BAP1 is a novel regulator of HIF-1α.

BAP1 is a powerful tumor suppressor gene characterized by haplo insufficiency. Individuals carrying germline BAP1 mutations often develop mesothelioma, an aggressive malignancy of the serosal layers covering the lungs, pericardium, and abdominal cavity. Intriguingly, mesotheliomas developing in carriers of germline BAP1 mutations are less aggressive, and these patients have significantly improved survival. We investigated the apparent paradox of a tumor suppressor gene that, when mutated, causes less aggressive mesotheliomas. We discovered that mesothelioma biopsies with biallelic BAP1 mutations showed loss of nuclear HIF-1α staining. We demonstrated that during hypoxia, BAP1 binds, deubiquitylates, and stabilizes HIF-1α, the master regulator of the hypoxia response and tumor cell invasion. Moreover, primary cells from individuals carrying germline BAP1 mutations and primary cells in which BAP1 was silenced using siRNA had reduced HIF-1α protein levels in hypoxia. Computational modeling and co-immunoprecipitation experiments revealed that mutations of BAP1 residues I675, F678, I679, and L691 -encompassing the C-terminal domain-nuclear localization signal- to A, abolished the interaction with HIF-1α. We found that BAP1 binds to the N-terminal region of HIF-1α, where HIF-1α binds DNA and dimerizes with HIF-1ß forming the heterodimeric transactivating complex HIF. Our data identify BAP1 as a key positive regulator of HIF-1α in hypoxia. We propose that the significant reduction of HIF-1α activity in mesothelioma cells carrying biallelic BAP1 mutations, accompanied by the significant reduction of HIF-1α activity in hypoxic tissues containing germline BAP1 mutations, contributes to the reduced aggressiveness and improved survival of mesotheliomas developing in carriers of germline BAP1 mutations.

High-density array-CGH with targeted NGS unmask multiple noncontiguous minute deletions on chromosome 3p21 in mesothelioma.

We used a custom-made comparative genomic hybridization array (aCGH; average probe interval 254 bp) to screen 33 malignant mesothelioma (MM) biopsies for somatic copy number loss throughout the 3p21 region (10.7 Mb) that harbors 251 genes, including BRCA1 (breast cancer 1)-associated protein 1 (BAP1), the most commonly mutated gene in MM. We identified frequent minute biallelic deletions (<3 kb) in 46 of 251 genes: four were cancer-associated genes: SETD2 (SET domain-containing protein 2) (7 of 33), BAP1 (8 of 33), PBRM1 (polybromo 1) (3 of 33), and SMARCC1 (switch/sucrose nonfermentable- SWI/SNF-related, matrix-associated, actin-dependent regulator of chromatin, subfamily c, member 1) (2 of 33). These four genes were further investigated by targeted next-generation sequencing (tNGS), which revealed sequence-level mutations causing biallelic inactivation. Combined high-density aCGH and tNGS revealed biallelic gene inactivation in SETD2 (9 of 33, 27%), BAP1 (16 of 33, 48%), PBRM1 (5 of 33, 15%), and SMARCC1 (2 of 33, 6%). The incidence of genetic alterations detected is much higher than reported in the literature because minute deletions are not detected by NGS or commercial aCGH. Many of these minute deletions were not contiguous, but rather alternated with segments showing oscillating copy number changes along the 3p21 region. In summary, we found that in MM: (i) multiple minute simultaneous biallelic deletions are frequent in chromosome 3p21, where they occur as distinct events involving multiple genes; (ii) in addition to BAP1, mutations of SETD2, PBRM1, and SMARCC1 are frequent in MM; and (iii) our results suggest that high-density aCGH combined with tNGS provides a more precise estimate of the frequency and types of genes inactivated in human cancer than approaches based exclusively on NGS strategy.

Summarizing performance for genome scale measurement of miRNA: reference samples and metrics.

BACKGROUND: The potential utility of microRNA as biomarkers for early detection of cancer and other diseases is being investigated with genome-scale profiling of differentially expressed microRNA. Processes for measurement assurance are critical components of genome-scale measurements. Here, we evaluated the utility of a set of total RNA samples, designed with between-sample differences in the relative abundance of miRNAs, as process controls. RESULTS: Three pure total human RNA samples (brain, liver, and placenta) and two different mixtures of these components were evaluated as measurement assurance control samples on multiple measurement systems at multiple sites and over multiple rounds. In silico modeling of mixtures provided benchmark values for comparison with physical mixtures. Biomarker development laboratories using next-generation sequencing (NGS) or genome-scale hybridization assays participated in the study and returned data from the samples using their routine workflows. Multiplexed and single assay reverse-transcription PCR (RT-PCR) was used to confirm in silico predicted sample differences. Data visualizations and summary metrics for genome-scale miRNA profiling assessment were developed using this dataset, and a range of performance was observed. These metrics have been incorporated into an online data analysis pipeline and provide a convenient dashboard view of results from experiments following the described design. The website also serves as a repository for the accumulation of performance values providing new participants in the project an opportunity to learn what may be achievable with similar measurement processes. CONCLUSIONS: The set of reference samples used in this study provides benchmark values suitable for assessing genome-scale miRNA profiling processes. Incorporation of these metrics into an online resource allows laboratories to periodically evaluate their performance and assess any changes introduced into their measurement process.

Fibulin-3 as a blood and effusion biomarker for pleural mesothelioma.

BACKGROUND: New biomarkers are needed to detect pleural mesothelioma at an earlier stage and to individualize treatment strategies. We investigated whether fibulin-3 in plasma and pleural effusions could meet sensitivity and specificity criteria for a robust biomarker. METHODS: We measured fibulin-3 levels in plasma (from 92 patients with mesothelioma, 136 asbestos-exposed persons without cancer, 93 patients with effusions not due to mesothelioma, and 43 healthy controls), effusions (from 74 patients with mesothelioma, 39 with benign effusions, and 54 with malignant effusions not due to mesothelioma), or both. A blinded validation was subsequently performed. Tumor tissue was examined for fibulin-3 by immunohistochemical analysis, and levels of fibulin-3 in plasma and effusions were measured with an enzyme-linked immunosorbent assay. RESULTS: Plasma fibulin-3 levels did not vary according to age, sex, duration of asbestos exposure, or degree of radiographic changes and were significantly higher in patients with pleural mesothelioma (105±7 ng per milliliter in the Detroit cohort and 113±8 ng per milliliter in the New York cohort) than in asbestos-exposed persons without mesothelioma (14±1 ng per milliliter and 24±1 ng per milliliter, respectively; P<0.001). Effusion fibulin-3 levels were significantly higher in patients with pleural mesothelioma (694±37 ng per milliliter in the Detroit cohort and 636±92 ng per milliliter in the New York cohort) than in patients with effusions not due to mesothelioma (212±25 and 151±23 ng per milliliter, respectively; P<0.001). Fibulin-3 preferentially stained tumor cells in 26 of 26 samples. In an overall comparison of patients with and those without mesothelioma, the receiver-operating-characteristic curve for plasma fibulin-3 levels had a sensitivity of 96.7% and a specificity of 95.5% at a cutoff value of 52.8 ng of fibulin-3 per milliliter. In a comparison of patients with early-stage mesothelioma with asbestos-exposed persons, the sensitivity was 100% and the specificity was 94.1% at a cutoff value of 46.0 ng of fibulin-3 per milliliter. Blinded validation revealed an area under the curve of 0.87 for plasma specimens from 96 asbestos-exposed persons as compared with 48 patients with mesothelioma. CONCLUSIONS: Plasma fibulin-3 levels can distinguish healthy persons with exposure to asbestos from patients with mesothelioma. In conjunction with effusion fibulin-3 levels, plasma fibulin-3 levels can further differentiate mesothelioma effusions from other malignant and benign effusions. (Funded by the Early Detection Research Network, National Institutes of Health, and others.).

Lung microbial and host genomic signatures as predictors of prognosis in early-stage adenocarcinoma.

BACKGROUND: Risk of early-stage lung adenocarcinoma (LUAD) recurrence after surgical resection is significant, and post-recurrence median survival is approximately two years. Currently there are no commercially available biomarkers that predict recurrence. Here, we investigated whether microbial and host genomic signatures in the lung can predict recurrence. METHODS: In 91 early-stage (Stage IA/IB) LUAD-patients with extensive follow-up, we used 16s rRNA gene sequencing and host RNA-sequencing to map the microbial and host transcriptomic landscape in tumor and adjacent unaffected lung samples. RESULTS: 23 out of 91 subjects had tumor recurrence over 5-year period. In tumor samples, LUAD recurrence was associated with enrichment with Dialister, Prevotella, while in unaffected lung, recurrence was associated with enrichment with Sphyngomonas and Alloiococcus. The strengths of the associations between microbial and host genomic signatures with LUAD recurrence were greater in adjacent unaffected lung samples than in the primary tumor. Among microbial-host features in the unaffected lung samples associated with recurrence, enrichment with Stenotrophomonas geniculata and Chryseobacterium were positively correlated with upregulation of IL-2, IL-3, IL-17, EGFR, HIF-1 signaling pathways among the host transcriptome. In tumor samples, enrichment with Veillonellaceae Dialister, Ruminococcacea, Haemophilus Influenza, and Neisseria were positively correlated with upregulation of IL-1, IL-6, IL17, IFN, and Tryptophan metabolism pathways. CONCLUSIONS: Overall, modeling suggested that a combined microbial/transcriptome approach using unaffected lung samples had the best biomarker performance (AUC=0.83). IMPACT: This study suggests that LUAD recurrence is associated with distinct pathophysiological mechanisms of microbial-host interactions in the unaffected lung rather than those present in the resected tumor.

Programmed necrosis induced by asbestos in human mesothelial cells causes high-mobility group box 1 protein release and resultant inflammation.

Asbestos carcinogenesis has been linked to the release of cytokines and mutagenic reactive oxygen species (ROS) from inflammatory cells. Asbestos is cytotoxic to human mesothelial cells (HM), which appears counterintuitive for a carcinogen. We show that asbestos-induced HM cell death is a regulated form of necrosis that links to carcinogenesis. Asbestos-exposed HM activate poly(ADP-ribose) polymerase, secrete H(2)O(2), deplete ATP, and translocate high-mobility group box 1 protein (HMGB1) from the nucleus to the cytoplasm, and into the extracellular space. The release of HMGB1 induces macrophages to secrete TNF-alpha, which protects HM from asbestos-induced cell death and triggers a chronic inflammatory response; both favor HM transformation. In both mice and hamsters injected with asbestos, HMGB1 was specifically detected in the nuclei, cytoplasm, and extracellular space of mesothelial and inflammatory cells around asbestos deposits. TNF-alpha was coexpressed in the same areas. HMGB1 levels in asbestos-exposed individuals were significantly higher than in nonexposed controls (P < 0.0001). Our findings identify the release of HMGB1 as a critical initial step in the pathogenesis of asbestos-related disease, and provide mechanistic links between asbestos-induced cell death, chronic inflammation, and carcinogenesis. Chemopreventive approaches aimed at inhibiting the chronic inflammatory response, and especially blocking HMGB1, may decrease the risk of malignant mesothelioma among asbestos-exposed cohorts.

Recurrence prediction of lung adenocarcinoma using an immune gene expression and clinical data trained and validated support vector machine classifier.

Background: Immune microenvironment plays a critical role in cancer from onset to relapse. Machine learning (ML) algorithm can facilitate the analysis of lab and clinical data to predict lung cancer recurrence. Prompt detection and intervention are crucial for long-term survival in lung cancer relapse. Our study aimed to evaluate the clinical and genomic prognosticators for lung cancer recurrence by comparing the predictive accuracy of four ML models. Methods: A total of 41 early-stage lung cancer patients who underwent surgery between June 2007 and October 2014 at New York University Langone Medical Center were included (with recurrence, n=16; without recurrence, n=25). All patients had tumor tissue and buffy coat collected at the time of resection. The CIBERSORT algorithm quantified tumor-infiltrating immune cells (TIICs). Protein-protein interaction (PPI) network and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted to unearth potential molecular drivers of tumor progression. The data was split into training (75%) and validation sets (25%). Ensemble linear kernel support vector machine (SVM) ML models were developed using optimized clinical and genomic features to predict tumor recurrence. Results: Activated natural killer (NK) cells, M0 macrophages, and M1 macrophages showed a positive correlation with progression. Conversely, T CD4+ memory resting cells were negatively correlated. In the PPI network, TNF and IL6 emerged as prominent hub genes. Prediction models integrating clinicopathological prognostic factors, tumor gene expression (45 genes), and buffy coat gene expression (47 genes) yielded varying receiver operating characteristic (ROC)-area under the curves (AUCs): 62.7%, 65.4%, and 59.7% in the training set, 58.3%, 83.3%, and 75.0% in the validation set, respectively. Notably, merging gene expression with clinical data in a linear SVM model led to a significant accuracy boost, with an AUC of 92.0% in training and 91.7% in validation. Conclusions: Using ML algorithm, immune gene expression data from tumor tissue and buffy coat may enhance the precision of lung cancer recurrence prediction.

Extracorporeal Membrane Oxygenation Impact on Host Transcriptomic Response in Severe Coronavirus.

Background: Evidence suggests that patients critically ill with COVID-19 have a dysregulated host immune response that contributes to end-organ damage. Extracorporeal membrane oxygenation (ECMO) has been used in this population with varying degrees of success. This study was performed to evaluate the impact of ECMO on the host immunotranscriptomic response in these patients. Methods: Eleven patients critically ill with COVID-19 requiring ECMO underwent an analysis of cytokines and immunotranscriptomic pathways before ECMO (T1), after ECMO for 24 hours (T2), and 2 hours after ECMO decannulation (T3). A Multiplex Human Cytokine panel was used to identify cytokine changes, and immunotranscriptomic changes in peripheral leukocytes were evaluated by PAXgene and NanoString nCounter. Results: Differential gene expression of 11 host immune genes was noted at T2 compared with T1. The most significant genes were MD2 and MRC1, which code for binding ligands for the activation of toll-like receptors 2 and 4. Reactome analyses of differential gene expression demonstrated an impact on many of the body's most important immune inflammatory pathways. Conclusions: These findings suggest a temporal impact of ECMO on the host immunotranscriptomic response in patients critically ill with COVID-19.

Pleural fluid microbiota as a biomarker for malignancy and prognosis.

Malignant pleural effusions (MPE) complicate malignancies and portend worse outcomes. MPE is comprised of various components, including immune cells, cancer cells, and cell-free DNA/RNA. There have been investigations into using these components to diagnose and prognosticate MPE. We hypothesize that the microbiome of MPE is unique and may be associated with diagnosis and prognosis. We compared the microbiota of MPE against microbiota of pleural effusions from non-malignant and paramalignant states. We collected a total of 165 pleural fluid samples from 165 subjects; Benign (n = 16), Paramalignant (n = 21), MPE-Lung (n = 57), MPE-Other (n = 22), and Mesothelioma (n = 49). We performed high throughput 16S rRNA gene sequencing on pleural fluid samples and controls. We showed that there are compositional differences among pleural effusions related to non-malignant, paramalignant, and malignant disease. Furthermore, we showed differential enrichment of bacterial taxa within MPE depending on the site of primary malignancy. Pleural fluid of MPE-Lung and Mesothelioma were associated with enrichment with oral and gut bacteria that are commonly thought to be commensals, including Rickettsiella, Ruminococcus, Enterococcus, and Lactobacillales. Mortality in MPE-Lung is associated with enrichment in Methylobacterium, Blattabacterium, and Deinococcus. These observations lay the groundwork for future studies that explore host-microbiome interactions and their influence on carcinogenesis.

Inflammation in the tumor-adjacent lung as a predictor of clinical outcome in lung adenocarcinoma.

Approximately 30% of early-stage lung adenocarcinoma patients present with disease progression after successful surgical resection. Despite efforts of mapping the genetic landscape, there has been limited success in discovering predictive biomarkers of disease outcomes. Here we performed a systematic multi-omic assessment of 143 tumors and matched tumor-adjacent, histologically-normal lung tissue with long-term patient follow-up. Through histologic, mutational, and transcriptomic profiling of tumor and adjacent-normal tissue, we identified an inflammatory gene signature in tumor-adjacent tissue as the strongest clinical predictor of disease progression. Single-cell transcriptomic analysis demonstrated the progression-associated inflammatory signature was expressed in both immune and non-immune cells, and cell type-specific profiling in monocytes further improved outcome predictions. Additional analyses of tumor-adjacent transcriptomic data from The Cancer Genome Atlas validated the association of the inflammatory signature with worse outcomes across cancers. Collectively, our study suggests that molecular profiling of tumor-adjacent tissue can identify patients at high risk for disease progression.

Pig-to-human heart xenotransplantation in two recently deceased human recipients.

Genetically modified xenografts are one of the most promising solutions to the discrepancy between the numbers of available human organs for transplantation and potential recipients. To date, a porcine heart has been implanted into only one human recipient. Here, using 10-gene-edited pigs, we transplanted porcine hearts into two brain-dead human recipients and monitored xenograft function, hemodynamics and systemic responses over the course of 66 hours. Although both xenografts demonstrated excellent cardiac function immediately after transplantation and continued to function for the duration of the study, cardiac function declined postoperatively in one case, attributed to a size mismatch between the donor pig and the recipient. For both hearts, we confirmed transgene expression and found no evidence of cellular or antibody-mediated rejection, as assessed using histology, flow cytometry and a cytotoxic crossmatch assay. Moreover, we found no evidence of zoonotic transmission from the donor pigs to the human recipients. While substantial additional work will be needed to advance this technology to human trials, these results indicate that pig-to-human heart xenotransplantation can be performed successfully without hyperacute rejection or zoonosis.

The lung microbiome, peripheral gene expression, and recurrence-free survival after resection of stage II non-small cell lung cancer.

BACKGROUND: Cancer recurrence after tumor resection in early-stage non-small cell lung cancer (NSCLC) is common, yet difficult to predict. The lung microbiota and systemic immunity may be important modulators of risk for lung cancer recurrence, yet biomarkers from the lung microbiome and peripheral immune environment are understudied. Such markers may hold promise for prediction as well as improved etiologic understanding of lung cancer recurrence. METHODS: In tumor and distant normal lung samples from 46 stage II NSCLC patients with curative resection (39 tumor samples, 41 normal lung samples), we conducted 16S rRNA gene sequencing. We also measured peripheral blood immune gene expression with nanoString®. We examined associations of lung microbiota and peripheral gene expression with recurrence-free survival (RFS) and disease-free survival (DFS) using 500 × 10-fold cross-validated elastic-net penalized Cox regression, and examined predictive accuracy using time-dependent receiver operating characteristic (ROC) curves. RESULTS: Over a median of 4.8 years of follow-up (range 0.2-12.2 years), 43% of patients experienced a recurrence, and 50% died. In normal lung tissue, a higher abundance of classes Bacteroidia and Clostridia, and orders Bacteroidales and Clostridiales, were associated with worse RFS, while a higher abundance of classes Alphaproteobacteria and Betaproteobacteria, and orders Burkholderiales and Neisseriales, were associated with better RFS. In tumor tissue, a higher abundance of orders Actinomycetales and Pseudomonadales were associated with worse DFS. Among these taxa, normal lung Clostridiales and Bacteroidales were also related to worse survival in a previous small pilot study and an additional independent validation cohort. In peripheral blood, higher expression of genes TAP1, TAPBP, CSF2RB, and IFITM2 were associated with better DFS. Analysis of ROC curves revealed that lung microbiome and peripheral gene expression biomarkers provided significant additional recurrence risk discrimination over standard demographic and clinical covariates, with microbiome biomarkers contributing more to short-term (1-year) prediction and gene biomarkers contributing to longer-term (2-5-year) prediction. CONCLUSIONS: We identified compelling biomarkers in under-explored data types, the lung microbiome, and peripheral blood gene expression, which may improve risk prediction of recurrence in early-stage NSCLC patients. These findings will require validation in a larger cohort.

The extracellular matrix protein fibulin-3/EFEMP1 promotes pleural mesothelioma growth by activation of PI3K/Akt signaling.

Malignant pleural mesothelioma (MPM) is an aggressive tumor with poor prognosis and limited therapeutic options. The extracellular matrix protein fibulin-3/EFEMP1 accumulates in the pleural effusions of MPM patients and has been proposed as a prognostic biomarker of these tumors. However, it is entirely unknown whether fibulin-3 plays a functional role on MPM growth and progression. Here, we demonstrate that fibulin-3 is upregulated in MPM tissue, promotes the malignant behavior of MPM cells, and can be targeted to reduce tumor progression. Overexpression of fibulin-3 increased the viability, clonogenic capacity and invasion of mesothelial cells, whereas fibulin-3 knockdown decreased these phenotypic traits as well as chemoresistance in MPM cells. At the molecular level, fibulin-3 activated PI3K/Akt signaling and increased the expression of a PI3K-dependent gene signature associated with cell adhesion, motility, and invasion. These pro-tumoral effects of fibulin-3 on MPM cells were disrupted by PI3K inhibition as well as by a novel, function-blocking, anti-fibulin-3 chimeric antibody. Anti-fibulin-3 antibody therapy tested in two orthotopic models of MPM inhibited fibulin-3 signaling, resulting in decreased tumor cell proliferation, reduced tumor growth, and extended animal survival. Taken together, these results demonstrate for the first time that fibulin-3 is not only a prognostic factor of MPM but also a relevant molecular target in these tumors. Further development of anti-fibulin-3 approaches are proposed to increase early detection and therapeutic impact against MPM.

Pro-tumorigenic effects of miR-31 loss in mesothelioma.

The human genome encodes several hundred microRNA (miRNA) genes that produce small (21-23n) single strand regulatory RNA molecules. Although abnormal expression of miRNAs has been linked to cancer progression, the mechanisms of this dysregulation are poorly understood. Malignant mesothelioma (MM) of pleura is an aggressive and highly lethal cancer resistant to conventional therapies. We and others previously linked loss of the 9p21.3 chromosome in MM with short time to tumor recurrence. In this study, we report that MM cell lines derived from patients with more aggressive disease fail to express miR-31, a microRNA recently linked with suppression of breast cancer metastases. We further demonstrate that this loss is due to homozygous deletion of the miR-31-encoding gene that resides in 9p21.3. Functional assessment of miR-31 activity revealed its ability to inhibit proliferation, migration, invasion, and clonogenicity of MM cells. Re-introduction of miR-31 suppressed the cell cycle and inhibited expression of multiple factors involved in cooperative maintenance of DNA replication and cell cycle progression, including pro-survival phosphatase PPP6C, which was previously associated with chemotherapy and radiation therapy resistance, and maintenance of chromosomal stability. PPP6C, whose mRNA is distinguished with three miR-31-binding sites in its 3'-untranslated region, was consistently down-regulated by miR-31 introduction and up-regulated in clinical MM specimens as compared with matched normal tissues. Taken together, our data suggest that tumor-suppressive propensity of miR-31 can be used for development of new therapies against mesothelioma and other cancers that show loss of the 9p21.3 chromosome.

Genomic Profiling of Lung Adenocarcinoma in Never-Smokers.

PURPOSE: Approximately 10%-40% of patients with lung cancer report no history of tobacco smoking (never-smokers). We analyzed whole-exome and RNA-sequencing data of 160 tumor and normal lung adenocarcinoma (LUAD) samples from never-smokers to identify clinically actionable alterations and gain insight into the environmental and hereditary risk factors for LUAD among never-smokers. METHODS: We performed whole-exome and RNA-sequencing of 88 and 69 never-smoker LUADs. We analyzed these data in conjunction with data from 76 never-smoker and 299 smoker LUAD samples sequenced by The Cancer Genome Atlas and Clinical Proteomic Tumor Analysis Consortium. RESULTS: We observed a high prevalence of clinically actionable driver alterations in never-smoker LUADs compared with smoker LUADs (78%-92% v 49.5%; P < .0001). Although a subset of never-smoker samples demonstrated germline alterations in DNA repair genes, the frequency of samples showing germline variants in cancer predisposing genes was comparable between smokers and never-smokers (6.4% v 6.9%; P = .82). A subset of never-smoker samples (5.9%) showed mutation signatures that were suggestive of passive exposure to cigarette smoke. Finally, analysis of RNA-sequencing data showed distinct immune transcriptional subtypes of never-smoker LUADs that varied in their expression of clinically relevant immune checkpoint molecules and immune cell composition. CONCLUSION: In this comprehensive genomic and transcriptome analysis of never-smoker LUADs, we observed a potential role for germline variants in DNA repair genes and passive exposure to cigarette smoke in the pathogenesis of a subset of never-smoker LUADs. Our findings also show that clinically actionable driver alterations are highly prevalent in never-smoker LUADs, highlighting the need for obtaining biopsies with adequate cellularity for clinical genomic testing in these patients.

Protumorigenic role of HAPLN1 and its IgV domain in malignant pleural mesothelioma.

PURPOSE: Tumor extracellular matrix (ECM) plays a crucial role in cancer progression mediating and transforming host-tumor interactions. Targeting the ECM is becoming an increasingly promising therapeutic approach in cancer treatment. We find that one of the ECM proteins, HAPLN1, is overexpressed in the majority of mesotheliomas. This study was designed to characterize the protumorigenic role of HAPLN1 in mesothelioma. EXPERIMENTAL DESIGN: Overexpression of HAPLN1 was assessed and validated on a large set of normal/mesothelioma specimens on the RNA and protein levels. We also analyzed DNA copy number alterations in the HAPLN1 genomic locus using the array-based comparative genomic hybridization representational oligonucleotide microarray analysis tool. Tumorigenic activities of the HAPLN1 domains were evaluated in vitro on mesothelioma cells transfected with HAPLN1-expressing constructs. RESULTS: We found that HAPLN1 is 23-fold overexpressed in stage I mesothelioma and confirmed it for 76% samples (n = 53) on RNA and 97% (n = 40) on protein levels. The majority of lung cancers showed no differential expression of HAPLN1. Analysis of DNA copy number alterations identified recurrent gain in the 5q14.3 HAPLN1 locus in approximately 27% of tumors. Noteworthy, high expression of HAPLN1 negatively correlated with time to progression (P = 0.05, log-rank test) and overall survival (P = 0.006). Proliferation, motility, invasion, and soft-agar colony formation assays on mesothelioma cells overexpressing full-length HAPLN1 or its functional domains strongly supported the protumorigenic role of HAPLN1 and its SP-IgV domain. CONCLUSION: Overexpression of HAPLN1 and its SP-IgV domain increases tumorigenic properties of mesothelioma. Thus, targeting the SP-IgV domain may be one of the therapeutic approaches in cancer treatment.

Mesothelioma Biomarkers: A Review Highlighting Contributions from the Early Detection Research Network.

Malignant pleural mesothelioma (MPM) is an asbestos-related neoplasm, which can be treated successfully only if correctly diagnosed and treated in early stages. The asbestos-exposed population serves as a high-risk group that could benefit from sensitive and specific blood- or tissue-based biomarkers. This review details the recent work with biomarker development in MPM and the contributions of the NCI Early Detection Research Network Biomarker Developmental Laboratory of NYU Langone Medical Center. The literature of the last 20 years was reviewed to comment on the most promising of the blood- and tissue-based biomarkers. Proteomic, genomic, and epigenomic platforms as well as novel studies such as "breath testing" are covered. Soluble mesothelin-related proteins (SMRP) have been characterized extensively and constitute an FDA-approved biomarker in plasma with diagnostic, monitoring, and prognostic value in MPM. Osteopontin is found to be a valuable prognostic biomarker for MPM, while its utility in diagnosis is slightly lower. Other biomarkers, such as calretinin, fibulin 3, and High-Mobility Group Box 1 (HMGB1), remain under study and need international validation trials with large cohorts of cases and controls to demonstrate any utility. The EDRN has played a key role in the development and testing of MPM biomarkers by enlisting collaborations all over the world. A comprehensive understanding of previously investigated biomarkers and their utility in screening and early diagnosis of MPM will provide guidance for further future research.See all articles in this CEBP Focus section, "NCI Early Detection Research Network: Making Cancer Detection Possible."

Mesothelioma Biomarkers: Discovery in Search of Validation.

Malignant pleural mesothelioma (MPM) is an asbestos-related neoplasm that can only be treated successfully when correctly diagnosed and treated early. The asbestos-exposed population is a high-risk group that could benefit from sensitive and specific blood- or tissue-based biomarkers. We review recent work with biomarker development in MPM and literature of the last 20 years on the most promising blood- and tissue-based biomarkers. Proteomic, genomic, and epigenomic platforms are covered. SMRP is the only validated blood-based biomarker with diagnostic, monitoring and prognostic value. To strengthen development and testing of MPM biomarkers, cohorts for validation must be established by enlisting worldwide collaborations.