ONGene: A literature-based database for human oncogenes

The potential regulation of the miR-17-92a cluster by miR-21

MicroRNAs (miRNA,miRs) are small noncoding RNAs that are ubiquitously expressed in all mammalian cells. Their primary function is the regulation of nascent RNA transcripts by direct binding to regions on the target. There is now exciting data to suggest that these miRNAs can bind to other miRNAs, and this may have a broader impact on gene regulation in disease states. The oncomiR miR-21 is one of the highest-expressing miRNAs in cancer cells, and in this study, we characterise which miRNAs could be potential targets of miR-21. In cancer cells delivered with a miR-21 mimic, there was an observable shift of the miRNA milieu. We demonstrate that the miR-17-92a cluster, which harbours six miRNA members, may be a target for miR-21 regulation. Additionally, the primary transcript of miR-17-92a was reduced in the presence of miR-21. In the broader context of miR:miR regulation, overexpression of miR-21 shifted the expression of more than 150 miRNAs, including those known to regulate genes in cancer pathways such as the MAPK signalling and FoxO pathways. This study expands upon our limited understanding of miR:miR regulatory network and reinforces the concept that miRNAs can regulate each other, thereby influencing broader gene networks.

Improving the efficacy of cancer immunotherapy by host-defence caerin 1.1 and 1.9 peptides

Cancer remains a major global health challenge. Immunotherapy has revolutionized the management of cancer, yet only a limited number of patients respond to such treatments. This is largely attributed to the immunosuppressive tumor microenvironment, which diminishes the effectiveness of immunotherapy. Recent studies have underscored the potential of naturally derived caerin 1 peptides, particularly caerin 1.1 and caerin 1.9, which exhibit strong antitumor effects and enhance the efficacy of immunotherapies in animal models. This review encapsulates the current research aimed at augmenting the effectiveness of immunotherapy, focusing on the role of caerin 1.1 and caerin 1.9 in boosting immunotherapeutic outcomes, elucidating possible mechanisms, and discussing their limitations and challenges.

Clinical Relevance and Drug Modulation of PPAR Signaling Pathway in Triple-Negative Breast Cancer: A Comprehensive Analysis

Triple-negative breast cancer (TNBC) is highly heterogeneous and poses a significant medical challenge due to limited treatment options and poor outcomes. Peroxisome proliferator-activated receptors (PPARs) play a crucial role in regulating metabolism and cell fate. While the association between PPAR signal and human cancers has been a topic of concern, its specific relationship with TNBC remains unclear. Integrated analysis of large published datasets from clinical cohorts and cell lines through databases has proven to be a powerful and essential approach for understanding cancer and uncovering new molecular targets. Here, we conducted a comprehensive study investigating the clinical relevance and drug modulation of the PPAR signaling pathway in TNBC, using data from The Cancer Genome Atlas (TCGA) for TNBC patients and Genomics of Drug Sensitivity in Cancer (GDSC) for TNBC cell lines, along with drug perturbation information from Connectivity Map (CMap). In the TCGA-TNBC cohort, higher PPAR signaling activity was not associated with clinical stage, prognosis, tumor mutational burden, microsatellite instability, homologous recombination deficiency, stemness, or proliferation status. However, it was linked to older age; an elevated rate of piccolo presynaptic cytomatrix protein (PCLO) mutations; and oncogenic signal transduction involving MAPK, Ras, and PI3K-Akt pathways. Additionally, it influenced biological pathways including fatty acid metabolism, AMPK signaling, and ferroptosis. Strikingly, higher PPAR activity appeared to promote the formation of an antitumor immune and microbial microenvironment. In the GDSC-TNBC cells, nevertheless, it seemed to incur chemoresistance. Furthermore, we identified a batch of potential compounds that can regulate the PPAR signaling pathway. Lastly, our experimental validation demonstrated the ability of the histone deacetylase (HDAC) inhibitor chidamide to activate the PPAR signal in TNBC cells. In conclusion, the PPAR signaling pathway likely has pleiotropic biological effects in TNBC. These preliminary but interesting findings enhance our understanding of the role played by PPAR signal and provide new insights into the heterogeneity driven by it in TNBC.

Dissecting the functions and regulatory mechanisms of disulfidoptosis-related RPN1 in pan-cancer: modulation of immune microenvironment and cellular senescence

Introduction

Cancer's inherent heterogeneity, marked by diverse genetic and molecular alterations, presents significant challenges for developing effective treatments. One such alteration is the regulation of disulfidoptosis, a recently discovered programmed cell death pathway. RPN1, a key regulator associated with disulfidoptosis, may influence various aspects of tumor biology, including immune evasion and cellular senescence. This study aims to dissect the role of RPN1 in pan-cancer and its potential as a therapeutic target.

Methods

We employed a pan-cancer analysis to explore RPN1 expression and its association with clinical outcomes across multiple tumor types. Immune cell infiltration and expression of immune checkpoint genes were analyzed in relation to RPN1. Additionally, cellular senescence markers were assessed in RPN1 knockdown tumor cells. Gene regulatory mechanisms were studied through gene copy number variations, DNA methylation analysis, and transcriptional regulation by SP1.

Results

RPN1 is overexpressed in a wide range of tumor types and correlates with poor clinical outcomes, including overall survival, disease-specific survival, and progression-free intervals. Our analysis shows that RPN1 is involved in immune evasion, correlating with the presence of myeloid dendritic cells, macrophages, and tumor-associated fibroblasts, and influencing T-cell activity. RPN1 knockdown led to reduced tumor cell proliferation and induced cellular senescence, marked by increased senescence-associated biomarkers and β-galactosidase activity. RPN1 expression was found to be regulated by gene copy number variations, reduced DNA methylation, and transcriptional control via SP1.

Discussion

These findings highlight RPN1 as a key pan-cancer regulator, influencing immune microenvironment interactions and cellular senescence. The regulation of disulfidoptosis by RPN1 presents a promising avenue for therapeutic intervention. Targeting RPN1 could enhance immunotherapy efficacy and help mitigate tumor progression, offering a potential strategy for cancer treatment.

FTO Facilitates Cervical Cancer Malignancy Through Inducing m6A-Demethylation of PIK3R3 mRNA

BACKGROUND

The incidence rate and mortality of cervical cancer rank the fourth in the global female cancer. N6-methyladenosine (m6A) always plays an important role in tumor progression, and fat mass and obesity-associated gene (FTO) works as the m6A demethylase.

AIMS

Our study aimed to narrate the biological function and potential mechanisms for FTO in cervical cancer malignancy.

MATERIALS & METHODS

We analyzed potential clinical value of FTO in cervical cancer patients. The relative protein levels of FTO in cervical cancerous tissue and paracancerous tissue were verified by IHC. After changing the FTO expression level by lentivirus transfection, the proliferation and metastasis ability of cervical cancer cells were detected both in vitro and in vivo. Further, Merip-seq and Merip-qPCR are used to profile m6A transcriptome-wide. Finally, western blot were performed to identify the regulatory mechanism.

RESULTS

Based on TCGA-CESC cohort and GEO dataset, FTO expression levels in HPV-positive cancer patients were significantly higher than those in HPV-negative cancer patients and could predict advanced FIGO stage. The protein level of FTO in cervical cancerous tissue was higher than that in paracancerous tissue. Functional assays indicated that FTO promoted the proliferation, migration and invasion of cervical cancer cells both in vitro and in vivo. The Merip-seq and Merip-qPCR evoked that relative PIK3R3 m6A level was significantly increased after FTO knockdown, which effected the activation of FoxO pathway. After knocking down FTO, upregulation of PIK3R3 can restore the malignancy of cervical cancer.

CONCLUSION

All in all, these data suggest a vital role for FTO in occurrence and development of cervical cancer.

ECGA: A web server to explore and analyze extrachromosomal gene in cancer

Circular extrachromosomal DNA (ecDNA) plays a crucial role in the onset, progression, and evolution of many types of cancers, with dysregulated gene expression driven by ecDNA as a key mechanism. Although database resources for ecDNA are now available, a sophisticated web application dedicated to ecDNA gene analysis remains absent. Therefore, we developed ecDNA gene analyzer (ECGA). ECGA catalogues 23,274 unique ecDNA genes of 27 cancers across 27 tissues. ECGA also offers five specialized analysis tools: (1) 'Venn analysis' looks for overlaps between a given gene list and ecDNA genes; (2) 'Enrichment analysis' performs over-representation analysis and gene set enrichment analysis of input gene list within predefined ecDNA gene sets; (3) 'Target discovery' identifies upregulated ecDNA genes as targets by comparing with reference expression in normal samples; (4) 'DE analysis' finds differentially expressed ecDNA genes; (5) 'Signature discovery' discerns ecDNA gene signatures capable of classifying samples into phenotypic groups, and it is accompanied by 'Signature validation' for model test on unseen data. In summary, ECGA emerges as an indispensable platform in cancer genetics, bridging gaps in basic research, medical reporting, and pharmaceutical development, and propelling ecDNA research forward. ECGA is freely available at https://www.zhounan.org/ecga/.

RNA splicing junction landscape reveals abundant tumor-specific transcripts in human cancer

RNA splicing is a critical process governing gene expression and transcriptomic diversity. Despite its importance, a detailed examination of transcript variation at the splicing junction level remains scarce. Here, we perform a thorough analysis of RNA splicing junctions in 34,775 samples across multiple sample types. We identified 29,051 tumor-specific transcripts (TSTs) in pan-cancer, with a majority of these TSTs being unannotated. Our findings show that TSTs are positively correlated with tumor stemness and linked to unfavorable outcomes in cancer patients. Additionally, TSTs display mutual exclusivity with somatic mutations and are overrepresented in transposable-element-derived transcripts possessing oncogenic functions. Importantly, TSTs can generate putative neoantigens for immunotherapy. Moreover, TSTs can be detected in blood extracellular vesicles from cancer patients. Our results shed light on the intricacies of RNA splicing and offer promising avenues for cancer diagnosis and therapy.

Towards simplified graph neural networks for identifying cancer driver genes in heterophilic networks

The identification of cancer driver genes is crucial for understanding the complex processes involved in cancer development, progression, and therapeutic strategies. Multi-omics data and biological networks provided by numerous databases enable the application of graph deep learning techniques that incorporate network structures into the deep learning framework. However, most existing methods do not account for the heterophily in the biological networks, which hinders the improvement of model performance. Meanwhile, feature confusion often arises in models based on graph neural networks in such graphs. To address this, we propose a Simplified Graph neural network for identifying Cancer Driver genes in heterophilic networks (SGCD), which comprises primarily two components: a graph convolutional neural network with representation separation and a bimodal feature extractor. The results demonstrate that SGCD not only performs exceptionally well but also exhibits robust discriminative capabilities compared to state-of-the-art methods across all benchmark datasets. Moreover, subsequent interpretability experiments on both the model and biological aspects provide compelling evidence supporting the reliability of SGCD. Additionally, the model can dissect gene modules, revealing clearer connections between driver genes in cancers. We are confident that SGCD holds potential in the field of precision oncology and may be applied to prognosticate biomarkers for a wide range of complex diseases.

Comprehensive profiling of extrachromosomal circular DNAs in colorectal cancer progression

Colorectal cancer (CRC) development involves a series of molecular events that drive the progression from normal colorectal epithelium to adenoma and eventually to invasive carcinoma. While the involvement of extrachromosomal circular DNAs (ecDNAs) in cancer genome remodeling has been established, their specific roles in CRC formation remain unclear. Using Circle-Sequencing and whole transcriptomic sequencing, we comprehensively profile circular DNAs and transcriptomes in healthy individuals, colorectal adenoma, and CRC patients. Our delineate analyses characterize the key circular DNAs involved in oncogene expression through the normal-adenoma-carcinoma continuum and highlight that immune response-related pathways and cell cycle pathways, are the dominat events in CRC progression. Notably, chr8 ecDNA 64950741-114379093 exhibits robust up-regulation during CRC progression. Further validation in a new cohort of 50 CRC patients confirms the higher expression of chr8 ecDNA 64950741-114379093 and its strong correlation with poor prognosis. Thus, these findings provide unprecedented insights into the landscape of circular DNAs in CRC and highlights the potential of chr8 ecDNA 64950741-114379093 as a promising biomarker and therapeutic target for CRC management.

Pan-cancer characterization of cellular senescence reveals its inter-tumor heterogeneity associated with the tumor microenvironment and prognosis

Cellular senescence (CS) is characterized by the irreversible cell cycle arrest and plays a key role in aging and diseases, such as cancer. Recent years have witnessed the burgeoning exploration of the intricate relationship between CS and cancer, with CS recognized as either a suppressing or promoting factor and officially acknowledged as one of the 14 cancer hallmarks. However, a comprehensive characterization remains absent from elucidating the divergences of this relationship across different cancer types and its involvement in the multi-facets of tumor development. Here we systematically assessed the cellular senescence of over 10,000 tumor samples from 33 cancer types, starting by defining a set of cancer-associated CS signatures and deriving a quantitative metric representing the CS status, called CS score. We then investigated the CS heterogeneity and its intricate relationship with the prognosis, immune infiltration, and therapeutic responses across different cancers. As a result, cellular senescence demonstrated two distinct prognostic groups: the protective group with eleven cancers, such as LIHC, and the risky group with four cancers, including STAD. Subsequent in-depth investigations between these two groups unveiled the potential molecular and cellular mechanisms underlying the distinct effects of cellular senescence, involving the divergent activation of specific pathways and variances in immune cell infiltrations. These results were further supported by the disparate associations of CS status with the responses to immuno- and chemo-therapies observed between the two groups. Overall, our study offers a deeper understanding of inter-tumor heterogeneity of cellular senescence associated with the tumor microenvironment and cancer prognosis.

Chromatin interaction maps identify oncogenic targets of enhancer duplications in cancer

As a major type of structural variants, tandem duplication plays a critical role in tumorigenesis by increasing oncogene dosage. Recent work has revealed that noncoding enhancers are also affected by duplications leading to the activation of oncogenes that are inside or outside of the duplicated regions. However, the prevalence of enhancer duplication and the identity of their target genes remains largely unknown in the cancer genome. Here, by analyzing whole-genome sequencing data in a non-gene-centric manner, we identify 881 duplication hotspots in 13 major cancer types, most of which do not contain protein-coding genes. We show that the hotspots are enriched with distal enhancer elements and are highly lineage-specific. We develop a HiChIP-based methodology that navigates enhancer-promoter contact maps to prioritize the target genes for the duplication hotspots harboring enhancer elements. The methodology identifies many novel enhancer duplication events activating oncogenes such as ESR1, FOXA1, GATA3, GATA6, TP63, and VEGFA, as well as potentially novel oncogenes such as GRHL2, IRF2BP2, and CREB3L1 In particular, we identify a duplication hotspot on Chromosome 10p15 harboring a cluster of enhancers, which skips over two genes, through a long-range chromatin interaction, to activate an oncogenic isoform of the NET1 gene to promote migration of gastric cancer cells. Focusing on tandem duplications, our study substantially extends the catalog of noncoding driver alterations in multiple cancer types, revealing attractive targets for functional characterization and therapeutic intervention.

Extrachromosomal DNA driven oncogene spatial heterogeneity and evolution in glioblastoma

Oncogene amplification on extrachromosomal DNA (ecDNA) is strongly associated with treatment resistance and shorter survival for patients with cancer, including patients with glioblastoma. The non-chromosomal inheritance of ecDNA during cell division is a major contributor to intratumoral genetic heterogeneity. At present, the spatial dynamics of ecDNA, and the impact on tumor evolutionary trajectories, are not well understood. Here, we investigate the spatial-temporal evolution of ecDNA and its clinical impact by analyzing tumor samples from 94 treatment-naive human IDH -wildtype glioblastoma patients. We developed a spatial-temporal computational model of ecDNA positive tumors ('SPECIES') that integrates whole-genome sequencing, multi-region DNA FISH, and nascent RNAscope, to provide unique insight into the spatial dynamics of ecDNA evolution. Random segregation in combination with positive selection of ecDNAs induce large, predictable spatial patterns of cell-to-cell ecDNA copy number variation that are highly dependent on the oncogene encoded on the circular DNA. EGFR ecDNAs often reach high mean copy number (mean of 50 copies per tumor cell), are under strong positive selection (mean selection coefficient, s > 2) and do not co-amplify other oncogenes on the same ecDNA particles. In contrast, PDGFRA ecDNAs have lower mean copy number (mean of 15 copies per cell), are under weaker positive selection and frequently co-amplify other oncogenes on the same ecDNA. Evolutionary modeling suggests that EGFR ecDNAs often accumulate prior to clonal expansion. EGFR structural variants, including vIII and c-terminal deletions are under strong positive selection, are found exclusively on ecDNA, and are intermixed with wild-type EGFR ecDNAs. Simulations show EGFRvIII ecDNA likely arises after ecDNA formation in a cell with high wild-type EGFR copy number (> 10) before the onset of the most recent clonal expansion. This remains true even in cases of co-selection and co-amplification of multiple oncogenic ecDNA species in a subset of patients. Overall, our results suggest a potential time window in which early ecDNA detection may provide an opportunity for more effective intervention.

Highlights

ecDNA is the most common mechanism of focal oncogene amplification in IDH wt glioblastoma. EGFR and its variants on ecDNA are particularly potent, likely arising early in tumor development, providing a strong oncogenic stimulus to drive tumorigenesis. Wild-type and variant EGFR ecDNA heteroplasmy (co-occurrence) is common with EGFR vIII or c-terminal deletions being derived from EGFR wild-type ecDNA prior to the most recent clonal expansion. Tumors with ecDNA amplified EGFR versus PDGFRA exhibit different evolutionary trajectories. SPECIES model can infer spatial evolutionary dynamics of ecDNA in cancer.A delay between ecDNA accumulation and subsequent oncogenic mutation may give a therapeutic window for early intervention.

Comparative analysis of methodologies for detecting extrachromosomal circular DNA

Extrachromosomal circular DNA (eccDNA) is crucial in oncogene amplification, gene transcription regulation, and intratumor heterogeneity. While various analysis pipelines and experimental methods have been developed for eccDNA identification, their detection efficiencies have not been systematically assessed. To address this, we evaluate the performance of 7 analysis pipelines using seven simulated datasets, in terms of accuracy, identity, duplication rate, and computational resource consumption. We also compare the eccDNA detection efficiency of 7 experimental methods through twenty-one real sequencing datasets. Here, we show that Circle-Map and Circle_finder (bwa-mem-samblaster) outperform the other short-read pipelines. However, Circle_finder (bwa-mem-samblaster) exhibits notable redundancy in its outcomes. CReSIL is the most effective pipeline for eccDNA detection in long-read sequencing data at depths higher than 10X. Moreover, long-read sequencing-based Circle-Seq shows superior efficiency in detecting copy number-amplified eccDNA over 10 kb in length. These results offer valuable insights for researchers in choosing the suitable methods for eccDNA research.

Oncogenic composite mutations can be predicted by co-mutations and their chromosomal location

Genetic heterogeneity in tumors can show a remarkable selectivity when two or more independent genetic events occur in the same gene. This phenomenon, called composite mutation, points toward a selective pressure, which frequently causes therapy resistance to mutation-specific drugs. Since composite mutations have been described to occur in sub-clonal populations, they are not always captured through biopsy sampling. Here, we provide a proof of concept to predict composite mutations to anticipate which patients might be at risk for sub-clonally driven therapy resistance. We found that composite mutations occur in 5% of cancer patients, mostly affecting the PIK3CA, EGFR, BRAF, and KRAS genes, which are common precision medicine targets. Furthermore, we found a strong and significant relationship between the frequencies of composite mutations with commonly co-occurring mutations in a non-composite context. We also found that co-mutations are significantly enriched on the same chromosome. These observations were independently confirmed using cell line data. Finally, we show the feasibility of predicting compositive mutations based on their co-mutations (AUC 0.62, 0.81, 0.82, and 0.91 for EGFR, PIK3CA, KRAS, and BRAF, respectively). This prediction model could help to stratify patients who are at risk of developing therapy resistance-causing mutations.

Bioinformatics tools and resources for cancer and application

ABSTRACT

Tumor bioinformatics plays an important role in cancer research and precision medicine. The primary focus of traditional cancer research has been molecular and clinical studies of a number of fundamental pathways and genes. In recent years, driven by breakthroughs in high-throughput technologies, large-scale cancer omics data have accumulated rapidly. How to effectively utilize and share these data is particularly important. To address this crucial task, many computational tools and databases have been developed over the past few years. To help researchers quickly learn and understand the functions of these tools, in this review, we summarize publicly available bioinformatics tools and resources for pan-cancer multi-omics analysis, regulatory analysis of tumorigenesis, tumor treatment and prognosis, immune infiltration analysis, immune repertoire analysis, cancer driver gene and driver mutation analysis, and cancer single-cell analysis, which may further help researchers find more suitable tools for their research.

Human cells contain myriad excised linear intron RNAs with links to gene regulation and potential utility as biomarkers

A previous study using Thermostable Group II Intron Reverse Transcriptase sequencing (TGIRT-seq) found human plasma contains short (≤300 nt) structured full-length excised linear intron (FLEXI) RNAs with potential to serve as blood-based biomarkers. Here, TGIRT-seq identified >9,000 different FLEXI RNAs in human cell lines, including relatively abundant FLEXIs with cell-type-specific expression patterns. Analysis of public CLIP-seq datasets identified 126 RNA-binding proteins (RBPs) that have binding sites within the region corresponding to the FLEXI or overlapping FLEXI splice sites in pre-mRNAs, including 53 RBPs with binding sites for ≥30 different FLEXIs. These included splicing factors, transcription factors, a chromatin remodeling protein, cellular growth regulators, and proteins with cytoplasmic functions. Analysis of ENCODE datasets identified subsets of these RBPs whose knockdown impacted FLEXI host gene mRNA levels or proximate alternative splicing, indicating functional interactions. Hierarchical clustering identified six subsets of RBPs whose FLEXI binding sites were co-enriched in six subsets of functionally related host genes: AGO1-4 and DICER, including but not limited to agotrons or mirtron pre-miRNAs; DKC1, NOLC1, SMNDC1, and AATF (Apoptosis Antagonizing Transcription Factor), including but not limited to snoRNA-encoding FLEXIs; two subsets of alternative splicing factors; and two subsets that included RBPs with cytoplasmic functions (e.g., LARP4, PABPC4, METAP2, and ZNF622) together with regulatory proteins. Cell fractionation experiments showed cytoplasmic enrichment of FLEXI RNAs with binding sites for RBPs with cytoplasmic functions. The subsets of host genes encoding FLEXIs with binding sites for different subsets of RBPs were co-enriched with non-FLEXI other short and long introns with binding sites for the same RBPs, suggesting overarching mechanisms for coordinately regulating expression of functionally related genes. Our findings identify FLEXIs as a previously unrecognized large class of cellular RNAs and provide a comprehensive roadmap for further analyzing their biological functions and the relationship of their RBPs to cellular regulatory mechanisms.

IMI-driver: Integrating multi-level gene networks and multi-omics for cancer driver gene identification

The identification of cancer driver genes is crucial for early detection, effective therapy, and precision medicine of cancer. Cancer is caused by the dysregulation of several genes at various levels of regulation. However, current techniques only capture a limited amount of regulatory information, which may hinder their efficacy. In this study, we present IMI-driver, a model that integrates multi-omics data into eight biological networks and applies Multi-view Collaborative Network Embedding to embed the gene regulation information from the biological networks into a low-dimensional vector space to identify cancer drivers. We apply IMI-driver to 29 cancer types from The Cancer Genome Atlas (TCGA) and compare its performance with nine other methods on nine benchmark datasets. IMI-driver outperforms the other methods, demonstrating that multi-level network integration enhances prediction accuracy. We also perform a pan-cancer analysis using the genes identified by IMI-driver, which confirms almost all our selected candidate genes as known or potential drivers. Case studies of the new positive genes suggest their roles in cancer development and progression.

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

Cancer genomes are composed of many complex structural alterations on chromosomes and extrachromosomal DNA (ecDNA), making it difficult to identify non-coding enhancer regions that are hijacked to activate oncogene expression. Here, we describe a 3D genomics-based analysis called HAPI (Highly Active Promoter Interactions) to characterize enhancer hijacking. HAPI analysis of HiChIP data from 34 cancer cell lines identified enhancer hijacking events that activate both known and potentially novel oncogenes such as MYC, CCND1, ETV1, CRKL, and ID4. Furthermore, we found enhancer hijacking among multiple oncogenes from different chromosomes, often including MYC, on the same complex amplicons such as ecDNA. We characterized a MYC-ERBB2 chimeric ecDNA, in which ERBB2 heavily hijacks MYC's enhancers. Notably, CRISPRi of the MYC promoter led to increased interaction of ERBB2 with MYC enhancers and elevated ERBB2 expression. Our HAPI analysis tool provides a robust strategy to detect enhancer hijacking and reveals novel insights into oncogene activation.

Survival-Related Genes on Chromosomes 6 and 17 in Medulloblastoma

Survival of Medulloblastoma (MB) depends on various factors, including the gene expression profiles of MB tumor tissues. In this study, we identified 967 MB survival-related genes (SRGs) using a gene expression dataset and the Cox proportional hazards regression model. Notably, the SRGs were over-represented on chromosomes 6 and 17, known for the abnormalities monosomy 6 and isochromosome 17 in MB. The most significant SRG was HMGA1 (high mobility group AT-hook 1) on chromosome 6, which is a known oncogene and a histone H1 competitor. High expression of HMGA1 was associated with worse survival, primarily in the Group 3γ subtype. The high expression of HMGA1 was unrelated to any known somatic copy number alteration. Most SRGs on chromosome 17p were associated with low expression in Group 4β, the MB subtype, with 93% deletion of 17p and 98% copy gain of 17q. GO enrichment analysis showed that both chromosomes 6 and 17 included SRGs related to telomere maintenance and provided a rationale for testing telomerase inhibitors in Group 3 MBs. We conclude that HMGA1, along with other SRGs on chromosomes 6 and 17, warrant further investigation as potential therapeutic targets in selected subgroups or subtypes of MB.

Identifying new cancer genes based on the integration of annotated gene sets via hypergraph neural networks

MOTIVATION

Identifying cancer genes remains a significant challenge in cancer genomics research. Annotated gene sets encode functional associations among multiple genes, and cancer genes have been shown to cluster in hallmark signaling pathways and biological processes. The knowledge of annotated gene sets is critical for discovering cancer genes but remains to be fully exploited.

RESULTS

Here, we present the DIsease-Specific Hypergraph neural network (DISHyper), a hypergraph-based computational method that integrates the knowledge from multiple types of annotated gene sets to predict cancer genes. First, our benchmark results demonstrate that DISHyper outperforms the existing state-of-the-art methods and highlight the advantages of employing hypergraphs for representing annotated gene sets. Second, we validate the accuracy of DISHyper-predicted cancer genes using functional validation results and multiple independent functional genomics data. Third, our model predicts 44 novel cancer genes, and subsequent analysis shows their significant associations with multiple types of cancers. Overall, our study provides a new perspective for discovering cancer genes and reveals previously undiscovered cancer genes.

AVAILABILITY AND IMPLEMENTATION

DISHyper is freely available for download at https://github.com/genemine/DISHyper.

Simultaneous screening of overexpressed genes in breast cancer for oncogenic drivers and tumor dependencies

There are hundreds of genes typically overexpressed in breast cancer cells and it's often assumed that their overexpression contributes to cancer progression. However, the precise proportion of these overexpressed genes contributing to tumorigenicity remains unclear. To address this gap, we undertook a comprehensive screening of a diverse set of seventy-two genes overexpressed in breast cancer. This systematic screening evaluated their potential for inducing malignant transformation and, concurrently, assessed their impact on breast cancer cell proliferation and viability. Select genes including ALDH3B1, CEACAM5, IL8, PYGO2, and WWTR1, exhibited pronounced activity in promoting tumor formation and establishing gene dependencies critical for tumorigenicity. Subsequent investigations revealed that CEACAM5 overexpression triggered the activation of signaling pathways involving β-catenin, Cdk4, and mTOR. Additionally, it conferred a growth advantage independent of exogenous insulin in defined medium and facilitated spheroid expansion by inducing multiple layers of epithelial cells while preserving a hollow lumen. Furthermore, the silencing of CEACAM5 expression synergized with tamoxifen-induced growth inhibition in breast cancer cells. These findings underscore the potential of screening overexpressed genes for both oncogenic drivers and tumor dependencies to expand the repertoire of therapeutic targets for breast cancer treatment.

Multimodal analysis of cfDNA methylomes for early detecting esophageal squamous cell carcinoma and precancerous lesions

Detecting early-stage esophageal squamous cell carcinoma (ESCC) and precancerous lesions is critical for improving survival. Here, we conduct whole-genome bisulfite sequencing (WGBS) on 460 cfDNA samples from patients with non-metastatic ESCC or precancerous lesions and matched healthy controls. We develop an expanded multimodal analysis (EMMA) framework to simultaneously identify cfDNA methylation, copy number variants (CNVs), and fragmentation markers in cfDNA WGBS data. cfDNA methylation markers are the earliest and most sensitive, detectable in 70% of ESCCs and 50% of precancerous lesions, and associated with molecular subtypes and tumor microenvironments. CNVs and fragmentation features show high specificity but are linked to late-stage disease. EMMA significantly improves detection rates, increasing AUCs from 0.90 to 0.99, and detects 87% of ESCCs and 62% of precancerous lesions with >95% specificity in validation cohorts. Our findings demonstrate the potential of multimodal analysis of cfDNA methylome for early detection and monitoring of molecular characteristics in ESCC.

Powerful and accurate detection of temporal gene expression patterns from multi-sample multi-stage single-cell transcriptomics data with TDEseq

We present a non-parametric statistical method called TDEseq that takes full advantage of smoothing splines basis functions to account for the dependence of multiple time points in scRNA-seq studies, and uses hierarchical structure linear additive mixed models to model the correlated cells within an individual. As a result, TDEseq demonstrates powerful performance in identifying four potential temporal expression patterns within a specific cell type. Extensive simulation studies and the analysis of four published scRNA-seq datasets show that TDEseq can produce well-calibrated p-values and up to 20% power gain over the existing methods for detecting temporal gene expression patterns.

CancerMHL: the database of integrating key DNA methylation, histone modifications and lncRNAs in cancer

The discovery of key epigenetic modifications in cancer is of great significance for the study of disease biomarkers. Through the mining of epigenetic modification data relevant to cancer, some researches on epigenetic modifications are accumulating. In order to make it easier to integrate the effects of key epigenetic modifications on the related cancers, we established CancerMHL (http://www.positionprediction.cn/), which provide key DNA methylation, histone modifications and lncRNAs as well as the effect of these key epigenetic modifications on gene expression in several cancers. To facilitate data retrieval, CancerMHL offers flexible query options and filters, allowing users to access specific key epigenetic modifications according to their own needs. In addition, based on the epigenetic modification data, three online prediction tools had been offered in CancerMHL for users. CancerMHL will be a useful resource platform for further exploring novel and potential biomarkers and therapeutic targets in cancer. Database URL: http://www.positionprediction.cn/.

Spatial transcriptomics reveals a low extent of transcriptionally active hepatitis B virus integration in patients with HBsAg loss

OBJECTIVE

Hepatitis B virus (HBV) can integrate into the chromosomes of infected hepatocytes, contributing to the production of hepatitis B surface antigen (HBsAg) and to hepatocarcinogenesis. In this study, we aimed to explore whether transcriptionally active HBV integration events spread throughout the liver tissue in different phases of chronic HBV infection, especially in patients with HBsAg loss.

DESIGN

We constructed high-resolution spatial transcriptomes of liver biopsies containing 13 059 tissue spots from 18 patients with chronic HBV infection to analyse the occurrence and relative distribution of transcriptionally active viral integration events. Immunohistochemistry was performed to evaluate the expression of HBsAg and HBV core antigen. Intrahepatic covalently closed circular DNA (cccDNA) levels were quantified by real-time qPCR.

RESULTS

Spatial transcriptome sequencing identified the presence of 13 154 virus-host chimeric reads in 7.86% (1026 of 13 059) of liver tissue spots in all patients, including three patients with HBsAg loss. These HBV integration sites were randomly distributed on chromosomes and can localise in host genes involved in hepatocarcinogenesis, such as ALB, CLU and APOB. Patients who were receiving or had received antiviral treatment had a significantly lower percentage of viral integration-containing spots and significantly fewer chimeric reads than treatment-naïve patients. Intrahepatic cccDNA levels correlated well with viral integration events.

CONCLUSION

Transcriptionally active HBV integration occurred in chronically HBV-infected patients at different phases, including in patients with HBsAg loss. Antiviral treatment was associated with a decreased number and extent of transcriptionally active viral integrations, implying that early treatment intervention may further reduce the number of viral integration events.

Histone 3 lysine 9 acetylation-specific reprogramming regulates esophageal squamous cell carcinoma progression and metastasis

Dysregulation of histone acetylation is widely implicated in tumorigenesis, yet its specific roles in the progression and metastasis of esophageal squamous cell carcinoma (ESCC) remain unclear. Here, we profiled the genome-wide landscapes of H3K9ac for paired adjacent normal (Nor), primary ESCC (EC) and metastatic lymph node (LNC) esophageal tissues from three ESCC patients. Compared to H3K27ac, we identified a distinct epigenetic reprogramming specific to H3K9ac in EC and LNC samples relative to Nor samples. This H3K9ac-related reprogramming contributed to the transcriptomic aberration of targeting genes, which were functionally associated with tumorigenesis and metastasis. Notably, genes with gained H3K9ac signals in both primary and metastatic lymph node samples (common-gained gene) were significantly enriched in oncogenes. Single-cell RNA-seq analysis further revealed that the corresponding top 15 common-gained genes preferred to be enriched in mesenchymal cells with high metastatic potential. Additionally, in vitro experiment demonstrated that the removal of H3K9ac from the common-gained gene MSI1 significantly downregulated its transcription, resulting in deficiencies in ESCC cell proliferation and migration. Together, our findings revealed the distinct characteristics of H3K9ac in esophageal squamous cell carcinogenesis and metastasis, and highlighted the potential therapeutic avenue for intervening ESCC through epigenetic modulation via H3K9ac.

Differential DNA methylation landscape of miRNAs genes in mice liver fibrosis

BACKGROUND

Patients with chronic liver disease were found nearly all to have liver fibrosis, which is characterized by excess accumulation of extracellular matrix (ECM) proteins. While ECM accumulation can prevent liver infection and injury, it can destroy normal liver function and architecture. miRNA's own regulation was involved in DNA methylation change. The purpose of this study is to detect DNA methylation landscape of miRNAs genes in mice liver fibrosis tissues.

METHODS

Male mice (10-12 weeks) were injected CCl4 from abdominal cavity to induced liver fibrosis. 850 K BeadChips were used to examine DNA methylation change in whole genome. The methylation change of 16 CpG dinucleotides located in promoter regions of 4 miRNA genes were detected by bisulfite sequencing polymerase chain reaction (BSP) to verify chip data accuracy, and these 4 miRNA genes' expressions were detected by RT-qPCR methods.

RESULTS

There are 769 differential methylation sites (DMS) in total between fibrotic liver tissue and normal mice liver tissue, which were related with 148 different miRNA genes. Chips array data were confirmed by bisulfite sequencing polymerase chain reaction (R = 0.953; P < 0.01). GO analysis of the target genes of 2 miRNA revealed that protein binding, cytoplasm and chromatin binding activity were commonly enriched; KEGG pathway enrichment analysis displayed that TGF-beta signaling pathway was commonly enriched.

CONCLUSION

The DNA of 148 miRNA genes was found to have methylation change in liver fibrosis tissue. These discoveries in miRNA genes are beneficial to future miRNA function research in liver fibrosis.

Identification and Analysis of Sex-Biased Copy Number Alterations

Background: Sex difference has long been recognized at cancer incidence, outcomes, and responses to therapy. Analyzing the somatic mutation profiles of large-scale cancer samples between the sexes have revealed several potential drivers of cancer with sex difference. However, it is still a demand for in-depth scrutinizing the sex-biased characteristics of genome instability to link the clinical differences for individual cancer type. Methods: Here, we utilized a published framework devised to specifically compare the copy number profiles between 2 groups to identify the sex-biased copy number alterations (CNAs) across 16 cancer types from the The Cancer Genome Atlas Program database, and dissected the impact of those CNAs. Results: Totally, 81 male-biased CNA regions and 23 female-biased CNA regions in 16 cancer types were found. Functional annotation analysis showed that several critical biological functions associated with sex-biased CNAs are shared in multiple cancer types, including immune-related pathways and regulation of cellular signaling. Most sex-biased CNAs have a substantial effect on transcriptional consequence, where the average of over 68% of genes have a linear relationship with CNAs across cancer types, and 14% of those genes are affected by the combination of the sex and copy number. Furthermore, 29 sex-biased CNA regions show latent capacity to be sex-specific prognostic biomarker such as CNA on 11q13.4 for head and neck cancer and lung cancer. Conclusions: This analysis offers new insights into the role of sex in cancer etiology and prognosis through a detailed characterization of sex differences in genome instability of diverse cancers.

Detecting and understanding meaningful cancerous mutations based on computational models of mRNA splicing

Cancer research has long relied on non-silent mutations. Yet, it has become overwhelmingly clear that silent mutations can affect gene expression and cancer cell fitness. One fundamental mechanism that apparently silent mutations can severely disrupt is alternative splicing. Here we introduce Oncosplice, a tool that scores mutations based on models of proteomes generated using aberrant splicing predictions. Oncosplice leverages a highly accurate neural network that predicts splice sites within arbitrary mRNA sequences, a greedy transcript constructor that considers alternate arrangements of splicing blueprints, and an algorithm that grades the functional divergence between proteins based on evolutionary conservation. By applying this tool to 12M somatic mutations we identify 8K deleterious variants that are significantly depleted within the healthy population; we demonstrate the tool's ability to identify clinically validated pathogenic variants with a positive predictive value of 94%; we show strong enrichment of predicted deleterious mutations across pan-cancer drivers. We also achieve improved patient survival estimation using a proposed set of novel cancer-involved genes. Ultimately, this pipeline enables accelerated insight-gathering of sequence-specific consequences for a class of understudied mutations and provides an efficient way of filtering through massive variant datasets - functionalities with immediate experimental and clinical applications.

CanVaxKB: a web-based cancer vaccine knowledgebase

Cancer vaccines have been increasingly studied and developed to prevent or treat various types of cancers. To systematically survey and analyze different reported cancer vaccines, we developed CanVaxKB (https://violinet.org/canvaxkb), the first web-based cancer vaccine knowledgebase that compiles over 670 therapeutic or preventive cancer vaccines that have been experimentally verified to be effective at various stages. Vaccine construction and host response data are also included. These cancer vaccines are developed against various cancer types such as melanoma, hematological cancer, and prostate cancer. CanVaxKB has stored 263 genes or proteins that serve as cancer vaccine antigen genes, which we have collectively termed 'canvaxgens'. Top three mostly used canvaxgens are PMEL, MLANA and CTAG1B, often targeting multiple cancer types. A total of 193 canvaxgens are also reported in cancer-related ONGene, Network of Cancer Genes and/or Sanger Cancer Gene Consensus databases. Enriched functional annotations and clusters of canvaxgens were identified and analyzed. User-friendly web interfaces are searchable for querying and comparing cancer vaccines. CanVaxKB cancer vaccines are also semantically represented by the community-based Vaccine Ontology to support data exchange. Overall, CanVaxKB is a timely and vital cancer vaccine source that facilitates efficient collection and analysis, further helping researchers and physicians to better understand cancer mechanisms.

Machine learning-based extrachromosomal DNA identification in large-scale cohorts reveals its clinical implications in cancer

The clinical implications of extrachromosomal DNA (ecDNA) in cancer therapy remain largely elusive. Here, we present a comprehensive analysis of ecDNA amplification spectra and their association with clinical and molecular features in multiple cohorts comprising over 13,000 pan-cancer patients. Using our developed computational framework, GCAP, and validating it with multifaceted approaches, we reveal a consistent pan-cancer pattern of mutual exclusivity between ecDNA amplification and microsatellite instability (MSI). In addition, we establish the role of ecDNA amplification as a risk factor and refine genomic subtypes in a cohort from 1015 colorectal cancer patients. Importantly, our investigation incorporates data from four clinical trials focused on anti-PD-1 immunotherapy, demonstrating the pivotal role of ecDNA amplification as a biomarker for guiding checkpoint blockade immunotherapy in gastrointestinal cancer. This finding represents clinical evidence linking ecDNA amplification to the effectiveness of immunotherapeutic interventions. Overall, our study provides a proof-of-concept of identifying ecDNA amplification from cancer whole-exome sequencing (WES) data, highlighting the potential of ecDNA amplification as a valuable biomarker for facilitating personalized cancer treatment.

Constructing and Evaluating a Mitophagy-Related Gene Prognostic Model: Implications for Immune Landscape and Tumor Biology in Lung Adenocarcinoma

Mitophagy, a conserved cellular mechanism, is crucial for cellular homeostasis through the selective clearance of impaired mitochondria. Its emerging role in cancer development has sparked interest, particularly in lung adenocarcinoma (LUAD). Our study aimed to construct a risk model based on mitophagy-related genes (MRGs) to predict survival outcomes, immune response, and chemotherapy sensitivity in LUAD patients. We mined the GeneCards database to identify MRGs and applied LASSO/Cox regression to formulate a prognostic model. Validation was performed using two independent Gene Expression Omnibus (GEO) cohorts. Patients were divided into high- and low-risk categories according to the median risk score. The high-risk group demonstrated significantly reduced survival. Multivariate Cox analysis confirmed the risk score as an independent predictor of prognosis, and a corresponding nomogram was developed to facilitate clinical assessments. Intriguingly, the risk score correlated with immune infiltration levels, oncogenic expression profiles, and sensitivity to anticancer agents. Enrichment analyses linked the risk score with key oncological pathways and biological processes. Within the model, MTERF3 emerged as a critical regulator of lung cancer progression. Functional studies indicated that the MTERF3 knockdown suppressed the lung cancer cell proliferation and migration, enhanced mitophagy, and increased the mitochondrial superoxide production. Our novel prognostic model, grounded in MRGs, promises to refine therapeutic strategies and prognostication in lung cancer management.

Pan-cancer analyses identify MIR210HG overexpression, epigenetic regulation and oncogenic role in human tumors and its interaction with the tumor microenvironment

BACKGROUND

Molecular entities showing dysregulation in multiple cancers may hold great biomarker or therapeutic potential. There is accumulating evidence that highlights the dysregulation of a long non-coding RNA, MIR210HG, in various cancers and its oncogenic role. However, a comprehensive analysis of MIR210HG expression pattern, molecular mechanisms, diagnostic or prognostic significance or evaluation of its interaction with tumor microenvironment across various cancers remains unstudied.

METHODS

A systematic pan-cancer analysis was done using multiple public databases and bioinformatic tools to study the molecular role and clinical significance of MIR210HG. We have analyzed expression patterns, genome alteration, transcriptional and epigenetic regulation, correlation with patient survival, immune infiltrates, co-expressed genes, interacting proteins, and pathways associated with MIR210HG.

RESULTS

The Pan cancer expression analysis of MIR210HG through various tumor datasets demonstrated that MIR210HG is significantly upregulated in most cancers and increased with the tumor stage in a subset of them. Furthermore, prognostic analysis revealed high MIR210HG expression is associated with poor overall and disease-free survival in specific cancer types. Genetic alteration analysis showed minimal alterations in the MIR210HG locus, indicating that overexpression in cancers is not due to gene amplification. The exploration of SNPs on MIR210HG suggested possible structural changes that may affect its interactions with the miRNAs. The correlation of MIR210HG with promoter methylation was found to be significantly negative in nature in majority of cancers depicting the possible epigenetic regulation of expression of MIR210HG. Additionally, MIR210HG showed negative correlations with immune cells and thus may have strong impact on the tumor microenvironment. Functional analysis indicates its association with hypoxia, angiogenesis, metastasis, and DNA damage repair processes. MIR210HG was found to interact with several proteins and potentially regulate chromatin modifications and transcriptional regulation.

CONCLUSIONS

A first pan-can cancer analysis of MIR210HG highlights its transcriptional and epigenetic deregulation and oncogenic role in the majority of cancers, its correlation with tumor microenvironment factors such as hypoxia and immune infiltration, and its potential as a prognostic biomarker and therapeutic target in several cancers.

Bioinformatics Prediction for Network-Based Integrative Multi-Omics Expression Data Analysis in Hirschsprung Disease

Hirschsprung's disease (HSCR) is a rare developmental disorder in which enteric ganglia are missing along a portion of the intestine. HSCR has a complex inheritance, with RET as the major disease-causing gene. However, the pathogenesis of HSCR is still not completely understood. Therefore, we applied a computational approach based on multi-omics network characterization and clustering analysis for HSCR-related gene/miRNA identification and biomarker discovery. Protein-protein interaction (PPI) and miRNA-target interaction (MTI) networks were analyzed by DPClusO and BiClusO, respectively, and finally, the biomarker potential of miRNAs was computationally screened by miRNA-BD. In this study, a total of 55 significant gene-disease modules were identified, allowing us to propose 178 new HSCR candidate genes and two biological pathways. Moreover, we identified 12 key miRNAs with biomarker potential among 137 predicted HSCR-associated miRNAs. Functional analysis of new candidates showed that enrichment terms related to gene ontology (GO) and pathways were associated with HSCR. In conclusion, this approach has allowed us to decipher new clues of the etiopathogenesis of HSCR, although molecular experiments are further needed for clinical validations.

EndoQuad: a comprehensive genome-wide experimentally validated endogenous G-quadruplex database

G-quadruplexes (G4s) are non-canonical four-stranded structures and are emerging as novel genetic regulatory elements. However, a comprehensive genomic annotation of endogenous G4s (eG4s) and systematic characterization of their regulatory network are still lacking, posing major challenges for eG4 research. Here, we present EndoQuad (https://EndoQuad.chenzxlab.cn/) to address these pressing issues by integrating high-throughput experimental data. First, based on high-quality genome-wide eG4s mapping datasets (human: 1181; mouse: 24; chicken: 2) generated by G4 ChIP-seq/CUT&Tag, we generate a reference set of genome-wide eG4s. Our multi-omics analyses show that most eG4s are identified in one or a few cell types. The eG4s with higher occurrences across samples are more structurally stable, evolutionarily conserved, enriched in promoter regions, mark highly expressed genes and associate with complex regulatory programs, demonstrating higher confidence level for further experiments. Finally, we integrate millions of functional genomic variants and prioritize eG4s with regulatory functions in disease and cancer contexts. These efforts have culminated in the comprehensive and interactive database of experimentally validated DNA eG4s. As such, EndoQuad enables users to easily access, download and repurpose these data for their own research. EndoQuad will become a one-stop resource for eG4 research and lay the foundation for future functional studies.

Pathway-driven analysis of synthetic lethal interactions in cancer using perturbation screens

Synthetic lethality offers a promising approach for developing effective therapeutic interventions in cancer when direct targeting of driver genes is impractical. In this study, we comprehensively analyzed large-scale CRISPR, shRNA, and PRISM screens to identify potential synthetic lethal (SL) interactions in pan-cancer and 12 individual cancer types, using a new computational framework that leverages the biological function and signaling pathway information of key driver genes to mitigate the confounding effects of background genetic alterations in different cancer cell lines. This approach has successfully identified several putative SL interactions, including KRAS-MAP3K2 and APC-TCF7L2 in pan cancer, and CCND1-METTL1, TP53-FRS3, SMO-MDM2, and CCNE1-MTOR in liver, blood, skin, and gastric cancers, respectively. In addition, we proposed several FDA-approved cancer-targeted drugs for various cancer types through PRISM drug screens, such as cabazitaxel for VHL-mutated kidney cancer and alectinib for lung cancer with NRAS or KRAS mutations. Leveraging pathway information can enhance the concordance of shRNA and CRISPR screens and provide clinically relevant findings such as the potential efficacy of dasatinib, an inhibitor of SRC, for colorectal cancer patients with mutations in the WNT signaling pathway. These analyses revealed that taking signaling pathway information into account results in the identification of more promising SL interactions.

Genomic diversity in functionally relevant genes modifies neurodevelopmental versus neoplastic risks in individuals with germline PTEN variants

Individuals with germline PTEN variants (PHTS) have increased risks of the seemingly disparate phenotypes of cancer and neurodevelopmental disorders (NDD), including autism spectrum disorder (ASD). Etiology of the phenotypic variability remains elusive. Here, we hypothesized that decreased genomic diversity, manifested by increased homozygosity, may be one etiology. Comprehensive analyses of 376 PHTS patients of European ancestry revealed significant enrichment of homozygous common variants in genes involved in inflammatory processes in the PHTS-NDD group and in genes involved in differentiation and chromatin structure regulation in the PHTS-ASD group. Pathway analysis revealed pathways germane to NDD/ASD, including neuroinflammation and synaptogenesis. Collapsing analysis of the homozygous variants identified suggestive modifier NDD/ASD genes. In contrast, we found enrichment of homozygous ultra-rare variants in genes modulating cell death in the PHTS-cancer group. Finally, homozygosity burden as a predictor of ASD versus cancer outcomes in our validated prediction model for NDD/ASD performed favorably.

Mosaic chromosomal alterations in peripheral blood leukocytes of children in sub-Saharan Africa

In high-income countries, mosaic chromosomal alterations in peripheral blood leukocytes are associated with an elevated risk of adverse health outcomes, including hematologic malignancies. We investigate mosaic chromosomal alterations in sub-Saharan Africa among 931 children with Burkitt lymphoma, an aggressive lymphoma commonly characterized by immunoglobulin-MYC chromosomal rearrangements, 3822 Burkitt lymphoma-free children, and 674 cancer-free men from Ghana. We find autosomal and X chromosome mosaic chromosomal alterations in 3.4% and 1.7% of Burkitt lymphoma-free children, and 8.4% and 3.7% of children with Burkitt lymphoma (P-values = 5.7×10-11 and 3.74×10-2, respectively). Autosomal mosaic chromosomal alterations are detected in 14.0% of Ghanaian men and increase with age. Mosaic chromosomal alterations in Burkitt lymphoma cases include gains on chromosomes 1q and 8, the latter spanning MYC, while mosaic chromosomal alterations in Burkitt lymphoma-free children include copy-neutral loss of heterozygosity on chromosomes 10, 14, and 16. Our results highlight mosaic chromosomal alterations in sub-Saharan African populations as a promising area of research.

Parvimonas micra, an oral pathobiont associated with colorectal cancer, epigenetically reprograms human colonocytes

Recently, an intestinal dysbiotic microbiota with enrichment in oral cavity bacteria has been described in colorectal cancer (CRC) patients. Here, we characterize and investigate one of these oral pathobionts, the Gram-positive anaerobic coccus Parvimonas micra. We identified two phylotypes (A and B) exhibiting different phenotypes and adhesion capabilities. We observed a strong association of phylotype A with CRC, with its higher abundance in feces and in tumoral tissue compared with the normal homologous colonic mucosa, which was associated with a distinct methylation status of patients. By developing an in vitro hypoxic co-culture system of human primary colonic cells with anaerobic bacteria, we show that P. micra phylotype A alters the DNA methylation profile promoters of key tumor-suppressor genes, oncogenes, and genes involved in epithelial-mesenchymal transition. In colonic mucosa of CRC patients carrying P. micra phylotype A, we found similar DNA methylation alterations, together with significant enrichment of differentially expressed genes in pathways involved in inflammation, cell adhesion, and regulation of actin cytoskeleton, providing evidence of P. micra's possible role in the carcinogenic process.

Synthetic viability induces resistance to immune checkpoint inhibitors in cancer cells

BACKGROUND

Immune checkpoint inhibitors (ICI) have revolutionized the treatment for multiple cancers. However, most of patients encounter resistance. Synthetic viability (SV) between genes could induce resistance. In this study, we established SV signature to predict the efficacy of ICI treatment for melanoma.

METHODS

We collected features and predicted SV gene pairs by random forest classifier. This work prioritized SV gene pairs based on CRISPR/Cas9 screens. SV gene pairs signature were constructed to predict the response to ICI for melanoma patients.

RESULTS

This study predicted robust SV gene pairs based on 14 features. Filtered by CRISPR/Cas9 screens, we identified 1,861 SV gene pairs, which were also related with prognosis across multiple cancer types. Next, we constructed the six SV pairs signature to predict resistance to ICI for melanoma patients. This study applied the six SV pairs signature to divide melanoma patients into high-risk and low-risk. High-risk melanoma patients were associated with worse response after ICI treatment. Immune landscape analysis revealed that high-risk melanoma patients had lower natural killer cells and CD8+ T cells infiltration.

CONCLUSIONS

In summary, the 14 features classifier accurately predicted robust SV gene pairs for cancer. The six SV pairs signature could predict resistance to ICI.

Functional Profiling of Soft Tissue Sarcoma Using Mechanistic Models

Soft tissue sarcoma is an umbrella term for a group of rare cancers that are difficult to treat. In addition to surgery, neoadjuvant chemotherapy has shown the potential to downstage tumors and prevent micrometastases. However, finding effective therapeutic targets remains a research challenge. Here, a previously developed computational approach called mechanistic models of signaling pathways has been employed to unravel the impact of observed changes at the gene expression level on the ultimate functional behavior of cells. In the context of such a mechanistic model, RNA-Seq counts sourced from the Recount3 resource, from The Cancer Genome Atlas (TCGA) Sarcoma project, and non-diseased sarcomagenic tissues from the Genotype-Tissue Expression (GTEx) project were utilized to investigate signal transduction activity through signaling pathways. This approach provides a precise view of the relationship between sarcoma patient survival and the signaling landscape in tumors and their environment. Despite the distinct regulatory alterations observed in each sarcoma subtype, this study identified 13 signaling circuits, or elementary sub-pathways triggering specific cell functions, present across all subtypes, belonging to eight signaling pathways, which served as predictors for patient survival. Additionally, nine signaling circuits from five signaling pathways that highlighted the modifications tumor samples underwent in comparison to normal tissues were found. These results describe the protective role of the immune system, suggesting an anti-tumorigenic effect in the tumor microenvironment, in the process of tumor cell detachment and migration, or the dysregulation of ion homeostasis. Also, the analysis of signaling circuit intermediary proteins suggests multiple strategies for therapy.

Evolutionary signatures of human cancers revealed via genomic analysis of over 35,000 patients

Recurring sequences of genomic alterations occurring across patients can highlight repeated evolutionary processes with significant implications for predicting cancer progression. Leveraging the ever-increasing availability of cancer omics data, here we unveil cancer's evolutionary signatures tied to distinct disease outcomes, representing "favored trajectories" of acquisition of driver mutations detected in patients with similar prognosis. We present a framework named ASCETIC (Agony-baSed Cancer EvoluTion InferenCe) to extract such signatures from sequencing experiments generated by different technologies such as bulk and single-cell sequencing data. We apply ASCETIC to (i) single-cell data from 146 myeloid malignancy patients and bulk sequencing from 366 acute myeloid leukemia patients, (ii) multi-region sequencing from 100 early-stage lung cancer patients, (iii) exome/genome data from 10,000+ Pan-Cancer Atlas samples, and (iv) targeted sequencing from 25,000+ MSK-MET metastatic patients, revealing subtype-specific single-nucleotide variant signatures associated with distinct prognostic clusters. Validations on several datasets underscore the robustness and generalizability of the extracted signatures.

Methylation-related genes involved in renal carcinoma progression

Renal carcinomas are a group of malignant tumors often originating in the cells lining the small tubes in the kidney responsible for filtering waste from the blood and urine production. Kidney tumors arise from the uncontrolled growth of cells in the kidneys and are responsible for a large share of global cancer-related morbidity and mortality. Understanding the molecular mechanisms driving renal carcinoma progression results crucial for the development of targeted therapies leading to an improvement of patient outcomes. Epigenetic mechanisms such as DNA methylation are known factors underlying the development of several cancer types. There is solid experimental evidence of relevant biological functions modulated by methylation-related genes, associated with the progression of different carcinomas. Those mechanisms can often be associated to different epigenetic marks, such as DNA methylation sites or chromatin conformation patterns. Currently, there is no definitive method to establish clear relations between genetic and epigenetic factors that influence the progression of cancer. Here, we developed a data-driven method to find methylation-related genes, so we could find relevant bonds between gene co-expression and methylation-wide-genome regulation patterns able to drive biological processes during the progression of clear cell renal carcinoma (ccRC). With this approach, we found out genes such as ITK oncogene that appear hypomethylated during all four stages of ccRC progression and are strongly involved in immune response functions. Also, we found out relevant tumor suppressor genes such as RAB25 hypermethylated, thus potentially avoiding repressed functions in the AKT signaling pathway during the evolution of ccRC. Our results have relevant implications to further understand some epigenetic-genetic-affected roles underlying the progression of renal cancer.

Mutational landscape of cancer-driver genes across human cancers

The genetic mutations that contribute to the transformation of healthy cells into cancerous cells have been the subject of extensive research. The molecular aberrations that lead to cancer development are often characterised by gain-of-function or loss-of-function mutations in a variety of oncogenes and tumour suppressor genes. In this study, we investigate the genomic sequences of 20,331 primary tumours representing 41 distinct human cancer types to identify and catalogue the driver mutations present in 727 known cancer genes. Our findings reveal significant variations in the frequency of cancer gene mutations across different cancer types and highlight the frequent involvement of tumour suppressor genes (94%), oncogenes (93%), transcription factors (72%), kinases (64%), cell surface receptors (63%), and phosphatases (22%), in cancer. Additionally, our analysis reveals that cancer gene mutations are predominantly co-occurring rather than exclusive in all types of cancer. Notably, we discover that patients with tumours displaying different combinations of gene mutation patterns tend to exhibit variable survival outcomes. These findings provide new insights into the genetic landscape of cancer and bring us closer to a comprehensive understanding of the underlying mechanisms driving the development of various forms of cancer.

Identification of signature genes and drug candidates for primary plasma cell leukemia: An integrated system biology approach

BACKGROUND

Plasma cell leukemia (PCL) is one of the rare cancer which is characterized by the uncontrolled proliferation of plasma cells in peripheral blood and bone marrow. The aggressive behavior of the disease and high mortality rate among PCL patients makes it a thirst area to be explored.

METHODS

The dataset for PCL was obtained from the GEO database and was analyzed using GEO2R for differentially expressed genes. Further, the functional enrichment analysis was carried out for DEGs using DAVID. The protein-protein interactions (PPI) for DEGs were obtained using STRING 11.5 and were analyzed in Cytoscape 3.7.2. to obtain the key hub genes. These key hub genes were investigated for their interaction with suitable drug candidates using DGIdb, DrugMAP, and Schrodinger's version 2022-1.

RESULTS

Out of the total of 104 DEGs, 39 genes were up-regulated whereas 65 genes were down-regulated. A total of 11 biological processes, 2 cellular components, and 5 molecular functions were enriched along with the 7 KEGG pathways for the DEGs. Further, a total of 11 hub genes were obtained from the PPI of DEGs of which TP53, MAPK1, SOCS1, MBD3, and YES1 were the key hub genes. Oxaliplatin, mitoxantrone, and ponatinib were found to have the highest binding affinity towards the p53, MAPK1, and YES1 proteins respectively.

CONCLUSION

TP53, MAPK1, SOCS1, MBD3, and YES1 are the signature hub genes that might be responsible for the aggressive prognosis of PCL leading to poor survival rate. However, p53, MAPK1, and YES1 can be targeted with oxaliplatin, mitoxantrone, and ponatinib.

Gene expression networks involved in multiple cellular programs coexist in individual hepatocellular cancer cells

The gene expression networks of a single cell can be used to reveal cell type- and condition-specific patterns that account for cell states, cell identity, and its responses to environmental changes. We applied single cell sequencing datasets to define mRNA patterns and visualized potential cellular capacities among hepatocellular cancer cells. The expressing numbers and levels of genes were highly heterogenous among the cancer cells. The cellular characteristics were dependent strongly on the expressing numbers and levels of genes, especially oncogenes and anti-oncogenes, in an individual cancer cell. The transcriptional activations of oncogenes and anti-oncogenes were strongly linked to inherent multiple cellular programs, some of which oppose and contend against other processes, in a cancer cell. The gene expression networks of multiple cellular programs proliferation, differentiation, apoptosis, autophagy, epithelial-mesenchymal transition, ATP production, and neurogenesis coexisted in an individual cancer cell. The findings give rise a hypothesis that a cancer cell expresses balanced combinations of genes and undergoes a given biological process by rapidly transmuting gene expressing networks.

Identifying the Common Cell-Free DNA Biomarkers across Seven Major Cancer Types

Blood-based detection of circulating cell-free DNA (cfDNA) is a non-invasive and easily accessible method for early cancer detection. Despite the extensive utility of cfDNA, there are still many challenges to developing clinical biomarkers. For example, cfDNA with genetic alterations often composes a small portion of the DNA circulating in plasma, which can be confounded by cfDNA contributed by normal cells. Therefore, filtering out the potential false-positive cfDNA mutations from healthy populations will be important for cancer-based biomarkers. Additionally, many low-frequency genetic alterations are easily overlooked in a small number of cfDNA-based cancer tests. We hypothesize that the combination of diverse types of cancer studies on cfDNA will provide us with a new perspective on the identification of low-frequency genetic variants across cancer types for promoting early diagnosis. By building a standardized computational pipeline for 1358 cfDNA samples across seven cancer types, we prioritized 129 shard genetic variants in the major cancer types. Further functional analysis of the 129 variants found that they are mainly enriched in ribosome pathways such as cotranslational protein targeting the membrane, some of which are tumour suppressors, oncogenes, and genes related to cancer initiation. In summary, our integrative analysis revealed the important roles of ribosome proteins as common biomarkers in early cancer diagnosis.

Enhancer remodeling drives MLL oncogene-dependent transcriptional dysregulation in leukemia stem cells

Acute myeloid leukemia (AML) with mixed-lineage leukemia (MLL) gene rearrangement (MLLr) comprises a cellular hierarchy in which a subpopulation of cells serves as functional leukemia stem cells (LSCs). They are maintained by a unique gene expression program and chromatin states, which are thought to reflect the actions of enhancers. Here, we delineate the active enhancer landscape and observe pervasive enhancer malfunction in LSCs. Reconstruction of regulatory networks revealed a master set of hematopoietic transcription factors. We show that EP300 is an essential transcriptional coregulator for maintaining LSC oncogenic potential because it controls essential gene expression through modulation of H3K27 acetylation and assessments of transcription factor dependencies. Moreover, the EP300 inhibitor A-485 affects LSC growth by targeting enhancer activity via histone acetyltransferase domain inhibition. Together, these data implicate a perturbed MLLr-specific enhancer accessibility landscape, suggesting the possibility for disruption of the LSC enhancer regulatory axis as a promising therapeutic strategy in AML.

Advances in sequencing-based studies of microDNA and ecDNA: Databases, identification methods, and integration with single-cell analysis

Extrachromosomal circular DNA (eccDNA) is a class of circular DNA molecules that originate from genomic DNA but are separate from chromosomes. They are common in various organisms, with sizes ranging from a few hundred to millions of base pairs. A special type of large extrachromosomal DNA (ecDNA) is prevalent in cancer cells. Research on ecDNA has significantly contributed to our comprehension of cancer development, progression, evolution, and drug resistance. The use of next-generation (NGS) and third-generation sequencing (TGS) techniques to identify eccDNAs throughout the genome has become a trend in current research. Here, we briefly review current advances in the biological mechanisms and applications of two distinct types of eccDNAs: microDNA and ecDNA. In addition to presenting available identification tools based on sequencing data, we summarize the most recent efforts to integrate ecDNA with single-cell analysis and put forth suggestions to promote the process.

Dimeric p53 Mutant Elicits Unique Tumor-Suppressive Activities through an Altered Metabolic Program

Cancer-related alterations of the p53 tetramerization domain (TD) abrogate wild-type (WT) p53 function. They result in a protein that preferentially forms monomers or dimers, which are also normal p53 states under basal cellular conditions. However, their physiologic relevance is not well understood. We have established in vivo models for monomeric and dimeric p53, which model Li-Fraumeni syndrome patients with germline p53 TD alterations. p53 monomers are inactive forms of the protein. Unexpectedly, p53 dimers conferred some tumor suppression that is not mediated by canonical WT p53 activities. p53 dimers upregulate the PPAR pathway. These activities are associated with lower prevalence of thymic lymphomas and increased CD8+ T-cell differentiation. Lymphomas derived from dimeric p53 mice show cooperating alterations in the PPAR pathway, further implicating a role for these activities in tumor suppression. Our data reveal novel functions for p53 dimers and support the exploration of PPAR agonists as therapies.

SIGNIFICANCE

New mouse models with TP53R342P (monomer) or TP53A347D (dimer) mutations mimic Li-Fraumeni syndrome. Although p53 monomers lack function, p53 dimers conferred noncanonical tumor-suppressive activities. We describe novel activities for p53 dimers facilitated by PPARs and propose these are "basal" p53 activities. See related commentary by Stieg et al., p. 1046. See related article by Choe et al., p. 1250. This article is highlighted in the In This Issue feature, p. 1027.