Correlation of Small Bowel Gastrointestinal Stromal Tumor Computed Tomography Features with the Grade of Pathological Risk

Abstract Objectives: The aim of this study was to investigate the diagnostic value of computerized tomography (CT) features of small intestinal stromal tumors in terms of their degree of risk. Methods: The clinical data and CT data of 107 patients with small intestinal stromal tumors confirmed by surgery and pathology in our hospital from June 2012 to October 2020 were selected. According to the results of postoperative pathological risk, the patients were divided into high-risk and low-risk groups, wherein 67 cases were in high-risk group and 40 cases were in the low-risk group The maximum diameter, solid component plain scan, arterial phase CT value, venous phase CT value, and delayed phase CT value of the two groups were measured, and the enhancement degree of arterial phase, venous phase, delayed CT value, and lesion enhancement mode were calculated. The difference between the two groups was compared. An independent sample t-test was used to compare quantitative indices, and the chi-squared test or Fisher’s exact test was used for qualitative index comparison. A receiver operating characteristic (ROC) curve was used to evaluate the diagnostic value of the arterial phase CT value, venous phase CT value, delayed phase CT value, arterial phase enhancement degree, venous phase enhancement degree, delayed phase enhancement degree, and the enhanced net value-added in the risk degree of SBGISTs. The relationship between preoperative imaging findings and tumor risk was retrospectively analyzed. Results: Univariate analysis showed that there were significant differences in the lesion location, growth pattern, lesion ulcer, necrotic cystic degeneration, lobulation, boundary with surrounding tissues, plain scan density and lesion enhancement mode, CT value in arterial phase, increment in arterial phase, CT value in venous phase, increment in venous phase, CT value in delayed phase, increment in delayed phase, and enhancement value in lesion between the two groups (P < 0.05); there were no significant differences in sex, age, calcification, bleeding, clinical symptoms, and CT value (P > 0.05). The ROC curve analysis showed that the area under the curve (AUC) of the long diameter of the lesion was 0.959 (P = 0.000), the optimal critical point of the ROC curve was the lesion ≥ 4.80 cm, the sensitivity was 88.1%, the specificity was 97.5%, and the accuracy was 91.6%; for the low-risk group, the AUC was 0.788 (the largest, P = 0.000), the sensitivity was 77.5%, the specificity was 70.1%, and the accuracy was 72.9%. Multivariate analysis showed that non-uniform density (P = 0.030; odds ratio [OR]: 12.544; 95% confidence interval [CI]: 1.269–123.969), arterial phase CT value (P = 0.024; OR: 10.790; 95% CI: 1.374–84.754), and lesion length (P = 0.000; OR: 648.694; 95% CI: 40.541–10,379.714) were risk factors for SBGISTs. Conclusions: The CT features of small intestinal stromal tumors have certain characteristics, which can help to grade the risk of small intestinal stromal tumors before surgery.

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Case 5.6

Mayo Clinic Body MRI Case Review ◽

10.1093/med/9780199915705.003.0134 ◽

2014 ◽

pp. 253-253

Author(s):

Christine U. Lee ◽

James F. Glockner

Keyword(s):

Abdominal Pain ◽

Equilibrium Phase ◽

Arterial Phase ◽

Recurrent Pancreatitis ◽

Portal Venous Phase ◽

History Of ◽

Venous Phase ◽

Delayed Phase

37-year-old woman with a history of recurrent pancreatitis and abdominal pain Arterial phase (Figure 5.6.1A), portal venous phase (Figure 5.6.1B), equilibrium phase (Figure 5.6.1C), and 8-minute delayed phase (Figure 5.6.1D) postgadolinium 3D SPGR images show multiple splenic lesions that are initially hypoenhancing relative to adjacent spleen and become hyperintense on delayed images....

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Quantitative Analysis of Enhanced Computed Tomography in Differentiating Cystitis Glandularis and Bladder Cancer

BioMed Research International ◽

10.1155/2020/4930621 ◽

2020 ◽

Vol 2020 ◽

pp. 1-7

Author(s):

Hui Hua ◽

Yuanxiang Gao ◽

Jizheng Lin ◽

Feng Hou ◽

Jun wei Wang ◽

...

Keyword(s):

Bladder Cancer ◽

Quantitative Analysis ◽

Sensitivity And Specificity ◽

Arterial Phase ◽

Relative Enhancement ◽

Enhanced Ct ◽

Venous Phase ◽

Enhanced Computed Tomography ◽

Quantitative Indicators ◽

Delayed Phase

Objective. This study was performed to assess the value of quantitative analysis of enhanced computed tomography (CT) values in the differential diagnosis of bladder cancer and cystitis glandularis (CG). Methods. Eighty patients with bladder masses (39 with CG and 41 with bladder cancer) who underwent enhanced CT were retrospectively reviewed. The CT enhancement values of the lesion and normal bladder wall in the arterial phase, venous phase, and delayed phase were measured. The relative enhancement CT values (relative enhancement CT value=enhancement CT value of lesion−enhancement CT value of normal bladder) in the arterial phase, venous phase, and delayed phase were also calculated. The pathological results were used as the gold standard, and the area under the curve (AUC), sensitivity, and specificity were calculated for the six groups of quantitative indicators (enhanced CT values and relative enhanced CT values of CG and bladder cancer in the arterial, venous, and delayed phases). We performed the leave-group-out cross-validation method to validate the accuracy, AUC, sensitivity, and specificity. The differences in accuracy, AUC, sensitivity, and specificity among the six groups of quantitative indicators were compared by the t-test. Results. In a combined analysis of the AUC, sensitivity, and specificity performance, the best indicator was the arterial-phase relative enhancement CT value with a cut-off of 25.85 HU (AUC, 0.966; sensitivity, 95.1%; specificity, 92.3%). We used the 100-times leave-group-out cross-validation method to validate the accuracy, AUC, sensitivity, and specificity. Arterial-phase relative enhancement CT values showed the highest AUC and accuracy among the six groups, with statistical significance (P<0.05). Conclusion. Quantitative analysis of enhanced CT is of great clinical value in the differential diagnosis of CG and bladder cancer.

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The Application of Dual-phase Enhanced CT Scan in Distinguishing Adrenal Ganglioneuromas From Adrenal Lipid-poor Adenomas

10.21203/rs.3.rs-903344/v1 ◽

2021 ◽

Author(s):

Huajun Yu ◽

Jian Wang ◽

Zhongfeng Niu ◽

Meihua Shao

Keyword(s):

Ct Scan ◽

Arterial Phase ◽

Dual Phase ◽

Operating Characteristics ◽

Portal Venous Phase ◽

Ct Value ◽

Ct Findings ◽

Imaging Characteristics ◽

Enhanced Ct ◽

Venous Phase

Abstract Background:The utility of dual-phase enhanced CT scan in distinguishing ganglioneuromas from lipid-poor adenomas has not been reported. We aimed to prospectively compare CT findings helpful in distinguishing adrenal ganglioneuromas from adrenal lipid-poor adenomas. Methods: We estimated the CT findings of 258 adrenal masses (42 ganglioneuromas, 216 lipid-poor adenomas) in 258 patients from July 2008 to July 2020 with ganglioneuromas and July 2016 to July 2020 with lipid-poor adenomas. The CT features between ganglioneuromas and lipid-poor adenomas were compared. Results:Significant differences were detected in CT value of unenhanced (CTU), CT value of arterial phase (CTA), CT value of venous phase (CTV), degree of enhancement in arterial phase (DEAP), degree of enhancement in portal venous phase (DEPP), age, tumor size [long diameter (LD), short diameter (SD), mean diameter (MD)], shape, calcification between the ganglioneuroma and lipid-poor adenoma groups (P < 0.05).The results of receiver operating characteristics (ROC) analyses showed that areas under ROC curves (AUC) of CTU, CTA and CTV were 0.713, 0.878, and 0.914, respectively. When the cut-off values were set at 22.5 HU, 51.5 HU, and 53.5 HU for CTU, CTA, and CTV, respectively the three parameters had a sensitivity of 46.8%, 67.6%, and 88.0% and a specificity of 100%, 100%, and 88.1% in distinguishing between ganglioneuromas and lipid-poor adenomas.Conclusion: Dual-phase enhanced abdominal CT can exhibit some of the primary imaging characteristics of ganglioneuromas and lipid-poor adenomas used to distinguish between these two entities.

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The Relationship Between CT Signs of Computed Tomography and Risk Classification of Gastric Stromal Tumors

Journal of Medical Imaging and Health Informatics ◽

10.1166/jmihi.2021.3336 ◽

2021 ◽

Vol 11 (2) ◽

pp. 642-647

Author(s):

Wang Chen ◽

Rong Guo ◽

WeiGao Sun ◽

DingYou Lu

Keyword(s):

High Risk ◽

Risk Group ◽

High Risk Group ◽

Risk Classification ◽

Low Risk ◽

Stromal Tumors ◽

Medium Risk ◽

Solid Part ◽

The Relationship

Objective: The study aims to explore the role of computed tomography (CT) in clinical diagnosis, thus having a preliminary understanding of the relationship between CT signs and the risk of gastric stromal tumors (GSTs). Methods: In this study, 213 patients with GST with complete preoperative CT and postoperative pathological results in Yancheng No. 1 People's Hospital from January 2016 to August 2019 are selected as research objects. The patient's basic information is collected. CT machine (Toshiba 320 row CT and Siemens dualsource CT (Somatom Definition Flash)) is used to examine all patients. The obtained image data are evaluated. Patients are divided into low-risk group, medium risk group and high-risk group according to the risk classification standard of GST. The data collected are analyzed statistically. Results: After risk classification of all patients, 87 patients in low-risk group, 74 in medium-risk group and 52 in high-risk group are found. After further analysis of the risk classification, it is found that there is no significant difference in GST risk classification between the tumor sites (P > 0.05). In the GST risk classification, the smaller the tumor, the more the low-risk group, the larger the tumor, the more the high-risk group, the difference is statistically significant (P < 0.05). In the observation of the relationship between tumor growth pattern and risk classification, it is found that the number of intraluminal growth is the most, while mixed growth is the least (P < 0.05). Further analysis of tumor density, solid part enhancement, distant metastasis and risk grade show that there are significant differences (P < 0.05). Conclusion: As an auxiliary diagnostic method in clinic, CT signs can be used to analyze the relationship with risk grade from tumor location, tumor size, tumor growth mode, tumor density, solid part enhancement degree and tumor distant metastasis, so as to have a more accurate understanding of patients' situation, and provide experimental basis for the later application of CT signs in tumor and auxiliary diagnosis.

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Predicting the difference in treatment response and survival time of lung adenocarcinoma patients based on a prognostic risk model of glycolysis-related genes

10.21203/rs.3.rs-952541/v1 ◽

2021 ◽

Author(s):

Rongchang Zhao ◽

Dan Ding ◽

Yan Ding ◽

Rongbo Han ◽

Xiujuan Wang ◽

...

Keyword(s):

High Risk ◽

Lung Adenocarcinoma ◽

Survival Time ◽

Risk Score ◽

Roc Curve ◽

Cox Regression ◽

Risk Group ◽

Risk Groups ◽

Low Risk ◽

Significant Difference

Abstract Background Multiple factors affect the survival time of patients with lung adenocarcinoma (LUAD). Specifically, the therapeutic effect of medicines and the disease recurrence probability differs among patients with the same stage of LUAD. Thus, effective prognostic predictors need to be identified. Methods Based on the tumor mutation burden (TMB) data obtained by TCGA, LUAD was divided into high and low groups, and the differentially expressed glycolysis-related genes between the two groups were screened out. Cox regression was used to obtain a prognostic model. A receiver operating characteristic (ROC) curve and calibration curve were generated to evaluate the nomogram that was constructed based on clinicopathological characteristics and the risk score. Two datasets (GSE68465 and GSE11969) from Gene Expression Omnibus (GEO) were used to verify the prognostic performance of the gene. Furthermore, differences in immune cell distribution, immune-related molecules and drug susceptibility were assessed for their relationship with the risk score. Results We confirmed a 5-gene signature (FKBP4, HMMR, B4GALT1, ERO1L, ENO1) capable of dividing patients into two risk groups. There was a significant difference in overall survival (OS) times between the high-risk group and the low-risk group (P = 1.085e-4), with the low-risk group having a better survival outcome. Through multivariate Cox analysis, the risk score was confirmed to be an independent prognostic factor (HR = 1.289, 95% CI = 1.202-1.383, P < 0.001), and the ROC curve and nomogram exhibited accurate prediction performance. Validation of the data obtained in the GEO database yielded similar results. Additionally, there were significant differences in cisplatin, paclitaxel, gemcitabine, docetaxel, gefitiniband erlotinib sensitivity between the low-risk and high-risk groups. Conclusions Our results reveal that glycolysis-related gene are feasible predictors of LUAD patient survival and response to therapeutics.

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Identification and Validation of an Autophagy-Related lncRNA Signature for Patients With Breast Cancer

Frontiers in Oncology ◽

10.3389/fonc.2020.597569 ◽

2021 ◽

Vol 10 ◽

Author(s):

Ruyue Zhang ◽

Qingwen Zhu ◽

Detao Yin ◽

Zhe Yang ◽

Jinxiu Guo ◽

...

Keyword(s):

Breast Cancer ◽

High Risk ◽

Cancer Patients ◽

Roc Curve ◽

Prognostic Model ◽

Risk Group ◽

High Risk Group ◽

Potential Functions ◽

Low Risk ◽

Breast Cancer Patients

BackgroundAutophagy is a “self-feeding” phenomenon of cells, which is crucial in mammalian development. Long non-coding RNA (lncRNA) is a new regulatory factor for cell autophagy, which can regulate the process of autophagy to affect tumor progression. However, poor attention has been paid to the roles of autophagy-related lncRNAs in breast cancer.ObjectiveThis study aimed to construct an autophagy-related lncRNA signature that can effectively predict the prognosis of breast cancer patients and explore the potential functions of these lncRNAs.MethodsThe RNA sequencing (RNA-Seq) data of breast cancer patients was collected from The Cancer Genome Atlas (TCGA) database and the GSE20685 database. Multivariate Cox analysis was implemented to produce an autophagy-related lncRNA signature in the TCGA cohort. The signature was then validated in the GSE20685 cohort. The receiver operator characteristic (ROC) curve was performed to evaluate the predictive ability of the signature. Gene set enrichment analysis (GSEA) was used to explore the potential functions based on the signature. Finally, the study developed a nomogram and internal verification based on the autophagy-related lncRNAs.ResultsA signature composed of 9 autophagy-related lncRNAs was determined as a prognostic model, and 1,109 breast cancer patients were divided into high-risk group and low-risk group based on median risk score of the signature. Further analysis demonstrated that the over survival (OS) of breast cancer patients in the high-risk group was poorer than that in the low-risk group based on the prognostic signature. The area under the curve (AUC) of ROC curve verified the sensitivity and specificity of this signature. Additionally, we confirmed the signature is an independent factor and found it may be correlated to the progression of breast cancer. GSEA showed gene sets were notably enriched in carcinogenic activation pathways and autophagy-related pathways. The qRT-PCR identified 5 lncRNAs with significantly differential expression in breast cancer cells based on the 9 lncRNAs of the prognostic model, and the results were consistent with the tissues.ConclusionIn summary, our signature has potential predictive value in the prognosis of breast cancer and these autophagy-related lncRNAs may play significant roles in the diagnosis and treatment of breast cancer.

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Comprehensive Analysis of the Association Between the Glycolysis Prognostic Risk Signature and Immune Infiltration in Endometrial Cancer

10.21203/rs.3.rs-37313/v1 ◽

2020 ◽

Author(s):

Xiao Yang ◽

Xingchen Li ◽

Boqiang Shen ◽

Jingyi Zhou ◽

Yuan Cheng ◽

...

Keyword(s):

Overall Survival ◽

Dendritic Cells ◽

Endometrial Cancer ◽

High Risk ◽

Roc Curve ◽

Risk Group ◽

Gene Signature ◽

Low Risk ◽

Prognostic Signature ◽

Immune Infiltration

Abstract Background: Glycolysis is the primary mechanism of energy metabolism in tumor cells. The purpose of this study is to develop a glycolysis-related risk signature for endometrial cancer and analyze its relationship with immune function.Methods: The mRNA expression profiling and clinical information of endometrial cancer were downloaded from TCGA database. GSEA was performed to screen out gene sets related to glycolysis, and the R software was used to screen DEGs. Univariate Cox and LASSO regression analyses were used to construct a glycolysis-related prognostic signature for endometrial cancer. WGCNA were performed to identify the potential mechanisms associated with the prognostic signature. Immune scores, stromal scores and ESTIMATE scores were calculated based on the R “ESTIMATE” algorithm. The “CIBERSORT” algorithm was used to evaluate the infiltration of immune cells. ROC curve, nomogram, gene alteration, coexpression analyses and PPIs were also performed. Results: We identified a glycolysis-related gene signature (PFKM, PSMC4, NUP85, PDHA1, CDK1, CLDN9, CENPA, GPI, NUP155 and GPCI) for predicting the prognosis of endometrial cancer. Based on this gene signature, the patients were divided into high- and low-risk subgroups. The overall survival of patients in the high-risk subgroup was significantly lower than that of the low-risk group. Multivariate Cox regression analysis results showed that the ten-gene signature was an independent prognostic factor for endometrial cancer. The ROC curve confirmed the accuracy of the prognostic signature (AUC=0.730). The immune scores and ESTIMATE scores of patients in the high-risk subgroup were lower than those of the low-risk subgroup, while the low immune score and ESTIMATE scores were closely related to the poor prognosis of patients. The high-risk group was associated with lower cellular immune infiltration of resting dendritic cells, resting memory T cells and Tregs, while the overall survival rate of resting dendritic cells and Tregs in the low-proportion group was significantly lower than that in the high-proportion group. Conclusions: we constructed a glycolysis-related ten-gene signature to predict the survival and prognosis of endometrial cancer. Our findings may help to elucidate the mechanism of glycolysis and provide new ideas for targeted therapy and prognosis of endometrial cancer.

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Comparison of spectral computed tomography imaging parameters between squamous cell carcinoma and adenocarcinoma at the gastroesophageal junction

Technology and Health Care ◽

10.3233/thc-202343 ◽

2020 ◽

pp. 1-9

Author(s):

Yi-Chuan Ma ◽

Shun-Hua Zhang ◽

Zong-Yu Xie ◽

Fei Guo ◽

Ai-Qi Chen

Keyword(s):

Computed Tomography ◽

Squamous Cell Carcinoma ◽

Roc Curve ◽

Gastroesophageal Junction ◽

Ct Imaging ◽

Arterial Phase ◽

Spectral Ct ◽

Imaging Parameters ◽

Spectral Computed Tomography ◽

Venous Phase

OBJECTIVE: To compare the spectral computed tomography (CT) imaging parameters between squamous cell carcinoma (SCC) and adenocarcinoma (AC) at the gastroesophageal junction (GEJ). METHODS: A total of 80 patients were enrolled in this retrospective study. Among them, 35 were diagnosed with SCC (SCC group) and 45 were diagnosed with AC (AC group). All patients underwent an enhanced scan with spectral CT. The following CT imaging parameters were evaluated: iodine concentration (IC), water content (WC), effective atomic number (Eff-Z) and slope of the spectral HU curve (λHU) of lesions. Receiver operating characteristic (ROC) curve was used to analyze the predictive value of spectral CT imaging parameters for diagnosis of SCC and AC. RESULTS: Patients with SCC had lower IC, Eff-Z, and λHU in arterial phase and venous phase compared with AC (p< 0.05). There were no significant differences in WC between the two groups. ROC curve analyses revealed that IC, Eff-Z, and λHU in arterial phase and venous phase were predictors for diagnosis of SCC and AC (AUC > 0.5). Moreover, the IC, Eff-Z and λHU in venous phase had better differential diagnostic performances than that in arterial phase. CONCLUSIONS: Spectral CT could be useful in the differential diagnosis of SCC and AC at the GEJ. Therefore, a routine spectral CT scan is recommended for patients with carcinoma of the GEJ.

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A Nomogram Predicting Microvascular Invasion Risk in BCLC 0/A Hepatocellular Carcinoma after Curative Resection

BioMed Research International ◽

10.1155/2019/9264137 ◽

2019 ◽

Vol 2019 ◽

pp. 1-8

Author(s):

Shuai-Xiang Gao ◽

Rui Liao ◽

Hua-Qiang Wang ◽

Dan Liu ◽

Fang Luo

Keyword(s):

Risk Factors ◽

Hepatocellular Carcinoma ◽

Tumor Size ◽

Training Group ◽

Microvascular Invasion ◽

Arterial Phase ◽

Ct Value ◽

Delayed Phase ◽

Curative Hepatectomy ◽

Peritumoral Enhancement

Background. Numerous studies have shown that hepatocellular carcinoma (HCC) without microvascular invasion (MVI) may have better outcomes. This study established a preoperative MVI risk nomogram mainly incorporating three related risk factors of MVI in BCLC 0/A HCC after surgery. Methods. Independent predictors for the risk of MVI were investigated, and an MVI risk nomogram was established based on 60 patients in the training group who underwent curative hepatectomy for BCLC 0/A HCC and validated using a dataset in the validation group. Results. Univariate analysis in the training group showed that hepatitis viral B (HBV) DNA (P=0.034), tumor size (P<0.001), CT value in the venous phase (P=0.039), CT value in the delayed phase (P=0.017), peritumoral enhancement (P=0.013), visible small blood vessels in the arterial phase (P=0.002), and distance from the tumor to the inferior vena cava (IVC) (DTI, P=0.004) were risk factors significantly associated with the presence of MVI. According to multivariate analysis, the independent predictive factors of MVI, including tumor size (P=0.002), CT value in the delayed phase (P=0.018), and peritumoral enhancement (P=0.057), were incorporated in the corresponding nomogram. The nomogram displayed an unadjusted C-index of 0.851 and a bootstrap-corrected C-index of 0.832. Calibration curves also showed good agreement on the presence of MVI. ROC curve analyses showed that the nomogram had a large AUC (0.851). Conclusions. The proposed nomogram consisting of tumor size, CT value in the delayed phase, and peritumoral enhancement was associated with MVI risk in BCLC 0/A HCC following curative hepatectomy.

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Immune-Related lncRNA Pairs as Prognostic Signature and Immune-Landscape Predictor in Lung Adenocarcinoma

Frontiers in Oncology ◽

10.3389/fonc.2021.673567 ◽

2022 ◽

Vol 11 ◽

Author(s):

Zhengrong Yin ◽

Mei Zhou ◽

Tingting Liao ◽

Juanjuan Xu ◽

Jinshuo Fan ◽

...

Keyword(s):

High Risk ◽

Lung Adenocarcinoma ◽

Risk Score ◽

Roc Curve ◽

Prognostic Model ◽

Risk Group ◽

Univariate Analysis ◽

Low Risk ◽

Prognostic Signature ◽

Chemotherapy Drugs

BackgroundSuppressive tumor microenvironment is closely related to the progression and poor prognosis of lung adenocarcinoma (LUAD). Novel individual and universal immune-related biomarkers to predict the prognosis and immune landscape of LUAD patients are urgently needed. Two-gene pairing patterns could integrate and utilize various gene expression data.MethodsThe RNA-seq and relevant clinicopathological data of the LUAD project from the TCGA and well-known immune-related genes list from the ImmPort database were obtained. Co-expression analysis followed by an analysis of variance was performed to identify differentially expressed immune-related lncRNA (irlncRNA) (DEirlncRNA) between tumor and normal tissues. Two arbitrary DEirlncRNAs (DEirlncRNAs pair) in a tumor sample underwent pairwise comparison to generate a score (0 or 1). Next, Univariate analysis, Lasso regression and Multivariate analysis were used to screen survival-related DEirlncRNAs pairs and construct a prognostic model. The Acak information standard (AIC) values of the receiver operating characteristic (ROC) curve for 3 years are calculated to determine the cut-off point for high- or low-risk score. Finally, we evaluated the relationship between the risk score and overall survival, clinicopathological features, immune landscape, and chemotherapy efficacy.ResultsData of 54 normal and 497 tumor samples of LUAD were enrolled. After a strict screening process, 15 survival-independent-related DEirlncRNA pairs were integrated to construct a prognostic model. The AUC value of the 3-year ROC curve was 0.828. Kaplan–Meier analysis showed that patients with low risk lived longer than patients with high risk (p <0.001). Univariate and Multivariate Cox analysis suggested that the risk score was an independent factor of survival. The risk score was negatively associated with most tumor-infiltrating immune cells, immune score, and microenvironment scores. The low-risk group was correlated with increased expression of ICOS. The high-risk group had a connection with lower half inhibitory centration (IC50) of most chemotherapy drugs (e.g., etoposide, paclitaxel, vinorelbine, gemcitabine, and docetaxel) and targeted medicine—erlotinib, but with higher IC50 of methotrexate.ConclusionThe established irlncRNA pairs-based model is a promising prognostic signature for LUAD patients. Furthermore, the prognostic signature has great potential in the evaluation of tumor immune landscape and guiding individualized treatment regimens.

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