An immune-based risk-stratification system for predicting prognosis in pulmonary sarcomatoid carcinoma (PSC)

Abstract

Pulmonary sarcomatoid carcinoma (PSC) is an uncommon subtype of lung cancer, and immune checkpoint blockade promises in clinical benefit. However, virtually nothing is known about the expression of common immune checkpoints in PSC. Here, we performed immunohistochemistry (IHC) to detect nine immune-related proteins in 97 PSC patients. Based on the univariable Cox regression, random forests were used to establish risk models for OS and DFS. Moreover, we used the GSEA, CIBERSORT, and ImmuCellAI to analyze the enriched pathways and microenvironment. Univariable analysis revealed that CD4 (P = 0.008), programmed cell death protein 1 (PD-1; P = 0.003), galectin-9 (Gal-9) on tumor cells (TCs; P = 0.021) were independent for DFS, while CD4 (P = 0.020), PD-1 (P = 0.004), Gal-9 (P = 0.033), and HLA on TILs (P = 0.031) were significant for OS. Meanwhile, the expression level of CD8 played a marginable role in DFS (P = 0.061), limited by the number of patients. The combination of Gal-9 on TC with CD4 and PD-1 on TILs demonstrated the most accurate prediction for DFS (AUC: 0.636-0.791, F1-score: 0.635-0.799), and a dramatic improvement to TNM-stage (P < 0.001 for F1-score of 1-y, 3-y, and 5-yDFS). A similar finding was also observed in the predictive ability of CD4 for OS (AUC: 0.602-0.678, F1-score: 0.635-0.679). CD4 was negatively associated with the infiltration of neutrophils (P = 0.015). PDCD1 (coding gene of PD-1) was positively correlated to the number of exhausted T cells (Texs; P = 0.020) and induced regulatory T cells (iTregs; P = 0.021), and LGALS9 (coding gene of Gal-9) was positively related to the level of dendritic cells (DCs; P = 0.021). Further, a higher combinational level of CD4, PDCD1 on TILs, and LAGLS9 on TCs were proved to be infiltrated with more M1-type macrophages (P < 0.05). We confirmed the expression status of nine immune-related proteins and established a TNM-Immune system for OS and DFS in PSC to assist clinical risk-stratification.

Integrated pathological analysis to develop a Gal-9 based immune survival stratification to predict the outcome of lung large cell neuroendocrine carcinoma and its usefulness in immunotherapy

“…Our research differs from prior similar studies in several ways [28][29]. The evaluation of multiple immune biomarkers in a single, large, homogeneous LCNEC cohort is an effective approach for developing a Gal-9-based immune risk model.…”

Integrative genomic and transcriptomic profiling of pulmonary sarcomatoid carcinoma identifies molecular subtypes associated with distinct immune features and clinical outcomes

“…ICB has been recently tested in PSCs and demonstrated promising clinical efficacy and tends to be associated with favorable survival [ 50 , 59 , 60 , 61 ]. However, the response rate is suboptimal in unselected patient populations [ 62 ]. Although ICB is better tolerated than chemotherapy, it does come with severe side effects [ 63 ].…”

Prognostic Value of18F-FDG PET/CT Radiomics in Extranodal Nasal-Type NK/T Cell Lymphoma

“…SPSS 26.0 (IBM Corp., Armonk, NY, USA) and R4.2.2 (R Foundation for Statistical Computing, Vienna, Austria) software were used for statistical analysis. X-tile 3.6.1 (Robert L Camp, Yale University, New Haven, CT, USA) software was used to convert continuous variables, including the radiomics scores, into categorical variables and to stratify patients by risk based on optimal cutoff points [ 18 19 ]. Categorical variables were compared by Chi-square test.…”