Decoding the Genomics of Abdominal Aortic Aneurysm.

A key aspect of genomic medicine is to make individualized clinical decisions from personal genomes. We developed a machine-learning framework to integrate personal genomes and electronic health record (EHR) data and used this framework to study abdominal aortic aneurysm (AAA), a prevalent irreversible cardiovascular disease with unclear etiology. Performing whole-genome sequencing on AAA patients and controls, we demonstrated its predictive precision solely from personal genomes. By modeling personal genomes with EHRs, this framework quantitatively assessed the effectiveness of adjusting personal lifestyles given personal genome baselines, demonstrating its utility as a personal health management tool. We showed that this new framework agnostically identified genetic components involved in AAA, which were subsequently validated in human aortic tissues and in murine models. Our study presents a new framework for disease genome analysis, which can be used for both health management and understanding the biological architecture of complex diseases. VIDEO ABSTRACT.

Autoimmune alleles at the major histocompatibility locus modify melanoma susceptibility.

Autoimmunity and cancer represent two different aspects of immune dysfunction. Autoimmunity is characterized by breakdowns in immune self-tolerance, while impaired immune surveillance can allow for tumorigenesis. The class I major histocompatibility complex (MHC-I), which displays derivatives of the cellular peptidome for immune surveillance by CD8+ T cells, serves as a common genetic link between these conditions. As melanoma-specific CD8+ T cells have been shown to target melanocyte-specific peptide antigens more often than melanoma-specific antigens, we investigated whether vitiligo- and psoriasis-predisposing MHC-I alleles conferred a melanoma-protective effect. In individuals with cutaneous melanoma from both The Cancer Genome Atlas (n = 451) and an independent validation set (n = 586), MHC-I autoimmune-allele carrier status was significantly associated with a later age of melanoma diagnosis. Furthermore, MHC-I autoimmune-allele carriers were significantly associated with decreased risk of developing melanoma in the Million Veteran Program (OR = 0.962, p = 0.024). Existing melanoma polygenic risk scores (PRSs) did not predict autoimmune-allele carrier status, suggesting these alleles provide orthogonal risk-relevant information. Mechanisms of autoimmune protection were neither associated with improved melanoma-driver mutation association nor improved gene-level conserved antigen presentation relative to common alleles. However, autoimmune alleles showed higher affinity relative to common alleles for particular windows of melanocyte-conserved antigens and loss of heterozygosity of autoimmune alleles caused the greatest reduction in presentation for several conserved antigens across individuals with loss of HLA alleles. Overall, this study presents evidence that MHC-I autoimmune-risk alleles modulate melanoma risk unaccounted for by current PRSs.

High-frequency and functional mitochondrial DNA mutations at the single-cell level.

Decline in mitochondrial function underlies aging and age-related diseases, but the role of mitochondrial DNA (mtDNA) mutations in these processes remains elusive. To investigate patterns of mtDNA mutations, it is particularly important to quantify mtDNA mutations and their associated pathogenic effects at the single-cell level. However, existing single-cell mtDNA sequencing approaches remain inefficient due to high cost and low mtDNA on-target rates. In this study, we developed a cost-effective mtDNA targeted-sequencing protocol called single-cell sequencing by targeted amplification of multiplex probes (scSTAMP) and experimentally validated its reliability. We then applied our method to assess single-cell mtDNA mutations in 768 B lymphocytes and 768 monocytes from a 76-y-old female. Across 632 B lymphocyte and 617 monocytes with medium mtDNA coverage over >100×, our results indicated that over 50% of cells carried at least one mtDNA mutation with variant allele frequencies (VAFs) over 20%, and that cells carried an average of 0.658 and 0.712 such mutation for B lymphocytes and monocytes, respectively. Surprisingly, more than 20% of the observed mutations had VAFs of over 90% in either cell population. In addition, over 60% of the mutations were in protein-coding genes, of which over 70% were nonsynonymous, and more than 50% of the nonsynonymous mutations were predicted to be highly pathogenic. Interestingly, about 80% of the observed mutations were singletons in the respective cell populations. Our results revealed mtDNA mutations with functional significance might be prevalent at advanced age, calling further investigation on age-related mtDNA mutation dynamics at the single-cell level.

Studies Related to the Involvement of EsA in Improving Intestinal Inflammation in Acute Pancreatitis via the NF-κB Pathway.

Background: Acute pancreatitis (AP) is a clinically frequent acute abdominal condition, which refers to an inflammatory response syndrome of edema, bleeding, and even necrosis caused by abnormal activation of the pancreas's own digestive enzymes. Intestinal damage can occur early in the course of AP and is manifested by impaired intestinal mucosal barrier function, and inflammatory reactions of the intestinal mucosa, among other factors. It can cause translocation of intestinal bacteria and endotoxins, further aggravating the condition of AP. Therefore, actively protecting the intestinal mucosal barrier, controlling the progression of intestinal inflammation, and improving intestinal dynamics in the early stages of AP play an important role in enhancing the prognosis of AP. Methods: The viability and apoptosis of RAW264.7 cells treated with Esculentoside A (EsA) and/or lipopolysaccharide were detected using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) and flow cytometry, respectively. The expression of apoptosis-related proteins and NF-κB signaling pathway-related proteins were detected by western blot (WB). An enzyme-linked immunosorbent assay was used to measure TNF-α and IL-6 secretion. Results: In vitro experiments demonstrated that EsA not only promoted the apoptosis of inflammatory cells but also reduced the secretion of TNF-α and IL-6 in a dose-dependent manner. Additionally, it inhibited the activation of the NF-κB signaling pathway by decreasing the expression of phosphorylated-p65(p-p65) and elevating the expression of IκBα. Similarly, in vivo experiments using a rat AP model showed that EsA inhibited the expression of p-p65 elevating the expression of IκBα in the intestinal tissues of the rat AP model and promoting the apoptosis of inflammatory cells in the intestinal mucosa in vivo experiments, while improving the pathological outcome of the pancreatic and intestinal tissues. Conclusion: Our results suggest that EsA can reduce intestinal inflammation in the rat AP model and that EsA may be a candidate for treating intestinal inflammation in AP and further arresting AP progression.

Genotyping Array Design and Data Quality Control in the Million Veteran Program.

The Million Veteran Program (MVP), initiated by the Department of Veterans Affairs (VA), aims to collect biosamples with consent from at least one million veterans. Presently, blood samples have been collected from over 800,000 enrolled participants. The size and diversity of the MVP cohort, as well as the availability of extensive VA electronic health records, make it a promising resource for precision medicine. MVP is conducting array-based genotyping to provide a genome-wide scan of the entire cohort, in parallel with whole-genome sequencing, methylation, and other 'omics assays. Here, we present the design and performance of the MVP 1.0 custom Axiom array, which was designed and developed as a single assay to be used across the multi-ethnic MVP cohort. A unified genetic quality-control analysis was developed and conducted on an initial tranche of 485,856 individuals, leading to a high-quality dataset of 459,777 unique individuals. 668,418 genetic markers passed quality control and showed high-quality genotypes not only on common variants but also on rare variants. We confirmed that, with non-European individuals making up nearly 30%, MVP's substantial ancestral diversity surpasses that of other large biobanks. We also demonstrated the quality of the MVP dataset by replicating established genetic associations with height in European Americans and African Americans ancestries. This current dataset has been made available to approved MVP researchers for genome-wide association studies and other downstream analyses. Further data releases will be available for analysis as recruitment at the VA continues and the cohort expands both in size and diversity.

Combined therapy of prednisone and mTOR inhibitor sirolimus for treating retroperitoneal fibrosis.

OBJECTIVES: Retroperitoneal fibrosis (RPF) is a rare autoimmune disease with fibrous tissue growth and inflammation in retroperitoneum. Its current treatments involve long-term uptake of glucocorticoids (e.g., prednisone) for controlling inflammation; however, side effects are common. We strived for an improved therapy for fibrosis remission while reducing side effects. METHODS: We surveyed gene-disease-drug databases and discovered that mammalian target of rapamycin (mTOR) was a key signalling protein in RPF and the mTOR inhibitor compound sirolimus affected many RPF pathways. We designed a therapy combining a gradual reduction of prednisone with a long-term, stable dosage of sirolimus. We then implemented a single-arm clinical trial and assessed the effects in eight RPF patients at 0, 12 and 48 weeks of treatment by measuring fibrous tissue mass by CT, markers of inflammation and kidney functions by lab tests, immune cell profiles by flow cytometry and plasma inflammatory proteins by Olink proteomics. RESULTS: With the combined therapy, fibrous tissue shrunk about by half, markers of acute inflammation reduced by 70% and most patients with abnormal kidney functions had them restored to normal range. Molecularly, fibrosis-related T cell subsets, including TH2, TH17 and circulating TFH cells, were reduced and tumour necrosis factor and related cytokines restored to healthy levels. No severe long-term side effects were observed. CONCLUSIONS: Our combined therapy resulted in significant fibrosis remission and an overall regression of the immune system towards healthy states, while achieving good tolerance. We concluded that this new therapy had the potential to replace the steroid monotherapy for treating RPF.

Hummingbird: efficient performance prediction for executing genomic applications in the cloud.

MOTIVATION: A major drawback of executing genomic applications on cloud computing facilities is the lack of tools to predict which instance type is the most appropriate, often resulting in an over- or under- matching of resources. Determining the right configuration before actually running the applications will save money and time. Here, we introduce Hummingbird, a tool for predicting performance of computing instances with varying memory and CPU on multiple cloud platforms. RESULTS: Our experiments on three major genomic data pipelines, including GATK HaplotypeCaller, GATK Mutect2 and ENCODE ATAC-seq, showed that Hummingbird was able to address applications in command line specified in JSON format or workflow description language (WDL) format, and accurately predicted the fastest, the cheapest and the most cost-efficient compute instances in an economic manner. AVAILABILITY AND IMPLEMENTATION: Hummingbird is available as an open source tool at: https://github.com/StanfordBioinformatics/Hummingbird. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Swarm: A federated cloud framework for large-scale variant analysis.

Genomic data analysis across multiple cloud platforms is an ongoing challenge, especially when large amounts of data are involved. Here, we present Swarm, a framework for federated computation that promotes minimal data motion and facilitates crosstalk between genomic datasets stored on various cloud platforms. We demonstrate its utility via common inquiries of genomic variants across BigQuery in the Google Cloud Platform (GCP), Athena in the Amazon Web Services (AWS), Apache Presto and MySQL. Compared to single-cloud platforms, the Swarm framework significantly reduced computational costs, run-time delays and risks of security breach and privacy violation.

Association of serum klotho levels with different-staged vascular calcification status in patients with maintenance hemodialysis.

BACKGROUND: Vascular calcification (VC) is suggested to be associated with serum klotho levels in patients with maintenance hemodialysis (MHD), whereas there is a lack of reports on the associations of VC status in whole arteries with serum klotho contents. METHODS: One hundred forty eligible patients with MHD and a total of age-and gender-matched normal controls (NCs) were recruited. We analyzed the VC statuses of large arteries and peripheral muscular arteries by calculating the sum of scores from each artery. The levels of serum klotho were determined by ELISA. In addition, the relationship between serum klotho and VC status was evaluated using correlation analysis and regression analysis. RESULTS: The VC severity in MHD patients tended to be worse in comparison with NCs. Serum klotho level in patients with MHD was lower than that in the NC subjects (​P < 0.0001), which was correlated with VC scores as reflected by correlation analysis and regression analysis. Serum klotho concentrations exhibited a dynamic decline along with increased VC status stages. Subjects with higher levels of serum klotho had a higher prevalence of cardiovascular events. CONCLUSION: Our study indicates serum klotho is strongly associated with VC status in a stage-dependent manner.

Genetic Architecture of Abdominal Aortic Aneurysm in the Million Veteran Program.

BACKGROUND: Abdominal aortic aneurysm (AAA) is an important cause of cardiovascular mortality; however, its genetic determinants remain incompletely defined. In total, 10 previously identified risk loci explain a small fraction of AAA heritability. METHODS: We performed a genome-wide association study in the Million Veteran Program testing ≈18 million DNA sequence variants with AAA (7642 cases and 172 172 controls) in veterans of European ancestry with independent replication in up to 4972 cases and 99 858 controls. We then used mendelian randomization to examine the causal effects of blood pressure on AAA. We examined the association of AAA risk variants with aneurysms in the lower extremity, cerebral, and iliac arterial beds, and derived a genome-wide polygenic risk score (PRS) to identify a subset of the population at greater risk for disease. RESULTS: Through a genome-wide association study, we identified 14 novel loci, bringing the total number of known significant AAA loci to 24. In our mendelian randomization analysis, we demonstrate that a genetic increase of 10 mm Hg in diastolic blood pressure (odds ratio, 1.43 [95% CI, 1.24-1.66]; P=1.6×10-6), as opposed to systolic blood pressure (odds ratio, 1.06 [95% CI, 0.97-1.15]; P=0.2), likely has a causal relationship with AAA development. We observed that 19 of 24 AAA risk variants associate with aneurysms in at least 1 other vascular territory. A 29-variant PRS was strongly associated with AAA (odds ratioPRS, 1.26 [95% CI, 1.18-1.36]; PPRS=2.7×10-11 per SD increase in PRS), independent of family history and smoking risk factors (odds ratioPRS+family history+smoking, 1.24 [95% CI, 1.14-1.35]; PPRS=1.27×10-6). Using this PRS, we identified a subset of the population with AAA prevalence greater than that observed in screening trials informing current guidelines. CONCLUSIONS: We identify novel AAA genetic associations with therapeutic implications and identify a subset of the population at significantly increased genetic risk of AAA independent of family history. Our data suggest that extending current screening guidelines to include testing to identify those with high polygenic AAA risk, once the cost of genotyping becomes comparable with that of screening ultrasound, would significantly increase the yield of current screening at reasonable cost.

PP2A delays APC/C-dependent degradation of separase-associated but not free securin.

The universal triggering event of eukaryotic chromosome segregation is cleavage of centromeric cohesin by separase. Prior to anaphase, most separase is kept inactive by association with securin. Protein phosphatase 2A (PP2A) constitutes another binding partner of human separase, but the functional relevance of this interaction has remained enigmatic. We demonstrate that PP2A stabilizes separase-associated securin by dephosphorylation, while phosphorylation of free securin enhances its polyubiquitylation by the ubiquitin ligase APC/C and proteasomal degradation. Changing PP2A substrate phosphorylation sites to alanines slows degradation of free securin, delays separase activation, lengthens early anaphase, and results in anaphase bridges and DNA damage. In contrast, separase-associated securin is destabilized by introduction of phosphorylation-mimetic aspartates or extinction of separase-associated PP2A activity. G2- or prometaphase-arrested cells suffer from unscheduled activation of separase when endogenous securin is replaced by aspartate-mutant securin. Thus, PP2A-dependent stabilization of separase-associated securin prevents precocious activation of separase during checkpoint-mediated arrests with basal APC/C activity and increases the abruptness and fidelity of sister chromatid separation in anaphase.

Cloud-based interactive analytics for terabytes of genomic variants data.

MOTIVATION: Large scale genomic sequencing is now widely used to decipher questions in diverse realms such as biological function, human diseases, evolution, ecosystems, and agriculture. With the quantity and diversity these data harbor, a robust and scalable data handling and analysis solution is desired. RESULTS: We present interactive analytics using a cloud-based columnar database built on Dremel to perform information compression, comprehensive quality controls, and biological information retrieval in large volumes of genomic data. We demonstrate such Big Data computing paradigms can provide orders of magnitude faster turnaround for common genomic analyses, transforming long-running batch jobs submitted via a Linux shell into questions that can be asked from a web browser in seconds. Using this method, we assessed a study population of 475 deeply sequenced human genomes for genomic call rate, genotype and allele frequency distribution, variant density across the genome, and pharmacogenomic information. AVAILABILITY AND IMPLEMENTATION: Our analysis framework is implemented in Google Cloud Platform and BigQuery. Codes are available at https://github.com/StanfordBioinformatics/mvp_aaa_codelabs. CONTACT: cuiping@stanford.edu or ptsao@stanford.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Sequence to Medical Phenotypes: A Framework for Interpretation of Human Whole Genome DNA Sequence Data.

High throughput sequencing has facilitated a precipitous drop in the cost of genomic sequencing, prompting predictions of a revolution in medicine via genetic personalization of diagnostic and therapeutic strategies. There are significant barriers to realizing this goal that are related to the difficult task of interpreting personal genetic variation. A comprehensive, widely accessible application for interpretation of whole genome sequence data is needed. Here, we present a series of methods for identification of genetic variants and genotypes with clinical associations, phasing genetic data and using Mendelian inheritance for quality control, and providing predictive genetic information about risk for rare disease phenotypes and response to pharmacological therapy in single individuals and father-mother-child trios. We demonstrate application of these methods for disease and drug response prognostication in whole genome sequence data from twelve unrelated adults, and for disease gene discovery in one father-mother-child trio with apparently simplex congenital ventricular arrhythmia. In doing so we identify clinically actionable inherited disease risk and drug response genotypes in pre-symptomatic individuals. We also nominate a new candidate gene in congenital arrhythmia, ATP2B4, and provide experimental evidence of a regulatory role for variants discovered using this framework.

Clinical interpretation and implications of whole-genome sequencing.

IMPORTANCE: Whole-genome sequencing (WGS) is increasingly applied in clinical medicine and is expected to uncover clinically significant findings regardless of sequencing indication. OBJECTIVES: To examine coverage and concordance of clinically relevant genetic variation provided by WGS technologies; to quantitate inherited disease risk and pharmacogenomic findings in WGS data and resources required for their discovery and interpretation; and to evaluate clinical action prompted by WGS findings. DESIGN, SETTING, AND PARTICIPANTS: An exploratory study of 12 adult participants recruited at Stanford University Medical Center who underwent WGS between November 2011 and March 2012. A multidisciplinary team reviewed all potentially reportable genetic findings. Five physicians proposed initial clinical follow-up based on the genetic findings. MAIN OUTCOMES AND MEASURES: Genome coverage and sequencing platform concordance in different categories of genetic disease risk, person-hours spent curating candidate disease-risk variants, interpretation agreement between trained curators and disease genetics databases, burden of inherited disease risk and pharmacogenomic findings, and burden and interrater agreement of proposed clinical follow-up. RESULTS: Depending on sequencing platform, 10% to 19% of inherited disease genes were not covered to accepted standards for single nucleotide variant discovery. Genotype concordance was high for previously described single nucleotide genetic variants (99%-100%) but low for small insertion/deletion variants (53%-59%). Curation of 90 to 127 genetic variants in each participant required a median of 54 minutes (range, 5-223 minutes) per genetic variant, resulted in moderate classification agreement between professionals (Gross κ, 0.52; 95% CI, 0.40-0.64), and reclassified 69% of genetic variants cataloged as disease causing in mutation databases to variants of uncertain or lesser significance. Two to 6 personal disease-risk findings were discovered in each participant, including 1 frameshift deletion in the BRCA1 gene implicated in hereditary breast and ovarian cancer. Physician review of sequencing findings prompted consideration of a median of 1 to 3 initial diagnostic tests and referrals per participant, with fair interrater agreement about the suitability of WGS findings for clinical follow-up (Fleiss κ, 0.24; P < 001). CONCLUSIONS AND RELEVANCE: In this exploratory study of 12 volunteer adults, the use of WGS was associated with incomplete coverage of inherited disease genes, low reproducibility of detection of genetic variation with the highest potential clinical effects, and uncertainty about clinically reportable findings. In certain cases, WGS will identify clinically actionable genetic variants warranting early medical intervention. These issues should be considered when determining the role of WGS in clinical medicine.

Abdominal aortic aneurysm and cardiometabolic traits share strong genetic susceptibility to lipid metabolism and inflammation.

Abdominal aortic aneurysm has a high heritability and often co-occurs with other cardiometabolic disorders, suggesting shared genetic susceptibility. We investigate this commonality leveraging recent GWAS studies of abdominal aortic aneurysm and 32 cardiometabolic traits. We find significant genetic correlations between abdominal aortic aneurysm and 21 of the cardiometabolic traits investigated, including causal relationships with coronary artery disease, hypertension, lipid traits, and blood pressure. For each trait pair, we identify shared causal variants, genes, and pathways, revealing that cholesterol metabolism and inflammation are shared most prominently. Additionally, we show the tissue and cell type specificity in the shared signals, with strong enrichment across traits in the liver, arteries, adipose tissues, macrophages, adipocytes, and fibroblasts. Finally, we leverage drug-gene databases to identify several lipid-lowering drugs and antioxidants with high potential to treat abdominal aortic aneurysm with comorbidities. Our study provides insight into the shared genetic mechanism between abdominal aortic aneurysm and cardiometabolic traits, and identifies potential targets for pharmacological intervention.

Polygenic risk score predicts all-cause death in East Asian patients with prior coronary artery disease.

Introduction: Coronary artery disease (CAD) is a highly heritable and multifactorial disease. Numerous genome-wide association studies (GWAS) facilitated the construction of polygenic risk scores (PRS) for predicting future incidence of CAD, however, exclusively in European populations. Furthermore, identifying CAD patients with elevated risks of all-cause death presents a critical challenge in secondary prevention, which will contribute largely to reducing the burden for public healthcare. Methods: We recruited a cohort of 1,776 Chinese CAD patients and performed medical follow-up for up to 11 years. A pruning and thresholding method was used to calculate PRS of CAD and its 14 risk factors. Their correlations with all-cause death were computed via Cox regression. Results and discussion: We found that the PRS for CAD and its seven risk factors, namely myocardial infarction, ischemic stroke, angina, heart failure, low-density lipoprotein cholesterol, total cholesterol and C-reaction protein, were significantly associated with death (P ≤ 0.05), whereas the PRS of body mass index displayed moderate association (P < 0.1). Elastic-net Cox regression with 5-fold cross-validation was used to integrate these nine PRS models into a meta score, metaPRS, which performed well in stratifying patients at different risks for death (P < 0.0001). Combining metaPRS with clinical risk factors further increased the discerning power and a 4% increase in sensitivity. The metaPRS generated from the genetic susceptibility to CAD and its risk factors can well stratify CAD patients by their risks of death. Integrating metaPRS and clinical risk factors may contribute to identifying patients at higher risk of poor prognosis.

Comprehensive whole-genome sequencing of an early-stage primary myelofibrosis patient defines low mutational burden and non-recurrent candidate genes.

In order to identify novel somatic mutations associated with classic BCR/ABL1-negative myeloproliferative neoplasms, we performed high-coverage genome sequencing of DNA from peripheral blood granulocytes and cultured skin fibroblasts from a patient with MPL W515K-positive primary myelofibrosis. The primary myelofibrosis genome had a low somatic mutation rate, consistent with that observed in similar hematopoietic tumor genomes. Interfacing of whole-genome DNA sequence data with RNA expression data identified three somatic mutations of potential functional significance: i) a nonsense mutation in CARD6, implicated in modulation of NF-kappaB activation; ii) a 19-base pair deletion involving a potential regulatory region in the 5'-untranslated region of BRD2, implicated in transcriptional regulation and cell cycle control; and iii) a non-synonymous point mutation in KIAA0355, an uncharacterized protein. Additional mutations in three genes (CAP2, SOX30, and MFRP) were also evident, albeit with no support for expression at the RNA level. Re-sequencing of these six genes in 178 patients with polycythemia vera, essential thrombocythemia, and myelofibrosis did not identify recurrent somatic mutations in these genes. Finally, we describe methods for reducing false-positive variant calls in the analysis of hematologic malignancies with a low somatic mutation rate. This trial is registered with ClinicalTrials.gov (NCT01108159).

Case report: Systemic muscle involvement as the primary clinical manifestation of chronic active Epstein-Barr virus infection: A case-based review.

Chronic active Epstein-Barr virus infection (CAEBV) is common in Asian countries and characterized by recurrent or persistent infectious mononucleosis-like symptoms. Here, we describe a rare case of CAEBV-associated generalized myositis with extranodal NK/T-cell lymphoma, who initially presented with swelling and muscle soreness in the extremities and was diagnosed as polymyositis at the initial stage. CAEBV-associated generalized myositis is different from polymyositis and other types of myositis. Furthermore, it is prone to lymphoma with poor prognosis.

Comparative proteomic phenotyping of cell lines and primary cells to assess preservation of cell type-specific functions.

Biological experiments are most often performed with immortalized cell lines because they are readily available and can be expanded without limitation. However, cell lines may differ from the in vivo situation in important aspects. Here we introduce a straightforward methodology to compare cell lines to their cognate primary cells and to derive a comparative functional phenotype. We used SILAC (stable isotope labeling by amino acids in cell culture) for quantitative, mass spectrometry-based comparison of the hepatoma cell line Hepa1-6 with primary hepatocytes. The resulting quantitative proteome of 4,063 proteins had an asymmetric distribution, with many proteins down-regulated in the cell line. Bioinformatic analysis of the quantitative proteomics phenotypes revealed that Hepa1-6 cells were deficient in mitochondria, reflecting re-arrangement of metabolic pathways, drastically up-regulate cell cycle-associated functions and largely shut down drug metabolizing enzymes characteristic for the liver. This quantitative knowledge of changes provides an important basis to adapt cell lines to more closely resemble physiological conditions.