The chromatin accessibility landscape of primary human cancers

TFTG: A comprehensive database for human transcription factors and their targets

Transcription factors (TFs) are major contributors to gene transcription, especially in controlling cell-specific gene expression and disease occurrence and development. Uncovering the relationship between TFs and their target genes is critical to understanding the mechanism of action of TFs. With the development of high-throughput sequencing techniques, a large amount of TF-related data has accumulated, which can be used to identify their target genes. In this study, we developed TFTG (Transcription Factor and Target Genes) database (http://tf.liclab.net/TFTG), which aimed to provide a large number of available human TF-target gene resources by multiple strategies, besides performing a comprehensive functional and epigenetic annotations and regulatory analyses of TFs. We identified extensive available TF-target genes by collecting and processing TF-associated ChIP-seq datasets, perturbation RNA-seq datasets and motifs. We also obtained experimentally confirmed relationships between TF and target genes from available resources. Overall, the target genes of TFs were obtained through integrating the relevant data of various TFs as well as fourteen identification strategies. Meanwhile, TFTG was embedded with user-friendly search, analysis, browsing, downloading and visualization functions. TFTG is designed to be a convenient resource for exploring human TF-target gene regulations, which will be useful for most users in the TF and gene expression regulation research.

Mapping cell diversity in human sporadic cerebral cavernous malformations

BACKGROUND

Cerebral cavernous malformation (CCM) is a low-flow, bleeding-prone vascular disease that can cause cerebral hemorrhage, seizure and neurological deficits. Its inheritance mode includes sporadic or autosomal dominant inheritance with incomplete penetrance, namely sporadic CCM (SCCM) and familial CCM. SCCM is featured by single lesion and single affection in a family. Among CCM patients especially SCCM, the pathogenesis of the corresponding phenotypes and pathological features or candidate genes have not been fully elucidated yet.

METHODS

Here, we performed in-depth single-cell RNA sequencing (scRNA-Seq) and bulk assay for transposase-accessible chromatin sequencing (ATAC-Seq) in SCCM and control patients. Further validation was conducted for the gene of interest using qPCR and RNA in situ hybridization (RNA FISH) techniques to provide further atlas and evidence for SCCM generative process.

RESULTS

We identified six cell types in the SCCM and control vessels and found that the expression of NEK1, RNPC3, FBRSL1, IQGAP2, MCUB, AP3B1, ESCO1, MYO9B and PVT1 were up-regulated in SCCM tissues. Among the six cell types, we found that compared with control conditions, PVT1 showed a rising peak which followed the pseudo-time axis in endothelial cell clusters of SCCM samples, while showed an increasing trend in smooth muscle cell clusters of SCCM samples. Further experiments indicated that, compared with the control vessels, PVT1 exhibited significantly elevated expression in SCCM samples.

CONCLUSION

In SCCM conditions, We found that in the process of development from control to lesion conditions, PVT1 showed a rising peak in endothelial cells and showed an increasing trend in smooth muscle cells at the same time. Overall, there was a significantly elevated expression of NEK1, RNPC3, FBRSL1, IQGAP2, MCUB, AP3B1, ESCO1, MYO9B and PVT1 in SCCM specimens compared to control samples.

Deconvoluting multi-person biological mixtures and accurate characterization and identification of separated contributors using non-targeted single-cell DNA sequencing

The genetic characterization and identification of individuals who contributed to biological mixtures are complex and mostly unresolved tasks. These tasks are relevant in various fields, particularly in forensic investigations, which frequently encounters crime scene stains generated by more than one person. Currently, forensic mixture deconvolution is mostly performed subsequent to forensic DNA profiling at the level of the mixed DNA profiles, which comes with several limitations. Some previous studies attempted at separating single cells prior to forensic DNA profiling. However, these approaches are biased at selection of the cells and, due to their targeted DNA analysis on low template DNA, provide incomplete and unreliable forensic DNA profiles. We recently demonstrated the feasibility of performing mixture deconvolution prior to forensic DNA profiling through the utilization of a non-targeted single-cell transcriptome sequencing (scRNA-seq). In addition to individual-specific mixture deconvolution, this approach also allowed accurate characterisation of biological sex, biogeographic ancestry and individual identification of the separated mixture contributors. However, RNA has the forensic disadvantage of being prone to degradation, and sequencing RNA - focussing on coding regions - limits the number of single nucleotide polymorphisms (SNPs) utilized for genetic mixture deconvolution, characterization, and identification. These limitations can be overcome by performing single-cell sequencing on the level of DNA instead of RNA. Here, for the first time, we applied non-targeted single-cell DNA sequencing (scDNA-seq) by applying the scATAC-seq (Assay for Transposase-Accessible Chromatin with sequencing) technique to address the challenges of mixture deconvolution in the forensic context. We demonstrated that scATAC-seq, together with our recently developed De-goulash data analysis pipeline, is capable of deconvoluting complex blood mixtures of five individuals from both sexes with varying biogeographic ancestries. We further showed that our approach achieved correct genetic characterization of the biological sex and the biogeographic ancestry of each of the separated mixture contributors and established their identity. Furthermore, by analysing in-silico generated scATAC-seq data mixtures, we demonstrated successful individual-specific mixture deconvolution of i) highly complex mixtures of 11 individuals, ii) balanced mixtures containing as few as 20 cells (10 per each individual), and iii) imbalanced mixtures with a ratio as low as 1:80. Overall, our proof-of-principle study demonstrates the general feasibility of scDNA-seq in general, and scATAC-seq in particular, for mixture deconvolution, genetic characterization and individual identification of the separated mixture contributors. Furthermore, it shows that compared to scRNA-seq, scDNA-seq detects more SNPs from fewer cells, providing higher sensitivity, that is valuable in forensic genetics.

From degraded to deciphered: ATAC-seq's application potential in forensic diagnosis

In recent years, molecular biology-based diagnostic techniques have made remarkable strides and are now extensively utilized in clinical practice, providing invaluable insights for disease diagnosis and treatment. However, forensic medicine, especially forensic pathology, has witnessed relatively limited progress in the application of molecular biology technologies. A significant challenge in employing molecular techniques for forensic diagnoses lies in the quantitative and qualitative changes observed in diagnostic markers due to sample degradation-a recognized and formidable obstacle. Inspired by the success of DNA sequencing in forensic practices, which enables accurate individual identification even in cases involving degraded and deteriorated tissues and organs, we propose the application of the assay for transposase-accessible chromatin with sequencing (ATAC-seq) to identify targets at the transcriptional onset, exploring chromatin and DNA-level alterations for injury and disease inference in forensic samples. This study employs ATAC-seq to explore alterations in chromatin accessibility post-injury and their subsequent changes over a 2-h degradation period, employing traumatic brain injury (TBI) as a representative model. Our findings reveal high sensitivity of chromatin accessibility sites to injury, evidenced by shifts in thousands of peak positions post-TBI. Remarkably, these alterations remain largely unaffected by early degradation. Our results robustly endorse the notion that integrating and incorporating these specific loci for injury and disease diagnosis in forensic samples holds tremendous promise for practical application. We further validated the above results using human cortical tissue, which supported that early degradation did not significantly affect chromatin accessibility. This pioneering advancement in molecular diagnostic techniques may revolutionize the field of forensic science, especially forensic pathology.

Systematically Evaluating Cell-Free DNA Fragmentation Patterns for Cancer Diagnosis and Enhanced Cancer Detection via Integrating Multiple Fragmentation Patterns

Cell-free DNA (cfDNA) fragmentation patterns have immense potential for early cancer detection. However, the definition of fragmentation varies, ranging from the entire genome to specific genomic regions. These patterns have not been systematically compared, impeding broader research and practical implementation. Here, 1382 plasma cfDNA sequencing samples from 8 cancer types are collected. Considering that cfDNA within open chromatin regions is more susceptible to fragmentation, 10 fragmentation patterns within open chromatin regions as features and employed machine learning techniques to evaluate their performance are examined. All fragmentation patterns demonstrated discernible classification capabilities, with the end motif showing the highest diagnostic value for cross-validation. Combining cross and independent validation results revealed that fragmentation patterns that incorporated both fragment length and coverage information exhibited robust predictive capacities. Despite their diagnostic potential, the predictive power of these fragmentation patterns is unstable. To address this limitation, an ensemble classifier via integrating all fragmentation patterns is developed, which demonstrated notable improvements in cancer detection and tissue-of-origin determination. Further functional bioinformatics investigations on significant feature intervals in the model revealed its impressive ability to identify critical regulatory regions involved in cancer pathogenesis.

Epigenomic signatures of sarcomatoid differentiation to guide the treatment of renal cell carcinoma

Renal cell carcinoma with sarcomatoid differentiation (sRCC) is associated with poor survival and a heightened response to immune checkpoint inhibitors (ICIs). Two major barriers to improving outcomes for sRCC are the limited understanding of its gene regulatory programs and the low diagnostic yield of tumor biopsies due to spatial heterogeneity. Herein, we characterized the epigenomic landscape of sRCC by profiling 107 epigenomic libraries from tissue and plasma samples from 50 patients with RCC and healthy volunteers. By profiling histone modifications and DNA methylation, we identified highly recurrent epigenomic reprogramming enriched in sRCC. Furthermore, CRISPRa experiments implicated the transcription factor FOSL1 in activating sRCC-associated gene regulatory programs, and FOSL1 expression was associated with the response to ICIs in RCC in two randomized clinical trials. Finally, we established a blood-based diagnostic approach using detectable sRCC epigenomic signatures in patient plasma, providing a framework for discovering epigenomic correlates of tumor histology via liquid biopsy.

Integrated single-cell analysis defines the epigenetic basis of castration-resistant prostate luminal cells

Understanding prostate response to castration and androgen receptor signaling inhibitors (ARSI) is critical to improving long-term prostate cancer (PCa) patient survival. Here, we use a multi-omics approach on 229,794 single cells to create a mouse single-cell reference atlas for interpreting mouse prostate biology and castration response. Our reference atlas refines single-cell annotations and provides a chromatin context, which, when coupled with mouse lineage tracing, demonstrates that castration-resistant luminal cells are distinct from the pre-existent urethra-proximal stem/progenitor cells. Molecular pathway analysis and therapeutic studies further implicate AP1 (JUN/FOS), WNT/β-catenin, FOXQ1, NF-κB, and JAK/STAT pathways as major drivers of castration-resistant luminal populations with relevance to human PCa. Our datasets, which can be explored through an interactive portal (https://visportal.roswellpark.org/data/tang/), can aid in developing combination treatments with ARSI for advanced PCa patients.

Mechanism of ERBB2 gene overexpression by the formation of super-enhancer with genomic structural abnormalities in lung adenocarcinoma without clinically actionable genetic alterations

BACKGROUND

In an extensive genomic analysis of lung adenocarcinomas (LUADs), driver mutations have been recognized as potential targets for molecular therapy. However, there remain cases where target genes are not identified. Super-enhancers and structural variants are frequently identified in several hundred loci per case. Despite this, most cancer research has approached the analysis of these data sets separately, without merging and comparing the data, and there are no examples of integrated analysis in LUAD.

METHODS

We performed an integrated analysis of super-enhancers and structural variants in a cohort of 174 LUAD cases that lacked clinically actionable genetic alterations. To achieve this, we conducted both WGS and H3K27Ac ChIP-seq analyses using samples with driver gene mutations and those without, allowing for a comprehensive investigation of the potential roles of super-enhancer in LUAD cases.

RESULTS

We demonstrate that most genes situated in these overlapped regions were associated with known and previously unknown driver genes and aberrant expression resulting from the formation of super-enhancers accompanied by genomic structural abnormalities. Hi-C and long-read sequencing data further corroborated this insight. When we employed CRISPR-Cas9 to induce structural abnormalities that mimicked cases with outlier ERBB2 gene expression, we observed an elevation in ERBB2 expression. These abnormalities are associated with a higher risk of recurrence after surgery, irrespective of the presence or absence of driver mutations.

CONCLUSIONS

Our findings suggest that aberrant gene expression linked to structural polymorphisms can significantly impact personalized cancer treatment by facilitating the identification of driver mutations and prognostic factors, contributing to a more comprehensive understanding of LUAD pathogenesis.

Single-Cell Chromatin Accessibility Analysis Reveals the Epigenetic Basis and Signature Transcription Factors for the Molecular Subtypes of Colorectal Cancers

Colorectal cancer is a highly heterogeneous disease, with well-characterized subtypes based on genome, DNA methylome, and transcriptome signatures. To chart the epigenetic landscape of colorectal cancers, we generated a high-quality single-cell chromatin accessibility atlas of epithelial cells for 29 patients. Abnormal chromatin states acquired in adenomas were largely retained in colorectal cancers, which were tightly accompanied by opposite changes of DNA methylation. Unsupervised analysis on malignant cells revealed two epigenetic subtypes, exactly matching the iCMS classification, and key iCMS-specific transcription factors (TFs) were identified, including HNF4A and PPARA for iCMS2 tumors and FOXA3 and MAFK for iCMS3 tumors. Notably, subtype-specific TFs bind to distinct target gene sets and contribute to both interpatient similarities and diversities for both chromatin accessibilities and RNA expressions. Moreover, we identified CpG-island methylator phenotypes and pinpointed chromatin state signatures and TF regulators for the CIMP-high subtype. Our work systematically revealed the epigenetic basis of the well-known iCMS and CIMP classifications of colorectal cancers.

SIGNIFICANCE

Our work revealed the epigenetic basis of the well-known iCMS and CIMP classifications of colorectal cancers. Moreover, interpatient minor similarities and major diversities of chromatin accessibility signatures of TF target genes can faithfully explain the corresponding interpatient minor similarities and major diversities of RNA expression signatures of colorectal cancers, respectively. This article is featured in Selected Articles from This Issue, p. 897.

MUFFIN: a suite of tools for the analysis of functional sequencing data

The large diversity of functional genomic assays allows for the characterization of non-coding and coding events at the tissue level or at a single-cell resolution. However, this diversity also leads to protocol differences, widely varying sequencing depths, substantial disparities in sample sizes, and number of features. In this work, we have built a Python package, MUFFIN, which offers a wide variety of tools suitable for a broad range of genomic assays and brings many tools that were missing from the Python ecosystem. First, MUFFIN has specialized tools for the exploration of the non-coding regions of genomes, such as a function to identify consensus peaks in peak-called assays, as well as linking genomic regions to genes and performing Gene Set Enrichment Analyses. MUFFIN also possesses a robust and flexible count table processing pipeline, comprising normalization, count transformation, dimensionality reduction, Differential Expression, and clustering. Our tools were tested on three widely different scRNA-seq, ChIP-seq and ATAC-seq datasets. MUFFIN integrates with the popular Scanpy ecosystem and is available on Conda and at https://github.com/pdelangen/Muffin.

Decoding polygenic diseases: advances in noncoding variant prioritization and validation

Genome-wide association studies (GWASs) provide a key foundation for elucidating the genetic underpinnings of common polygenic diseases. However, these studies have limitations in their ability to assign causality to particular genetic variants, especially those residing in the noncoding genome. Over the past decade, technological and methodological advances in both analytical and empirical prioritization of noncoding variants have enabled the identification of causative variants by leveraging orthogonal functional evidence at increasing scale. In this review, we present an overview of these approaches and describe how this workflow provides the groundwork necessary to move beyond associations toward genetically informed studies on the molecular and cellular mechanisms of polygenic disease.

Ultrasensitive plasma-based monitoring of tumor burden using machine-learning-guided signal enrichment

In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole-genome sequencing (WGS). Here we now introduce MRD-EDGE, a machine-learning-guided WGS ctDNA single-nucleotide variant (SNV) and copy-number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by ~300× compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, vastly expanding its applicability within solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in TF in response to neoadjuvant immunotherapy in lung cancer and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables plasma-only (non-tumor-informed) disease monitoring in advanced melanoma and lung cancer, yielding clinically informative TF monitoring for patients on immune-checkpoint inhibition.

Cancer-specific epigenome identifies oncogenic hijacking by nuclear factor I family proteins for medulloblastoma progression

Normal cells coordinate proliferation and differentiation by precise tuning of gene expression based on the dynamic shifts of the epigenome throughout the developmental timeline. Although non-mutational epigenetic reprogramming is an emerging hallmark of cancer, the epigenomic shifts that occur during the transition from normal to malignant cells remain elusive. Here, we capture the epigenomic changes that occur during tumorigenesis in a prototypic embryonal brain tumor, medulloblastoma. By comparing the epigenomes of the different stages of transforming cells in mice, we identify nuclear factor I family of transcription factors, known to be cell fate determinants in development, as oncogenic regulators in the epigenomes of precancerous and cancerous cells. Furthermore, genetic and pharmacological inhibition of NFIB validated a crucial role of this transcription factor by disrupting the cancer epigenome in medulloblastoma. Thus, this study exemplifies how epigenomic changes contribute to tumorigenesis via non-mutational mechanisms involving developmental transcription factors.

Vaginal microbes alter epithelial transcriptome and induce epigenomic modifications providing insight into mechanisms for susceptibility to adverse reproductive outcomes

The cervicovaginal microbiome is highly associated with women's health, with microbial communities dominated by Lactobacillus species considered optimal. Conversely, a lack of lactobacilli and a high abundance of strict and facultative anaerobes, including Gardnerella vaginalis, have been associated with adverse reproductive outcomes. However, how host-microbial interactions alter specific molecular pathways and impact cervical and vaginal epithelial function remains unclear. Using RNA-sequencing, we characterized the in vitro cervicovaginal epithelial transcriptional response to different vaginal bacteria and their culture supernatants. We showed that G. vaginalis upregulates genes associated with an activated innate immune response. Unexpectedly, G. vaginalis specifically induced inflammasome pathways through activation of NLRP3-mediated increases in caspase-1, IL-1β and cell death, while live L. crispatus had minimal transcriptomic changes on epithelial cells. L. crispatus culture supernatants resulted in a shift in the epigenomic landscape of cervical epithelial cells that was confirmed by ATAC-sequencing showing reduced chromatin accessibility. This study reveals new insights into host-microbe interactions in the lower reproductive tract and suggests potential therapeutic strategies leveraging the vaginal microbiome to improve reproductive health.

Genetic dependencies associated with transcription factor activities in human cancer cell lines

Transcription factors (TFs) are important mediators of aberrant transcriptional programs in cancer cells. In this study, we focus on TF activity (TFa) as a biomarker for cell-line-selective anti-proliferative effects, in that high TFa predicts sensitivity to loss of function of a given gene (i.e., genetic dependencies [GDs]). Our linear-regression-based framework identifies 3,047 pan-cancer and 3,952 cancer-type-specific candidate TFa-GD associations from cell line data, which are then cross-examined for impact on survival in patient cohorts. One of the most prominent biomarkers is TEAD1 activity, whose associations with its predicted GDs are validated through experimental evidence as proof of concept. Overall, these TFa-GD associations represent an attractive resource for identifying innovative, biomarker-driven hypotheses for drug discovery programs in oncology.

Cell of origin epigenetic priming determines susceptibility to Tet2 mutation

Hematopoietic stem cell (HSC) mutations can result in clonal hematopoiesis (CH) with heterogeneous clinical outcomes. Here, we investigate how the cell state preceding Tet2 mutation impacts the pre-malignant phenotype. Using an inducible system for clonal analysis of myeloid progenitors, we find that the epigenetic features of clones at similar differentiation status are highly heterogeneous and functionally respond differently to Tet2 mutation. Cell differentiation stage also influences Tet2 mutation response indicating that the cell of origin's epigenome modulates clone-specific behaviors in CH. Molecular features associated with higher risk outcomes include Sox4 that sensitizes cells to Tet2 inactivation, inducing dedifferentiation, altered metabolism and increasing the in vivo clonal output of mutant cells, as confirmed in primary GMP and HSC models. Our findings validate the hypothesis that epigenetic features can predispose specific clones for dominance, explaining why identical genetic mutations can result in different phenotypes.

The Long Non-Coding RNA MALAT1 Modulates NR4A1 Expression through a Downstream Regulatory Element in Specific Cancer Cell Types

Long non-coding RNAs (lncRNAs) have been shown to modulate gene expression and are involved in the initiation and progression of various cancer types. Despite the wealth of studies describing transcriptome changes upon lncRNA knockdown, there is limited information describing lncRNA-mediated effects on regulatory elements (REs) modulating gene expression. In this study, we investigated how the metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) lncRNA regulates primary target genes using time-resolved MALAT1 knockdown followed by parallel RNA-seq and ATAC-seq assays. The results revealed that MALAT1 primarily regulates specific protein-coding genes and a substantial decrease in the accessibility downstream of the NR4A1 gene that was associated with a decreased NR4A1 expression. Moreover, the presence of an NR4A1-downstream RE was demonstrated by CRISPR-i assays to define a functional MALAT1/NR4A1 axis. By analyzing TCGA data, we identified a positive correlation between NR4A1 expression and NR4A1-downstream RE accessibility in breast cancer but not in pancreatic cancer. Accordingly, this regulatory mechanism was experimentally validated in breast cancer cells (MCF7) but not in pancreatic duct epithelial carcinoma (PANC1) cells. Therefore, our results demonstrated that MALAT1 is involved in a molecular mechanism that fine-tunes NR4A1 expression by modulating the accessibility of a downstream RE in a cell type-specific manner.

Estrogen receptor 1 chromatin profiling in human breast tumors reveals high inter-patient heterogeneity with enrichment of risk SNPs and enhancer activity at most-conserved regions

Estrogen Receptor 1 (ESR1; also known as ERα, encoded by ESR1 gene) is the main driver and prime drug target in luminal breast cancer. ESR1 chromatin binding is extensively studied in cell lines and a limited number of human tumors, using consensi of peaks shared among samples. However, little is known about inter-tumor heterogeneity of ESR1 chromatin action, along with its biological implications. Here, we use a large set of ESR1 ChIP-seq data from 70 ESR1+ breast cancers to explore inter-patient heterogeneity in ESR1 DNA binding to reveal a striking inter-tumor heterogeneity of ESR1 action. Of note, commonly shared ESR1 sites show the highest estrogen-driven enhancer activity and are most engaged in long-range chromatin interactions. In addition, the most commonly shared ESR1-occupied enhancers are enriched for breast cancer risk SNP loci. We experimentally confirm SNVs to impact chromatin binding potential for ESR1 and its pioneer factor FOXA1. Finally, in the TCGA breast cancer cohort, we can confirm these variations to associate with differences in expression for the target gene. Cumulatively, we reveal a natural hierarchy of ESR1-chromatin interactions in breast cancers within a highly heterogeneous inter-tumor ESR1 landscape, with the most common shared regions being most active and affected by germline functional risk SNPs for breast cancer development.

A time-resolved multi-omics atlas of transcriptional regulation in response to high-altitude hypoxia across whole-body tissues

High-altitude hypoxia acclimatization requires whole-body physiological regulation in highland immigrants, but the underlying genetic mechanism has not been clarified. Here we use sheep as an animal model for low-to-high altitude translocation. We generate multi-omics data including whole-genome sequences, time-resolved bulk RNA-Seq, ATAC-Seq and single-cell RNA-Seq from multiple tissues as well as phenotypic data from 20 bio-indicators. We characterize transcriptional changes of all genes in each tissue, and examine multi-tissue temporal dynamics and transcriptional interactions among genes. Particularly, we identify critical functional genes regulating the short response to hypoxia in each tissue (e.g., PARG in the cerebellum and HMOX1 in the colon). We further identify TAD-constrained cis-regulatory elements, which suppress the transcriptional activity of most genes under hypoxia. Phenotypic and transcriptional evidence indicate that antenatal hypoxia could improve hypoxia tolerance in offspring. Furthermore, we provide time-series expression data of candidate genes associated with human mountain sickness (e.g., BMPR2) and high-altitude adaptation (e.g., HIF1A). Our study provides valuable resources and insights for future hypoxia-related studies in mammals.

Identification of prognostic stemness-related genes in kidney renal papillary cell carcinoma

BACKGROUND

Kidney renal papillary cell carcinoma (KIRP) is the second most prevalent malignant cancer originating from the renal epithelium. Nowadays, cancer stem cells and stemness-related genes (SRGs) are revealed to play important roles in the carcinogenesis and metastasis of various tumors. Consequently, we aim to investigate the underlying mechanisms of SRGs in KIRP.

METHODS

RNA-seq profiles of 141 KIRP samples were downloaded from the TCGA database, based on which we calculated the mRNA expression-based stemness index (mRNAsi). Next, we selected the differentially expressed genes (DEGs) between low- and high-mRNAsi groups. Then, we utilized weighted gene correlation network analysis (WGCNA) and univariate Cox analysis to identify prognostic SRGs. Afterwards, SRGs were included in the multivariate Cox regression analysis to establish a prognostic model. In addition, a regulatory network was constructed by Pearson correlation analysis, incorporating key genes, upstream transcription factors (TFs), and downstream signaling pathways. Finally, we used Connectivity map analysis to identify the potential inhibitors.

RESULTS

In total, 1124 genes were characterized as DEGs between low- and high-RNAsi groups. Based on six prognostic SRGs (CCKBR, GPR50, GDNF, SPOCK3, KC877982.1, and MYO15A), a prediction model was established with an area under curve of 0.861. Furthermore, among the TFs, genes, and signaling pathways that had significant correlations, the CBX2-ASPH-Notch signaling pathway was the most significantly correlated. Finally, resveratrol might be a potential inhibitor for KIRP.

CONCLUSIONS

We suggested that CBX2 could regulate ASPH through activation of the Notch signaling pathway, which might be correlated with the carcinogenesis, development, and unfavorable prognosis of KIRP.

Disease related changes in ATAC-seq of iPSC-derived motor neuron lines from ALS patients and controls

Amyotrophic Lateral Sclerosis (ALS), like many other neurodegenerative diseases, is highly heritable, but with only a small fraction of cases explained by monogenic disease alleles. To better understand sporadic ALS, we report epigenomic profiles, as measured by ATAC-seq, of motor neuron cultures derived from a diverse group of 380 ALS patients and 80 healthy controls. We find that chromatin accessibility is heavily influenced by sex, the iPSC cell type of origin, ancestry, and the inherent variance arising from sequencing. Once these covariates are corrected for, we are able to identify ALS-specific signals in the data. Additionally, we find that the ATAC-seq data is able to predict ALS disease progression rates with similar accuracy to methods based on biomarkers and clinical status. These results suggest that iPSC-derived motor neurons recapitulate important disease-relevant epigenomic changes.

Identification of lineage-specific epigenetic regulators FOXA1 and GRHL2 through chromatin accessibility profiling in breast cancer cell lines

Breast cancer is a heterogeneous disease, and breast cancer cell lines are invaluable for studying this heterogeneity. However, the epigenetic diversity across these cell lines remains poorly understood. In this study, we performed genome-wide chromatin accessibility analysis on 23 breast cancer cell lines, including 2 estrogen receptor (ER)-positive/human epidermal growth factor receptor 2 (HER2)-negative (ER+/HER2-), 3 ER+/HER2+, 3 HER2+, and 15 triple-negative breast cancer (TNBC) lines. These cell lines were classified into three groups based on their chromatin accessibility: the receptor-positive group (Group-P), TNBC basal group (Group-B), and TNBC mesenchymal group (Group-M). Motif enrichment analysis revealed that only Group-P exhibited coenrichment of forkhead box A1 (FOXA1) and grainyhead-like 2 (GRHL2) motifs, whereas Group-B was characterized by the presence of the GRHL2 motif without FOXA1. Notably, Group-M did not show enrichment of either FOXA1 or GRHL2 motifs. Furthermore, gene ontology analysis suggested that group-specific accessible regions were associated with their unique lineage characteristics. To investigate the epigenetic landscape regulatory roles of FOXA1 and GRHL2, we performed knockdown experiments targeting FOXA1 and GRHL2, followed by assay for transposase-accessible chromatin sequencing analysis. The findings revealed that FOXA1 maintains Group-P-specific regions while suppressing Group-B-specific regions in Group-P cells. In contrast, GRHL2 preserves commonly accessible regions shared between Group-P and Group-B in Group-B cells, suggesting that FOXA1 and GRHL2 play a pivotal role in preserving distinct chromatin accessibility patterns for each group. Specifically, FOXA1 distinguishes between receptor-positive and TNBC cell lines, whereas GRHL2 distinguishes between basal-like and mesenchymal subtypes in TNBC lines.

The epigenetic regulators EP300/CREBBP represent promising therapeutic targets in MLL-rearranged acute myeloid leukemia

Acute myeloid leukemia (AML) with mixed-lineage leukemia (MLL) gene rearrangements (MLL-r) is an aggressive subtype of blood cancer with dismal prognosis, underscoring the urgent need for novel therapeutic strategies. E1A-binding protein (EP300) and CREB-binding protein (CREBBP) function as essential transcriptional coactivators and acetyltransferases, governing leukemogenesis through diverse mechanisms. Targeting EP300/CREBBP holds great promise for treating leukemia with some certain cytogenetic abnormalities. Here, we demonstrated that EP300 and CREBBP are core epigenetic regulators in the pathogenesis of MLL-r AML through assaying the transposase-accessible chromatin with high-throughput sequencing (ATAC-seq). Knocking-out EP300/CREBBP and inhibitor (A-485) treatment depressed the MLL-r cells proliferation, while the MLL wild-type cells remained uninfluenced. We found that the CDK4/RB/E2F axis was downregulated specifically in MLL-r AML cell after A-485 treatment by RNA-seq, western blot and cut-tag analyses. EP300/CREBBP inhibitor selectively exerted potent anti-leukemia activity through blocking the MLL-r-BET complex binding to H3K27Ac modification on critical genes loci, distinct from global histone acetylation. Collectively, our study identified EP300/CREBBP as a critical epigenetic driver of MLL-r leukemia and validated their therapeutic potential through targeting inhibition, offering a promising avenue for improving clinical outcomes in this aggressive leukemia.

Kataegis in clinical and molecular subgroups of primary breast cancer

Kataegis is a hypermutation phenomenon characterized by localized clusters of single base pair substitution (SBS) reported in multiple cancer types. Despite a high frequency in breast cancer, large-scale analyses of kataegis patterns and associations with clinicopathological and molecular variables in established breast cancer subgroups are lacking. Therefore, WGS profiled primary breast cancers (n = 791) with associated clinical and molecular data layers, like RNA-sequencing data, were analyzed for kataegis frequency, recurrence, and associations with genomic contexts and functional elements, transcriptional patterns, driver alterations, homologous recombination deficiency (HRD), and prognosis in tumor subgroups defined by ER, PR, and HER2/ERBB2 status. Kataegis frequency was highest in the HER2-positive(p) subgroups, including both ER-negative(n)/positive(p) tumors (ERnHER2p/ERpHER2p). In TNBC, kataegis was neither associated with PAM50 nor TNBC mRNA subtypes nor with distant relapse in chemotherapy-treated patients. In ERpHER2n tumors, kataegis was associated with aggressive characteristics, including PR-negativity, molecular Luminal B subtype, higher mutational burden, higher grade, and expression of proliferation-associated genes. Recurrent kataegis loci frequently targeted regions commonly amplified in ER-positive tumors, while few recurrent loci were observed in TNBC. SBSs in kataegis loci appeared enriched in regions of open chromatin. Kataegis status was not associated with HRD in any subgroup or with distinct transcriptional patterns in unsupervised or supervised analysis. In summary, kataegis is a common hypermutation phenomenon in established breast cancer subgroups, particularly in HER2p subgroups, coinciding with an aggressive tumor phenotype in ERpHER2n disease. In TNBC, the molecular implications and associations of kataegis are less clear, including its prognostic value.

Convergent epigenetic evolution drives relapse in acute myeloid leukemia

Relapse of acute myeloid leukemia (AML) is highly aggressive and often treatment refractory. We analyzed previously published AML relapse cohorts and found that 40% of relapses occur without changes in driver mutations, suggesting that non-genetic mechanisms drive relapse in a large proportion of cases. We therefore characterized epigenetic patterns of AML relapse using 26 matched diagnosis-relapse samples with ATAC-seq. This analysis identified a relapse-specific chromatin accessibility signature for mutationally stable AML, suggesting that AML undergoes epigenetic evolution at relapse independent of mutational changes. Analysis of leukemia stem cell (LSC) chromatin changes at relapse indicated that this leukemic compartment underwent significantly less epigenetic evolution than non-LSCs, while epigenetic changes in non-LSCs reflected overall evolution of the bulk leukemia. Finally, we used single-cell ATAC-seq paired with mitochondrial sequencing (mtscATAC) to map clones from diagnosis into relapse along with their epigenetic features. We found that distinct mitochondrially-defined clones exhibit more similar chromatin accessibility at relapse relative to diagnosis, demonstrating convergent epigenetic evolution in relapsed AML. These results demonstrate that epigenetic evolution is a feature of relapsed AML and that convergent epigenetic evolution can occur following treatment with induction chemotherapy.

Proteasome Inhibition Reprograms Chromatin Landscape in Breast Cancer

The 26S proteasome is the major protein degradation machinery in cells. Cancer cells use the proteasome to modulate gene expression networks that promote tumor growth. Proteasome inhibitors have emerged as effective cancer therapeutics, but how they work mechanistically remains unclear. Here, using integrative genomic analysis, we discovered unexpected reprogramming of the chromatin landscape and RNA polymerase II (RNAPII) transcription initiation in breast cancer cells treated with the proteasome inhibitor MG132. The cells acquired dynamic changes in chromatin accessibility at specific genomic loci termed differentially open chromatin regions (DOCR). DOCRs with decreased accessibility were promoter proximal and exhibited unique chromatin architecture associated with divergent RNAPII transcription. Conversely, DOCRs with increased accessibility were primarily distal to transcription start sites and enriched in oncogenic superenhancers predominantly accessible in non-basal breast tumor subtypes. These findings describe the mechanisms by which the proteasome modulates the expression of gene networks intrinsic to breast cancer biology.

SIGNIFICANCE

Our study provides a strong basis for understanding the mechanisms by which proteasome inhibitors exert anticancer effects. We find open chromatin regions that change during proteasome inhibition, are typically accessible in non-basal breast cancers.

Pathogenic role of super-enhancers as potential therapeutic targets in lung cancer

Lung cancer is still one of the deadliest malignancies today, and most patients with advanced lung cancer pass away from disease progression that is uncontrollable by medications. Super-enhancers (SEs) are large clusters of enhancers in the genome's non-coding sequences that actively trigger transcription. Although SEs have just been identified over the past 10 years, their intricate structure and crucial role in determining cell identity and promoting tumorigenesis and progression are increasingly coming to light. Here, we review the structural composition of SEs, the auto-regulatory circuits, the control mechanisms of downstream genes and pathways, and the characterization of subgroups classified according to SEs in lung cancer. Additionally, we discuss the therapeutic targets, several small-molecule inhibitors, and available treatment options for SEs in lung cancer. Combination therapies have demonstrated considerable advantages in preclinical models, and we anticipate that these drugs will soon enter clinical studies and benefit patients.

SMARCA4 is a haploinsufficient B cell lymphoma tumor suppressor that fine-tunes centrocyte cell fate decisions

SMARCA4 encodes one of two mutually exclusive ATPase subunits in the BRG/BRM associated factor (BAF) complex that is recruited by transcription factors (TFs) to drive chromatin accessibility and transcriptional activation. SMARCA4 is among the most recurrently mutated genes in human cancer, including ∼30% of germinal center (GC)-derived Burkitt lymphomas. In mice, GC-specific Smarca4 haploinsufficiency cooperated with MYC over-expression to drive lymphomagenesis. Furthermore, monoallelic Smarca4 deletion drove GC hyperplasia with centroblast polarization via significantly increased rates of centrocyte recycling to the dark zone. Mechanistically, Smarca4 loss reduced the activity of TFs that are activated in centrocytes to drive GC-exit, including SPI1 (PU.1), IRF family, and NF-κB. Loss of activity for these factors phenocopied aberrant BCL6 activity within murine centrocytes and human Burkitt lymphoma cells. SMARCA4 therefore facilitates chromatin accessibility for TFs that shape centrocyte trajectories, and loss of fine-control of these programs biases toward centroblast cell-fate, GC hyperplasia and lymphoma.

Genome-Wide Analysis Identifies Nuclear Factor 1C as a Novel Transcription Factor and Potential Therapeutic Target in SCLC

INTRODUCTION

Recent insights regarding mechanisms mediating stemness, heterogeneity, and metastatic potential of lung cancers have yet to be fully translated to effective regimens for the treatment of these malignancies. This study sought to identify novel targets for lung cancer therapy.

METHODS

Transcriptomes and DNA methylomes of 14 SCLC and 10 NSCLC lines were compared with normal human small airway epithelial cells (SAECs) and induced pluripotent stem cell (iPSC) clones derived from SAEC. SCLC lines, lung iPSC (Lu-iPSC), and SAEC were further evaluated by DNase I hypersensitive site sequencing (DHS-seq). Changes in chromatin accessibility and depths of transcription factor (TF) footprints were quantified using Bivariate analysis of Genomic Footprint. Standard techniques were used to evaluate growth, tumorigenicity, and changes in transcriptomes and glucose metabolism of SCLC cells after NFIC knockdown and to evaluate NFIC expression in SCLC cells after exposure to BET inhibitors.

RESULTS

Considerable commonality of transcriptomes and DNA methylomes was observed between Lu-iPSC and SCLC; however, this analysis was uninformative regarding pathways unique to lung cancer. Linking results of DHS-seq to RNA sequencing enabled identification of networks not previously associated with SCLC. When combined with footprint depth, NFIC, a transcription factor not previously associated with SCLC, had the highest score of occupancy at open chromatin sites. Knockdown of NFIC impaired glucose metabolism, decreased stemness, and inhibited growth of SCLC cells in vitro and in vivo. ChIP-seq analysis identified numerous sites occupied by BRD4 in the NFIC promoter region. Knockdown of BRD4 or treatment with Bromodomain and extra-terminal domain (BET) inhibitors (BETis) markedly reduced NFIC expression in SCLC cells and SCLC PDX models. Approximately 8% of genes down-regulated by BETi treatment were repressed by NFIC knockdown in SCLC, whereas 34% of genes repressed after NFIC knockdown were also down-regulated in SCLC cells after BETi treatment.

CONCLUSIONS

NFIC is a key TF and possible mediator of transcriptional regulation by BET family proteins in SCLC. Our findings highlight the potential of genome-wide chromatin accessibility analysis for elucidating mechanisms of pulmonary carcinogenesis and identifying novel targets for lung cancer therapy.

MYC activity at enhancers drives prognostic transcriptional programs through an epigenetic switch

The transcription factor MYC is overexpressed in most cancers, where it drives multiple hallmarks of cancer progression. MYC is known to promote oncogenic transcription by binding to active promoters. In addition, MYC has also been shown to invade distal enhancers when expressed at oncogenic levels, but this enhancer binding has been proposed to have low gene-regulatory potential. Here, we demonstrate that MYC directly regulates enhancer activity to promote cancer type-specific gene programs predictive of poor patient prognosis. MYC induces transcription of enhancer RNA through recruitment of RNA polymerase II (RNAPII), rather than regulating RNAPII pause-release, as is the case at promoters. This process is mediated by MYC-induced H3K9 demethylation and acetylation by GCN5, leading to enhancer-specific BRD4 recruitment through its bromodomains, which facilitates RNAPII recruitment. We propose that MYC drives prognostic cancer type-specific gene programs through induction of an enhancer-specific epigenetic switch, which can be targeted by BET and GCN5 inhibitors.

Wnt dose escalation during the exit from pluripotency identifies tranilast as a regulator of cardiac mesoderm

Wnt signaling is a critical determinant of cell lineage development. This study used Wnt dose-dependent induction programs to gain insights into molecular regulation of stem cell differentiation. We performed single-cell RNA sequencing of hiPSCs responding to a dose escalation protocol with Wnt agonist CHIR-99021 during the exit from pluripotency to identify cell types and genetic activity driven by Wnt stimulation. Results of activated gene sets and cell types were used to build a multiple regression model that predicts the efficiency of cardiomyocyte differentiation. Cross-referencing Wnt-associated gene expression profiles to the Connectivity Map database, we identified the small-molecule drug, tranilast. We found that tranilast synergistically activates Wnt signaling to promote cardiac lineage differentiation, which we validate by in vitro analysis of hiPSC differentiation and in vivo analysis of developing quail embryos. Our study provides an integrated workflow that links experimental datasets, prediction models, and small-molecule databases to identify drug-like compounds that control cell differentiation.

Oncogenic enhancers prime quiescent metastatic cells to escape NK immune surveillance by eliciting transcriptional memory

Metastasis arises from disseminated tumour cells (DTCs) that are characterized by intrinsic phenotypic plasticity and the capability of seeding to secondary organs. DTCs can remain latent for years before giving rise to symptomatic overt metastasis. In this context, DTCs fluctuate between a quiescent and proliferative state in response to systemic and microenvironmental signals including immune-mediated surveillance. Despite its relevance, how intrinsic mechanisms sustain DTCs plasticity has not been addressed. By interrogating the epigenetic state of metastatic cells, we find that tumour progression is coupled with the activation of oncogenic enhancers that are organized in variable interconnected chromatin domains. This spatial chromatin context leads to the activation of a robust transcriptional response upon repeated exposure to retinoic acid (RA). We show that this adaptive mechanism sustains the quiescence of DTCs through the activation of the master regulator SOX9. Finally, we determine that RA-stimulated transcriptional memory increases the fitness of metastatic cells by supporting the escape of quiescent DTCs from NK-mediated immune surveillance. Overall, these findings highlight the contribution of oncogenic enhancers in establishing transcriptional memories as an adaptive mechanism to reinforce cancer dormancy and immune escape, thus amenable for therapeutic intervention.

Evidence of zoonotic pathogens through biophysically induced genomic variance

Zoonoses are infectious agents that are transmissible between animals and humans. Up to 60% of known infectious diseases and 75% of emergent diseases are zoonotic. Genomic variation between homeostatic populations provides a novel window into the effect of environmental pathogens on allelic distributions within the populations. Genodynamics is a biophysical approach utilizing developed metrics on biallelic single-nucleotide polymorphisms (SNPs) that can be used to quantify the adaptive influences due to pathogens. A genomic free energy that is minimized when overall population health is optimized describes the influence of environmental agents upon genomic variation. A double-blind exploration of over 100 thousand SNPs searching for smooth functional dependencies upon four zoonotic pathogens carried by four possible hosts amidst populations that live in their ancestral environments has been conducted. Exemplars that infectious agents can have significant adaptive influence on human populations are presented. One discussed SNP is likely associated with both adaptive and innate immune regulation. The adaptive response of another SNP suggests an intriguing connection between zoonoses and human cancers. The adaptive forces of the presented pathogens upon the human genome have been quantified.

Identification of a core transcriptional program driving the human renal mesenchymal-to-epithelial transition

During kidney development, nephron epithelia arise de novo from fate-committed mesenchymal progenitors through a mesenchymal-to-epithelial transition (MET). Downstream of fate specification, transcriptional mechanisms that drive establishment of epithelial morphology are poorly understood. We used human iPSC-derived renal organoids, which recapitulate nephrogenesis, to investigate mechanisms controlling renal MET. Multi-ome profiling via snRNA-seq and ATAC-seq of organoids identified dynamic changes in gene expression and chromatin accessibility driven by activators and repressors throughout MET. CRISPR interference identified that paired box 8 (PAX8) is essential for initiation of MET in human renal organoids, contrary to in vivo mouse studies, likely by activating a cell-adhesion program. While Wnt/β-catenin signaling specifies nephron fate, we find that it must be attenuated to allow hepatocyte nuclear factor 1-beta (HNF1B) and TEA-domain (TEAD) transcription factors to drive completion of MET. These results identify the interplay between fate commitment and morphogenesis in the developing human kidney, with implications for understanding both developmental kidney diseases and aberrant epithelial plasticity following adult renal tubular injury.

Uncovering dark matter in cancer by identifying epigenetic drivers

The complex relationship between chromatin accessibility, transcriptional regulation, and cancer transitions presents a daunting puzzle. Terekhanova et al. created a pan-cancer epigenetic and transcriptomic atlas at single-cell resolution, yielding important insights into the underlying chromatin architecture of cancer transitions and novel discoveries with the potential to advance precision medicine.

TSCRE: a comprehensive database for tumor-specific cis-regulatory elements

Cis-regulatory elements (CREs) and super cis-regulatory elements (SCREs) are non-coding DNA regions which influence the transcription of nearby genes and play critical roles in development. Dysregulated CRE and SCRE activities have been reported to alter the expression of oncogenes and tumor suppressors, thereby regulating cancer hallmarks. To address the strong need for a comprehensive catalogue of dysregulated CREs and SCREs in human cancers, we present TSCRE (http://tscre.zsqylab.com/), an open resource providing tumor-specific and cell type-specific CREs and SCREs derived from the re-analysis of publicly available histone modification profiles. Currently, TSCRE contains 1 864 941 dysregulated CREs and 68 253 dysregulated SCREs identified from 1366 human patient samples spanning 17 different cancer types and 9 histone marks. Over 95% of these elements have been validated in public resources. TSCRE offers comprehensive annotations for each element, including associated genes, expression patterns, clinical prognosis, somatic mutations, transcript factor binding sites, cancer-type specificity, and drug response. Additionally, TSCRE integrates pathway and transcript factor enrichment analyses for each study, enabling in-depth functional and mechanistic investigations. Furthermore, TSCRE provides an interactive interface for users to explore any CRE and SCRE of interest. We believe TSCRE will be a highly valuable platform for the community to discover candidate cancer biomarkers.

Moving toward precision medicine to predict drug sensitivity in patients with metastatic breast cancer

Tumor heterogeneity represents a major challenge in breast cancer, being associated with disease progression and treatment resistance. Precision medicine has been extensively applied to dissect tumor heterogeneity and, through a deeper molecular understanding of the disease, to personalize therapeutic strategies. In the last years, technological advances have widely improved the understanding of breast cancer biology and several trials have been developed to translate these new insights into clinical practice, with the ultimate aim of improving patients' outcomes. In the era of molecular oncology, genomics analyses and other methodologies are shaping a new treatment algorithm in breast cancer care. In this manuscript, we review the main steps of precision medicine to predict drug sensitivity in breast cancer from a translational point of view. Genomic developments and their clinical implications are discussed, along with technological advancements that could broaden precision medicine applications. Current achievements are put into perspective to provide an overview of the state-of-art of breast cancer precision oncology as well as to identify future research directions.

[Screening of immune related gene and survival prediction of lung adenocarcinoma patients based on LightGBM model]

Lung cancer is one of the malignant tumors with the greatest threat to human health, and studies have shown that some genes play an important regulatory role in the occurrence and development of lung cancer. In this paper, a LightGBM ensemble learning method is proposed to construct a prognostic model based on immune relate gene (IRG) profile data and clinical data to predict the prognostic survival rate of lung adenocarcinoma patients. First, this method used the Limma package for differential gene expression, used CoxPH regression analysis to screen the IRG to prognosis, and then used XGBoost algorithm to score the importance of the IRG features. Finally, the LASSO regression analysis was used to select IRG that could be used to construct a prognostic model, and a total of 17 IRG features were obtained that could be used to construct model. LightGBM was trained according to the IRG screened. The K-means algorithm was used to divide the patients into three groups, and the area under curve (AUC) of receiver operating characteristic (ROC) of the model output showed that the accuracy of the model in predicting the survival rates of the three groups of patients was 96%, 98% and 96%, respectively. The experimental results show that the model proposed in this paper can divide patients with lung adenocarcinoma into three groups [5-year survival rate higher than 65% (group 1), lower than 65% but higher than 30% (group 2) and lower than 30% (group 3)] and can accurately predict the 5-year survival rate of lung adenocarcinoma patients.

RFX4 is an intrinsic factor for neuronal differentiation through induction of proneural genes POU3F2 and NEUROD1

Proneural genes play a crucial role in neuronal differentiation. However, our understanding of the regulatory mechanisms governing proneural genes during neuronal differentiation remains limited. RFX4, identified as a candidate regulator of proneural genes, has been reported to be associated with the development of neuropsychiatric disorders. To uncover the regulatory relationship, we utilized a combination of multi-omics data, including ATAC-seq, ChIP-seq, Hi-C, and RNA-seq, to identify RFX4 as an upstream regulator of proneural genes. We further validated the role of RFX4 using an in vitro model of neuronal differentiation with RFX4 knock-in and a CRISPR-Cas9 knock-out system. As a result, we found that RFX4 directly interacts with the promoters of POU3F2 and NEUROD1. Transcriptomic analysis revealed a set of genes associated with neuronal development, which are highly implicated in the development of neuropsychiatric disorders, including schizophrenia. Notably, ectopic expression of RFX4 can drive human embryonic stem cells toward a neuronal fate. Our results strongly indicate that RFX4 serves as a direct upstream regulator of proneural genes, a role that is essential for normal neuronal development. Impairments in RFX4 function could potentially be related to the development of various neuropsychiatric disorders. However, understanding the precise mechanisms by which the RFX4 gene influences the onset of neuropsychiatric disorders requires further investigation through human genetic studies.

Integrated characterization of hepatobiliary tumor organoids provides a potential landscape of pharmacogenomic interactions

Despite considerable efforts to identify human liver cancer genomic alterations that might unveil druggable targets, the systematic translation of multiomics data remains challenging. Here, we report success in long-term culture of 64 patient-derived hepatobiliary tumor organoids (PDHOs) from a Chinese population. A divergent response to 265 metabolism- and epigenetics-related chemicals and 36 anti-cancer drugs is observed. Integration of the whole genome, transcriptome, chromatin accessibility profiles, and drug sensitivity results of 64 clinically relevant drugs defines over 32,000 genome-drug interactions. RUNX1 promoter mutation is associated with an increase in chromatin accessibility and a concomitant gene expression increase, promoting a cluster of drugs preferentially sensitive in hepatobiliary tumors. These results not only provide an annotated PDHO biobank of human liver cancer but also suggest a systematic approach for obtaining a comprehensive understanding of the gene-regulatory network of liver cancer, advancing the applications of potential personalized medicine.

Identification of somatic mutation-driven enhancers and their clinical utility in breast cancer

Somatic mutations contribute to cancer development by altering the activity of enhancers. In the study, a total of 135 mutation-driven enhancers, which displayed significant chromatin accessibility changes, were identified as candidate risk factors for breast cancer (BRCA). Furthermore, we identified four mutation-driven enhancers as independent prognostic factors for BRCA subtypes. In Her2 subtype, enhancer G > C mutation was associated with poorer prognosis through influencing its potential target genes FBXW9, TRIR, and WDR83. We identified aminoglutethimide and quinpirole as candidate drugs targeting the mutated enhancer. In normal subtype, enhancer G > A mutation was associated with poorer prognosis through influencing its target genes ALOX15B, LINC00324, and MPDU1. We identified eight candidate drugs such as erastin, colforsin, and STOCK1N-35874 targeting the mutated enhancer. Our findings suggest that somatic mutations contribute to breast cancer subtype progression by altering enhancer activity, which could be potential candidates for cancer therapy.

SMARCAL1 is a dual regulator of innate immune signaling and PD-L1 expression that promotes tumor immune evasion

Genomic instability can trigger cancer-intrinsic innate immune responses that promote tumor rejection. However, cancer cells often evade these responses by overexpressing immune checkpoint regulators, such as PD-L1. Here, we identify the SNF2-family DNA translocase SMARCAL1 as a factor that favors tumor immune evasion by a dual mechanism involving both the suppression of innate immune signaling and the induction of PD-L1-mediated immune checkpoint responses. Mechanistically, SMARCAL1 limits endogenous DNA damage, thereby suppressing cGAS-STING-dependent signaling during cancer cell growth. Simultaneously, it cooperates with the AP-1 family member JUN to maintain chromatin accessibility at a PD-L1 transcriptional regulatory element, thereby promoting PD-L1 expression in cancer cells. SMARCAL1 loss hinders the ability of tumor cells to induce PD-L1 in response to genomic instability, enhances anti-tumor immune responses and sensitizes tumors to immune checkpoint blockade in a mouse melanoma model. Collectively, these studies uncover SMARCAL1 as a promising target for cancer immunotherapy.

Regulome-wide association study identifies genetically driven accessible regions associated with pancreatic cancer risk

Genome-wide association studies (GWAS) have identified two dozen genetic variants that are associated with the risk of pancreatic ductal adenocarcinoma (PDAC), a deadly malignancy. However, a majority of these variants are located in noncoding regions of the genome, which limits the translation of GWAS findings into clinical applications. The regulome-wide association study (RWAS) is a recently developed method for identifying TF binding-induced accessibility regions for diseases. However, their potential connection to PDAC has yet to be fully explored. We evaluated the associations between genetically predicted levels of chromatin accessibility and risk of PDAC by using pan-cancer chromatin accessibility genetic prediction models. Our analysis included 8275 cases and 6723 controls from the PanScan (I, II, and III) and PanC4 consortia. To further refine our results, we also integrated genes associated to allele-specific accessibility quantitative trait loci (as-aQTL) and TF motifs located in the as-aQTL. We found that 50 chromatin accessibility features were associated with PDAC risk at a false discovery rate (FDR) of less than 0.05. A total of 28 RWAS peaks were identified as conditionally significant. By integrating the results from as-aQTL, motif analysis, and RWAS, we identified candidate causal regulatory elements for two potential chromatin accessibility regions (THCA_89956 and ESCA_89167) that are associated with PDAC risk. Our study identified chromatin accessibility features in noncoding genomic regions that are associated with PDAC risk. We also predicted the associated genes and disrupt motifs. Our findings provide new insights into the regulatory mechanisms of noncoding regions for pancreatic tumorigenesis.

Epigenome and early selection determine the tumour-immune evolutionary trajectory of colorectal cancer

Immune system control is a major hurdle that cancer evolution must circumvent. The relative timing and evolutionary dynamics of subclones that have escaped immune control remain incompletely characterized, and how immune-mediated selection shapes the epigenome has received little attention. Here, we infer the genome- and epigenome-driven evolutionary dynamics of tumour-immune coevolution within primary colorectal cancers (CRCs). We utilise our existing CRC multi-region multi-omic dataset that we supplement with high-resolution spatially-resolved neoantigen sequencing data and highly multiplexed imaging of the tumour microenvironment (TME). Analysis of somatic chromatin accessibility alterations (SCAAs) reveals frequent somatic loss of accessibility at antigen presenting genes, and that SCAAs contribute to silencing of neoantigens. We observe that strong immune escape and exclusion occur at the outset of CRC formation, and that within tumours, including at the microscopic level of individual tumour glands, additional immune escape alterations have negligible consequences for the immunophenotype of cancer cells. Further minor immuno-editing occurs during local invasion and is associated with TME reorganisation, but that evolutionary bottleneck is relatively weak. Collectively, we show that immune evasion in CRC follows a "Big Bang" evolutionary pattern, whereby genetic, epigenetic and TME-driven immune evasion acquired by the time of transformation defines subsequent cancer-immune evolution.

Logical design of synthetic cis-regulatory DNA for genetic tracing of cell identities and state changes

Descriptive data are rapidly expanding in biomedical research. Instead, functional validation methods with sufficient complexity remain underdeveloped. Transcriptional reporters allow experimental characterization and manipulation of developmental and disease cell states, but their design lacks flexibility. Here, we report logical design of synthetic cis-regulatory DNA (LSD), a computational framework leveraging phenotypic biomarkers and trans-regulatory networks as input to design reporters marking the activity of selected cellular states and pathways. LSD uses bulk or single-cell biomarkers and a reference genome or custom cis-regulatory DNA datasets with user-defined boundary regions. By benchmarking validated reporters, we integrate LSD with a computational ranking of phenotypic specificity of putative cis-regulatory DNA. Experimentally, LSD-designed reporters targeting a wide range of cell states are functional without minimal promoters. Applied to broadly expressed genes from human and mouse tissues, LSD generates functional housekeeper-like sLCRs compatible with size constraints of AAV vectors for gene therapy applications. A mesenchymal glioblastoma reporter designed by LSD outperforms previously validated ones and canonical cell surface markers. In genome-scale CRISPRa screens, LSD facilitates the discovery of known and novel bona fide cell-state drivers. Thus, LSD captures core principles of cis-regulation and is broadly applicable to studying complex cell states and mechanisms of transcriptional regulation.

Cell cycle gene alterations associate with a redistribution of mutation risk across chromosomal domains in human cancers

Mutations in human cells exhibit increased burden in heterochromatic, late DNA replication time (RT) chromosomal domains, with variation in mutation rates between tissues mirroring variation in heterochromatin and RT. We observed that regional mutation risk further varies between individual tumors in a manner independent of cell type, identifying three signatures of domain-scale mutagenesis in >4,000 tumor genomes. The major signature reflects remodeling of heterochromatin and of the RT program domains seen across tumors, tissues and cultured cells, and is robustly linked with higher expression of cell proliferation genes. Regional mutagenesis is associated with loss of activity of the tumor-suppressor genes RB1 and TP53, consistent with their roles in cell cycle control, with distinct mutational patterns generated by the two genes. Loss of regional heterogeneity in mutagenesis is associated with deficiencies in various DNA repair pathways. These mutation risk redistribution processes modify the mutation supply towards important genes, diverting the course of somatic evolution.

Shaping immune landscape of colorectal cancer by cholesterol metabolites

Cancer immunotherapies have achieved unprecedented success in clinic, but they remain largely ineffective in some major types of cancer, such as colorectal cancer with microsatellite stability (MSS CRC). It is therefore important to study tumor microenvironment of resistant cancers for developing new intervention strategies. In this study, we identify a metabolic cue that determines the unique immune landscape of MSS CRC. Through secretion of distal cholesterol precursors, which directly activate RORγt, MSS CRC cells can polarize T cells toward Th17 cells that have well-characterized pro-tumor functions in colorectal cancer. Analysis of large human cancer cohorts revealed an asynchronous pattern of the cholesterol biosynthesis in MSS CRC, which is responsible for the abnormal accumulation of distal cholesterol precursors. Inhibiting the cholesterol biosynthesis enzyme Cyp51, by pharmacological or genetic interventions, reduced the levels of intratumoral distal cholesterol precursors and suppressed tumor progression through a Th17-modulation mechanism in preclinical MSS CRC models. Our study therefore reveals a novel mechanism of cancer-immune interaction and an intervention strategy for the difficult-to-treat MSS CRC.

3D genomic analysis reveals novel enhancer-hijacking caused by complex structural alterations that drive oncogene overexpression

Enhancer hijacking, caused by structural alterations on chromosomes as well as extrachromosomal DNA (ecDNA), is a common cancer driver event. The complexity and ubiquity of structural alterations in cancer genomes make it difficult to identify enhancer hijacking using genome sequencing alone. Here we describe a 3D genomics-based analysis called HAPI (Highly Active Promoter Interactions) to characterize enhancer hijacking caused by structural alterations. HAPI analysis of HiChIP data from 34 cancer cell lines identified novel enhancer hijacking events that involve chromosomal rearrangements and activate both known and potentially novel oncogenes such as MYC, CCND1, ETV1, CRKL, and ID4, which we validated using CRISPRi assays and RNA-seq analysis. Furthermore, we found that ecDNAs often contain multiple oncogenes from different chromosomes, which causes nested enhancer hijacking among them. We found that ecDNAs containing MYC often harbor additional oncogenes from other chromosomes such as CDX2, ERBB2, or CD44 that co-opt MYC's enhancers for their overexpression, which we validated using dual-color DNA FISH and CRISPRi assays. These enhancer hijacking events involving multiple oncogenes on ecDNAs have important implications for therapeutic strategies that either target the co-opting oncogenes or the hijacked enhancers. Our publicly available HAPI analysis tool provides a robust strategy to detect enhancer hijacking and reveals novel insights into oncogene activation caused by chromosomal and extrachromosomal structural alterations.

Glioblastoma evolution and heterogeneity from a 3D whole-tumor perspective

Treatment failure for the lethal brain tumor glioblastoma (GBM) is attributed to intratumoral heterogeneity and tumor evolution. We utilized 3D neuronavigation during surgical resection to acquire samples representing the whole tumor mapped by 3D spatial coordinates. Integrative tissue and single-cell analysis revealed sources of genomic, epigenomic, and microenvironmental intratumoral heterogeneity and their spatial patterning. By distinguishing tumor-wide molecular features from those with regional specificity, we inferred GBM evolutionary trajectories from neurodevelopmental lineage origins and initiating events such as chromothripsis to emergence of genetic subclones and spatially restricted activation of differential tumor and microenvironmental programs in the core, periphery, and contrast-enhancing regions. Our work depicts GBM evolution and heterogeneity from a 3D whole-tumor perspective, highlights potential therapeutic targets that might circumvent heterogeneity-related failures, and establishes an interactive platform enabling 360° visualization and analysis of 3D spatial patterns for user-selected genes, programs, and other features across whole GBM tumors.

Cancer epigenetics: from laboratory studies and clinical trials to precision medicine

Epigenetic dysregulation is a common feature of a myriad of human diseases, particularly cancer. Defining the epigenetic defects associated with malignant tumors has become a focus of cancer research resulting in the gradual elucidation of cancer cell epigenetic regulation. In fact, most stages of tumor progression, including tumorigenesis, promotion, progression, and recurrence are accompanied by epigenetic alterations, some of which can be reversed by epigenetic drugs. The main objective of epigenetic therapy in the era of personalized precision medicine is to detect cancer biomarkers to improve risk assessment, diagnosis, and targeted treatment interventions. Rapid technological advancements streamlining the characterization of molecular epigenetic changes associated with cancers have propelled epigenetic drug research and development. This review summarizes the main mechanisms of epigenetic dysregulation and discusses past and present examples of epigenetic inhibitors in cancer diagnosis and treatment, with an emphasis on the development of epigenetic enzyme inhibitors or drugs. In the final part, the prospect of precise diagnosis and treatment is considered based on a better understanding of epigenetic abnormalities in cancer.