoint expression. This risk scoring system is capable of predicting the overall survival of patients at various time points, with receiver operating characteristic areas exceeding 0.8. This study establishes SIC method to predict the clinical response of HBV-HCC patients after TACE treatment, providing new guidance for future immunotherapy and identification of non-invasive biomarkers.

Introduction Despite advancements in adoptive cell therapy (ACT) for hematologic tumors, its role in solid tumors still lacks satisfactory performance, especially in Primary Liver Cancer (PLC). Therefore, further studies are needed on potential ACT sources for PLC. Methods Primary liver cancer patients who had not previously received treatment were prospectively enrolled in this research. Tumor tissues combined with lymph node and blood samples were acquired during surgery. Two different antigen-specific T-cell induction approaches were used to form cytotoxic T-cell groups from PBMCs, and antitumor T cells from tumor tissues combined with TDLNs were derived. A single-cell RNA sequence coupled with a T-cell receptor sequence was used to identify the cell subsets based on the molecular and functional properties of diverse antitumor T-cell induction approaches and sources. Results Three primary liver cancer patients were included in the present study. A total of 79,300 cell transcriptomes in 19 clusters were isolated from the clinical samples. After two different induction approaches, substantial amplification of immune cells occurred in both the CTL and CTL2 groups, with highly consistent T-cell subtypes, and selective amplification of antitumor T-cell clones in the two groups was also detected. The three-aspect comparison, which was based on the proliferation score, effect score and cytokine expression, indicated that the immunological effect of the mRNA approach was comparable to that of the multiantigen peptide approach. Finally, the antigen-specific expanded T-cell clones found in CTL, CTL2 and TAL-T cells indicated the potential of tumors combined with lymph nodes as sources for ACT. Conclusions Diverse antitumor T-cell induction approaches and sources were compared, revealing multiple effective options for antitumor T-cell derivation as a source of ACT for liver cancer. Graphical abstract

Epidermal growth factor receptor (EGFR) is reportedly overexpressed in most esophageal squamous cell carcinoma (ESCC) patients, but anti-EGFR treatments offer limited survival benefits. Our preclinical data showed the promising antitumor activity of afatinib in EGFR-overexpressing ESCC. This proof-of-concept, phase II trial assessed the efficacy and safety of afatinib in pretreated metastatic ESCC patients (n = 41) with EGFR overexpression (NCT03940976). The study met its primary endpoint, with a confirmed objective response rate (ORR) of 39% in 38 efficacy-evaluable patients and a median overall survival of 7.8 months, with a manageable toxicity profile. Transcriptome analysis of pretreatment tumors revealed that neurotrophic receptor tyrosine kinase 2 (NTRK2) was negatively associated with afatinib sensitivity and might serve as a predictive biomarker, irrespective of EGFR expression. Notably, knocking down or inhibiting NTRK2 sensitized ESCC cells to afatinib treatment. Our study provides novel findings on the molecular factors underlying afatinib resistance and indicates that afatinib has the potential to become an important treatment for metastatic ESCC patients.

Background: Immune checkpoint inhibitors (ICIs) have significantly improved patient survival in multiple cancers. However, therapy response in esophageal cancer is limited to subgroups of patients and clinically useful predictive biomarkers are lacking. Methods: We collected a series of plasma samples from 91 patients with esophageal cancer before and after ICI treatment. The Olink Immuno-Oncology panel (92 proteins) with proximity extension assays was used to detect the dynamic changes in plasma and potential biomarkers associated with treatment outcomes. We screened all survival-related proteins and established a risk score model to better predict the prognosis and treatment response in patients with esophageal cancer immunotherapy. Results: We found that 47 out of 92 quantified proteins had significant changes in plasma levels during ICI treatment (p<0.050), and these changed proteins were involved in immune-related reactions, such as intercellular adhesion and T-cell activation. Notably, the baseline levels of three angiogenesis-related proteins (IL-8, TIE2, and HGF) were significantly associated with the survival outcomes of patients treated with ICIs (p<0.050). According to these prognostic proteins, we established an angiogenesis-related risk score, which could be a superior biomarker for ICI response prediction. In addition, antiangiogenic therapy combined with ICIs significantly improved overall survival compared with ICI monotherapy (p=0.044). Conclusions: An angiogenesis-related risk score based on three proteins (IL-8, TIE2, and HGF) could predict ICI response and prognosis in patients with esophageal cancer, which warrants verification in the future. Our study highlights the potential application of combining ICIs and antiangiogenic therapy and supports Olink plasma protein sequencing as a liquid biopsy method for biomarker exploration.

Background: The cancer-immunity cycle (CI cycle) provides a theoretical framework to illustrate the process of the anticancer immune response. Recently, the update of the CI cycle theory emphasizes the importance of tumor’s immunological phenotype. However, there is lack of immunological phenotype of pan-cancer based on CI cycle theory. Methods: Here, we applied a visualizing method termed ‘cancer immunogram’ to visualize the state of CI cycle of 8460 solid tumors from TCGA cohort. Unsupervised clustering of the cancer immunogram was performed using the nonnegative matrix factorization (NMF) analysis. We applied an evolutionary genomics approach (dN/dS ratio) to evaluate the clonal selection patterns of tumors with distinct immunogram subtypes. Results: We defined four major CI cycle patterns across 32 cancer types using a cancer immunogram approach. Immunogram-I was characterized by ‘hot’ and ‘exhausted’ features, indicating a favorable prognosis. Strikingly, immunogram-II, immunogram-III, and immunogram-IV represented distinct immunosuppressive patterns of ‘cold’ tumor. Immunogram-II was characterized by ‘cold’ and ‘radical’ features, which represented increased expression of immune inhibitor molecules and high levels of positive selection, indicating the worst prognosis. Immunogram-III was characterized by ‘cold’ and ‘recognizable’ features and upregulated expression of MHC I molecules. Immunogram-IV was characterized by ‘cold’ and ‘inert’ features, which represented overall immunosuppression, lower levels of immunoediting and positive selection, and accumulation of more tumor neoantigens. In particular, favorable overall survival was observed in metastatic urothelial cancer patients with immunogram-I and immunogram-IV after immune checkpoint inhibitor (ICI) therapy. Meanwhile, a higher response rate to ICI therapy was observed in metastatic gastric cancer patients with immunogram-I phenotype. Conclusions: Our findings provide new insight into the interaction between immunity and cancer evolution, which may contribute to optimizing immunotherapy strategies.