The prognostic and predictive value of solid subtype in invasive lung adenocarcinoma.
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ABSTRACT:
SUBMITTER: Zhang Y
PROVIDER: S-EPMC4650946 | biostudies-other | 2014
REPOSITORIES: biostudies-other
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Project description:Background: Lung adenocarcinoma (LUAD) is the leading cause of cancer-related mortality worldwide. Molecular characterization-based methods hold great promise for improving the diagnostic accuracy and for predicting treatment response. The DNA methylation patterns of LUAD display a great potential as a specific biomarker that will complement invasive biopsy, thus improving early detection. Method: In this study, based on the whole-genome methylation datasets from The Cancer Genome Atlas (TCGA) and several machine learning methods, we evaluated the possibility of DNA methylation signatures for identifying lymph node metastasis of LUAD, differentiating between tumor tissue and normal tissue, and predicting the overall survival (OS) of LUAD patients. Using the regularized logistic regression, we built a classifier based on the 3616 CpG sites to identify the lymph node metastasis of LUAD. Furthermore, a classifier based on 14 CpG sites was established to differentiate between tumor and normal tissues. Using the Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression, we built a 16-CpG-based model to predict the OS of LUAD patients. Results: With the aid of 3616-CpG-based classifier, we were able to identify the lymph node metastatic status of patients directly by the methylation signature from the primary tumor tissues. The 14-CpG-based classifier could differentiate between tumor and normal tissues. The area under the receiver operating characteristic (ROC) curve (AUC) for both classifiers achieved values close to 1, demonstrating the robust classifier effect. The 16-CpG-based model showed independent prognostic value in LUAD patients. Interpretation: These findings will not only facilitate future treatment decisions based on the DNA methylation signatures but also enable additional investigations into the utilization of LUAD DNA methylation pattern by different machine learning methods.
| S-EPMC6492637 | biostudies-literature
Project description:BackgroundInvasive adenocarcinoma (IA) has a worse prognosis and different clinical management strategies compared to indolent lung adenocarcinoma including adenocarcinoma in situ (AIS) and minimally IA (MIA). The purpose of this study was to evaluate the predictive value of computed tomography (CT) value in differentiating invasive from indolent lung adenocarcinoma.MethodsThe pathological diagnoses and imaging data of confirmed lung adenocarcinomas manifested as lung nodules with homogeneous internal density which were surgically resected between August 2021 and July 2022 were retrospectively analyzed. Differences in CT values between invasive and indolent lung adenocarcinomas were compared in the primary cohort (n=766), and receiver operating characteristic (ROC) curve analysis was used to determine the optimal cut-off value. The predictive performance of the cut-off value was evaluated in the validation cohort (n=341).ResultsA total of 1,107 lung nodules from 1,014 patients were included in the total cohort. The CT values had a significant difference between invasive and indolent lung adenocarcinomas (P<0.001). Using the primary cohort, we determined the optimal cut-off value of -415 Hounsfield units (HU) of the CT value based on ROC curve, which showed good discrimination between IA and AIS/MIA in both the primary and validation cohorts (sensitivity, 85.98% and 87.42%, specificity, 87.67% and 84.74%, respectively).ConclusionsThe CT value of >-415 HU could be an effective predictor of invasive lung adenocarcinoma, thereby providing an appropriate clinical decision guide.
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Project description:Despite the success of therapies in lung cancer, more studies of new biomarkers for patient selection are urgently needed. The present study aims to analyze the role of galectin-3 (GAL-3) in the lung tumor microenvironment (TME) using tumorspheres as a model and explore its potential role as a predictive and prognostic biomarker in non-small cell lung cancer patients. For in vitro studies, lung adenocarcinoma (LUAD) and lung squamous carcinoma (LUSC) primary cultures from early-stage patients and commercial cell lines were cultured, using tumorsphere-forming assays and adherent conditions for the control counterparts. We analyzed the pattern of secretion and expression of GAL-3 using reverse transcription-quantitative real-time PCR (RTqPCR), immunoblot, immunofluorescence, flow cytometry, and immunoassay analysis. Our results using three-dimensional (3D) models of lung tumor cells revealed that soluble GAL-3 (sGAL-3) is highly expressed and secreted. To more accurately mimic the TME, a co-culture of tumorspheres and fibroblasts was used, revealing that GAL-3 could be important as an immunomodulatory molecule expressed and secreted in the TME, modulating immunosuppression through regulatory T cells (TREGS ). In the translational phase, we confirmed that patients with high expression levels of GAL-3 had more TREGS , which suggests that tumors may be recruiting this population through GAL-3. Next, we evaluated levels of sGAL-3 before surgery in LUAD and LUSC patients, hypothesizing that sGAL-3 could be used as an independent prognostic biomarker for overall survival and relapse-free survival in early-stage LUAD patients. Additionally, levels of sGAL-3 at pretreatment and first response assessment from plasma to predict clinical outcomes in advanced LUAD and LUSC patients treated with first-line pembrolizumab were evaluated, further supporting that sGAL-3 has a high efficiency in predicting durable clinical response to pembrolizumab with an area under curve of 0.801 (P = 0.011). Moreover, high levels might predict decreased progression-free survival and OS to anti-PD-1 therapy, with sGAL-3 being a prognosis-independent biomarker for advanced LUAD.
| S-EPMC10766205 | biostudies-literature
Project description:ObjectiveTo investigate the association between CT imaging features and survival outcomes in patients with primary invasive mucinous adenocarcinoma (IMA).Materials and methodsPreoperative CT image findings were consecutively evaluated in 317 patients with resected IMA from January 2011 to December 2015. The association between CT features and long-term survival were assessed by univariate analysis. The independent prognostic factors were identified by the multivariate Cox regression analyses. The survival comparison of IMA patients was investigated using the Kaplan-Meier method and propensity scores. Furthermore, the prognostic impact of CT features was assessed based on different imaging subtypes, and the results were adjusted using the Bonferroni method.ResultsThe median follow-up time was 52.8 months; the 5-year disease-free survival (DFS) and overall survival rates of resected IMAs were 68.5% and 77.6%, respectively. The univariate analyses of all IMA patients demonstrated that 15 CT imaging features, in addition to the clinicopathologic characteristics, significantly correlated with the recurrence or death of IMA patients. The multivariable analysis revealed that five of them, including imaging subtype (p = 0.002), spiculation (p < 0.001), tumor density (p = 0.008), air bronchogram (p < 0.001), emphysema (p < 0.001), and location (p = 0.029) were independent prognostic factors. The subgroup analysis demonstrated that pneumonic-type IMA had a significantly worse prognosis than solitary-type IMA. Moreover, for solitary-type IMAs, the most independent CT imaging biomarkers were air bronchogram and emphysema with an adjusted p value less than 0.05; for pneumonic-type IMA, the tumors with mixed consolidation and ground-glass opacity were associated with a longer DFS (adjusted p = 0.012).ConclusionCT imaging features characteristic of IMA may provide prognostic information and individual risk assessment in addition to the recognized clinical predictors.
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Project description:BackgroundBased on computed tomography (CT) findings of lung cancer, solid nodules have a much worse prognosis than subsolid nodules, even if the nodules are subcentimeter in size. There is, however, no systematic method for determining the prognosis of solid tumors on CT. This study aimed to discover the prognostic factor of early-stage solid lung adenocarcinoma using three-dimensional CT volumetry.MethodsPatients with pathological stage I solid lung adenocarcinoma who underwent complete resection between 2007 and 2012 were selected in this retrospective study. Clinicopathological data and preoperative multidetector CT findings, such as tumor size on the two-dimensional axial image, three-dimensional tumor volume between -600 and 199 HU, and three-dimensional solid volume between 0 and 199 HU, which corresponded to highly solid components, were compared between recurrence and non-recurrence. Furthermore, these radiological values were compared to pathological invasive volume (PIV).ResultsDuring this time, 709 patients had their lung cancer completely removed. From this cohort, 90 patients with pathological stage I solid lung adenocarcinoma were selected. In addition, recurrence was found in 26 patients (28.9%). Although two-dimensional axial image, serum carcinoembryonic antigen (CEA) level, and SUVmax on 18F fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) did not differ statistically between recurrent and non-recurrent patients, three-dimensional tumor and solid tumor volume did. Multivariate analysis indicated that three-dimensional solid tumor volume [hazard ratio: 2.440; 95% confidence interval (CI): 1.110-5.361, P=0.026] and epidermal growth factor receptor (EGFR) mutation (hazard ratio: 4.307; 95% CI: 1.328-13.977, P=0.015) were significantly associated with disease-free survival (DFS). When three-dimensional tumor and solid tumor volume were compared to PIV, three-dimensional solid tumor volume (3,091 mm3 on average) showed a highly similar value with PIV (2,930 mm3 on average), whereas three-dimensional tumor volume (6,175 mm3 on average) was significantly larger than PIV (P<0.001).ConclusionsIn patients with early-stage solid lung adenocarcinoma, the measurement of three-dimensional solid tumor volume, which is correlated with PIV, accurately predicted the postoperative outcome.
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Project description:Previous studies have demonstrated that members of the brain-expressed X-linked (BEX) family participate in a wide range of biological functions in normal and tumor tissues. However, their role and clinical significance in lung adenocarcinoma (LUAD) remains unclear. The present study investigated The Cancer Genome Atlas data and revealed that the BEX family was downregulated in LUAD tissues compared with adjacent non-cancerous tissues. Additionally, analysis of LUAD cohorts from the Oncomine database revealed similar results. Furthermore, the expression of BEX members was significantly decreased in several LUAD cell lines compared with normal lung epithelial cells . The aforementioned data mining and results suggested that the BEX family may be involved in the development of LUAD. Furthermore, receiver operating characteristic curve analysis revealed that BEX members exhibited high sensitivity and specificity for the diagnosis of patients with LUAD. The low expression levels of BEX1, BEX4 and BEX5 were associated with certain pathologic features, particularly in advanced LUAD. Survival analysis demonstrated that BEX members, particularly BEX4, were involved in the prognosis of patients with LUAD at early and late clinical stages. The results obtained in the current study suggested that BEX members may serve as potential tumor biomarkers for the diagnosis and prognosis of patients with LUAD.
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Project description:BackgroundInvasive mucinous adenocarcinoma (IMA) of the lung is a distinct histological subtype with unique clinical and pathological features. Despite previous genomic studies on lung IMA, the genetic characteristics and the prognosis-related biomarkers in Chinese surgically resected lung IMA remain unclear.MethodsWe collected 76 surgically resected primary tumors of invasive lung adenocarcinoma, including 51 IMA and 25 non-mucinous adenocarcinomas (non-IMA). IMA was further divided into pure-IMA (mucinous features≥90%) and mixed-IMA subgroups. Comprehensive genomic profiling based on targeted next-generation sequencing (NGS) of 425 genes was explored and genomic characteristics were evaluated for the correlation with postoperative disease-free survival (DFS).ResultsIMA had a unique genetic profile, with more diverse driver mutations and more tumor drivers/suppressors co-occurrence than that of non-IMA. The frequency of EGFR (72.0% vs. 40.0% vs. 23.1%, p=0.002) and ALK (undetected vs. 20.0% vs. 26.9%, p=0.015) alterations showed a trend of gradual decrease and increase from non-IMA to mixed-IMA to pure-IMA, respectively. The frequency of KRAS mutations in pure-IMA was higher than that in mixed-IMA, albeit statistically insignificant (23.1% vs. 4.0%, p=0.10). TP53 mutation was significantly less in pure-IMA compared to mixed-IMA and non-IMA (23.1% vs. 52.0% vs. 56.0%, p=0.03). Besides, IMA exhibited less arm-level amplifications (p=0.04) and more arm-level deletions (p=0.004) than non-IMA, and the frequency of amplification and deletion also showed a trend of gradual decrease and increase from non-IMA to mixed-IMA to pure-IMA, respectively. Furthermore, prognosis analysis in stage III IMA patients showed that patients harboring alterations in EGFR (mDFS=30.3 vs. 16.0 months, HR=0.19, P=0.027) and PI3K pathway (mDFS=36.0 vs. 16.0 months, HR=0.12, P=0.023) achieved prolonged DFS, while patients with poorly differentiated tumors (mDFS=14.1 vs. 28.0 months, HR=3.75, p=0.037) or with KRAS mutations (mDFS=13.0 vs. 20.0 months, HR=6.95, p=0.027) had shorter DFS. Multivariate analysis showed that KRAS mutations, PI3K pathway alterations, and tumor differentiation status were independent factors that have statistically significant influences on clinical outcomes of IMA patients.ConclusionOur study provided genomic insights into Chinese surgically resected lung IMA. We also identified several genomic features that may serve as potential biomarkers on postoperative recurrence in IMA patients with stage III disease.
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Project description:Chemoradioimmunotherapy of patients with pancreatic adenocarcinoma from the CapRI trial did not show any benefit of interferon-? in addition to a 5-fluorouracil (5FU)-based treatment. The aim of this study was to identify immunological parameters in patients from this trial to be used for predictive and/or prognostic purposes.The following methods were used: tumour immunohistology, FACS analyses, cytokine measurement, as well as cytotoxicity and ELIspot. Immunological parameters were correlated with patients' survival using the Kaplan-Meier method.Irrespective of therapy type, high lymphocyte accumulation in tumours and frequencies of NK cells and effector (eff) CD8(+) T cells in peripheral blood of the patients were associated with patients' survival. Amount of CD3(+) and effector-memory CD8(+) blood lymphocytes, expression of CD152 and interleukin (IL)-2 serum level showed a predictive value for chemoradioimmunotherapy. Tumoural accumulation of CD3(+) and CD8(+) cells was predictive for outcome of chemotherapy alone. Besides, we identified the frequencies of CD3(+) lymphocytes, effCD8(+) T cells and NK cells in the peripheral blood of the patients, and IL-10 amount in serum, to be predictive values for 5FU-based chemotherapy.Immunological parameters, identified in this trial as possible markers, may be of interest in personalized medicine towards the improvement of the treatment and prognosis of pancreatic carcinoma patients.
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Project description:Mitochondrial fission regulator 2 (MTFR2) belongs to the MTFR1 family, which plays a crucial role in regulating oxidative phosphorylation. Recent studies indicate that it also participates in cancer carcinogenesis and development; however, the clinical significance of MTFR2 in lung adenocarcinoma has not been fully confirmed. Our current study investigated the relationships between clinical characteristics and MTFR2 expression based on The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GSE31210) dataset, and clinical histopathological sample cohort. In addition, Kaplan-Meier and Cox regression analyses were additionally performed to evaluate the association between MTFR2 expression and patient survival. Gene set enrichment analysis (GESA) was conducted to spot possible pathways associated with MTFR2. Moreover, a single-sample GESA (ssGESA) was performed to evaluate the association between MTFR2 expression and immune cell infiltration. Cell colony formation assay, CCK-8 assay, cell cycle assay, and transwell assay were performed to verify the cell proliferation, migration, and invasion abilities after interfering with MTFR2 in lung cancer cells. Western blot assay was applied to identify the underlying protein levels. The results indicated that the elevated MTFR2 expression in lung adenocarcinoma samples correlated with T stage (P < 0.001), N stage (P = 0.005), M stage (P = 0.015), pathological stage (P = 0.002), and TP53 status (P < 0.001). Patients with a higher MTFR2 expression correlated with poorer overall survival (P < 0.01) and progression-free survival (P = 0.002). Knockdown of MTFR2 inhibited cell proliferation, migration, and invasion via AKT-cyclin D1 signaling and EMT pathways. Moreover, MTFR2 expression significantly positively correlated with Th2 cells (P < 0.001). Taken together, MTFR2 could serve as a novel prognostic indicator and therapeutic target for lung adenocarcinoma.
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