Mapping the cortico-striatal transcriptome in attention deficit hyperactivity disorder.

Despite advances in identifying rare and common genetic variants conferring risk for ADHD, the lack of a transcriptomic understanding of cortico-striatal brain circuitry has stymied a molecular mechanistic understanding of this disorder. To address this gap, we mapped the transcriptome of the caudate nucleus and anterior cingulate cortex in post-mortem tissue from 60 individuals with and without ADHD. Significant differential expression of genes was found in the anterior cingulate cortex and, to a lesser extent, the caudate. Significant downregulation emerged of neurotransmitter gene pathways, particularly glutamatergic, in keeping with models that implicate these neurotransmitters in ADHD. Consistent with the genetic overlap between mental disorders, correlations were found between the cortico-striatal transcriptomic changes seen in ADHD and those seen in other neurodevelopmental and mood disorders. This transcriptomic evidence points to cortico-striatal neurotransmitter anomalies in the pathogenesis of ADHD, consistent with current models of the disorder.

Characterization and clustering of kinase isoform expression in metastatic melanoma.

Mutations to the human kinome are known to play causal roles in cancer. The kinome regulates numerous cell processes including growth, proliferation, differentiation, and apoptosis. In addition to aberrant expression, aberrant alternative splicing of cancer-driver genes is receiving increased attention as it could lead to loss or gain of functional domains, altering a kinase's downstream impact. The present study quantifies changes in gene expression and isoform ratios in the kinome of metastatic melanoma cells relative to primary tumors. We contrast 538 total kinases and 3,040 known kinase isoforms between 103 primary tumor and 367 metastatic samples from The Cancer Genome Atlas (TCGA). We find strong evidence of differential expression (DE) at the gene level in 123 kinases (23%). Additionally, of the 468 kinases with alternative isoforms, 60 (13%) had significant difference in isoform ratios (DIR). Notably, DE and DIR have little correlation; for instance, although DE highlights enrichment in receptor tyrosine kinases (RTKs), DIR identifies altered splicing in non-receptor tyrosine kinases (nRTKs). Using exon junction mapping, we identify five examples of splicing events favored in metastatic samples. We demonstrate differential apoptosis and protein localization between SLK isoforms in metastatic melanoma. We cluster isoform expression data and identify subgroups that correlate with genomic subtypes and anatomic tumor locations. Notably, distinct DE and DIR patterns separate samples with BRAF hotspot mutations and (N/K/H)RAS hotspot mutations, the latter of which lacks effective kinase inhibitor treatments. DE in RAS mutants concentrates in CMGC kinases (a group including cell cycle and splicing regulators) rather than RTKs as in BRAF mutants. Furthermore, isoforms in the RAS kinase subgroup show enrichment for cancer-related processes such as angiogenesis and cell migration. Our results reveal a new approach to therapeutic target identification and demonstrate how different mutational subtypes may respond differently to treatments highlighting possible new driver events in cancer.

Identification of human silencers by correlating cross-tissue epigenetic profiles and gene expression.

Compared to enhancers, silencers are notably difficult to identify and validate experimentally. In search for human silencers, we utilized H3K27me3-DNase I hypersensitive site (DHS) peaks with tissue specificity negatively correlated with the expression of nearby genes across 25 diverse cell lines. These regions are predicted to be silencers since they are physically linked, using Hi-C loops, or associated, using expression quantitative trait loci (eQTL) results, with a decrease in gene expression much more frequently than general H3K27me3-DHSs. Also, these regions are enriched for the binding sites of transcriptional repressors (such as CTCF, MECOM, SMAD4, and SNAI3) and depleted of the binding sites of transcriptional activators. Using sequence signatures of these regions, we constructed a computational model and predicted approximately 10,000 additional silencers per cell line and demonstrated that the majority of genes linked to these silencers are expressed at a decreased level. Furthermore, single nucleotide polymorphisms (SNPs) in predicted silencers are significantly associated with disease phenotypes. Finally, our results show that silencers commonly interact with enhancers to affect the transcriptional dynamics of tissue-specific genes and to facilitate fine-tuning of transcription in the human genome.

A novel role for nucleolin in splice site selection.

Latent 5' splice sites, not normally used, are highly abundant in human introns, but are activated under stress and in cancer, generating thousands of nonsense mRNAs. A previously proposed mechanism to suppress latent splicing was shown to be independent of NMD, with a pivotal role for initiator-tRNA independent of protein translation. To further elucidate this mechanism, we searched for nuclear proteins directly bound to initiator-tRNA. Starting with UV-crosslinking, we identified nucleolin (NCL) interacting directly and specifically with initiator-tRNA in the nucleus, but not in the cytoplasm. Next, we show the association of ini-tRNA and NCL with pre-mRNA. We further show that recovery of suppression of latent splicing by initiator-tRNA complementation is NCL dependent. Finally, upon nucleolin knockdown we show activation of latent splicing in hundreds of coding transcripts having important cellular functions. We thus propose nucleolin, a component of the endogenous spliceosome, through its direct binding to initiator-tRNA and its effect on latent splicing, as the first protein of a nuclear quality control mechanism regulating splice site selection to protect cells from latent splicing that can generate defective mRNAs.

Differential gene expression identifies a transcriptional regulatory network involving ER-alpha and PITX1 in invasive epithelial ovarian cancer.

BACKGROUND: The heterogeneous subtypes and stages of epithelial ovarian cancer (EOC) differ in their biological features, invasiveness, and response to chemotherapy, but the transcriptional regulators causing their differences remain nebulous. METHODS: In this study, we compared high-grade serous ovarian cancers (HGSOCs) to low malignant potential or serous borderline tumors (SBTs). Our aim was to discover new regulatory factors causing distinct biological properties of HGSOCs and SBTs. RESULTS: In a discovery dataset, we identified 11 differentially expressed genes (DEGs) between SBTs and HGSOCs. Their expression correctly classified 95% of 267 validation samples. Two of the DEGs, TMEM30B and TSPAN1, were significantly associated with worse overall survival in patients with HGSOC. We also identified 17 DEGs that distinguished stage II vs. III HGSOC. In these two DEG promoter sets, we identified significant enrichment of predicted transcription factor binding sites, including those of RARA, FOXF1, BHLHE41, and PITX1. Using published ChIP-seq data acquired from multiple non-ovarian cell types, we showed additional regulatory factors, including AP2-gamma/TFAP2C, FOXA1, and BHLHE40, bound at the majority of DEG promoters. Several of the factors are known to cooperate with and predict the presence of nuclear hormone receptor estrogen receptor alpha (ER-alpha). We experimentally confirmed ER-alpha and PITX1 presence at the DEGs by performing ChIP-seq analysis using the ovarian cancer cell line PEO4. Finally, RNA-seq analysis identified recurrent gene fusion events in our EOC tumor set. Some of these fusions were significantly associated with survival in HGSOC patients; however, the fusion genes are not regulated by the transcription factors identified for the DEGs. CONCLUSIONS: These data implicate an estrogen-responsive regulatory network in the differential gene expression between ovarian cancer subtypes and stages, which includes PITX1. Importantly, the transcription factors associated with our DEG promoters are known to form the MegaTrans complex in breast cancer. This is the first study to implicate the MegaTrans complex in contributing to the distinct biological trajectories of malignant and indolent ovarian cancer subtypes.

Aberrant DNA methylation defines isoform usage in cancer, with functional implications.

Alternative transcript isoforms are common in tumors and act as potential drivers of cancer. Mechanisms determining altered isoform expression include somatic mutations in splice regulatory sites or altered splicing factors. However, since DNA methylation is known to regulate transcriptional isoform activity in normal cells, we predicted the highly dysregulated patterns of DNA methylation present in cancer also affect isoform activity. We analyzed DNA methylation and RNA-seq isoform data from 18 human cancer types and found frequent correlations specifically within 11 cancer types. Examining the top 25% of variable methylation sites revealed that the location of the methylated CpG site in a gene determined which isoform was used. In addition, the correlated methylation-isoform patterns classified tumors into known subtypes and predicted distinct protein functions between tumor subtypes. Finally, methylation-correlated isoforms were enriched for oncogenes, tumor suppressors, and cancer-related pathways. These findings provide new insights into the functional impact of dysregulated DNA methylation in cancer and highlight the relationship between the epigenome and transcriptome.

CAGI experiments: Modeling sequence variant impact on gene splicing using predictions from computational tools.

Improving predictions of phenotypic consequences for genomic variants is part of ongoing efforts in the scientific community to gain meaningful insights into genomic function. Within the framework of the critical assessment of genome interpretation experiments, we participated in the Vex-seq challenge, which required predicting the change in the percent spliced in measure (ΔΨ) for 58 exons caused by more than 1,000 genomic variants. Experimentally determined through the Vex-seq assay, the Ψ quantifies the fraction of reads that include an exon of interest. Predicting the change in Ψ associated with specific genomic variants implies determining the sequence changes relevant for splicing regulators, such as splicing enhancers and silencers. Here we took advantage of two computational tools, SplicePort and SPANR, that incorporate relevant sequence features in their models of splice sites and exon-inclusion level, respectively. Specifically, we used the SplicePort and SPANR outputs to build mathematical models of the experimental data obtained for the variants in the training set, which we then used to predict the ΔΨ associated with the mutations in the test set. We show that the sequence changes captured by these computational tools provide a reasonable foundation for modeling the impact on splicing associated with genomic variants.

SigSeeker: a peak-calling ensemble approach for constructing epigenetic signatures.

MOTIVATION: Epigenetic data are invaluable when determining the regulatory programs governing a cell. Based on use of next-generation sequencing data for characterizing epigenetic marks and transcription factor binding, numerous peak-calling approaches have been developed to determine sites of genomic significance in these data. Such analyses can produce a large number of false positive predictions, suggesting that sites supported by multiple algorithms provide a stronger foundation for inferring and characterizing regulatory programs associated with the epigenetic data. Few methodologies integrate epigenetic based predictions of multiple approaches when combining profiles generated by different tools. RESULTS: The SigSeeker peak-calling ensemble uses multiple tools to identify peaks, and with user-defined thresholds for peak overlap and signal strength it retains only those peaks that are concordant across multiple tools. Peaks predicted to be co-localized by only a very small number of tools, discovered to be only marginally overlapping, or found to represent significant outliers to the approximation model are removed from the results, providing concise and high quality epigenetic datasets. SigSeeker has been validated using established benchmarks for transcription factor binding and histone modification ChIP-Seq data. These comparisons indicate that the quality of our ensemble technique exceeds that of single tool approaches, enhances existing peak-calling ensembles, and results in epigenetic profiles of higher confidence. AVAILABILITY AND IMPLEMENTATION: http://sigseeker.org. CONTACT: lichtenbergj@mail.nih.gov. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Significant associations between driver gene mutations and DNA methylation alterations across many cancer types.

Recent evidence shows that mutations in several driver genes can cause aberrant methylation patterns, a hallmark of cancer. In light of these findings, we hypothesized that the landscapes of tumor genomes and epigenomes are tightly interconnected. We measured this relationship using principal component analyses and methylation-mutation associations applied at the nucleotide level and with respect to genome-wide trends. We found that a few mutated driver genes were associated with genome-wide patterns of aberrant hypomethylation or CpG island hypermethylation in specific cancer types. In addition, we identified associations between 737 mutated driver genes and site-specific methylation changes. Moreover, using these mutation-methylation associations, we were able to distinguish between two uterine and two thyroid cancer subtypes. The driver gene mutation-associated methylation differences between the thyroid cancer subtypes were linked to differential gene expression in JAK-STAT signaling, NADPH oxidation, and other cancer-related pathways. These results establish that driver gene mutations are associated with methylation alterations capable of shaping regulatory network functions. In addition, the methodology presented here can be used to subdivide tumors into more homogeneous subsets corresponding to underlying molecular characteristics, which could improve treatment efficacy.

Defining functional DNA elements in the human genome.

With the completion of the human genome sequence, attention turned to identifying and annotating its functional DNA elements. As a complement to genetic and comparative genomics approaches, the Encyclopedia of DNA Elements Project was launched to contribute maps of RNA transcripts, transcriptional regulator binding sites, and chromatin states in many cell types. The resulting genome-wide data reveal sites of biochemical activity with high positional resolution and cell type specificity that facilitate studies of gene regulation and interpretation of noncoding variants associated with human disease. However, the biochemically active regions cover a much larger fraction of the genome than do evolutionarily conserved regions, raising the question of whether nonconserved but biochemically active regions are truly functional. Here, we review the strengths and limitations of biochemical, evolutionary, and genetic approaches for defining functional DNA segments, potential sources for the observed differences in estimated genomic coverage, and the biological implications of these discrepancies. We also analyze the relationship between signal intensity, genomic coverage, and evolutionary conservation. Our results reinforce the principle that each approach provides complementary information and that we need to use combinations of all three to elucidate genome function in human biology and disease.

Computational analysis reveals a correlation of exon-skipping events with splicing, transcription and epigenetic factors.

Alternative splicing (AS), in higher eukaryotes, is one of the mechanisms of post-transcriptional regulation that generate multiple transcripts from the same gene. One particular mode of AS is the skipping event where an exon may be alternatively excluded or constitutively included in the resulting mature mRNA. Both transcript isoforms from this skipping event site, i.e. in which the exon is either included (inclusion isoform) or excluded (skipping isoform), are typically present in one cell, and maintain a subtle balance that is vital to cellular function and dynamics. However, how the prevailing conditions dictate which isoform is expressed and what biological factors might influence the regulation of this process remain areas requiring further exploration. In this study, we have developed a novel computational method, graph-based exon-skipping scanner (GESS), for de novo detection of skipping event sites from raw RNA-seq reads without prior knowledge of gene annotations, as well as for determining the dominant isoform generated from such sites. We have applied our method to publicly available RNA-seq data in GM12878 and K562 cells from the ENCODE consortium and experimentally validated several skipping site predictions by RT-PCR. Furthermore, we integrated other sequencing-based genomic data to investigate the impact of splicing activities, transcription factors (TFs) and epigenetic histone modifications on splicing outcomes. Our computational analysis found that splice sites within the skipping-isoform-dominated group (SIDG) tended to exhibit weaker MaxEntScan-calculated splice site strength around middle, 'skipping', exons compared to those in the inclusion-isoform-dominated group (IIDG). We further showed the positional preference pattern of splicing factors, characterized by enrichment in the intronic splice sites immediately bordering middle exons. Finally, our analysis suggested that different epigenetic factors may introduce a variable obstacle in the process of exon-intron boundary establishment leading to skipping events.

Whole-genome sequencing identifies a recurrent functional synonymous mutation in melanoma.

Synonymous mutations, which do not alter the protein sequence, have been shown to affect protein function [Sauna ZE, Kimchi-Sarfaty C (2011) Nat Rev Genet 12(10):683-691]. However, synonymous mutations are rarely investigated in the cancer genomics field. We used whole-genome and -exome sequencing to identify somatic mutations in 29 melanoma samples. Validation of one synonymous somatic mutation in BCL2L12 in 285 samples identified 12 cases that harbored the recurrent F17F mutation. This mutation led to increased BCL2L12 mRNA and protein levels because of differential targeting of WT and mutant BCL2L12 by hsa-miR-671-5p. Protein made from mutant BCL2L12 transcript bound p53, inhibited UV-induced apoptosis more efficiently than WT BCL2L12, and reduced endogenous p53 target gene transcription. This report shows selection of a recurrent somatic synonymous mutation in cancer. Our data indicate that silent alterations have a role to play in human cancer, emphasizing the importance of their investigation in future cancer genome studies.

Ascertaining regions affected by GC-biased gene conversion through weak-to-strong mutational hotspots.

A major objective for evolutionary biology is to identify regions affected by positive selection. High dN/dS values for proteins and accelerated lineage-specific substitution rates for non-coding regions are considered classic signatures of positive selection. However, these could also be the result of non-adaptive phenomena, such as GC-biased gene conversion (gBGC), which favors the fixation of strong (C/G) over weak (A/T) nucleotides. Recent estimates indicate that gBGC affected up to 20% of regions with signatures of positive selection. Here we evaluate the impact of gBGC through its molecular signature of weak-to-strong mutational hotspots. We implemented specific modifications to the test proposed by Tang and Lewontin (1999) for identifying regions of differential variability and applied it to regions previously investigated for the influence of gBGC. While we found significant agreement with previous reports, our results suggest a smaller influence of gBGC than previously estimated, warranting further development of methods for its detection.

Orthology-driven mapping of bidirectional promoters in human and mouse genomes.

BACKGROUND: The presence of bidirectional promoters in all vertebrate species suggests that the promoters may be maintained in orthologous positions. Therefore the identification of the comprehensive orthologous mapping of this type promoter across species can facilitate elucidation of regulatory mechanisms controlling bidirectional gene expression. However, the lack of annotation for many transcribed regions in the genome can impact the orthology designation of these promoters. Human and mouse are among genomes that have been relatively well annotated. Thus we used them as models to study the orthologous patterns of bidirectional promoters. RESULTS: We developed a method to annotate these regulatory regions by confirming the orthology of the genes found on each side of the promoters. In this manuscript we report the cross-species comparisons between human and mouse genomes, where the bidirectional promoter sets regulating UCSC Known Genes and spliced EST annotations were mapped from human to mouse and vice versa. We validate hundreds of orthologous bidirectional promoters through the presence of orthologous flanking gene annotations in the second species. We also show that regulatory activity of these orthologous promoters confers similar gene expression profiles in 21 tissues of human and mouse. In particular, more than one third of human bidirectional promoters annotated from spliced EST annotations regulate ncRNA, of which over 90% are lncRNAs. CONCLUSIONS: Although evolutionary conservation shows a weaker signature in promoters than coding regions, our technique of mapping of orthologous genes shows that most bidirectional promoter arrangements are conserved across human and mouse genomes, suggesting a critical function. In addition, the similar expression patterns of the orthologous gene sets indicate that the regulatory mechanisms remain largely conserved as well.

Examining epigenetic aging in the post-mortem brain in attention deficit hyperactivity disorder.

Mathematical algorithms known as "epigenetic clocks" use methylation values at a set of CpG sites to estimate the biological age of an individual in a tissue-specific manner. These clocks have demonstrated both acceleration and delays in epigenetic aging in multiple neuropsychiatric conditions, including schizophrenia and neurodevelopmental disorders such as autism spectrum disorder. However, no study to date has examined epigenetic aging in ADHD despite its status as one of the most prevalent neurodevelopmental conditions, with 1 in 9 children having ever received an ADHD diagnosis in the US. Only a handful of studies have examined epigenetic age in brain tissue from neurodevelopmental conditions, with none focused on ADHD, despite the obvious relevance to pathogenesis. Thus, here we asked if post-mortem brain tissue in those with lifetime histories of ADHD would show accelerated or delayed epigenetic age, as has been found for other neurodevelopmental conditions. We applied four different epigenetic clocks to estimate epigenetic age in individuals with ADHD and unaffected controls from cortical (anterior cingulate cortex, N = 55) and striatal (caudate, N = 56) post-mortem brain tissue, as well as peripheral blood (N = 84) and saliva (N = 112). After determining which epigenetic clock performed best in each tissue, we asked if ADHD was associated with altered biological aging in corticostriatal brain and peripheral tissues. We found that a range of epigenetic clocks accurately predicted chronological age in all tissues. We also found that a diagnosis of ADHD was not significantly associated with differential epigenetic aging, neither for the postmortem ACC or caudate, nor for peripheral tissues. These findings held when accounting for comorbid psychiatric diagnoses, substance use, and stimulant medication. Thus, in this study of epigenetic clocks in ADHD, we find no evidence of altered epigenetic aging in corticostriatal brain regions nor in peripheral tissue. We consider reasons for this unexpected finding, including the limited sampling of brain regions, the age range of individuals studied, and the possibility that processes that accelerate epigenetic age may be counteracted by the developmental delay posited in some models of ADHD.

Cortico-striatal differences in the epigenome in attention-deficit/ hyperactivity disorder.

While epigenetic modifications have been implicated in ADHD through studies of peripheral tissue, to date there has been no examination of the epigenome of the brain in the disorder. To address this gap, we mapped the methylome of the caudate nucleus and anterior cingulate cortex in post-mortem tissue from fifty-eight individuals with or without ADHD. While no single probe showed adjusted significance in differential methylation, several differentially methylated regions emerged. These regions implicated genes involved in developmental processes including neurogenesis and the differentiation of oligodendrocytes and glial cells. We demonstrate a significant association between differentially methylated genes in the caudate and genes implicated by GWAS not only in ADHD but also in autistic spectrum, obsessive compulsive and bipolar affective disorders through GWAS. Using transcriptomic data available on the same subjects, we found modest correlations between the methylation and expression of genes. In conclusion, this study of the cortico-striatal methylome points to gene and gene pathways involved in neurodevelopment, consistent with studies of common and rare genetic variation, as well as the post-mortem transcriptome in ADHD.

The Megacomplex protects ER-alpha from degradation by Fulvestrant in epithelial ovarian cancer.

Ovarian cancer, a significant contributor to cancer-related mortality, exhibits limited responsiveness to hormonal therapies targeting the estrogen receptor (ERα). This study aimed to elucidate the mechanisms behind ERα resistance to the therapeutic drug Fulvestrant (ICI182780 or ICI). Notably, compared to the cytoplasmic version, nuclear ERα was minimally degraded by ICI, suggesting a mechanism for drug resistance via the protective confines of the nuclear substructures. Of these substructures, we identified a 1.3MDa Megacomplex comprising transcription factors ERα, FOXA1, and PITX1 using size exclusion chromatography (SEC) in the ovarian cancer cell line, PEO4. ChIP-seq revealed these factors colocalized at 6,775 genomic positions representing sites of Megacomplex formation. Megacomplex ERα exhibited increased resistance to degradation by ICI compared to cytoplasmic and nuclear ERα. A small molecule inhibitor of active chromatin and super-enhancers, JQ1, in combination with ICI significantly enhanced ERα degradation from Megacomplex as revealed by SEC and ChIP-seq. Interestingly, this combination degraded both the cytoplasmic as well as nuclear ERa. Pathway enrichment analysis showed parallel results for RNA-seq gene sets following Estradiol, ICI, or ICI plus JQ1 treatments as those defined by Megacomplex binding identified through ChIP-seq. Furthermore, similar pathway enrichments were confirmed in mass-spec analysis of the Megacomplex macromolecule fractions after modulation by Estradiol or ICI. These findings implicate Megacomplex in ERα-driven ovarian cancer chromatin regulation. This combined treatment strategy exhibited superior inhibition of cell proliferation and viability. Therefore, by uncovering ERα's resistance within the Megacomplex, the combined ICI plus JQ1 treatment elucidates a novel drug treatment vulnerability.

Genome-wide detection of a TFIID localization element from an initial human disease mutation.

Eukaryotic core promoters are often characterized by the presence of consensus motifs such as the TATA box or initiator elements, which attract and direct the transcriptional machinery to the transcription start site. However, many human promoters have none of the known core promoter motifs, suggesting that undiscovered promoter motifs exist in the genome. We previously identified a mutation in the human Ankyrin-1 (ANK-1) promoter that causes the disease ankyrin-deficient Hereditary Spherocytosis (HS). Although the ANK-1 promoter is CpG rich, no discernable basal promoter elements had been identified. We showed that the HS mutation disrupted the binding of the transcription factor TFIID, the major component of the pre-initiation complex. We hypothesized that the mutation identified a candidate promoter element with a more widespread role in gene regulation. We examined 17,181 human promoters for the experimentally validated binding site, called the TFIID localization sequence (DLS) and found three times as many promoters containing DLS than TATA motifs. Mutational analyses of DLS sequences confirmed their functional significance, as did the addition of a DLS site to a minimal Sp1 promoter. Our results demonstrate that novel promoter elements can be identified on a genome-wide scale through observations of regulatory disruptions that cause human disease.

Evaluating Stacked Methylation Markers for Blood-Based Multicancer Detection.

The ability to detect several types of cancer using a non-invasive, blood-based test holds the potential to revolutionize oncology screening. We mined tumor methylation array data from the Cancer Genome Atlas (TCGA) covering 14 cancer types and identified two novel, broadly-occurring methylation markers at TLX1 and GALR1. To evaluate their performance as a generalized blood-based screening approach, along with our previously reported methylation biomarker, ZNF154, we rigorously assessed each marker individually or combined. Utilizing TCGA methylation data and applying logistic regression models within each individual cancer type, we found that the three-marker combination significantly increased the average area under the ROC curve (AUC) across the 14 tumor types compared to single markers (p = 1.158 × 10-10; Friedman test). Furthermore, we simulated dilutions of tumor DNA into healthy blood cell DNA and demonstrated increased AUC of combined markers across all dilution levels. Finally, we evaluated assay performance in bisulfite sequenced DNA from patient tumors and plasma, including early-stage samples. When combining all three markers, the assay correctly identified nine out of nine lung cancer plasma samples. In patient plasma from hepatocellular carcinoma, ZNF154 alone yielded the highest combined sensitivity and specificity values averaging 68% and 72%, whereas multiple markers could achieve higher sensitivity or specificity, but not both. Altogether, this study presents a comprehensive pipeline for the identification, testing, and validation of multi-cancer methylation biomarkers with a considerable potential for detecting a broad range of cancer types in patient blood samples.