Novel genome-wide DNA methylation profiling reveals distinct epigenetic landscape, prognostic model and cellular composition of early-stage lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) has been a leading cause of cancer-related mortality worldwide. Early intervention can significantly improve prognosis. DNA methylation could occur in the early stage of tumor. Comprehensive understanding the epigenetic landscape of early-stage LUAD is crucial in understanding tumorigenesis. METHODS: Enzymatic methyl sequencing (EM-seq) was performed on 23 tumors and paired normal tissue to reveal distinct epigenetic landscape, for compared with The Cancer Genome Atlas (TCGA) 450K methylation microarray data. Then, an integrative analysis was performed combined with TCGA LUAD RNA-seq data to identify significant differential methylated and expressed genes. Subsequently, the prognostic risk model was constructed and cellular composition was analyzed. RESULTS: Methylome analysis of EM-seq comparing tumor and normal tissues identified 25 million cytosine-phosphate-guanine (CpG) sites and 30,187 differentially methylated regions (DMR) with a greater number of untraditional types. EM-seq identified a significantly higher number of CpG sites and DMRs compared to the 450K microarray. By integrating the differentially methylated genes (DMGs) with LUAD-related differentially expressed genes (DEGs) from the TCGA database, we constructed prognostic model based on six differentially methylated-expressed genes (MEGs) and verified our prognostic model in GSE13213 and GSE42127 dataset. Finally, cell deconvolution based on the in-house EM-seq methylation profile was used to estimate cellular composition of early-stage LUAD. CONCLUSIONS: This study firstly delves into novel pattern of epigenomic DNA methylation and provides a multidimensional analysis of the role of DNA methylation revealed by EM-seq in early-stage LUAD, providing distinctive insights into its potential epigenetic mechanisms.

Whole genome and transcriptome integrated analyses guide clinical care of pediatric poor prognosis cancers.

The role for routine whole genome and transcriptome analysis (WGTA) for poor prognosis pediatric cancers remains undetermined. Here, we characterize somatic mutations, structural rearrangements, copy number variants, gene expression, immuno-profiles and germline cancer predisposition variants in children and adolescents with relapsed, refractory or poor prognosis malignancies who underwent somatic WGTA and matched germline sequencing. Seventy-nine participants with a median age at enrollment of 8.8 y (range 6 months to 21.2 y) are included. Germline pathogenic/likely pathogenic variants are identified in 12% of participants, of which 60% were not known prior. Therapeutically actionable variants are identified by targeted gene report and whole genome in 32% and 62% of participants, respectively, and increase to 96% after integrating transcriptome analyses. Thirty-two molecularly informed therapies are pursued in 28 participants with 54% achieving a clinical benefit rate; objective response or stable disease ≥6 months. Integrated WGTA identifies therapeutically actionable variants in almost all tumors and are directly translatable to clinical care of children with poor prognosis cancers.

Genome-wide identification of replication fork stalling/pausing sites and the interplay between RNA Pol II transcription and DNA replication progression.

BACKGROUND: DNA replication progression can be affected by the presence of physical barriers like the RNA polymerases, leading to replication stress and DNA damage. Nonetheless, we do not know how transcription influences overall DNA replication progression. RESULTS: To characterize sites where DNA replication forks stall and pause, we establish a genome-wide approach to identify them. This approach uses multiple timepoints during S-phase to identify replication fork/stalling hotspots as replication progresses through the genome. These sites are typically associated with increased DNA damage, overlapped with fragile sites and with breakpoints of rearrangements identified in cancers but do not overlap with replication origins. Overlaying these sites with a genome-wide analysis of RNA polymerase II transcription, we find that replication fork stalling/pausing sites inside genes are directly related to transcription progression and activity. Indeed, we find that slowing down transcription elongation slows down directly replication progression through genes. This indicates that transcription and replication can coexist over the same regions. Importantly, rearrangements found in cancers overlapping transcription-replication collision sites are detected in non-transformed cells and increase following treatment with ATM and ATR inhibitors. At the same time, we find instances where transcription activity favors replication progression because it reduces histone density. CONCLUSIONS: Altogether, our findings highlight how transcription and replication overlap during S-phase, with both positive and negative consequences for replication fork progression and genome stability by the coexistence of these two processes.

Geographic variation of mutagenic exposures in kidney cancer genomes.

International differences in the incidence of many cancer types indicate the existence of carcinogen exposures that have not yet been identified by conventional epidemiology make a substantial contribution to cancer burden1. In clear cell renal cell carcinoma, obesity, hypertension and tobacco smoking are risk factors, but they do not explain the geographical variation in its incidence2. Underlying causes can be inferred by sequencing the genomes of cancers from populations with different incidence rates and detecting differences in patterns of somatic mutations. Here we sequenced 962 clear cell renal cell carcinomas from 11 countries with varying incidence. The somatic mutation profiles differed between countries. In Romania, Serbia and Thailand, mutational signatures characteristic of aristolochic acid compounds were present in most cases, but these were rare elsewhere. In Japan, a mutational signature of unknown cause was found in more than 70% of cases but in less than 2% elsewhere. A further mutational signature of unknown cause was ubiquitous but exhibited higher mutation loads in countries with higher incidence rates of kidney cancer. Known signatures of tobacco smoking correlated with tobacco consumption, but no signature was associated with obesity or hypertension, suggesting that non-mutagenic mechanisms of action underlie these risk factors. The results of this study indicate the existence of multiple, geographically variable, mutagenic exposures that potentially affect tens of millions of people and illustrate the opportunities for new insights into cancer causation through large-scale global cancer genomics.

Haplotype-resolved assembly of diploid and polyploid genomes using quantum computing.

Precision medicine's emphasis on individual genetic variants highlights the importance of haplotype-resolved assembly, a computational challenge in bioinformatics given its combinatorial nature. While classical algorithms have made strides in addressing this issue, the potential of quantum computing remains largely untapped. Here, we present the vehicle routing problem (VRP) assembler: an approach that transforms this task into a vehicle routing problem, an optimization formulation solvable on a quantum computer. We demonstrate its potential and feasibility through a proof of concept on short synthetic diploid and triploid genomes using a D-Wave quantum annealer. To tackle larger-scale assembly problems, we integrate the VRP assembler with Google's OR-Tools, achieving a haplotype-resolved local assembly across the human major histocompatibility complex (MHC) region. Our results show encouraging performance compared to Hifiasm with phasing accuracy approaching the theoretical limit, underscoring the promising future of quantum computing in bioinformatics.

Leveraging functional genomic annotations and genome coverage to improve polygenic prediction of complex traits within and between ancestries.

We develop a method, SBayesRC, that integrates genome-wide association study (GWAS) summary statistics with functional genomic annotations to improve polygenic prediction of complex traits. Our method is scalable to whole-genome variant analysis and refines signals from functional annotations by allowing them to affect both causal variant probability and causal effect distribution. We analyze 50 complex traits and diseases using ∼7 million common single-nucleotide polymorphisms (SNPs) and 96 annotations. SBayesRC improves prediction accuracy by 14% in European ancestry and up to 34% in cross-ancestry prediction compared to the baseline method SBayesR, which does not use annotations, and outperforms other methods, including LDpred2, LDpred-funct, MegaPRS, PolyPred-S and PRS-CSx. Investigation of factors affecting prediction accuracy identifies a significant interaction between SNP density and annotation information, suggesting whole-genome sequence variants with annotations may further improve prediction. Functional partitioning analysis highlights a major contribution of evolutionary constrained regions to prediction accuracy and the largest per-SNP contribution from nonsynonymous SNPs.

N6-adenosine methylation and the regulatory mechanism on LINE-1.

Long interspersed elements-1(LINE-1) is the only autonomous transposon in human genome，and its retrotransposition results in change of cellular genome structure and function, leading occurrence of various severe diseases. As a central key intermediated component during life cycle of LINE-1 retrotransposition, the host modification of LINE-1 mRNA affects the LINE-1 transposition directly. N6-adenosine methylation(m6A), the most abundant epigenetic modification on eukaryotic RNA, is dynamically reversible. m6A modification is also found on LINE-1 mRNA, and it participants regulation of the whole LINE-1 replication cycle, with affecting LINE-1 retrotransposition as well as its adjacent genes expression, followed by influencing genomic stability, cellular self-renewal, and differentiation potential, which plays important roles in human development and diseases. In this review, we summarize the research progress in LINE-1 m6A modification, including its modification positions, patterns and related mechanisms, hoping to provide a new sight on the mechanism research and treatment of related diseases.

Human Vault RNAs: Exploring Their Potential Role in Cellular Metabolism.

Non-coding RNAs have been described as crucial regulators of gene expression and guards of cellular homeostasis. Some recent papers focused on vault RNAs, one of the classes of non-coding RNA, and their role in cell proliferation, tumorigenesis, apoptosis, cancer response to therapy, and autophagy, which makes them potential therapy targets in oncology. In the human genome, four vault RNA paralogues can be distinguished. They are associated with vault complexes, considered the largest ribonucleoprotein complexes. The protein part of these complexes consists of a major vault protein (MVP) and two minor vault proteins (vPARP and TEP1). The name of the complex, as well as vault RNA, comes from the hollow barrel-shaped structure that resembles a vault. Their sequence and structure are highly evolutionarily conserved and show many similarities in comparison with different species, but vault RNAs have various roles. Vaults were discovered in 1986, and their functions remained unclear for many years. Although not much is known about their contribution to cell metabolism, it has become clear that vault RNAs are involved in various processes and pathways associated with cancer progression and modulating cell functioning in normal and pathological stages. In this review, we discuss known functions of human vault RNAs in the context of cellular metabolism, emphasizing processes related to cancer and cancer therapy efficacy.

sOCP: a framework predicting smORF coding potential based on TIS and in-frame features and effectively applied in the human genome.

Small open reading frames (smORFs) have been acknowledged to play various roles on essential biological pathways and affect human beings from diabetes to tumorigenesis. Predicting smORFs in silico is quite a prerequisite for processing the omics data. Here, we proposed the smORF-coding-potential-predicting framework, sOCP, which provides functions to construct a model for predicting novel smORFs in some species. The sOCP model constructed in human was based on in-frame features and the nucleotide bias around the start codon, and the small feature subset was proved to be competent enough and avoid overfitting problems for complicated models. It showed more advanced prediction metrics than previous methods and could correlate closely with experimental evidence in a heterogeneous dataset. The model was applied to Rattus norvegicus and exhibited satisfactory performance. We then scanned smORFs with ATG and non-ATG start codons from the human genome and generated a database containing about a million novel smORFs with coding potential. Around 72 000 smORFs are located on the lncRNA regions of the genome. The smORF-encoded peptides may be involved in biological pathways rare for canonical proteins, including glucocorticoid catabolic process and the prokaryotic defense system. Our work provides a model and database for human smORF investigation and a convenient tool for further smORF prediction in other species.

STRIDE-DB: a comprehensive database for exploration of instability and phenotypic relevance of short tandem repeats in the human genome.

Short Tandem Repeats (STRs) are genetic markers made up of repeating DNA sequences. The variations of the STRs are widely studied in forensic analysis, population studies and genetic testing for a variety of neuromuscular disorders. Understanding polymorphic STR variation and its cause is crucial for deciphering genetic information and finding links to various disorders. In this paper, we present STRIDE-DB, a novel and unique platform to explore STR Instability and its Phenotypic Relevance, and a comprehensive database of STRs in the human genome. We utilized RepeatMasker to identify all the STRs in the human genome (hg19) and combined it with frequency data from the 1000 Genomes Project. STRIDE-DB, a user-friendly resource, plays a pivotal role in investigating the relationship between STR variation, instability and phenotype. By harnessing data from genome-wide association studies (GWAS), ClinVar database, Alu loci, Haploblocks in genome and Conservation of the STRs, it serves as an important tool for researchers exploring the variability of STRs in the human genome and its direct impact on phenotypes. STRIDE-DB has its broad applicability and significance in various research domains like forensic sciences and other repeat expansion disorders. Database URL: https://stridedb.igib.res.in.

Targeted phasing of 2-200 kilobase DNA fragments with a short-read sequencer and a single-tube linked-read library method.

In the human genome, heterozygous sites refer to genomic positions with a different allele or nucleotide variant on the maternal and paternal chromosomes. Resolving these allelic differences by chromosomal copy, also known as phasing, is achievable on a short-read sequencer when using a library preparation method that captures long-range genomic information. TELL-Seq is a library preparation that captures long-range genomic information with the aid of molecular identifiers (barcodes). The same barcode is used to tag the reads derived from the same long DNA fragment within a range of up to 200 kilobases (kb), generating linked-reads. This strategy can be used to phase an entire genome. Here, we introduce a TELL-Seq protocol developed for targeted applications, enabling the phasing of enriched loci of varying sizes, purity levels, and heterozygosity. To validate this protocol, we phased 2-200 kb loci enriched with different methods: CRISPR/Cas9-mediated excision coupled with pulse-field electrophoresis for the longest fragments, CRISPR/Cas9-mediated protection from exonuclease digestion for mid-size fragments, and long PCR for the shortest fragments. All selected loci have known clinical relevance: BRCA1, BRCA2, MLH1, MSH2, MSH6, APC, PMS2, SCN5A-SCN10A, and PKI3CA. Collectively, the analyses show that TELL-Seq can accurately phase 2-200 kb targets using a short-read sequencer.

Accelerated somatic mutation calling for whole-genome and whole-exome sequencing data from heterogenous tumor samples.

Accurate detection of somatic mutations in DNA sequencing data is a fundamental prerequisite for cancer research. Previous analytical challenges were overcome by consensus mutation calling from four to five popular callers. This, however, increases the already nontrivial computing time from individual callers. Here, we launch MuSE 2, powered by multistep parallelization and efficient memory allocation, to resolve the computing time bottleneck. MuSE 2 speeds up 50 times more than MuSE 1 and eight to 80 times more than other popular callers. Our benchmark study suggests combining MuSE 2 and the recently accelerated Strelka2 achieves high efficiency and accuracy in analyzing large cancer genomic data sets.

Aspiring toward equitable benefits from genomic advances to individuals of ancestrally diverse backgrounds.

Advancements in genomic technologies have shown remarkable promise for improving health trajectories. The Human Genome Project has catalyzed the integration of genomic tools into clinical practice, such as disease risk assessment, prenatal testing and reproductive genomics, cancer diagnostics and prognostication, and therapeutic decision making. Despite the promise of genomic technologies, their full potential remains untapped without including individuals of diverse ancestries and integrating social determinants of health (SDOHs). The NHGRI launched the 2020 Strategic Vision with ten bold predictions by 2030, including "individuals from ancestrally diverse backgrounds will benefit equitably from advances in human genomics." Meeting this goal requires a holistic approach that brings together genomic advancements with careful consideration to healthcare access as well as SDOHs to ensure that translation of genetics research is inclusive, affordable, and accessible and ultimately narrows rather than widens health disparities. With this prediction in mind, this review delves into the two paramount applications of genetic testing-reproductive genomics and precision oncology. When discussing these applications of genomic advancements, we evaluate current accessibility limitations, highlight challenges in achieving representativeness, and propose paths forward to realize the ultimate goal of their equitable applications.

Structural Features and Physiological Associations of Human 14-3-3ζ Pseudogenes.

There are about 14,000 pseudogenes that are mutated or truncated sequences resembling functional parent genes. About two-thirds of pseudogenes are processed, while others are duplicated. Although initially thought dead, emerging studies indicate they have functional and regulatory roles. We study 14-3-3ζ, an adaptor protein that regulates cytokine signaling and inflammatory diseases, including rheumatoid arthritis, cancer, and neurological disorders. To understand how 14-3-3ζ (gene symbol YWHAZ) performs diverse functions, we examined the human genome and identified nine YWHAZ pseudogenes spread across many chromosomes. Unlike the 32 kb exon-to-exon sequence in YWHAZ, all pseudogenes are much shorter and lack introns. Out of six, four YWHAZ exons are highly conserved, but the untranslated region (UTR) shows significant diversity. The putative amino acid sequence of pseudogenes is 78-97% homologous, resulting in striking structural similarities with the parent protein. The OMIM and Decipher database searches revealed chromosomal loci containing pseudogenes are associated with human diseases that overlap with the parent gene. To the best of our knowledge, this is the first report on pseudogenes of the 14-3-3 family protein and their implications for human health. This bioinformatics-based study introduces a new insight into the complexity of 14-3-3ζ's functions in biology.

Genome-first evaluation with exome sequence and clinical data uncovers underdiagnosed genetic disorders in a large healthcare system.

Population-based genomic screening may help diagnose individuals with disease-risk variants. Here, we perform a genome-first evaluation for nine disorders in 29,039 participants with linked exome sequences and electronic health records (EHRs). We identify 614 individuals with 303 pathogenic/likely pathogenic or predicted loss-of-function (P/LP/LoF) variants, yielding 644 observations; 487 observations (76%) lack a corresponding clinical diagnosis in the EHR. Upon further investigation, 75 clinically undiagnosed observations (15%) have evidence of symptomatic untreated disease, including familial hypercholesterolemia (3 of 6 [50%] undiagnosed observations with disease evidence) and breast cancer (23 of 106 [22%]). These genetic findings enable targeted phenotyping that reveals new diagnoses in previously undiagnosed individuals. Disease yield is greater with variants in penetrant genes for which disease is observed in carriers in an independent cohort. The prevalence of P/LP/LoF variants exceeds that of clinical diagnoses, and some clinically undiagnosed carriers are discovered to have disease. These results highlight the potential of population-based genomic screening.

Clinical Value of Molecular Targets and FDA-Approved Genome-Targeted Cancer Therapies.

Importance: The number of new genome-targeted cancer drugs has increased, offering the possibility of personalized therapy, often at a very high cost. Objective: To assess the validity of molecular targets and therapeutic benefits of US Food and Drug Administration-approved genome-targeted cancer drugs based on the outcomes of their corresponding pivotal clinical trials. Design and Settings: In this cohort study, all genome-targeted cancer drugs that were FDA-approved between January 1, 2015, and December 31, 2022, were analyzed. From FDA drug labels and trial reports, key characteristics of pivotal trials were extracted, including the outcomes assessed. Main Outcomes and Measures: The strength of evidence supporting molecular targetability was assessed using the European Society for Medical Oncology (ESMO) Scale for Clinical Actionability of Molecular Targets (ESCAT). Clinical benefit for their approved indications was evaluated using the ESMO-Magnitude of Clinical Benefit Scale (ESMO-MCBS). Substantial clinical benefit was defined as a grade of A or B for curative intent and 4 or 5 for noncurative intent. Molecular targets qualifying for ESCAT category level I-A and I-B associated with substantial clinical benefit by ESMO-MCBS were rated as high-benefit genomic-based cancer treatments. Results: A total of 50 molecular-targeted drugs covering 84 indications were analyzed. Forty-five indications (54%) were approved based on phase 1 or phase 2 pivotal trials, 45 (54%) were supported by single-arm pivotal trials, and 48 (57%) were approved on the basis of subgroup analyses. By each indication, 46 of 84 primary end points (55%) were overall response rate (median [IQR] overall response rate, 57% [40%-69%]; median [IQR] duration of response, 11.1 [9.2-19.8] months). Among the 84 pivotal trials supporting these 84 indications, 38 trials (45%) had I-A ESCAT targetability, and 32 (38%) had I-B targetability. Overall, 24 of 84 trials (29%) demonstrated substantial clinical benefit via ESMO-MCBS. Combining these ratings, 24 of 84 indications (29%) were associated with high-benefit genomic-based cancer treatments. Conclusions and Relevance: The results of this cohort study demonstrate that among recently approved molecular-targeted cancer therapies, fewer than one-third demonstrated substantial patient benefits at approval. Benefit frameworks such as ESMO-MCBS and ESCAT can help physicians, patients, and payers identify therapies with the greatest clinical potential.

Deconstructing cancer with precision genome editing.

Recent advances in genome editing technologies are allowing investigators to engineer and study cancer-associated mutations in their endogenous genetic contexts with high precision and efficiency. Of these, base editing and prime editing are quickly becoming gold-standards in the field due to their versatility and scalability. Here, we review the merits and limitations of these precision genome editing technologies, their application to modern cancer research, and speculate how these could be integrated to address future directions in the field.

SAFB restricts contact domain boundaries associated with L1 chimeric transcription.

Long interspersed element-1 (LINE-1 or L1) comprises 17% of the human genome, continuously generates genetic variations, and causes disease in certain cases. However, the regulation and function of L1 remain poorly understood. Here, we uncover that L1 can enrich RNA polymerase IIs (RNA Pol IIs), express L1 chimeric transcripts, and create contact domain boundaries in human cells. This impact of L1 is restricted by a nuclear matrix protein scaffold attachment factor B (SAFB) that recognizes transcriptionally active L1s by binding L1 transcripts to inhibit RNA Pol II enrichment. Acute inhibition of RNA Pol II transcription abolishes the domain boundaries associated with L1 chimeric transcripts, indicating a transcription-dependent mechanism. Deleting L1 impairs domain boundary formation, and L1 insertions during evolution have introduced species-specific domain boundaries. Our data show that L1 can create RNA Pol II-enriched regions that alter genome organization and that SAFB regulates L1 and RNA Pol II activity to preserve gene regulation.

Genome-wide screening and functional validation of methylation barriers near promoters.

CpG islands near promoters are normally unmethylated despite being surrounded by densely methylated regions. Aberrant hypermethylation of these CpG islands has been associated with the development of various human diseases. Although local genetic elements have been speculated to play a role in protecting promoters from methylation, only a limited number of methylation barriers have been identified. In this study, we conducted an integrated computational and experimental investigation of colorectal cancer methylomes. Our study revealed 610 genes with disrupted methylation barriers. Genomic sequences of these barriers shared a common 41-bp sequence motif (MB-41) that displayed homology to the chicken HS4 methylation barrier. Using the CDKN2A (P16) tumor suppressor gene promoter, we validated the protective function of MB-41 and showed that loss of such protection led to aberrant hypermethylation. Our findings highlight a novel sequence signature of cis-acting methylation barriers in the human genome that safeguard promoters from silencing.