Predicting survival within the lung cancer histopathological hierarchy using a multi-scale genomic model of development

Artificial intelligence-assisted selection and efficacy prediction of antineoplastic strategies for precision cancer therapy

The rapid development of artificial intelligence (AI) technologies in the context of the vast amount of collectable data obtained from high-throughput sequencing has led to an unprecedented understanding of cancer and accelerated the advent of a new era of clinical oncology with a tone of precision treatment and personalized medicine. However, the gains achieved by a variety of AI models in clinical oncology practice are far from what one would expect, and in particular, there are still many uncertainties in the selection of clinical treatment options that pose significant challenges to the application of AI in clinical oncology. In this review, we summarize emerging approaches, relevant datasets and open-source software of AI and show how to integrate them to address problems from clinical oncology and cancer research. We focus on the principles and procedures for identifying different antitumor strategies with the assistance of AI, including targeted cancer therapy, conventional cancer therapy, and cancer immunotherapy. In addition, we also highlight the current challenges and directions of AI in clinical oncology translation. Overall, we hope this article will provide researchers and clinicians with a deeper understanding of the role and implications of AI in precision cancer therapy, and help AI move more quickly into accepted cancer guidelines.

Identification of Prognostic Biomarkers for Multiple Solid Tumors Using a Human Villi Development Model

The processes of embryonic development that rely on epithelial-mesenchymal transition (EMT) for the implantation of trophoblast cells are co-opted by tumors, reflecting their inherent uncontrolled characteristics and leading to invasion and metastasis. Although tumorigenesis and embryogenesis have similar EMT characteristics, trophoblasts have been shown to exhibit "physiological metastasis" or be "pseudo-malignant," resulting in different outcomes. The gene co-expression network is the basis of embryonic development and tumorigenesis. We hypothesize that if the gene co-expression network in tumors is "off-track" from that in villi, it is more likely to develop into malignant tumors and have a worse prognosis, and we proposed the "off-track theory" for the first time. In this study, we examined gene co-expression networks in villi and multiple solid tumors. Through network functional enrichment analyses, we found that most tumors and villi exhibited a significantly enriched EMT, but the genes that performed this function were not identical. Then, we identified the "off-track genes" in the EMT-related gene interaction network using the "off-track theory," and through survival analysis, we discovered that the risk score of "off-track genes" was associated with poor survival of cancer patients. Our study indicated that villi development is a reliable and strictly regulated model that can illuminate the trajectory of human cancer development and that the gene co-expression networks in tumor development are "off-track" from those in villi. These "off-track genes" may have a substantial impact on tumor development and could reveal novel prognostic biomarkers.

Dissecting expression profiles of gastric precancerous lesions and early gastric cancer to explore crucial molecules in intestinal-type gastric cancer tumorigenesis

Intestinal‐type gastric cancer (IGC) has a clear and multistep histological evolution. No studies have comprehensively explored gastric tumorigenesis from inflammation through low‐grade intraepithelial neoplasia (LGIN) and high‐grade intraepithelial neoplasia (HGIN) to early gastric cancer (EGC). We sought to investigate the characteristics participating in IGC tumorigenesis and identify related prognostic information within the process. RNA expression profiles of 94 gastroscopic biopsies from 47 patients, including gastric precancerous lesions (GPL: LGIN and HGIN), EGC, and paired controls, were detected by Agilent Microarray. During IGC tumorigenesis from LGIN through HGIN to EGC, the number of activity‐changed tumor hallmarks increased. LGIN and HGIN had similar expression profiles when compared to EGC. We observed an increase in the stemness of gastric epithelial cells in LGIN, HGIN, and EGC, and we found 27 consistent genes that might contribute to dedifferentiation, including five driver genes. Remarkably, we perceived that the immune microenvironment was more active in EGC than in GPL, especially in the infiltration of lymphocytes and macrophages. We identified a five‐gene signature from the gastric tumorigenesis process that could independently predict the overall survival and disease‐free survival of GC patients (log‐rank test: p < 0.0001), and the robustness was verified in an independent cohort (n > 300) and by comparing with two established prognostic signatures in GC. In conclusion, during IGC tumorigenesis, cancer‐like changes occur in LGIN and accumulate in HGIN and EGC. The immune microenvironment is more active in EGC than in LGIN and HGIN. The identified signature from the tumorigenesis process has robust prognostic significance for GC patients. © 2020 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Genome-wide screening identifies oncofetal lncRNA Ptn-dt promoting the proliferation of hepatocellular carcinoma cells by regulating the Ptn receptor

Oncofetal genes are genes that express abundantly in both fetal and tumor tissues yet downregulated or undetected in adult tissues, and can be used as tumor markers for cancer diagnosis and treatment. Meanwhile, long noncoding RNAs (lncRNAs) are known to play crucial roles in the pathogenesis of hepatocellular carcinoma (HCC), including tumor growth, proliferation, metastasis, invasion, and recurrence. We performed a genome-wide screening using microarrays to detect the lncRNA expression profiles in fetal livers, adult livers, and liver cancer tissues from mice to identify oncofetal lncRNAs in HCC. From the microarray data analysis, we identified lncRNA Ptn-dt as a possible oncofetal gene. Both in vitro and in vivo experiments results confirmed that overexpression of Ptn-dt significantly promoted the proliferation of mouse HCC cells. RNA pulldown assay showed that Ptn-dt could interact with the HuR protein. Interestingly, miR-96 binds with HuR to maintain its stability as well. Overexpression of lncRNA Ptn-dt led to the downregulation of miR-96, which might be due to the interaction between Ptn-dt and HuR. Meanwhile, previous studies have reported that Ptn can promote tumor growth and vascular abnormalization via anaplastic lymphoma kinase (Alk) signaling. In our study, we found that overexpression of Ptn-dt could promote the expression of Alk through repressing miR-96 via interacting with HuR, thus enhancing the biologic function of Ptn. In summary, a new oncofetal lncRNA Ptn-dt is identified, and it can promote the proliferation of HCC cells by regulating the HuR/miR-96/Alk pathway and Ptn-Alk axis.

A multi-gene expression profile panel for predicting liver metastasis: An algorithmic approach

Background & aim

Liver metastasis has been found to affect outcome in prostate, pancreatic and colorectal cancers, but its role in lung cancer is unclear. The 5 year survival rate remains extensively low owing to intrinsic resistance to conventional therapy which can be attributed to the genetic modulators involved in the pathogenesis of the disease. Thus, this study aims to generate a model for early diagnosis and timely treatment of liver metastasis in lung cancer patients.

Methods

mRNA expression of 15 genes was quantified by real time PCR on lung cancer specimens with (n = 32) and without (n = 30) liver metastasis and their normal counterparts. Principal Component analysis, linear discriminant analysis and hierarchical clustering were conducted to obtain a predictive model. The accuracy of the models was tested by performing Receiver Operating Curve analysis.

Results

The expression profile of all the 15 genes were subjected to PCA and LDA analysis and 5 models were generated. ROC curve analysis was performed for all the models and the individual genes. It was observed that out of the 15 genes only 8 genes showed significant sensitivity and specificity. Another model consisting of the selected eight genes was generated showing a specificity and sensitivity of 90.0 and 96.87 respectively (p <0.0001). Moreover, hierarchical clustering showed that tumors with a greater fold change lead to poor prognosis.

Conclusion

Our study led to the generation of a concise, biologically relevant multi-gene panel that significantly and non-invasively predicts liver metastasis in lung cancer patients.

Identification of prognostic genes in colorectal cancer through transcription profiling of multi-stage carcinogenesis

Colorectal cancer is a complex multistage process following the adenoma-carcinoma sequence. Additional research on the basis of molecular dysregulations, particularly in the precancerous stage, may provide insight into the realization of potential biomarkers and therapeutic targets for the disease. In the present study, the expression profile of human multistage colorectal mucosa tissues, including healthy, adenoma and adenocarcinoma samples, was downloaded. Genes that were consistently differentially expressed in precancerous tissues and cancer samples were collected. Based on a merged biological network, the biggest connected component composed of these identified genes and their one-step neighbors were retrieved to conduct random walk with restart algorithm, in order to identify genes significantly affected during carcinogenesis. Therefore, 35 genes significantly affected by carcinogenic dysregulation were successfully identified. Survival and Cox analysis indicated that the expression of these genes was an independent prognostic factor confirmed by six cohorts. In summary, based on the transcription profile of multi-stage carcinogenesis and bioinformatics analysis, 35 genes significantly associated with patient survival were successfully identified, which may serve as promising therapeutic targets for the disease.

GATA6-positive lung adenocarcinomas are associated with invasive mucinous adenocarcinoma morphology, hepatocyte nuclear factor 4α expression, and KRAS mutations

AIMS

GATA6 is known to play a role in lung development. However, its role in the carcinogenesis of lung cancer is not well studied. The aim of this study was to analyse GATA6 expression in lung adenocarcinomas (LAs) by immunohistochemistry (IHC) in order to define its association with clinicopathological characteristics.

METHODS AND RESULTS

IHC analysis of GATA6 was performed with tissue microarray slides containing 348 LAs. The association between GATA6 expression and clinicopathological parameters was evaluated. GATA6 expression in epithelial tumours other than lung cancer was also evaluated. GATA6 expression was found in 47 LAs (13.5%). This occurred more frequently in younger patients (P = 0.005), and was associated with the absence of lymph node metastasis (P =0.024), well-differentiated to moderately differentiated tumours (P < 0.001), the absence of lymphatic invasion (P = 0.020), and the absence of vascular invasion (P = 0.011). GATA6 expression was associated with mucin production (P < 0.001), the invasive mucinous adenocarcinoma subtype (P < 0.001), KRAS mutations (P = 0.026), expression of MUC2 (P < 0.001), CDX2 (P = 0.049), and MUC5AC (P < 0.001), and absence of expression of TTF-1 (P = 0.002). GATA6 expression was also associated with hepatocyte nuclear factor 4α (HNF4α) expression (P < 0.001). GATA6 expression tended to indicate better prognoses, whereas patients with HNF4α expression had significantly worse prognoses (P = 0.033). Of 270 tumours other than lung cancer, 110 expressed GATA6.

CONCLUSIONS

These findings suggest that GATA6 might interact with HNF4α and contribute to the development of mucinous-type LAs.

Proliferation genes in lung development associated with the prognosis of lung adenocarcinoma but not squamous cell carcinoma

There are many similarities between embryonic development and tumorigenesis, and gene expression profiles show that certain correlations exist between the gene signature during development and the clinical phenotypes of different cancers. Our group previously reported the gene expression profiles of human lung development, and the expression of one group of proliferation-related genes (PTN1 genes) steadily decreased during lung development. Here, we examined the prognostic value of PTN1 genes in 5 independent lung adenocarcinoma (ADC) and 5 lung independent squamous cell carcinoma (SCC) microarray datasets and found that the expression levels of PTN1 genes were associated with survival in lung ADC but not lung SCC. All of the lung ADC datasets contained a set of highly correlated genes from PTN1 genes, but the lung SCC datasets had no similar set of genes. We identified 63 unique core genes from the PTN1 genes in the 5 lung ADC datasets: 17 of these core genes appeared in at least 4 of the lung ADC datasets, and the 17 corresponding proteins clearly interacted more strongly with each other in lung ADC than in lung SCC. Moreover, 16 of the 17 core genes play major roles in the G₂ /M phase of the cell cycle. These data indicate that proliferation-related genes in lung development have a significant prognostic value for lung ADC; the synergistic effects of the 17 core genes play an important role in lung ADC prognosis. These genes may have significant clinical implications for the treatment and prognosis of lung ADC.

Association of Omics Features with Histopathology Patterns in Lung Adenocarcinoma

Adenocarcinoma accounts for more than 40% of lung malignancy, and microscopic pathology evaluation is indispensable for its diagnosis. However, how histopathology findings relate to molecular abnormalities remains largely unknown. Here, we obtained H&E-stained whole-slide histopathology images, pathology reports, RNA sequencing, and proteomics data of 538 lung adenocarcinoma patients from The Cancer Genome Atlas and used these to identify molecular pathways associated with histopathology patterns. We report cell-cycle regulation and nucleotide binding pathways underpinning tumor cell dedifferentiation, and we predicted histology grade using transcriptomics and proteomics signatures (area under curve >0.80). We built an integrative histopathology-transcriptomics model to generate better prognostic predictions for stage I patients (p = 0.0182 ± 0.0021) compared with gene expression or histopathology studies alone, and the results were replicated in an independent cohort (p = 0.0220 ± 0.0070). These results motivate the integration of histopathology and omics data to investigate molecular mechanisms of pathology findings and enhance clinical prognostic prediction.

Non-invasive lung cancer diagnosis by detection of GATA6 and NKX2-1 isoforms in exhaled breath condensate

Lung cancer (LC) is the leading cause of cancer‐related deaths worldwide. Early LC diagnosis is crucial to reduce the high case fatality rate of this disease. In this case–control study, we developed an accurate LC diagnosis test using retrospectively collected formalin‐fixed paraffin‐embedded (FFPE) human lung tissues and prospectively collected exhaled breath condensates (EBCs). Following international guidelines for diagnostic methods with clinical application, reproducible standard operating procedures (SOP) were established for every step comprising our LC diagnosis method. We analyzed the expression of distinct mRNAs expressed from GATA6 and NKX2‐1, key regulators of lung development. The Em/Ad expression ratios of GATA6 and NKX2‐1 detected in EBCs were combined using linear kernel support vector machines (SVM) into the LC score, which can be used for LC detection. LC score‐based diagnosis achieved a high performance in an independent validation cohort. We propose our method as a non‐invasive, accurate, and low‐price option to complement the success of computed tomography imaging (CT) and chest X‐ray (CXR) for LC diagnosis.

Cell cycle related genes up-regulated in human colorectal development predict the overall survival of late-stage colorectal cancer patients

A tumor can be perceived as a special "organ" that undergoes aberrant and poorly regulated organogenesis. Embryonic development and carcinogenesis share striking similarities in their cellular behavior and underlying molecular mechanisms. This intimate association makes embryonic development a viable reference model for studying cancer thereby circumventing the potentially misleading complexity of tumor heterogeneity. Therefore, on the basis of global expression profile, the genes simultaneously activated (up-regulated in terms of expression profile) or suppressed (down-regulated) in both the embryonic development and cancer stage, probably contain profound information on the molecular mechanism of cancer. In this study, the Affymetrix expression profile of 1593 colorectal cancer samples was downloaded from Gene Expression Omnibus. The 1396 differentially expressed probes were robustly obtained using 660 colorectal normal and cancer samples, the expression pattern of which was analyzed using our human colorectal developmental data. All of these 1396 probes were classified into 27 distinct patterns based on their expression patterns during the developmental process. By means of gene set enrichment analysis, we collected 393 V probes simultaneously up-regulated in both development and carcinogenesis and 207 A probes down-regulated in both. Functional enrichment analysis indicated that the V probes were significantly related to cell cycle regulation. Notably, 28 cell-cycle related probes within the V probe group were found to be significantly associated with an overall survival of Stage III/IV patients (GSE17536 cross validation, n = 96, p = 5.70 × 10(-3); GSE29621, n = 36, p = 1.70 × 10(-3); GSE39084, n = 38, p = 0.05; GSE39582, n = 264, p = 0.047; GSE17537, n = 36, p = 5.90 × 10(-3)).

SMC4, which is essentially involved in lung development, is associated with lung adenocarcinoma progression

Structural maintenance of chromosome 4 (SMC4) is a core subunit of condensin complexes that mainly contributes to chromosome condensation and segregation. Our previous study demonstrated that the gene expression profile during lung development is of great values for the study of lung cancer. In this study, we identified SMC4 through co-expression network analysis and clique percolation clustering using genes that constant changes during four stages of lung development. Gene ontology and KEGG pathway enrichment analysis demonstrated that SMC4 is closely related to cell cycle, cell adhesion, and RNA processing in lung development and carcinogenesis. Moreover, SMC4 is overexpressed in lung adenocarcinoma tissues and acts as an independent prognostic factor. SMC4 knockdown significantly inhibits the proliferation and invasion of A549 cells. Furthermore, we found that SMC4 interacts with DDX46 (DEAD-box helicase 46). In conclusion, the pivotal role of SMC4 in lung development and carcinogenesis suggests that genes with a similar expression pattern to SMC4 in lung development may also contribute to lung cancer progression. The identification of genes that are essentially involved in development through a comparative study between development and cancer may be a practical strategy for discovering potential biomarkers and illuminating the mechanisms of carcinogenesis.

A phase I trial of the Hedgehog inhibitor, sonidegib (LDE225), in combination with etoposide and cisplatin for the initial treatment of extensive stage small cell lung cancer

OBJECTIVES

The Hedgehog pathway has been implicated in small cell lung cancer (SCLC) tumor initiation and progression. Pharmacologic blockade of the key Hedgehog regulator, Smoothened, may inhibit these processes. We performed a phase I study to determine the maximum tolerated dose (MTD) of sonidegib (LDE225), a selective, oral Smoothened antagonist, in combination with etoposide/cisplatin in newly diagnosed patients with extensive stage SCLC.

MATERIALS AND METHODS

Patients received 4-6 21-day cycles of etoposide/cisplatin with daily sonidegib. Patients with response or stable disease were continued on sonidegib until disease progression or unacceptable toxicity. Two dose levels of sonidegib were planned: 400mg and 800mg daily, with 200mg daily de-escalation if necessary. Next generation sequencing was performed on available specimens. Circulating tumor cells (CTCs) were quantified at baseline and with disease evaluation.

RESULTS

Fifteen patients were enrolled. 800mg was established as the recommended phase II dose of sonidegib in combination with etoposide/cisplatin. Grade 3 or greater toxicities included: anemia (n=5), neutropenia (n=8), CPK elevation (n=2), fatigue (n=2), and nausea (n=2). Toxicity led to removal of one patient from study. Partial responses were confirmed in 79% (11/14; 95% CI: 49-95%). One patient with SOX2 amplification remains progression-free on maintenance sonidegib after 27 months. CTC count, at baseline, was associated with the presence of liver metastases and after 1 cycle of therapy, with overall survival.

CONCLUSIONS

Sonidegib 800mg daily was the MTD when administered with EP. Further genomic characterization of exceptional responders may reveal clinically relevant predictive biomarkers that could tailor use in patients most likely to benefit.

A network-based method for identifying prognostic gene modules in lung squamous carcinoma

Similarities in gene expression between both developing embryonic and precancerous tissues and cancer tissues may help identify much-needed biomarkers and therapeutic targets in lung squamous carcinoma. In this study, human lung samples representing ten successive time points, from embryonic development to carcinogenesis, were used to construct global gene expression profiles. Differentially expressed genes with similar expression in precancerous and cancer samples were identified. Using a network-based greedy searching algorithm to analyze the training cohort (n = 69) and three independent testing cohorts, we successfully identified a significant 22-gene module in which expression levels were correlated with overall survival in lung squamous carcinoma patients.

Small cell lung cancer: will recent progress lead to improved outcomes?

Small cell lung cancer (SCLC) is an aggressive neuroendocrine malignancy with a unique natural history characterized by a short doubling time, high growth fraction, and early development of widespread metastases. Although a chemotherapy- and radiation-sensitive disease, SCLC typically recurs rapidly after primary treatment, with only 6% of patients surviving 5 years from diagnosis. This disease has been notable for the absence of major improvements in its treatment: Nearly four decades after the introduction of a platinum-etoposide doublet, therapeutic options have remained virtually unchanged, with correspondingly little improvement in survival rates. Here, we summarize specific barriers and challenges inherent to SCLC research and care that have limited progress in novel therapeutic development to date. We discuss recent progress in basic and translational research, especially in the development of mouse models, which will provide insights into the patterns of metastasis and resistance in SCLC. Opportunities in clinical research aimed at exploiting SCLC biology are reviewed, with an emphasis on ongoing trials. SCLC has been described as a recalcitrant cancer, for which there is an urgent need for accelerated progress. The NCI convened a panel of laboratory and clinical investigators interested in SCLC with a goal of defining consensus recommendations to accelerate progress in the treatment of SCLC, which we summarize here.

Integrative analysis of lung development-cancer expression associations reveals the roles of signatures with inverse expression patterns

Recent studies have focused on exploring the associations between organ development and malignant tumors; however, the clinical relevance of the development signatures was inadequately addressed in lung cancer. In this study, we explored the associations between lung development and lung cancer progression by analyzing a total of two development and seven cancer datasets. We identified representative expression patterns (continuously up- and down-regulated) from development and cancer profiles, and inverse pattern associations were observed at both the gene and functional levels. Furthermore, we dissected the biological processes dominating the associations, and found that proliferation and immunity were respectively involved in the two inverse development-cancer expression patterns. Through sub-pathway analysis of the signatures with inverse expression patterns, we finally identified a 13-gene risk signature from the cell cycle sub-pathway, and evaluated its predictive performance for lung cancer patient clinical outcome using independent cohorts. Our findings indicated that the integrative analysis of development and cancer expression patterns provided a framework for identifying effective molecular signatures for clinical utility.

Developmental genes significantly afflicted by aberrant promoter methylation and somatic mutation predict overall survival of late-stage colorectal cancer

Carcinogenesis is an exceedingly complicated process, which involves multi-level dysregulations, including genomics (majorly caused by somatic mutation and copy number variation), DNA methylomics, and transcriptomics. Therefore, only looking into one molecular level of cancer is not sufficient to uncover the intricate underlying mechanisms. With the abundant resources of public available data in the Cancer Genome Atlas (TCGA) database, an integrative strategy was conducted to systematically analyze the aberrant patterns of colorectal cancer on the basis of DNA copy number, promoter methylation, somatic mutation and gene expression. In this study, paired samples in each genomic level were retrieved to identify differentially expressed genes with corresponding genetic or epigenetic dysregulations. Notably, the result of gene ontology enrichment analysis indicated that the differentially expressed genes with corresponding aberrant promoter methylation or somatic mutation were both functionally concentrated upon developmental process, suggesting the intimate association between development and carcinogenesis. Thus, by means of random walk with restart, 37 significant development-related genes were retrieved from a priori-knowledge based biological network. In five independent microarray datasets, Kaplan-Meier survival and Cox regression analyses both confirmed that the expression of these genes was significantly associated with overall survival of Stage III/IV colorectal cancer patients.

Foxa2 and Cdx2 cooperate with Nkx2-1 to inhibit lung adenocarcinoma metastasis

Li et al. demonstrate that loss of Foxa2 and Cdx2 synergizes with loss of Nkx2-1 to fully activate the metastatic program in lung cancer. Silencing of these three transcription factors is sufficient to account for a significant fraction of the gene expression differences between the nonmetastatic and metastatic states in lung adenocarcinoma.

Despite the fact that the majority of lung cancer deaths are due to metastasis, the molecular mechanisms driving metastatic progression are poorly understood. Here, we present evidence that loss of Foxa2 and Cdx2 synergizes with loss of Nkx2-1 to fully activate the metastatic program. These three lineage-specific transcription factors are consistently down-regulated in metastatic cells compared with nonmetastatic cells. Knockdown of these three factors acts synergistically and is sufficient to promote the metastatic potential of nonmetastatic cells to that of naturally arising metastatic cells in vivo. Furthermore, silencing of these three transcription factors is sufficient to account for a significant fraction of the gene expression differences between the nonmetastatic and metastatic states in lung adenocarcinoma, including up-regulated expression of the invadopodia component Tks5_long, the embryonal proto-oncogene Hmga2, and the epithelial-to-mesenchymal mediator Snail. Finally, analyses of tumors from a genetically engineered mouse model and patients show that low expression of Nkx2-1, Foxa2, and Cdx2 strongly correlates with more advanced tumors and worse survival. Our findings reveal that a large part of the complex transcriptional network in metastasis can be controlled by a small number of regulatory nodes that function redundantly, and loss of multiple nodes is required to fully activate the metastatic program.

Discovery of a Novel Immune Gene Signature with Profound Prognostic Value in Colorectal Cancer: A Model of Cooperativity Disorientation Created in the Process from Development to Cancer

Immune response-related genes play a major role in colorectal carcinogenesis by mediating inflammation or immune-surveillance evasion. Although remarkable progress has been made to investigate the underlying mechanism, the understanding of the complicated carcinogenesis process was enormously hindered by large-scale tumor heterogeneity. Development and carcinogenesis share striking similarities in their cellular behavior and underlying molecular mechanisms. The association between embryonic development and carcinogenesis makes embryonic development a viable reference model for studying cancer thereby circumventing the potentially misleading complexity of tumor heterogeneity. Here we proposed that the immune genes, responsible for intra-immune cooperativity disorientation (defined in this study as disruption of developmental expression correlation patterns during carcinogenesis), probably contain untapped prognostic resource of colorectal cancer. In this study, we determined the mRNA expression profile of 137 human biopsy samples, including samples from different stages of human colonic development, colorectal precancerous progression and colorectal cancer samples, among which 60 were also used to generate miRNA expression profile. We originally established Spearman correlation transition model to quantify the cooperativity disorientation associated with the transition from normal to precancerous to cancer tissue, in conjunction with miRNA-mRNA regulatory network and machine learning algorithm to identify genes with prognostic value. Finally, a 12-gene signature was extracted, whose prognostic value was evaluated using Kaplan–Meier survival analysis in five independent datasets. Using the log-rank test, the 12-gene signature was closely related to overall survival in four datasets (GSE17536, n = 177, p = 0.0054; GSE17537, n = 55, p = 0.0039; GSE39582, n = 562, p = 0.13; GSE39084, n = 70, p = 0.11), and significantly associated with disease-free survival in four datasets (GSE17536, n = 177, p = 0.0018; GSE17537, n = 55, p = 0.016; GSE39582, n = 557, p = 4.4e-05; GSE14333, n = 226, p = 0.032). Cox regression analysis confirmed that the 12-gene signature was an independent factor in predicting colorectal cancer patient’s overall survival (hazard ratio: 1.759; 95% confidence interval: 1.126–2.746; p = 0.013], as well as disease-free survival (hazard ratio: 2.116; 95% confidence interval: 1.324–3.380; p = 0.002).

The effects and mechanisms of SLC34A2 in tumorigenesis and progression of human non-small cell lung cancer

BACKGROUND

SLC34A2 with highest expressions in lung, small intestine and kidney encoded a type 2b sodium-dependent phosphate transporter (NaPi-IIb). In lung, SLC34A2 only expressed in the apical membrane of type II alveolar epithelium cells (ATII cells) and played a pivotal role during the fetal lung development and embryonic development. ATII cells acting as multifunctional stem cells might transform into NSCLC after undergoing exogenous or endogenous factors. Increasing evidences showed that the genes performing critical roles during embryogenesis were also expressed during the development of cancer. In addition, recent research found the expression of SLC34A2 had a significant difference between the surgical samples of NSCLC and normal tissues, and SLC34A2 was down-regulated in lung adenocarcinoma cell line A549 and up-regulation expression of SLC34A2 could significantly inhibit cell viability and invasion of A549 in vitro. These results suggested SLC34A2 might play an important role in the development of NSCLC. However, the role of SLC34A2 in tumorigenesis and progression of NSCLC remains unknown.

RESULTS

Our study found that SLC34A2 was also significantly down-regulated in 14/15 of examined NSCLC tissues. Moreover, we found that expressions of SLC34A2 were reduced in six NSCLC cell lines for the first time. Our result also revealed a dramatic inhibitory effects of SLC34A2 on cell growth, migration and invasion of several NSCLC cell lines. SLC34A2 also strongly inhibited tumor growth and metastasis ability in A549 subcutaneous tumor model and lung metastasis model, respectively. Further studies found that the suppressive effects of SLC34A2 on tumorigenesis and progression might be associated with the down-regulation of related protein in PI3K/Akt and Ras/Raf/MEK signal pathway.

CONCLUSIONS

For the first time, our data indicated that SLC34A2 could exert significantly suppressive effects on tumorigenesis and progression of NSCLC. SLC34A2 might provide new insights for further understanding the early pathogenesis of human NSCLC.

Discovery of prognostic biomarkers for predicting lung cancer metastasis using microarray and survival data

BACKGROUND

Few studies have investigated prognostic biomarkers of distant metastases of lung cancer. One of the central difficulties in identifying biomarkers from microarray data is the availability of only a small number of samples, which results overtraining. Recently obtained evidence reveals that epithelial-mesenchymal transition (EMT) of tumor cells causes metastasis, which is detrimental to patients' survival.

RESULTS

This work proposes a novel optimization approach to discovering EMT-related prognostic biomarkers to predict the distant metastasis of lung cancer using both microarray and survival data. This weighted objective function maximizes both the accuracy of prediction of distant metastasis and the area between the disease-free survival curves of the non-distant and distant metastases. Seventy-eight patients with lung cancer and a follow-up time of 120 months are used to identify a set of gene markers and an independent cohort of 26 patients is used to evaluate the identified biomarkers. The medical records of the 78 patients show a significant difference between the disease-free survival times of the 37 non-distant- and the 41 distant-metastasis patients. The experimental results thus obtained are as follows. 1) The use of disease-free survival curves can compensate for the shortcoming of insufficient samples and greatly increase the test accuracy by 11.10%; and 2) the support vector machine with a set of 17 transcripts, such as CCL16 and CDKN2AIP, can yield a leave-one-out cross-validation accuracy of 93.59%, a test accuracy of 76.92%, a large disease-free survival area of 74.81%, and a mean survival prediction error of 3.99 months. The identified putative biomarkers are examined using related studies and signaling pathways to reveal the potential effectiveness of the biomarkers in prospective confirmatory studies.

CONCLUSIONS

The proposed new optimization approach to identifying prognostic biomarkers by combining multiple sources of data (microarray and survival) can facilitate the accurate selection of biomarkers that are most relevant to the disease while solving the problem of insufficient samples.

Gene expression profiling in human lung development: an abundant resource for lung adenocarcinoma prognosis

A tumor can be viewed as a special “organ” that undergoes aberrant and poorly regulated organogenesis. Progress in cancer prognosis and therapy might be facilitated by re-examining distinctive processes that operate during normal development, to elucidate the intrinsic features of cancer that are significantly obscured by its heterogeneity. The global gene expression signatures of 44 human lung tissues at four development stages from Asian descent and 69 lung adenocarcinoma (ADC) tissue samples from ethnic Chinese patients were profiled using microarrays. All of the genes were classified into 27 distinct groups based on their expression patterns (named as PTN1 to PTN27) during the developmental process. In lung ADC, genes whose expression levels decreased steadily during lung development (genes in PTN1) generally had their expression reactivated, while those with uniformly increasing expression levels (genes in PTN27) had their expression suppressed. The genes in PTN1 contain many n-gene signatures that are of prognostic value for lung ADC. The prognostic relevance of a 12-gene demonstrator for patient survival was characterized in five cohorts of healthy and ADC patients [ADC_CICAMS (n = 69, p = 0.007), ADC_PNAS (n = 125, p = 0.0063), ADC_GSE13213 (n = 117, p = 0.0027), ADC_GSE8894 (n = 62, p = 0.01), and ADC_NCI (n = 282, p = 0.045)] and in four groups of stage I patients [ADC_CICAMS (n = 22, p = 0.017), ADC_PNAS (n = 76, p = 0.018), ADC_GSE13213 (n = 79, p = 0.02), and ADC_qPCR (n = 62, p = 0.006)]. In conclusion, by comparison of gene expression profiles during human lung developmental process and lung ADC progression, we revealed that the genes with a uniformly decreasing expression pattern during lung development are of enormous prognostic value for lung ADC.

Elevated expression of SLC34A2 inhibits the viability and invasion of A549 cells

Abnormal expression of solute carrier family 34 (sodium phosphate), member 2 (SLC34A2) in the lung may induce abnormal alveolar type II (AT II) cells to transform into lung adenocarcinoma cells, and may also be important in biological process of lung adenocarcinoma. However, at present, the effects and molecular mechanisms of SLC34A2 in the initiation and progression of lung cancer remain to be elucidated. To the best of our knowledge, the present study revealed for the first time that the expression levels of SLC34A2 were downregulated in the A549 and H1299 lung adenocarcinoma cell lines. Further investigation demonstrated that the elevated expression of SLC34A2 in A549 cells was able to significantly inhibit cell viability and invasion in vitro. In addition, 10 upregulated genes between the A549-P-S cell line stably expressing SLC34A2 and the control cell line A549-P were identified by microarray analysis and quantitative polymerase chain reaction, including seven tumor suppressor genes and three complement genes. Furthermore, the upregulation of complement gene C3 and complement 4B preproprotein (C4b) in A549-P-S cells was confirmed by ELISA analysis and was identified to be correlated with recovering Pi absorption in A549 cells by the phosphomolybdic acid method by enhancing the expression of SLC34A2. Therefore, it was hypothesized that the mechanisms underlying the effect of SLC34A2 on A549 cells might be associated with the activation of the complement alternative pathway (C3 and C4b) and upregulation of the expression of selenium binding protein 1, thioredoxin-interacting protein, PDZK1-interacting protein 1 and dual specificity protein phosphatase 6. Downregulation of SLC34A2 may primarily cause abnormal AT II cells to escape from complement-associated immunosurveillance and abnormally express certain tumor-suppressor genes inducing AT II cells to develop into lung adenocarcinoma. The present study further elucidated the effects and mechanisms of SLC34A2 in the generation and development of lung cancer.

C-C chemokine receptor 5 on pulmonary mesenchymal cells promotes experimental metastasis via the induction of erythroid differentiation regulator 1

C-C Chemokine receptor 5 knockout (Ccr5(-/-)) mice develop fewer experimental pulmonary metastases than wild-type (WT) mice. This phenomenon was explored by applying gene expression profiling to the lungs of mice with these metastases. Consequently, erythroid differentiation regulator 1 (Erdr1) was identified as upregulated in the WT mice. Though commonly associated with bone marrow stroma, Erdr1 was differentially expressed in WT pulmonary mesenchymal cells (PMC) and murine embryonic fibroblasts (MEF). Moreover, the Ccr5 ligand Ccl4 increased its expression by 3.36 ± 0.14-fold. Ccr5 signaling was dependent on the mitogen-activated protein kinase kinase (Map2k) but not the phosphoinositide 3-kinase (Pi3k) pathway because treatment with U0126 inhibited upregulation of Erdr1, but treatment with LY294002 increased the expression by 3.44 ± 0.92-fold (P < 0.05). The effect Erdr1 on B16-F10 melanoma metastasis was verified by the adoptive transfer of WT MEFs into Ccr5(-/-) mice. In this model, MEFs that had been transduced with Erdr1 short hairpin RNA (shRNA) lowered metastasis by 33% compared with control transduced MEFs. The relevance of ERDR1 on human disease was assessed by coculturing chronic lymphocytic leukemia (CLL) cells with M2-10B4 stromal cells that had been transfected with shRNA or control plasmids. After 96 hours of coculture, the cell counts were higher with control cell lines than with Erdr1 knockdown lines [odds ratio (OR), 1.88 ± 0.27, 2.52 ± 0.66, respectively]. This increase was associated with a decrease in apoptotic cells (OR, 0.69 ± 0.18, 0.58 ± 0.12, respectively).

IMPLICATIONS

Therefore, ERDR1 is a stromal-derived factor that promotes cancer cell survival in vitro and in an experimental metastasis model.

Prediction of lung tumor types based on protein attributes by machine learning algorithms

Early diagnosis of lung cancers and distinction between the tumor types (Small Cell Lung Cancer (SCLC) and Non-Small Cell Lung Cancer (NSCLC) are very important to increase the survival rate of patients. Herein, we propose a diagnostic system based on sequence-derived structural and physicochemical attributes of proteins that involved in both types of tumors via feature extraction, feature selection and prediction models. 1497 proteins attributes computed and important features selected by 12 attribute weighting models and finally machine learning models consist of seven SVM models, three ANN models and two NB models applied on original database and newly created ones from attribute weighting models; models accuracies calculated through 10-fold cross and wrapper validation (just for SVM algorithms). In line with our previous findings, dipeptide composition, autocorrelation and distribution descriptor were the most important protein features selected by bioinformatics tools. The algorithms performances in lung cancer tumor type prediction increased when they applied on datasets created by attribute weighting models rather than original dataset. Wrapper-Validation performed better than X-Validation; the best cancer type prediction resulted from SVM and SVM Linear models (82%). The best accuracy of ANN gained when Neural Net model applied on SVM dataset (88%). This is the first report suggesting that the combination of protein features and attribute weighting models with machine learning algorithms can be effectively used to predict the type of lung cancer tumors (SCLC and NSCLC).

Molecular biology of lung cancer: Diagnosis and management of lung cancer, 3rd ed: American College of Chest Physicians evidence-based clinical practice guidelines

Based on recent bench and clinical research, the treatment of lung cancer has been refined, with treatments allocated according to histology and specific molecular features. For example, targeting mutations such as epidermal growth factor receptor (EGFR) with tyrosine kinase inhibitors has been particularly successful as a treatment modality, demonstrating response rates in selected patients with adenocarcinoma tumors harboring EGFR mutations that are significantly higher than those for conventional chemotherapy. However, the development of new targeted therapies is, in part, highly dependent on an improved understanding of the molecular underpinnings of tumor initiation and progression, knowledge of the role of molecular aberrations in disease progression, and the development of highly reproducible platforms for high-throughput biomarker discovery and testing. In this article, we review clinically relevant research directed toward understanding the biology of lung cancer. The clinical purposes of this research are (1) to identify susceptibility variants and field molecular alterations that will promote the early detection of tumors and (2) to identify tumor molecular alterations that serve as therapeutic targets, prognostic biomarkers, or predictors of tumor response. We focus on research developments in the understanding of lung cancer somatic DNA mutations, chromosomal aberrations, epigenetics, and the tumor microenvironment, and how they can advance diagnostics and therapeutics.

Genes involved in the transition from normal epithelium to intraepithelial neoplasia are associated with colorectal cancer patient survival

Whether the heterogeneity in tumor cell morphology and behavior is the consequence of a progressive accumulation of genetic alterations or an intrinsic property of cancer-initiating cells established at initiation remains controversial. The hypothesis of biological predetermination in human cancer was proposed many years ago and states that the biological potency of cancer cells is predestinated in the precancerous stage. The present study aimed to investigate whether the aberrant molecular events occurring in initial cancer stages could eventually influence colorectal cancer (CRC) progression. We analyzed the mRNA and miRNA expression profiles of colorectal normal mucosa, low-grade intraepithelial neoplasia (LIN), high-grade intraepithelial neoplasia (HIN), and adenocarcinoma tissues. Compared with the transitions from LIN to HIN to invasive carcinoma, the transition from normal epithelium to LIN appeared to be associated with greater changes in the number and expression levels of mRNAs and miRNAs, with a differential expression of 2322 mRNAs and 71 miRNAs detected. Utilizing these early molecular changes, a miRNA-hub network analysis showed that 166 genes were identified as targets regulated by 30 miRNAs. Among these genes, a 55-gene signature regulated by 5 miRNAs was shown to be associated with overall survival or disease-free survival in three independent sample sets. Thus, the molecular changes in the transcriptome associated with the transition from normal to intraepithelial neoplasm may influence CRC progression.

A prognosis classifier for breast cancer based on conserved gene regulation between mammary gland development and tumorigenesis: a multiscale statistical model

Identification of novel cancer genes for molecular therapy and diagnosis is a current focus of breast cancer research. Although a few small gene sets were identified as prognosis classifiers, more powerful models are still needed for the definition of effective gene sets for the diagnosis and treatment guidance in breast cancer. In the present study, we have developed a novel statistical approach for systematic analysis of intrinsic correlations of gene expression between development and tumorigenesis in mammary gland. Based on this analysis, we constructed a predictive model for prognosis in breast cancer that may be useful for therapy decisions. We first defined developmentally associated genes from a mouse mammary gland epithelial gene expression database. Then, we found that the cancer modulated genes were enriched in this developmentally associated genes list. Furthermore, the developmentally associated genes had a specific expression profile, which associated with the molecular characteristics and histological grade of the tumor. These result suggested that the processes of mammary gland development and tumorigenesis share gene regulatory mechanisms. Then, the list of regulatory genes both on the developmental and tumorigenesis process was defined an 835-member prognosis classifier, which showed an exciting ability to predict clinical outcome of three groups of breast cancer patients (the predictive accuracy 64∼72%) with a robust prognosis prediction (hazard ratio 3.3∼3.8, higher than that of other clinical risk factors (around 2.0-2.8)). In conclusion, our results identified the conserved molecular mechanisms between mammary gland development and neoplasia, and provided a unique potential model for mining unknown cancer genes and predicting the clinical status of breast tumors. These findings also suggested that developmental roles of genes may be important criteria for selecting genes for prognosis prediction in breast cancer.

Systems biology approaches to identify developmental bases for lung diseases

A greater understanding of the regulatory processes contributing to lung development could be helpful to identify strategies to ameliorate morbidity and mortality in premature infants and to identify individuals at risk for congenital and/or chronic lung diseases. Over the past decade, genomics technologies have enabled the production of rich gene expression databases providing information for all genes across developmental time or in diseased tissue. These data sets facilitate systems biology approaches for identifying underlying biological modules and programs contributing to the complex processes of normal development and those that may be associated with disease states. The next decade will undoubtedly see rapid and significant advances in redefining both lung development and disease at the systems level.

Tissue-preserving antibody cocktails to differentiate primary squamous cell carcinoma, adenocarcinoma, and small cell carcinoma of lung

CONTEXT

With the availability of cell type-specific therapies, differentiating primary lung squamous cell carcinomas (SCCs) and adenocarcinomas (ACAs) has become important. The limitations of small sample size and the need to conserve tissue for additional molecular studies necessitate the use of sensitive and specific marker panels on a single slide.

OBJECTIVE

To distinguish SCC from ACA and small cell carcinoma (SmCC) of lung using 2 novel tissue-conserving cocktails.

DESIGN

We compared two antibody cocktails, desmoglein 3 + cytokeratin 5/napsin A and p40/thyroid transcription factor 1 (Biocare Medical, Concord, California) in diagnosing SCC and ACA of the lung on tissue microarray, cytology, and surgical specimens. Both lung and nonlung tissue were evaluated on an 1150-core tissue microarray that contained 200 lung cancers. A microarray of 35 SmCCs and 5 small cell SCCs was also evaluated.

RESULTS

A cocktail of desmoglein 3 + cytokeratin 5/napsin A provided diagnostic accuracy in lung cancers with a sensitivity and specificity of 100% in SCCs and a sensitivity of 86% and a specificity of 100% in ACAs. A p40/thyroid transcription factor 1 cocktail showed p40 to have a specificity of 92% and a sensitivity of 93% in SCCs, whereas thyroid transcription factor 1 had a specificity of 100% and a sensitivity of 77% in ACAs. Cell blocks of fine-needle aspiration cytology compared with corresponding surgical (n = 20) specimens displayed similar findings. The p40 was useful in differentiating bladder from prostate carcinoma with 88% sensitivity. Isolated carcinomas from nonlung tissues were desmoglein 3 + cytokeratin 5 positive. Napsin A was positive in 22% of renal tumors as previously observed. Both cocktails were excellent in differentiating SmCCs and small cell SCCs because none of the SmCCs stained with p40.

CONCLUSIONS

Both antibody cocktails are excellent in differentiating primary lung ACA from SCC, as well as excluding SmCC and ACAs from all other sites on small specimens. A cocktail of desmoglein 3 + cytokeratin 5/napsin A is slightly superior compared with p40/thyroid transcription factor 1 cocktail.

NOTCH1, HIF1A and other cancer-related proteins in lung tissue from uranium miners--variation by occupational exposure and subtype of lung cancer

Background

Radon and arsenic are established pulmonary carcinogens. We investigated the association of cumulative exposure to these carcinogens with NOTCH1, HIF1A and other cancer-specific proteins in lung tissue from uranium miners.

Methodology/Principal Findings

Paraffin-embedded tissue of 147 miners was randomly selected from an autopsy repository by type of lung tissue, comprising adenocarcinoma (AdCa), squamous cell carcinoma (SqCC), small cell lung cancer (SCLC), and cancer-free tissue. Within each stratum, we additionally stratified by low or high level of exposure to radon or arsenic. Lifetime exposure to radon and arsenic was estimated using a quantitative job-exposure matrix developed for uranium mining. For 22 cancer-related proteins, immunohistochemical scores were calculated from the intensity and percentage of stained cells. We explored the associations of these scores with cumulative exposure to radon and arsenic with Spearman rank correlation coefficients (r_s). Occupational exposure was associated with an up-regulation of NOTCH1 (radon r_s = 0.18, 95% CI 0.02–0.33; arsenic: r_s = 0.23, 95% CI 0.07–0.38). Moreover, we investigated whether these cancer-related proteins can classify lung cancer using supervised and unsupervised classification. MUC1 classified lung cancer from cancer-free tissue with a failure rate of 2.1%. A two-protein signature discriminated SCLC (HIF1A low), AdCa (NKX2-1 high), and SqCC (NKX2-1 low) with a failure rate of 8.4%.

Conclusions/Significance

These results suggest that the radiation-sensitive protein NOTCH1 can be up-regulated in lung tissue from uranium miners by level of exposure to pulmonary carcinogens. We evaluated a three-protein signature consisting of a physiological protein (MUC1), a cancer-specific protein (HIF1A), and a lineage-specific protein (NKX2-1) that could discriminate lung cancer and its major subtypes with a low failure rate.

Cigarette smoking and lung cancer--relative risk estimates for the major histological types from a pooled analysis of case-control studies

Lung cancer is mainly caused by smoking, but the quantitative relations between smoking and histologic subtypes of lung cancer remain inconclusive. By using one of the largest lung cancer datasets ever assembled, we explored the impact of smoking on risks of the major cell types of lung cancer. This pooled analysis included 13,169 cases and 16,010 controls from Europe and Canada. Studies with population controls comprised 66.5% of the subjects. Adenocarcinoma (AdCa) was the most prevalent subtype in never smokers and in women. Squamous cell carcinoma (SqCC) predominated in male smokers. Age-adjusted odds ratios (ORs) were estimated with logistic regression. ORs were elevated for all metrics of exposure to cigarette smoke and were higher for SqCC and small cell lung cancer (SCLC) than for AdCa. Current male smokers with an average daily dose of >30 cigarettes had ORs of 103.5 (95% confidence interval (CI): 74.8-143.2) for SqCC, 111.3 (95% CI: 69.8-177.5) for SCLC and 21.9 (95% CI: 16.6-29.0) for AdCa. In women, the corresponding ORs were 62.7 (95% CI: 31.5-124.6), 108.6 (95% CI: 50.7-232.8) and 16.8 (95% CI: 9.2-30.6), respectively. Although ORs started to decline soon after quitting, they did not fully return to the baseline risk of never smokers even 35 years after cessation. The major result that smoking exerted a steeper risk gradient on SqCC and SCLC than on AdCa is in line with previous population data and biological understanding of lung cancer development.

Reversal of aberrant cancer methylome and transcriptome upon direct reprogramming of lung cancer cells

Recent reports on direct reprogramming of cancer cells (iPCs) which results in reduced tumorigenic potential has attributed the importance of epigenetics in tumorigenesis, but lacked genome-wide analysis. Here we describe successful generation of iPCs from non-small cell lung cancer (NSCLC) cell lines. Following reprogramming, they resembled embryonic stem and induced pluripotent stem cells in pluripotency markers expression, gene expression patterns and in vitro differentiation ability. Genome-wide methylation analysis revealed that aberrantly methylated promoters which were mostly developmental-associated genes and tumor suppressors; as well as commonly upregulated genes in NSCLC i.e. KRT19 and S100P were reversed in iPCs upon reprogramming. Also, the reversal of oncogenes and tumor suppressors status were partially explainable by DNA methylation. These findings suggest that DNA methylation patterns explain the downstream transcriptional effects, which potentially caused the reduced tumorigenicity in iPCs, thus providing evidence that reprogramming reverses the aberrantly dysregulated genes in NSCLC both epigenetically and transcriptionally.

Genome-wide analyses of Nkx2-1 binding to transcriptional target genes uncover novel regulatory patterns conserved in lung development and tumors

The homeodomain transcription factor Nkx2-1 is essential for normal lung development and homeostasis. In lung tumors, it is considered a lineage survival oncogene and prognostic factor depending on its expression levels. The target genes directly bound by Nkx2-1, that could be the primary effectors of its functions in the different cellular contexts where it is expressed, are mostly unknown. In embryonic day 11.5 (E11.5) mouse lung, epithelial cells expressing Nkx2-1 are predominantly expanding, and in E19.5 prenatal lungs, Nkx2-1-expressing cells are predominantly differentiating in preparation for birth. To evaluate Nkx2-1 regulated networks in these two cell contexts, we analyzed genome-wide binding of Nkx2-1 to DNA regulatory regions by chromatin immunoprecipitation followed by tiling array analysis, and intersected these data to expression data sets. We further determined expression patterns of Nkx2-1 developmental target genes in human lung tumors and correlated their expression levels to that of endogenous NKX2-1. In these studies we uncovered differential Nkx2-1 regulated networks in early and late lung development, and a direct function of Nkx2-1 in regulation of the cell cycle by controlling the expression of proliferation-related genes. New targets, validated in Nkx2-1 shRNA transduced cell lines, include E2f3, Cyclin B1, Cyclin B2, and c-Met. Expression levels of Nkx2-1 direct target genes identified in mouse development significantly correlate or anti-correlate to the levels of endogenous NKX2-1 in a dosage-dependent manner in multiple human lung tumor expression data sets, supporting alternative roles for Nkx2-1 as a transcriptional activator or repressor, and direct regulator of cell cycle progression in development and tumors.

Eight-Signature Classifier for Prediction of Nasopharyngeal Carcinoma Survival

Purpose

Currently, nasopharyngeal carcinoma (NPC) prognosis evaluation is based primarily on the TNM staging system. This study aims to identify prognostic markers for NPC.

Patients and Methods

We detected expression of 18 biomarkers by immunohistochemistry in NPC tumors from 209 patients and evaluated the association between gene expression level and disease-specific survival (DSS). We used support vector machine (SVM) –based methods to develop a prognostic classifier for NPC (NPC-SVM classifier). Further validation of the NPC-SVM classifier was performed in an independent cohort of 1,059 patients.

Results

The NPC-SVM classifier integrated patient sex and the protein expression level of seven genes, including Epstein-Barr virus latency membrane protein 1, CD147, caveolin-1, phospho-P70S6 kinase, matrix metalloproteinase 11, survivin, and secreted protein acidic and rich in cysteine. The NPC-SVM classifier distinguished patients with NPC into low- and high-risk groups with significant differences in 5-year DSS in the evaluated patients (87% v 37.7%; P < .001) in the validation cohort. In multivariate analysis adjusted for age, TNM stage, and histologic subtype, the NPC-SVM classifier was an independent predictor of 5-year DSS in the evaluated patients (hazard ratio, 4.9; 95% CI, 3.0 to 7.9) in the validation cohort.

Conclusion

As a powerful predictor of 5-year DSS among patients with NPC, the newly developed NPC-SVM classifier based on tumor-associated biomarkers will facilitate patient counseling and individualize management of patients with NPC.

DNA hypermethylation in lung cancer is targeted at differentiation-associated genes

Aberrant DNA hypermethylation of tumor suppressor genes is thought to be an early event in tumorigenesis. Many studies have reported the methylation status of individual genes with known involvement in cancer, but an unbiased assessment of the biological function of the collective of hypermethylated genes has not been conducted so far. Based on the observation that a variety of human cancers recapitulate developmental gene expression patterns (that is activate genes normally expressed in early development and suppress late developmental genes), we hypothesized that the silencing of differentiation-associated genes in cancer could be attributed in part to DNA hypermethylation. To this end, we investigated the developmental expression patterns of genes with hypermethylated CpG islands in primary human lung carcinomas and lung cancer cell lines. We found that DNA hypermethylation primarily affects genes that are expressed in late stages of murine lung development. Gene ontology characterization of these genes shows that they are almost exclusively involved in morphogenetic differentiation processes. Our results indicate that DNA hypermethylation in cancer functions as a selective silencing mechanism of genes that are required for the maintenance of a differentiated state. The process of cellular de-differentiation that is evident on both the microscopic and transcriptional level in cancer might at least partly be mediated by these epigenetic events. Our observations provide a mechanistic explanation for induction of differentiation upon treatment with DNA methyltransferase inhibitors.

Novel strategies for the treatment of small-cell lung carcinoma

Small-cell lung cancer (SCLC) is a disease with a poor prognosis and limited treatment options. Over the past 30 years, basic and clinical research have translated to little innovation in the treatment of this disease. The Study of Picoplatin Efficacy After Relapse (SPEAR) evaluated best supportive care with or without picoplatin for second-line SCLC treatment and failed to meet its primary end point of overall survival. As the largest second-line, randomized study in patients with SCLC, SPEAR provides an opportunity to critically examine the drug development model in this disease. In this Review, we discuss the current standard approach for the management of SCLC that progresses after first-line therapy, analyze the preliminary data that supported the evaluation of picoplatin in this setting, and critically evaluate the SPEAR trial design and results. Lastly, we present advances in the understanding of the molecular biology of SCLC that could potentially inform future clinical trials and hopefully lead to the successful development of molecular targeted agents for the treatment of this disease.

International association for the study of lung cancer/american thoracic society/european respiratory society international multidisciplinary classification of lung adenocarcinoma

INTRODUCTION

Adenocarcinoma is the most common histologic type of lung cancer. To address advances in oncology, molecular biology, pathology, radiology, and surgery of lung adenocarcinoma, an international multidisciplinary classification was sponsored by the International Association for the Study of Lung Cancer, American Thoracic Society, and European Respiratory Society. This new adenocarcinoma classification is needed to provide uniform terminology and diagnostic criteria, especially for bronchioloalveolar carcinoma (BAC), the overall approach to small nonresection cancer specimens, and for multidisciplinary strategic management of tissue for molecular and immunohistochemical studies.

METHODS

An international core panel of experts representing all three societies was formed with oncologists/pulmonologists, pathologists, radiologists, molecular biologists, and thoracic surgeons. A systematic review was performed under the guidance of the American Thoracic Society Documents Development and Implementation Committee. The search strategy identified 11,368 citations of which 312 articles met specified eligibility criteria and were retrieved for full text review. A series of meetings were held to discuss the development of the new classification, to develop the recommendations, and to write the current document. Recommendations for key questions were graded by strength and quality of the evidence according to the Grades of Recommendation, Assessment, Development, and Evaluation approach.

RESULTS

The classification addresses both resection specimens, and small biopsies and cytology. The terms BAC and mixed subtype adenocarcinoma are no longer used. For resection specimens, new concepts are introduced such as adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA) for small solitary adenocarcinomas with either pure lepidic growth (AIS) or predominant lepidic growth with ≤ 5 mm invasion (MIA) to define patients who, if they undergo complete resection, will have 100% or near 100% disease-specific survival, respectively. AIS and MIA are usually nonmucinous but rarely may be mucinous. Invasive adenocarcinomas are classified by predominant pattern after using comprehensive histologic subtyping with lepidic (formerly most mixed subtype tumors with nonmucinous BAC), acinar, papillary, and solid patterns; micropapillary is added as a new histologic subtype. Variants include invasive mucinous adenocarcinoma (formerly mucinous BAC), colloid, fetal, and enteric adenocarcinoma. This classification provides guidance for small biopsies and cytology specimens, as approximately 70% of lung cancers are diagnosed in such samples. Non-small cell lung carcinomas (NSCLCs), in patients with advanced-stage disease, are to be classified into more specific types such as adenocarcinoma or squamous cell carcinoma, whenever possible for several reasons: (1) adenocarcinoma or NSCLC not otherwise specified should be tested for epidermal growth factor receptor (EGFR) mutations as the presence of these mutations is predictive of responsiveness to EGFR tyrosine kinase inhibitors, (2) adenocarcinoma histology is a strong predictor for improved outcome with pemetrexed therapy compared with squamous cell carcinoma, and (3) potential life-threatening hemorrhage may occur in patients with squamous cell carcinoma who receive bevacizumab. If the tumor cannot be classified based on light microscopy alone, special studies such as immunohistochemistry and/or mucin stains should be applied to classify the tumor further. Use of the term NSCLC not otherwise specified should be minimized.

CONCLUSIONS

This new classification strategy is based on a multidisciplinary approach to diagnosis of lung adenocarcinoma that incorporates clinical, molecular, radiologic, and surgical issues, but it is primarily based on histology. This classification is intended to support clinical practice, and research investigation and clinical trials. As EGFR mutation is a validated predictive marker for response and progression-free survival with EGFR tyrosine kinase inhibitors in advanced lung adenocarcinoma, we recommend that patients with advanced adenocarcinomas be tested for EGFR mutation. This has implications for strategic management of tissue, particularly for small biopsies and cytology samples, to maximize high-quality tissue available for molecular studies. Potential impact for tumor, node, and metastasis staging include adjustment of the size T factor according to only the invasive component (1) pathologically in invasive tumors with lepidic areas or (2) radiologically by measuring the solid component of part-solid nodules.

Oligonucleotide DNA microarray profiling of lung adenocarcinoma revealed significant downregulation and deletions of vasoactive intestinal peptide receptor 1

The purpose of this study was to find novel gene(s) involved in the development of lung adenocarcinoma (AD). Using DNA microarrays, we identified 31 up-regulated and 8 downregulated genes in 12 AD. Real time PCR was used to measure expression of VIPR1 and SPP1 mRNA and possible losses or gains of genes in 32 AD. We describe significant upregulation of the SPP1 gene, downregulation of VIPR1, and losses of the VIPR1 gene. Our findings complement a proposed VIPR1 tumor suppressor role, in which deletions in the 3p22 chromosome region are an important mechanism leading to loss of the VIPR1 gene.

Identification of some human genes oppositely regulated during esophageal squamous cell carcinoma formation and human embryonic esophagus development

Here we directly compared gene expression profiles in human esophageal squamous cell carcinomas and in human fetal esophagus development. We used the suppression subtractive hybridization technique to subtract cDNAs prepared from tumor and normal human esophageal samples. cDNA sequencing and reverse transcription polymerase chain reaction (RT-PCR) analysis of RNAs from human tumor and the normal esophagus revealed 10 differentially transcribed genes: CSTA, CRNN, CEACAM1, MAL, EMP1, ECRG2, and SPRR downregulated, and PLAUR, SFRP4, and secreted protein that is acidic and rich in cysteine upregulated in tumor tissue as compared with surrounding normal tissue. In turn, genes up- and downregulated in tumor tissue were down- and upregulated, respectively, during development from the fetal to adult esophagus. Thus, we demonstrated that, as reported for other tumors, gene transcriptional activation and/or suppression events in esophageal tumor progression were opposite to those observed during development from the fetal to adult esophagus. This tumor 'embryonization' supports the idea that stem or progenitor cells are implicated in esophageal cancer emergence.

How is gene-expression profiling going to challenge the future management of lung cancer?

Lung cancer has a very high recurrence rate and mortality, even in early stages of the disease. Current clinical staging techniques have limitations in terms of predicting which patients have an increased risk of recurrence, and they are not capable of sorting out who will benefit most from adjuvant therapy in term of survival advantage. The study of genomics has revolutionized how researchers are able to identify new molecular targets and improve patient care through the identification of 'genetic fingerprints or profiles' that might be able to predict responsiveness to therapy or prognosis. Techniques such as microarray-based gene-expression profiling have also allowed investigators to reveal different non-small-cell lung cancer subtypes that have been associated with different clinical outcomes, independently of histology and current clinical staging techniques. We review the current advances in gene-expression profiling and its potential role as a diagnostic and prognostic/predictive biomarker, and how this may translate into a 'personalized medicine' for lung cancer.

Knowledge-based data analysis comes of age

The emergence of high-throughput technologies for measuring biological systems has introduced problems for data interpretation that must be addressed for proper inference. First, analysis techniques need to be matched to the biological system, reflecting in their mathematical structure the underlying behavior being studied. When this is not done, mathematical techniques will generate answers, but the values and reliability estimates may not accurately reflect the biology. Second, analysis approaches must address the vast excess in variables measured (e.g. transcript levels of genes) over the number of samples (e.g. tumors, time points), known as the 'large-p, small-n' problem. In large-p, small-n paradigms, standard statistical techniques generally fail, and computational learning algorithms are prone to overfit the data. Here we review the emergence of techniques that match mathematical structure to the biology, the use of integrated data and prior knowledge to guide statistical analysis, and the recent emergence of analysis approaches utilizing simple biological models. We show that novel biological insights have been gained using these techniques.

Stem cells and lung cancer: future therapeutic targets?

In both the UK and USA more people die of lung cancer than any other type of cancer. Lung cancer's high mortality rate is also reflected on a global scale, with lung cancer accounting for more than 1 million deaths per year. In tissues with ordered structure such a lung epithelia, it is likely that the cancers have their origins in normal adult stem cells, and then the tumours themselves are maintained by a population of malignant stem cells - so-called cancer stem cells. This review examines both these postulates in animal models and in the clinical setting, noting that stem cell niches appear to foster tumour development, and that drug resistance can often be attributed to malignant cells with stem cell properties.

Transcriptomic analysis of human lung development

RATIONALE

Current understanding of the molecular regulation of lung development is limited and derives mostly from animal studies.

OBJECTIVES

To define global patterns of gene expression during human lung development.

METHODS

Genome-wide expression profiling was used to measure the developing lung transcriptome in RNA samples derived from 38 normal human lung tissues at 53 to 154 days post conception. Principal component analysis was used to characterize global expression variation and to identify genes and bioontologic attributes contributing to these variations. Individual gene expression patterns were verified by quantitative reverse transcriptase-polymerase chain reaction analysis.

MEASUREMENTS AND MAIN RESULTS

Gene expression analysis identified attributes not previously associated with lung development, such as chemokine-immunologic processes. Lung characteristics attributes (e.g., surfactant function) were observed at an earlier-than-anticipated age. We defined a 3,223 gene developing lung characteristic subtranscriptome capable of describing a majority of the process. In gene expression space, the samples formed a time-contiguous trajectory with transition points correlating with histological stages and suggesting the existence of novel molecular substages. Induction of surfactant gene expression characterized a pseudoglandular "molecular phase" transition. Individual gene expression patterns were independently validated. We predicted the age of independent human lung transcriptome profiles with a median absolute error of 5 days, supporting the validity of the data and modeling approach.

CONCLUSIONS

This study extends our knowledge of key gene expression patterns and bioontologic attributes underlying early human lung developmental processes. The data also suggest the existence of molecular phases of lung development.

A novel five-antibody immunohistochemical test for subclassification of lung carcinoma

Malignant epithelial lung carcinoma can be subclassified by histology into several tumor types, including adenocarcinoma and squamous cell carcinoma. The need for a uniform method of classifying lung carcinomas is growing as clinical trials reveal treatment and side effect differences associated with histological subtypes. Diagnosis is primarily performed by morphological assessment. However, the increased use of needle biopsy has diminished the amount of tissue available for interpretation. These changes in how lung carcinomas are diagnosed and treated suggest that the development of improved molecular-based classification tools could improve patient management. We used a 551-patient surgical specimen lung carcinoma retrospective cohort from a regional hospital to assess the association of a large number of proteins with histological type by immunohistochemistry. Five of these antibodies, targeting the proteins TRIM29, CEACAM5, SLC7A5, MUC1, and CK5/6, were combined into one test using a weighted algorithm trained to discriminate adenocarcinoma from squamous cell carcinoma. Antibody-based classification on 600 muM tissue array cores with the five-antibody test was compared to standard histological evaluation on surgical specimens in three independent lung carcinoma cohorts (combined population of 1111 patients). In addition, the five-antibody test was tested against the two-marker panel thyroid transcription factor-1 (TTF-1) and TP63. Both the five-antibody test and TTF-1/TP63 panel had similarly low misclassification rates on the validation cohorts compared to morphological-based diagnosis (4.1 vs 3.5%). However the percentage of patients remaining unclassifiable by TTF-1/TP63 (22%, 95% CI: 20-25%) was twice that of the five-antibody test (11%, 95% CI: 8-13%). The results of this study suggest the five-antibody test may have an immediate function in the clinic for helping pathologists distinguish lung carcinoma histological types. The results also suggest that if validated in prospectively defined clinical trials this classifier might identify candidates for targeted therapy that are overlooked with current diagnostic approaches.

Gene expression profiling and non-small-cell lung cancer: where are we now?

Despite new developments in molecular techniques and better knowledge on lung cancer tumor biology, many genetic alterations associated with the development and progression of lung carcinogenesis still remain unclear. Although the development of targeted agents has improved response rates and survival, lung cancer has a very high mortality rate, even for early stages. Thus, there is a greater need for other mechanisms or technologies that may help us diagnose, predict, and treat patients with lung cancer in a more effective way. One of these technologies has been the use of genomics. Some of the available genomic technologies include single-nucleotide polymorphism analysis, high-throughput capillary sequencing, serial analysis of gene expression, and gene expression arrays. DNA microarray analysis is capable of discovering changes in DNA expression within the neoplastic tumor. Thus, gene expression array could help us to decipher the complexity and interaction of different oncogenic pathways and, hence, could contribute to the selection of better targeted agents on an individual basis rather than a general and nonspecific approach as it has been done for many decades. Several studies initiated a few years ago have started to produce fruitful results. Herein, we review the role of gene expression profiling in lung cancer as a diagnostic tool, predictive and prognostic biomarker, and its potential use for a "personalized" medicine in the years to come.