Single-Cell Profiling Reveals Sustained Immune Infiltration, Surveillance, and Tumor Heterogeneity in Infiltrative Basal Cell Carcinoma

Predictors of Local Invasion in Infiltrative Basal Cell Carcinoma: Tumour Budding Outperforms the WHO Subtyping

Tumour budding (TB) correlates with increased local invasion in various neoplasms. Certain basal cell carcinomas (BCCs) exhibit local aggressiveness. Detecting adverse prognostic factors in partial biopsies could aid in identifying cases with heightened local risk. The absolute number of TB (≤ 3 tumour cells) in excision specimens of 271 infiltrative BCCs (0: absent; 1: 1-2 foci; 2: ≥ 3 foci; 3: ≥ 10 foci), the histopathological subtype and depth of infiltration, perineural invasion, and other histological features were evaluated. A significant correlation was found between TB and both depth of infiltration (rho 0.445, p < 0.001) and perineural invasion (p = 0.009). In the multivariate analysis of depth and perineural invasion (multiple regression, stepwise), TB was identified as a significant covariate together with diameter, inflammation, and perineural invasion for the former, and depth for the latter. Conversely, no correlation existed between the WHO histological subtypes (infiltrating, sclerosing, and micronodular), and depth of infiltration or perineural invasion. This study demonstrates the value of TB as a biomarker for local invasiveness in BCC. In routine practice, a count of ≥ 3 TB foci in lesions incompletely excised or with narrow tumour-free surgical margins would be a straightforward and reproducible method to guide BCC treatment.

Deciphering tumor microenvironment: CXCL9 and SPP1 as crucial determinants of tumor-associated macrophage polarity and prognostic indicators

The tumor microenvironment (TME) is an intricate system comprised of tumor cells and the surrounding cellular and non-cellular components, exerting a pivotal influence on the initiation and progression of tumors. Exhibiting dynamic and diverse compositions as well as functional states across various tumors and patients, a profound comprehension of its specific internal interactions is indispensable for formulating efficacious anti-cancer treatment strategies. Extensive interactions among various immune cell types within the TME are well-documented, with their phenotypes and abundances closely linked to clinical prognoses. TME research is progressing towards greater complexity and precision, yet, to date, no representative TME biomarkers suitable for clinical applications have been definitively identified and validated. In a recent study, the collaborative actions of CXCL9 and SPP1 (CXCL9:SPP1) were found to collectively dictate the polarity of tumor-associated macrophages (TAMs) within the TME, exerting profound effects on tumor progression and treatment responses. The mutually exclusive expression of CXCL9:SPP1 in the TME not only governs TAM polarity but also exhibits strong correlations with immune cell profiles, antitumor factors, and patient outcomes, significantly influencing prognosis. This article consolidates the significance and prospects of CXCL9:SPP1 as a novel indicator for tumor development and prognosis, while also proposing future research directions and addressing potential challenges in this promising field.

Single-cell transcriptome analysis reveals the clinical implications of myeloid-derived suppressor cells in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSC) is the most common malignant tumor that arises in the epithelium of the head and neck regions. Myeloid-derived suppressor cells (MDSCs) are one of the tumor-infiltrating immune cell populations, which play a powerful role in inhibiting anti-tumor immune response. Herein, we employed a single-cell RNA sequencing (scRNA-seq) dataset to dissect the heterogeneity of myeloid cells. We found that SPP1 ⁺ tumor-associated macrophages (TAMs) and MDSCs were the most abundant myeloid cells in the microenvironment. By cell cluster deconvolution from bulk RNA-seq datasets of larger patient groups, we observed that highly-infiltrated MDSC was a poor prognostic marker for patients' overall survival (OS) probabilities. To better apply the MDSC OS prediction values, we identified a set of six MDSC-related genes (ALDOA, CD52, FTH1, RTN4, SLC2A3, and TNFAIP6) as the prognostic signature. In both training and test cohorts, MDSC-related prognostic signature showed a promising value for predicting patients' prognosis outcomes. Further parsing the ligand-receptor pairs of intercellular communications by CellChat, we found that MDSCs could frequently interact with cytotoxic CD8 ⁺ T cells, SPP1 ⁺ TAMs, and endothelial cells. These interactions likely contributed to the establishment of an immunosuppressive microenvironment and the promotion of tumor angiogenesis. Our findings suggest that targeting MDSCs may serve as an alternative and promising target for the immunotherapy of HNSC.