Prognostic value of esophageal cancer immune prognostic index in advanced esophageal squamous cell carcinoma patients with anti‐programmed cell death‐1 therapy

Lu, Jiangyue; Du, Le; Xiao, Lanbo; Zhang, Zhibo

doi:10.1002/cam4.5844

Cited by 3 publications

(1 citation statement)

References 46 publications

(80 reference statements)

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“…Other types of factors include dietary, 10 lymph node metastasis, 11,12 treatment patterns, 13 and molecular biomarkers. 14,15 In recent years,radiomics has been explored to characterize image textures in medical imaging, but there have been limited studies on esophageal cancer. Iwashita et al 16 analyzed skeletal muscle (SM) radiomics and suggested that integrating SM radiomics and clinical data could help determine survival outcomes in patients with esophageal cancer treated with radical radiotherapy.…”

Section: Introductionmentioning

confidence: 99%

Graphical modeling of causal factors associated with the postoperative survival of esophageal cancer subjects

Ren,

Beeche,

Iyer

et al. 2023

Medical Physics

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PurposeTo clarify the causal relationship between factors contributing to the postoperative survival of patients with esophageal cancer.MethodsA cohort of 195 patients who underwent surgery for esophageal cancer between 2008 and 2021 was used in the study. All patients had preoperative chest computed tomography (CT) and positron emission tomography‐CT (PET‐CT) scans prior to receiving any treatment. From these images, high throughput and quantitative radiomic features, tumor features, and various body composition features were automatically extracted. Causal relationships among these image features, patient demographics, and other clinicopathological variables were analyzed and visualized using a novel score‐based directed graph called “Grouped Greedy Equivalence Search” (GGES) while taking prior knowledge into consideration. After supplementing and screening the causal variables, the intervention do‐calculus adjustment (IDA) scores were calculated to determine the degree of impact of each variable on survival. Based on this IDA score, a GGES prediction formula was generated. Ten‐fold cross‐validation was used to assess the performance of the models. The prediction results were evaluated using the R‐Squared Score (R2 score).ResultsThe final causal graphical model was formed by two PET‐based image variables, ten body composition variables, four pathological variables, four demographic variables, two tumor variables, and one radiological variable (Percentile 10). Intramuscular fat mass was found to have the most impact on overall survival month. Percentile 10 and overall TNM (T: tumor, N: nodes, M: metastasis) stage were identified as direct causes of overall survival (month). The GGES casual model outperformed GES in regression prediction (R2 = 0.251) (p < 0.05) and was able to avoid unreasonable causality that may contradict common sense.ConclusionThe GGES causal model can provide a reliable and straightforward representation of the intricate causal relationships among the variables that impact the postoperative survival of patients with esophageal cancer.

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Section: Introductionmentioning

confidence: 99%

Graphical modeling of causal factors associated with the postoperative survival of esophageal cancer subjects

Ren,

Beeche,

Iyer

et al. 2023

Medical Physics

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Prognostic value of esophageal cancer immune prognostic index in advanced esophageal squamous cell carcinoma patients with anti‐programmed cell death‐1 therapy

Xiao

et al. 2023

Cancer Medicine

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Background: This study aimed to determine whether the immune prognostic index (ECIPI), based on hemoglobin (Hb) and neutrophil-to-lymphocyte ratio (NLR), could predict the prognosis in patients with advanced esophageal squamous cell carcinoma (ESCC) receiving programmed cell death-1 (PD-1) inhibitor treatment. Methods: Advanced ESCC patients who had been treated with PD-1 inhibitors from Jan 2016 to Oct 2021 were included. Kaplan-Meier method and Cox proportional hazards regression were used to analyze progression-free survival (PFS) and overall survival (OS). The overall response rate (ORR) was the percentage of complete and partial responses. Univariate and multivariate analyses were used for estimating hazard ratio (HR) and 95% confidence interval (CI). Patients were grouped by ECIPI (good: Hb > 105 g/L and NLR ≤ 4.3; intermediate: Hb ≤ 105 g/L and NLR ≤ 4.3, or Hb > 105 g/L and NLR < 4.3; poor: Hb ≤ 105 g/L and NLR > 4.3).Variables for the multivariate model were selected if the p-value was below 0.05 in the univariate analysis. All statistical comparisons were two-way, and a p-value below 0.05 was set as statistical significance.Results: Totally, of 123 ESCC patients with stage III or IV were included in the study. Efficacy evaluation showed that patients with pretreatment ECIPI good had the best ORR compared with those with ECIPI intermediate and ECIPI poor (53% vs. 22% vs. 8%, p < 0.01). Multivariate analysis showed that ECIPI was an independent influential factor for PFS (p = 0.004) and OS (p < 0.001). Kaplan-Meier curves demonstrated that patients with ECIPI good had the longest PFS (median: 11.6 vs. 3.5 vs. 1.7 months, p < 0.0001) and OS (median: 23.6 vs. 16.7 vs. 4.0 months, p < 0.0001) compared with those with ECIPI intermediate and ECIPI poor. Subgroup analysis indicated that ECIPI good was associated with improved PFS and OS in patients with ECOG 0-1, PD-1 inhibitor plus chemotherapy, firstline treatment, and smoke (all p < 0.05).

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Inhibiting the expression of spindle appendix cooled coil protein 1 can suppress tumor cell growth and metastasis and is associated with cancer immune cells in esophageal squamous cell carcinoma

Liu,

Xu,

Zhang

et al. 2024

PLoS ONE

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Inhibiting the expression of spindle appendix cooled coil protein 1 (SPDL1) can slow down disease progression and is related to poor prognosis in patients with esophageal cancer. However, the specific roles and molecular mechanisms of SPDL1 in esophageal squamous cell carcinoma (ESCC) have not been explored yet. The current study aimed to investigate the expression levels of SPDL1 in ESCC via transcriptome analysis using data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases. Moreover, the biological roles, molecular mechanisms, and protein networks involved in SPDL1 were identified using machine learning and bioinformatics. The cell counting kit-8 assay, EdU staining, and transwell assay were used to investigate the effects of inhibiting SPDL1 expression on ESCC cell proliferation, migration, and invasion. Finally, the correlation between the SPDL1 expression and cancer immune infiltrating cells was evaluated by analyzing data from the TCGA database. Results showed that SPDL1 was overexpressed in the ESCC tissues. The SPDL1 expression was related to age in patients with ESCC. The SPDL1 co-expressed genes included those involved in cell division, cell cycle, DNA repair and replication, cell aging, and other processes. The high-risk scores of SPDL1-related long non-coding RNAs were significantly correlated with overall survival and cancer progression in patients with ESCC (P < 0.05). Inhibiting the SPDL1 expression was effective in suppressing the proliferation, migration, and invasion of ESCC TE-1 cells (P < 0.05). The overexpression of SPDL1 was positively correlated with the levels of Th2 and T-helper cells, and was negatively correlated with the levels of plasmacytoid dendritic cells and mast cells. In conclusion, SPDL1 was overexpressed in ESCC and was associated with immune cells. Further, inhibiting the SPDL1 expression could effectively slow down cancer cell growth and migration. SPDL1 is a promising biomarker for treating patients with ESCC.

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Prognostic value of esophageal cancer immune prognostic index in advanced esophageal squamous cell carcinoma patients with anti‐programmed cell death‐1 therapy

Cited by 3 publications

References 46 publications

Graphical modeling of causal factors associated with the postoperative survival of esophageal cancer subjects

Graphical modeling of causal factors associated with the postoperative survival of esophageal cancer subjects

Prognostic value of esophageal cancer immune prognostic index in advanced esophageal squamous cell carcinoma patients with anti‐programmed cell death‐1 therapy

Inhibiting the expression of spindle appendix cooled coil protein 1 can suppress tumor cell growth and metastasis and is associated with cancer immune cells in esophageal squamous cell carcinoma

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