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Patients with chronic lymphocytic leukemia (CLL) progressing on ibrutinib constitute an unmet clinical need. Though BTK and PLCG2 mutations are associated with ibrutinib resistance, their frequency and relevance to progression are not fully understood. In this multicenter retrospective observational study, we analyzed 98 patients with CLL treated with ibrutinib (49 relapsing after an initial response and 49 still responding after ≥1 year of continuous treatment) using a next-generation sequencing (NGS) panel (1% sensitivity) comprising 13 CLL-relevant genes including BTK and PLCG2. BTK hotspot mutations were validated by droplet digital PCR (ddPCR) (0.1% sensitivity). By integrating NGS and ddPCR results, 32/49 relapsing cases (65%) carried at least 1 hotspot BTK mutation and/or PLCG2 mutation(s); in 6/32, BTK mutations were only detected by ddPCR [variant allele frequency (VAF) 0.1-1.2%]. BTK/PLCG2 mutations were also identified in 6/49 responding patients (12%; 5/6 VAF

In this longitudinal study, cell-free tumour DNA (a liquid biopsy) from plasma was explored as a prognostic biomarker for gastro-oesophageal cancer. Both tumour-informed and tumour-agnostic approaches for plasma variant filtering were evaluated in 47 participants. This was possible through sequencing of DNA from tissue biopsies from all participants and cell-free DNA from plasma sampled before and after surgery (n = 42), as well as DNA from white blood cells (n = 21) using a custom gene panel with and without unique molecular identifiers (UMIs). A subset of the plasma samples (n = 12) was also assayed with targeted droplet digital PCR (ddPCR). In 17/31 (55%) diagnostic plasma samples, tissue-verified cancer-associated variants could be detected by the gene panel. In the tumour-agnostic approach, 26 participants (59%) had cancer-associated variants, and UMIs were necessary to filter the true variants from the technical artefacts. Additionally, clonal haematopoietic variants could be excluded using the matched white blood cells or follow-up plasma samples. ddPCR detected its targets in 10/12 (83%) and provided an ultra-sensitive method for follow-up. Detectable cancer-associated variants in plasma correlated to a shorter overall survival and shorter time to progression, with a significant correlation for the tumour-informed approaches. In summary, liquid biopsy gene panel sequencing using a tumour-agnostic approach can be applied to all patients regardless of the presence of a tissue biopsy, although this requires UMIs and the exclusion of clonal haematopoietic variants. However, if sequencing data from tumour biopsies are available, a tumour-informed approach improves the value of cell-free tumour DNA as a negative prognostic biomarker in gastro-oesophageal cancer patients.

The associated publication reports proteogenomic analysis of non-small cell lung cancer, where we identified molecular subtypes with distinct immune evasion mechanisms and therapeutic targets, and validated our classification method in separate clinical cohorts. This protocol describes histological, tertiary lymphoid structure (TLS), and immunohistochemical evaluation of clinical samples. Specifically, immunohistochemistry was performed for PD-L1, CD3, and CD8 on tumor microarrays (TMAs) derived from formalin-fixed paraffin embedded (FFPE) samples.

The associated publication reports proteogenomic analysis of non-small cell lung cancer (NSCLC), where we identified molecular subtypes with distinct immune evasion mechanisms and therapeutic targets, and validated our classification method in separate clinical cohorts. This protocol describes sections of the bioinformatics analysis of the multi-omics data, namely, data analysis and processing for panel sequencing, identification of cancer- and driver-related proteins in proteomics data, proteogenomics search, and machine learning-based classifiers for NSCLC subtyping. Specifically, a cohort classifier was built using support-vector machine-recursive feature elimination (SVM-RFE) algorithm applied to in-depth proteomics data from a cohort of 141 samples. The classifier was then validated in three external datasets. Another classifier, suitable for single-sample subtyping, was built using k-top scoring pairs (k-TSP) algorithm applied to label-free data from a cohort of 136 samples. The k-TSP-based classifier was validated in two independent cohorts and an additional external dataset.

The associated publication reports proteogenomic analysis of non-small cell lung cancer (NSCLC), where we identified molecular subtypes with distinct immune evasion mechanisms and therapeutic targets, and validated our classification method in separate clinical cohorts. The in-depth proteomic analysis pointed to a potential role of STK11 inactivation in liver-specific signaling and subsequent cancer growth and immune evasion mechanisms. This protocol describes in vitro validation of the downstream effects of STK11-AMPK signaling on HNF1A and FGL1 in a liver and two lung cancer cell lines.

The associated publication reports proteogenomic analysis of non-small cell lung cancer, where we identified molecular subtypes with distinct immune evasion mechanisms and therapeutic targets, and validated our classification method in separate clinical cohorts. This protocol describes the sample preparation and mass spectrometry (MS)-based in-depth and rapid proteomic analyses of tumor and biopsy samples. We deployed single-pot solid-phase-enhanced sample preparation (SP3). For the in-depth analysis, we used TMT labeling, followed by high-resolution isoelectric focusing (HiRIEF) prefractionation and LC-MS with data-dependent acquisition (DDA). The reported protocol achieved analytical depth of close to 14,000 quantified proteins and almost 10,000 across the entire cohort of 141 samples. The rapid analysis was label-free, based on LC-MS with data-independent acquisition (DIA). The median number of identified proteins was 3,967 and 3,552 in two independent cohorts of tumor samples (n = 141 and 208, respectively), and 2,494 in another cohort of biopsy material (n = 84).

OBJECTIVES To investigate gene alterations as diagnostic and prognostic markers in upper tract urothelial carcinoma (UTUC). PATIENTS AND METHODS Patients with UTUC who underwent nephroureterectomy between 2005 and 2012 were followed until November 2020. DNA was extracted from paraffin-embedded tumour tissue. Next-generation sequencing using a 388-gene panel was performed. First a blinded analysis using principal component analysis and hierarchical clustering was used to search for patterns of mutations. Then a comparative analysis using analysis of variance (ANOVA) was used to search for mutations enriched in groups of various grades, stages, and survival. In addition, careful manual annotation was used to identify pathogenic mutations over-represented in tumours of high grade/stage and/or poor survival. RESULTS A total of 39 patients were included. All tumour stages and grades were represented in the cohort. The median follow-up was 10.6 years. In all, 11 patients died from UTUC during the follow-up. Tumour mutational burden showed a statistically significant correlation with stage, grade, and stage + grade. Grade 1, Grade 2, and Grade 3 tumours had different mutational patterns. Patients who died from UTUC had pathogenic mutations in specific genes e.g. tumour protein p53 (TP53) and HRas proto-oncogene, GTPase (HRAS). Patients with Ta Grade 1 tumours with a known pathogenic fibroblast growth factor receptor 3 (FGFR3) mutation did not die from UTUC. CONCLUSION The genetic analysis was highly concordant with histopathological features and added prognostic information in some cases. Thus, results from genomic profiling may contribute to the choice of treatment and follow-up regimens in the future.

Despite major advancements in lung cancer treatment, long-term survival is still rare and a deeper understanding of molecular phenotypes would allow the identification of specific cancer dependencies and immune-evasion mechanisms. Here we performed in-depth mass-spectrometry-based proteogenomic analysis of 141 tumors representing all major histologies of non-small cell lung cancer (NSCLC). We identified six distinct proteome subtypes with striking differences in immune cell composition and subtype-specific expression of immune checkpoints. Unexpectedly, high neoantigen burden was linked to global hypomethylation and complex neoantigens mapped to genomic regions, such as endogenous retroviral elements and introns, in immune-cold subtypes. Further, we linked immune evasion with LAG-3 via STK11 mutation-dependent HNF1A activation and FGL1 expression. Finally, we develop a data-independent acquisition mass-spectrometry-based NSCLC subtype classification method, validate it in an independent cohort of 208 NSCLC cases and demonstrate its clinical utility by analyzing an additional cohort of 84 late-stage NSCLC biopsy samples. Lehtio and colleagues perform proteogenomic analysis of non-small cell lung cancer and identify molecular subtypes with distinct immune-evasion mechanisms and therapeutic targets and validate their classification method in separate clinical cohorts.

Objective— Recently, poliovirus receptor–related 2 ( Pvrl2 ) emerged as a top gene in a global gene expression study aiming to detect plasma cholesterol–responsive genes causally related to atherosclerosis regression in hypercholesterolemic mice. PVRL2 is an adherens junction protein implied to play a role in transendothelial migration of leukocytes, a key feature in atherosclerosis development. In this study, we investigated the effect of Pvrl2 deficiency on atherosclerosis development and transendothelial migration of leukocytes activity. Approach and Results— Pvrl2 -deficient mice bred onto an atherosclerosis-prone background ( Pvrl2 −/− Ldlr −/− Apob 100/100 ) had less atherosclerotic lesions and more stable plaques compared with littermate controls ( Pvrl2 +/+ Ldlr −/− Apob 100/100 ). Pvrl2 −/− Ldlr −/− Apob 100/100 mice also showed a 49% decrease in transendothelial migration of leukocytes activity observed using the in vivo air pouch model. In accordance, augmented arterial wall expression of Pvrl2 during atherosclerosis progression coincided with an increased gene expression of migrating leukocytes into the vessel wall. Both in human and mice, gene and protein expression of PVRL2 was predominantly observed in the vascular endothelium according to the immunohistochemical and gene expression data. In addition, the cholesterol responsiveness of PVRL2 was also observed in humans. Conclusions— PVRL2 is a plasma cholesterol–responsive gene acting at endothelial sites of vascular inflammation that could potentially be a new therapeutic target for atherosclerosis prevention through its suggested transendothelial migration of leukocytes modulating activity.

Genome-wide association studies (GWAS) have identified hundreds of cardiometabolic disease (CMD) risk loci. However, they contribute little to genetic variance, and most downstream gene-regulatory mechanisms are unknown. We genotyped and RNA-sequenced vascular and metabolic tissues from 600 coronary artery disease patients in the Stockholm-Tartu Atherosclerosis Reverse Networks Engineering Task study (STARNET). Gene expression traits associated with CMD risk single-nucleotide polymorphism (SNPs) identified by GWAS were more extensively found in STARNET than in tissue- and disease-unspecific gene-tissue expression studies, indicating sharing of downstream cis-/trans-gene regulation across tissues and CMDs. In contrast, the regulatory effects of other GWAS risk SNPs were tissue-specific; abdominal fat emerged as an important gene-regulatory site for blood lipids, such as for the low-density lipoprotein cholesterol and coronary artery disease risk gene PCSK9 STARNET provides insights into gene-regulatory mechanisms for CMD risk loci, facilitating their translation into opportunities for diagnosis, therapy, and prevention.

Genome-wide association studies (GWAS) have identified over two hundred chromosomal loci that modulate risk of coronary artery disease (CAD). The genes affected by variants at these loci are largely unknown and an untapped resource to improve our understanding of CAD pathophysiology and identify potential therapeutic targets. Here, we prioritized 68 genes as the most likely causal genes at genome-wide significant loci identified by GWAS of CAD and examined their regulatory roles in 286 metabolic and vascular tissue gene-protein sub-networks (“modules”). The modules and genes within were scored for CAD druggability potential. The scoring enriched for targets of cardiometabolic drugs currently in clinical use and in-depth analysis of the top-scoring modules validated established and revealed novel target tissues, biological processes, and druggable targets. This study provides an unprecedented resource of tissue-defined gene–protein interactions directly affected by genetic variance in CAD risk loci.

Background: Tobacco smoking is a major risk factor for atherosclerotic disease and has been associated with DNA methylation (DNAm) changes in blood cells. However, whether smoking influences DNAm in the diseased vascular wall is unknown but may prove crucial in understanding the pathophysiology of atherosclerosis. In this study, we associated current tobacco smoking to epigenome-wide DNAm in atherosclerotic plaques from patients undergoing carotid endarterectomy. Methods: DNAm at commonly methylated sites (cytosine-guanine nucleotide pairs separated by a phospho-group [CpGs]) was assessed in atherosclerotic plaque samples and peripheral blood samples from 485 carotid endarterectomy patients. We tested the association of current tobacco smoking with DNAm corrected for age and sex. To control for bias and inflation because of cellular heterogeneity, we applied a Bayesian method to estimate an empirical null distribution as implemented by the R package bacon. Replication of the smoking-associated methylated CpGs in atherosclerotic plaques was executed in the second sample of 190 carotid endarterectomy patients, and results were meta-analyzed using a fixed-effects model. Results: Tobacco smoking was significantly associated to differential DNAm in atherosclerotic lesions of 4 CpGs (false discovery rate

Supplemental Digital Content is available in the text., Background: Atherosclerosis is a chronic inflammatory disease in part caused by lipid uptake in the vascular wall, but the exact underlying mechanisms leading to acute myocardial infarction and stroke remain poorly understood. Large consortia identified genetic susceptibility loci that associate with large artery ischemic stroke and coronary artery disease. However, deciphering their underlying mechanisms are challenging. Histological studies identified destabilizing characteristics in human atherosclerotic plaques that associate with clinical outcome. To what extent established susceptibility loci for large artery ischemic stroke and coronary artery disease relate to plaque characteristics is thus far unknown but may point to novel mechanisms. Methods: We studied the associations of 61 established cardiovascular risk loci with 7 histological plaque characteristics assessed in 1443 carotid plaque specimens from the Athero-Express Biobank Study. We also assessed if the genotyped cardiovascular risk loci impact the tissue-specific gene expression in 2 independent biobanks, Biobank of Karolinska Endarterectomy and Stockholm Atherosclerosis Gene Expression. Results: A total of 21 established risk variants (out of 61) nominally associated to a plaque characteristic. One variant (rs12539895, risk allele A) at 7q22 associated to a reduction of intraplaque fat, P=5.09×10−6 after correction for multiple testing. We further characterized this 7q22 Locus and show tissue-specific effects of rs12539895 on HBP1 expression in plaques and COG5 expression in whole blood and provide data from public resources showing an association with decreased LDL (low-density lipoprotein) and increase HDL (high-density lipoprotein) in the blood. Conclusions: Our study supports the view that cardiovascular susceptibility loci may exert their effect by influencing the atherosclerotic plaque characteristics.

Background and aims Mitochondrial damage and augmented production of reactive oxygen species (ROS) may represent an intermediate step by which hypercholesterolemia exacerbates atherosclerotic lesion formation. Methods To test this hypothesis, in mice with severe but genetically reversible hypercholesterolemia (i.e. the so called Reversa mouse model), we performed time-resolved analyses of mitochondrial transcriptome in the aortic arch employing a systems-level network approach. Results During hypercholesterolemia, we observed a massive down-regulation (>28%) of mitochondrial genes, specifically at the time of rapid atherosclerotic lesion expansion and foam cell formation, i.e. between 30 and 40 weeks of age. Both phenomena - down-regulation of mitochondrial genes and lesion expansion - were largely reversible by genetically lowering plasma cholesterol (by >80%, from 427 to 54 ± 31 mg/L) at 30 weeks. Co-expression network analysis revealed that both mitochondrial signature genes were highly connected in two modules, negatively correlating with lesion size and supported as causal for coronary artery disease (CAD) in humans, as expression-associated single nucleotide polymorphisms (eSNPs) representing their genes overlapped markedly with established disease risk loci. Within these modules, we identified the transcription factor estrogen related receptor (ERR)-α and its co-factors PGC1-α and -β, i.e. two members of the peroxisome proliferator-activated receptor γ co-activator 1 family of transcription regulators, as key regulatory genes. Together, these factors are known as major orchestrators of mitochondrial biogenesis and antioxidant responses. Conclusions Using a network approach, we demonstrate how hypercholesterolemia could hamper mitochondrial activity during atherosclerosis progression and pinpoint potential therapeutic targets to counteract these processes.

Objective— Using a multi-tissue, genome-wide gene expression approach, we recently identified a gene module linked to the extent of human atherosclerosis. This atherosclerosis module was enriched with inherited risk for coronary and carotid artery disease (CAD) and overlapped with genes in the transendothelial migration of leukocyte (TEML) pathway. Among the atherosclerosis module genes, the transcription cofactor Lim domain binding 2 (LDB2) was the most connected in a CAD vascular wall regulatory gene network. Here, we used human genomics and atherosclerosis-prone mice to evaluate the possible role of LDB2 in TEML and atherosclerosis. Approach and Results— mRNA profiles generated from blood macrophages in patients with CAD were used to infer transcription factor regulatory gene networks; Ldlr –/– Apob 100/100 mice were used to study the effects of Ldb2 deficiency on TEML activity and atherogenesis. LDB2 was the most connected gene in a transcription factor regulatory network inferred from TEML and atherosclerosis module genes in CAD macrophages. In Ldlr –/– Apob 100/100 mice, loss of Ldb2 increased atherosclerotic lesion size ≈2-fold and decreased plaque stability. The exacerbated atherosclerosis was caused by increased TEML activity, as demonstrated in air-pouch and retinal vasculature models in vivo, by ex vivo perfusion of primary leukocytes, and by leukocyte migration in vitro. In THP1 cells, migration was increased by overexpression and decreased by small interfering RNA inhibition of LDB2 . A functional LDB2 variant (rs10939673) was associated with the risk and extent of CAD across several cohorts. Conclusions— As a key driver of the TEML pathway in CAD macrophages, LDB2 is a novel candidate to target CAD by inhibiting the overall activity of TEML.

Background Genome-wide association studies (GWAS) have revealed many susceptibility loci for complex genetic diseases. For most loci, the causal genes have not been identified. Currently, the identification of candidate genes is predominantly based on genes that localize close to or within identified loci. We have recently shown that 92 of the 163 inflammatory bowel disease (IBD)-loci co-localize with non-coding DNA regulatory elements (DREs). Mutations in DREs can contribute to IBD pathogenesis through dysregulation of gene expression. Consequently, genes that are regulated by these 92 DREs are to be considered as candidate genes. This study uses circular chromosome conformation capture-sequencing (4C-seq) to systematically analyze chromatin-interactions at IBD susceptibility loci that localize to regulatory DNA. Results Using 4C-seq, we identify genomic regions that physically interact with the 92 DRE that were found at IBD susceptibility loci. Since the activity of regulatory elements is cell-type specific, 4C-seq was performed in monocytes, lymphocytes, and intestinal epithelial cells. Altogether, we identified 902 novel IBD candidate genes. These include genes specific for IBD-subtypes and many noteworthy genes including ATG9A and IL10RA. We show that expression of many novel candidate genes is genotype-dependent and that these genes are upregulated during intestinal inflammation in IBD. Furthermore, we identify HNF4α as a potential key upstream regulator of IBD candidate genes. Conclusions We reveal many novel and relevant IBD candidate genes, pathways, and regulators. Our approach complements classical candidate gene identification, links novel genes to IBD and can be applied to any existing GWAS data. Electronic supplementary material The online version of this article (doi:10.1186/s13059-016-1100-3) contains supplementary material, which is available to authorized users.

Objective— The genetically modified mouse is the most commonly used animal model for studying the pathogenesis of atherosclerotic disease. We aimed to assess if mice atherosclerosis-related genes could be validated in human disease through examination of results from genome-wide association studies. Approach and Results— We performed a systematic review to identify atherosclerosis-causing genes in mice and carried out gene-based association tests of their human orthologs for an association with human coronary artery disease and human large artery ischemic stroke. Moreover, we investigated the association of these genes with human atherosclerotic plaque characteristics. In addition, we assessed the presence of tissue-specific cis -acting expression quantitative trait loci for these genes in humans. Finally, using pathway analyses we show that the putative atherosclerosis-causing genes revealed few associations with human coronary artery disease, large artery ischemic stroke, or atherosclerotic plaque characteristics, despite the fact that the majority of these genes have cis -acting expression quantitative trait loci. Conclusions— A role for genes that has been observed in mice for atherosclerotic lesion development could scarcely be confirmed by studying associations of disease development with common human genetic variants. The value of murine atherosclerotic models for selection of therapeutic targets in human disease remains unclear.

Objective— Genome-wide association studies have to date identified 159 significant and suggestive loci for coronary artery disease (CAD). We now report comprehensive bioinformatics analyses of sequence variation in these loci to predict candidate causal genes. Approach and Results— All annotated genes in the loci were evaluated with respect to protein-coding single-nucleotide polymorphism and gene expression parameters. The latter included expression quantitative trait loci, tissue specificity, and miRNA binding. High priority candidate genes were further identified based on literature searches and our experimental data. We conclude that the great majority of causal variations affecting CAD risk occur in noncoding regions, with 41% affecting gene expression robustly versus 6% leading to amino acid changes. Many of these genes differed from the traditionally annotated genes, which was usually based on proximity to the lead single-nucleotide polymorphism. Indeed, we obtained evidence that genetic variants at CAD loci affect 98 genes which had not been linked to CAD previously. Conclusions— Our results substantially revise the list of likely candidates for CAD and suggest that genome-wide association studies efforts in other diseases may benefit from similar bioinformatics analyses.

Inferring molecular networks can reveal how genetic perturbations interact with environmental factors to cause common complex diseases. We analyzed genetic and gene expression data from seven tissues relevant to coronary artery disease (CAD) and identified regulatory gene networks (RGNs) and their key drivers. By integrating data from genome-wide association studies, we identified 30 CAD-causal RGNs interconnected in vascular and metabolic tissues, and we validated them with corresponding data from the Hybrid Mouse Diversity Panel. As proof of concept, by targeting the key drivers AIP, DRAP1, POLR2I, and PQBP1 in a cross-species-validated, arterial-wall RGN involving RNA-processing genes, we re-identified this RGN in THP-1 foam cells and independent data from CAD macrophages and carotid lesions. This characterization of the molecular landscape in CAD will help better define the regulation of CAD candidate genes identified by genome-wide association studies and is a first step toward achieving the goals of precision medicine.

Background The eicosanoid genes ALOX5 , ALOX5AP and LTA4H have been implicated in atherosclerosis. We assessed the impact of common variants in these genes on gene expression, circulating protein levels, and atherosclerotic plaque phenotypes. Methods We included patients from the Stockholm Atherosclerosis Gene Expression study (STAGE, N = 109), and the Athero-Express Biobank Study (AE, N = 1443). We tested 1453 single-nucleotide variants (SNVs) in ALOX5 , ALOX5AP and LTA4H for association with gene expression in STAGE. We also tested these SNVs for association with seven histologically defined plaque phenotypes in the AE (which included calcification, collagen, cellular content, atheroma size, and intraplaque vessel density and hemorrhage). Results We replicate a known cis -eQTL (rs6538697, p = 1.96 × 10 −6 ) for LTA4H expression in whole blood of patients from STAGE. We found no significant association for any of the SNVs tested with serum levels of ALOX5 or ALOX5AP (p > 5.79 × 10 −4 ). For atherosclerotic plaque phenotypes the strongest associations were found for intraplaque vessel density and smooth muscle cells in the ALOX5AP locus (p > 1.67 × 10 −4 ). Conclusions We replicate a known eQTL for LTA4H expression in whole blood using STAGE data. We found no associations of variants in and around ALOX5 , ALOX5AP and LTA4H with serum ALOX5 or ALOX5AP levels, or plaque phenotypes. On the supposition that these genes play a causal role in atherosclerosis, these results suggest that common variants in these loci play a limited role (if any) in influencing advanced atherosclerotic plaque morphology to the extent that it impacts atherosclerotic disease.

The Kruskal-Wallis test is a popular non-parametric statistical test for identifying expression quantitative trait loci (eQTLs) from genome-wide data due to its robustness against variations in the underlying genetic model and expression trait distribution, but testing billions of marker-trait combinations one-by-one can become computationally prohibitive. We developed kruX, an algorithm implemented in Matlab, Python and R that uses matrix multiplications to simultaneously calculate the Kruskal-Wallis test statistic for several millions of marker-trait combinations at once. KruX is more than ten thousand times faster than computing associations one-by-one on a typical human dataset. We used kruX and a dataset of more than 500k SNPs and 20k expression traits measured in 102 human blood samples to compare eQTLs detected by the Kruskal-Wallis test to eQTLs detected by the parametric ANOVA and linear model methods. We found that the Kruskal-Wallis test is more robust against data outliers and heterogeneous genotype group sizes and detects a higher proportion of non-linear associations, but is more conservative for calling additive linear associations. In summary, kruX enables the use of robust non-parametric methods for massive eQTL mapping without the need for a high-performance computing infrastructure., minor revision; 6 pages, 5 figures; software available at http://krux.googlecode.com

Plasma cholesterol lowering (PCL) slows and sometimes prevents progression of atherosclerosis and may even lead to regression. Little is known about how molecular processes in the atherosclerotic arterial wall respond to PCL and modify responses to atherosclerosis regression. We studied atherosclerosis regression and global gene expression responses to PCL (≥80%) and to atherosclerosis regression itself in early, mature, and advanced lesions. In atherosclerotic aortic wall from Ldlr−/−Apob 100/100 Mttp flox/floxMx1-Cre mice, atherosclerosis regressed after PCL regardless of lesion stage. However, near-complete regression was observed only in mice with early lesions; mice with mature and advanced lesions were left with regression-resistant, relatively unstable plaque remnants. Atherosclerosis genes responding to PCL before regression, unlike those responding to the regression itself, were enriched in inherited risk for coronary artery disease and myocardial infarction, indicating causality. Inference of transcription factor (TF) regulatory networks of these PCL-responsive gene sets revealed largely different networks in early, mature, and advanced lesions. In early lesions, PPARG was identified as a specific master regulator of the PCL-responsive atherosclerosis TF-regulatory network, whereas in mature and advanced lesions, the specific master regulators were MLL5 and SRSF10/XRN2, respectively. In a THP-1 foam cell model of atherosclerosis regression, siRNA targeting of these master regulators activated the time-point-specific TF-regulatory networks and altered the accumulation of cholesterol esters. We conclude that PCL leads to complete atherosclerosis regression only in mice with early lesions. Identified master regulators and related PCL-responsive TF-regulatory networks will be interesting targets to enhance PCL-mediated regression of mature and advanced atherosclerotic lesions., Author Summary The main underlying cause of heart attacks and strokes is atherosclerosis. One strategy to prevent these often deadly clinical events is therefore either to slow atherosclerosis progression or better, induce regression of atherosclerotic plaques making them more stable. Plasma cholesterol lowering (PCL) is the most efficient way to induce atherosclerosis regression but sometimes fails to do so. In our study, we used a mouse model with elevated LDL cholesterol levels, similar to humans who develop early atherosclerosis, and a genetic switch to lower plasma cholesterol at any time during atherosclerosis progression. In this model, we examined atherosclerosis gene expression and regression in response to PCL at three different stages of atherosclerosis progression. PCL led to complete regression in mice with early lesions but was incomplete in mice with mature and advanced lesions, indicating that early prevention with PCL in individuals with increased risk for heart attack or stroke would be particularly useful. In addition, by inferring PCL-responsive gene networks in early, mature and advanced atherosclerotic lesions, we identified key drivers specific for regression of early (PPARG), mature (MLL5) and advanced (SRSF10/XRN2) atherosclerosis. These key drivers should be interesting therapeutic targets to enhance PCL-mediated regression of atherosclerosis.