Macrophages-based immune-related risk score model for relapse prediction in stage I–III non-small cell lung cancer assessed by multiplex immunofluorescence

Xiao-yue, WU; Peng, Haitao; He, Miao; Zhong, Ran; Li, Jun; Wen, Yujie; Li, Caichen; Li, Jianfu; Xiong, Shan; Yu, Tao; Zheng, Hongbo; Chen, Yanhui; He, Jianxing; Liang, Wenhua

doi:10.21037/tlcr-21-916

Cited by 12 publications

(8 citation statements)

References 52 publications

(52 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Previous studies have suggested that tumorinfiltrating macrophages are related to poor outcomes in lung cancer (17)(18)(19). However, other studies have revealed the positive role of tumor-infiltrating macrophages in lung cancer was independent risk factor for NSCLC progression (20)(21)(22). The function of macrophages in the prognosis of lung cancer is still controversial, and further investigation is required to clarify this issue.…”

Section: Discussionmentioning

confidence: 99%

The relationship between tumor infiltrating immune cells and the prognosis of patients with lung adenocarcinoma

Tong¹,

Wang²,

Liu³

et al. 2023

J Thorac Dis

View full text Add to dashboard Cite

Background: To depict the immune infiltration characteristics of tumor cells in patients with lung adenocarcinoma (LUAD) and evaluate the predictive value and significance of tumor immune cells on the prognosis of LUAD patients. Methods:The clinical characteristics and transcriptome of LUAD patients were obtained from The Cancer Genome Atlas (TCGA), and the immune cell abundance in LUAD tissue was evaluated using the CIBERSORT algorithm. We created a simplified immune cell-based Cox regression model according to the survival status of patients and clarified the correlation between the survival status of patients and seven types of immune cells. An immune cell-based risk prediction model was created by Cox proportional hazards regression. Subsequently, the gene expression profile of LUAD patients was obtained from the Gene Expression Omnibus (GEO) database to validate the tumor immune infiltration and patient prognosis prediction model attained using the CIBERSORT algorithm.Results: The abundance of 22 tumor-infiltrating immune cells in these patients was detected using the CIBERSORT algorithm. According to Pearson correlation analysis, the immune cells appeared to be closely related to each other. The immune cell composition was remarkably different between the LUAD tumor tissue and paracancerous tissue. The simplified COX model showed that seven kinds of immune cells have predictive value for the prognosis and survival status of LUAD. The receiver operating characteristic curve (ROC) curve confirmed that the prediction model performed well for 1-, 3-, and 5-year survival status. The calibration curve suggested that the prediction model was consistent with the clinical results. Correlation analysis revealed that the clinical features were significantly related to immune cell infiltration. A total of 246 LUAD specimens were from the GEO database, and the risk score model suggested that high risk scores were indicative of a poor prognosis. Finally, enzyme-linked immunosorbent assay (ELISA) revealed that the expressions of tumor necrosis factor-α (TNF-α), interleukin 8 (IL-8), IL-6, and interferon-γ (IFN-γ) in tumor tissues were remarkably higher compared with those in adjacent tissues.Conclusions: There is a close correlation between the tumor-infiltrating immune cells and the prognosis and clinical characteristics of LUAD patients. The risk score model based on TCGA and GEO designed in this study can be applied in clinical practice.

show abstract

Section: Discussionmentioning

confidence: 99%

The relationship between tumor infiltrating immune cells and the prognosis of patients with lung adenocarcinoma

Tong¹,

Wang²,

Liu³

et al. 2023

J Thorac Dis

View full text Add to dashboard Cite

show abstract

“…A number of studies have noted correlations between immune cell levels and DFS. In particular, a study by Wu et al [ 32 ] showed that higher levels of CD68 and M1 macrophages are associated with worse DFS ( P < 0.0001). Based on the results obtained, a nomogram was constructed that included age and sex, the presence of visceral pleural invasion, the number of lymph nodes removed, clinical stage and the immune-related risk assessment nomogram.…”

Section: Discussionmentioning

confidence: 99%

Predictors of disease recurrence after radical resection and adjuvant chemotherapy in patients with stage IIb-IIIa squamous cell lung cancer: A retrospective analysis

Senchukova,

Kalinin,

Volchenko

2024

World J Exp Med

View full text Add to dashboard Cite

BACKGROUND Lung cancer (LC) is a global medical, social and economic problem and is one of the most common cancers and the leading cause of mortality from malignant neoplasms. LC is characterized by an aggressive course, and in the presence of disease recurrence risk factors, patients, even at an early stage, may be indicated for adjuvant therapy to improve survival. However, combined treatment does not always guarantee a favorable prognosis. In this regard, establishing predictors of LC recurrence is highly important both for determining the optimal treatment plan for the patients and for evaluating its effectiveness. AIM To establish predictors of disease recurrence after radical resection and adjuvant chemotherapy in patients with stage IIb-IIIa lung squamous cell carcinoma (LSCC). METHODS A retrospective case-control cohort study included 69 patients with LSCC who underwent radical surgery at the Orenburg Regional Clinical Oncology Center from 2009 to 2018. Postoperatively, all patients received adjuvant chemotherapy. Histological samples of the resected lung were stained with Mayer's hematoxylin and eosin and examined under a light microscope. Univariate and multivariate analyses were used to identify predictors associated with the risk of disease recurrence. Receiver operating characteristic curves were constructed to discriminate between patients with a high risk of disease recurrence and those with a low risk of disease recurrence. Survival was analyzed using the Kaplan-Meier method. The log-rank test was used to compare survival curves between patient subgroups. Differences were considered to be significant at P < 0.05. RESULTS The following predictors of a high risk of disease recurrence in patients with stage IIb-IIa LSCC were established: a low degree of tumor differentiation [odds ratio (OR) = 7.94, 95%CI = 1.08-135.81, P = 0.049]; metastases in regional lymph nodes (OR = 5.67, 95%CI = 1.09-36.54, P = 0.048); the presence of loose, fine-fiber connective tissue in the tumor stroma (OR = 21.70, 95%CI = 4.27-110.38, P = 0.0002); and fragmentation of the tumor solid component (OR = 2.53, 95%CI = 1.01-12.23, P = 0.049). The area under the curve of the predictive model was 0.846 (95%CI = 0.73-0.96, P < 0.0001). The sensitivity, accuracy and specificity of the method were 91.8%, 86.9% and 75.0%, respectively. In the group of patients with a low risk of LSCC recurrence, the 1-, 2- and 5-year disease-free survival (DFS) rates were 84.2%, 84.2% and 75.8%, respectively, while in the group with a high risk of LSCC recurrence the DFS rates were 71.7%, 40.1% and 8.2%, respectively (P < 0.00001). Accordingly, in the first group of patients, the 1-, 2- and 5-year overall survival (OS) rates were 94.7%, 82.5% and 82.5%, respectively, while in the second group of patients, the OS rates were 89.8%, 80.1% and 10.3%, respectively (P < 0.00001). CONCLUSION The developed method allows us to identify a group of patients at high risk of disease recurrence and to adjust to ongoing treatment.

show abstract

“…We found that LUSCs with low and high MSS estimates corresponded to tumours with immunoreactive and immunosuppressive TMEs, respectively. Recent findings by Wu et al revealed macrophage numbers were moderately correlated with the level of PD‐L1, CD133, and CD8 [ 66 ]. Consistently, our findings suggest that MSS and immunological indicators may be related.…”

Section: Discussionmentioning

confidence: 99%

Identification of tumour‐infiltrating myeloid subsets associated with overall survival in lung squamous cell carcinoma

Duan

Liu

et al. 2022

The Journal of Pathology

View full text Add to dashboard Cite

Lung squamous cell carcinoma (LUSC) is a primary subtype of lung cancer with limited therapeutic options and poor prognosis, and tumour‐infiltrating myeloid cells (TIMs) are key regulators of LUSC. However, the correlation between the abundance of TIM subtypes and clinical outcomes of LUSC remains unexplored. This study aimed to develop and validate a prognostic model for low‐ and high‐risk patients with LUSC based on myeloid cell microenvironments. TIM markers in the tumoural (T) and stromal (S) regions were quantified using immunohistochemistry for 502 LUSC patients. L1‐penalized Cox regression was used to develop a myeloid survival score (MSS) model based on the training cohort, followed by validation in distinct cohorts from multiple centres. RNA sequencing and immunostaining were used to examine the mechanisms of myeloid cells in LUSC progression and predict potential drug targets and therapeutic agents. Of the 12 myeloid markers, CD163T, CD163S, and S100A12T were highly associated with overall survival (OS) in LUSC patients. The MSS of the three myeloid signatures accurately categorized LUSC patients into risk categories, with an observable difference in OS between the training and validation cohorts. Tumours with high MSS were associated with enhanced antioxidative ability and hedgehog signalling and a shift to a more pro‐tumorigenic microenvironment, accompanied by a reduced tumour cell immunogenicity and increased CD8+ T cell exhaustion patterns. Additionally, in high‐risk patients, potential drug targets and compounds regulating hedgehog signalling were identified. Our study provides the first prognostic myeloid signature for LUSC, which may help advance precision medicine. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

show abstract

Macrophages-based immune-related risk score model for relapse prediction in stage I–III non-small cell lung cancer assessed by multiplex immunofluorescence

Cited by 12 publications

References 52 publications

The relationship between tumor infiltrating immune cells and the prognosis of patients with lung adenocarcinoma

The relationship between tumor infiltrating immune cells and the prognosis of patients with lung adenocarcinoma

Predictors of disease recurrence after radical resection and adjuvant chemotherapy in patients with stage IIb-IIIa squamous cell lung cancer: A retrospective analysis

Identification of tumour‐infiltrating myeloid subsets associated with overall survival in lung squamous cell carcinoma

Contact Info

Product

Resources

About