Construction and validation of classification models for predicting the response to concurrent chemo-radiotherapy of patients with esophageal squamous cell carcinoma based on multi-omics data.

BACKGROUND: Concurrent chemo-radiotherapy (CCRT) is the preferred non-surgical treatment for patients with locally advanced esophageal squamous cell carcinoma (ESCC). Unfortunately, some patients respond poorly, which leads to inappropriate or excessive treatment and affects patient survival. To accurately predict the response of ESCC patients to CCRT, we developed classification models based on the clinical, serum proteomic and radiomic data. METHODS: A total of 138 ESCC patients receiving CCRT were enrolled in this study and randomly split into a training cohort (n = 92) and a test cohort (n = 46). All patients were classified into either complete response (CR) or incomplete response (non-CR) groups according to RECIST1.1. Radiomic features were extracted by 3Dslicer. Serum proteomic data was obtained by Olink proximity extension assay. The logistic regression model with elastic-net penalty and the R-package "rms" v6.2-0 were applied to construct classification and nomogram models, respectively. The area under the receiver operating characteristic curves (AUC) was used to evaluate the predictive performance of the models. RESULTS: Seven classification models based on multi-omics data were constructed, of which Model-COR, which integrates five clinical, five serum proteomic, and seven radiomic features, achieved the best predictive performance on the test cohort (AUC = 0.8357, 95 % CI: 0.7158-0.9556). Meanwhile, patients predicted to be CR by Model-COR showed significantly longer overall survival than those predicted to be non-CR in both cohorts (Log-rank P = 0.0014 and 0.027, respectively). Furthermore, two nomogram models based on multi-omics data also performed well in predicting response to CCRT (AUC = 0.8398 and 0.8483, respectively). CONCLUSION: We developed and validated a multi-omics based classification model and two nomogram models for predicting the response of ESCC patients to CCRT, which achieved the best prediction performance by integrating clinical, serum Olink proteomic, and radiomic data. These models could be useful for personalized treatment decisions and more precise clinical radiotherapy and chemotherapy for ESCC patients.

Spatial analysis of stromal signatures identifies invasive front carcinoma-associated fibroblasts as suppressors of anti-tumor immune response in esophageal cancer.

BACKGROUND: Increasing evidence indicates that the tumor microenvironment (TME) is a crucial determinant of cancer progression. However, the clinical and pathobiological significance of stromal signatures in the TME, as a complex dynamic entity, is still unclear in esophageal squamous cell carcinoma (ESCC). METHODS: Herein, we used single-cell transcriptome sequencing data, imaging mass cytometry (IMC) and multiplex immunofluorescence staining to characterize the stromal signatures in ESCC and evaluate their prognostic values in this aggressive disease. An automated quantitative pathology imaging system determined the locations of the lamina propria, stroma, and invasive front. Subsequently, IMC spatial analyses further uncovered spatial interaction and distribution. Additionally, bioinformatics analysis was performed to explore the TME remodeling mechanism in ESCC. To define a new molecular prognostic model, we calculated the risk score of each patient based on their TME signatures and pTNM stages. RESULTS: We demonstrate that the presence of fibroblasts at the tumor invasive front was associated with the invasive depth and poor prognosis. Furthermore, the amount of α-smooth muscle actin (α-SMA)+ fibroblasts at the tumor invasive front positively correlated with the number of macrophages (MØs), but negatively correlated with that of tumor-infiltrating granzyme B+ immune cells, and CD4+ and CD8+ T cells. Spatial analyses uncovered a significant spatial interaction between α-SMA+ fibroblasts and CD163+ MØs in the TME, which resulted in spatially exclusive interactions to anti-tumor immune cells. We further validated the laminin and collagen signaling network contributions to TME remodeling. Moreover, compared with pTNM staging, a molecular prognostic model, based on expression of α-SMA+ fibroblasts at the invasive front, and CD163+ MØs, showed higher accuracy in predicting survival or recurrence in ESCC patients. Regression analysis confirmed this model is an independent predictor for survival, which also identifies a high-risk group of ESCC patients that can benefit from adjuvant therapy. CONCLUSIONS: Our newly defined biomarker signature may serve as a complement for current clinical risk stratification approaches and provide potential therapeutic targets for reversing the fibroblast-mediated immunosuppressive microenvironment.

STAT3ß Enhances Sensitivity to Concurrent Chemoradiotherapy by Inducing Cellular Necroptosis in Esophageal Squamous Cell Carcinoma.

Concurrent chemoradiotherapy (CCRT), especially platinum plus radiotherapy, is considered to be one of the most promising treatment modalities for patients with advanced esophageal cancer. STAT3ß regulates specific target genes and inhibits the process of tumorigenesis and development. It is also a good prognostic marker and a potential marker for response to adjuvant chemoradiotherapy (ACRT). We aimed to investigate the relationship between STAT3ß and CCRT. We examined the expression of STAT3α and STAT3ß in pretreatment tumor biopsies of 105 ESCC patients who received CCRT by immunohistochemistry. The data showed that ESCC patients who demonstrate both high STAT3α expression and high STAT3ß expression in the cytoplasm have a significantly better survival rate, and STAT3ß expression is an independent protective factor (HR = 0.424, p = 0.003). Meanwhile, ESCC patients with high STAT3ß expression demonstrated a complete response to CCRT in 65 patients who received platinum plus radiation therapy (p = 0.014). In ESCC cells, high STAT3ß expression significantly inhibits the ability of colony formation and cell proliferation, suggesting that STAT3ß enhances sensitivity to CCRT (platinum plus radiation therapy). Mechanistically, through RNA-seq analysis, we found that the TNF signaling pathway and necrotic cell death pathway were significantly upregulated in highly expressed STAT3ß cells after CCRT treatment. Overall, our study highlights that STAT3ß could potentially be used to predict the response to platinum plus radiation therapy, which may provide an important insight into the treatment of ESCC.

Decreased plasma riboflavin is associated with poor prognosis, invasion, and metastasis in esophageal squamous cell carcinoma.

BACKGROUND: Riboflavin deficiency confers a predisposition for esophageal cancer. The role of plasma riboflavin levels in development and prognosis of individuals with digestive tract inflammation and ulcer (DTIU), digestive tract polyps (DTPs), and ESCC is not well understood. METHODS: We performed a cross-sectional study, including 177 DTIU, 80 DTP, and 324 ESCC cases, to measure the plasma riboflavin levels among the three populations. Correlation between plasma riboflavin levels (categorized as ≥31.8, 6.5-31.8 and ≤6.5 nmol/L groups) and clinical characteristics, as well as survival of ESCC patients (556 cases) was analyzed. RESULTS: There was no difference in plasma riboflavin levels between DTIU, DTP, and ESCC cases (P > 0.05). Plasma riboflavin levels were inversely correlated with invasive depth (correlation coefficient = -0.09, P = 0.026) and lymph node metastasis (correlation coefficient = -0.11, P = 0.010) of ESCC, and ESCC patients with low riboflavin levels had poor recurrence-free survival (P = 0.035) and overall survival (P = 0.003). Decreased riboflavin was a prognostic factor for poor overall survival (HR = 1.91, 95% CI = 1.19-3.07, P = 0.007). CONCLUSIONS: Plasma riboflavin levels in DTIU, DTP, and ESCC patients are similar. Plasma riboflavin levels are associated with the development and prognosis of ESCC.