Background: Immune cell heterogenicity is known to determine the therapeutic response to cancer progression. Neoadjuvant chemoimmunotherapy (NACI) has shown clinical benefits in some patients with advanced head and neck squamous cell carcinoma (HNSCC), but the underlying mechanism behind this clinical response is unknown. The efficacy of NACI needs to be potentiated by identifying accurate biomarkers to predict clinical responses. Here, we attempted to identify molecules predicting NACI response in advanced HNSCC. Methods: We performed combined single‐cell RNA sequencing (scRNA‐seq) and multiplex immunofluorescence (mIHC) staining with tumor samples derived from NACI‐treated HNSCC patients to identify a new tumor‐infiltrating cell (TIL) subtype, CD103 ⁺ CD8 ⁺ TILs, associated with clinical response, while both in vitro and in vivo assays were carried out to determine its antitumor efficiency. The regulatory mechanism of the CD103 ⁺ CD8 ⁺ TILs population was examined by performing cell‐cell interaction analysis of the scRNA‐seq data and spatial analysis of the mIHC images. Results: We established intratumoral CD103 ⁺ CD8 ⁺ TILs density as a determinant of NACI efficacy in cancers. Our scRNA‐seq results indicated that the population of CD103 ⁺ CD8 ⁺ TILs was dramatically increased in the responders of NACI‐treated HNSCC patients, while mIHC analysis confirmed the correlation between intratumoral CD103 ⁺ CD8 ⁺ TILs density and NACI efficacy in HNSCC patients. Further receiver operating characteristic curve analysis defined this TIL subset as a potent marker to predict patient response to NACI. Functional assays showed that CD103 ⁺ CD8 ⁺ TILs were tumor‐reactive T cells, while programmed cell death protein‐1 (PD‐1) blockade enhanced CD103 ⁺ CD8 ⁺ TILs cytotoxicity against tumor growth in vivo. Mechanistically, targeting the triggering receptor expressed on myeloid cells 2‐positive (TREM2 ⁺ ) macrophages might enhance the population of CD103 ⁺ CD8 ⁺ TILs and facilitate antitumor immunity during NACI treatment. Conclusions: Our study highlights the impact of intratumoral CD103 ⁺ CD8 ⁺ TILs density on NACI efficacy in different cancers, while the efforts to elevate its population warrant further clinical investigation.

Background: Surgery and postoperative adjuvant therapy is the standard treatment for locally advanced resectable oral squamous cell carcinoma (OSCC), while neoadjuvant chemoimmunotherapy (NACI) is believed to lead to better outcomes. This study aims to investigate the effectiveness of NACI regimens in treating locally advanced resectable OSCC. Materials and methods: Patients diagnosed with locally advanced resectable OSCC who received NACI and non-NACI were reviewed between December 2020 and June 2022 in our single center. The pathologic response was evaluated to the efficacy of NACI treatment. Adverse events apparently related to NACI treatment were graded by Common Terminology Criteria for Adverse Events, version 5.0. The disease-free survival (DFS) and overall survival (OS) rate were assessed. Results: Our analysis involved 104 patients who received NACI. Notably, the pathological complete response rate was 47.1%, and the major pathological response (MPR) rate was 65.4%. The top three grade 1–2 treatment-related adverse events (TRAEs) were alopecia (104; 100%), anemia (81; 77.9%), and pruritus (62; 59.6%). Importantly, patients achieving MPR exhibited higher programmed cell death-ligand 1 (PD-L1) combined positive scores (CPS). The diagnostic value of CPS as a biomarker for NACI efficacy was enhanced when combined with total cholesterol level. The 3-year estimated DFS rates were 89.0% in the NACI cohort compared to 60.8% in the non-NACI cohort, while the 3-year estimated OS rates were 91.3 versus 64.0%, respectively. Conclusions: The NACI treatment showed safe and encouragingly efficacious for locally advanced resectable OSCC patients. The high response rates and favorable prognosis suggest this approach as a potential treatment option. Prospective randomized controlled trials are needed to further validate these findings.

Background: Substantial studies reveal that tertiary lymphoid structure (TLS) correlate with prognosis and immunotherapy response in various types of cancers. However, the predictive value of TLS, the specific immune cell subtype within TLS and their anti-tumor mechanisms remain unclear.Methods: Based on 23 TLS-related genes (TLSRGs), we utilized bioinformatics methods to construct a scoring system, named TLSscore. By integrating RNA and single-cell sequencing data, we assessed the utility of TLSscore in head and neck squamous cell carcinoma (HNSCC). Flow cytometric sorting was used to isolate specific T cells subtypes, in vivo and in vitro experiments were conducted to demonstrate its anti-tumor effects.Results: The TLSscore model was constructed and specific TLSscore-genes were found to consistently align with the spatial location of TLS. TLSscore has proven to be a robust predictive model for predicting survival prognosis, immune cell infiltration, somatic mutation and immunotherapy response. Notably, a specific PD1⁺CXCL13⁺CD8⁺T cell subtype was identified within TLS. Both in vivo and in vitro experiments demonstrated that PD1⁺CXCL13⁺CD8⁺T cell might represent a functional cell subtype exerting anti-tumor effects during the process of immune surveillance.Conclusions: Our study presents a predictive model for TLS, which can evaluate its presence and predicts survival prognosis and immunotherapy response in HNSSC patients. Additionally, we identify a specific subtype of T cells that might elucidate the mechanism of TLS function in anti-tumor activities. This T cell subtype holds the potential to be a prognostic marker and a target for adoptive cell therapy (ACT) in the future.

A validated prognostic index for the outcome of patients with advanced high-grade serous ovarian cancer (HGSOC) undergoing neoadjuvant chemotherapy (NACT) remains elusive. To address this need, we developed an ovarian neoadjuvant chemotherapy prognostic index (ONCPI) to improve predictive accuracy. We encompassed an analysis of the clinicopathological characteristics of patients with advanced HGSOC who were administered platinum-based NACT. Blood inflammatory composite markers were calculated and converted into binary values using optimal cutoffs. Omental hematoxylin and eosin (H&E) stained slides were selected for the assessment of chemotherapy response score (CRS), which served as a measure of NACT efficacy. Logistic regression analysis and Cox proportional hazards regression model were utilized to construct a prognostic index. Multivariate logistic analysis showed that both CRS and neutrophil-to-lymphocyte ratio (NLR) independently influenced the response to platinum-based chemotherapy. Meanwhile, Kaplan–Meier and Cox regression analysis revealed that CRS score was significantly correlated with progression-free survival (PFS) and overall survival (OS), and patients with high NLR showed poor OS. We further developed an ovarian neoadjuvant chemotherapy prognostic index (ONCPI) based on the CRS and NLR. The area under the curve (AUC) value of ONCPI was 0.771 (P < 0.001, 95% CI: 0.656–0.887) for the prediction of platinum resistance. This AUC value surpasses that of the individual NLR and CRS, which were 0.670 (P = 0.018, 95% CI: 0.547–0.793) and 0.714 (P = 0.003, 95% CI: 0.590–0.839), respectively. Moreover, survival analysis suggested that patients with ONCPI of 0 and 1 were significantly associated with improved PFS and OS. The ONCPI emerges as a significant prognostic marker for predicting NACT outcome in advanced HGSOC patients and holds promise for integration into clinical practice and risk-stratified trial design.

Background: A prognostic index validated for the outcomes of advanced high-grade serous ovarian cancer (HGSOC) patients with neoadjuvant chemotherapy (NACT) is still lacking. We therefore developed an ovarian neoadjuvant chemotherapy prognostic index (ONCPI) to enhance predictive accuracy. Methods: We analyzed clinicopathologic feature of advanced HGSOC patients receiving platinum-based NACT. Blood inflammatory composite markers were calculated and binary-transformed by optimal cutoffs. The omental hematoxylin and eosin (H&E) stained slides were selected for the assessment of chemotherapy response score (CRS). Logistic regression analyses and Cox proportional hazard regression model were utilized to develop a prognostic index. Results: Multivariate analysis showed that CRS and neutrophils-to-lymphocyte ratio (NLR) are independent risk factors for platinum-chemotherapy response. Meanwhile, Kaplan–Meier and Cox regression analysis revealed that CRS score was significantly correlated with PFS and OS, and NLR-high patients was associated with poor OS. We further developed an ONCPI model based on the CRS score and NLR level. Survival analysis suggested that patients with score 0 and 1 of ONCPI were significantly associated with improved PFS and OS. Conclusions: The ONCPI score emerges as a significant prognostic marker for predicting NACT outcomes in advanced HGSOC patients. Its integration into clinical practice and risk-stratified trial design is conceivable.