scholarly journals A Prognostic Model for Glioblastoma Patients Treated With Standard Therapy Based on a Prospective Cohort of Consecutive Non-Selected Patients From a Single Institution

2021 ◽  
Vol 11 ◽  
Author(s):  
Armita Armina Abedi ◽  
Kirsten Grunnet ◽  
Ib Jarle Christensen ◽  
Signe Regner Michaelsen ◽  
Aida Muhic ◽  
...  

BackgroundGlioblastoma patients administered standard therapies, comprising maximal surgical resection, radiation therapy with concomitant and adjuvant temozolomide, have a variable prognosis with a median overall survival of 15–16 months and a 2-year overall survival of 30%. The aim of this study was to develop a prognostic nomogram for overall survival for glioblastoma patients treated with standard therapy outside clinical trials.MethodsThe study included 680 consecutive, non-selected glioblastoma patients administered standard therapy as primary treatment between the years 2005 and 2016 at Rigshospitalet, Copenhagen, Denmark. The prognostic model was generated employing multivariate Cox regression analysis modeling overall survival.ResultsThe following poor prognostic factors were included in the final prognostic model for overall survival: Age (10-year increase: HR = 1.18, 95% CI: 1.08–1.28, p < 0.001), ECOG performance status (PS) 1 vs. 0 (HR = 1.30, 95% CI: 1.07–1.57, p = 0.007), PS 2 vs. 0 (HR = 2.99, 95% CI: 1.99–4.50, p < 0.001), corticosteroid use (HR = 1.42, 95% CI: 1.18–1.70, p < 0.001), multifocal disease (HR = 1.63, 95% CI: 1.25–2.13, p < 0.001), biopsy vs. resection (HR = 1.35, 95% CI: 1.04–1.72, p = 0.02), un-methylated promoter of the MGMT (O6-methylguanine-DNA methyltransferase) gene (HR = 1.71, 95% CI: 1.42–2.04, p < 0.001). The model was validated internally and had a concordance index of 0.65.ConclusionA nomogram for overall survival was established. This model can be used for risk stratification and treatment planning, as well as improve enrollment criteria for clinical trials.

2021 ◽  
Vol 20 ◽  
pp. 153303382110414
Author(s):  
Xiaoyong Li ◽  
Jiaqong Lin ◽  
Yuguo pan ◽  
Peng Cui ◽  
Jintang Xia

Background: Liver progenitor cells (LPCs) play significant roles in the development and progression of hepatocellular carcinoma (HCC). However, no studies on the value of LPC-related genes for evaluating HCC prognosis exist. We developed a gene signature of LPC-related genes for prognostication in HCC. Methods: To identify LPC-related genes, we analyzed mRNA expression arrays from a dataset (GSE57812 & GSE 37071) containing LPCs, mature hepatocytes, and embryonic stem cell samples. HCC RNA-Seq data from The Cancer Genome Atlas (TCGA) were used to explore the differentially expressed genes (DEGs) related to prognosis through DEG analysis and univariate Cox regression analysis. Lasso and multivariate Cox regression analyses were performed to construct the LPC-related gene prognostic model in the TCGA training dataset. This model was validated in the TCGA testing set and an external dataset (International Cancer Genome Consortium [ICGC] dataset). Finally, we investigated the relationship between this prognostic model with tumor-node-metastasis stage, tumor grade, and vascular invasion of HCC. Results: Overall, 1770 genes were identified as LPC-related genes, of which 92 genes were identified as DEGs in HCC tissues compared with normal tissues. Furthermore, we randomly assigned patients from the TCGA dataset to the training and testing cohorts. Twenty-six DEGs correlated with overall survival (OS) in the univariate Cox regression analysis. Lasso and multivariate Cox regression analyses were performed in the TCGA training set, and a 3-gene signature was constructed to stratify patients into 2 risk groups: high-risk and low-risk. Patients in the high-risk group had significantly lower OS than those in the low-risk group. Receiver operating characteristic curve analysis confirmed the signature's predictive capacity. Moreover, the risk score was confirmed to be an independent predictor for patients with HCC. Conclusion: We demonstrated that the LPC-related gene signature can be used for prognostication in HCC. Thus, targeting LPCs may serve as a therapeutic alternative for HCC.


2011 ◽  
Vol 29 (4_suppl) ◽  
pp. 210-210
Author(s):  
T. J. Huang ◽  
D. Li ◽  
Y. Li ◽  
S. P. Kar ◽  
S. Krishnan ◽  
...  

210 Background: The plasma membrane xCT cystine-specific subunit of the cystine/glutamate transporter contributes to chemotherapy resistance in pancreatic cancer by regulating intracellular glutathione levels and protecting cancer cells against oxidative stress. We previously noted that the rs7674870 single nucleotide polymorphism (SNP) of xCT correlated with overall survival in pancreatic cancer and may be predictive of platinum resistance. There are no data regarding xCT protein expression in pancreatic cancer or the functional significance of this SNP. Methods: Paraffin-embedded core and surgical biopsy tumor specimens from 49 patients with metastatic pancreatic adenocarcinoma were analyzed by immunohistochemistry (IHC) using an xCT specific antibody (Novus Biologicals). xCT protein IHC expression scores (product of intensity and percentage of staining cells) were analyzed in relation to overall survival and genotype of the patients using the one factor ANOVA test, Kaplan-Meier plot, log-rank test, and Cox regression analysis. Overall survival was measured from the date of diagnosis to the date of death or last follow-up. Results: Positive xCT expression was detected in 38 (78%) of the 49 samples, and 9 (18%) patients had high levels of expression. High xCT expression was associated with lower overall survival as compared with low expression (5.1 months versus 8.8 months; p = 0.119). In a multivariate Cox regression model with adjustment for prognostic parameters of age, sex, performance status and CA19-9 level, high xCT expression was associated with a 2.1-fold increased risk of death (p = 0.096). Performance status also correlated with overall survival (p = 0.027). Preliminary analysis on the genotype-phenotype association (n = 12) indicated that xCT expression was higher with the TT genotype than the TC/CC genotype (p = 0.115), which is consistent with the previous observation that the TT genotype was associated with reduced survival. Conclusions: These data provide supporting evidence for a possible role of cystine/glutamate transporter xCT subunit in pancreatic cancer progression and survival. Further pharmacogenomic and clinicopathologic studies are ongoing. No significant financial relationships to disclose.


2021 ◽  
Author(s):  
Liusheng Wu ◽  
Xiaoqiang Li ◽  
Jixian Liu ◽  
Da Wu ◽  
Dingwang Wu ◽  
...  

Abstract Objective: Autophagy-related LncRNA genes play a vital role in the development of esophageal adenocarcinoma.Our study try to construct a prognostic model of autophagy-related LncRNA esophageal adenocarcinoma, and use this model to calculate patients with esophageal adenocarcinoma. The survival risk value of esophageal adenocarcinoma can be used to evaluate its survival prognosis. At the same time, to explore the sites of potential targeted therapy genes to provide valuable guidance for the clinical diagnosis and treatment of esophageal adenocarcinoma.Methods: Our study have downloaded 261 samples of LncRNA-related transcription and clinical data of 87 patients with esophageal adenocarcinoma from the TCGA database, and 307 autophagy-related gene data from www.autuphagy.com. We applied R software (Version 4.0.2) for data analysis, merged the transcriptome LncRNA genes, autophagy-related genes and clinical data, and screened autophagy LncRNA genes related to the prognosis of esophageal adenocarcinoma. We also performed KEGG and GO enrichment analysis and GSEA enrichment analysis in these LncRNA genes to analysis the risk characteristics and bioinformatics functions of signal transduction pathways. Univariate and multivariate Cox regression analysis were used to determine the correlation between autophagy-related LncRNA and independent risk factors. The establishment of ROC curve facilitates the evaluation of the feasibility of predicting prognostic models, and further studies the correlation between autophagy-related LncRNA and the clinical characteristics of patients with esophageal adenocarcinoma. Finally, we also used survival analysis, risk analysis and independent prognostic analysis to verify the prognosis model of esophageal adenocarcinoma.Results: We screened and identified 22 autophagic LncRNA genes that are highly correlated with the overall survival (OS) of patients with esophageal adenocarcinoma. The area under the ROC curve(AUC=0.941)and the calibration curve have a good lineup, which has statistical analysis value. In addition, univariate and multivariate Cox regression analysis showed that the autophagy LncRNA feature of this esophageal adenocarcinoma is an independent predictor of esophageal adenocarcinoma.Conclusion: These LncRNA screened and identified may participate in the regulation of cellular autophagy pathways, and at the same time affect the tumor development and prognosis of patients with esophageal adenocarcinoma. These results indicate that risk signature and nomogram are important indicators related to the prognosis of patients with esophageal adenocarcinoma.


2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 7040-7040 ◽  
Author(s):  
P. Bonomi ◽  
C. Langer ◽  
M. O’Brien ◽  
K. O’Byrne ◽  
B. Bandstra ◽  
...  

7040 Background: A phase III trial compared PPX to docetaxel as 2nd-line treatment in pts with relapsed/refractory advanced NSCLC (STELLAR 2). While overall survival was similar between arms, the need for supportive measures to manage the effects of myelosuppression was significantly reduced in the PPX arm. The current analysis was performed to evaluate determinants of survival in the 2nd-line treatment of NSCLC. Methods: STELLAR 2 enrolled 849 pts, 427 on PPX and 422 on docetaxel; all patients were included in the analysis. Randomization between the study arms was stratified by tumor stage, performance status (PS), start of frontline chemotherapy (< 4 mo vs more than 4 mo), gender, and prior taxane therapy. Univariate and multivariate Cox regression analyses were performed to evaluate the impact of baseline characteristics on overall survival (OS). Results: At randomization, 29% of pts had received prior taxane, 14% were PS2, 80% had stage IV disease, and 31% had started frontline therapy within the prior 4 months. Risk factors significantly affecting survival as determined by multivariate analysis are listed in the table . These factors were consistent when treatment was added to the model. Prior exposure to taxane was not predictive of survival; tumor stage was a significant univariate predictor (p=0.0349), but had relatively less impact in the multivariate model. Conclusion: These analyses identified several factors associated with reduced survival benefit from standard second line therapy. Consequently, alternative treatment strategies may be necessary in patients with poor prognosis. For example, more tolerable agents may enhance the benefit/toxicity ratio in these patients. [Table: see text] [Table: see text]


2009 ◽  
Vol 27 (15_suppl) ◽  
pp. 7535-7535
Author(s):  
T. E. Stinchcombe ◽  
L. Hodgson ◽  
J. E. Herndon ◽  
M. J. Kelley ◽  
M. Cicchetti ◽  
...  

7535 Background: CALGB 39801 was designed to test whether treatment with induction chemotherapy and concurrent chemoradiotherapy (arm B) would improve OS in comparison to identical chemoradiotherapy alone (arm A), and demonstrated no significant benefit in OS for induction therapy. The objective of this analysis was to identify factors predictive of OS, and to use relevant factors to dichotomize pts into prognostic groups. Methods: Between July 1998 and May 2002, 331 pts were studied and included in a Cox proportional hazard regression analysis investigating previously identified prognostic factors: age (< 70 vs. ≥ 70 years), gender, race/ethnicity, hemoglobin (hgb) (< 13 vs. ≥13), performance status (PS) (0 vs.1), pretreatment weight loss (wt loss) (<5% vs. ≥ 5%), and treatment arm. Results: Cox regression analysis identified weight loss ≥ 5%, age ≥ 70, PS of 1, and hgb < 13 as predictive of worse survival (p<0.05), but not treatment arm (p=0.55). The median survival for pts with 0 (n=66), 1 (n=100), 2 (n=100), or ≥ 3 (n=65) risk factors were 24, 18, 10, and 8 months, respectively (p=0.0001). The pts were dichotomized into “poor prognosis” (PP) defined as ≥2 factors (n=165) and “good prognosis” (GP) defined as ≤ 1 factors (n=166). The hazard ratio (HR) for overall survival for the PP in comparison GP was 1.88 (95% CI, 1.49 to 2.37; p-value < 0.0001); the median survival times (MST) observed were 9 and 18 months, respectively (p<0.0001). The reasons for discontinuing treatment, and the rates of hematologic and non-hematologic adverse events were similar between the two groups. In the PP group the OS was similar between arms A (n=82) and B (n=83) (HR=0.97, 95% CI, 0.70 to 1.4; p=0.34); MST of 8.7 and 9.5 months, respectively. In the GP the OS was similar between arms A (n=79) and B (n=87) (HR=0.86, 95% CI, 0.63 to 1.1; p=0.87); MST of 19.3 and 17.6 months, respectively. Conclusions: Factors predictive of OS can be used to dichotomize pts into prognostic groups. Induction chemotherapy was not beneficial in either prognostic group. No significant financial relationships to disclose.


2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 3051-3051 ◽  
Author(s):  
Yukiya Narita ◽  
Keiji Sugiyama ◽  
Seiichiro Mitani ◽  
Kazunori Honda ◽  
Toshiki Masuishi ◽  
...  

3051 Background: Anti-PD-1 monotherapy has proven effective for the patients (pts) with MGC. However, the identification of biomarkers for predicting clinical outcomes remain as critical needs. We aimed to identify baseline characteristics associated with time to treatment failure (TTF) or overall survival (OS) for anti-PD-1/PD-L1 monotherapy as second- or later-line therapy in MGC. Methods: Routine blood count parameters and clinical characteristics at baseline were retrospectively investigated in 31 pts with MGC in Aichi Cancer Center Hospital. Endpoints were TTF and OS following anti-PD-1/PD-L1 monotherapy. Kaplan-Meiyer and Cox regression analysis were applied for survival analyses. Results: Patient characteristics were as follows: median age (range), 68 (47–83); ECOG performance status (PS) 0/1, 21/10; PM +ve/-ve, 12/19; No. of metastatic sites 1–2/≥3, 18/13; No. of prior chemotherapy regimens 1–2/≥3, 11/20; and absolute eosinophil count (AEC) <150/≥150 /μl, 14/17. Objective response rate and disease control rate (RECIST ver. 1.1) were 26% vs. 0% (odds ratio [OR], 3.76; P = 0.12) and 79% vs. 50% (OR, 3.58; P = 0.12) in the PM -ve group (Cohort A) and the PM +ve group (Cohort B), respectively. On univariate analysis, the pts with poor PS, PM +ve, and high AEC were significantly poor TTF; and poor PS and PM +ve were significantly identified as prognostic factors of poor OS. On multivariate analysis, only PM +ve was independent negative impact not only for TTF but also for OS. Median TTF and OS were 5.4 vs. 1.3 months (M) (adjusted hazard ratio [HR], 4.29; 95%CI, 1.60–11.5; P < 0.01) and 28.2 vs. 7.5 M (adjusted HR, 3.68; 95%CI, 1.25–10.8; P = 0.02) in Cohort A and Cohort B. Six-months TTF probabilities of 42% vs. 0% ( P = 0.03) and one-year OS probabilities of 58% vs. 8% ( P< 0.01) were observed in Cohort A compared to in Cohort B. Conclusions: PM -ve in the pts treated with anti-PD-1/PD-L1 monotherapy was associated with better efficacy. In the pts with PM -ve, anti-PD-1/PD-L1 monotherapy could be adapted in first-line therapy. [Table: see text]


2021 ◽  
pp. 153537022110535
Author(s):  
Nan Li ◽  
Kai Yu ◽  
Zhong Lin ◽  
Dingyuan Zeng

Uterine corpus endometrial carcinoma (UCEC) is the third most frequent gynecological malignancies in the female reproductive system. Long non-coding RNAs (lncRNAs) are closely involved in tumor progression. This study aimed to develop an immune subtyping system and a prognostic model based on lncRNAs for UCEC. Paired lncRNAs and non-negative matrix factorization were applied to identify immune subtypes. Enrichment analysis was conducted to assess functional pathways, immune-related genes, and cells. Univariate and multivariate Cox regression analysis were performed to analyze the relation between lncRNAs and overall survival (OS). A prognostic model was constructed and optimized by least absolute shrinkage and selection operator (LASSO) and Akaike information criterion (AIC). Two immune subtypes (C1 and C2) and four paired-prognostic lncRNAs closely associated with overall survival were identified. Some immune features, sensitivity of chemotherapy and immunotherapy, and the relation with immune escape showed variations between two subtypes. A nomogram established based on prognostic model and clinical features was effective in OS prediction. The immune subtyping system based on lncRNAs and the four-paired-lncRNA signature was predictive of UCEC prognosis and can facilitate personalized therapies such as immunotherapy or RNA-based therapy for UCEC patients.


Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 2004-2004
Author(s):  
Athanasios Galanopoulos ◽  
Christos K. Kontos ◽  
Nora-Athina Viniou ◽  
Ioannis Kotsianidis ◽  
Vassiliki Pappa ◽  
...  

Abstract Introduction - Aims: Several prognostic scoring systems have been developed for patients with myelodysplastic syndromes (MDS), including the International Prognostic System (IPSS), the WHO Prognostic Scoring System (WPSS) and the Revised IPSS (IPSS-R). We evaluated the prognostic value of the IPSS-R on an independent group of 2,582 Greek patients with MDS, registered in the Hellenic National MDS Registry. The aim of this multicenter study was to validate the IPSS-R as a predictor for leukemia-free survival (LFS) and overall survival (OS), in newly-diagnosed MDS patients and to compare its prognostic significance with that of IPSS and WPSS. Moreover, to investigate the predictive value of IPSS-R in association with other recognized prognostic variables, such as patient's age, baseline serum lactate dehydrogenase (LDH), and ferritin concentrations, IPSS, WPSS, Eastern Cooperative Oncology Group (ECOG) performance status, transfusion dependency, and response to first-line treatment. Methods: Clinicopathological data from 2,582 MDS patients, diagnosed between 1/2000 - 1/2015 and registered in the Hellenic National MDS Registry were analyzed. Patients with MDS/MPN were excluded. Data included age, gender, date of diagnosis, clinical characteristics, WHO-2008 classification, laboratory parameters, transfusion dependency, bone marrow aspirate and biopsy morphology, cytogenetic findings, and type of treatment. LFS was calculated from the date of initial diagnosis of MDS until bone marrow blast increased to ≥20% [transformation to acute myeloid leukemia (AML), according to the WHO classification], or last contact. OS was defined as the time from MDS diagnosis to death, or last contact. Patients alive and not having developed AML until last follow-up were censored for OS and LFS, respectively. Kaplan-Meier survival analysis and Cox regression analysis were performed with regard to LFS and OS. Differences between Kaplan-Meier curves were evaluated using the Mantel-Cox (log-rank) test. All significant variables identified by univariate Cox regression analysis and clinical factors important for MDS were used to build the multivariate Cox regression models. Multivariate Cox regression analysis included only those patients for whom the status of all variables was known, and comprised age, serum LDH, and ferritin levels, transfusion dependency, response to first-line treatment, IPSS, WPSS, and IPSS-R. Confidence intervals (CI) were estimated at the 95% level; all tests were two-sided, accepting p<0.05 as indicative of a statistically significant difference. All statistical analyses were performed with the statistical software SPSS (version 21). Results: 1,623 male (62.9%) and 959 female MDS patients with a median age of 74 years at diagnosis were included in the current study. Complete follow-up information was available for 2,376 patients. The estimated median OS was 58 months (95% CI = 52.9 - 63.1 months). For 1,974 patients, data used in the calculation of all three scoring systems were complete, thus allowing risk score calculation and comparison of the three risk assessment systems. Median OS was significantly different in patient subgroups classified according to IPSS, WPSS, and IPSS-R, as shown by the Kaplan-Meier survival analysis (p<0.001). Fig. 1 shows Kaplan-Meier OS curves of MDS patients stratified according to IPSS-R (p<0.001). Moreover, the comparison of the prognostic value of the IPSS, WPSS, and IPSS-R revealed that the IPSS-R was significantly superior to both, WPSS and IPSS (p<0.001 in all cases). Multivariate Cox regression analysis demonstrated that the high prognostic value of IPSS-R, in terms of LFS and OS, was independent of patient's age, serum LDH, and ferritin concentration, ECOG performance status, and transfusion dependency (p<0.001). Interestingly, besides IPSS-R, patient age and transfusion dependency retain their small - yet significant - prognostic impact in the multiparametric models, thus implying that these two parameters could add prognostic value to the IPSS-R. Conclusions: Our data support the notion that all three prognostic scores are very useful predictors for both, LFS and OS in MDS, yet IPSS-R is superior to IPSS and WPSS as a prognostic tool, with regard to OS. Disclosures No relevant conflicts of interest to declare.


Neurosurgery ◽  
2002 ◽  
Vol 50 (1) ◽  
pp. 41-47 ◽  
Author(s):  
Emmanuel C. Nwokedi ◽  
Steven J. DiBiase ◽  
Salma Jabbour ◽  
Joseph Herman ◽  
Pradip Amin ◽  
...  

ABSTRACT OBJECTIVE Stereotactic radiosurgery (SRS) has become an effective therapeutic modality for the treatment of patients with glioblastoma multiforme (GBM). This retrospective review evaluates the impact of SRS delivered on a gamma knife (GK) unit as an adjuvant therapy in the management of patients with GBM. METHODS Between August 1993 and December 1998, 82 patients with pathologically confirmed GBM received external beam radiotherapy (EBRT) at the University of Maryland Medical Center. Of these 82 patients, 64 with a minimum follow-up duration of at least 1 month are the focus of this analysis. Of the 64 assessable patients, 33 patients were treated with EBRT alone (Group 1), and 31 patients received both EBRT plus a GK-SRS boost (Group 2). GK-SRS was administered to most patients within 6 weeks of the completion of EBRT. The median EBRT dose was 59.7 Gy (range, 28–70.2 Gy), and the median GK-SRS dose to the prescription volume was 17.1 Gy (range, 10–28 Gy). The median age of the study population was 50.4 years, and the median pretreatment Karnofsky performance status was 80. Patient-, tumor-, and treatment-related variables were analyzed by Cox regression analysis, and survival curves were generated by the Kaplan-Meier product limit. RESULTS Median overall survival for the entire cohort was 16 months, and the actuarial survival rate at 1, 2, and 3 years were 67, 40, and 26%, respectively. When comparing age, Karnofsky performance status, extent of resection, and tumor volume, no statistical differences where discovered between Group 1 versus Group 2. When comparing the overall survival of Group 1 versus Group 2, the median survival was 13 months versus 25 months, respectively (P = 0.034). Age, Karnofsky performance status, and the addition of GK-SRS were all found to be significant predictors of overall survival via Cox regression analysis. No acute Grade 3 or Grade 4 toxicity was encountered. CONCLUSION The addition of a GK-SRS boost in conjunction with surgery and EBRT significantly improved the overall survival time in this retrospective series of patients with GBM. A prospective, randomized validation of the benefit of SRS awaits the results of the recently completed Radiation Therapy Oncology Group's trial RTOG 93-05.


PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e10628
Author(s):  
Juan Chen ◽  
Rui Zhou

Background Lung adenocarcinoma (LUAD) is the most common histological type of lung cancers, which is the primary cause of cancer‐related mortality worldwide. Growing evidence has suggested that tumor microenvironment (TME) plays a pivotal role in tumorigenesis and progression. Hence, we investigate the correlation of TME related genes with LUAD prognosis. Method The information of LUAD gene expression data was obtained from The Cancer Genome Atlas (TCGA). According to their immune/stromal scores calculated by the ESTIMATE algorithm, differentially expressed genes (DEGs) were identified. Then, we performed univariate Cox regression analysis on DEGs to obtain genes that are apparently bound up with LUAD survival (SurGenes). Functional annotation and protein-protein interaction (PPI) was also conducted on SurGenes. By validating the SurGenes with data sets of lung cancer from the Gene Expression Omnibus (GEO), 106 TME related SurGenes were generated. Further, intersection analysis was executed between the 106 TME related SurGenes and hub genes from PPI network, PTPRC and CD19 were obtained. Gene Set Enrichment Analysis and CIBERSORT analysis were performed on PTPRC and CD19. Based on the TCGA LUAD dataset, we conducted factor analysis and Step-wise multivariate Cox regression analysis for 106 TME related SurGenes to construct the prognostic model for LUAD survival prediction. The LUAD dataset in GEO (GSE68465) was used as the testing dataset to confirm the prognostic model. Multivariate Cox regression analysis was used between risk score from the prognostic model and clinical parameters. Result A total of 106 TME related genes were collected in our research totally, which were markedly correlated with the overall survival (OS) of LUAD patient. Bioinformatics analysis suggest them mainly concentrated on immune response, cell adhesion, and extracellular matrix. More importantly, among 106 TME related SurGenes, PTPRC and CD19 were highly interconnected nodes among PPI network and correlated with immune activity, exhibiting significant prognostic potential. The prognostic model was a weighted linear combination of the 106 genes, by which the low-OS LUAD samples could be separated from the high-OS samples with success. This model was also able to rebustly predict the situation of survival (training set: p-value < 0.0001, area under the curve (AUC) = 0.649; testing set: p-value = 0.0009, AUC = 0.617). By combining with clinical parameters, the prognostic model was optimized. The AUC achieved 0.716 for 3 year and 0.699 for 5 year. Conclusion A series of TME-related prognostic genes were acquired in this research, which could reflect immune disorders within TME, and PTPRC and CD19 show the potential to be an indicator for LUAD prognosis and tumor microenvironment modulation. The prognostic model constructed base on those prognostic genes presented a high predictive ability, and may have clinical implications in the overall survival prediction of LUAD.


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