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Author(s): Luting Xu [1, 3]; Li Zhang [1, 3]; Yajun Yi [1, 2, 3]; Hee-Kap Kang [1]; Syamal K Datta (corresponding author) [1] Autoimmune T-helper cells drive pathogenic autoantibody production [...]

Abstract Background Widespread use of high-throughput techniques such as microarrays to monitor gene expression levels has resulted in an explosive growth of data sets in public domains. Integration and exploration of these complex and heterogeneous data have become a major challenge. Results The EXALT (EXpression signature AnaLysis Tool) online program enables meta-analysis of gene expression profiles derived from publically accessible sources. Searches can be executed online against two large databases currently containing more than 28,000 gene expression signatures derived from GEO (Gene Expression Omnibus) and published expression profiles of human cancer. Comparisons among gene expression signatures can be performed with homology analysis and co-expression analysis. Results can be visualized instantly in a plot or a heat map. Three typical use cases are illustrated. Conclusions The EXALT online program is uniquely suited for discovering relationships among transcriptional profiles and searching gene expression patterns derived from diverse physiological and pathological settings. The EXALT online program is freely available for non-commercial users from http://seq.mc.vanderbilt.edu/exalt/.

Abstract Background The purpose of this study was to identify candidate metastasis suppressor genes from a mouse allograft model of prostate cancer (NE-10). This allograft model originally developed metastases by twelve weeks after implantation in male athymic nude mice, but lost the ability to metastasize after a number of in vivo passages. We performed high resolution array comparative genomic hybridization on the metastasizing and non-metastasizing allografts to identify chromosome imbalances that differed between the two groups of tumors. Results This analysis uncovered a deletion on chromosome 2 that differed between the metastasizing and non-metastasizing tumors. Bioinformatics filters were employed to mine this region of the genome for candidate metastasis suppressor genes. Of the 146 known genes that reside within the region of interest on mouse chromosome 2, four candidate metastasis suppressor genes (Slc27a2, Mall, Snrpb, and Rassf2) were identified. Quantitative expression analysis confirmed decreased expression of these genes in the metastasizing compared to non-metastasizing tumors. Conclusion This study presents combined genomics and bioinformatics approaches for identifying potential metastasis suppressor genes. The genes identified here are candidates for further studies to determine their functional role in inhibiting metastases in the NE-10 allograft model and human prostate cancer.

Aims. To evaluate the performance of a factory-calibrated flash glucose monitoring system in children with diabetes compared to venous blood glucose (BG). Methods. A total of 13 hospitalized participants newly diagnosed with type 1 diabetes, aged 1~14 years old, were involved in the study. Sensor glucose measurements on days 2, 3, 6, 7, 12, and 13 of wear were compared with venous BG. During these days, the venous BG results were obtained either 4 or 7 times per day. Results. The accuracy was evaluated against venous BG, with 469 of 469 (100.0%) sensor and venous BG pairs within consensus error grid zones A and B, including 94.7% in zone A. The overall mean absolute relative difference (MARD) was 11.67%. The MARD of blood glucose lower than 4.0 mmol/L (MARD=16.89%) was higher than blood glucose between 4 and 10 mmol/L (MARD=11.58%) and blood glucose higher than 10 mmol/L (MARD=7.79%). Compared to venous BG, the MARDs of wear days 2, 3, 6, 7, 12, and 13 were 11.53%, 9.66%, 11.79%, 10.89%, 13.18%, and 13.92%, respectively, with no statistically significant difference (P=0.25). The median ARD was highest when the glucose decreased >0.11 mmol/L/min (20.27%) and lower than 10.00% when the glucose changed between 0.06 and 0.11 mmol/L/min, changed <0.06 mmol/L/min, and increased >0.11 mmol/L/min. Conclusions. The accuracy of the system is good and remains stable over 14 days of wear; however, the accuracy depends on the glucose level and rates of glucose concentration changes. [ABSTRACT FROM AUTHOR]

In order to realize video surveillance and optimized identification, in the embedded environment, a video feature location system based on embedded technology and VIX bus technology is proposed. The video feature positioning system designed in this paper becomes smaller and easier to carry and adapt outside test, inside test, with better performance and lower cost, higher signal to noise ratio, better video positioning accuracy. [ABSTRACT FROM AUTHOR]

Systemic lupus erythematosus (SLE) is an autoimmune disease characterized by a wide spectrum of clinical manifestations and degrees of severity. Few genomic biomarkers for SLE have been validated and employed to inform clinical classifications and decisions. To discover and assess the gene-expression based SLE predictors in published studies, we performed a meta-analysis using our established signature database and a data similarity-driven strategy. From 13 training data sets on SLE gene-expression studies, we identified a SLE meta-signature (SLEmetaSig100) containing 100 concordant genes that are involved in DNA sensors and the IFN signaling pathway. We rigorously examined SLEmetaSig100 with both retrospective and prospective validation in two independent data sets. Using unsupervised clustering, we retrospectively elucidated that SLEmetaSig100 could classify clinical samples into two groups that correlated with SLE disease status and disease activities. More importantly, SLEmetaSig100 enabled personalized stratification demonstrating its ability to prospectively predict SLE disease at the individual patient level. To evaluate the performance of SLEmetaSig100 in predicting SLE, we predicted 1,171 testing samples to be either non-SLE or SLE with positive predictive value (97–99%), specificity (85%-84%), and sensitivity (60–84%). Our study suggests that SLEmetaSig100 has enhanced predictive value to facilitate current SLE clinical classification and provides personalized disease activity monitoring. [ABSTRACT FROM AUTHOR]

Sulfur-doped microporous carbons have been fabricated through a facile pyrolyzing method using the raw coal as the carbon precursor and K2S as porogen and the sulfur source. Benefiting from the characteristics of appropriate BET surface area, abundant microporous structure and sulfur functionality, the sample Coal-K2S-750 exhibited a high specific capacitance of 188.9 F/g at 0.5 A/g and 123.0 F/g at 10 A/g as well as the excellent cycling stability with the capacitance fading of 3.6% over 5000 cycles at 5.0 A/g. [ABSTRACT FROM AUTHOR]

The LMO2 oncogene is deregulated in the majority of human T-cell leukemia cases and in most gene therapy-induced T-cell leukemias. We made transgenic mice with enforced expression of Lmo2 in T-cells by the CD2 promoter/enhancer. These transgenic mice developed highly penetrant T-ALL by two distinct patterns of gene expression: one in which there was concordant activation of Lyl1, Hhex, and Mycn or alternatively, with Notch1 target gene activation. Most strikingly, this gene expression clustering was conserved in human Early T-cell Precursor ALL (ETP-ALL), where LMO2, HHEX, LYL1, and MYCN were most highly expressed. We discovered that HHEX is a direct transcriptional target of LMO2 consistent with its concordant gene expression. Furthermore, conditional inactivation of Hhex in CD2-Lmo2 transgenic mice markedly attenuated T-ALL development, demonstrating that Hhex is a crucial mediator of Lmo2's oncogenic function. The CD2-Lmo2 transgenic mice offer mechanistic insight into concordant oncogene expression and provide a model for the highly treatment-resistant ETP-ALL subtype. [ABSTRACT FROM AUTHOR]

Castration-resistant prostate cancer can be treated with the antiandrogen enzalutamide, but responses and duration of response are variable. To identify genes that support enzalutamide resistance, we performed a short hairpin RNA (shRNA) screen in the bone-homing, castration-resistant prostate cancer cell line, C4-2B. We identified 11 genes ( TFAP2C, CAD, SPDEF, EIF6, GABRG2, CDC37, PSMD12, COL5A2, AR, MAP3K11, and ACAT1 ) whose loss resulted in decreased cell survival in response to enzalutamide. To validate our screen, we performed transient knockdowns in C4-2B and 22Rv1 cells and evaluated cell survival in response to enzalutamide. Through these studies, we validated three genes ( ACAT1, MAP3K11, and PSMD12 ) as supporters of enzalutamide resistance in vitro Although ACAT1 expression is lower in metastatic castration-resistant prostate cancer samples versus primary prostate cancer samples, knockdown of ACAT1 was sufficient to reduce cell survival in C4-2B and 22Rv1 cells. MAP3K11 expression increases with Gleason grade, and the highest expression is observed in metastatic castration-resistant disease. Knockdown of MAP3K11 reduced cell survival, and pharmacologic inhibition of MAP3K11 with CEP-1347 in combination with enzalutamide resulted in a dramatic increase in cell death. This was associated with decreased phosphorylation of AR-Serine650, which is required for maximal AR activation. Finally, although PSMD12 expression did not change during disease progression, knockdown of PSMD12 resulted in decreased AR and AR splice variant expression, likely contributing to the C4-2B and 22Rv1 decrease in cell survival. Our study has therefore identified at least three new supporters of enzalutamide resistance in castration-resistant prostate cancer cells in vitro ., (©2020 American Association for Cancer Research.)

Background: Systematic analysis of cancer gene-expression patterns using high-throughput transcriptional profiling technologies has led to the discovery and publication of hundreds of gene-expression signatures. However, few public signature values have been cross-validated over multiple studies for the prediction of cancer prognosis and chemosensitivity in the neoadjuvant setting., Methods: To analyze the prognostic and predictive values of publicly available signatures, we have implemented a systematic method for high-throughput and efficient validation of a large number of datasets and gene-expression signatures. Using this method, we performed a meta-analysis including 351 publicly available signatures, 37,000 random signatures, and 31 breast cancer datasets. Survival analyses and pathologic responses were used to assess prediction of prognosis, chemoresponsiveness, and chemo-drug sensitivity., Results: Among 31 breast cancer datasets and 351 public signatures, we identified 22 validation datasets, two robust prognostic signatures (BRmet50 and PMID18271932Sig33) in breast cancer and one signature (PMID20813035Sig137) specific for prognosis prediction in patients with ER-negative tumors. The 22 validation datasets demonstrated enhanced ability to distinguish cancer gene profiles from random gene profiles. Both prognostic signatures are composed of genes associated with TP53 mutations and were able to stratify the good and poor prognostic groups successfully in 82%and 68% of the 22 validation datasets, respectively. We then assessed the abilities of the two signatures to predict treatment responses of breast cancer patients treated with commonly used chemotherapeutic regimens. Both BRmet50 and PMID18271932Sig33 retrospectively identified those patients with an insensitive response to neoadjuvant chemotherapy (mean positive predictive values 85%-88%). Among those patients predicted to be treatment sensitive, distant relapse-free survival (DRFS) was improved (negative predictive values 87%-88%). BRmet50 was further shown to prospectively predict taxane-anthracycline sensitivity in patients with HER2-negative (HER2-) breast cancer., Conclusions: We have developed and applied a high-throughput screening method for public cancer signature validation. Using this method, we identified appropriate datasets for cross-validation and two robust signatures that differentiate TP53 mutation status and have prognostic and predictive value for breast cancer patients.

In many patients with prostate cancer, the cancer will be recurrent and eventually progress to lethal metastatic disease after primary treatment, such as surgery or radiation therapy. Therefore, it would be beneficial to better predict which patients with early-stage prostate cancer would progress or recur after primary definitive treatment. In addition, many studies indicate that activation of NF-κB signaling correlates with prostate cancer progression; however, the precise underlying mechanism is not fully understood. Our studies show that activation of NF-κB signaling via deletion of one allele of its inhibitor, IκBα, did not induce prostatic tumorigenesis in our mouse model. However, activation of NF-κB signaling did increase the rate of tumor progression in the Hi-Myc mouse prostate cancer model when compared with Hi-Myc alone. Using the nonmalignant NF-κB-activated androgen-depleted mouse prostate, a NF-κB-activated recurrence predictor 21 (NARP21) gene signature was generated. The NARP21 signature successfully predicted disease-specific survival and distant metastases-free survival in patients with prostate cancer. This transgenic mouse model-derived gene signature provides a useful and unique molecular profile for human prostate cancer prognosis, which could be used on a prostatic biopsy to predict indolent versus aggressive behavior of the cancer after surgery., (©2014 American Association for Cancer Research.)

The LMO2 oncogene is deregulated in the majority of human T-cell leukemia cases and in most gene therapy-induced T-cell leukemias. We made transgenic mice with enforced expression of Lmo2 in T-cells by the CD2 promoter/enhancer. These transgenic mice developed highly penetrant T-ALL by two distinct patterns of gene expression: one in which there was concordant activation of Lyl1, Hhex, and Mycn or alternatively, with Notch1 target gene activation. Most strikingly, this gene expression clustering was conserved in human Early T-cell Precursor ALL (ETP-ALL), where LMO2, HHEX, LYL1, and MYCN were most highly expressed. We discovered that HHEX is a direct transcriptional target of LMO2 consistent with its concordant gene expression. Furthermore, conditional inactivation of Hhex in CD2-Lmo2 transgenic mice markedly attenuated T-ALL development, demonstrating that Hhex is a crucial mediator of Lmo2's oncogenic function. The CD2-Lmo2 transgenic mice offer mechanistic insight into concordant oncogene expression and provide a model for the highly treatment-resistant ETP-ALL subtype.

Background: Robust transcriptional signatures in cancer can be identified by data similarity-driven meta-analysis of gene expression profiles. An unbiased data integration and interrogation strategy has not previously been available., Methods and Findings: We implemented and performed a large meta-analysis of breast cancer gene expression profiles from 223 datasets containing 10,581 human breast cancer samples using a novel data similarity-based approach (iterative EXALT). Cancer gene expression signatures extracted from individual datasets were clustered by data similarity and consolidated into a meta-signature with a recurrent and concordant gene expression pattern. A retrospective survival analysis was performed to evaluate the predictive power of a novel meta-signature deduced from transcriptional profiling studies of human breast cancer. Validation cohorts consisting of 6,011 breast cancer patients from 21 different breast cancer datasets and 1,110 patients with other malignancies (lung and prostate cancer) were used to test the robustness of our findings. During the iterative EXALT analysis, 633 signatures were grouped by their data similarity and formed 121 signature clusters. From the 121 signature clusters, we identified a unique meta-signature (BRmet50) based on a cluster of 11 signatures sharing a phenotype related to highly aggressive breast cancer. In patients with breast cancer, there was a significant association between BRmet50 and disease outcome, and the prognostic power of BRmet50 was independent of common clinical and pathologic covariates. Furthermore, the prognostic value of BRmet50 was not specific to breast cancer, as it also predicted survival in prostate and lung cancers., Conclusions: We have established and implemented a novel data similarity-driven meta-analysis strategy. Using this approach, we identified a transcriptional meta-signature (BRmet50) in breast cancer, and the prognostic performance of BRmet50 was robust and applicable across a wide range of cancer-patient populations.

Transforming growth factor beta (TGF-beta) is a master regulator of autocrine and paracrine signaling pathways between a tumor and its microenvironment. Decreased expression of TGF-beta type II receptor (TbetaRII) in stromal cells is associated with increased tumor metastasis and shorter patient survival. In this study, SILAC quantitative proteomics was used to identify differentially externalized proteins in the conditioned media from the mammary fibroblasts with or without intact TbetaRII. Over 1000 proteins were identified and their relative differential levels were quantified. Immunoassays were used to further validate identification and quantification of the proteomic results. Differential expression was detected for various extracellular proteins, including proteases and their inhibitors, growth factors, cytokines, and extracellular matrix proteins. CXCL10, a cytokine found to be up-regulated in the TbetaRII knockout mammary fibroblasts, is shown to directly stimulate breast tumor cell proliferation and migration. Overall, this study revealed hundreds of specific extracellular protein changes modulated by deletion of TbetaRII in mammary fibroblasts, which may play important roles in the tumor microenvironment. These results warrant further investigation into the effects of inhibiting the TGF-beta signaling pathway in fibroblasts because systemic inhibition of TGF-beta signaling pathways is being considered as a potential cancer therapy.

Tissue remodeling or regeneration is believed to initiate from multipotent stem and progenitor cells. We report here the establishment of two spontaneously immortalized adult non-tumorigenic human prostate epithelial cell lines, NHPrE1 and BHPrE1. NHPrE1 (CD133(high)/CD44(high)/OCT4(high)/PTEN(high)) was characterized as a putative progenitor cell, and BHPrE1 (p63(high)/p53(high)/p21(WAF1)(high)/RB(high)) was characterized as a putative epithelial intermediate cell. Genomic analysis demonstrated an abnormal karyotype with genomic rearrangements including PTEN amplification in NHPrE1 and CTNNB1 (beta-catenin) amplification in BHPrE1 cells. Embedded three-dimensional culture of NHPrE1 showed greater branching than BHPrE1. A tissue recombination-xenografting model was utilized to compare remodeling of human prostatic tissues in vivo. A series of tissue recombinants, made by mixing different ratios of human prostatic epithelial cells and inductive rat urogenital sinus mesenchyme, were grafted to the renal capsule of severe combined immunodeficient mice. Both cell lines were able to regenerate benign secretory ductal-acinar architecture in vivo, containing intact basal and luminal epithelial layers confirmed by the expression of appropriate CK profiles. Prostate-specific antigen, 15-lipoxygenase-2, androgen receptor, and NKX3.1 proteins were appropriately expressed in the regenerated epithelia. Regeneration of benign prostatic glandular structures could be achieved using as few as 10 NHPrE1 cells, whereas 200,000 BHPrE1 cells were required to achieve prostatic architecture. This suggests a greater proportion of progenitor/stem cells in NHPrE1 than in BHPrE1. These cell lines provide important data on progenitor and intermediate cell phenotypes and represent significant new tools for the elucidation of molecular mechanisms of human prostatic regeneration, pathogenesis, and carcinogenesis.

Background: Widespread use of high-throughput techniques such as microarrays to monitor gene expression levels has resulted in an explosive growth of data sets in public domains. Integration and exploration of these complex and heterogeneous data have become a major challenge., Results: The EXALT (EXpression signature AnaLysis Tool) online program enables meta-analysis of gene expression profiles derived from publically accessible sources. Searches can be executed online against two large databases currently containing more than 28,000 gene expression signatures derived from GEO (Gene Expression Omnibus) and published expression profiles of human cancer. Comparisons among gene expression signatures can be performed with homology analysis and co-expression analysis. Results can be visualized instantly in a plot or a heat map. Three typical use cases are illustrated., Conclusions: The EXALT online program is uniquely suited for discovering relationships among transcriptional profiles and searching gene expression patterns derived from diverse physiological and pathological settings. The EXALT online program is freely available for non-commercial users from http://seq.mc.vanderbilt.edu/exalt/.

Background: The purpose of this study was to identify candidate metastasis suppressor genes from a mouse allograft model of prostate cancer (NE-10). This allograft model originally developed metastases by twelve weeks after implantation in male athymic nude mice, but lost the ability to metastasize after a number of in vivo passages. We performed high resolution array comparative genomic hybridization on the metastasizing and non-metastasizing allografts to identify chromosome imbalances that differed between the two groups of tumors., Results: This analysis uncovered a deletion on chromosome 2 that differed between the metastasizing and non-metastasizing tumors. Bioinformatics filters were employed to mine this region of the genome for candidate metastasis suppressor genes. Of the 146 known genes that reside within the region of interest on mouse chromosome 2, four candidate metastasis suppressor genes (Slc27a2, Mall, Snrpb, and Rassf2) were identified. Quantitative expression analysis confirmed decreased expression of these genes in the metastasizing compared to non-metastasizing tumors., Conclusion: This study presents combined genomics and bioinformatics approaches for identifying potential metastasis suppressor genes. The genes identified here are candidates for further studies to determine their functional role in inhibiting metastases in the NE-10 allograft model and human prostate cancer.

EXALT (EXpression signature AnaLysis Tool) is a computational system enabling comparisons of microarray data across experimental platforms and different laboratories http://seq.mc.vanderbilt.edu/exalt/. An essential feature of EXALT is a database holding thousands of gene expression signatures extracted from the Gene Expression Omnibus, and encoded in a searchable format. This novel approach to performing global comparisons of shared microarray data may have enormous value when coupled directly with a shared data repository.

Gene expression signatures generated from DNA microarray analyses have shown promise as predictive biomarkers of clinical outcome. In this study, we determined a high-risk signature for disease recurrence using formalin-fixed head and neck squamous cell carcinoma (HNSCC) tumors and compared the results with an independent data set obtained from fresh frozen tumors. We also showed that genes involved in epithelial-to-mesenchymal transition (EMT) and nuclear factor-kappaB (NF-kappaB) signaling deregulation are the most prominent molecular characteristics of the high-risk tumors. Gene expression was determined in 40 samples, including 34 formalin-fixed tissues and 6 matched frozen tissues, from 29 HNSCC patients. A 75-gene list predictive of disease recurrence was determined by training on the formalin-fixed tumor data set and tested on data from the independent frozen tumor set from 60 HNSCC patients. The difference in recurrence-free survival (RFS) between the high-risk versus low-risk groups in the training and test sets was statistically significant (P = 0.002 and 0.03, respectively, log-rank test). In addition, the gene expression data was interrogated using Gene Set Enrichment Analysis to determine biological significance. The most significant sets of genes enriched in the high-risk tumors were genes involving EMT, NF-kappaB activation, and cell adhesion. In conclusion, global gene expression analysis is feasible using formalin-fixed tissue. The 75-gene list can be used as a prognostic biomarker of recurrence, and our data suggest that the molecular determinants of EMT and NF-kappaB activation can be targeted as the novel therapy in the identified high-risk patients.

Human papillomavirus (HPV) is associated with a subset of head and neck squamous cell carcinoma (HNSCC). Between 15% and 35% of HNSCCs harbor HPV DNA. Demographic and exposure differences between HPV-positive (HPV+) and negative (HPV-) HNSCCs suggest that HPV+ tumors may constitute a subclass with different biology, whereas clinical differences have also been observed. Gene expression profiles of HPV+ and HPV- tumors were compared with further exploration of the biological effect of HPV in HNSCC. Thirty-six HNSCC tumors were analyzed using Affymetrix Human 133U Plus 2.0 GeneChip and for HPV by PCR and real-time PCR. Eight of 36 (22%) tumors were positive for HPV subtype 16. Statistical analysis using Significance Analysis of Microarrays based on HPV status as a supervising variable resulted in a list of 91 genes that were differentially expressed with statistical significance. Results for a subset of these genes were verified by real-time PCR. Genes highly expressed in HPV+ samples included cell cycle regulators (p16(INK4A), p18, and CDC7) and transcription factors (TAF7L, RFC4, RPA2, and TFDP2). The microarray data were also investigated by mapping genes by chromosomal location (DIGMAP). A large number of genes on chromosome 3q24-qter had high levels of expression in HPV+ tumors. Further investigation of differentially expressed genes may reveal the unique pathways in HPV+ tumors that may explain the different natural history and biological properties of these tumors. These properties may be exploited as a target of novel therapeutic agents in HNSCC treatment.

Purpose: After an initial response to androgen ablation, most prostate tumors recur, ultimately progressing to highly aggressive androgen-independent cancer. The molecular mechanisms underlying progression are not well known in part due to the rarity of androgen-independent samples from primary and metastatic sites., Experimental Design: We compared the gene expression profiles of 10 androgen-independent primary prostate tumor biopsies with 10 primary, untreated androgen-dependent tumors. Samples were laser capture microdissected, the RNA was amplified, and gene expression was assessed using Affymetrix Human Genome U133A GeneChip. Differential expression was examined with principal component analysis, hierarchical clustering, and Student's t testing. Analysis of gene ontology was done with Expression Analysis Systematic Explorer and gene expression data were integrated with genomic alterations with Differential Gene Locus Mapping., Results: Unsupervised principal component analysis showed that the androgen-dependent and androgen-independent tumors segregated from one another. After filtering the data, 239 differentially expressed genes were identified. Two main gene ontologies were found discordant between androgen-independent and androgen-dependent tumors: macromolecule biosynthesis was down-regulated and cell adhesion was up-regulated in androgen-independent tumors. Other differentially expressed genes were related to interleukin-6 signaling as well as angiogenesis, cell adhesion, apoptosis, oxidative stress, and hormone response. The Differential Gene Locus Mapping analysis identified nine regions of potential chromosomal deletion in the androgen-independent tumors, including 1p36, 3p21, 6p21, 8p21, 11p15, 11q12, 12q23, 16q12, and 16q21., Conclusions: Taken together, these data identify several unique characteristics of androgen-independent prostate cancer that may hold potential for the development of targeted therapeutic intervention.