scholarly journals Mining the potential prognostic value of synaptosomal-associated protein 25 (SNAP25) in colon cancer based on stromal-immune score

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e10142
Author(s):  
Jinyan Zou ◽  
Darong Duan ◽  
Changfa Yu ◽  
Jie Pan ◽  
Jinwei Xia ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Prognostic Value ◽  
Enrichment Analysis ◽  
Rank Test ◽  
Hub Genes ◽  
Qrt Pcr ◽  
Log Rank Test ◽  
Poor Outcomes ◽  
Immune Score ◽  
Geo Database

Background Colon cancer is one of the deadliest tumors worldwide. Stromal cells and immune cells play important roles in cancer biology and microenvironment across different types of cancer. This study aimed to identify the prognostic value of stromal/immune cell-associated genes for colon cancer in The Cancer Genome Atlas (TCGA) database using bioinformatic technology. Methods The gene expression data and corresponding clinical information of colon cancer were downloaded from TCGA database. Stromal and immune scores were estimated based on the ESTIMATE algorithm. Sanger software was used to identify the differentially expressed genes (DEGs) and prognostic DEGs based on stromal and immune scores. External validation of prognostic biomarkers was conducted in Gene Expression Omnibus (GEO) database. Gene ontology (GO) analysis, pathway enrichment analysis, and gene set enrichment analysis (GSEA) were used for functional analysis. STRING and Cytoscape were used to assess the protein-protein interaction (PPI) network and screen hub genes. Quantitative real-time PCR (qRT-PCR) was used to validate the expression of hub genes in clinical tissues. Synaptosomal-associated protein 25 (SNAP25) was selected for analyzing its correlations with tumor-immune system in the TISIDB database. Results Worse overall survivals of colon cancer patients were found in high stromal score group (2963 vs. 1930 days, log-rank test P = 0.038) and high immune score group (2894 vs. 2230 days, log-rank test P = 0.076). 563 up-regulated and 9 down-regulated genes were identified as stromal-immune score-related DEGs. 70 up-regulated DEGs associated with poor outcomes were identified by COX proportional hazard regression model, and 15 hub genes were selected later. Then, we verified aquaporin 4 (AQP4) and SNAP25 as prognostic biomarkers in GEO database. qRT-PCR results revealed that AQP4 and SNAP25 were significantly elevated in colon cancer tissues compared with adjacent normal tissues (P = 0.003, 0.001). GSEA and TISIDB suggested that SNAP25 involved in cancer-related signaling pathway, immunity and metabolism progresses. Conclusion SNAP25 is a microenvironment-related and immune-related gene that can predict poor outcomes in colon cancer.

A prognostic miRNA based signature in early-stage HER2-positive breast cancer patients.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e12600-e12600
Author(s):  
Anna Adam-Artigues ◽  
Miguel Angel Beltran ◽  
Juan Antonio Carbonell-Asins ◽  
Sheila Zuñiga ◽  
Santiago Moragon ◽  
...  
Keyword(s):  
Systemic Treatment ◽  
Early Stage ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Risk Groups ◽  
Low Risk ◽  
Functional Enrichment ◽  
Rank Test ◽  
Prognostic Signature ◽  
Log Rank Test

e12600 Background: In early-stage HER2+ breast cancer (BC), escalation or de-escalation of systemic treatment is an unmet need. Integration of promising biomarkers into risk scoring will further help progressing in the field. We aim to develop a prognostic signature that integrates two miRNAs (A and B) and quantitative and qualitative clinical variables in patients diagnosed with HER2+ BC. Methods: This study was conducted in a retrospective cohort of 45 HER2+ BC patients. Patients received standard treatment for localized disease. We calculated a prognostic signature for disease-free survival (DFS) using principal components analysis for mixed data combining clinicopathological data (Ki67 and axillary lymph node [pN0, pN1, pN2, pN3]) and expression of two microRNAs (we used mir-16 as housekeeping). Multiple DFS prognostic signatures were calculated and goodness of fit was evaluated by means of Akaike’s Information Criterion (AIC) to perform Cox model selection. Signature was then dichotomized into “high risk” and “low risk” using maximally selected Log-Rank statistics by Hothorn and Lausen, as method for optimal cut-off. Kaplan-Meier curves, Log-Rank test and Breslow test were used to ascertain statistical differences in the probability of DFS between high and low risk groups. MiRNA targeted genes were selected and used to perform functional enrichment analysis with the KEGG pathway database. To select significant terms/pathways, p-values were adjusted by the Benjamini-Hochberg method (p < 0.05). Results: MiR-A and miR-B expression was higher in primary tumor of patients who relapse compared to those free of disease after treatment (p = 0.018 and 0.004, respectively). Both miRNAs were strongly correlated (r = 0.84). This signature was significantly associated with relapse of the disease (HR 1.72; CI 95%: 1.243–2.382; p < 0.01, AIC = 114.02). The optimal cut-off of this score was obtained and patients were classified into high and low risk groups. Median DFS of the high-risk was 44 months while it has been not reached yet across the low risk after a median follow-up of 67 months (HR 8.39; p = 0.005, AIC = 111.784). Significant differences in survival between both groups were found (log rank test p < 0.001; Breslow test p = 0.002). miR-A and miR-B functional enrichment analysis returned 55 significant pathways. Interestingly, P53 pathway, apoptosis and cell cycle which are closely related to tumorigenesis and treatment response, were in the top 5 enriched pathways. Conclusions: Both miRNAs included in this signature are related to important biological pathways associated to BC progression. Our new prognostic signature identifies patients with early-stage, HER2+ BC who might be candidates for escalated or de-escalated systemic treatment. This signature was able to classify patients for DFS in high or low risk groups at the moment of BC diagnosis. Further investigations to validate the value of this new signature are on-going.

Stromal Score-based Gene Signature: A Prognostic Prediction Model for Colon Cancer

2020 ◽  
Author(s):  
Jing Jia ◽  
Yuhan Dai ◽  
Qing Zhang ◽  
Peiyu Tang ◽  
Qiang Fu ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Overall Survival ◽  
Prediction Model ◽  
Differentially Expressed Genes ◽  
Gene Signature ◽  
Rank Test ◽  
Regression Analyses ◽  
Log Rank Test ◽  
Auc Value ◽  
Prognostic Prediction

Abstract BackgroundGrowing evidence has revealed the crucial roles of stromal cells in the microenvironment of various malignant tumors. However, efficient prognostic signatures based on stromal characteristics in colon cancer have not been well-established yet. The present study aimed to construct a stromal score-based multigene prognostic prediction model for colon cancer.MethodStromal scores were calculated based on the expression profiles of a colon cancer cohort from TCGA database applying the ESTIMATE algorithm. Linear models were used to identify differentially expressed genes between low-score and high-score groups by limma R package. Univariate and multivariate CoxPH regression analyses were used successively to select prognostic gene signature. An independent dataset from GEO was used as a validation cohort.ResultsLow stromal score was demonstrated to be a favorable factor to overall survival of colon cancer patients in TCGA cohort (log-rank test p = 0.0046). Three hundred and seven stromal score-related differentially expressed genes were identified. Through univariate and multivariate CoxPH regression analyses, a gene signature consisting of LEP, SYT3, NOG and IGSF11 was recognized to build a prognostic prediction model. Based on the predictive values estimated by the established integrated model, patients were divided into two groups with significantly different overall survival outcomes (log-rank test p < 0.0001). Time-dependent Receiver operating characteristic curve analyses suggested the satisfactory predictive efficacy for 5-year overall survival of the model (AUC value = 0.736). A nomogram with great predictive performance combining the multigene prediction model and clinicopathological factors was developed. The established model was verified to be of significant prognostic value for different subgroups in an independent colon cancer cohort from GEO database, which was demonstrated to be especially accurate for young patients (AUC value = 0.752). ConclusionThe well-established model based on stromal score-related gene signature might serve as a promising tool for the prognostic prediction of colon cancer.

miR-181 Expression is Associated With The Prognosis in Lung Cancer.

2020 ◽  
Author(s):  
Yue Zhao ◽  
Xiangjun Kong ◽  
Hongbing Wang
Keyword(s):  
Lung Cancer ◽  
Overall Survival ◽  
Prognostic Value ◽  
Cox Regression ◽  
Suppressor Gene ◽  
Rank Test ◽  
High Morbidity ◽  
Cox Regression Analysis ◽  
Log Rank Test ◽  
Cancer Tissues

Abstract Background: Lung cancer is one of the most common cancers, with high morbidity and mortality. MiRNAs are proved to play important roles in various human cancers. In our study, we aimed to explore the prognostic value of miR-181 in lung cancerMethods: Quantitative real-time polymerase chain reaction (QRT-PCR) was used to detect the expression level of miR-181 in lung cancer tissues and the paired non-cancerous tissues. The relationship between miR-181 expression and clinicopathologic parameters were analyzed by chi-square test. Kaplan-Meier method with log rank test was applied for overall survival analysis. Furthermore, the Cox regression analyses were performed to evaluate the prognostic value of miR-181 in lung cancer.Results: Down-regulated miR-181 expression was observed in lung cancer tissues (P<0.001), moreover, its expression was significantly correlated with TNM stage (P=0.015) and metastasis (P=0.000). In addition, lung cancer patients with lower miR-181 expression level had poorer overall survival than those with higher expression (log rank test, P=0.011). Cox regression analysis suggested that miR-181 was an independent prognostic factor for lung cancer (HR=1.961, 95%CI=1.135-3.388, P=0.016).Conclusion: MiR-181 may be a tumor suppressor gene in lung cancer, which can predict outcomes for the patients.

scholarly journals Clinicopathological Factors Influencing Lymph Node Yield in Colorectal Cancer: A Retrospective Study

2019 ◽  
Vol 2019 ◽  
pp. 1-6 ◽  
Author(s):  
Elena Orsenigo ◽  
Giulia Gasparini ◽  
Michele Carlucci
Keyword(s):  
Colorectal Cancer ◽  
Rectal Cancer ◽  
Colon Cancer ◽  
Lymph Node ◽  
Lymph Nodes ◽  
Cancer Patients ◽  
Rank Test ◽  
Lymph Node Yield ◽  
Log Rank Test ◽  
Lymph Node Retrieval

Many colorectal resections do not meet the minimum of 12 lymph nodes (LNs) recommended by the American Joint Committee on Cancer for accurate staging of colorectal cancer. The aim of this study was to investigate factors affecting the number of the adequate nodal yield in colorectal specimens subject to routine pathological assessment. We have retrospectively analysed the data of 2319 curatively resected colorectal cancer patients in San Raffaele Scientific Institute, Milan, between 1993 and 2017 (1259 colon cancer patients and 675 rectal cancer patients plus 385 rectal cancer patients who underwent neoadjuvant therapy). The factors influencing lymph node retrieval were subjected to uni- and multivariate analyses. Moreover, a survival analysis was carried out to verify the prognostic implications of nodal counts. The mean number of evaluated nodes was 24.08±11.4, 20.34±11.8, and 15.33±9.64 in surgically treated right-sided colon cancer, left-sided colon cancer, and rectal tumors, respectively. More than 12 lymph nodes were reported in surgical specimens in 1094 (86.9%) cases in the colon cohort and in 425 (63%) cases in the rectal cohort, and patients who underwent neoadjuvant chemoradiation were analysed separately. On univariate analysis of the colon cancer group, higher LNs counts were associated with female sex, right colon cancer, emergency surgery, pT3-T4 diseases, higher tumor size, and resected specimen length. On multivariate analysis right colon tumors, larger mean size of tumor, length of specimen, pT3-T4 disease, and female sex were found to significantly affect lymph node retrieval. Colon cancer patients with 12 or more lymph nodes removed had a significantly better long-term survival than those with 11 or fewer nodes (P=0.002, log-rank test). Rectal cancer patients with 12 or more lymph nodes removed approached but did not reach a statistically different survival (P=0.055, log-rank test). Multiple tumor and patients’ factors are associated with lymph node yield, but only the removal of at least 12 lymph nodes will reliably determine lymph node status.

scholarly journals Diagnostic biomarker candidates for pulpitis revealed by bioinformatics analysis of merged microarray gene expression datasets

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Ming Chen ◽  
Junkai Zeng ◽  
Yeqing Yang ◽  
Buling Wu
Keyword(s):  
Gene Expression ◽  
Dental Pulp ◽  
Bioinformatics Analysis ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Biological Pathways ◽  
Signalling Pathway ◽  
Diagnostic Biomarker ◽  
Hub Genes ◽  
Geo Database

Abstract Background Pulpitis is an inflammatory disease, the grade of which is classified according to the level of inflammation. Traditional methods of evaluating the status of dental pulp tissue in clinical practice have limitations. The rapid and accurate diagnosis of pulpitis is essential for determining the appropriate treatment. By integrating different datasets from the Gene Expression Omnibus (GEO) database, we analysed a merged expression matrix of pulpitis, aiming to identify biological pathways and diagnostic biomarkers of pulpitis. Methods By integrating two datasets (GSE77459 and GSE92681) in the GEO database using the sva and limma packages of R, differentially expressed genes (DEGs) of pulpitis were identified. Then, the DEGs were analysed to identify biological pathways of dental pulp inflammation with Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and Gene Set Enrichment Analysis (GSEA). Protein–protein interaction (PPI) networks and modules were constructed to identify hub genes with the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and Cytoscape. Results A total of 470 DEGs comprising 394 upregulated and 76 downregulated genes were found in pulpitis tissue. GO analysis revealed that the DEGs were enriched in biological processes related to inflammation, and the enriched pathways in the KEGG pathway analysis were cytokine-cytokine receptor interaction, chemokine signalling pathway and NF-κB signalling pathway. The GSEA results provided further functional annotations, including complement system, IL6/JAK/STAT3 signalling pathway and inflammatory response pathways. According to the degrees of nodes in the PPI network, 10 hub genes were identified, and 8 diagnostic biomarker candidates were screened: PTPRC, CD86, CCL2, IL6, TLR8, MMP9, CXCL8 and ICAM1. Conclusions With bioinformatics analysis of merged datasets, biomarker candidates of pulpitis were screened and the findings may be as reference to develop a new method of pulpitis diagnosis.

Early 18fluorodeoxyglucose PET Scan as a Prognostic Tool in Diffuse Large B-Cell Lymphoma Patients Treated with An Anthracycline-Based Chemotherapy Plus Rituximab.

Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 98-98 ◽  
Author(s):  
Violaine Safar ◽  
Jehan Dupuis ◽  
Fabrice Jardin ◽  
Christophe Fruchart ◽  
Stéphane Bardet ◽  
...  
Keyword(s):  
B Cell ◽  
Prognostic Value ◽  
Cell Lymphoma ◽  
Treatment Strategies ◽  
B Cell Lymphoma ◽  
Rank Test ◽  
Log Rank Test ◽  
Large B Cell Lymphoma ◽  
Dose Dense ◽  
Large B Cell

Abstract Abstract 98 Background: 18Fluorodeoxyglucose PET has been quickly integrated to the diagnostic and therapeutic armamentarium in diffuse large-B cell lymphoma (DLBCL). Moreover, early PET appears a promising prognostic tool for tailoring treatment strategies. We evaluated the predictive value of early PET in a large prospective cohort of patients treated with immunochemotherapy. Patients and methods: 112 previously untreated patients from three institutions were treated between January 2000 and October 2008 for DLBCL using an anthracycline-based regimen plus Rituximab. Chemotherapy was either an R-CHOP21 regimen (n=57) or a dose-dense regimen (R-ACVBP, n=31 or R-CHOP14, n= 24). PET was performed at diagnosis and after two cycles of treatment. Early PET results were interpreted visually as positive (PET2p) or negative (PET2n), as previously described1, but did not modify the scheduled therapy. Results: Median age at diagnosis was 59 years (range 20–79 years) and 67% of patients were males, 44% were over 60 years, 81% presented with an advanced Ann Arbor stage (III–IV), 29% had a poor performance status (ECOG 2-4), 36% had more than one extra-nodal site involved and LDH were elevated in 68%. The repartition on the basis of the International Prognosis Index was the following: low=5%, low-intermediate =35%, intermediate-high=37% and high risk=23%. After two cycles, 70 patients (63%) were PET2n and 42 (38%) were PET2p (38 patients in partial response and 4 with stable disease). Median follow-up was 38 months for living patients. Ten of 70 (14%) PET2n patients showed progression versus 22 of 42 (52%) PET2p patients. The estimated 5-year progression free survival (PFS) was 81% for PET2n and 47% for PET2p patients (log rank test, p<0.0001). Prognostic value of early PET was significant in terms of PFS whether patients were treated with R-CHOP21 (p=0.0006) or with dose-dense regimens (p=0.0056). Nine of 70 (13%) PET2n and 15 of 42 (36%) PET2p patients died. The estimated 5-year overall survival (OS) was 88% for PET2n and 62% for PET2p patients (log rank test, p<0.0034). Prognostic value of early PET was significant in terms of OS for patients treated with R-CHOP21 (p=0. 0225) but not for those treated with dose-dense regimens (p=0.133). Conclusion: Early PET after 2 cycles of treatment is a powerful tool to predict outcome in DLBCL patients treated with Rituximab combined with an anthracycline-based chemotherapy. It brings promising opportunities in the designing of new treatment strategies for DLBCL. Reference : 1 Haioun et al. Blood 2005; 106(4):1376–81. Disclosures: No relevant conflicts of interest to declare.

Benefit of fluorouracil and folinic acid adjuvant in colon cancer elderly patients

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 13564-13564 ◽  
Author(s):  
S. Lonardi ◽  
M. Stefani ◽  
A. Jirillo ◽  
C. Ghiotto ◽  
L. M. Pasetto ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Adjuvant Chemotherapy ◽  
Cancer Recurrence ◽  
Progression Free Survival ◽  
Tnm Stage ◽  
Stage Ii ◽  
Rank Test ◽  
Log Rank Test ◽  
Significant Difference ◽  
Unselected Population

13564 Background: Retrospective analyses on elderly people enrolled in clinical trials of adjuvant chemotherapy for colon cancer indicated the maintenance of the efficacy in that subset of patients (pts). However, data on the benefit of the routinely used adjuvant treatment in an unselected population of pts aged more than 65 years are few. Methods: All the charts of pts radically operated for colon cancer from 1996–2001 at Medical Oncology, Padua Hospital, were retrospectively analysed. 147 out of 330 pts consecutively treated with fluorouracil (FU)-based chemotherapy was aged 65 years or more at the time of diagnosis. Kaplan-Meyer progression-free-survival (PFS) and overall survival (OS) of stage II and III pts were calculated. Results: Pts characteristics were: males/females: 87/60, median age 71 (range 65–87), ECOG PS 0/1: 124/23, right/left colon primary tumor: 62/85, TNM stage: 24/63/60. 86 out of 147 pts were treated with the following regimen of adjuvant chemotherapy: FU 370 mg/mq + leucovorin (LV) 20 mg/mq day 1–5 q 28 for 6 cycles (Machover regimen, n=69), or FU 500 mg/mq + LV 250 mg/mq weekly × 6 q 56 for 4 cycles (Roswell Park regimen, n=17). Treated pts were staged as follows: TNM stage I/II/III: 1/38/47. No toxic death were observed and only nine of 86 pts (10.4%) stopped the treatment due to acute grade III gastrointestinal toxicity. At a median follow-up of 73.2 months, 19 out of 86 pts (22%) developed cancer recurrence (3-y PFS: 82.2%, 5-y PFS: 80.3%). Seventeen pts (19.7%) died, 13 (15.1%) due to tumor progression, 3 (3.4%) due to acute heart failure, and 1 (1.1%) due to chronic pulmonary disease (3-y OS: 88.8%, 5-y OS: 82.4%). No statistically significant difference in survival was observed comparing pts aged 65–70 (n=41) with pts more than 70 years old (n=45): 5-y OS 84.1% vs 77.8%, respectively (p=2.23, log rank test). A separate survival analysis on stage II pts was performed (n=63). 5 of 38 (13.1) treated pts dead, compared to 9 of 25 (36%) non treated pts; 5-y survival in the two groups were 86.6% and 60.8%, respectively (p= 0.03, log-rank test). Conclusions: The efficacy of adjuvant chemotherapy appears maintained in an unselected population of elderly pts. Surprisingly, our retrospective analysis suggest that even stage II pts may benefit of a fluorouracil-based well tolerated chemotherapy. No significant financial relationships to disclose.

Associations between K-ras mutation, smoking, and prognosis of pancreatic cancer.

2014 ◽  
Vol 32 (3_suppl) ◽  
pp. 298-298
Author(s):  
Kei Saito ◽  
Yousuke Nakai ◽  
Hiroyuki Isayama ◽  
Takashi Sasaki ◽  
Naminatsu Takahara ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Colon Cancer ◽  
Cox Regression ◽  
Performance Status ◽  
Rank Test ◽  
Ras Mutation ◽  
Kaplan Meier ◽  
Never Smokers ◽  
Poor Outcomes ◽  
The University

298 Background: Smoking is recognized as a risk factor for pancreatic cancer, but its associations with prognosis are not fully elucidated. Smoking was associated with poor outcomes in colon cancer, especially in patients with K-ras mutation (J Clin Oncol. 2013;31:2016-23). Therefore, we conducted this retrospective analysis of the associations of K-ras mutation, smoking and prognosis in patients with pancreatic cancer. Methods: Patients with pancreatic cancer who received surgery or chemotherapy at the University of Tokyo Hospital were retrospectively studied. The prognosis of patients with mutant and wild K-ras were compared. Overall survival was evaluated using Kaplan-Meier methods and compared by long-rank test. Cox regression models were used to calculate hazard ratios (HRs) to evaluate the prognostic factors in patients with pancreatic cancer with mutant K-ras or wild K-ras. Results: Between January 2009 and August 2013, K-ras mutation analysis was evaluated in 187 patients (47 surgical resection and 140 chemotherapy). K-ras mutation was detected in 74.3%. The rates of current-, ex- and never-smokers were 18.2%, 31.6% and 50.3%, respectively. In patients with mutant K-ras, the rate of male gender (46.0% vs. 29.0%), presence of distant metastasis (50.4% vs. 31.3%) and median CA19-9 (374 U/mL vs. 136 U/mL) were significantly higher than that in patients with wild K-ras. The rate of ever smokers (current- and ex-smokers) did not differ significantly (48.2% in mutant K-ras vs. 56.3% in wild K-ras, p=0.403). Median survival time (MST) was 16.7 (95%CI, 11.9-21.8) months in patients with mutant K-ras, compared with 20.3 (95%CI, 15.8-34.6) in patients with wild K-ras (p=0.193). Meanwhile, MST was 22.2 (95%CI, 16.9-27.9) vs. 14.8 (95%CI, 9.1-19.4) months in patients with and without smoking (p=0.024). After adjustment by age, gender, performance status, CA19-9 and treatment, HRs of smoking were 1.96 (95%CI, 1.06-3.68, p=0.032) in patients with mutant K-ras, but the association was not significant in patients with wild-K-ras (HR 1.35 [95%CI, 0.37-5.28], p=0.653). Conclusions: As previously reported in colon cancer, smoking was associated with poor prognosis in pancreatic cancer with K-ras mutation.

scholarly journals Immune Score Closely Associated With Tumor Microenvironment as A Prognostic Factor in Lung Adenocarcinoma

2020 ◽  
Author(s):  
Na Li ◽  
Xiaoling Chen ◽  
Chang Liu ◽  
Yong Feng ◽  
Xiaoqiang Sun ◽  
...  
Keyword(s):  
Prognostic Factors ◽  
High Risk ◽  
Prognostic Factor ◽  
Tumor Microenvironment ◽  
Lung Adenocarcinoma ◽  
Prognostic Significance ◽  
Risk Groups ◽  
Rank Test ◽  
Log Rank Test ◽  
Immune Score

Abstract Background: The tumor microenvironment plays a vital role in tumor biology and has recently attracted widespread attention. However, the prognostic significance of integrated immune scores in lung adenocarcinoma has not yet been identified. This study aimed to systematically estimate the association between immune scores and prognosis and develop a clinical nomogram to predict the survival of patients with lung adenocarcinoma. This study also systematically explored the underlying prognostic factors of the immune score in lung adenocarcinoma.Methods: Public datasets for lung adenocarcinoma was acquired from The Cancer Genome Atlas data portal. The immune score of each sample was calculated using the ESTIMATE algorithm. Univariate and multivariate Cox regression analyses identified several significant prognostic factors and further developed a prognostic nomogram. The C-index, calibration curve, and ROC curve were used to evaluate the predictive accuracy and discriminative ability of the resultant nomogram. Results: We found that patients with higher immune scores had a better prognosis (log rank test p = 0.0004). The nomogram that integrated the immune score could effectively stratify high-risk LUAD patients in terms of clinical response. Patients in the high-risk groups usually had a worse prognosis (log rank test p < 0.0001) and higher mortality. The mortality rate in high and low risk groups was 42.67% and 26.37%, respectively (p < 0.0001). In addition, correlation analysis showed that the immune score was significantly dependent on the mRNA expression of immunotherapy-associated biomarkers (PD-1, PD-L1, and LAG3) as well as on the presence of certain immune cell subtypes, but had no correlation with tumor mutation burden.Conclusion: The immune score is a prognostic factor in lung adenocarcinoma. The nomogram with an integrated immune score can effectively predict the survival of patients with lung adenocarcinoma. The mechanism by which the immune score estimates the prognosis of patients with lung adenocarcinoma is related to the tumor immune microenvironment.

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