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.

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.

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.

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.

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.

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.

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.

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.

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."

Tumor-draining lymph nodes demonstrate a suppressive immunophenotype in patients with non-small cell lung cancer assessed by endobronchial ultrasound-guided transbronchial needle aspiration: A pilot study.

OBJECTIVES: Tumor draining lymph nodes (TDLN) are key sites of early immunoediting in patients with non-small cell lung cancer (NSCLC) and play an important role in generating anti-tumor immunity. Immune suppression in the tumor microenvironment has prognostic implications and may predict therapeutic response. T cell composition of draining lymph nodes may reflect an immunophenotype with similar prognostic potential which could be measured during standard-of-care bronchoscopic assessment. In this study, we compared the immunophenotype from different sites within individuals to primary tumor characteristics in patients with NSCLC to see whether there were tumor-regional differences in immunophenotype which could be evaluated from transbronchial needle aspirates. MATERIALS AND METHODS: Twenty patients were enrolled in this study and had tissue (lymph node aspirates and/or peripheral blood) obtained during standard of care bronchoscopy with endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) for diagnosis or staging of known or suspected NSCLC. Aspirates and blood underwent flow-assisted cell sorting and a subset of sorted effector T cells underwent RNA quantitation to determine feasibility of this approach. Immunophenotypic patterns from twelve patients with paired data from tumor-draining and non-tumor draining lymph nodes (NDLN) were compared relative to one another and based on PD-L1 immunohistochemistry and primary tumor histology. RESULTS: TDLN had significantly fewer CD4+ T cells (12.68% vs 27%, p = 0.002) and significantly more regulatory T cells (Treg, 12.03% vs 9.52%, p = 0.03) relative to paired NDLN suggesting tumor-regional immunosuppression. There were significantly more Treg in NDLN relative to paired PBMC (9.52% vs 5.6%, p = 0.016). Patients with PD-L1 expression ≥50% had significantly greater tumor-regional CD4+ T cell depletion compared to patients with PD-L1 expression <50% (-35.98% vs -1.89%, p = 0.0357; negative values represent absolute difference between paired TDLN and NDLN). CONCLUSIONS: In patients with NSCLC, TDLN have a suppressive immunophenotype correlating with tumor PD-L1 status and can be assessed during routine EBUS-TBNA.

When RON MET TAM in Mesothelioma: All Druggable for One, and One Drug for All?

Malignant pleural mesothelioma (MPM) is an aggressive inflammatory cancer with a poor survival rate. Treatment options are limited at best and drug resistance is common. Thus, there is an urgent need to identify novel therapeutic targets in this disease in order to improve patient outcomes and survival times. MST1R (RON) is a trans-membrane receptor tyrosine kinase (RTK), which is part of the c-MET proto-oncogene family. The only ligand recognized to bind MST1R (RON) is Macrophage Stimulating 1 (MST1), also known as Macrophage Stimulating Protein (MSP) or Hepatocyte Growth Factor-Like Protein (HGFL). In this study, we demonstrate that the MST1-MST1R (RON) signaling axis is active in MPM. Targeting this pathway with a small molecule inhibitor, LCRF-0004, resulted in decreased proliferation with a concomitant increase in apoptosis. Cell cycle progression was also affected. Recombinant MST1 treatment was unable to overcome the effect of LCRF-0004 in terms of either proliferation or apoptosis. Subsequently, the effect of an additional small molecular inhibitor, BMS-777607 (which targets MST1R (RON), MET, Tyro3, and Axl) also resulted in a decreased proliferative capacity of MPM cells. In a cohort of MPM patient samples, high positivity for total MST1R by IHC was an independent predictor of favorable prognosis. Additionally, elevated expression levels of MST1 also correlated with better survival. This study also determined the efficacy of LCRF-0004 and BMS-777607 in xenograft MPM models. Both LCRF-0004 and BMS-777607 demonstrated significant anti-tumor efficacy in vitro, however BMS-777607 was far superior to LCRF-0004. The in vivo and in vitro data generated by this study indicates that a multi-TKI, targeting the MST1R/MET/TAM signaling pathways, may provide a more effective therapeutic strategy for the treatment of MPM as opposed to targeting MST1R alone.

The Microbiome in Lung Cancer Tissue and Recurrence-Free Survival.

BACKGROUND: Human microbiota have many functions that could contribute to cancer initiation and/or progression at local sites, yet the relation of the lung microbiota to lung cancer prognosis has not been studied. METHODS: In a pilot study, 16S rRNA gene sequencing was performed on paired lung tumor and remote normal samples from the same lobe/segment in 19 patients with non-small cell lung cancer (NSCLC). We explored associations of tumor or normal tissue microbiome diversity and composition with recurrence-free (RFS) and disease-free survival (DFS), and compared microbiome diversity and composition between paired tumor and normal samples. RESULTS: Higher richness and diversity in normal tissue were associated with reduced RFS (richness P = 0.08, Shannon index P = 0.03) and DFS (richness P = 0.03, Shannon index P = 0.02), as was normal tissue overall microbiome composition (Bray-Curtis P = 0.09 for RFS and P = 0.02 for DFS). In normal tissue, greater abundance of family Koribacteraceae was associated with increased RFS and DFS, whereas greater abundance of families Bacteroidaceae, Lachnospiraceae, and Ruminococcaceae were associated with reduced RFS or DFS (P < 0.05). Tumor tissue diversity and overall composition were not associated with RFS or DFS. Tumor tissue had lower richness and diversity (P ≤ 0.0001) than paired normal tissue, though overall microbiome composition did not differ between the paired samples. CONCLUSIONS: We demonstrate, for the first time, a potential relationship between the normal lung microbiota and lung cancer prognosis, which requires confirmation in a larger study. IMPACT: Definition of bacterial biomarkers of prognosis may lead to improved survival outcomes for patients with lung cancer.

A Subset of Mesotheliomas With Improved Survival Occurring in Carriers of BAP1 and Other Germline Mutations.

PURPOSE: We hypothesized that four criteria could help identify malignant mesotheliomas (MMs) most likely linked to germline mutations of BAP1 or of other genes: family history of MM, BAP1-associated cancers, or multiple malignancies; or age younger than 50 years. PATIENTS AND METHODS: Over the course of 7 years, 79 patients with MM met the four criteria; 22 of the 79 (28%) reported possible asbestos exposure. They were screened for germline BAP1 mutations by Sanger sequencing and by targeted next-generation sequencing (tNGS) for germline mutations in 55 additional cancer-linked genes. Deleterious mutations detected by tNGS were validated by Sanger sequencing. RESULTS: Of the 79 patients, 43 (16 probands and 27 relatives) had deleterious germline BAP1 mutations. The median age at diagnosis was 54 years and median survival was 5 years. Among the remaining 36 patients with no BAP1 mutation, median age at diagnosis was 45 years, median survival was 9 years, and 12 had deleterious mutations of additional genes linked to cancer. When compared with patients with MMs in the SEER cohort, median age at diagnosis (72 years), median survival for all MM stages (8 months), and stage I (11 months) were significantly different from the 79 patients with MM in the current study ( P < .0001). CONCLUSION: We provide criteria that help identify a subset of patients with MM who had significantly improved survival. Most of these patients were not aware of asbestos exposure and carried either pathogenic germline mutations of BAP1 or of additional genes linked to cancer, some of which may have targeted-therapy options. These patients and their relatives are susceptible to development of additional cancers; therefore, genetic counseling and cancer screening should be considered.

Epigenetically regulated PAX6 drives cancer cells toward a stem-like state via GLI-SOX2 signaling axis in lung adenocarcinoma.

It remains unclear whether PAX6 acts as a crucial transcription factor for lung cancer stem cell (CSC) traits. We demonstrate that PAX6 acts as an oncogene responsible for induction of cancer stemness properties in lung adenocarcinoma (LUAD). Mechanistically, PAX6 promotes GLI transcription, resulting in SOX2 upregulation directly by the binding of GLI to the proximal promoter region of the SOX2 gene. The overexpressed SOX2 enhances the expression of key pluripotent factors (OCT4 and NANOG) and suppresses differentiation lineage factors (HOPX and NKX2-1), driving cancer cells toward a stem-like state. In contrast, in the differentiated non-CSCs, PAX6 is transcriptionally silenced by its promoter methylation. In human lung cancer tissues, the positive linear correlations of PAX6 expression with GLI and SOX2 expression and its negative correlations with HOPX and NKX2-1 expression were observed. Therapeutically, the blockade of the PAX6-GLI-SOX2 signaling axis elicits a long-lasting therapeutic efficacy by limiting CSC expansion following chemotherapy. Furthermore, a methylation panel including the PAX6 gene yielded a sensitivity of 79.1% and specificity of 83.3% for cancer detection using serum DNA from stage IA LUAD. Our findings provide a rationale for targeting the PAX6-GLI-SOX2 signaling axis with chemotherapy as an effective therapeutic strategy and support the clinical utility of PAX6 gene promoter methylation as a biomarker for early lung cancer detection.

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.

Involvement of Heparanase in the Pathogenesis of Mesothelioma: Basic Aspects and Clinical Applications.

Background: Mammalian cells express a single functional heparanase, an endoglycosidase that cleaves heparan sulfate and thereby promotes tumor metastasis, angiogenesis, and inflammation. Malignant mesothelioma is highly aggressive and has a poor prognosis because of the lack of markers for early diagnosis and resistance to conventional therapies. The purpose of this study was to elucidate the mode of action and biological significance of heparanase in mesothelioma and test the efficacy of heparanase inhibitors in the treatment of this malignancy. Methods: The involvement of heparanase in mesothelioma was investigated by applying mouse models of mesothelioma and testing the effect of heparanase gene silencing (n = 18 mice per experiment; two different models) and heparanase inhibitors (ie, PG545, defibrotide; n = 18 per experiment; six different models). Synchronous pleural effusion and plasma samples from patients with mesothelioma (n = 35), other malignancies (12 non-small cell lung cancer, two small cell lung carcinoma, four breast cancer, three gastrointestinal cancers, two lymphomas), and benign effusions (five patients) were collected and analyzed for heparanase content (enzyme-linked immunosorbent assay). Eighty-one mesothelioma biopsies were analyzed by H-Score for the prognostic impact of heparanase using immunohistochemistry. All statistical tests were two-sided. Results: Mesothelioma tumor growth, measured by bioluminescence or tumor weight at termination, was markedly attenuated by heparanase gene silencing (P = .02) and by heparanase inhibitors (PG545 and defibrotide; P < .001 and P = .01, respectively). A marked increase in survival of the mesothelioma-bearing mice (P < .001) was recorded. Heparanase inhibitors were more potent in vivo than conventional chemotherapy. Clinically, heparanase levels in patients' pleural effusions could distinguish between malignant and benign effusions, and a heparanase H-score above 90 was associated with reduced patient survival (hazard ratio = 1.89, 95% confidence interval = 1.09 to 3.27, P = .03). Conclusions: Our results imply that heparanase is clinically relevant in mesothelioma development. Given these preclinical and clinical data, heparanase appears to be an important mediator of mesothelioma, and heparanase inhibitors are worthy of investigation as a new therapeutic modality in mesothelioma clinical trials.