A gene expression signature from peripheral whole blood for stage I lung adenocarcinoma

An engineered niche delineates metastatic potential of breast cancer

Metastatic breast cancer is often not diagnosed until secondary tumors have become macroscopically visible and millions of tumor cells have invaded distant tissues. Yet, metastasis is initiated by a cascade of events leading to formation of the pre-metastatic niche, which can precede tumor formation by a matter of years. We aimed to distinguish the potential for metastatic disease from nonmetastatic disease at early times in triple-negative breast cancer using sister cell lines 4T1 (metastatic), 4T07 (invasive, nonmetastatic), and 67NR (nonmetastatic). We used a porous, polycaprolactone scaffold, that serves as an engineered metastatic niche, to identify metastatic disease through the characteristics of the microenvironment. Analysis of the immune cell composition at the scaffold was able to distinguish noninvasive 67NR tumor-bearing mice from 4T07 and 4T1 tumor-bearing mice but could not delineate metastatic potential between the two invasive cell lines. Gene expression in the scaffolds correlated with the up-regulation of cancer hallmarks (e.g., angiogenesis, hypoxia) in the 4T1 mice relative to 4T07 mice. We developed a 9-gene signature (Dhx9, Dusp12, Fth1, Ifitm1, Ndufs1, Pja2, Slc1a3, Soga1, Spon2) that successfully distinguished 4T1 disease from 67NR or 4T07 disease throughout metastatic progression. Furthermore, this signature proved highly effective at distinguishing diseased lungs in publicly available datasets of mouse models of metastatic breast cancer and in human models of lung cancer. The early and accurate detection of metastatic disease that could lead to early treatment has the potential to improve patient outcomes and quality of life.

Increased expression of individual genes in whole blood is associated with late-stage lung cancer at and close to diagnosis

Lung cancer (LC) mortality rates are still increasing globally. As survival is linked to stage, there is a need to identify markers for earlier LC diagnosis and individualized treatment. The whole blood transcriptome of LC patients represents a source of potential LC biomarkers. We compared expression of > 60,000 genes in whole blood specimens taken from LC cases at diagnosis (n = 128) and controls (n = 62) using genome-wide RNA sequencing, and identified 14 candidate genes associated with LC. High expression of ANXA3, ARG1 and HP was strongly associated with lower survival in late-stage LC cases (hazard ratios (HRs) = 2.81, 2.16 and 2.54, respectively). We validated these markers in two independent population-based studies with pre-diagnostic whole blood specimens taken up to eight years prior to LC diagnosis (n = 163 cases, 184 matched controls). ANXA3 and ARG1 expression was strongly associated with LC in these specimens, especially with late-stage LC within two years of diagnosis (odds ratios (ORs) = 3.47 and 5.00, respectively). Additionally, blood CD4 T cells, NK cells and neutrophils were associated with LC at diagnosis and improved LC discriminative ability beyond candidate genes. Our results indicate that in whole blood, increased expression levels of ANXA3, ARG1 and HP are diagnostic and prognostic markers of late-stage LC.

Therapeutic effects of medicinal plants and their constituents on lung cancer, in vitro, in vivo and clinical evidence

The most common type of cancer in the world is lung cancer. Traditional treatments have an important role in cancer therapy. In the present review, the most recent findings on the effects of medicinal plants and their constituents or natural products (NP) in treating lung cancer are discussed. Empirical studies until the end of March 2022 were searched using the appropriate keywords through the databases PubMed, Science Direct and Scopus. The extracts and essential oils tested were all shown to effect lung cancer by several mechanisms including decreased tumour weight and volume, cell viability and modulation of cytokine. Some plant constituents increased expression of apoptotic proteins, the proportion of cells in the G2/M phase and subG0/G1 phase, and Cyt c levels. Also, natural products (NP) activate apoptotic pathways in lung cancer cell including p-JNK, Akt/mTOR, PI3/ AKT\ and Bax, Bcl2, but suppressed AXL phosphorylation. Plant-derived substances altered the cell morphology, reduced cell migration and metastasis, oxidative marker production, p-eIF2α and GRP78, IgG, IgM levels and reduced leukocyte counts, LDH, GGT, 5'NT and carcinoembryonic antigen (CEA). Therefore, medicinal plant extracts and their constituents could have promising therapeutic value for lung cancer, especially if used in combination with ordinary anti-cancer drugs.

Biomarkers for Immune Checkpoint Inhibitor Response in NSCLC: Current Developments and Applicability

Lung cancer has the highest mortality rate among all cancer types, resulting in over 1.8 million deaths annually. Immunotherapy utilizing immune checkpoint inhibitors (ICIs) has revolutionized the treatment of non-small cell lung cancer (NSCLC). ICIs, predominantly monoclonal antibodies, modulate co-stimulatory and co-inhibitory signals crucial for maintaining immune tolerance. Despite significant therapeutic advancements in NSCLC, patients still face challenges such as disease progression, recurrence, and high mortality rates. Therefore, there is a need for predictive biomarkers that can guide lung cancer treatment strategies. Currently, programmed death-ligand 1 (PD-L1) expression is the only established biomarker for predicting ICI response. However, its accuracy and robustness are not consistently reliable. This review provides an overview of potential biomarkers currently under development or in the validation stage that hold promise in improving the classification of responders and non-responders to ICI therapy in the near future.

Toward a Systematic Assessment of Sex Differences in Cystic Fibrosis

(1) Background: Cystic fibrosis (CF) is a disease with well-documented clinical differences between female and male patients. However, this gender gap is very poorly studied at the molecular level. (2) Methods: Expression differences in whole blood transcriptomics between female and male CF patients are analyzed in order to determine the pathways related to sex-biased genes and assess their potential influence on sex-specific effects in CF patients. (3) Results: We identify sex-biased genes in female and male CF patients and provide explanations for some sex-specific differences at the molecular level. (4) Conclusion: Genes in key pathways associated with CF are differentially expressed between sexes, and thus may account for the gender gap in morbidity and mortality in CF.

Dual inhibition of EGFR‑VEGF: An effective approach to the treatment of advanced non‑small cell lung cancer with EGFR mutation (Review)

On a global scale, the incidence and mortality rates of lung cancer are gradually increasing year by year. A number of bad habits and environmental factors are associated with lung cancer, including smoking, second‑hand smoke exposure, occupational exposure, respiratory diseases and genetics. At present, low‑dose spiral computed tomography is routinely the first choice in the diagnosis of lung cancer. However, pathological examination is still the gold standard for the diagnosis of lung cancer. Based on the classification and stage of the cancer, treatment options such as surgery, radiotherapy, chemotherapy, targeted therapy and immunotherapy are available. The activation of the EGFR pathway can promote the survival and proliferation of tumor cells, and the VEGF pathway can promote the formation of blood vessels, thereby promoting tumor growth. In non‑small cell lung cancer (NSCLC) with EGFR mutation, EGFR activation can promote tumor growth by promoting VEGF upregulation through a hypoxia‑independent mechanism. The upregulation of VEGF can make tumor cells resistant to EGFR inhibitors. In addition, the expression of the VEGF signal is also affected by other factors. Therefore, the use of a single EGFR inhibitor cannot completely inhibit the expression of the VEGF signal. In order to overcome this problem, the combination of VEGF inhibitors and EGFR inhibitors has become the method of choice. Dual inhibition can not only overcome the resistance of tumor cells to EGFR inhibitors, but also significantly increase the progression‑free survival time of patients with NSCLC. The present review discusses the associations between the EGFR and VEGF pathways, and the characteristics of dual inhibition of the EGFR‑VEGF pathway.

Differential expression of immune-regulatory proteins C5AR1, CLEC4A and NLRP3 on peripheral blood mononuclear cells in early-stage non-small cell lung cancer patients

Changes in gene expression profiling of peripheral blood mononuclear cells (PBMC) appear to represent the host's response to the cancer cells via paracrine signaling. We speculated that protein expression on circulating T-lymphocytes represent T-lymphocyte trafficking before infiltration into the tumor microenvironment. The possibility of using protein expression on circulating T-lymphocytes as a biomarker to discriminate early-stage non-small cell lung cancer (NSCLC) was explored. Four independent PBMC gene expression microarray datasets (GSE12771, GSE13255, GSE20189 and GSE3934) were analyzed. We selected C5AR1, CLEC4A and NLRP3 based on their significant protein expression in tumor-infiltrating lymphocytes, but not in normal lymphoid tissue. A validation study using automated flow cytometry was conducted in 141 study participants including 76 treatment-naive early-stage non-small cell lung cancer patients (NSCLC), 12 individuals with non-malignant pulmonary diseases, and 53 healthy individuals. Median ratios of C5AR1, CLEC4A and NLRP3 specific antibody staining to CD3 positive cells in early-stage NSCLC patients compared to healthy controls were 0.014 [0-0.37] vs. 0.01 [0-0.07, p = 0.13], 0.03 [0-0.87] vs. 0.02 [0-0.13, p = 0.10] and 0.19 [0-0.60] vs. 0.09 [0.02-0.31, p < 0.0001], respectively. Median fluorescence intensity (MFI) of CD3⁺C5AR1⁺, CD3⁺CLEC4A⁺ and CD3⁺NLRP3⁺ expression in early-stage NSCLC patients compared to healthy volunteers was 185 [64.2-4801] vs. 107.5 [27-229, p < 0.0001], 91.2 [42.4-2355] vs. 71.25 [46.2-103, p = 0.0005], and 1585 [478-5224] vs. 758.5 [318-1976, p < 0.0001], respectively. NLRP3:CD3 ratio, CD3⁺C5AR1⁺, CD3⁺CLEC4A⁺ and CD3⁺NLRP3⁺ MFI were significantly higher in early-stage NSCLC than healthy volunteers with an area under the ROC curve of 0.69-0.76. The CD3⁺NLRP3⁺ MFI provided the most distinguishable expression at 71.5% sensitivity and 70% specificity. Furthermore, CD3⁺NLRP3⁺ MFI potentially discriminated between early-stage NSCLC from malignant-mimic inflammation and infection pulmonary disease. Further validation in various pulmonary inflammatory disease might be warranted. Our proof-of-principle findings strengthen the hypothesis that malignancies generate distinctive protein expression fingerprints on circulating T-lymphocytes.

A novel meta-analysis based on data augmentation and elastic data shared lasso regularization for gene expression

Background

Gene expression analysis can provide useful information for analyzing complex biological mechanisms. However, many reported findings are unrepeatable due to small sample sizes relative to a large number of genes and the low signal-to-noise ratios of most gene expression datasets.

Results

Meta-analysis of multi-data sets is an efficient method for tackling the above problem. To improve the performance of meta-analysis, we propose a novel meta-analysis framework. It consists of two parts: (1) a novel data augmentation strategy. Various cross-platform normalization methods exist, which can preserve original biological information of gene expression datasets from different angles and add different “perturbations” to the dataset. Using such perturbation, we provide a feasible means for gene expression data augmentation; (2) elastic data shared lasso (DSL-\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${{\varvec{L}}}_{\mathbf{2}}$$\end{document}L2). The DSL-\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathbf{L}}_{\mathbf{2}}$$\end{document}L2 method spans the continuum between individual models for each dataset and one model for all datasets. It also overcomes the shortcomings of the data shared lasso method when dealing with highly correlated features. Comprehensive simulation experiment results show that the proposed method has high prediction and gene selection performance. We then apply the proposed method to non-small cell lung cancer (NSCLC) blood gene expression data in order to identify key tumor-related genes. The outcomes of our experiment indicate that the method could be used for identifying a set of robust disease-related gene signatures that may be used for NSCLC early diagnosis or prognosis or even targeting.

Conclusion

We propose a novel and effective meta-analysis method for biological research, extrapolating and integrating information from multiple gene expression datasets.

Intelligent Programmable DNA Nanomachines for the Spatially Controllable Imaging of Intracellular MicroRNA

The high programmability of DNA molecules makes them particularly suitable for constructing artificial molecular machines to perform sophisticated functions by simulating complex living systems. However, intelligent DNA nanomachines which can perform precise tasks logically in complex environments still remain challenging. Herein, we develop a general strategy to design a pH-responsive programmable DNA (PRPD) nanomachine to perform multilayer DNA cascades, enabling precise sensing and calculation of intracellular biomolecules. The PRPD nanomachine is built on a four-stranded DNAzyme walker precursor with a DNA switch on the surface of an Au nanoparticle, which is capable of precisely responding to pH variations in living cells by sequence tuning. This multilayer DNA cascade networks have been applicated in spatially controlled imaging of intracellular microRNA, which efficiently avoided the DNA nanomachine activated by nonspecific extracellular molecules and achieved apparent signal amplification. Our strategy enables the sensing-computing-output functional integration of DNA nanomachines, facilitating the application of programmable and complex nanomachines in nanoengineering, chemistry, and biomedicine.

Using biological information to analyze potential miRNA-mRNA regulatory networks in the plasma of patients with non-small cell lung cancer

Background

Lung cancer is the most common malignant tumor, and it has a high mortality rate. However, the study of miRNA-mRNA regulatory networks in the plasma of patients with non-small cell lung cancer (NSCLC) is insufficient. Therefore, this study explored the differential expression of mRNA and miRNA in the plasma of NSCLC patients.

Methods

The Gene Expression Omnibus (GEO) database was used to download microarray datasets, and the differentially expressed miRNAs (DEMs) were analyzed. We predicted transcription factors and target genes of the DEMs by using FunRich software and the TargetScanHuman database, respectively. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was used for GO annotation and KEGG enrichment analysis of downstream target genes. We constructed protein-protein interaction (PPI) and DEM-hub gene networks using the STRING database and Cytoscape software. The GSE20189 dataset was used to screen out the key hub gene. Using The Cancer Genome Atlas (TCGA) and UALCAN databases to analyze the expression and prognosis of the key hub gene and DEMs. Then, GSE17681 and GSE137140 datasets were used to validate DEMs expression. Finally, the receiver operating characteristic (ROC) curve was used to verify the ability of the DEMs to distinguish lung cancer patients from healthy patients.

Results

Four upregulated candidate DEMs (hsa-miR199a-5p, hsa-miR-186-5p, hsa-miR-328-3p, and hsa-let-7d-3p) were screened from 3 databases, and 6 upstream transcription factors and 2253 downstream target genes were predicted. These genes were mainly enriched in cancer pathways and PI3k-Akt pathways. Among the top 30 hub genes, the expression of KLHL3 was consistent with the GSE20189 dataset. Except for let-7d-3p, the expression of other DEMs and KLHL3 in tissues were consistent with those in plasma. LUSC patients with high let-7d-3p expression had poor overall survival rates (OS). External validation demonstrated that the expression of hsa-miR-199a-5p and hsa-miR-186-5p in peripheral blood of NSCLC patients was higher than the healthy controls. The ROC curve confirmed that the DEMs could better distinguish lung cancer patients from healthy people.

Conclusion

The results showed that miR-199a-5p and miR-186-5p may be noninvasive diagnostic biomarkers for NSCLC patients. MiR-199a-5p-KLHL3 may be involved in the occurrence and development of NSCLC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09281-1.

Effects of Allium cepa and Its Constituents on Respiratory and Allergic Disorders: A Comprehensive Review of Experimental and Clinical Evidence

The health benefits of Allium cepa (A. cepa) have been proclaimed for centuries. Various pharmacological and therapeutic effects on respiratory, allergic, and immunologic disorders are shown by A. cepa and its constituents. Flavonoids such as quercetin and kaempferol, alk(en)yl cysteine sulfoxides including S-methyl cysteine sulfoxide and S-propyl cysteine sulfoxide, cycloalliin, thiosulfinates, and sulfides are the main compounds of the plant. A. cepa displays broad-spectrum pharmacological activities including antioxidant, anti-inflammatory, antihypertensive, and antidiabetic effects. Our objective in this review is to present the effects of A. cepa and its constituents on respiratory, allergic, and immunologic disorders. Different online databases were searched to find articles related to the effect of A. cepa extracts and its constituents on respiratory, allergic, and immunologic disorders until the end of December 2020 using keywords such as onion, A. cepa, constituents of A. cepa, therapeutic effects and pharmacological effects, and respiratory, allergic, and immunologic disorders. Extracts and constituents of A. cepa showed tracheal smooth muscle relaxant effects, indicating possible bronchodilator activities or relieving effects on obstructive respiratory diseases. In experimental animal models of different respiratory diseases, the preventive effect of various extracts and constituents of A. cepa was induced by their antioxidant, immunomodulatory, and anti-inflammatory effects. The preventive effects of the plant and its components on lung disorders induced by exposure to noxious agents as well as lung cancer, lung infection, and allergic and immunologic disorders were also indicated in the experimental and clinical studies. Therefore, this review may be considered a scientific basis for development of therapies using this plant, to improve respiratory, allergic, and immunologic disorders.

Current and Future Development in Lung Cancer Diagnosis

Lung cancer is the leading cause of cancer-related deaths in North America and other developed countries. One of the reasons lung cancer is at the top of the list is that it is often not diagnosed until the cancer is at an advanced stage. Thus, the earliest diagnosis of lung cancer is crucial, especially in screening high-risk populations, such as smokers, exposure to fumes, oil fields, toxic occupational places, etc. Based on the current knowledge, it looks that there is an urgent need to identify novel biomarkers. The current diagnosis of lung cancer includes different types of imaging complemented with pathological assessment of biopsies, but these techniques can still not detect early lung cancer developments. In this review, we described the advantages and disadvantages of current methods used in diagnosing lung cancer, and we provide an analysis of the potential use of body fluids as carriers of biomarkers as predictors of cancer development and progression.

Identification of a methylomics-associated nomogram for predicting overall survival of stage I-II lung adenocarcinoma

The aim of this paper was to identify DNA methylation based biomarkers for predicting overall survival (OS) of stage I–II lung adenocarcinoma (LUAD) patients. Methylation profile data of patients with stage I–II LUAD from The Cancer Genome Atlas (TCGA) database was used to determine methylation sites-based hallmark for stage I–II LUAD patients’ OS. The patients were separated into training and validation datasets by using median risk score as cutoff. Univariate Cox, least absolute shrinkage and selection operator (LASSO) and multivariate Cox analyses were employed to develop a DNA methylation signature for OS of patients with stage I–II LUAD. As a result, an 11-DNA methylation signature was determined to be critically associated with the OS of patients with stage I–II LUAD. Analysis of receiver operating characteristics (ROC) suggested a high prognostic effectiveness of the 11-DNA methylation signature in patients with stage I–II LUAD (AUC at 1, 3, 5 years in training set were (0.849, 0.879, 0.831, respectively), validation set (0.742, 0.807, 0.904, respectively), entire TCGA dataset (0.747, 0.818, 0.870, respectively). Kaplan–Meier survival analyses exhibited that survival was significantly longer in the low-risk cohort compared to the high-risk cohort in the training dataset (P = 7e − 07), in the validation dataset (P = 1e − 08), and in the all-cohort dataset (P = 6e − 14). In addition, a nomogram was developed based on molecular factor (methylation risk score) as well as clinical factors (age and cancer status) (AUC at 1, 3, 5 years entire TCGA dataset were 0.770, 0.849, 0.979, respectively). The result verified that our methylomics-associated nomogram had a strong robustness for predicting stage I–II LUAD patients’ OS. Furthermore, the nomogram combined clinical and molecular factors to determine an individualized probability of recurrence for patients with stage I–II LUAD, which stood for a major advance in the field of personalized medicine for pulmonary oncology. Collectively, we successfully identified a DNA methylation biomarker and a DNA methylation-based nomogram to predict the OS of patients with stage I–II LUAD.

Abnormal Expression and Prognostic Significance of Bone Morphogenetic Proteins and Their Receptors in Lung Adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is one of the most life-threatening malignancies. The crucial role of bone morphogenetic protein (BMP)/BMP receptors reveals the significance of exploring BMP protein-related prognostic predictors in LUAD.

Methods

The mRNA expression of BMPs/BMP receptors was investigated in LUAD and normal lung tissues. Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes pathway analyses were performed, and the prognostic values were assessed by Kaplan-Meier Plotter. Univariate and multivariate Cox regression analyses were executed to ascertain the correlation between overall survival (OS) and the mRNA expression of BMPs/BMP receptors. The receiver operating characteristic (ROC) curves were implemented to evaluate the predictive power of the prognostic model. Then, the prognostic model was validated in the GEO cohort. Furthermore, a nomogram comprising the prognostic model was established.

Results

The mRNA expression of BMP2/5/6/R2, ACVRL1, and TGFBR2/3 was lower in LUAD tissues than in normal lung tissues. High expression of BMP2/4/5/R1A/R2, ACVR1/2A/L1, and TGFBR1/3 was associated with better OS, while BMP7 and ACVR1C/2B were associated with poorer OS. Three genes (BMP5, BMP7, and ACVR2A) were screened by univariate and multivariate Cox regression analyses to develop the prognostic model in TCGA. Significantly better survival was observed in LUAD patients with a low-risk score than those with a high-risk score. The ROC curves confirmed the good performance of the prognostic model, then, the prognostic model was validated in the GSE31210 dataset. A nomogram was constructed (AUCs>0.7). And hub genes were further evaluated, including gene set enrichment analysis and immune cell infiltration.

Conclusions

BMP5, BMP7, and ACVR2A are potential therapeutic targets in LUAD. The three-gene prognostic model and the nomogram are reliable tools for predicting the OS of LUAD patients.

Tissue-specific transplantation antigen P35B functions as an oncogene and is regulated by microRNA-125a-5p in lung cancer

Tissue‑specific transplantation antigen P35B (TSTA3) expression is upregulated in esophageal squamous cell carcinoma and breast cancer, and functions as an oncogene in breast cancer. However, the roles and underlying mechanisms of TSTA3 in lung cancer have not been fully elucidated. The current study aimed to reveal the role of TSTA3 in lung cancer and explore whether TSTA3 may be modulated by microRNA (miR)‑125a‑5p to activate β‑catenin signaling. Immunohistochemical staining and western blotting were used to analyze TSTA3 expression in lung cancer tissues and cells. Cell functions were assessed via Cell Counting Kit‑8, flow cytometry, wound‑healing, Transwell and in vivo tumor formation assays. The effect of TSTA3 on the activation of β‑catenin signaling was determined using western blot and immunofluorescence analyses. The association between miR‑125a‑5p and TSTA3 was determined by western blotting and luciferase gene reporter assay. The present study revealed that, compared with normal tissues and cells, TSTA3 expression was significantly increased in lung cancer tissues and cell lines, and high TSTA3 expression predicted a poor prognosis and more malignant clinical features in patients with lung cancer. TSTA3 upregulation significantly enhanced β‑catenin expression and promoted its nuclear accumulation. In addition, TSTA3 expression was negatively regulated by miR‑125a‑5p, which was downregulated in lung cancer. Furthermore, TSTA3 overexpression markedly promoted cell proliferation, migration, invasion and tumorigenesis, and suppressed cell apoptosis. TSTA3 downregulation abolished the effects of miR‑125a‑5p downregulation on promoting lung cancer cell malignant transformation. Overall, the current study demonstrates that TSTA3 is regulated by miR‑125a‑5p and functions as an oncogene in lung cancer via promoting the activation of β‑catenin signaling.

Transcriptomic signals in blood prior to lung cancer focusing on time to diagnosis and metastasis

Recent studies have indicated that there are functional genomic signals that can be detected in blood years before cancer diagnosis. This study aimed to assess gene expression in prospective blood samples from the Norwegian Women and Cancer cohort focusing on time to lung cancer diagnosis and metastatic cancer using a nested case–control design. We employed several approaches to statistically analyze the data and the methods indicated that the case–control differences were subtle but most distinguishable in metastatic case–control pairs in the period 0–3 years prior to diagnosis. The genes of interest along with estimated blood cell populations could indicate disruption of immunological processes in blood. The genes identified from approaches focusing on alterations with time to diagnosis were distinct from those focusing on the case–control differences. Our results support that explorative analyses of prospective blood samples could indicate circulating signals of disease-related processes.

Engineered Niches to Analyze Mechanisms of Metastasis and Guide Precision Medicine

Cancer metastasis poses a challenging problem both clinically and scientifically, as the stochastic nature of metastatic lesion formation introduces complexity for both early detection and the study of metastasis in preclinical models. Engineered metastatic niches represent an emerging approach to address this stochasticity by creating bioengineered sites where cancer can preferentially metastasize. As the engineered niche captures the earliest metastatic cells at a nonvital location, both noninvasive and biopsy-based monitoring of these sites can be performed routinely to detect metastasis early and monitor alterations in the forming metastatic niche. The engineered metastatic niche also provides a new platform technology that serves as a tunable site to molecularly dissect metastatic disease mechanisms. Ultimately, linking the engineered niches with advances in sensor development and synthetic biology can provide enabling tools for preclinical cancer models and fosters the potential to impact the future of clinical cancer care.

TSTA3 facilitates esophageal squamous cell carcinoma progression through regulating fucosylation of LAMP2 and ERBB2

Background: TSTA3 gene encodes an enzyme responsible for synthesis of GDP-L-fucose as the only donor in fucosylation. This study was designed to explore clinical value, function and underlying mechanism of TSTA3 in the development of esophageal squamous cell carcinoma (ESCC). Methods: Whole genomic sequencing data from 663 ESCC patients and RNA sequencing data from 155 ESCC patients were used to analyze the copy number variation and mRNA expression of TSTA3 respectively. Immunohistochemistry based or not based on the tissue microarrays was used to detect its protein expression. Transwell assay and in vivo metastasis assay were used to study the effect of TSTA3 on invasion and metastasis of ESCC. Immunofluorescence was used to analyze fucosylation level. N-glycoproteomics and proteomics analysis, Lens Culinaris Agglutinin (LCA) and Ulex Europaeus Agglutinin I (UEA-I) affinity chromatography, immunoprecipitation, glycosyltransferase activity kit and rescue assay were used to explore the mechanism of TSTA3. Results: TSTA3 was frequently amplified and overexpressed in ESCC. TSTA3 amplification and protein overexpression were significantly associated with malignant progression and poor prognosis of ESCC patients. TSTA3 knockdown significantly suppressed ESCC cells invasion and tumor dissemination by decreasing fucosylation level. Conversely, exogenous overexpression of TSTA3 led to increased invasion and tumor metastasis in vitro and in vivo by increasing fucosylation level. Moreover, core fucosylated LAMP2 and terminal fucosylated ERBB2 might be mediators of TSTA3-induced pro-invasion in ESCC and had a synergistic effect on the process. Peracetylated 2-F-Fuc, a fucosyltransferase activity inhibitor, reduced TSTA3 expression and fucosylation modification of LAMP2 and ERBB2, thereby inhibiting ESCC cell invasion. Conclusion: Our results indicate that TSTA3 may be a driver of ESCC metastasis through regulating fucosylation of LAMP2 and ERBB2. Fucosylation inhibitor may have prospect to suppress ESCC metastasis by blocking aberrant fucosylation.

Cancer diagnosis with DNA molecular computation

Early and precise cancer diagnosis substantially improves patient survival. Recent work has revealed that the levels of multiple microRNAs in serum are informative as biomarkers for the diagnosis of cancers. Here, we designed a DNA molecular computation platform for the analysis of miRNA profiles in clinical serum samples. A computational classifier is first trained in silico using miRNA profiles from The Cancer Genome Atlas. This is followed by a computationally powerful but simple molecular implementation scheme using DNA, as well as an effective in situ amplification and transformation method for miRNA enrichment in serum without perturbing the original variety and quantity information. We successfully achieved rapid and accurate cancer diagnosis using clinical serum samples from 22 healthy people (8) and people with lung cancer (14) with an accuracy of 86.4%. We envision that this DNA computational platform will inspire more clinical applications towards inexpensive, non-invasive and rapid disease screening, classification and progress monitoring.

Prognostic implications of a molecular classifier derived from whole-exome sequencing in nasopharyngeal carcinoma

The aim of this study was to use whole-exome sequencing to derive a molecular classifier for nasopharyngeal carcinoma (NPC) and evaluate its clinical performance. We performed whole-exome sequencing on 82 primary NPC tumors from Sun Yat-sen University Cancer Center (Guangzhou cohort) to obtain somatic single-nucleotide variants, indels, and copy number variants. A novel molecular classifier was then developed and validated in another NPC cohort (Hong Kong cohort, n = 99). Survival analysis was estimated by the Kaplan-Meier method and compared using the log-rank test. Cox proportional hazards model was adopted for univariate and multivariate analyses. We identified three prominent NPC genetic subtypes: RAS/PI3K/AKT (based on RAS, AKT1, and PIK3CA mutations), cell-cycle (based on CDKN2A/CDKN2B deletions, and CDKN1B and CCND1 amplifications), and unclassified (based on dominant mutations in epigenetic regulators, such as KMT2C/2D, or the Notch signaling pathway, such as NOTCH1/2). These subtypes differed in survival analysis, with good, intermediate, and poor progression-free survival in the unclassified, cell-cycle, and RAS/PI3K/AKT subgroups, respectively, among the Guangzhou, Hong Kong, and combined cohorts (n = 82, P = 0.0342; n = 99, P = 0.0372; and n = 181, P = 0.0023; log-rank test). We have uncovered genetic subtypes of NPC with distinct mutations and/or copy number changes, reflecting discrete paths of NPC tumorigenesis and providing a roadmap for developing new prognostic biomarkers and targeted therapies.

A Meta-Analysis of the Performance of a Blood-Based Exposure Response Gene Signature Across Clinical Studies on the Tobacco Heating System 2.2 (THS 2.2)

As part of emerging tobacco harm reduction strategies, modified risk tobacco products (MRTP) are being developed to offer alternatives that have the potential to reduce the individual risk and population harm compared with smoking cigarettes for adult smokers who want to continue using tobacco and nicotine products. MRTPs are defined as any tobacco products that are distributed for use to reduce harm or the risk of tobacco-related disease associated with commercially marketed tobacco products. One such candidate MRTP is the Tobacco Heating System (THS) 2.2, which does not burn tobacco but instead heats it, thus producing significantly reduced levels of harmful and potentially harmful constituents compared with cigarettes. The clinical assessment of candidate MRTPs requires the development of exposure-response markers to distinguish current smokers from either nonsmokers or former smokers with high specificity and sensitivity. Toward this end, a whole blood-derived gene signature was previously developed and reported. Four randomized, controlled, open-label, three-arm parallel group reduced exposure clinical studies have been conducted with subjects randomized to three arms: switching from cigarettes to THS 2.2, continuous use of cigarettes, or smoking abstinence. These clinical studies had an investigational period of 5 days in confinement, which was followed by an 85-day ambulatory period in two studies. Here we tested the previously developed blood-derived signature on the samples derived from those clinical studies. We showed that in all four studies, the signature scores were reduced consistently in subjects who either stopped smoking or switched to THS 2.2 compared with subjects who continued smoking cigarettes.

Detection of early lung cancer among military personnel (DECAMP) consortium: study protocols

BACKGROUND

Lung cancer is the leading cause of cancer-related death due in large part to our inability to diagnose it at an early and potentially curable stage. Screening for lung cancer via low dose computed tomographic (LDCT) imaging has been demonstrated to improve mortality but also results in a high rate of false positive tests. The identification and application of non-invasive molecular biomarkers that improve the performance of CT imaging for the detection of lung cancer in high risk individuals would aid in clinical decision-making, eliminate the need for unnecessary LDCT follow-up, and further refine the screening criteria for an already large high-risk population.

METHODS

The Detection of Early Lung Cancer Among Military Personnel (DECAMP) consortium is conducting two multicenter prospective studies with the goals of developing an integrated panel of both airway and blood-based molecular biomarkers that discriminate benign and malignant indeterminate nodules detected on CT scan as well as predict the future development of lung cancer in high-risk individuals. To achieve these goals, DECAMP is compiling an extensive array of biospecimens including nasal brushings, serum, plasma and intrathoracic airway samples (bronchial brushings and bronchial biopsies) from normal-appearing airway epithelium.

DISCUSSION

This bank of samples is the foundation for multiple DECAMP efforts focused on the identification of those at greatest risk of developing lung cancer as well as the discrimination of benign and malignant pulmonary nodules. The clinical, imaging and biospecimen repositories will serve as a resource for the biomedical community and their investigation of the molecular basis of chronic respiratory disease.

TRIAL REGISTRATION

Retrospectively registered as NCT01785342 - DECAMP-1: Diagnosis and Surveillance of Indeterminate Pulmonary Nodules (DECAMP-1). Date of Registration: February 7, 2013. Retrospectively registered as NCT02504697 - DECAMP-2: Screening of Patients With Early Stage Lung Cancer or at High Risk for Developing Lung Cancer (DECAMP-2). Date of Registration: July 22, 2015.

The Airway Transcriptome as a Biomarker for Early Lung Cancer Detection

Lung cancer remains the leading cause of cancer-related death due to its advanced stage at diagnosis. Early detection of lung cancer can be improved by better defining who should be screened radiographically and determining which imaging-detected pulmonary nodules are malignant. Gene expression biomarkers measured in normal-appearing airway epithelium provide an opportunity to use lung cancer-associated molecular changes in this tissue for early detection of lung cancer. Molecular changes in the airway may result from an etiologic field of injury and/or field cancerization. The etiologic field of injury reflects the aberrant physiologic response to carcinogen exposure that creates a susceptible microenvironment for cancer initiation. In contrast, field cancerization reflects effects of "first-hit" mutations in a clone of cells from which the tumor ultimately arises or the effects of the tumor on the surrounding tissue. These fields might have value both for assessing lung cancer risk and diagnosis. Cancer-associated gene expression changes in the bronchial airway have recently been used to develop and validate a 23-gene classifier that improves the diagnostic yield of bronchoscopy for lung cancer among intermediate-risk patients. Recent studies have demonstrated that these lung cancer-related gene expression changes extend to nasal epithelial cells that can be sampled noninvasively. While the bronchial gene expression biomarker is being adopted clinically, further work is necessary to explore the potential clinical utility of gene expression profiling in the nasal epithelium for lung cancer diagnosis, lung cancer risk assessment, and precision medicine for lung cancer treatment and chemoprevention. Clin Cancer Res; 24(13); 2984-92. ©2018 AACR.

A molecular multi-gene classifier for disease diagnostics

Despite its early promise as a diagnostic and prognostic tool, gene expression profiling remains cost-prohibitive and challenging to implement in a clinical setting. Here, we introduce a molecular computation strategy for analysing the information contained in complex gene expression signatures without the need for costly instrumentation. Our workflow begins by training a computational classifier on labelled gene expression data. This in silico classifier is then realized at the molecular level to enable expression analysis and classification of previously uncharacterized samples. Classification occurs through a series of molecular interactions between RNA inputs and engineered DNA probes designed to differentially weigh each input according to its importance. We validate our technology with two applications: a classifier for early cancer diagnostics and a classifier for differentiating viral and bacterial respiratory infections based on host gene expression. Together, our results demonstrate a general and modular framework for low-cost gene expression analysis.

Curated compendium of human transcriptional biomarker data

One important use of genome-wide transcriptional profiles is to identify relationships between transcription levels and patient outcomes. These translational insights can guide the development of biomarkers for clinical application. Data from thousands of translational-biomarker studies have been deposited in public repositories, enabling reuse. However, data-reuse efforts require considerable time and expertise because transcriptional data are generated using heterogeneous profiling technologies, preprocessed using diverse normalization procedures, and annotated in non-standard ways. To address this problem, we curated 45 publicly available, translational-biomarker datasets from a variety of human diseases. To increase the data's utility, we reprocessed the raw expression data using a uniform computational pipeline, addressed quality-control problems, mapped the clinical annotations to a controlled vocabulary, and prepared consistently structured, analysis-ready data files. These data, along with scripts we used to prepare the data, are available in a public repository. We believe these data will be particularly useful to researchers seeking to perform benchmarking studies—for example, to compare and optimize machine-learning algorithms' ability to predict biomedical outcomes.

High BMI1 mRNA expression in peripheral whole blood is associated with favorable prognosis in advanced non-small cell lung cancer patients

Polycomb group member protein BMI1 is involved in maintaining cell identity, proliferation, differentiation and human oncogenesis. In the present study, we determined BMI1 mRNA expression in whole blood and evaluated the impact of the expression level on the treatment response and survival of 96 advanced NSCLC patients treated with first-line platinum-based chemotherapy. We also determined BMI1 mRNA expression in primary tumors from 22 operable NSCLC patients treated with radical surgery. We found that compared with control subjects, BMI1 mRNA expression in whole blood of advanced NSCLC patients was decreased (P<0.001). Similarly, we observed decreased BMI1 mRNA expression in primary tumors compared to normal lungs from operable NSCLC patients (P=0.001). We found high BMI1 mRNA expression in blood was associated with longer progression-free survival (PFS) (P=0.049) and overall survival (OS) (P=0.012) in advanced NSCLC patients treated with first-line platinum-based chemotherapy. However, no association between the BMI1 mRNA level and response to chemotherapy was found (P=0.21). Multivariate Cox proportional hazards regression analysis showed elevated BMI1 mRNA level in whole blood was an independent prognostic factor for longer PFS (P=0.012) and OS (P<0.001). In conclusion, BMI1 mRNA expression in whole blood might represent a new biomarker for the diagnosis and prognosis of NSCLC.

SUOX is negatively associated with multistep carcinogenesis and proliferation in oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) is the most common malignant tumor in the head and neck region. The aim of this study was to identify the key molecules and to elucidate the molecular mechanisms of OSCC carcinogenesis through a microarray analysis of RNA extracted from normal epithelium, dysplasia, and squamous cell carcinoma components. Out of molecules that showed changes in gene expression in the microarray analysis, we focused on Sulfite oxidase (SUOX), which correlated significantly with carcinogenic process and exhibited a stepwise decrease in expression. The expression of SUOX was evaluated in detail at the protein level using samples from 58 patients with cancer of the tongue, and correlating clinicopathological factors were also comprehensively examined. SUOX expression declined significantly from normal epithelium to dysplasia to squamous cell carcinoma components in line with carcinogenic process. With regard to squamous cell carcinoma, SUOX expression was significantly lower when T classification was high. Our findings indicated that SUOX is negatively associated with the progression and proliferation of tongue cancer, and suggest that SUOX may be a key molecule in tongue tumors.

Peripheral blood leucocytes show differential expression of tumour progression-related genes in colorectal cancer patients who have a postoperative intra-abdominal infection: a prospective matched cohort study

AIM

Anastomotic leak is associated with higher rates of recurrence after surgery for colorectal cancer. However, the mechanisms responsible are unknown. We hypothesized that the infection-induced inflammatory response may induce overexpression of tumour progression-related genes in immune cells. The aim was to investigate the effect of postoperative intra-abdominal infection on the gene expression patterns of peripheral blood leucocytes (PBL) after surgery for colorectal cancer.

METHOD

Prospective matched cohort study. Patients undergoing surgery for colorectal cancer were included. Patients who had anastomotic leak or intra-abdominal abscess were included in the infection group (n = 23) and matched with patients without complications for the control group (n = 23). PBL were isolated from postoperative blood samples. Total RNA was extracted and hybridized to the Affymetrix Human Gene 1.0 ST microarray.

RESULTS

Patients in the infection group displayed 162 upregulated genes and 146 downregulated genes with respect to the control group. Upregulated genes included examples coding for secreted cytokines involved in tumour growth and invasion (S100P, HGF, MMP8, MMP9, PDGFC, IL1R2). Infection also upregulated some proangiogenic genes (CEP55, TRPS1) and downregulated some inhibitors of angiogenesis (MME, ALOX15, CXCL10). Finally, some inhibitors (HP, ORM1, OLFM4, IRAK3) and activators (GNLY, PRF1, FGFBP2) of antitumour immunity were upregulated and downregulated, respectively, suggesting that the inflammatory environment caused by a postoperative infection favours immune evasion mechanisms of the tumour.

CONCLUSION

Analysis of PBL shows differential expression of certain tumour progression-related genes in colorectal cancer patients who have a postoperative intra-abdominal infection, which in turn may promote the growth of residual cancer cells to become recurrent tumours.

Gene expression network analyses in response to air pollution exposures in the trucking industry

BACKGROUND

Exposure to air pollution, including traffic-related pollutants, has been associated with a variety of adverse health outcomes, including increased cardiopulmonary morbidity and mortality, and increased lung cancer risk.

METHODS

To better understand the cellular responses induced by air pollution exposures, we performed genome-wide gene expression microarray analysis using whole blood RNA sampled at three time-points across the work weeks of 63 non-smoking employees at 10 trucking terminals in the northeastern US. We defined genes and gene networks that were differentially activated in response to PM_2.5 (particulate matter ≤ 2.5 microns in diameter) and elemental carbon (EC) and organic carbon (OC).

RESULTS

Multiple transcripts were strongly associated (p_adj < 0.001) with pollutant levels (48, 260, and 49 transcripts for EC, OC, and PM_2.5, respectively), including 63 that were statistically significantly correlated with at least two out of the three exposures. These genes included many that have been implicated in ischemic heart disease, chronic obstructive pulmonary disease (COPD), lung cancer, and other pollution-related illnesses. Through the combination of Gene Set Enrichment Analysis and network analysis (using GeneMANIA), we identified a core set of 25 interrelated genes that were common to all three exposure measures and were differentially expressed in two previous studies assessing gene expression attributable to air pollution. Many of these are members of fundamental cancer-related pathways, including those related to DNA and metal binding, and regulation of apoptosis and also but include genes implicated in chronic heart and lung diseases.

CONCLUSIONS

These data provide a molecular link between the associations of air pollution exposures with health effects.

Identification of gene expression signature for cigarette smoke exposure response--from man to mouse

Gene expression profiling data can be used in toxicology to assess both the level and impact of toxicant exposure, aligned with a vision of 21st century toxicology. Here, we present a whole blood-derived gene signature that can distinguish current smokers from either nonsmokers or former smokers with high specificity and sensitivity. Such a signature that can be measured in a surrogate tissue (whole blood) may help in monitoring smoking exposure as well as discontinuation of exposure when the primarily impacted tissue (e.g., lung) is not readily accessible. The signature consisted of LRRN3, SASH1, PALLD, RGL1, TNFRSF17, CDKN1C, IGJ, RRM2, ID3, SERPING1, and FUCA1. Several members of this signature have been previously described in the context of smoking. The signature translated well across species and could distinguish mice that were exposed to cigarette smoke from ones exposed to air only or had been withdrawn from cigarette smoke exposure. Finally, the small signature of only 11 genes could be converted into a polymerase chain reaction-based assay that could serve as a marker to monitor compliance with a smoking abstinence protocol.

Disease-specific classification using deconvoluted whole blood gene expression

Blood-based biomarker assays have an advantage in being minimally invasive. Diagnostic and prognostic models built on peripheral blood gene expression have been reported for various types of disease. However, most of these studies focused on only one disease type, and failed to address whether the identified gene expression signature is disease-specific or more widely applicable across diseases. We conducted a meta-analysis of 46 whole blood gene expression datasets covering a wide range of diseases and physiological conditions. Our analysis uncovered a striking overlap of signature genes shared by multiple diseases, driven by an underlying common pattern of cell component change, specifically an increase in myeloid cells and decrease in lymphocytes. These observations reveal the necessity of building disease-specific classifiers that can distinguish different disease types as well as normal controls, and highlight the importance of cell component change in deriving blood gene expression based models. We developed a new strategy to develop blood-based disease-specific models by leveraging both cell component changes and cell molecular state changes, and demonstrate its superiority using independent datasets.

Omics for prediction of environmental health effects: Blood leukocyte-based cross-omic profiling reliably predicts diseases associated with tobacco smoking

The utility of blood-based omic profiles for linking environmental exposures to their potential health effects was evaluated in 649 individuals, drawn from the general population, in relation to tobacco smoking, an exposure with well-characterised health effects. Using disease connectivity analysis, we found that the combination of smoking-modified, genome-wide gene (including miRNA) expression and DNA methylation profiles predicts with remarkable reliability most diseases and conditions independently known to be causally associated with smoking (indicative estimates of sensitivity and positive predictive value 94% and 84%, respectively). Bioinformatics analysis reveals the importance of a small number of smoking-modified, master-regulatory genes and suggest a central role for altered ubiquitination. The smoking-induced gene expression profiles overlap significantly with profiles present in blood cells of patients with lung cancer or coronary heart disease, diseases strongly associated with tobacco smoking. These results provide proof-of-principle support to the suggestion that omic profiling in peripheral blood has the potential of identifying early, disease-related perturbations caused by toxic exposures and may be a useful tool in hazard and risk assessment.

Aberrant DNA damage response pathways may predict the outcome of platinum chemotherapy in ovarian cancer

Ovarian carcinoma (OC) is the most lethal gynecological malignancy. Despite the advances in the treatment of OC with combinatorial regimens, including surgery and platinum-based chemotherapy, patients generally exhibit poor prognosis due to high chemotherapy resistance. Herein, we tested the hypothesis that DNA damage response (DDR) pathways are involved in resistance of OC patients to platinum chemotherapy. Selected DDR signals were evaluated in two human ovarian carcinoma cell lines, one sensitive (A2780) and one resistant (A2780/C30) to platinum treatment as well as in peripheral blood mononuclear cells (PBMCs) from OC patients, sensitive (n = 7) or resistant (n = 4) to subsequent chemotherapy. PBMCs from healthy volunteers (n = 9) were studied in parallel. DNA damage was evaluated by immunofluorescence γH2AX staining and comet assay. Higher levels of intrinsic DNA damage were found in A2780 than in A2780/C30 cells. Moreover, the intrinsic DNA damage levels were significantly higher in OC patients relative to healthy volunteers, as well as in platinum-sensitive patients relative to platinum-resistant ones (all P<0.05). Following carboplatin treatment, A2780 cells showed lower DNA repair efficiency than A2780/C30 cells. Also, following carboplatin treatment of PBMCs ex vivo, the DNA repair efficiency was significantly higher in healthy volunteers than in platinum-resistant patients and lowest in platinum-sensitive ones (t_1/2 for loss of γH2AX foci: 2.7±0.5h, 8.8±1.9h and 15.4±3.2h, respectively; using comet assay, t_1/2 of platinum-induced damage repair: 4.8±1.4h, 12.9±1.9h and 21.4±2.6h, respectively; all P<0.03). Additionally, the carboplatin-induced apoptosis rate was higher in A2780 than in A2780/C30 cells. In PBMCs, apoptosis rates were inversely correlated with DNA repair efficiencies of these cells, being significantly higher in platinum-sensitive than in platinum-resistant patients and lowest in healthy volunteers (all P<0.05). We conclude that perturbations of DNA repair pathways as measured in PBMCs from OC patients correlate with the drug sensitivity of these cells and reflect the individualized response to platinum-based chemotherapy.

Expression of MALAT1 in the peripheral whole blood of patients with lung cancer

A blood-based biomarker assay is a non-invasive way to screen that can identify lung cancer at an earlier stage to improve the clinical outcome. MALAT1 is a broadly expressed, long non-coding RNA in human tissues and is overexpressed in numerous human carcinomas. The potential of MALAT1 in the whole blood of lung cancer was evaluated. In the present study, blood samples of patients with lung cancer and healthy volunteers (controls) were recruited and analyzed by quantitative polymerase chain reaction (qPCR) for MALAT1 expression and clinicopathological data. Lung cancer tissues were also analyzed by qPCR. The expression of MALAT1 in the whole blood of lung cancer was lower compared to the control. The area under the receiver operator curve was 0.718 (P<0.001). Relatively, the expression of MALAT1 was stronger in the whole blood of lung cancer with metastasis compared to non-metastasis. Additionally, the whole blood with bone or brain metastasis exhibited a higher expression of MALAT1 compared to the blood with lymph node or pleura metastasis. Subsequently, a lower expression of MALAT1 was detected in metastatic lymph node tissues than that of the carcinoma in situ of the lung. Taken together, these results indicate that MALAT1 as a biomarker to screen lung cancer may represent a host response to lung cancer.

Translating the transcriptome into tools for the early detection and prevention of lung cancer

Despite advances in the management of lung cancer, this disease remains a significant global health burden with survival rates that have not significantly improved in decades. The mortality reduction achieved by low-dose helical CT (LDCT) screening of select high-risk patients is challenged by the high false positive rate of this screening modality and the potential for morbidity associated with follow-up diagnostic evaluation in patients with high risk for iatrogenic complications. The diagnostic dilemma of the indeterminate nodule incidentally identified on diagnostic or screening CT has created a need for reliable biomarkers capable of distinguishing benign from malignant disease. Furthermore, there is an urgent need to develop molecular biomarkers to supplement clinical risk models in order to identify patients at highest risk for having an early stage lung cancer that may derive the greatest benefit from LDCT screening, as well as identifying patients at high-risk for developing lung cancer that may be candidates for emerging chemopreventive strategies. Evolving bioinformatic techniques and the application of these algorithms to analyse the transcriptomic changes associated with lung cancer promise translational discoveries that can bridge these large clinical gaps. The identification of lung cancer associated transcriptomic alterations in readily accessible tissue sampling sites offers the potential to develop early diagnostic and risk stratification strategies applicable to large populations. This review summarises the challenges associated with the early detection, screening and chemoprevention of lung cancer with an emphasis on how genomic information encapsulated by the transcriptome can facilitate future innovations in these clinical settings.

Identification of module biomarkers from the dysregulated ceRNA–ceRNA interaction network in lung adenocarcinoma

The dysregulated ceRNA–ceRNA interaction network in lung adenocarcinoma.

Similar source of differential blood mRNAs in lung cancer and pulmonary inflammatory diseases: calls for improved strategy for identifying cancer-specific biomarkers

BACKGROUND

Many studies try to identify cancer diagnostic biomarkers by comparing peripheral whole blood (PWB) of cancer samples and healthy controls, explicitly or implicitly assuming that such biomarkers are potential candidate biomarkers for distinguishing cancer from nonmalignant inflammation-associated diseases.

METHODS

Multiple PWB gene expression profiles for lung cancer/inflammation-associated pulmonary diseases were used for differential mRNAs identification and comparison and for proportion estimation of PWB cell subtypes.

RESULTS

The differentially expressed genes (DE genes) between lung cancer/inflammation-associated pulmonary patients and healthy controls were reproducibly identified in different datasets. For these DE genes observed in lung cancer/inflammation-associated pulmonary diseases, more than 90.2% were differentially expressed between myeloid cells and lymphoid cells, with at least 96.8% having consistent directions of regulation (up- or down-regulations) in myeloid cells compared to lymphoid cells, explainable by the shifted populations of PWB cell subtypes under the disease conditions. The comparison of DE genes for lung cancer and inflammation-associated pulmonary diseases showed that the overlapping genes were 100% consistent in the sense of direction of regulation.

CONCLUSIONS

The differential blood mRNAs observed in lung cancer and in inflammation-associated pulmonary diseases were similar, both mainly reflecting the difference between myeloid cells and lymphoid cells predominantly determined by PWB cell population shifts. Thus, the strategy of comparing cancer with healthy controls may provide little information of the ability of the identified candidate biomarkers in discriminating cancer from inflammation-associated pulmonary diseases.

Using logistic regression to improve the prognostic value of microarray gene expression data sets: application to early-stage squamous cell carcinoma of the lung and triple negative breast carcinoma

BACKGROUND

Numerous microarray-based prognostic gene expression signatures of primary neoplasms have been published but often with little concurrence between studies, thus limiting their clinical utility. We describe a methodology using logistic regression, which circumvents limitations of conventional Kaplan Meier analysis. We applied this approach to a thrice-analyzed and published squamous cell carcinoma (SQCC) of the lung data set, with the objective of identifying gene expressions predictive of early death versus long survival in early-stage disease. A similar analysis was applied to a data set of triple negative breast carcinoma cases, which present similar clinical challenges.

METHODS

Important to our approach is the selection of homogenous patient groups for comparison. In the lung study, we selected two groups (including only stages I and II), equal in size, of earliest deaths and longest survivors. Genes varying at least four-fold were tested by logistic regression for accuracy of prediction (area under a ROC plot). The gene list was refined by applying two sliding-window analyses and by validations using a leave-one-out approach and model building with validation subsets. In the breast study, a similar logistic regression analysis was used after selecting appropriate cases for comparison.

RESULTS

A total of 8594 variable genes were tested for accuracy in predicting earliest deaths versus longest survivors in SQCC. After applying the two sliding window and the leave-one-out analyses, 24 prognostic genes were identified; most of them were B-cell related. When the same data set of stage I and II cases was analyzed using a conventional Kaplan Meier (KM) approach, we identified fewer immune-related genes among the most statistically significant hits; when stage III cases were included, most of the prognostic genes were missed. Interestingly, logistic regression analysis of the breast cancer data set identified many immune-related genes predictive of clinical outcome.

CONCLUSIONS

Stratification of cases based on clinical data, careful selection of two groups for comparison, and the application of logistic regression analysis substantially improved predictive accuracy in comparison to conventional KM approaches. B cell-related genes dominated the list of prognostic genes in early stage SQCC of the lung and triple negative breast cancer.

Progressive changes in chromatin structure and DNA damage response signals in bone marrow and peripheral blood during myelomagenesis

The molecular pathways implicated in multiple myeloma (MM) development are rather unknown. We studied epigenetic and DNA damage response (DDR) signals at selected model loci (N-ras, p53, d-globin) in bone marrow plasma cells and peripheral blood mononuclear cells (PBMCs) from patients with monoclonal gammopathy of undetermined significance (MGUS; n=20), smoldering/asymptomatic MM (SMM; n=29) and MM (n=18), as well as in healthy control-derived PBMCs (n=20). In both tissues analyzed, a progressive, significant increase in the looseness of local chromatin structure, gene expression levels and DNA repair efficiency from MGUS to SMM and finally to MM was observed (all P<0.002). Following ex vivo treatment with melphalan, a gradual suppression of the apoptotic pathway occurred in samples collected at different stages of myelomagenesis, with the severity and duration of the inhibition of RNA synthesis, p53 phosphorylation at serine15 and induction of apoptosis being higher in MGUS than SMM and lowest in MM patients (all P<0.0103). Interestingly, for all endpoints analyzed, a strong correlation between plasma cells and corresponding PBMCs was observed (all P<0.0003). We conclude that progressive changes in chromatin structure, transcriptional activity and DDR pathways during myelomagenesis occur in malignant plasma cells and that these changes are also reflected in PBMCs.

Analysis of the transcriptome in molecular epidemiology studies

The human transcriptome is complex, comprising multiple transcript types, mostly in the form of non-coding RNA (ncRNA). The majority of ncRNA is of the long form (lncRNA, ≥ 200 bp), which plays an important role in gene regulation through multiple mechanisms including epigenetics, chromatin modification, control of transcription factor binding, and regulation of alternative splicing. Both mRNA and ncRNA exhibit additional variability in the form of alternative splicing and RNA editing. All aspects of the human transcriptome can potentially be dysregulated by environmental exposures. Next-generation RNA sequencing (RNA-Seq) is the best available methodology to measure this although it has limitations, including experimental bias. The third phase of the MicroArray Quality Control Consortium project (MAQC-III), also called Sequencing Quality Control (SeQC), aims to address these limitations through standardization of experimental and bioinformatic methodologies. A limited number of toxicogenomic studies have been conducted to date using RNA-Seq. This review describes the complexity of the human transcriptome, the application of transcriptomics by RNA-Seq or microarray in molecular epidemiology studies, and limitations of these approaches including the type of cell or tissue analyzed, experimental variation, and confounding. By using good study designs with precise, individual exposure measurements, sufficient power and incorporation of phenotypic anchors, studies in human populations can identify biomarkers of exposure and/or early effect and elucidate mechanisms of action underlying associated diseases, even at low doses. Analysis of datasets at the pathway level can compensate for some of the limitations of RNA-Seq and, as more datasets become available, will increasingly elucidate the exposure-disease continuum.

Making sense of OMICS data in population-based environmental health studies

Although experience from the application of OMICS technologies in population-based environmental health studies is still relatively limited, the accumulated evidence shows that it can allow the identification of features (genes, proteins, and metabolites), or sets of such features, which are targeted by particular exposures or correlate with disease risk. Such features or profiles can therefore serve as biomarkers of exposure or disease risk. Blood-based OMIC profiles appear to reflect to some extent events occurring in target tissues and are associated with toxicity or disease and therefore have the potential to facilitate the elucidation of exposure-disease relationships. Further progress in this direction requires better understanding of the significance of exposure-induced network perturbations for disease initiation and progression and the development of a framework that combines agnostic searches with the utilization of prior knowledge, taking account of particular elements which characterize the structure and evolution of complex systems and brings in principles of systems biology.

Bridging the clinical gaps: genetic, epigenetic and transcriptomic biomarkers for the early detection of lung cancer in the post-National Lung Screening Trial era

Lung cancer is the leading cause of cancer death worldwide in part due to our inability to identify which smokers are at highest risk and the lack of effective tools to detect the disease at its earliest and potentially curable stage. Recent results from the National Lung Screening Trial have shown that annual screening of high-risk smokers with low-dose helical computed tomography of the chest can reduce lung cancer mortality. However, molecular biomarkers are needed to identify which current and former smokers would benefit most from annual computed tomography scan screening in order to reduce the costs and morbidity associated with this procedure. Additionally, there is an urgent clinical need to develop biomarkers that can distinguish benign from malignant lesions found on computed tomography of the chest given its very high false positive rate. This review highlights recent genetic, transcriptomic and epigenomic biomarkers that are emerging as tools for the early detection of lung cancer both in the diagnostic and screening setting.

TGF-β signaling in myeloid cells is required for tumor metastasis

TGF-β is overexpressed in advanced human cancers. It correlates with metastasis and poor prognosis. However, TGF-β functions as both a tumor suppressor and a tumor promoter. Here, we report for the first time that genetic deletion of Tgfbr2 specifically in myeloid cells (Tgfbr2(MyeKO)) significantly inhibited tumor metastasis. Reconstitution of tumor-bearing mice with Tgfbr2(MyeKO) bone marrow recapitulated the inhibited metastasis phenotype. This effect is mediated through decreased production of type II cytokines, TGF-β1, arginase 1, and inducible nitric oxide synthase, which promoted IFN-γ production and improved systemic immunity. Depletion of CD8 T cells diminished the metastasis defect in the Tgfbr2(MyeKO) mice. Consistent with animal studies, myeloid cells from patients with advanced-stage cancer showed increased TGF-β receptor II expression. Our studies show that myeloid-specific TGF-β signaling is an essential component of the metastasis-promoting puzzle of TGF-β. This is in contrast to the previously reported tumor-suppressing phenotypes in fibroblasts, epithelial cells, and T cells.

Gene expression analysis of peripheral blood cells reveals Toll-like receptor pathway deregulation in colorectal cancer

Colorectal cancer is the leading cause of cancer-related deaths worldwide. The disease is curable when detected at an early stage. However, the compliance rate with current screening recommendations remains poor. An accurate, minimally invasive blood test that has the potential for greater patient compliance would be a welcome addition to the current methods. Recent data have shown that gene expression profile of peripheral blood cells can reflect disease states and thus have diagnostic value. In this study, genome-wide gene expression profiling of peripheral blood cells from 20 healthy controls and 20 colorectal cancer patients were performed using PAXgene™ technology and Affymetrix GeneChip® microarrays. We identified a list of 1,469 genes that were differentially expressed between the healthy controls and cancer patients. Gene annotation and functional enrichment analysis revealed that those genes are mainly related to immune functions. Particularly, a set of genes belonging to the Toll-Like Receptor pathways were up-regulated in the colorectal cancer patients. These findings provide a new understanding of blood gene expression profile in colorectal cancer. Our result may serve as the basis for further development of blood biomarkers for the diagnosis and treatment of colorectal cancer.

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.

Expression signature in peripheral blood cells for molecular diagnosis of head and neck squamous cell carcinoma

Patients with head and neck squamous cell carcinoma (HNSCC) have a poor prognosis due to the development of locoregional recurrences, distant metastases, and second primary tumors. There is an urgent need for biomarkers that enable detection and monitoring of the disease to provide adequate therapeutic strategies. In this study, we have investigated markers in peripheral blood cells (PBC) of 28 HNSCC patients who underwent surgery by means of expression profiling. Our hypothesis is that nucleated blood cells circulate continuously, also pass the tumor, and change their expression profile in response to tumor cell factors. For comparison, we enrolled a control group of 11 patients who underwent surgery in the head and neck region for non-HNSCC reasons. A set of 2949 genes was found to be statistically different between the groups (P < 0.05, false discovery rate-corrected) and the most prominently different pathways were EIF2, EIF4, and mTOR signaling. These preliminary results are promising and warrant further studies on the definitive role of PBC gene expression as a biomarker for HNSCC detection and monitoring.

GSTM1 and GSTT1 copy numbers and mRNA expression in lung cancer

Large fractions of the human population do not express GSTM1 and GSTT1 (GSTM1/T1) enzymes because of deletions in these genes. These variations affect xenobiotic metabolism and have been evaluated in relation to lung cancer risk, mostly based on null/present gene models. We measured GSTM1/T1 heterozygous deletions, not tested in genome-wide association studies, in 2,120 controls and 2,100 cases from the Environment And Genetics in Lung cancer Etiology (EAGLE) study. We evaluated their effect on mRNA expression on lung tissue and peripheral blood samples and their association with lung cancer risk overall and by histology types. We tested the null/present, dominant, and additive models using logistic regression. Cigarette smoking and gender were studied as possible modifiers. Gene expression from blood and lung tissue cells was strongly down regulated in subjects carrying GSTM1/T1 deletions by both trend and dominant models (P < 0.001). In contrast to the null/present model, analyses distinguishing subjects with 0, 1, or 2 GSTM1/T1 deletions revealed several associations. There was a decreased lung cancer risk in never-smokers (OR = 0.44; 95%CI = 0.23-0.82; P = 0.01) and women (OR = 0.50; 95%CI = 0.28-0.90; P = 0.02) carrying 1 or 2 GSTM1 deletions. Analogously, male smokers had an increased risk (OR = 1.13; 95%CI = 1.0-1.28; P = 0.05) and women a decreased risk (OR = 0.78; 95%CI = 0.63-0.97; P = 0.02) for increasing GSTT1 deletions. The corresponding gene smoking and gene-gender interactions were significant (P < 0.05). Our results suggest that decreased activity of GSTM1/T1 enzymes elevates lung cancer risk in male smokers, likely due to impaired carcinogens' detoxification. A protective effect of the same mutations may be operative in never-smokers and women, possibly because of reduced activity of other genotoxic chemicals.