Complex glandular pattern as an independent predictor of survival probability in lung adenocarcinoma
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PROVIDER: S-EPMC9554688 | biostudies-literature | 2022 Sep
REPOSITORIES: biostudies-literature
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Project description:BackgroundComplex glandular pattern (CGP) was included as high-grade pattern in the new grading system proposed by The International Association for the Study of Lung Cancer. We aimed to investigate the mutational profile and validate the prognostic significance and proper cut-off value to distinguish the aggressive behavior of CGP.MethodsCGP was defined as nests of tumor cells with sieve-like perforation, fused glands with irregular borders or back-to-back glands without intervening stroma. Patients were categorized into four groups according to the percentage of CGP component (0%, 1-19%, 20-49%, 50-100%). Cox's proportional hazards model was applied to analyze recurrence free survival (RFS) and overall survival (OS).ResultsA total of 950 patients with resected lung adenocarcinoma was enrolled. The most frequent driver mutation in this cohort was EGFR and was detected in 624 (65.7%) patients. EGFR mutation was more frequently observed in patients with <20% CGP than in patients with ≥20% CGP (73.6% vs. 60.2%), while KRAS mutation and ALK rearrangement was significantly associated with ≥20% CGP. Patients with 20% or greater CGP exhibited significant worse RFS (P<0.001) and OS (P<0.001) than their counterparts. Moreover, the multivariate Cox regression analysis confirmed that CGP (≥20%) was a risk factor for a worse RFS (P=0.001) and OS (P<0.001) independent of staging and gene mutation. Smaller portion of CGP (<20%) were comparable in RFS and OS to those without CGP (0%). There was also no significant difference in RFS and OS between the 20-49% and ≥50% group.ConclusionsOur study provided mutational profile of patients with different CGP, validated CGP as a negative prognostic factor and provided extra evidences for the optimal cut-off value of CGP percentage.
| S-EPMC9359943 | biostudies-literature
Project description:PurposeRecent researches showed the vital role of BACH1 in promoting the metastasis of lung cancer. We aimed to explore the value of BACH1 in predicting the overall survival (OS) of early-stage (stages I-II) lung adenocarcinoma. Patients and Methods. Lung adenocarcinoma cases were screened from the Cancer Genome Atlas (TCGA) database. Functional enrichment analysis was performed to obtain the biological mechanisms of BACH1. Gene set enrichment analysis (GSEA) was performed to identify the difference of biological pathways between high- and low-BACH1 groups. Univariate and multivariate COX regression analysis had been used to screen prognostic factors, which were used to establish the BACH1 expression-based prognostic model in the TCGA dataset. The C-index and time-dependent AUC curve were used to evaluate predictive power of the model. External validation of prognostic value was performed in two independent datasets from Gene Expression Omnibus (GEO). Decision analysis curve was finally used to evaluate clinical usefulness of the BACH1-based model beyond pathologic stage alone.ResultsBACH1 was an independent prognostic factor for lung adenocarcinoma. High-expression BACH1 cases had worse OS. BACH1-based prognostic model showed an ideal C-index and t-AUC and validated by two GEO datasets, independently. More importantly, the BACH1-based model indicated positive clinical applicability by DCA curves.ConclusionOur research confirmed that BACH1 was an important predictor of prognosis in early-stage lung adenocarcinoma. The higher the expression of BACH1, the worse OS of the patients.
| S-EPMC8758312 | biostudies-literature
Project description:ObjectivesTo explore whether complex glandular patterns (CGPs) have a potential role in the clinical management of patients with lung adenocarcinoma.MethodsWe included 356 patients with lung adenocarcinoma with available clinicopathologic information, gene mutations, and clinical outcomes for analysis.ResultsWe identified 54 (15.2%) CGP-predominant cases. The CGPs were associated with ALK rearrangement and HER2 mutation. Survival analysis showed that the clinical outcome of CGP-predominant patients was worse than that for acinar-predominant patients (overall survival [OS], 66.4 vs 90.3 months, P < .01; recurrence-free survival [RFS], 50.1 vs 73.1 months, P = .022) but was comparable with solid-predominant subtype tumors (OS, 66.4 vs 67.8 months, P = .558; RFS, 50.1 vs 41.3 months, P = .258). In particular, the coexistence of the cribriform and fused gland pattern was associated with the poorest survival, with a death risk increased by 2.25-fold (hazard ratio, 3.25; 95% confidence interval, 1.35-7.86, P = .009).ConclusionsOur results provide new insight into the potential role of CGPs in clinical management and will be beneficial for treatment decision making in patients with lung adenocarcinoma.
| S-EPMC5978020 | biostudies-literature
Project description:The active form of vitamin D, 1?,25-dihydroxyvitamin D(3) (1,25-D(3)), exerts antiproliferative effects in cancers, including lung adenocarcinoma (AC). CYP24A1 is overexpressed in many cancers and encodes the enzyme that catabolizes 1,25-D(3). The purpose of our study was to assess CYP24A1 as a prognostic marker and to study its relevance to antiproliferative activity of 1,25-D(3) in lung AC cells.Tumors and corresponding normal specimens from 86 patients with lung AC (stages I-III) were available. Affymetrix array data and subsequent confirmation by quantitative real time-PCR were used to determine CYP24A1 mRNA expression. A subsequent validation set of 101 lung AC was used to confirm CYP24A1 mRNA expression and its associations with clinical variables. The antiproliferative effects of 1,25-D(3) were examined using lung cancer cell lines with high as well as low expression of CYP24A1 mRNA.CYP24A1 mRNA was elevated 8- to 50-fold in lung AC (compared to normal nonneoplastic lung) and significantly higher in poorly differentiated cancers. At 5 years of follow-up, the probability of survival was 42% (high CYP24A1, n = 29) versus 81% (low CYP24A1, n = 57) (P = 0.007). The validation set of 101 tumors showed that CYP24A1 was independently prognostic of survival (multivariate Cox model adjusted for age, gender, and stage, P = 0.001). A549 cells (high CYP24A1) were more resistant to antiproliferative effects of 1,25-D(3) compared with SKLU-1 cells (low CYP24A1).CYP24A1 overexpression is associated with poorer survival in lung AC. This may relate to abrogation of antiproliferative effects of 1,25-D(3) in high CYP24A1 expressing lung AC.
| S-EPMC3058389 | biostudies-literature
Project description:Lung adenocarcinoma is the most common type of primary lung cancer. The purpose of this study was to delineate gene expression patterns for survival prediction in lung adenocarcinoma. Gene expression profiles of 82 (discovery set) and 442 (validation set 1) lung adenocarcinoma tumor tissues were analyzed using a systems biology-based network approach. We also examined the expression profiles of 78 adjacent normal lung tissues from 82 patients. We found a significant correlation of an expression module with overall survival (adjusted hazard ratio or HR=1.71; 95% CI=1.06-2.74 in discovery set; adjusted HR=1.26; 95% CI=1.08-1.49 in validation set 1). This expression module contained genes enriched in the biological process of the cell cycle. Interestingly, the cell cycle gene module and overall survival association were also significant in normal lung tissues (adjusted HR=1.91; 95% CI, 1.32-2.75). From these survival-related modules, we further defined three hub genes (UBE2C, TPX2, and MELK) whose expression-based risk indices were more strongly associated with poor 5-year survival (HR=3.85, 95% CI=1.34-11.05 in discovery set; HR=1.72, 95% CI=1.21-2.46 in validation set 1; and HR=3.35, 95% CI=1.08-10.04 in normal lung set). The 3-gene prognostic result was further validated using 92 adenocarcinoma tumor samples (validation set 2); patients with a high-risk gene signature have a 1.52-fold increased risk (95% CI, 1.02-2.24) of death than patients with a low-risk gene signature. These results suggest that a network-based approach may facilitate discovery of key genes that are closely linked to survival in patients with lung adenocarcinoma.
| S-EPMC3595338 | biostudies-literature
Project description:BackgroundTransforming growth factor β-induced protein (TGFBI) is a secreted protein that mediates cell anchoring to the extracellular matrix. This protein is downregulated in lung cancer, and when overexpressed, contributes to apoptotic cell death. Using a small series of stage IV non-small cell lung cancer (NSCLC) patients, we previously suggested the usefulness of TGFBI as a prognostic and predictive factor in chemotherapy-treated late-stage NSCLC. In order to validate and extend these results, we broaden the analysis and studied TGFBI expression in a large series of samples obtained from stage I-IV NSCLC patients.MethodsTGFBI expression was assessed by immunohistochemistry in 364 completely resected primary NSCLC samples: 242 adenocarcinomas (ADCs) and 122 squamous cell carcinomas (SCCs). Kaplan-Meier curves, log-rank tests and the Cox proportional hazards model were used to analyse the association between TGFBI expression and survival.ResultsHigh TGFBI levels were associated with longer overall survival (OS, P<0.001) and progression-free survival (PFS, P<0.001) in SCC patients who received adjuvant platinium-based chemotherapy. Moreover, multivariate analysis demonstrated that high TGFBI expression is an independent predictor of better survival in patients (OS: P=0.030 and PFS: P=0.026).ConclusionsTGFBI may be useful for the identification of a subset of NSCLC who may benefit from adjuvant therapy.
| S-EPMC3960613 | biostudies-literature
Project description:Complex focal chromosomal rearrangements in cancer genomes, also called "firestorms", can be scored from DNA copy number data. The complex arm-wise aberration index (CAAI) is a score that captures DNA copy number alterations that appear as focal complex events in tumors, and has potential prognostic value in breast cancer. This study aimed to validate this DNA-based prognostic index in breast cancer and test for the first time its potential prognostic value in ovarian cancer. Copy number alteration (CNA) data from 1950 breast carcinomas (METABRIC cohort) and 508 high-grade serous ovarian carcinomas (TCGA dataset) were analyzed. Cases were classified as CAAI positive if at least one complex focal event was scored. Complex alterations were frequently localized on chromosome 8p (n = 159), 17q (n = 176) and 11q (n = 251). CAAI events on 11q were most frequent in estrogen receptor positive (ER+) cases and on 17q in estrogen receptor negative (ER-) cases. We found only a modest correlation between CAAI and the overall rate of genomic instability (GII) and number of breakpoints (r = 0.27 and r = 0.42, p < 0.001). Breast cancer specific survival (BCSS), overall survival (OS) and ovarian cancer progression free survival (PFS) were used as clinical end points in Cox proportional hazard model survival analyses. CAAI positive breast cancers (43%) had higher mortality: hazard ratio (HR) of 1.94 (95%CI, 1.62-2.32) for BCSS, and of 1.49 (95%CI, 1.30-1.71) for OS. Representations of the 70-gene and the 21-gene predictors were compared with CAAI in multivariable models and CAAI was independently significant with a Cox adjusted HR of 1.56 (95%CI, 1.23-1.99) for ER+ and 1.55 (95%CI, 1.11-2.18) for ER- disease. None of the expression-based predictors were prognostic in the ER- subset. We found that a model including CAAI and the two expression-based prognostic signatures outperformed a model including the 21-gene and 70-gene signatures but excluding CAAI. Inclusion of CAAI in the clinical prognostication tool PREDICT significantly improved its performance. CAAI positive ovarian cancers (52%) also had worse prognosis: HRs of 1.3 (95%CI, 1.1-1.7) for PFS and 1.3 (95%CI, 1.1-1.6) for OS. This study validates CAAI as an independent predictor of survival in both ER+ and ER- breast cancer and reveals a significant prognostic value for CAAI in high-grade serous ovarian cancer.
| S-EPMC4286124 | biostudies-literature
Project description:The eukaryotic initiation factor 3 (eIF3) is the largest and most complex translation initiation factor in mammalian cells. It consists of 13 subunits and among which several were implicated to have significant prognostic effects on multiple human cancer entities. To examine the expression profiles of eIF3 subunits and determine their prognostic value in patients with lung adenocarcinoma (LUAD), the genomic data, survival data, and related clinical information were obtained from The Cancer Genome Atlas (TCGA) project for a secondary analysis. The results showed that among ten aberrantly expressed eIF3 subunits in tumours compared with adjacent normal counterparts (p < 0.05), only upregulated eIF3D could predict poor overall survival (OS) outcome independent of multiple clinicopathological parameters (HR = 2.043, 95% CI: 1.132-3.689, p = 0.018). Chi-square analysis revealed that the highly expressed eIF3D group had larger ratios of patients with advanced pathological stage (68/40 vs. 184/206, p = 0.0046), residual tumour (13/4 vs. 163/176, p = 0.0257), and targeted molecular therapy (85/65 vs. 138/164, p = 0.0357). In silico analysis demonstrated that the altered expression of eIF3D was at least regulated by both copy number alterations (CNAs) and the hypomethylation of cg14297023 site. In conclusion, high eIF3D expression might serve as a valuable independent prognostic indicator of shorter OS in patients with LUAD.
| S-EPMC6925810 | biostudies-literature
Project description:BackgroundDespite the recent development of molecular-targeted treatment and immunotherapy, survival of patients with esophageal adenocarcinoma (EAC) with poor prognosis is still poor due to lack of an effective biomarker. In this study, we aimed to explore the ceRNA and construct a multivariate gene expression predictor model using data from The Cancer Genome Atlas (TCGA) to predict the prognosis of EAC patients.MethodsWe conducted differential expression analysis using mRNA, miRNA and lncRNA transciptome data from EAC and normal patients as well as corresponding clinical information from TCGA database, and gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of those unique differentially expressed mRNAs using the Integrate Discovery Database (DAVID) database. We then constructed the lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) network of EAC and used Cox proportional hazard analysis to generate a multivariate gene expression predictor model. We finally performed survival analysis to determine the effect of differentially expressed mRNA on patients' overall survival and discover the hub gene.ResultsWe identified a total of 488 lncRNAs, 33 miRNAs, and 1207 mRNAs with differentially expressed profiles. Cox proportional hazard analysis and survival analysis using the ceRNA network revealed four genes (IL-11, PDGFD, NPTX1, ITPR1) as potential biomarkers of EAC prognosis in our predictor model, and IL-11 was identified as an independent prognostic factor.ConclusionsIn conclusion, we identified differences in the ceRNA regulatory networks and constructed a four-gene expression-based survival predictor model, which could be referential for future clinical research.
| S-EPMC7529573 | biostudies-literature
Project description:More than 35% of lung adenocarcinoma patients have bone metastases at diagnosis and have a poor survival. Periostin, a carboxylated matrix protein, mediates lung cancer cell dissemination by promoting epithelial-mesenchymal transition, and is involved in bone response to mechanical stress and bone formation regulation. This suggests that periostin may be used as a biomarker to predict survival in lung cancer patients. Serum periostin was assessed at diagnosis in a prospective cohort of 133 patients with lung adenocarcinoma of all stages. Patients were divided into localized and bone metastatic groups. Both groups were matched to healthy controls. Survival analysis and Cox proportional hazards models were conducted in the total population and in bone metastatic group. The median serum periostin level was higher in bone metastatic (n = 67; median: 1752 pmol/L) than in the localized group (n = 66; 861 pmol/L; p < 0.0001). Patients with high periostin (>median) had a poorer overall survival in the whole population (33.3 weeks vs. NR; p < 0.0001) and the bone metastatic group (24.4 vs. 66.1 weeks; p < 0.001). In multivariate analysis, patients with high periostin had increased risk of death (HR = 2.09, 95%CI [1.06-4.13]; p = 0.03). This was also found in the bone metastatic group (HR = 3.62, 95%CI [1.74-7.52]; p = 0.0005). Immunohistochemistry on bone metastasis biopsies showed periostin expression in the bone matrix and nuclear and cytoplasmic staining in cancer cells. Serum periostin was an independent survival biomarker in all-stage and in bone metastatic lung adenocarcinoma patients. IHC data suggest that periostin might be induced in cancer cells in bone metastatic niche in addition to bone microenvironment expression.
| S-EPMC8190464 | biostudies-literature