Identification of Subtype-Specific Prognostic Genes for Early-Stage Lung Adenocarcinoma and Squamous Cell Carcinoma Patients Using an Embedded Feature Selection Algorithm.
ABSTRACT: The existence of fundamental differences between lung adenocarcinoma (AC) and squamous cell carcinoma (SCC) in their underlying mechanisms motivated us to postulate that specific genes might exist relevant to prognosis of each histology subtype. To test on this research hypothesis, we previously proposed a simple Cox-regression model based feature selection algorithm and identified successfully some subtype-specific prognostic genes when applying this method to real-world data. In this article, we continue our effort on identification of subtype-specific prognostic genes for AC and SCC, and propose a novel embedded feature selection method by extending Threshold Gradient Descent Regularization (TGDR) algorithm and minimizing on a corresponding negative partial likelihood function. Using real-world datasets and simulated ones, we show these two proposed methods have comparable performance whereas the new proposal is superior in terms of model parsimony. Our analysis provides some evidence on the existence of such subtype-specific prognostic genes, more investigation is warranted.
Project description:To investigate the clinicopathological features and outcomes between node-negative, early-stage cervical squamous cell carcinoma (SCC) and adenocarcinoma (AC) after hysterectomy.Patients diagnosed with International Federation of Gynecology and Obstetrics (FIGO) stages I-IIA cervical SCC and AC between 1988 and 2013 were retrospectively reviewed using the Surveillance, Epidemiology, and End Results database. We used propensity score-matching to balance patient baseline characteristics. Univariate and multivariate Cox regression analyses were used for prognostic analyses of cause-specific survival (CSS) and overall survival (OS).A total of 9,858 patients were identified, comprising 6,117 patients (62.1%) and 3,741 (37.9%) patients with cervical SCC and AC, respectively. Compared with cervical SCC, cervical AC cases were more likely to be younger, diagnosed after 2000, white, and have well-differentiated and FIGO stage IB1 disease. For SCC and AC, the 10-year CSS rates were 93.4% and 94.7%, respectively (p=0.011), and the 10-year OS rates were 89.6% and 92.2%, respectively (p<0.001). Multivariate analysis revealed that age, ethnicity, tumor grade, and FIGO stage were independent prognostic factors of CSS and OS, but that histologic subtype was not associated with CSS and OS. In the propensity score-matched patient population, univariate and multivariate analyses also showed that histologic subtype was not associated with survival outcomes.Cervical AC has equivalent survival to cervical SCC in node-negative, early-stage disease after hysterectomy and lymphadenectomy.
Project description:We analyzed the gene expression patterns of 138 Non-Small Cell Lung Cancer (NSCLC) samples and developed a new algorithm called Coverage Analysis with Fisher's Exact Test (CAFET) to identify molecular pathways that are differentially activated in squamous cell carcinoma (SCC) and adenocarcinoma (AC) subtypes. Analysis of the lung cancer samples demonstrated hierarchical clustering according to the histological subtype and revealed a strong enrichment for the Wnt signaling pathway components in the cluster consisting predominantly of SCC samples. The specific gene expression pattern observed correlated with enhanced activation of the Wnt Planar Cell Polarity (PCP) pathway and inhibition of the canonical Wnt signaling branch. Further real time RT-PCR follow-up with additional primary tumor samples and lung cancer cell lines confirmed enrichment of Wnt/PCP pathway associated genes in the SCC subtype. Dysregulation of the canonical Wnt pathway, characterized by increased levels of ?-catenin and epigenetic silencing of negative regulators, has been reported in adenocarcinoma of the lung. Our results suggest that SCC and AC utilize different branches of the Wnt pathway during oncogenesis.
Project description:BACKGROUND:Monotonically expressed genes (MEGs) are genes whose expression values increase or decrease monotonically as a disease advances or time proceeds. Non-small cell lung cancer (NSCLC) is a multistage progression process resulting from genetic sequences mutations, the identification of MEGs for NSCLC is important. RESULTS:With the aid of a feature selection algorithm capable of identifying MEGs - the MFSelector method - two sets of potential MEGs were selected in this study: the MEGs across the different pathologic stages and the MEGs across the risk levels of death for the NSCLC patients at early stages. For the lung adenocarcinoma (AC) subtypes no statistically significant MEGs were identified across pathologic stages, however dozens of MEGs were identified across the risk levels of death. By contrast, for the squamous cell lung carcinoma (SCC) there were no statistically significant MEGs as either stage or risk level advanced. CONCLUSIONS:The pathologic stage of non-small cell lung cancer patients at early stages has no prognostic value, making the identification of prognostic gene signatures for them more meaningful and highly desirable.
Project description:Accurate classification of adenocarcinoma (AC) and squamous cell carcinoma (SCC) in lung cancer is critical to physicians' clinical decision-making. Exhaled breath analysis provides a tremendous potential approach in non-invasive diagnosis of lung cancer but was rarely reported for lung cancer subtypes classification. In this paper, we firstly proposed a combined method, integrating K-nearest neighbor classifier (KNN), borderline2-synthetic minority over-sampling technique (borderlin2-SMOTE), and feature reduction methods, to investigate the ability of exhaled breath to distinguish AC from SCC patients. The classification performance of the proposed method was compared with the results of four classification algorithms under different combinations of borderline2-SMOTE and feature reduction methods. The result indicated that the KNN classifier combining borderline2-SMOTE and feature reduction methods was the most promising method to discriminate AC from SCC patients and obtained the highest mean area under the receiver operating characteristic curve (0.63) and mean geometric mean (58.50) when compared to others classifiers. The result revealed that the combined algorithm could improve the classification performance of lung cancer subtypes in breathomics and suggested that combining non-invasive exhaled breath analysis with multivariate analysis is a promising screening method for informing treatment options and facilitating individualized treatment of lung cancer subtypes patients.
Project description:Non-small cell lung cancer (NSCLC) can be classified into the major subtypes adenocarcinoma (AC) and squamous cell carcinoma (SCC) subtypes. Although explicit molecular, histological and clinical characteristics have been reported for both subtypes, no specific therapy exists so far. However, the characterization of suitable molecular targets holds great promises to develop novel therapies in NSCLC. In the present study, global gene expression profiling of 58 human high grade NSCLC specimens revealed large transcriptomic differences between AC and SCC subtypes: More than 1.700 genes were found to be differentially expressed. Keywords: disease subtype analysis Overall design: The NSCLC patient collective was composed of the histological subtype adenocarcinoma (n=40) and squamous cell carcinoma (n=18). We subjected gene expression profiles of 40 AC and 18 SCC samples into further analysis. Unsupervised hierarchical clustering of all 58 NSCLC tumors using the 500 most variably expressed transcripts revealed two different clusters, which were strongly associated with the histological subtypes AC and SCC of NSCLC. Our result indicated that the major impact on global transcriptional changes was due to the NSCLC histology.
Project description:Large, population-based analyses of rectal squamous cell carcinoma (SCC) have not been previously conducted. We assessed patterns of care, prognostic factors, and outcomes of rectal SCC and adenocarcinoma (AC) in population-based cohorts. Surveillance, Epidemiology, and End Results (SEER) registry searches were performed (1998-2011), producing 42,308 nonmetastatic rectal cancer patients (999 SCC and 41,309 AC). Patient, tumor, and treatment characteristics were compared. Based on risk factors, SCC/AC groups were subdivided into low-, intermediate-, and high-risk groups. Overall survival (OS) was compared between histological and risk groups using Kaplan-Meier method and log-rank test. Multivariate logistic regression models evaluated prognostic factors for 5-year survival. Cox regression modeling was performed on propensity-matched data. Rectal SCC, more common in females and associated with larger tumors of higher grade, was more often treated with radiotherapy (RT) than surgery. Surgery was associated with higher OS in AC but not SCC, and RT had proportionally greater benefits in SCC. These effects of RT and surgery were retained when stratified into risk groups (particularly high/intermediate-risk). Favorable prognostic factors for survival included younger age, non-black race, SCC histology, size ?3.9 cm, localized stage, lower grade, surgery, and RT. For SCC, race, tumor grade, and surgery were not prognostic factors for survival. Cox regression modeling of propensity-matched data showed that AC histology increased risk of death versus SCC. In the largest analysis of rectal SCC to date, and in the notable absence (and unlikelihood) of prospective data, nonsurgical and RT-based treatment is recommended.
Project description:Background: An antibody panel is needed to definitively differentiate between adenocarcinoma (AC) and squamous cell carcinoma (SCC) in order to meet more stringent requirements for the histologic classification of lung cancers. Staining of desmosomal plaque-related proteins may be useful in the diagnosis of lung SCC.Materials and methods: We compared the usefulness of six conventional (CK5/6, p40, p63, CK7, TTF1, and Napsin A) and three novel (PKP1, KRT15, and DSG3) markers to distinguish between lung SCC and AC in 85 small biopsy specimens (41 ACs and 44 SCCs). Correlations were examined between expression of the markers and patients' histologic and clinical data.Results: The specificity for SCC of membrane staining for PKP1, KRT15, and DSG3 was 97.4%, 94.6%, and 100%, respectively, and it was 100% when the markers were used together and in combination with the conventional markers (AUCs of 0.7619 for Panel 1 SCC, 0.7375 for Panel 2 SCC, 0.8552 for Panel 1 AC, and 0.8088 for Panel 2 AC). In a stepwise multivariate logistic regression model, the combination of CK5/6, p63, and PKP1 in membrane was the optimal panel to differentiate between SCC and AC, with a percentage correct classification of 96.2% overall (94.6% of ACs and 97.6% of SCCs). PKP1 and DSG3 are related to the prognosis.Conclusions: PKP1, KRT15, and DSG3 are highly specific for SCC, but they were more useful to differentiate between SCC and AC when used together and in combination with conventional markers. PKP1 and DSG3 expressions may have prognostic value.
Project description:To compare the survival outcomes of patients with cervical squamous cell carcinoma (SCC) and adenocarcinoma/adenosquamous carcinoma (AC/ASC) among patients with locally advanced cervical cancer that were treated with definitive radiotherapy.The baseline characteristics and outcome data of patients with locally advanced cervical cancer who were treated with definitive radiotherapy between November 1993 and February 2014 were collected and retrospectively reviewed. A Cox proportional hazards regression model was used to investigate the prognostic significance of AC/ASC histology.The patients with AC/ASC of the cervix exhibited significantly shorter overall survival (OS) (p=0.004) and progression-free survival (PFS) (p=0.002) than the patients with SCC of the cervix. Multivariate analysis showed that AC/ASC histology was an independent negative prognostic factor for PFS. Among the patients who displayed AC/ASC histology, larger tumor size, older age, and incomplete response to radiotherapy were found to be independent prognostic factors. PFS was inversely associated with the number of poor prognostic factors the patients exhibited (the estimated 1-year PFS rates; 100.0%, 77.8%, 42.8%, 0.0% for 0, 1, 2, 3 factors, respectively).Locally advanced cervical cancer patients with AC/ASC histology experience significantly worse survival outcomes than those with SCC. Further clinical studies are warranted to develop a concurrent chemoradiotherapy (CCRT) protocol that is specifically tailored to locally advanced cervical AC/ASC.
Project description:Non-small cell lung cancer (NSCLC) has two major subtypes: adenocarcinoma (AC) and squamous cell carcinoma (SCC). The diagnosis and treatment of NSCLC are hindered by the limited knowledge about the pathogenesis mechanisms of subtypes of NSCLC. It is necessary to research the molecular mechanisms related with AC and SCC. In this work, we improved the logic analysis algorithm to mine the sufficient and necessary conditions for the presence states (presence or absence) of phenotypes. We applied our method to AC and SCC specimens, and identified [Formula: see text] lower and [Formula: see text] higher logic relationships between genes and two subtypes of NSCLC. The discovered relationships were independent of specimens selected, and their significance was validated by statistic test. Compared with the two earlier methods (the non-negative matrix factorization method and the relevance analysis method), the current method outperformed these methods in the recall rate and classification accuracy on NSCLC and normal specimens. We obtained [Formula: see text] biomarkers. Among [Formula: see text] biomarkers, [Formula: see text] genes have been used to distinguish AC from SCC in practice, and other six genes were newly discovered biomarkers for distinguishing subtypes. Furthermore, NKX2-1 has been considered as a molecular target for the targeted therapy of AC, and [Formula: see text] other genes may be novel molecular targets. By gene ontology analysis, we found that two biological processes ('epidermis development' and 'cell adhesion') were closely related with the tumorigenesis of subtypes of NSCLC. More generally, the current method could be extended to other complex diseases for distinguishing subtypes and detecting the molecular targets for targeted therapy.
Project description:Non-small cell lung cancer (NSCLC) can be classified into the major subtypes adenocarcinoma (AC) and squamous cell carcinoma (SCC) subtypes. Although explicit molecular, histological and clinical characteristics have been reported for both subtypes, no specific therapy exists so far. However, the characterization of suitable molecular targets holds great promises to develop novel therapies in NSCLC. In the present study, global gene expression profiling of 58 human high grade NSCLC specimens revealed large transcriptomic differences between AC and SCC subtypes: More than 1.700 genes were found to be differentially expressed. Experiment Overall Design: The NSCLC patient collective was composed of the histological subtype adenocarcinoma (n=40) and squamous cell carcinoma (n=18). We subjected gene expression profiles of 40 AC and 18 SCC samples into further analysis. Unsupervised hierarchical clustering of all 58 NSCLC tumors using the 500 most variably expressed transcripts revealed two different clusters, which were strongly associated with the histological subtypes AC and SCC of NSCLC. Our result indicated that the major impact on global transcriptional changes was due to the NSCLC histology.