Identification of Prognostic and Chemopredictive microRNAs for Non-Small-Cell Lung Cancer by Integrating SEER-Medicare Data.
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ABSTRACT:
SUBMITTER: Ye Q
PROVIDER: S-EPMC8306800 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Exosomal miRNAs are proposed as excellent candidate biomarkers for clinical applications. However, little is known about their potential roles as prognostic biomarkers in lung cancer. In this study, we explored the prognostic value of plasma exosomal microRNAs (miRNAs) for non-small-cell lung cancer (NSCLC). Using a quantitative polymerase chain reaction (qPCR) array panel, we analyzed 84 plasma exosomal miRNAs in 10 lung adenocarcinoma patients and 10 matched healthy controls. The qPCR array showed 30 aberrantly expressed exosomal miRNAs. Nine candidate miRNAs were selected based on differential expression and previous reports for further evaluating their prognostic roles in 196 NSCLC patients. Elevated levels of exosomal miR-23b-3p, miR-10b-5p and miR-21-5p were independently associated with poor overall survival (with hazard ratio [95% confidence interval]: 2.42 (1.45 - 4.04), P = 0.001; 2.22 (1.18 - 4.16), P = 0.013; 2.12 (1.28 - 3.49), P = 0.003, respectively). When compared to the clinical prognostic variables only model, adding the three exosomal miRNA signatures significantly improved survival predictive accuracy with an increase of time-dependent area under the receiver operating characteristic curve from 0.88 to 0.91 (P=0.015). Our results indicated that plasma exosomal miR-23b-3p, miR-10b-5p and miR-21-5p are promising non-invasive prognostic biomarkers of NSCLC.
| S-EPMC5355076 | biostudies-literature
Project description:Introduction: Accumulating evidence showed that a large number of microRNAs (miRNAs) are abnormally expressed in lung cancer tissues and play critical roles in cancer development and progression. The aim of this study is to identify the differentially expressed miRNAs (DEMs) between non-small cell lung cancer (NSCLC) and normal lung tissues, and evaluate the prognostic value and potential target gene functional enrichment of the DEMs. Materials and Methods: We first downloaded the high-throughput miRNA data from The Cancer Genome Atlas Project (TCGA) database, and subsequently analyzed the data using bioinformatics analysis including limma package in R, Kaplan-Meier curve and Log-rank method, and several online analysis tools. Results: A total of 125 DEMs and 138 DEMs were respectively identified in lung adenocarcinoma (LUAD) tissues and lung squamous cell carcinoma (LUSC) tissues compared with their matched normal tissues. Moreover, we found that the prognostic function of the eight miRNAs (miR-375, miR-148a, miR-29b-1 and miR-584 for LUAD; miR-4746, miR-326, miR-93 and miR-671 for LUSC). Furthermore, the two four-miRNA signatures were constructed and found to be an independent prognostic factor for LUAD and LUSC patients, respectively. Additionally, our results indicated that the target genes of eight miRNAs may be involved in various pathways related to NSCLC, including PI3K-Akt, TGF-beta, FoxO, Ras, GPI-anchor biosynthesis and metabolic, Rap1, HIF-1 and proteasome. Conclusion: Overall, eight miRNAs were closely correlated with survival of NSCLC patients, and the constructed two four-miRNA signatures could be respectively used as prognostic markers in LUAD and LUSC patients.
| S-EPMC6843868 | biostudies-literature
Project description:BackgroundThe population-based Surveillance, Epidemiology, and End Results (SEER) registries collect information on first-course treatment, including surgery, chemotherapy, radiation therapy, and hormone therapy. However, the SEER program does not release data on chemotherapy or hormone therapy due to uncertainties regarding data completeness. Activities are ongoing to investigate the opportunity to supplement SEER treatment data with other data sources.MethodsUsing the linked SEER-Medicare data, we examined the validity of the SEER data to identify receipt of chemotherapy and radiation therapy among those aged 65 and older diagnosed from 2000 to 2006 with bladder, female breast, colorectal, lung, ovarian, pancreas, or prostate cancer and hormone therapy among men diagnosed with prostate cancer at age 65 or older. Treatment collected by SEER was compared with treatment as determined by Medicare claims, using Medicare claims as the gold standard. The ?, sensitivity, specificity, positive predictive values, and negative predictive values were calculated for the receipt of each treatment modality.ResultsThe overall sensitivity of SEER data to identify chemotherapy, radiation, and hormone therapy receipt was moderate (68%, 80%, and 69%, respectively) and varied by cancer site, stage, and patient characteristics. The overall positive predictive value was high (>85%) for all treatment types and cancer sites except chemotherapy for prostate cancer.ConclusionsSEER data should not generally be used for comparisons of treated and untreated individuals or to estimate the proportion of treated individuals in the population. Augmenting SEER data with other data sources will provide the most accurate treatment information.
| S-EPMC4981219 | biostudies-literature
Project description:IntroductionThe crosstalk between receptor kinase signaling, such as EGFR and androgen receptor signaling, suggests a potential interaction between androgen deprivation therapy (ADT) and lung cancer outcome.MethodsWe employed the SEER-Medicare data of lung cancer patients diagnosed between 1988 and 2005 to test for an association between ADT for prostate cancer and lung cancer outcome. We employed the Kaplan-Meier method and Cox proportional hazard with log-rank test model to assess any significant impact of ADT on survival.ResultsWe included data from 367,750 lung cancer patients; 17.4%, 2.9%, 33.6% and 46.1% with stages I, II, III and IV, respectively; 84.5% were >65 years; 57.2% males; 84.2% Caucasians and 9.3% Blacks. There were 11,061 patients (3%) with an initial prostate cancer diagnosis followed by lung cancer (P-L group); 3017 (0.8%) with an initial diagnosis of lung cancer and subsequent prostate cancer diagnosis (L-P group); the remainder had only lung cancer (L group). Stage I lung cancer was most common in the L-P group compared to the L and P-L groups-54% vs. 17.13% vs. 17.92%, p < 0.0001 for L-P, L and P-L, respectively. The median OS for lung cancer diagnosis was 93 months versus 10 and 9 months, respectively, for the L-P, L and P-L subgroups. ADT was associated with improved survival on multivariate analysis, especially in Caucasian patients (HR of death: 0.86; 95% CI: 0.76-0.97; p = 0.012).ConclusionADT was associated with improved outcome for NSCLC, in line with the hypothesis of a role for the androgen receptor in lung cancer. Our findings support a systematic evaluation of the potential benefit of ADT as a therapy for lung cancer.
| S-EPMC9265064 | biostudies-literature
Project description:To rapidly identify new prognostic imaging biomarkers, we propose a bioinformatics approach that integrates gene expression and image data and leverages public gene expression data. We demonstrate our approach in non-small cell lung carcinoma patients for whom CT, PET/CT and gene expression data are available but without clinical follow-up. We extracted 180 image features and 56 high quality gene expression clusters, represented by metagenes. 115 image features were expressed in terms of metagenes, using sparse linear regression and cross-validation, with an accuracy of 65-86%. After mapping the signatures to a public gene expression dataset, 26 image features were significantly associated with recurrence-free survival and 22 with overall survival. A multivariate analysis identified multiple image features that were prognostic, independent of clinical covariates. Identifying prognostic imaging biomarkers by linking images and gene expression with outcomes in public gene expression datasets promises to accelerate the role of imaging in personalized medicine. We studied 26 cases of NSCLC with both PET/CT and microarray data under IRB approval from Stanford University and the Veterans Administration Palo Alto Health Care System. The collection of tissue samples consisted of a distribution of poorly- to well-differentiated adenocarcinomas and squamous cell cancers. The surgeon had removed necrotic debris during excision and sampled cavitary lesions to include as much solid component as practical. Then, from the excised tumor, he cut a 3 to 5 mm thick slice along its longest axis, and froze it within 30 minutes of excision. We retrieved the frozen tissue and extracted the RNA that was then processed by the Stanford Functional Genomics Facility using Illumina Whole Genome Bead Chips (Human HT-12 v3.0)
| S-ECPF-GEOD-28827 | biostudies-other
Project description:Background:MicroRNAs (miRNAs) have been found to play an important role in the development and outcomes for multiple human cancers. Their role as a prognostic biomarker in non-small-cell lung cancer (NSCLC) remains unclear. This meta-analysis aims to clarify the role of various miRNAs in the survival of NSCLC patients. Materials and Methods:All studies were identified through medical database search engines. A meta-analysis was conducted to assess the correlation between miRNAs expressions and overall survival among those NSCLC studies. Relevant data were extracted from each eligible study regarding baseline characteristics and key statistics such as hazard ratio (HR), 95% confidence interval (CI), and P value, which were utilized to calculate a pooled effect size. Result:Thirty-two studies were included in the meta-analysis. Using a random effect model, the combined HR and 95% CI for overall survival (OS) was calculated as 1.59 (1.39-1.82), predicting a poor overall survival. Five miRNAs (miR-21, miR-155, miR-let-7, miR-148a, and miR-148b) were found to be of significance for predicting OS in at least two studies, hence, selected for subgroup analysis. Subgroup analysis disclosed that elevated levels of miR-21 and miR-155 in both cancer tissue and blood samples were associated with worse OS. Compared to American studies (I-squared: <0.001% and P value: 0.94), Asian and European studies exhibited greater heterogeneity in miRNA expression and relationship to OS (I-squared, P values were approximately 78.85%, <0.001 and 61.28%, 0.006, respectively). These subgroup analyses also highlighted that elevated expression of miR-21 and miR-155 and low levels of expression of miR-148a, miR-148b, and miR-let-7 were associated with poor prognosis in NSCLC. Conclusion:miR-21, miR-155, miR-148a, miR-148b, and miR-let-7 are consistently up- or downregulated in NSCLC and are associated with poor OS. These miRNAs show potential as useful prognostic biomarkers in the diagnosis, treatment, and follow-up of NSCLC.
| S-EPMC6260404 | biostudies-literature
Project description:Circulating microRNAs (miRNAs) are key regulators of the crosstalk between tumor cells and immune response. In the present study, miRNAs (let-7c, miR-26a, miR-30d, miR-98, miR-195, miR-202) reported to be involved in the polarization of macrophages were examined for associations with the outcomes of non-small cell lung cancer (NSCLC) patients (N = 125) treated with first-line platinum-based chemotherapy. RT-qPCR was used to analyze miRNA expression levels in the plasma of patients prior to treatment. In our results, disease progression was correlated with high miR-202 expression (HR: 2.335; p = 0.040). Additionally, high miR-202 expression was characterized as an independent prognostic factor for shorter progression-free survival (PFS, HR: 1.564; p = 0.021) and overall survival (OS, HR: 1.558; p = 0.024). Moreover, high miR-202 independently predicted shorter OS (HR: 1.989; p = 0.008) in the non-squamous (non-SqCC) subgroup, and high miR-26a was correlated with shorter OS in the squamous (SqCC) subgroup (10.07 vs. 13.53 months, p = 0.033). The results of the present study propose that the expression levels of circulating miRNAs involved in macrophage polarization are correlated with survival measures in NSCLC patients, and their role as potential biomarkers merits further investigation.
| S-EPMC8391493 | biostudies-literature
Project description:ObjectivesThe effectiveness and costs of new treatments should be assessed in relation to existing practice. We describe treatments, survival and costs for advanced or metastatic small cell lung cancer (SCLC) patients receiving systemic therapy in the period preceding the introduction of immunotherapies.Materials and methodsThis was a retrospective cohort study of patients aged ?65 years, identified using linked Surveillance, Epidemiology, and End Results and Medicare databases. Individuals with a new primary diagnosis of SCLC between January 2007 and December 2013 were followed until December 2014. Chemotherapy treatments, health care visits and costs (in 2016 USD), and survival were determined by line of therapy.ResultsA total of 11 812 patients were identified with SCLC. First-line (1L) chemotherapy was received by 6509 (55.1%) patients, most (93.2%) with carboplatin- (71.0%) or cisplatin- (22.2%) based therapies, typically combined with etoposide (79.2%). Second- (2L) and third- (3L) line chemotherapies were received by 2238 (18.9%) and 679 (5.7%) patients, of which 48.4% and 30.9%, respectively, were platinum-based. The median durations of 1L, 2L, and 3L carboplatin-based therapies were 5.9, 4.8, and 5.4 months, respectively, and the corresponding durations of cisplatin-based therapies were 5.3, 4.2, and 5.3 months. During 1L, 2L, and 3L chemotherapies, patients averaged 8.2, 7.4, and 7.3 health care visits per month, respectively, and incurred total mean health care costs of $60 223, $42 636, and $35 903 per patient, respectively. Median survival from the start of 1L, 2L, and 3L chemotherapy was 9.2, 6.0, and 5.7 months, respectively.ConclusionFirst-line chemotherapy was primarily platinum-based, and a plethora of different regimens was used for 2L and 3L chemotherapies. Median survival from the start of 1L chemotherapy was 9 months, with an associated health care cost of $60 000. These data highlight an unmet medical need among SCLC patients receiving systemic therapy.
| S-EPMC6912057 | biostudies-literature
Project description:Lung adenocarcinoma (LUAD) is the most common histological subtype of non-small cell lung cancer, but novel biomarkers for early diagnosis are lacking. Extensive effort has been exerted to identify miRNA biomarkers in LUAD. Unfortunately, high inter-lab variability and small sample sizes have produced inconsistent conclusions in this field. To resolve the above-mentioned limitations, we performed a comprehensive analysis based on LUAD miRNome profiling studies using the robust rank aggregation (RRA) method. Moreover, miRNA-gene interaction network, pathway enrichment analysis and Kaplan-Meier survival curves were used to investigate the clinical values and biological functions of the identified miRNAs. A total of six common differentially expressed miRNAs (DEMs) were identified in LUAD. An independent cohort further confirmed that four miRNAs (miR-21-5p, miR-210-3p, miR-182-5p and miR-183-5p) were up-regulated and two miRNAs (miR-126-3p and miR-218-5p) were down-regulated in LUAD tissues. Pathway enrichment analysis also suggested that the above-listed six DEMs may affect LUAD progression via the estrogen signaling pathway. Survival analysis based on the TCGA dataset revealed the potential prognostic values of six DEMs in patients with LUAD (P-value<0.01). In conclusion, we identified a panel of six miRNAs from LUAD using miRNome profiling studies. Our results provide evidence for the use of these six DEMs as novel diagnostic and prognostic biomarkers for LUAD patients.
| S-EPMC5609990 | biostudies-literature
Project description:Non-small cell lung cancer (NSCLC) is one of the most common lung cancers worldwide. Accurate prognostic stratification of NSCLC can become an important clinical reference when designing therapeutic strategies for cancer patients. With this clinical application in mind, we developed a deep neural network (DNN) combining heterogeneous data sources of gene expression and clinical data to accurately predict the overall survival of NSCLC patients. Based on microarray data from a cohort set (614 patients), seven well-known NSCLC biomarkers were used to group patients into biomarker- and biomarker+ subgroups. Then, by using a systems biology approach, prognosis relevance values (PRV) were then calculated to select eight additional novel prognostic gene biomarkers. Finally, the combined 15 biomarkers along with clinical data were then used to develop an integrative DNN via bimodal learning to predict the 5-year survival status of NSCLC patients with tremendously high accuracy (AUC: 0.8163, accuracy: 75.44%). Using the capability of deep learning, we believe that our prediction can be a promising index that helps oncologists and physicians develop personalized therapy and build the foundation of precision medicine in the future.
| S-EPMC7069964 | biostudies-literature