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Purpose: Metastasis is the main cause of mortality in non–small cell lung cancer (NSCLC) patients. Genes that can discriminate the invasion ability of cancer cells may become useful candidates for clinical outcome prediction. We identify invasion-associated genes through computational and laboratorial approach that supported this idea in NSCLC.Experimental Design: We first conducted invasion assay to characterize the invasion abilities of NCI-60 lung cancer cell lines. We then systematically exploited NCI-60 microarray databases to identify invasion-associated genes that showed differential expression between the high and the low invasion cell line groups. Furthermore, using the microarray data of Duke lung cancer cohort (GSE 3141), invasion-associated genes with good survival prediction potentials were obtained. Finally, we validated the findings by conducting quantitative PCR assay on an in-house collected patient group (n = 69) and by using microarray data from two public western cohorts (n = 257 and 186).Results: The invasion-associated four-gene signature (ANKRD49, LPHN1, RABAC1, and EGLN2) had significant prediction in three validation cohorts (P = 0.0184, 0.002, and 0.017, log-rank test). Moreover, we showed that four-gene signature was an independent prognostic factor (hazard ratio, 2.354, 1.480, and 1.670; P = 0.028, 0.014, and 0.033), independent of other clinical covariates, such as age, gender, and stage.Conclusion: The invasion-associated four-gene signature derived from NCI-60 lung cancer cell lines had good survival prediction power for NSCLC patients. (Clin Cancer Res 2009;15(23):7309–15)

Supplementary Data from A Four-Gene Signature from NCI-60 Cell Line for Survival Prediction in Non–Small Cell Lung Cancer

The tumorous niche may drive the plasticity of heterogeneity and cancer stemness, leading to drug resistance and metastasis, which is the main reason of treatment failure in most cancer patients. The aim of this study was to establish a tumor microenvironment (TME)-based screening to identify drugs that can specifically target cancer stem cells (CSCs) and cancer-associated fibroblasts (CAFs) in the TME. Methods: Lung cancer patient-derived cancer cell and CAFs were utilized to mimic the TME and reproduce the stemness properties of CSCs in vitro and develop a high-throughput drug screening platform with phenotypical parameters. Limiting dilution assay, sphere-forming and ALDH activity assay were utilized to measure the cancer stemness characteristics. In vivo patient-derived xenograft (PDX) models and single-cell RNA sequencing were used to evaluate the mechanisms of the compounds in CSCs and CAFs. Results: The TME-based drug screening platform could comprehensively evaluate the response of cancer cells, CSCs and CAFs to different treatments. Among the 1,524 compounds tested, several drugs were identified to have anti-CAFs, anticancer and anti-CSCs activities. Aloe-emodin and digoxin both show anticancer and anti-CSCs activity in vitro and in vivo, which was further confirmed in the lung cancer PDX model. The combination of digoxin and chemotherapy improved therapeutic efficacy. The single-cell transcriptomics analysis revealed that digoxin could suppress the CSCs subpopulation in CAFs-cocultured cancer cells and cytokine production in CAFs. Conclusions: The TME-based drug screening platform provides a tool to identify and repurpose compounds targeting cancer cells, CSCs and CAFs, which may accelerate drug development and therapeutic application for lung cancer patients.

Background Malignant pleural effusion (MPE)-macrophage (Mφ) of lung cancer patients within unique M1/M2 spectrum showed plasticity in M1–M2 transition. The M1/M2 features of MPE-Mφ and their significance to patient outcomes need to be clarified; furthermore, whether M1-repolarization could benefit treatment remains unclear. Methods Total 147 stage-IV lung adenocarcinoma patients undergoing MPE drainage were enrolled for profiling and validation of their M1/M2 spectrum. In addition, the MPE-Mφ signature on overall patient survival was analyzed. The impact of the M1-polarization strategy of patient-derived MPE-Mφ on anti-cancer activity was examined. Results We found that MPE-Mφ expressed both traditional M1 (HLA-DRA) and M2 (CD163) markers and showed a wide range of M1/M2 spectrum. Most of the MPE-Mφ displayed diverse PD-L1 expression patterns, while the low PD-L1 expression group was correlated with higher levels of IL-10. Among these markers, we identified a novel two-gene MPE-Mφ signature, IL-1β and TGF-β1, representing the M1/M2 tendency, which showed a strong predictive power in patient outcomes in our MPE-Mφ patient cohort (N = 60, p = 0.013) and The Cancer Genome Atlas Lung Adenocarcinoma dataset (N = 478, p Conclusions We identified MPE-Mφ on the M1/M2 spectrum and plasticity and described a two-gene M1/M2 signature that could predict the outcome of late-stage lung cancer patients. In addition, we found that “re-education” of these MPE-Mφ toward anti-cancer M1 macrophages using clinically applicable strategies may overcome tumor immune escape and benefit anti-cancer therapies.

Unlike the better-studied aberrant epigenome in the tumor, the clinicopathologic impact of DNA methylation in the tumor microenvironment (TME), especially the contribution from cancer-associated fibroblasts (CAFs), remains elusive. CAFs exhibit profound patient-to-patient tumorigenic heterogeneity. We asked whether such heterogeneity may be exploited to quantify the level of TME malignancy. We developed a robust and efficient methylome/transcriptome co-analytical system for CAFs and paired normal fibroblasts (NFs) from non-small-cell lung cancer patients. We found 14,781 CpG sites of CAF/NF differential methylation, of which 3,707 sites showed higher methylation changes in ever-smokers than in nonsmokers. Concomitant CAF/NF differential gene expression analysis pointed to a subset of 54 smoking-associated CpG sites with strong methylation-regulated gene expression. A methylation index that summarizes the β values of these CpGs was built for NF/CAF discrimination (MIND) with high sensitivity and specificity. The potential of MIND in detecting premalignancy across individual patients was shown. MIND succeeded in predicting tumor recurrence in multiple lung cancer cohorts without reliance on patient survival data, suggesting that the malignancy level of TME may be effectively graded by this index. Precision TME grading may provide additional pathological information to guide cancer prognosis and open up more options in personalized medicine.

Lung cancer is the leading cause of cancer death worldwide and cancer relapse accounts for the majority of cancer mortality. The mechanism is still unknown, especially in hereditary lung cancer without known actionable mutations. To identify genetic alternations involved in hereditary lung cancer and relapse is urgently needed. We collected genetic materials from a unique hereditary lung cancer patient's blood, first cancer tissue (T1), adjacent normal tissue (N1), relapse cancer tissue (T2), and adjacent normal tissue (N2) for whole genome sequencing. We identified specific mutations in T1 and T2, and attributed them to tumorigenesis and recurrence. These tumor specific variants were enriched in antigen presentation pathway. In addition, a lung adenocarcinoma cohort from the TCGA dataset was used to confirm our findings. Patients with high mutation burdens in tumor specific genes had decreased relapse‐free survival (P = 0.017, n = 186). Our study may provide important insight for designing immunotherapeutic treatment for hereditary lung cancer.

PURPOSE Epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) show efficacy in treating patients with lung adenocarcinoma with EGFR-activating mutations. However, a significant subset of targeted patients fail to respond. Unlike acquired resistance (AR), intrinsic resistance (IR) remains poorly understood. We investigated whether epigenomic factors contribute to patient-to-patient heterogeneity in the EGFR-TKI response and aimed to characterize the IR subpopulation that obtains no benefit from EGFR-TKIs. PATIENTS AND METHODS We conducted genome-wide DNA methylation profiling of 79 tumors sampled from patients with advanced lung adenocarcinoma before they received EGFR-TKI treatment and analyzed the patient responses. Pyrosequencing was performed in a validation cohort of 163 patients with EGFR-activating mutations. RESULTS A DNA methylation landscape of 216 CpG sites with differential methylation was established to elucidate the association of DNA methylation with the characteristics and EGFR-TKI response status of the patients. Functional analysis of 37 transcription-repressive sites identified the enrichment of transcription factors, notably homeobox ( HOX) genes. DNA methylation of HOXB9 (cg13643585) in the enhancer region yielded 88% sensitivity for predicting drug response (odds ratio [OR], 6.64; 95% CI, 1.98 to 25.23; P = .0009). Pyrosequencing validated that HOXB9 gained methylation in patients with a poor EGFR-TKI response (OR, 3.06; 95% CI, 1.13 to 8.19; P = .019). CONCLUSION Our data suggest that homeobox DNA methylation could be a novel tumor cellular state that can aid the precise categorization of tumor heterogeneity in the study of IR to EGFR-TKIs. We identified, for the first time, an epigenomic factor that can potentially complement DNA mutation status in discriminating patients with lung adenocarcinoma who are less likely to benefit from EGFR-TKI treatment, thereby leading to improved patient management in precision medicine.

Risk factors including genetic effects are still being investigated in lung adenocarcinoma (LUAD). Mitochondria play an important role in controlling imperative cellular parameters, and anomalies in mitochondrial function might be crucial for cancer development. The mitochondrial genomic aberrations found in lung adenocarcinoma and their associations with cancer development and progression are not yet clearly characterized. Here, we identified a spectrum of mitochondrial genome mutations in early-stage lung adenocarcinoma and explored their association with prognosis and clinical outcomes. Next-generation sequencing was used to reveal the mitochondrial genomes of tumor and conditionally normal adjacent tissues from 61 Stage 1 LUADs. Mitochondrial somatic mutations and clinical outcomes including relapse-free survival (RFS) were analyzed. Patients with somatic mutations in the D-loop region had longer RFS (adjusted hazard ratio, adjHR = 0.18, p = 0.027), whereas somatic mutations in mitochondrial Complex IV and Complex V genes were associated with shorter RFS (adjHR = 3.69, p = 0.012, and adjHR = 6.63, p = 0.002, respectively). The risk scores derived from mitochondrial somatic mutations were predictive of RFS (adjHR = 9.10, 95%CI: 2.93&ndash, 28.32, p &lt, 0.001). Our findings demonstrated the vulnerability of the mitochondrial genome to mutations and the potential prediction ability of somatic mutations. This research may contribute to improving molecular guidance for patient treatment in precision medicine.

// Hsuan-Yu Chen 1, 2, 3 , Chia-Hsin Liu 1, 4, 5, * , Ya-Hsuan Chang 1, * , Sung-Liang Yu 6 , Bing-Ching Ho 6 , Chung-Ping Hsu 7 , Tsung-Ying Yang 7 , Kun-Chieh Chen 7 , Kuo-Hsuan Hsu 7 , Jeng-Sen Tseng 7 , Jiun-Yi Hsia 7 , Cheng-Yen Chuang 7 , Chi-Sheng Chang 6 , Yu-Cheng Li 1 , Ker-Chau Li 1 , Gee-Chen Chang 7, 8, 9 , Pan-Chyr Yang 6, 10, 11 1 Institute of Statistical Sciences, Academia Sinica, Taipei, Taiwan 2 College of Medicine, National Taiwan University, Taipei, Taiwan 3 College of Life Science, National Taiwan University, Taipei, Taiwan 4 Bioinformatics Program, Taiwan International Graduate Program, Academia Sinica, Taipei, Taiwan 5 Institute of Biomedical Informatics, National Yang-Ming University, Taipei, Taiwan 6 Center of Genomic Medicine, National Taiwan University, Taipei, Taiwan 7 Taichung Veterans General Hospital, Taichung, Taiwan 8 Faculty of Medicine, School of Medicine, National Yang-Ming University, Taipei, Taiwan 9 Comprehensive Cancer Center, Taichung Veterans General Hospital, Taichung, Taiwan 10 Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan 11 Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan * Chia-Hsin Liu and Ya-Hsuan Chang contributed equally as the first author Correspondence to: Hsuan-Yu Chen, e-mail: hychen@stat.sinica.edu.tw Gee-Chen Chang, e-mail: august@vghtc.gov.tw Keywords: lung adenocarcinoma, DNA copy number abundance, ErbB family, EGFR-activating mutation, prognosis Received: July 07, 2015 Accepted: January 12, 2016 Published: January 27, 2016 ABSTRACT In this study, EGFR -activating mutation status and DNA copy number abundances of members of ErbB family were measured in 261 lung adenocarcinomas. The associations between DNA copy number abundances of ErbB family, EGFR -activating mutation status, and prognosis were explored. Results showed that DNA copy number abundances of EGFR , ERBB2 , ERBB3 , and ERBB4 had associations with overall survival in lung adenocarcinoma with EGFR -activating mutations. In the stratification analysis, only ERBB2 showed significant discrepancy in patients carrying wild type EGFR and other members of ErbB family in patients carrying EGFR -activating mutation. This indicated that CNAs of ErbB family had effect modifications of EGFR -activating mutation status. Findings of this study demonstrate potential molecular guidance of patient management of lung adenocarcinoma with or without EGFR -activating mutations.

e17512 Background: Very-small-nuclear circulating tumor cells (vsnCTCs) as a subset of CTCs with nuclear size < 8.5 μm associated with visceral metastases (VM) in advanced metastatic, castration-resistant prostate cancer (mCRPC). As VM predicts foreshortened survival, we hypothesized that vsnCTCs would be directly associated with poor overall survival (OS). Methods: Clinically annotated, blood samples from patients with mCRPC with survival follow-up within the Translational Oncology Program Blood & Biospecimen Bank were selected for analysis. CTCs were isolated and analyzed using the NanoVelcro assay. The nuclear size from all CTCs from each patient sample was compared to OS and progression-free survival (PFS) from the time of the blood draw. Results: A total of 76 patients had samples suitable for analysis. Sixty-six (87%) had CTCs; 49 (64%) were vsnCTC+ (≥1 vsnCTC). vsnCTCs were more common in mCRPC patients with previous androgen receptor signaling inhibitor (ARSI) therapy and/or 2 or more lines of treatment. OS was significantly shorter for vsnCTC+ than vsnCTC- patients (median 34 vs. 149 weeks; log-rank HR = 2.6; 95% CI = 1.5 to 4.5; P = 0.0006). Fifty patient samples were available for PFS analysis (i.e. drawn within 4 weeks of starting therapy). vsnCTC+ patients experienced more rapid progression than vsnCTC- patients (median 12 vs. 26 weeks, log-rank HR = 2.2, 95% CI = 1.3 to 4.0; P = 0.004). Multivariable Cox regression revealed that vsnCTC status was independently associated with OS and PFS. P-spline plot analysis showed that the HR of OS increased as the minimum CTC nuclear size decreased. The minimum CTC nuclear size was also independently associated with OS and PFS in a multivariable Cox regression analysis. Patients with prior use of androgen receptor signaling inhibitor (ARSI) therapy had significantly smaller minimum CTC nuclear size compared to those without prior use of ARSI. Average and median nuclear size did not strongly associate with OS or PFS. Conclusions: vsnCTC+ patients are at risk for more rapid clinical progression and have greater risk of death than vsnCTC-. We posit that the vsnCTC may be a biomarker of aggressive mCRPC with foreshortened survival. Interestingly, the CTCs with the smallest nuclei appear to best reflect the observed clinical behavior. This has potential importance in optimizing therapeutic choices and may point toward a unique biology relating nuclear size to aggressive molecular features. Our group continues to explore the biology underlying the vsnCTC.

Predicting a patient’s risk of recurrence after the resection of liver metastases from colorectal cancer is critical for evaluating and selecting therapeutic approaches. Clinical and pathologic parameters have shown limited accuracy thus far. Therefore, we combined the clinical status with a genomic approach to stratify relapse-free survival in colorectal cancer liver metastases patients. To identify new molecular and genetic signatures specific to colorectal cancer with liver metastasis (CRCLM) patients, we conducted DNA copy number profiling on a cohort of 21 Taiwanese CRCLM patients using a comparative genomic hybridization (CGH) array. We identified a three-gene signature based on differential copy number alteration between patients with different statuses of (1) recurrence and (2) synchronous metastasis. In relapse hotspot regions, only three genes (S100PBP, CSMD2, and TGFBI) were significantly associated with the synchronous liver metastasis factor. A final set of three genes—S100PBP, CSMD2, TGFBI—significantly predicted relapse-free survival in our cohort (p = 0.04) and another CRCLM cohort (p = 0.02). This three-gene signature is the first genomic signature validated for relapse-free survival in post-hepatectomy CRCLM patients. Our three-gene signature was developed using a whole-genome CGH array and has a good prognostic position for the relapse-free survival of CRCLM patients after hepatectomy.

BACKGROUND Although enumeration of circulating tumor cells (CTCs) has shown some clinical value, the pool of CTCs contains a mixture of cells that contains additional information that can be extracted. The authors subclassified CTCs by shape features focusing on nuclear size and related this with clinical information. METHODS A total of 148 blood samples were obtained from 57 patients with prostate cancer across the spectrum of metastatic states: no metastasis, nonvisceral metastasis, and visceral metastasis. CTCs captured and enumerated on NanoVelcro Chips (CytoLumina, Los Angeles, Calif) were subjected to pathologic review including nuclear size. The distribution of nuclear size was analyzed using a Gaussian mixture model. Correlations were made between CTC subpopulations and metastatic status. RESULTS Statistical modeling of nuclear size distribution revealed 3 distinct subpopulations: large nuclear CTCs, small nuclear CTCs, and very small nuclear CTCs (vsnCTCs). Small nuclear CTCs and vsnCTC identified those patients with metastatic disease. However, vsnCTC counts alone were found to be elevated in patients with visceral metastases when compared with those without (0.36 ± 0.69 vs 1.95 ± 3.77 cells/mL blood; P

Model averaging has long been proposed as a powerful alternative to model selection in regression analysis. However, how well it performs in high-dimensional regression is still poorly understood. Recently, Ando and Li [J. Amer. Statist. Assoc. 109 (2014) 254–265] introduced a new method of model averaging that allows the number of predictors to increase as the sample size increases. One notable feature of Ando and Li’s method is the relaxation on the total model weights so that weak signals can be efficiently combined from high-dimensional linear models. It is natural to ask if Ando and Li’s method and results can be extended to nonlinear models. Because all candidate models should be treated as working models, the existence of a theoretical target of the quasi maximum likelihood estimator under model misspecification needs to be established first. In this paper, we consider generalized linear models as our candidate models. We establish a general result to show the existence of pseudo-true regression parameters under model misspecification. We derive proper conditions for the leave-one-out cross-validation weight selection to achieve asymptotic optimality. Technically, the pseudo true target parameters between working models are not linearly linked. To overcome the encountered difficulties, we employ a novel strategy of decomposing and bounding the bias and variance terms in our proof. We conduct simulations to illustrate the merits of our model averaging procedure over several existing methods, including the lasso and group lasso methods, the Akaike and Bayesian information criterion model-averaging methods and some other state-of-the-art regularization methods.

The transcriptional repressor Slug is best known to control epithelial-mesenchymal transition (EMT) and promote cancer invasion/metastasis. In this study, we demonstrate that Slug is temporally regulated during cell cycle progression. At G1/S transition, cyclin E-cyclin-dependent kinase 2 mediates the phosphorylation of Slug at Ser-54 and Ser-104, resulting in its ubiquitylation and degradation. Non-phosphorylatable Slug is markedly stabilized at G1/S transition compared with wild-type Slug and greatly leads to downregulation of DNA synthesis and checkpoint-related proteins, including TOP1, DNA Ligase IV and Rad17, reduces cell proliferation, delays S-phase progression and contributes to genome instability. Our results indicate that Slug has multifaceted roles in cancer progression by controlling both EMT and genome stability.

This article considers high-dimensional regression problems in which the number of predictors p exceeds the sample size n. We develop a model-averaging procedure for high-dimensional regression problems. Unlike most variable selection studies featuring the identification of true predictors, our focus here is on the prediction accuracy for the true conditional mean of y given the p predictors. Our method consists of two steps. The first step is to construct a class of regression models, each with a smaller number of regressors, to avoid the degeneracy of the information matrix. The second step is to find suitable model weights for averaging. To minimize the prediction error, we estimate the model weights using a delete-one cross-validation procedure. Departing from the literature of model averaging that requires the weights always sum to one, an important improvement we introduce is to remove this constraint. We derive some theoretical results to justify our procedure. A theorem is proved, showing that del...

α-Catulin is an oncoprotein that helps sustain proliferation by preventing cellular senescence. Here, we report that α-catulin also drives malignant invasion and metastasis. α-Catulin was upregulated in highly invasive non–small cell lung cancer (NSCLC) cell lines, where its ectopic expression or short-hairpin RNA–mediated attenuation enhanced or limited invasion or metastasis, respectively. α-Catulin interacted with integrin-linked kinase (ILK), a serine/threonine protein kinase implicated in cancer cell proliferation, antiapoptosis, invasion, and angiogenesis. Attenuation of ILK or α-catulin reciprocally blocked cell migration and invasion induced by the other protein. Mechanistic investigations revealed that α-catulin activated Akt-NF-κB signaling downstream of ILK, which in turn led to increased expression of fibronectin and integrin αvβ3. Pharmacologic or antibody-mediated blockade of NF-κB or αvβ3 was sufficient to inhibit α-catulin–induced cell migration and invasion. Clinically, high levels of expression of α-catulin and ILK were associated with poor overall survival in patients with NSCLC. Taken together, our study shows that α-catulin plays a critical role in cancer metastasis by activating the ILK-mediated Akt-NF-κB-αvβ3 signaling axis. Cancer Res; 73(1); 428–38. ©2012 AACR.

INTRODUCTION AND OBJECTIVES: The relation of serum androgens and the development of prostate cancer (PCa) is subject of debate. Lower total testosterone (TT) levels have been associated with increased PCa detection and worse pathological features after treatment. The aim of this study is to investigate the association of serum androgens levels and PCa detection in a prospective screening study of men at higher genetic risk due to BRCA mutation METHODS: Six hundred and fifty seven participants in the IMPACT study had sequential TT and sexual hormone binding globulin (SHBG) measurements in serum samples at annual visits, giving 2783 prospective androgen levels, from 234 BRCA1 carriers, 268 BRCA2 carriers and 155 mutation negative controls. Free and bioavailable testosterone were calculated from TT and SHBG using the Sordergaard equation. Age, BMI, PSA and hormonal concentrations were compared between men affected and unaffected with PCa within each genetic cohort using unpaired t-test. The Fisher exact test was used to correlate hypogonadic levels of testosterone and genetic status with PCa diagnosis within each genetic category RESULTS: There were no significant differences in the PSA levels and BMI at study entry. Mean ages were 53.52, 52.17, and 51.17 years, for the control, BRCA1 and BRCA2 groups, respectively (BRCA1 p1⁄40.24 and BRCA2 p1⁄40.01). In the BRCA2 cohort, serum TT levels were lower in carriers diagnosed with PCa, compared with unaffected carriers and controls (11.2, 13.78, 13.4 nmol/L, mean values per group, respectively, p1⁄40.02 and p1⁄40.009). In the BRCA1 cohort, no significant difference was observed between affected and unaffected carriers and controls (13.6, 13.5, 13.4, nmol/L, mean values per group respectively, p1⁄40.82 and p-0.69). SHBG levels were significantly higher in BRCA1 carriers with PCa than unaffected carriers and controls (47.62, 37.97, 40.34 nmol/L, respectively; p1⁄40.002 and p1⁄40.03). TT levels

Allen Brain Atlas (ABA) provides a valuable resource of spatial/temporal gene expressions in mammalian brains. Despite rich information extracted from this database, current analyses suffer from several limitations. First, most studies are either gene-centric or region-centric, thus are inadequate to capture the superposition of multiple spatial-temporal patterns. Second, standard tools of expression analysis such as matrix factorization can capture those patterns but do not explicitly incorporate spatial dependency. To overcome those limitations, we proposed a computational method to detect recurrent patterns in the spatial-temporal gene expression data of developing mouse brains. We demonstrated that regional distinction in brain development could be revealed by localized gene expression patterns. The patterns expressed in the forebrain, medullary and pontomedullary and basal ganglia are enriched with genes involved in forebrain development, locomotory behavior and dopamine metabolism respectively. In addition, the timing of global gene expression patterns reflects the general trends of molecular events in mouse brain development. Furthermore, we validated functional implications of the inferred patterns by showing genes sharing similar spatial-temporal expression patterns with Lhx2 exhibited differential expression in the embryonic forebrains of Lhx2 mutant mice. These analysis outcomes confirm the utility of recurrent expression patterns in studying brain development.

Lung cancer is the leading cause of cancer-related deaths worldwide. High-throughput technologies such as microarrays provide an opportunity to explore biomarkers for cancer prevention, prognosis and treatment guidance. Recent studies have revealed many biomarkers with the potential for clinical application. However, major limitations still exist. Although useful data on cancer genomics has accumulated rapidly, there has also been a simultaneous tendency for amplification of the complex relationships among the enormous number of variables that need to be considered. Disentangling these complex gene–gene interactions requires new approaches to data analysis to reveal information that has been obscured by traditional methods. Here, we review the current findings on biomarker identification in lung cancer, address their limitations and discuss some future directions for improvements in this area of research.

Purpose Patients with non–small-cell lung cancer (NSCLC) with epidermal growth factor receptor (EGFR)–activating mutations have excellent response to EGFR tyrosine kinase inhibitors (TKIs), but T790M mutation accounts for most TKI drug resistance. This study used highly sensitive methods to detect T790M before and after TKI therapy and investigated the association of T790M and its mutation frequencies with clinical outcome. Patients and Methods Direct sequencing, matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS) and next-generation sequencing (NGS) were used to assess T790M in the following two cohorts of patients with NSCLC: TKI-naive patients (n = 107) and TKI-treated patients (n = 85). Results were correlated with TKI treatment response and survival. Results MALDI-TOF MS was highly sensitive in detecting and quantifying the frequency of EGFR-activating mutations and T790M (detection limits, 0.4% to 2.2%). MALDI-TOF MS identified more T790M than direct sequencing in TKI-naive patients with NSCLC (27 of 107 patients, 25.2% v three of 107 patients, 2.8%, respectively; P < .001) and in TKI-treated patients (before TKI: 23 of 73 patients, 31.5% v two of 73 patients, 2.7%, respectively; P < .001; and after TKI: 10 of 12 patients, 83.3% v four of 12 patients, 33.3%, respectively; P = .0143). The EGFR mutations and their frequencies were confirmed by NGS. T790M was an independent predictor of decreased progression-free survival (PFS) in patients with NSCLC who received TKI treatment (P < .05, multivariate Cox regression). Conclusion T790M may not be a rare event before or after TKI therapy in patients with NSCLC with EGFR-activating mutations. The pretreatment T790M mutation was associated with shorter PFS with EGFR TKI therapy in patients with NSCLC.

Purpose Although epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) have been proven more effective for patients with lung adenocarcinoma with EGFR-activating mutation rather than wild type, the former group still includes approximately 30% nonresponders. The molecular basis of this substantial response heterogeneity is unknown. Our purpose was to seek molecular aberrations contributing to disease progression at the genome-wide level and identify the prognostic signature unique to patients with EGFR-activating mutation. Patients and Methods We first investigated the molecular differences between tumors with EGFR-activating mutation and wild-type tumors by conducting high-density array comparative genomic hybridization on a collection of 138 adenocarcinoma tissues. We then used an independent group of 114 patients to validate the clinical relevance of copy-number alterations (CNAs) in predicting overall and disease-free survival. Finally, focusing on 23 patients with EGFR mutation receiving EGFR-TKI treatment, we investigated the association between CNAs and response to EGFR-TKIs. Results We identified chromosome regions with differential CNAs between tumors with EGFR-activating mutation and wild-type tumors and found the aberration sites to cluster highly on chromosome 7p. A cluster of six representative chromosome 7p genes predicted overall and disease-free survival for patients with EGFR-activating mutation but not for those with wild type. Importantly, simultaneous presence of more genes with increased CNAs in this cluster correlated with less favorable response to EGFR-TKIs in patients with EGFR-activating mutation. Conclusion Our results shed light on why responses to EGFR-TKIs are heterogeneous among patients with EGFR-activating mutation. They may lead to better patient management in this population.

The diagnosis of acute rejection is suspected by clinical presentation and confirmed by biopsy. Serum creatinine levels increase during allograft dysfunction, but this measure is neither sensitive nor specific for acute rejection (1, 2). The gold standard for diagnosing rejection is needle biopsy, which is invasive, painful, and as sociated with patient morbidity (1–4). It would be advantageous to develop a noninvasive test that could detect rejection, improve transplant outcomes, and reduce the cost of care. The use of human plasma for biomarker discovery provides a means to monitor disease states in a relatively noninvasive manner (5, 6). Plasma comes in contact with tissues which are apt to release protein components that reflect the disease-altered state of the tissue (6). The SELDI ProteinChip System (Bio-Rad, Hercules, CA) uses solid phase extraction of proteins and peptides from biological mixtures followed by detection using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry. ProteinChip arrays use a variety of chromatographic and biological surfaces to bind subsets of proteins from complex biological samples (7). The bound proteins are used to generate protein profiles used for biomarker discovery (7, 8). Urine protein profiles from renal allograft rejection patients have identified potential biomarker candidates and generated valuable insight into the biology of graft injury (9–15). The utilization of plasma for finding candidate bio-markers of renal allograft rejection holds promise as a biological fluid that can provide informative proteomic signatures of renal allograft rejection (16). This study analyzes the plasma proteomes of renal transplant patients by SELDI. Twenty-two proteins/peptides had significant differences when comparing plasma during rejection with postrejection. The combination of two candidate proteins had a high discriminatory value for detecting rejection. Two of the 22 candidates were identified and one, apolipoprotein A1 (Apo A1), was validated by enzyme-linked immunosorbent assay (ELISA) in the original and a larger independent cohort.

Motivation: Various clustering methods have been applied to microarray gene expression data for identifying genes with similar expression profiles. As the biological annotation data accumulated, more and more genes have been organized into functional categories. Functionally related genes may be regulated by common cellular signals, thus likely to be co-expressed. Consequently, utilizing the rapidly increasing functional annotation resources such as Gene Ontology (GO) to improve the performance of clustering methods is of great interest. On the opposite side of clustering, there are genes that have distinct expression profiles and do not co-express with other genes. Identification of these scattered genes could enhance the performance of clustering methods. Results: We developed a new clustering algorithm, Dynamically Weighted Clustering with Noise set (DWCN), which makes use of gene annotation information and allows for a set of scattered genes, the noise set, to be left out of the main clusters. We tested the DWCN method and contrasted its results with those obtained using several common clustering techniques on a simulated dataset as well as on two public datasets: the Stanford yeast cell-cycle gene expression data, and a gene expression dataset for a group of genetically different yeast segregants. Conclusion: Our method produces clusters with more consistent functional annotations and more coherent expression patterns than existing clustering techniques. Contact: yshen@stat.ucla.edu Supplementary information: Supplementary data are available at Bioinformatics online.

The tumour suppressor p53 is known to prevent cancer progression by inhibiting proliferation and inducing apoptosis of tumour cells. Slug, an invasion promoter, exerts its effects by repressing E-cadherin transcription. Here we show that wild-type p53 (wtp53) suppresses cancer invasion by inducing Slug degradation, whereas mutant p53 may stabilize Slug protein. In non-small-cell lung cancer (NSCLC), mutation of p53 correlates with low MDM2, high Slug and low E-cadherin expression. This expression profile is associated with poor overall survival and short metastasis-free survival in patients with NSCLC. wtp53 upregulates MDM2 and forms a wtp53-MDM2-Slug complex that facilitates MDM2-mediated Slug degradation. Downregulation of Slug by wtp53 or MDM2 enhances E-cadherin expression and represses cancer cell invasiveness. In contrast, mutant p53 inactivates Slug degradation and leads to Slug accumulation and increased cancer cell invasiveness. Our findings indicate that wtp53 and p53 mutants may differentially control cancer invasion and metastasis through the p53-MDM2-Slug pathway.

Many successful functional studies by gene expression profiling in the literature have led to the perception that profile similarity is likely to imply functional association. But how true is the converse of the above statement? Do functionally associated genes tend to be co-regulated at the transcription level? In this paper, we focus on a set of well-validated yeast protein complexes provided by Munich Information Center for Protein Sequences (MIPS). Using four well-known large-scale microarray expression data sets, we computed the correlations between genes from the same complex. We then analyzed the relationship between the distribution of correlations and the complex size (the number of genes in a protein complex). We found that except for a few large protein complexes, such as mitochondrial ribosomal and cytoplasmic ribosomal proteins, the correlations are on the average not much higher than that from a pair of randomly selected genes. The global impact of large complexes on the expression of other genes in the genome is also studied. Our result also showed that the expression of over 85% of the genes are affected by six large complexes: the cytoplasmic ribosomal complex, mitochondrial ribosomal complex, proteasome complex, F0/F1 ATP synthase (complex V) (size 18), rRNA splicing (size 24) and H+- transporting ATPase, vacular (size 15).

Previous studies have demonstrated focal but limited molecular similarities between circulating tumor cells (CTCs) and biopsies using isolated genetic assays. We hypothesized that molecular similarity between CTCs and tissue exists at the single cell level when characterized by whole genome sequencing (WGS). By combining the NanoVelcro CTC Chip with laser capture microdissection (LCM), we developed a platform for single-CTC WGS. We performed this procedure on CTCs and tissue samples from a patient with advanced prostate cancer who had serial biopsies over the course of his clinical history. We achieved 30X depth and ≥ 95% coverage. Twenty-nine percent of the somatic single nucleotide variations (SSNVs) identified were founder mutations that were also identified in CTCs. In addition, 86% of the clonal mutations identified in CTCs could be traced back to either the primary or metastatic tumors. In this patient, we identified structural variations (SVs) including an intrachromosomal rearrangement in chr3 and an interchromosomal rearrangement between chr13 and chr15. These rearrangements were shared between tumor tissues and CTCs. At the same time, highly heterogeneous short structural variants were discovered in PTEN, RB1, and BRCA2 in all tumor and CTC samples. Using high-quality WGS on single-CTCs, we identified the shared genomic alterations between CTCs and tumor tissues. This approach yielded insight into the heterogeneity of the mutational landscape of SSNVs and SVs. It may be possible to use this approach to study heterogeneity and characterize the biological evolution of a cancer during the course of its natural history.

Recently, with the development of next generation sequencing (NGS), the combination of chromatin immunoprecipitation (ChIP) and NGS, namely ChIP-seq, has become a powerful technique to capture potential genomic binding sites of regulatory factors, histone modifications and chromatin accessible regions. For most researchers, additional information including genomic variations on the TF binding site, allele frequency of variation between different populations, variation associated disease, and other neighbour TF binding sites are essential to generate a proper hypothesis or a meaningful conclusion. Many ChIP-seq datasets had been deposited on the public domain to help researchers make new discoveries. However, researches are often intimidated by the complexity of data structure and largeness of data volume. Such information would be more useful if they could be combined or downloaded with ChIP-seq data. To meet such demands, we built a webtool: ePIgenomic ANNOtation tool (ePIANNO, http://epianno.stat.sinica.edu.tw/index.html). ePIANNO is a web server that combines SNP information of populations (1000 Genomes Project) and gene-disease association information of GWAS (NHGRI) with ChIP-seq (hmChIP, ENCODE, and ROADMAP epigenomics) data. ePIANNO has a user-friendly website interface allowing researchers to explore, navigate, and extract data quickly. We use two examples to demonstrate how users could use functions of ePIANNO webserver to explore useful information about TF related genomic variants. Users could use our query functions to search target regions, transcription factors, or annotations. ePIANNO may help users to generate hypothesis or explore potential biological functions for their studies.

Although enumeration of circulating tumor cells (CTCs) has shown some clinical value, the pool of CTCs contains a mixture of cells that contains additional information that can be extracted. The authors subclassified CTCs by shape features focusing on nuclear size and related this with clinical information.A total of 148 blood samples were obtained from 57 patients with prostate cancer across the spectrum of metastatic states: no metastasis, nonvisceral metastasis, and visceral metastasis. CTCs captured and enumerated on NanoVelcro Chips (CytoLumina, Los Angeles, Calif) were subjected to pathologic review including nuclear size. The distribution of nuclear size was analyzed using a Gaussian mixture model. Correlations were made between CTC subpopulations and metastatic status.Statistical modeling of nuclear size distribution revealed 3 distinct subpopulations: large nuclear CTCs, small nuclear CTCs, and very small nuclear CTCs (vsnCTCs). Small nuclear CTCs and vsnCTC identified those patients with metastatic disease. However, vsnCTC counts alone were found to be elevated in patients with visceral metastases when compared with those without (0.36 ± 0.69 vs 1.95 ± 3.77 cells/mL blood; P.001). Serial enumeration studies suggested the emergence of vsnCTCs occurred before the detection of visceral metastases.There are morphologic subsets of CTCs that can be identified by fundamental pathologic approaches, such as nuclear size measurement. The results of this observational study strongly suggest that CTCs contain relevant information regarding disease status. In particular, the detection of vsnCTCs was found to be correlated with the presence of visceral metastases and should be formally explored as a putative blood-borne biomarker to identify patients at risk of developing this clinical evolution of prostate cancer.