Increases in regional brain volume across two native South American male populations

Industrialized environments, despite benefits such as higher levels of formal education and lower rates of infections, can also have pernicious impacts upon brain atrophy. Partly for this reason, comparing age-related brain volume trajectories between industrialized and non-industrialized populations can help to suggest lifestyle correlates of brain health. The Tsimane, indigenous to the Bolivian Amazon, derive their subsistence from foraging and horticulture and are physically active. The Moseten, a mixed-ethnicity farming population, are physically active but less than the Tsimane. Within both populations (N = 1024; age range = 46-83), we calculated regional brain volumes from computed tomography and compared their cross-sectional trends with age to those of UK Biobank (UKBB) participants (N = 19,973; same age range). Surprisingly among Tsimane and Moseten (T/M) males, some parietal and occipital structures mediating visuospatial abilities exhibit small but significant increases in regional volume with age. UKBB males exhibit a steeper negative trend of regional volume with age in frontal and temporal structures compared to T/M males. However, T/M females exhibit significantly steeper rates of brain volume decrease with age compared to UKBB females, particularly for some cerebro-cortical structures (e.g., left subparietal cortex). Across the three populations, observed trends exhibit no interhemispheric asymmetry. In conclusion, the age-related rate of regional brain volume change may differ by lifestyle and sex. The lack of brain volume reduction with age is not known to exist in other human population, highlighting the putative role of lifestyle in constraining regional brain atrophy and promoting elements of non-industrialized lifestyle like higher physical activity.

Distinct sets of molecular characteristics define tumor-rejecting neoantigens

Challenges in identifying tumor-rejecting neoantigens limit the efficacy of neoantigen vaccines to treat cancers, including cutaneous squamous cell carcinoma (cSCC). A minority of human cSCC tumors shared neoantigens, supporting the need for personalized vaccines. Using a UV-induced mouse cSCC model which recapitulated the mutational signature and driver mutations found in human disease, we found that CD8 T cells constrain cSCC. Two MHC class I neoantigens were identified that constrained cSCC growth. Compared to the wild-type peptides, one tumor-rejecting neoantigen exhibited improved MHC binding and the other had increased solvent accessibility of the mutated residue. Across known neoantigens that do not impact MHC binding, structural modeling of the peptide/MHC complexes indicated that increased solvent accessibility, which will facilitate TCR recognition of the neoantigen, distinguished tumor-rejecting from non-immunogenic neoantigens. This work reveals characteristics of tumor-rejecting neoantigens that may be of considerable importance in identifying optimal vaccine candidates in cSCC and other cancers.

Multi-modal efficacy of a chimeric vesiculovirus expressing the Morreton glycoprotein in sarcoma

Vesiculoviruses are attractive oncolytic virus platforms due to their rapid replication, appreciable transgene capacity, broad tropism, limited preexisting immunity, and tumor selectivity through type I interferon response defects in malignant cells. We developed a synthetic chimeric virus (VMG) expressing the glycoprotein (G) from Morreton virus (MorV) and utilizing the remaining structural genes from vesicular stomatitis virus (VSV). VMG exhibited in vitro efficacy by inducing oncolysis in a broad range of sarcoma subtypes across multiple species. Notably, all cell lines tested showed the ability of VMG to yield productive infection with rapid replication kinetics and induction of apoptosis. Furthermore, pilot safety evaluations of VMG in immunocompetent, non-tumor-bearing mice showed an absence of toxicity with intranasal doses as high as 1e10 50% tissue culture infectious dose (TCID50)/kg. Locoregional administration of VMG in vivo resulted in tumor reduction in an immunodeficient Ewing sarcoma xenograft at doses as low as 2e5 TCID50. In a murine syngeneic fibrosarcoma model, while no tumor inhibition was achieved with VMG, there was a robust induction of CD8+ T cells within the tumor. The studies described herein establish the promising potential for VMG to be used as a novel oncolytic virotherapy platform with anticancer effects in sarcoma.

The role of Neanderthal introgression in liver cancer

BACKGROUND

Neanderthal introgressed DNA has been linked to different normal and disease traits including immunity and metabolism-two important functions that are altered in liver cancer. However, there is limited understanding of the relationship between Neanderthal introgression and liver cancer risk. The aim of this study was to investigate the relationship between Neanderthal introgression and liver cancer risk.

METHODS

Using germline and somatic DNA and tumor RNA from liver cancer patients from The Cancer Genome Atlas, along with ancestry-match germline DNA from unaffected individuals from the 1000 Genomes Resource, and allele specific expression data from normal liver tissue from The Genotype-Tissue Expression project we investigated whether Neanderthal introgression impacts cancer etiology. Using a previously generated set of Neanderthal alleles, we identified Neanderthal introgressed haplotypes. We then tested whether somatic mutations are enriched or depleted on Neanderthal introgressed haplotypes compared to modern haplotypes. We also computationally assessed whether somatic mutations have a functional effect or show evidence of regulating expression of Neanderthal haplotypes. Finally, we compared patterns of Neanderthal introgression in liver cancer patients and the general population.

RESULTS

We find Neanderthal introgressed haplotypes exhibit an excess of somatic mutations compared to modern haplotypes. Variant Effect Predictor analysis revealed that most of the somatic mutations on these Neanderthal introgressed haplotypes are not functional. We did observe expression differences of Neanderthal alleles between tumor and normal for four genes that also showed a pattern of enrichment of somatic mutations on Neanderthal haplotypes. However, gene expression was similar between liver cancer patients with modern ancestry and liver cancer patients with Neanderthal ancestry at these genes. Provocatively, when analyzing all genes, we find evidence of Neanderthal introgression regulating expression in tumor from liver cancer patients in two genes, ARK1C4 and OAS1. Finally, we find that most genes do not show a difference in the proportion of Neanderthal introgression between liver cancer patients and the general population.

CONCLUSION

Our results suggest that Neanderthal introgression provides opportunity for somatic mutations to accumulate, and that some Neanderthal introgression may impact liver cancer risk.

Abstract A001: Shared gene expression and immune pathway changes associated with progression from nevi to melanoma

There is a need to identify biomarkers of melanoma progression to assist the development of chemoprevention strategies to lower melanoma incidence. In this study, we assessed the feasibility of creating a molecular signature for melanomagenesis using three publicly available RNA sequencing and microarray expression datasets. We performed differential expression and regularized regression analyses across nevi and melanoma samples to identify consistent genes associated with melanomagenesis. The regularized regression models demonstrated that a small number of genes could successfully distinguish between nevi and melanoma, providing evidence for the feasibility of creating a molecular signature. Differential expression analysis identified consistent upregulation of C1QB, CXCL9, CXCL10, DFNA5 (GSDME), FCGR1B, and PRAME in melanoma and consistent downregulation of SCGB1D2 in melanoma compared to nevi. Additionally, each of these genes demonstrated a linear association with the progression from benign nevi to dysplastic nevi, to radial growth phase melanoma to vertical growth phase melanoma, providing additional evidence for their role in melanomagenesis. Subsequent pathway analysis demonstrated significant enrichment of immune-related pathways among the differentially expressed genes. Overall, this study 1) demonstrates the feasibility of creating a gene signature for melanomagenesis and 2) highlights genes and pathways of interest for melanoma progression. We are in the process of generating a new dataset with benign nevi, dysplastic nevi, and melanoma with which to build and validate a molecular signature of melanoma.

Citation Format: Elizabeth S. Borden, Anngela C. Adams, Kenneth H. Buetow, Melissa A. Wilson, Julie E. Bauman, Clara Curiel-Lewandrowski, H.-H. Sherry Chow, Bonnie J. LaFleur, Karen Taraszka Hastings. Shared gene expression and immune pathway changes associated with progression from nevi to melanoma [abstract]. In: Proceedings of the Second Biennial NCI Meeting: Translational Advances in Cancer Prevention Agent Development (TACPAD); 2022 Sep 7-9. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_2): Abstract nr A001.

Abstract A006: Shared gene expression and immune pathway changes associated with progression from nevi to melanoma

There is a need to identify biomarkers of melanoma progression to assist the development of chemoprevention strategies to lower melanoma incidence. In this study, we assessed the feasibility of creating a molecular signature for melanomagenesis using three publicly available RNA sequencing and microarray expression datasets. We performed differential expression and regularized regression analyses across nevi and melanoma samples to identify consistent genes associated with melanomagenesis. The regularized regression models demonstrated that a small number of genes could successfully distinguish between nevi and melanoma, providing evidence for the feasibility of creating a molecular signature. Differential expression analysis identified consistent upregulation of C1QB, CXCL9, CXCL10, DFNA5 (GSDME), FCGR1B, and PRAME in melanoma and consistent downregulation of SCGB1D2 in melanoma compared to nevi. Additionally, each of these genes demonstrated a linear association with the progression from benign nevi to dysplastic nevi, to radial growth phase melanoma to vertical growth phase melanoma, providing additional evidence for their role in melanomagenesis. Subsequent pathway analysis demonstrated significant enrichment of immune-related pathways among the differentially expressed genes. Overall, this study 1) demonstrates the feasibility of creating a gene signature for melanomagenesis and 2) highlights genes and pathways of interest for melanoma progression. We are in the process of generating a new dataset with benign nevi, dysplastic nevi, and melanoma with which to build and validate a molecular signature of melanoma.

Citation Format: Elizabeth S. Borden, Anngela C. Adams, Kenneth H. Buetow, Melissa A. Wilson, Julie E. Bauman, Clara Curiel-Lewandrowski, H.-H. Sherry Chow, Bonnie J. LaFleur, Karen Taraszka Hastings. Shared gene expression and immune pathway changes associated with progression from nevi to melanoma [abstract]. In: Proceedings of the Second Biennial NCI Meeting: Translational Advances in Cancer Prevention Agent Development (TACPAD); 2022 Sep 7-9. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_2): Abstract nr A006.

NeoScore Integrates Characteristics of the Neoantigen:MHC Class I Interaction and Expression to Accurately Prioritize Immunogenic Neoantigens

Accurate prioritization of immunogenic neoantigens is key to developing personalized cancer vaccines and distinguishing those patients likely to respond to immune checkpoint inhibition. However, there is no consensus regarding which characteristics best predict neoantigen immunogenicity, and no model to date has both high sensitivity and specificity and a significant association with survival in response to immunotherapy. We address these challenges in the prioritization of immunogenic neoantigens by (1) identifying which neoantigen characteristics best predict immunogenicity; (2) integrating these characteristics into an immunogenicity score, the NeoScore; and (3) demonstrating a significant association of the NeoScore with survival in response to immune checkpoint inhibition. One thousand random and evenly split combinations of immunogenic and nonimmunogenic neoantigens from a validated dataset were analyzed using a regularized regression model for characteristic selection. The selected characteristics, the dissociation constant and binding stability of the neoantigen:MHC class I complex and expression of the mutated gene in the tumor, were integrated into the NeoScore. A web application is provided for calculation of the NeoScore. The NeoScore results in improved, or equivalent, performance in four test datasets as measured by sensitivity, specificity, and area under the receiver operator characteristics curve compared with previous models. Among cutaneous melanoma patients treated with immune checkpoint inhibition, a high maximum NeoScore was associated with improved survival. Overall, the NeoScore has the potential to improve neoantigen prioritization for the development of personalized vaccines and contribute to the determination of which patients are likely to respond to immunotherapy.

Cancer Neoantigens: Challenges and Future Directions for Prediction, Prioritization, and Validation

Prioritization of immunogenic neoantigens is key to enhancing cancer immunotherapy through the development of personalized vaccines, adoptive T cell therapy, and the prediction of response to immune checkpoint inhibition. Neoantigens are tumor-specific proteins that allow the immune system to recognize and destroy a tumor. Cancer immunotherapies, such as personalized cancer vaccines, adoptive T cell therapy, and immune checkpoint inhibition, rely on an understanding of the patient-specific neoantigen profile in order to guide personalized therapeutic strategies. Genomic approaches to predicting and prioritizing immunogenic neoantigens are rapidly expanding, raising new opportunities to advance these tools and enhance their clinical relevance. Predicting neoantigens requires acquisition of high-quality samples and sequencing data, followed by variant calling and variant annotation. Subsequently, prioritizing which of these neoantigens may elicit a tumor-specific immune response requires application and integration of tools to predict the expression, processing, binding, and recognition potentials of the neoantigen. Finally, improvement of the computational tools is held in constant tension with the availability of datasets with validated immunogenic neoantigens. The goal of this review article is to summarize the current knowledge and limitations in neoantigen prediction, prioritization, and validation and propose future directions that will improve personalized cancer treatment.

Synergistic combination of cytotoxic chemotherapy and cyclin-dependent kinase 4/6 inhibitors in biliary tract cancers

BACKGROUND AND AIMS

Biliary tract cancers (BTCs) are uncommon, but highly lethal, gastrointestinal malignancies. Gemcitabine/cisplatin is a standard-of-care systemic therapy, but has a modest impact on survival and harbors toxicities, including myelosuppression, nephropathy, neuropathy, and ototoxicity. Whereas BTCs are characterized by aberrations activating the cyclinD1/cyclin-dependent kinase (CDK)4/6/CDK inhibitor 2a/retinoblastoma pathway, clinical use of CDK4/6 inhibitors as monotherapy is limited by lack of validated biomarkers, diffident preclinical efficacy, and development of acquired drug resistance. Emerging studies have explored therapeutic strategies to enhance the antitumor efficacy of CDK4/6 inhibitors by the combination with chemotherapy regimens, but their mechanism of action remains elusive.

APPROACH AND RESULTS

Here, we report in vitro and in vivo synergy in BTC models, showing enhanced efficacy, reduced toxicity, and better survival with a combination comprising gemcitabine/cisplatin and CDK4/6 inhibitors. Furthermore, we demonstrated that abemaciclib monotherapy had only modest efficacy attributable to autophagy-induced resistance. Notably, triplet therapy was able to potentiate efficacy through elimination of the autophagic flux. Correspondingly, abemaciclib potentiated ribonucleotide reductase catalytic subunit M1 reduction, resulting in sensitization to gemcitabine.

CONCLUSIONS

As such, these data provide robust preclinical mechanistic evidence of synergy between gemcitabine/cisplatin and CDK4/6 inhibitors and delineate a path forward for translation of these findings to preliminary clinical studies in advanced BTC patients.

Shared Gene Expression and Immune Pathway Changes Associated with Progression from Nevi to Melanoma

Simple Summary

Melanoma is a deadly skin cancer, and the incidence of melanoma is rising. Chemoprevention, using small molecule drugs to prevent the development of cancer, is a key strategy that could reduce the burden of melanoma on society. The long-term goal of our study is to develop a gene signature biomarker of progression from nevi to melanoma. We found that a small number of genes can distinguish nevi from melanoma and identified shared genes and immune-related pathways that are associated with progression from nevi to melanoma across independent datasets. This study demonstrates (1) a novel approach to aid melanoma chemoprevention trials by using a gene signature as a surrogate endpoint and (2) the feasibility of determining a gene signature biomarker of melanoma progression.

Abstract

There is a need to identify molecular biomarkers of melanoma progression to assist the development of chemoprevention strategies to lower melanoma incidence. Using datasets containing gene expression for dysplastic nevi and melanoma or melanoma arising in a nevus, we performed differential gene expression analysis and regularized regression models to identify genes and pathways that were associated with progression from nevi to melanoma. A small number of genes distinguished nevi from melanoma. Differential expression of seven genes was identified between nevi and melanoma in three independent datasets. C1QB, CXCL9, CXCL10, DFNA5 (GSDME), FCGR1B, and PRAME were increased in melanoma, and SCGB1D2 was decreased in melanoma, compared to dysplastic nevi or nevi that progressed to melanoma. Further supporting an association with melanomagenesis, these genes demonstrated a linear change in expression from benign nevi to dysplastic nevi to radial growth phase melanoma to vertical growth phase melanoma. The genes associated with melanoma progression showed significant enrichment of multiple pathways related to the immune system. This study demonstrates (1) a novel application of bioinformatic approaches to aid clinical trials of melanoma chemoprevention and (2) the feasibility of determining a gene signature biomarker of melanomagenesis.

Penalized regression analysis identifies features of the peptide:MHC class I interaction and mRNA expression as key to prioritizing neoantigen immunogenicity

Current approaches to prioritization of tumor-specific neoantigens have low sensitivity and specificity, directly impacting the development of personalized vaccines and the prediction of immunotherapy efficacy. Many biological features have been suggested to contribute to accurate neoantigen prioritization. We calculated predictors for a comprehensive set of biological features for presentation and recognition of neoantigens on a validated neoantigen dataset. One thousand random, evenly-split combinations of immunogenic and non-immunogenic neoantigens were analyzed using penalized regression (lasso) for variable selection. This analysis isolated the peptide:MHC class I dissociation constant, binding stability, and mRNA expression as the key predictive variables of tumor-specific neoantigens. Based on these results, we fit a logistic regression model and tested its performance on three independent datasets. We compared our results to the models by Wells et al., Łuksza et al., and Zhou et al. Our model has improved performance as measured by the area under the receiver operator curve (AUC) compared to Łuksza and Zhou et al. Our model selects the same terms as Wells et al. and performs equivalently. However, it has the advantage of providing a predicted immunogenicity score for each individual neoantigen. Individual antigen approaches are useful for prioritizing vaccine candidates and predicting response to immunotherapy. Future work will focus on the application of this predictor to patient response to immunotherapy.

Neoantigen Fitness Model Predicts Lower Immune Recognition of Cutaneous Squamous Cell Carcinomas Than Actinic Keratoses

A low percentage of actinic keratoses progress to develop into cutaneous squamous cell carcinoma. The immune mechanisms that successfully control or eliminate the majority of actinic keratoses and the mechanisms of immune escape by invasive squamous cell carcinoma are not well-understood. Here, we took a systematic approach to evaluate the neoantigens present in actinic keratosis and cutaneous squamous cell carcinoma specimens. We compared the number of mutations, the number of neoantigens predicted to bind MHC class I, and the number of neoantigens that are predicted to bind MHC class I and be recognized by a T cell receptor in actinic keratoses and cutaneous squamous cell carcinomas. We also considered the relative binding strengths to both MHC class I and the T cell receptor in a fitness cost model that allows for a comparison of the immune recognition potential of the neoantigens in actinic keratosis and cutaneous squamous cell carcinoma samples. The fitness cost was subsequently adjusted by the expression rates of the neoantigens to examine the role of neoantigen expression in tumor immune evasion. Our analyses indicate that, while the number of mutations and neoantigens are not significantly different between actinic keratoses and cutaneous squamous cell carcinomas, the predicted immune recognition of the neoantigen with the highest expression-adjusted fitness cost is lower for cutaneous squamous cell carcinomas compared with actinic keratoses. These findings suggest a role for the down-regulation of expression of highly immunogenic neoantigens in the immune escape of cutaneous squamous cell carcinomas. Furthermore, these findings highlight the importance of incorporating additional factors, such as the quality and expression of the neoantigens, rather than focusing solely on tumor mutational burden, in assessing immune recognition potential.

High GILT Expression and an Active and Intact MHC Class II Antigen Presentation Pathway Are Associated with Improved Survival in Melanoma

The MHC class I Ag presentation pathway in melanoma cells has a well-established role in immune-mediated destruction of tumors. However, the clinical significance of the MHC class II Ag presentation pathway in melanoma cells is less clear. In Ag-presenting cells, IFN-γ-inducible lysosomal thiol reductase (GILT) is critical for MHC class II-restricted presentation of multiple melanoma Ags. Although not expressed in benign melanocytes of nevi, GILT and MHC class II expression is induced in malignant melanocytes in a portion of melanoma specimens. Analysis of The Cancer Genome Atlas cutaneous melanoma data set showed that high GILT mRNA expression was associated with improved overall survival. Expression of IFN-γ, TNF-α, and IL-1β was positively associated with GILT expression in melanoma specimens. These cytokines were capable of inducing GILT expression in human melanoma cells in vitro. GILT protein expression in melanocytes was induced in halo nevi, which are nevi undergoing immune-mediated regression, and is consistent with the association of GILT expression with improved survival in melanoma. To explore potential mechanisms of GILT's association with patient outcome, we investigated pathways related to GILT function and expression. In contrast to healthy skin specimens, in which the MHC class II pathway was nearly uniformly expressed and intact, there was substantial variation in the MHC class II pathway in the The Cancer Genome Atlas melanoma specimens. Both an active and intact MHC class II pathway were associated with improved overall survival in melanoma. These studies support a role for GILT and the MHC class II Ag presentation pathway in melanoma outcome.

Novel Mechanisms of Cancer Emerge When Accounting for Sex as a Biological Variable

There is a large gap between the aspiration of considering sex as biological variable and the execution of such studies, particularly in genomic studies of human cancer. This represents a lost opportunity to identify sex-specific molecular etiologies that may underpin the dramatic sex differences in cancer incidence and outcome. There are conceptual and practical challenges associated with considering sex as a biological variable, including the definition of sex itself and the need for novel study designs. A better understanding of cancer mechanisms, resulting in improved outcomes, will reward the effort invested in incorporating sex as a biological variable.

Distinct molecular etiologies of male and female hepatocellular carcinoma

BACKGROUND

Sex-differences in cancer occurrence and mortality are evident across tumor types; men exhibit higher rates of incidence and often poorer responses to treatment. Targeted approaches to the treatment of tumors that account for these sex-differences require the characterization and understanding of the fundamental biological mechanisms that differentiate them. Hepatocellular Carcinoma (HCC) is the second leading cause of cancer death worldwide, with the incidence rapidly rising. HCC exhibits a male-bias in occurrence and mortality, but previous studies have failed to explore the sex-specific dysregulation of gene expression in HCC.

METHODS

Here, we characterize the sex-shared and sex-specific regulatory changes in HCC tumors in the TCGA LIHC cohort using combined and sex-stratified differential expression and eQTL analyses.

RESULTS

By using a sex-specific differential expression analysis of tumor and tumor-adjacent samples, we uncovered etiologically relevant genes and pathways differentiating male and female HCC. While both sexes exhibited activation of pathways related to apoptosis and cell cycle, males and females differed in the activation of several signaling pathways, with females showing PPAR pathway enrichment while males showed PI3K, PI3K/AKT, FGFR, EGFR, NGF, GF1R, Rap1, DAP12, and IL-2 signaling pathway enrichment. Using eQTL analyses, we discovered germline variants with differential effects on tumor gene expression between the sexes. 24.3% of the discovered eQTLs exhibit differential effects between the sexes, illustrating the substantial role of sex in modifying the effects of eQTLs in HCC. The genes that showed sex-specific dysregulation in tumors and those that harbored a sex-specific eQTL converge in clinically relevant pathways, suggesting that the molecular etiologies of male and female HCC are partially driven by differential genetic effects on gene expression.

CONCLUSIONS

Sex-stratified analyses detect sex-specific molecular etiologies of HCC. Overall, our results provide new insight into the role of inherited genetic regulation of transcription in modulating sex-differences in HCC etiology and provide a framework for future studies on sex-biased cancers.

The Pregnancy Pickle: Evolved Immune Compensation Due to Pregnancy Underlies Sex Differences in Human Diseases

We hypothesize that, ancestrally, sex-specific immune modulation evolved to facilitate survival of the pregnant person in the presence of an invasive placenta and an immunologically challenging pregnancy - an idea we term the 'pregnancy compensation hypothesis' (PCH). Further, we propose that sex differences in immune function are mediated, at least in part, by the evolution of gene content and dosage on the sex chromosomes, and are regulated by reproductive hormones. Finally, we propose that changes in reproductive ecology in industrialized environments exacerbate these evolved sex differences, resulting in the increasing risk of autoimmune disease observed in females, and a counteracting reduction in diseases such as cancer that can be combated by heightened immune surveillance. The PCH generates a series of expectations that can be tested empirically and that may help to identify the mechanisms underlying sex differences in modern human diseases.

High GILT expression and an active and intact MHC class II antigen presentation pathway are associated with improved survival in melanoma

The MHC class I antigen presentation pathway in melanoma cells has a well-established role in immune-mediated destruction of tumors. However, the clinical significance of the MHC class II antigen presentation pathway in melanoma cells is less clear. In antigen presenting cells, gamma-interferon-inducible lysosomal thiol reductase (GILT) is critical for MHC class II-restricted presentation of multiple melanoma antigens. While not expressed in benign melanocytes of nevi, GILT and MHC class II expression is induced in malignant melanocytes in a portion of melanoma specimens. Analysis of The Cancer Genome Atlas (TCGA) cutaneous melanoma dataset showed that high GILT mRNA expression was associated with improved overall survival. Expression of IFN-γ, TNF-α, and IL-1β was positively associated with GILT expression in the TCGA melanoma specimens. These cytokines were capable of inducing GILT expression in melanoma cells in vitro. GILT protein expression in melanocytes was induced in halo nevi, which are nevi undergoing immune-mediated regression, and is consistent with the association of GILT expression with improved survival in melanoma. To explore potential mechanisms of GILT’s association with patient outcome, we analyzed the mRNA expression pattern in the MHC class II antigen presentation pathway. In contrast to healthy skin where the MHC class II pathway was nearly uniformly expressed and intact, there was substantial variation in the MHC class II pathway of the TCGA melanoma dataset. Both an active and intact MHC class II pathway were associated with improved overall survival in melanoma. These studies support a role for GILT and the MHC class II antigen presentation pathway in melanoma outcome.

Quantification of read species behavior within whole genome sequencing of cancer genomes for the stratification and visualization of genomic variation

The cancer genome is abnormal genome, and the ability to monitor its sequence had undergone a technological revolution. Yet prognosis and diagnosis remain an expert-based decision, with only limited abilities to provide machine-based decisions. We introduce a heterogeneity-based method for stratifying and visualizing whole-genome sequencing (WGS) reads. This method uses the heterogeneity within WGS reads to markedly reduce the dimensionality of next-generation sequencing data; it is available through the tool HiBS (Heterogeneity-Based Subclassification) that allows cancer sample classification. We validated HiBS using >200 WGS samples from nine different cancer types from The Cancer Genome Atlas (TCGA). With HiBS, we show progress with two WGS related issues: (i) differentiation between normal (NB) and tumor (TP) samples based solely on the information structure of their WGS data, and (ii) identification of specific regions of chromosomal amplification/deletion and their association with tumor stage. By comparing results to those obtained through available WGS analyses tools, we demonstrate some of the novelties obtained by the approach implemented in HiBS and also show nearly perfect normal/tumor classification, used to identify known and unknown chromosomal aberrations. Finally, the HiBS index has been associated with breast cancer tumor stage.

Systems analysis utilising pathway interactions identifies sonic hedgehog pathway as a primary biomarker and oncogenic target in hepatocellular carcinoma

The development and progression of cancer is associated with disruption of biological networks. Historically studies have identified sets of signature genes involved in events ultimately leading to the development of cancer. Identification of such sets does not indicate which biologic processes are oncogenic drivers and makes it difficult to identify key networks to target for interventions. Using a comprehensive, integrated computational approach, the authors identify the sonic hedgehog (SHH) pathway as the gene network that most significantly distinguishes tumour and tumour-adjacent samples in human hepatocellular carcinoma (HCC). The analysis reveals that the SHH pathway is commonly activated in the tumour samples and its activity most significantly differentiates tumour from the non-tumour samples. The authors experimentally validate these in silico findings in the same biologic material using Western blot analysis. This analysis reveals that the expression levels of SHH, phosphorylated cyclin B1, and CDK7 levels are much higher in most tumour tissues as compared to normal tissue. It is also shown that siRNA-mediated silencing of SHH gene expression resulted in a significant reduction of cell proliferation in a liver cancer cell line, SNU449 indicating that SHH plays a major role in promoting cell proliferation in liver cancer. The SHH pathway is a key network underpinning HCC aetiology which may guide the development of interventions for this most common form of human liver cancer.

Genome-wide transcriptional sequencing identifies novel mutations in metabolic genes in human hepatocellular carcinoma

We report on next-generation transcriptome sequencing results of three human hepatocellular carcinoma tumor/tumor-adjacent pairs. This analysis robustly examined ∼12,000 genes for both expression differences and molecular alterations. We observed 4,513 and 1,182 genes demonstrating 2-fold or greater increase or decrease in expression relative to their normal, respectively. Network analysis of expression data identified the Aurora B signaling, FOXM1 transcription factor network and Wnt signaling pathways pairs being altered in HCC. We validated as differential gene expression findings in a large data set containing of 434 liver normal/tumor sample pairs. In addition to known driver mutations in TP53 and CTNNB1, our mutation analysis identified non-synonymous mutations in genes implicated in metabolic diseases, i.e. diabetes and obesity: IRS1, HMGCS1, ATP8B1, PRMT6 and CLU, suggesting a common molecular etiology for HCC of alternative pathogenic origin.

Life sciences domain analysis model

Objective

Meaningful exchange of information is a fundamental challenge in collaborative biomedical research. To help address this, the authors developed the Life Sciences Domain Analysis Model (LS DAM), an information model that provides a framework for communication among domain experts and technical teams developing information systems to support biomedical research. The LS DAM is harmonized with the Biomedical Research Integrated Domain Group (BRIDG) model of protocol-driven clinical research. Together, these models can facilitate data exchange for translational research.

Materials and methods

The content of the LS DAM was driven by analysis of life sciences and translational research scenarios and the concepts in the model are derived from existing information models, reference models and data exchange formats. The model is represented in the Unified Modeling Language and uses ISO 21090 data types.

Results

The LS DAM v2.2.1 is comprised of 130 classes and covers several core areas including Experiment, Molecular Biology, Molecular Databases and Specimen. Nearly half of these classes originate from the BRIDG model, emphasizing the semantic harmonization between these models. Validation of the LS DAM against independently derived information models, research scenarios and reference databases supports its general applicability to represent life sciences research.

Discussion

The LS DAM provides unambiguous definitions for concepts required to describe life sciences research. The processes established to achieve consensus among domain experts will be applied in future iterations and may be broadly applicable to other standardization efforts.

Conclusions

The LS DAM provides common semantics for life sciences research. Through harmonization with BRIDG, it promotes interoperability in translational science.

CREBBP mutations in relapsed acute lymphoblastic leukaemia

Relapsed acute lymphoblastic leukaemia (ALL) is a leading cause of death due to disease in young people, but the biological determinants of treatment failure remain poorly understood. Recent genome-wide profiling of structural DNA alterations in ALL have identified multiple submicroscopic somatic mutations targeting key cellular pathways, and have demonstrated substantial evolution in genetic alterations from diagnosis to relapse. However, DNA sequence mutations in ALL have not been analysed in detail. To identify novel mutations in relapsed ALL, we resequenced 300 genes in matched diagnosis and relapse samples from 23 patients with ALL. This identified 52 somatic non-synonymous mutations in 32 genes, many of which were novel, including the transcriptional coactivators CREBBP and NCOR1, the transcription factors ERG, SPI1, TCF4 and TCF7L2, components of the Ras signalling pathway, histone genes, genes involved in histone modification (CREBBP and CTCF), and genes previously shown to be targets of recurring DNA copy number alteration in ALL. Analysis of an extended cohort of 71 diagnosis-relapse cases and 270 acute leukaemia cases that did not relapse found that 18.3% of relapse cases had sequence or deletion mutations of CREBBP, which encodes the transcriptional coactivator and histone acetyltransferase CREB-binding protein (CREBBP, also known as CBP). The mutations were either present at diagnosis or acquired at relapse, and resulted in truncated alleles or deleterious substitutions in conserved residues of the histone acetyltransferase domain. Functionally, the mutations impaired histone acetylation and transcriptional regulation of CREBBP targets, including glucocorticoid responsive genes. Several mutations acquired at relapse were detected in subclones at diagnosis, suggesting that the mutations may confer resistance to therapy. These results extend the landscape of genetic alterations in leukaemia, and identify mutations targeting transcriptional and epigenetic regulation as a mechanism of resistance in ALL.

Bambino: a variant detector and alignment viewer for next-generation sequencing data in the SAM/BAM format

SUMMARY

Bambino is a variant detector and graphical alignment viewer for next-generation sequencing data in the SAM/BAM format, which is capable of pooling data from multiple source files. The variant detector takes advantage of SAM-specific annotations, and produces detailed output suitable for genotyping and identification of somatic mutations. The assembly viewer can display reads in the context of either a user-provided or automatically generated reference sequence, retrieve genome annotation features from a UCSC genome annotation database, display histograms of non-reference allele frequencies, and predict protein-coding changes caused by SNPs.

AVAILABILITY

Bambino is written in platform-independent Java and available from https://cgwb.nci.nih.gov/goldenPath/bamview/documentation/index.html, along with documentation and example data. Bambino may be launched online via Java Web Start or downloaded and run locally.

Detecting cancer gene networks characterized by recurrent genomic alterations in a population

High resolution, system-wide characterizations have demonstrated the capacity to identify genomic regions that undergo genomic aberrations. Such research efforts often aim at associating these regions with disease etiology and outcome. Identifying the corresponding biologic processes that are responsible for disease and its outcome remains challenging. Using novel analytic methods that utilize the structure of biologic networks, we are able to identify the specific networks that are highly significantly, nonrandomly altered by regions of copy number amplification observed in a systems-wide analysis. We demonstrate this method in breast cancer, where the state of a subset of the pathways identified through these regions is shown to be highly associated with disease survival and recurrence.

Genetic variations at loci involved in the immune response are risk factors for hepatocellular carcinoma

Primary liver cancer is the third most common cause of cancer-related death worldwide, with a rising incidence in Western countries. Little is known about the genetic etiology of this disease. To identify genetic factors associated with hepatocellular carcinoma (HCC) and liver cirrhosis (LC), we conducted a comprehensive, genome-wide variation analysis in a population of unrelated Asian individuals. Copy number variation (CNV) and single nucleotide polymorphisms (SNPs) were assayed in peripheral blood with the high-density Affymetrix SNP6.0 microarray platform. We used a two-stage discovery and replication design to control for overfitting and to validate observed results. We identified a strong association with CNV at the T-cell receptor gamma and alpha loci (P < 1 × 10(-15)) in HCC cases when contrasted with controls. This variation appears to be somatic in origin, reflecting differences between T-cell receptor processing in lymphocytes from individuals with liver disease and healthy individuals that is not attributable to chronic hepatitis virus infection. Analysis of constitutional variation identified three susceptibility loci including the class II MHC complex, whose protein products present antigen to T-cell receptors and mediate immune surveillance. Statistical analysis of biologic networks identified variation in the "antigen presentation and processing" pathway as being highly significantly associated with HCC (P = 1 × 10(-11)). SNP analysis identified two variants whose allele frequencies differ significantly between HCC and LC. One of these (P = 1.74 × 10(-12)) lies in the PTEN homolog TPTE2.

CONCLUSION

Combined analysis of CNV, individual SNPs, and pathways suggest that HCC susceptibility is mediated by germline factors affecting the immune response and differences in T-cell receptor processing.

Using biomedical informatics to see the forest AND the trees for molecular diagnostics in cancer therapeutic development

Cancer research in general—and molecular diagnostic development in particular—are leveraging the diverse collection of publicly-accessible molecular information that underpins disease. The ability to access and integrate this information will be crucial to the development of molecular diagnostics. Use of this data requires overcoming the silos and data disconnects common throughout biomedicine and new models for interpreting this massive amount of information. The National Cancer Institute has developed the caBIG® initiative (Cancer Biomedical Informatics Grid) to integrate the diverse multidimensional data. An active area of research is developing biologic process models for integrating and interpreting this massive volume of data.

The Cancer Genome Atlas (TCGA) is an example of the challenges faced in transforming data to information. Large volumes of diverse, multidimensional data including various genomic characterizations and clinical information must be synthesized. Through the caBIG® generated Cancer Molecular Analysis portal (http://cma.nci.nih.gov), it is possible to see integrated views of the TCGA data from different research perspectives including genomic and clinical views. Tools leveraging this data can be used to display and analyze the data in biologic networks. As more TCGA data and additional molecular data are shared through the portal it will become increasingly possible to obtain a comprehensive view of the molecular basis of cancer and drive development of molecular diagnostics.

The BioPAX community standard for pathway data sharing

BioPAX (Biological Pathway Exchange) is a standard language to represent biological pathways at the molecular and cellular level. Its major use is to facilitate the exchange of pathway data (http://www.biopax.org). Pathway data captures our understanding of biological processes, but its rapid growth necessitates development of databases and computational tools to aid interpretation. However, the current fragmentation of pathway information across many databases with incompatible formats presents barriers to its effective use. BioPAX solves this problem by making pathway data substantially easier to collect, index, interpret and share. BioPAX can represent metabolic and signaling pathways, molecular and genetic interactions and gene regulation networks. BioPAX was created through a community process. Through BioPAX, millions of interactions organized into thousands of pathways across many organisms, from a growing number of sources, are available. Thus, large amounts of pathway data are available in a computable form to support visualization, analysis and biological discovery.

Novel pathway analysis of genomic polymorphism-cancer risk interaction in the Breast Cancer Prevention Trial

PURPOSE

Tamoxifen was approved for breast cancer risk reduction in high-risk women based on the National Surgical Adjuvant Breast and Bowel Project's Breast Cancer Prevention Trial (P-1:BCPT), which showed 50% fewer breast cancers with tamoxifen versus placebo, supporting tamoxifen's efficacy in preventing breast cancer. Poor metabolizing CYP2D6 variants are currently the subject of intensive scrutiny regarding their impact on clinical outcomes in the adjuvant setting. Our study extends to variants in a wider spectrum of tamoxifen-metabolizing genes and applies to the prevention setting.

METHODS

Our case-only study, nested within P-1:BCPT, explored associations of polymorphisms in estrogen/tamoxifen-metabolizing genes with responsiveness to preventive tamoxifen. Thirty-nine candidate polymorphisms in 17 candidate genes were genotyped in 249 P-1:BCPT cases.

RESULTS

CVP2D6_C1111T, individually and within a CYP2D6 haplotype, showed borderline significant association with treatment arm. Path analysis of the entire tamoxifen pathway gene network showed that the tamoxifen pathway model was consistent with the pattern of observed genotype variability within the placebo-arm dataset. However, correlation of variations in genes in the tamoxifen arm differed significantly from the predictions of the tamoxifen pathway model. Strong correlations between allelic variation in the tamoxifen pathway at CYP1A1-CYP3A4, CYP3A4-CYP2C9, and CYP2C9-SULT1A2, in addition to CYP2D6 and its adjacent genes, were seen in the placebo-arm but not the tamoxifen-arm. In conclusion, beyond reinforcing a role for CYP2D6 in tamoxifen response, our pathway analysis strongly suggests that specific combinations of allelic variants in other genes make major contributions to the tamoxifen-resistance phenotype.

Abstract LB-130: The NCI-Nature Pathway Interaction Database: A cell signaling resource

The NCI-Nature Pathway Interaction Database (PID, http://pid.nci.nih.gov) is a freely available collection of professionally curated and expert-reviewed signaling and regulatory pathways composed of human molecular interactions, signaling events and cellular processes extracted from primary literature. Pathways selected for curation are based on potential drug targets, suggestions made by our users and reviewers, and other prominent cell signaling molecules. As of February 2010, the database contains 106 pathways encompassing 6696 interactions, 3231 proteins, 142 small molecules, 2622 complexes and 4843 peer-reviewed publications, and includes recent additions to both the p53 and EGFR pathways. Created in a collaboration between the U.S. National Cancer Institute and Nature Publishing Group, the PID is aimed at researchers interested in cell signaling pathways, such as molecular cell biologists, and bioinformaticians. The database offers a range of tools to facilitate pathway exploration. Users can browse the pre-defined set of pathways and create network maps centered on a single molecule or biological process of interest. The Batch query tool allows users to upload molecule lists, such as those derived from microarray data, and visualize the resulting molecular connectivity map. In addition, users can download lists of proteins, references used to create the pathway and complete database content in extensible markup language (XML) or Biological Pathways Exchange (BioPAX) format. The database is updated every month and supplemented by a concise editorial section that provides synopses of recent noteworthy papers in cell signaling and specially commissioned articles on the practical uses of other relevant Bioinformatics tools. Users can sign up for email alerts or RSS feeds to receive database updates.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr LB-130.

The completion of the Mammalian Gene Collection (MGC)

Since its start, the Mammalian Gene Collection (MGC) has sought to provide at least one full-protein-coding sequence cDNA clone for every human and mouse gene with a RefSeq transcript, and at least 6200 rat genes. The MGC cloning effort initially relied on random expressed sequence tag screening of cDNA libraries. Here, we summarize our recent progress using directed RT-PCR cloning and DNA synthesis. The MGC now contains clones with the entire protein-coding sequence for 92% of human and 89% of mouse genes with curated RefSeq (NM-accession) transcripts, and for 97% of human and 96% of mouse genes with curated RefSeq transcripts that have one or more PubMed publications, in addition to clones for more than 6300 rat genes. These high-quality MGC clones and their sequences are accessible without restriction to researchers worldwide.

Enabling personalized medicine through an interoperable IT infrastructure: an overview of the cancer Biomedical Informatics Grid®

To implement personalized medicine successfully, multidisciplinary teams of collaborating scientists must manage and analyze vast quantities of genomic and clinical outcomes data in a cohesive and integrated way. This process is complex and not supported by the existing IT infrastructure and tools available to most researchers. To address these needs, the National Cancer Institute initiated the cancer Biomedical Informatics Grid initiative in 2004, to develop and deploy the interoperable IT infrastructure and tools needed to help basic and clinical researchers manage and share these data. Now, the cancer Biomedical Informatics Grid is being deployed to cancer centers and other biomedical research organizations across the USA and around the world, facilitating collaborative research that will ultimately lead to improved patient outcomes.

Global transcription in pluripotent embryonic stem cells

The molecular mechanisms underlying pluripotency and lineage specification from embryonic stem cells (ESCs) are largely unclear. Differentiation pathways may be determined by the targeted activation of lineage-specific genes or by selective silencing of genome regions. Here we show that the ESC genome is transcriptionally globally hyperactive and undergoes large-scale silencing as cells differentiate. Normally silent repeat regions are active in ESCs, and tissue-specific genes are sporadically expressed at low levels. Whole-genome tiling arrays demonstrate widespread transcription in coding and noncoding regions in ESCs, whereas the transcriptional landscape becomes more discrete as differentiation proceeds. The transcriptional hyperactivity in ESCs is accompanied by disproportionate expression of chromatin-remodeling genes and the general transcription machinery. We propose that global transcription is a hallmark of pluripotent ESCs, contributing to their plasticity, and that lineage specification is driven by reduction of the transcribed portion of the genome.

Global transcription in pluripotent embryonic stem cells

The molecular mechanisms underlying pluripotency and lineage specification from embryonic stem cells (ESCs) are largely unclear. Differentiation pathways may be determined by the targeted activation of lineage-specific genes or by selective silencing of genome regions. Here we show that the ESC genome is transcriptionally globally hyperactive and undergoes large-scale silencing as cells differentiate. Normally silent repeat regions are active in ESCs, and tissue-specific genes are sporadically expressed at low levels. Whole-genome tiling arrays demonstrate widespread transcription in coding and noncoding regions in ESCs, whereas the transcriptional landscape becomes more discrete as differentiation proceeds. The transcriptional hyperactivity in ESCs is accompanied by disproportionate expression of chromatin-remodeling genes and the general transcription machinery. We propose that global transcription is a hallmark of pluripotent ESCs, contributing to their plasticity, and that lineage specification is driven by reduction of the transcribed portion of the genome.

PID: the Pathway Interaction Database

The Pathway Interaction Database (PID, http://pid.nci.nih.gov) is a freely available collection of curated and peer-reviewed pathways composed of human molecular signaling and regulatory events and key cellular processes. Created in a collaboration between the US National Cancer Institute and Nature Publishing Group, the database serves as a research tool for the cancer research community and others interested in cellular pathways, such as neuroscientists, developmental biologists and immunologists. PID offers a range of search features to facilitate pathway exploration. Users can browse the predefined set of pathways or create interaction network maps centered on a single molecule or cellular process of interest. In addition, the batch query tool allows users to upload long list(s) of molecules, such as those derived from microarray experiments, and either overlay these molecules onto predefined pathways or visualize the complete molecular connectivity map. Users can also download molecule lists, citation lists and complete database content in extensible markup language (XML) and Biological Pathways Exchange (BioPAX) Level 2 format. The database is updated with new pathway content every month and supplemented by specially commissioned articles on the practical uses of other relevant online tools.

e-Science, caGrid, and Translational Biomedical Research

Translational research projects target a wide variety of diseases, test many different kinds of biomedical hypotheses, and employ a large assortment of experimental methodologies. Diverse data, complex execution environments, and demanding security and reliability requirements make the implementation of these projects extremely challenging and require novel e-Science technologies.

Allele-specific chromatin immunoprecipitation studies show genetic influence on chromatin state in human genome

Several recent studies have shown a genetic influence on gene expression variation, including variation between the two chromosomes within an individual and variation between individuals at the population level. We hypothesized that genetic inheritance may also affect variation in chromatin states. To test this hypothesis, we analyzed chromatin states in 12 lymphoblastoid cells derived from two Centre d'Etude du Polymorphisme Humain families using an allele-specific chromatin immunoprecipitation (ChIP-on-chip) assay with Affymetrix 10K SNP chip. We performed the allele-specific ChIP-on-chip assays for the 12 lymphoblastoid cells using antibodies targeting at RNA polymerase II and five post-translation modified forms of the histone H3 protein. The use of multiple cell lines from the Centre d'Etude du Polymorphisme Humain families allowed us to evaluate variation of chromatin states across pedigrees. These studies demonstrated that chromatin state clustered by family. Our results support the idea that genetic inheritance can determine the epigenetic state of the chromatin as shown previously in model organisms. To our knowledge, this is the first demonstration in humans that genetics may be an important factor that influences global chromatin state mediated by histone modification, the hallmark of the epigenetic phenomena.

Human health and disease are determined by an interaction between genetic background and environmental exposures. Both normal development and disease are mediated by epigenetic regulation of gene expression. The epigenetic regulation causes heritable changes in gene expression, which is not associated with DNA sequence changes. Instead, it is mediated by chemical modification of DNA such as DNA methylation or by protein modifications such as histone acetylation and methylation. Although much has been known about epigenetic inheritance during development, little is known about the influence of the genetic background on epigenetic processes such as histone modifications. In this report the authors studied five histone modifications on a genome-wide level in cells from different families. Global epigenetic states, as measured by these histone modifications, showed a similar pattern for cells derived from the same family. This study demonstrates that genetic inheritance may be an important factor influencing global chromatin states mediated by histone modifications in humans. These observations illustrate the importance of integrating genetic and epigenetic information into studies of human health and complex diseases.

Systematic analysis of genetic alterations in tumors using Cancer Genome WorkBench (CGWB)

Systematic investigations of genetic changes in tumors are expected to lead to greatly improved understanding of cancer etiology. To meet the analytical challenges presented by such studies, we developed the Cancer Genome WorkBench (http://cgwb.nci.nih.gov), the first computational platform to integrate clinical tumor mutation profiles with the reference human genome. A novel heuristic algorithm, IndelDetector, was developed to automatically identify insertion/deletion (indel) polymorphisms as well as indel somatic mutations with high sensitivity and accuracy. It was incorporated into an automated pipeline that detects genetic alterations and annotates their effects on protein coding and 3D structure. The ability of the system to facilitate identifying genetic alterations is illustrated in three projects with publicly accessible data. Mutagenesis in tumor DNA replication leading to complex genetic changes in the EGFR kinase domain is suggested by a novel deletion-insertion combination observed in paired tumor-normal lung cancer resequencing data. Automated analysis of 152 genes resequenced by the SeattleSNPs group was able to identify 91% of the 1251 indel polymorphisms discovered by SeattleSNPs. In addition, our system discovered 518 novel indels in this data set, 451 of which were found to be valid by manual inspection of sequence traces. Our experience demonstrates that CGWB not only greatly improves the productivity and the accuracy of mutation identification, but also, through its data integration and visualization capabilities, facilitates identification of underlying genetic etiology.

Identification of key processes underlying cancer phenotypes using biologic pathway analysis

Cancer is recognized to be a family of gene-based diseases whose causes are to be found in disruptions of basic biologic processes. An increasingly deep catalogue of canonical networks details the specific molecular interaction of genes and their products. However, mapping of disease phenotypes to alterations of these networks of interactions is accomplished indirectly and non-systematically. Here we objectively identify pathways associated with malignancy, staging, and outcome in cancer through application of an analytic approach that systematically evaluates differences in the activity and consistency of interactions within canonical biologic processes. Using large collections of publicly accessible genome-wide gene expression, we identify small, common sets of pathways – Trka Receptor, Apoptosis response to DNA Damage, Ceramide, Telomerase, CD40L and Calcineurin – whose differences robustly distinguish diverse tumor types from corresponding normal samples, predict tumor grade, and distinguish phenotypes such as estrogen receptor status and p53 mutation state. Pathways identified through this analysis perform as well or better than phenotypes used in the original studies in predicting cancer outcome. This approach provides a means to use genome-wide characterizations to map key biological processes to important clinical features in disease.

SNPdetector: a software tool for sensitive and accurate SNP detection

Identification of single nucleotide polymorphisms (SNPs) and mutations is important for the discovery of genetic predisposition to complex diseases. PCR resequencing is the method of choice for de novo SNP discovery. However, manual curation of putative SNPs has been a major bottleneck in the application of this method to high-throughput screening. Therefore it is critical to develop a more sensitive and accurate computational method for automated SNP detection. We developed a software tool, SNPdetector, for automated identification of SNPs and mutations in fluorescence-based resequencing reads. SNPdetector was designed to model the process of human visual inspection and has a very low false positive and false negative rate. We demonstrate the superior performance of SNPdetector in SNP and mutation analysis by comparing its results with those derived by human inspection, PolyPhred (a popular SNP detection tool), and independent genotype assays in three large-scale investigations. The first study identified and validated inter- and intra-subspecies variations in 4,650 traces of 25 inbred mouse strains that belong to either the Mus musculus species or the M. spretus species. Unexpected heterozygosity in CAST/Ei strain was observed in two out of 1,167 mouse SNPs. The second study identified 11,241 candidate SNPs in five ENCODE regions of the human genome covering 2.5 Mb of genomic sequence. Approximately 50% of the candidate SNPs were selected for experimental genotyping; the validation rate exceeded 95%. The third study detected ENU-induced mutations (at 0.04% allele frequency) in 64,896 traces of 1,236 zebra fish. Our analysis of three large and diverse test datasets demonstrated that SNPdetector is an effective tool for genome-scale research and for large-sample clinical studies. SNPdetector runs on Unix/Linux platform and is available publicly (http://lpg.nci.nih.gov).

ATG deserts define a novel core promoter subclass

The MHC class I gene, PD1, has neither functional TATAA nor Initiator (Inr) elements in its core promoter and initiates transcription at multiple, dispersed sites over an extended region in vitro. Here, we define a novel core promoter feature that supports regulated transcription through selective transcription start site (TSS) usage. We demonstrate that TSS selection is actively regulated and context dependent. Basal and activated transcriptions initiate from largely nonoverlapping TSS regions. Transcripts derived from multiple TSS encode a single protein, due to the absence of any ATG triplets within approximately 430 bp upstream of the major transcription start site. Thus, the PD1 core promoter is embedded within an "ATG desert". Remarkably, extending this analysis genome-wide, we find that ATG deserts define a novel promoter subclass. They occur nonrandomly, are significantly associated with non-TATAA promoters that use multiple TSS, independent of the presence of CpG islands (CGI). We speculate that ATG deserts may provide a core promoter platform upon which complex upstream regulatory signals can be integrated, targeting multiple TSS whose products encode a single protein.

Detecting false expression signals in high-density oligonucleotide arrays by an in silico approach

High-density oligonucleotide arrays have become a popular assay for concurrent measurement of mRNA expression at the genome scale. Much effort has been devoted to the development of statistical analysis tools aimed at reducing experimental noise and normalizing experimental variation in gene expression analysis. However, these investigations do not detect or catalog systematic problems associated with specific oligonucleotide probes. Here, we present an investigation of problematic probes that yield consistent but inaccurate signals across multiple experiments. By evaluating data integrity among gene, probe sequence, and genomic structure we identified a total of 20,696 (10.5%) nonspecific probes that could cross-hybridize to multiple genes and a total of 18,363 (9.3%) probes that miss the target transcript sequences on the Affymetrix GeneChip U95A/Av2 array. The numbers of nonspecific and mistargeted probes on the U133A array are 29,405 (12.1%) and 19,717 (8.0%), respectively. The poor performance of the mistargeted probes was confirmed in two GeneChip experiments, in which these probes showed a 20-30% decrease in detecting present signals compared with normal probes. Comparison of qualitative expression signals obtained from SAGE and EST data with those from GeneChip arrays showed that the consistency of the two platforms is 30% lower in problematic probes than in normal probes. A Web application was developed to apply our results for improving the accuracy of expression analysis.

Genome-wide association study in esophageal cancer using GeneChip mapping 10K array

Whole genome association studies of complex human diseases represent a new paradigm in the postgenomic era. In this study, we report application of the Affymetrix, Inc. (Santa Clara, CA) high-density single nucleotide polymorphism (SNP) array containing 11,555 SNPs in a pilot case-control study of esophageal squamous cell carcinoma (ESCC) that included the analysis of germ line samples from 50 ESCC patients and 50 matched controls. The average genotyping call rate for the 100 samples analyzed was 96%. Using the generalized linear model (GLM) with adjustment for potential confounders and multiple comparisons, we identified 37 SNPs associated with disease, assuming a recessive mode of transmission; similarly, 48 SNPs were identified assuming a dominant mode and 53 SNPs in a continuous mode. When the 37 SNPs identified from the GLM recessive mode were used in a principal components analysis, the first principal component correctly predicted 46 of 50 cases and 47 of 50 controls. Among all the SNPs selected from GLMs for the three modes of transmission, 39 could be mapped to 1 of 33 genes. Many of these genes are involved in various cancers, including GASC1, shown previously to be amplified in ESCCs, and EPHB1 and PIK3C3. In conclusion, we have shown the feasibility of the Affymetrix 10K SNP array in genome-wide association studies of common cancers and identified new candidate loci to study in ESCC.

Cyberinfrastructure: empowering a "third way" in biomedical research

Biomedicine has experienced explosive growth, fueled in parts by the substantial increase of government support, continued development of the biotechnology industry, and the increasing adoption of molecular-based medicine. At its core, it is composed of fiercely independent, innovative, entrepreneurial individuals, organizations, and institutions. The field has developed unprecedented capacity to characterize biologic systems at their most fundamental levels with the use of tools and technologies almost unimaginable a generation ago. Biomedicine is at the precipice of unlocking the very essence of biologic life and enabling a new generation of medicine. Development and deployment of cyberinfrastructure may prove to be on the critical path to obtaining these goals.

A high-resolution multistrain haplotype analysis of laboratory mouse genome reveals three distinctive genetic variation patterns

Understanding of the structure and the origin of genetic variation patterns in the laboratory inbred mouse provides insight into the utility of the mouse model for studying human complex diseases and strategies for disease gene mapping. In order to address this issue, we have constructed a multistrain, high-resolution haplotype map for the 99-Mb mouse Chromosome 16 using approximately 70,000 single nucleotide polymorphism (SNP) markers derived from whole-genome shotgun sequencing of five laboratory inbred strains. We discovered that large polymorphic blocks (i.e., regions where only two haplotypes, thus one SNP conformation, are found in the five strains), large monomorphic blocks (i.e., regions where the five strains share the same haplotype), and fragmented blocks (i.e., regions of greater complexity not resembling at all the first two categories) span 50%, 18%, and 32% of the chromosome, respectively. The haplotype map has 98% accuracy in predicting mouse genotypes in two other studies. Its predictions are also confirmed by experimental results obtained from resequencing of 40-kb genomic sequences at 21 distinct genomic loci in 13 laboratory inbred strains and 12 wild-derived strains. We demonstrate that historic recombination, intra-subspecies variations and inter-subspecies variations have all contributed to the formation of the three distinctive genetic signatures. The results suggest that the controlled complexity of the laboratory inbred strains may provide a means for uncovering the biological factors that have shaped genetic variation patterns.

A computational approach to measuring coherence of gene expression in pathways

This study uses a computational approach to analyze coherence of expression of genes in pathways. Microarray data were analyzed with respect to coherent gene expression in a group of genes defined as a pathway in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Our hypothesis is that genes in the same pathway are more likely to be coordinately regulated than a randomly selected gene set. A correlation coefficient for each pair of genes in a pathway was estimated based on gene expression in normal or tumor samples, and statistically significant correlation coefficients were identified. The coherence indicator was defined as the ratio of the number of gene pairs in the pathway whose correlation coefficients are significant, divided by the total number of gene pairs in the pathway. We defined all genes that appeared in the KEGG pathways as a reference gene set. Our analysis indicated that the mean coherence indicator of pathways is significantly larger than the mean coherence indicator of random gene sets drawn from the reference gene set. Thus, the result supports our hypothesis. The significance of each individual pathway of n genes was evaluated by comparing its coherence indicator with coherence indicators of 1000 random permutation sets of n genes chosen from the reference gene set. We analyzed three data sets: two Affymetrix microarrays and one cDNA microarray. For each of the three data sets, statistically significant pathways were identified among all KEGG pathways. Seven of 96 pathways had a significant coherence indicator in normal tissue and 14 of 96 pathways had a significant coherence indicator in tumor tissue in all three data sets. The increase in the number of pathways with significant coherence indicators may reflect the fact that tumor cells have a higher rate of metabolism than normal cells. Five pathways involved in oxidative phosphorylation, ATP synthesis, protein synthesis, or RNA synthesis were coherent in both normal and tumor tissue, demonstrating that these are essential genes, a high level of expression of which is required regardless of cell type.