Pan-cancer analysis of whole genomes

Paired CRISPR screens to map gene regulation in cis and trans

Recent massively-parallel approaches to decipher gene regulatory circuits have focused on the discovery of either cis -regulatory elements (CREs) or trans -acting factors. Here, we develop a scalable approach that pairs cis - and trans -regulatory CRISPR screens to systematically dissect how the key immune checkpoint PD-L1 is regulated. In human pancreatic ductal adenocarcinoma (PDAC) cells, we tile the PD-L1 locus using ∼25,000 CRISPR perturbations in constitutive and IFNγ-stimulated conditions. We discover 67 enhancer- or repressor-like CREs and show that distal CREs tend to contact the promoter of PD-L1 and related genes. Next, we measure how loss of all ∼2,000 transcription factors (TFs) in the human genome impacts PD-L1 expression and, using this, we link specific TFs to individual CREs and reveal novel PD-L1 regulatory circuits. For one of these regulatory circuits, we confirm the binding of predicted trans -factors (SRF and BPTF) using CUT&RUN and show that loss of either the CRE or TFs potentiates the anti-cancer activity of primary T cells engineered with a chimeric antigen receptor. Finally, we show that expression of these TFs correlates with PD-L1 expression in vivo in primary PDAC tumors and that somatic mutations in TFs can alter response and overall survival in immune checkpoint blockade-treated patients. Taken together, our approach establishes a generalizable toolkit for decoding the regulatory landscape of any gene or locus in the human genome, yielding insights into gene regulation and clinical impact.

Loss of chromosome cytoband 13q14.2 orchestrates breast cancer pathogenesis and drug response

Breast cancer (BCa) is a major global health challenge. The BCa genome often carries extensive somatic copy number alterations (CNAs), including gains/amplifications and losses/deletions. These CNAs significantly affect tumor development, drug response and patient survival. However, how individual CNAs contribute is mostly elusive. We identified loss of chromosome 13q14.2 as a key CNA in BCa, occurring in up to 63% of patients, depending on the subtype, and correlating with poor survival. Through multi-omics and in vitro analyses, we uncover a paradoxical role of 13q14.2 loss, promoting both cell cycle and pro-apoptotic pathways in cancer cells, while also associating with increased NK cell and macrophage populations in the tumor microenvironment. Notably, 13q14.2 loss increases BCa susceptibility to BCL2 inhibitors, both in vitro and in patient-derived xenografts. Thus, 13q14.2 loss could serve as a biomarker for BCa prognosis and treatment, potentially improving outcomes for BCa patients.

Protein structural context of cancer mutations reveals molecular mechanisms and candidate driver genes

Advances in protein structure determination and modeling allow us to study the structural context of human genetic variants on an unprecedented scale. Here, we analyze millions of cancer-associated missense mutations based on their structural locations and predicted perturbative effects. By considering the collective properties of mutations at the level of individual proteins, we identify distinct patterns associated with tumor suppressors and oncogenes. Tumor suppressors are enriched in structurally damaging mutations, consistent with loss-of-function mechanisms, while oncogene mutations tend to be structurally mild, reflecting selection for gain-of-function driver mutations and against loss-of-function mutations. Although oncogenes are difficult to distinguish from genes with no role in cancer using only structural damage, we find that the three-dimensional clustering of mutations is highly predictive. These observations allow us to identify candidate driver genes and speculate about their molecular roles, which we expect will have general utility in the analysis of cancer sequencing data.

c-Jun and Fra-2 pair up to Myc-anistically drive HCC

Hepatocellular carcinoma (HCC), a leading cause of cancer-related death with limited therapies, is a complex disease developing in a background of Hepatitis Virus infection or systemic conditions, such as the metabolic syndrome. Investigating HCC pathogenesis in model organisms is therefore crucial for developing novel diagnostic and therapeutic tools. Genetically engineered mouse models (GEMMs) have been instrumental in recapitulating the local and systemic features of HCC. Early studies using GEMMs and patient material implicated members of the dimeric Activator Protein-1 (AP-1) transcription factor family, such as c-Jun and c-Fos, in HCC formation. In a recent report, we described how switchable, hepatocyte-restricted expression of a single-chain c-Jun~Fra-2 protein, functionally mimicking the c-Jun/Fra-2 AP-1 dimer, results in spontaneous and largely reversible liver tumors in GEMMs. Dysregulated cell cycle, inflammation, and dyslipidemia are observed at early stages and tumors display molecular HCC signatures. We demonstrate that increased c-Myc expression is an essential molecular determinant of tumor formation that can be therapeutically targeted using the BET inhibitor JQ1. Here, we discuss these findings with additional results illustrating how AP-1 GEMMs can foster preclinical research on liver diseases with novel perspectives offered by the constantly increasing wealth of HCC-related datasets.

From precursor to cancer: decoding the intrinsic and extrinsic pathways of pancreatic intraepithelial neoplasia progression

This review explores the progression of pancreatic intraepithelial neoplasia (PanIN) to pancreatic ductal adenocarcinoma through a dual lens of intrinsic molecular alterations and extrinsic microenvironmental influences. PanIN development begins with Kirsten rat sarcoma viral oncogene (KRAS) mutations driving PanIN initiation. Key additional mutations in cyclin-dependent kinase inhibitor 2A (CDKN2A), tumor protein p53 (TP53), and mothers against decapentaplegic homolog 4 (SMAD4) disrupt cell cycle control and genomic stability, crucial for PanIN progression from low-grade to high-grade dysplasia. Additional molecular alterations in neoplastic cells, including epigenetic modifications and chromosomal alterations, can further contribute to neoplastic progression. In parallel with these alterations in neoplastic cells, the microenvironment, including fibroblast activation, extracellular matrix remodeling, and immune modulation, plays a pivotal role in PanIN initiation and progression. Crosstalk between neoplastic and stromal cells influences nutrient support and immune evasion, contributing to tumor development, growth, and survival. This review underscores the intricate interplay between cell-intrinsic molecular drivers and cell-extrinsic microenvironmental factors, shaping PanIN predisposition, initiation, and progression. Future research aims to unravel these interactions to develop targeted therapeutic strategies and early detection techniques, aiming to alleviate the severe impact of pancreatic cancer by addressing both genetic predispositions and environmental influences.

Combining evolution and protein language models for an interpretable cancer driver mutation prediction with D2Deep

The mutations driving cancer are being increasingly exposed through tumor-specific genomic data. However, differentiating between cancer-causing driver mutations and random passenger mutations remains challenging. State-of-the-art homology-based predictors contain built-in biases and are often ill-suited to the intricacies of cancer biology. Protein language models have successfully addressed various biological problems but have not yet been tested on the challenging task of cancer driver mutation prediction at a large scale. Additionally, they often fail to offer result interpretation, hindering their effective use in clinical settings. The AI-based D2Deep method we introduce here addresses these challenges by combining two powerful elements: (i) a nonspecialized protein language model that captures the makeup of all protein sequences and (ii) protein-specific evolutionary information that encompasses functional requirements for a particular protein. D2Deep relies exclusively on sequence information, outperforms state-of-the-art predictors, and captures intricate epistatic changes throughout the protein caused by mutations. These epistatic changes correlate with known mutations in the clinical setting and can be used for the interpretation of results. The model is trained on a balanced, somatic training set and so effectively mitigates biases related to hotspot mutations compared to state-of-the-art techniques. The versatility of D2Deep is illustrated by its performance on non-cancer mutation prediction, where most variants still lack known consequences. D2Deep predictions and confidence scores are available via https://tumorscope.be/d2deep to help with clinical interpretation and mutation prioritization.

A comprehensive benchmark study of methods for identifying significantly perturbed subnetworks in cancer

Network-based methods utilize protein-protein interaction information to identify significantly perturbed subnetworks in cancer and to propose key molecular pathways. Numerous methods have been developed, but to date, a rigorous benchmark analysis to compare the performance of existing approaches is lacking. In this paper, we proposed a novel benchmarking framework using synthetic data and conducted a comprehensive analysis to investigate the ability of existing methods to detect target genes and subnetworks and to control false positives, and how they perform in the presence of topological biases at both gene and subnetwork levels. Our analysis revealed insights into algorithmic performance that were previously unattainable. Based on the results of the benchmark study, we presented a practical guide for users on how to select appropriate detection methods and protein-protein interaction networks for cancer pathway identification, and provided suggestions for future algorithm development.

Classification of pediatric soft and bone sarcomas using DNA methylation-based profiling

Pediatric sarcomas present heterogeneous morphology, genetics and clinical behavior posing a challenge for an accurate diagnosis. DNA methylation is an epigenetic modification that coordinates chromatin structure and regulates gene expression, determining cell type and function. DNA methylation-based tumor profiling classifier for sarcomas (known as sarcoma classifier) from the German Cancer Research Center (Deutsches Krebsforschungszentrum) was applied to 122 pediatric sarcomas referred to a reference pediatric oncology hospital. The classifiers reported 88.5% of agreement between histopathological and molecular classification confirming the initial diagnosis of all osteosarcomas and Ewing sarcomas. The Ewing-like sarcomas were reclassified into sarcomas with BCOR or CIC alterations, later confirmed by orthogonal diagnostic techniques. Regarding the CNAs profile, osteosarcomas had several chromosomal gains and losses as well as chromothripsis, whereas Ewing sarcomas had few large events, such as amplifications of chromosomes 8 and 12. The molecular classification together with clinical and histopathological assessment could improve the diagnosis of pediatric sarcomas although there are limitations to deal with more rare classes. This study provides an increase in the number of sarcomas evaluated for DNA methylation profiling in the pediatric population.

Mutagenic impact and evolutionary influence of radiotherapy in hematologic malignancies

Ionizing radiotherapy (RT) is a widely used palliative and curative treatment strategy for malignancies. In solid tumors, RT-induced double strand breaks lead to the accumulation of indels, and their repair by non-homologous end-joining has been linked to the ID8 mutational signature in resistant cells. However, the extent of RT-induced DNA damage in hematologic malignancies and its impact on their evolution and interplay with commonly used chemotherapies has not yet been explored. Here, we interrogated 580 whole genome sequencing (WGS) from patients with large B-cell lymphoma, multiple myeloma, and myeloid neoplasms and identified ID8 only in relapsed disease. Yet, it was detected after exposure to both RT and mutagenic chemotherapy (i.e., platinum). Using WGS of single-cell colonies derived from treated lymphoma cells, we revealed a dose-response relationship between RT and platinum and ID8. Finally, using ID8 as a genomic barcode we demonstrate that a single RT-resistant cell may seed systemic relapse.

Loss of the predicted cell adhesion molecule MPZL3 promotes EMT and chemoresistance in ovarian cancer

Myelin protein zero-like 3 (MPZL3) is an Immunoglobulin-containing transmembrane protein with predicted cell adhesion molecule function. Loss of 11q23, where the MPZL3 gene resides, is frequently observed in cancer, and MPZL3 copy number alterations are frequently detected in tumor specimens. Yet the role and consequences of altered MPZL3 expression have not been explored in tumor development and progression. We addressed this in ovarian cancer, where both MPZL3 amplification and deletions are observed in respective subsets of high-grade serous specimens. While high and low MPZL3 expressing populations were similarly observed in primary ovarian tumors from an independent patient cohort, metastatic omental tumors largely displayed decreased MPZL3 expression, suggesting that MPZL3 loss is associated with metastatic progression. MPZL3 knock-down leads to strong upregulation of vimentin and an EMT gene signature that is associated with poor patient outcomes. Moreover, MPZL3 is necessary for homotypic cancer cell adhesion, and decreasing MPZL3 expression enhances invasion and clearance of mesothelial cell monolayers. In addition, MPZL3 loss abrogated cell cycle progression and proliferation. This was associated with increased resistance to Cisplatin and Olaparib and reduced DNA damage and apoptosis in response to these agents. Enhanced Cisplatin resistance was further validated in vivo . These data demonstrate for the first time that MPZL3 acts as an adhesion molecule and that MPZL3 loss results in EMT, decreased proliferation, and drug resistance in ovarian cancer. Our study suggests that decreased MPZL3 expression is a phenotype of ovarian cancer tumor progression and metastasis and may contribute to treatment failure in advanced-stage patients.

Tumor-infiltrating B cell-related lncRNA crosstalk reveals clinical outcomes and tumor immune microenvironment in ovarian cancer based on single-cell and bulk RNA-sequencing

Background

The tumor immune microenvironment (TIME) plays a pivotal role in determining ovarian cancer (OC) prognosis. Long non-coding RNAs (lncRNAs) are key regulators of immune response and tumor progression in OC. Among these, tumor-infiltrating B cells represent an emerging target in immune response pathways. However, the specific involvement of B cell-related lncRNAs (BCRLs) in OC remains unclarified.

Methods

Leveraging single-cell and bulk RNA-sequencing data, correlation analysis identified BCRLs in ovarian serous cystadenocarcinoma (OV) from the TCGA database. Subsequently, BCRLIs were filtered through COX survival analysis and the LASSO algorithm, leading to the development of a B cell-related lncRNA scoring system (BCRLss). The predictive accuracy of BCRLss for prognosis in TCGA-OV was assessed and externally validated in an independent cohort. Functional enrichment analyses were conducted to elucidate biological pathways associated with risk subgroups. Additionally, the relationship between BCRLss and TIME was investigated through multiple algorithms and consensus clustering, uncovering potential immune response targets. Drug sensitivity analyses further identified potential therapeutic options tailored to risk subgroups. The highest risk score lncRNA was selected for in vitro validation.

Results

The BCRLss was constructed using six BCRLIs. Survival analysis revealed an improved prognosis in the low-risk group, with results corroborated by external validation in the ICGC-OV cohort. ROC analysis and nomogram construction confirmed the strong prognostic accuracy of BCRLss. Enrichment analysis highlighted associations between risk subgroups and tumor immune pathways, with the low-risk group demonstrating a more robust immune response and elevated expression of immune checkpoint-related genes. Drug sensitivity tests revealed notable differences across risk subgroups. In vitro experiments confirmed elevated LINC01150 expression in OC cells, and LINC01150 knockdown significantly inhibited the proliferation, invasion, and migration of SKOV3 cells.

Conclusions

In conclusion, BCRLss provides a reliable prognostic tool for predicting clinical outcomes and the immune landscape of patients with OC, offering valuable guidance for immunotherapy target selection and personalized treatment strategies.

Base-excision repair pathway shapes 5-methylcytosine deamination signatures in pan-cancer genomes

Transition of cytosine to thymine in CpG dinucleotides is the most frequent type of mutation in cancer. This increased mutability is commonly attributed to the spontaneous deamination of 5-methylcytosine (5mC), which is normally repaired by the base-excision repair (BER) pathway. However, the contribution of 5mC deamination in the increasing diversity of cancer mutational signatures remains poorly explored. We integrate mutational signatures analysis in a large series of tumor whole genomes with lineage-specific epigenomic data to draw a detailed view of 5mC deamination in cancer. We uncover tumor type-specific patterns of 5mC deamination signatures in CpG and non-CpG contexts. We demonstrate that the BER glycosylase MBD4 preferentially binds to active chromatin and early replicating DNA, which correlates with lower mutational burden in these domains. We validate our findings by modeling BER deficiencies in isogenic cell models. Here, we establish MBD4 as the main actor responsible for 5mC deamination repair in humans.

PKCα Activation via the Thyroid Hormone Membrane Receptor Is Key to Thyroid Cancer Growth

Thyroid carcinoma (TC) is the most common endocrine neoplasia, with its incidence increasing in the last 40 years worldwide. The determination of genetic and/or protein markers for thyroid carcinoma could increase diagnostic precision. Accumulated evidence shows that Protein kinase C alpha (PKCα) contributes to tumorigenesis and therapy resistance in cancer. However, the role of PKCα in TC remains poorly studied. Our group and others have demonstrated that PKCs can mediate the proliferative effects of thyroid hormones (THs) through their membrane receptor, the integrin αvβ3, in several cancer types. We found that PKCα is overexpressed in TC cell lines, and it also appeared as the predominant expressed isoform in public databases of TC patients. PKCα-depleted cells significantly reduced THs-induced proliferation, mediated by the integrin αvβ3 receptor, through AKT and Erk activation. In databases of TC patients, higher PKCα expression was associated with lower overall survival. Further analyses showed a positive correlation between PKCα and genes from the MAPK and PI3K-Akt pathways. Finally, immunohistochemical analysis showed abnormal upregulation of PKCα in human thyroid tumors. Our findings establish a potential role for PKCα in the control of hormone-induced proliferation that can be explored as a therapeutic and/or diagnostic target for TC.

What are the essential determinants of human papillomavirus carcinogenesis?

Human papillomavirus (HPV) infection is the leading viral cause of cancer. Over the past several decades, research on HPVs has provided remarkable insight into human cell biology and into the pathology of viral and non-viral cancers. The HPV E6 and E7 proteins engage host cellular proteins to establish an environment in infected cells that is conducive to virus replication. They rewire host cell signaling pathways to promote proliferation, inhibit differentiation, and limit cell death. The activity of the "high-risk" HPV E6 and E7 proteins is so potent that their dysregulated expression is sufficient to drive the initiation and maintenance of HPV-associated cancers. Consequently, intensive research efforts have aimed to identify the host cell targets of E6 and E7, in part with the idea that some or all of the virus-host interactions would be essential cancer drivers. These efforts have identified a large number of potential binding partners of each oncoprotein. However, over the same time period, parallel research has revealed that a relatively small number of genetic mutations drive carcinogenesis in most non-viral cancers. We therefore propose that a high-priority goal is to identify which of the many targets of E6 and E7 are critical drivers of HPV carcinogenesis. By identifying the cancer-driving targets of E6 and E7, it should be possible to better understand the distinct roles of other targets, perhaps in the viral life cycle, and to focus efforts to develop anti-cancer therapies on the subset of virus-host interactions for which therapeutic intervention would have the greatest impact.

Advancements in Multiple Myeloma Research: High-Throughput Sequencing Technologies, Omics, and the Role of Artificial Intelligence

Multiple myeloma is a complex and challenging type of blood cancer that affects plasma cells in the bone marrow. In recent years, the development of advanced research techniques, such as omics approaches-which involve studying large sets of biological data like genes and proteins-and high-throughput sequencing technologies, has allowed researchers to analyze vast amounts of genetic information rapidly and gain new insights into the disease. Additionally, the advent of artificial intelligence tools has accelerated data analysis, enabling more accurate predictions and improved treatment strategies. This review aims to highlight recent research advances in multiple myeloma made possible by these novel techniques and to provide guidance for researchers seeking effective approaches in this field.

Identifying barriers and opportunities to facilitate the uptake of whole genome sequencing in paediatric haematology and oncology practice

BACKGROUND

The clinical utility of whole genome sequencing (WGS) in paediatric cancer has been demonstrated in recent years. WGS has been routinely available in the National Health Service (NHS) England for all children with cancer in England since 2021, but its uptake has been variable geographically. To explore the underlying barriers to routine use of WGS in this population across England and more widely in the United Kingdom (UK) and the Republic of Ireland (ROI), a one-day workshop was held in Cambridge, United Kingdom in October 2022.

METHODS

Following a series of talks, delegates participated in open, round-table discussions to outline local and broader challenges limiting routine WGS for diagnostic work-up for children with cancer in their Principal Treatment Centres (PTCs) and Genomic Laboratory Hubs (GLHs). Within smaller groups, delegates answered structured questions regarding clinical capability, education and training needs, and workforce competence and requirements. Data was recorded, centrally collated, and analysed following the event using thematic analysis.

RESULTS

Sixty participants attended the workshop with broad representation from the 20 PTCs across the UK and ROI and the seven GLHs in England. All healthcare professionals involved in the WGS pathway were represented, including paediatric oncologists, clinical geneticists, clinical scientists, and histopathologists. The main themes highlighted by the group in ensuring equitable access to WGS identified were: lack of knowledge equity between NHS trusts, with a perception of WGS being for research only; and perception of lack of financial support for the clinical process surrounding WGS, including lack of time to take informed consent from patients. The latter also included limited trained staff available for data interpretation, affecting the turnaround time for reporting. Finally, the need for an integrated digital pathway to order, track, and return data to clinicians was highlighted.

CONCLUSION

At the workshop, the general motivation for including WGS in the diagnostic work up for children with cancer was high throughout the UK, however a perceived lack of resources and education opportunities limit the widespread use of this commissioned assay. This workshop has led to some recommendations to increase access to WGS in this population in England and more widely in the devolved national of the UK and the ROI.

Targeting Catechol-O-Methyltransferase Induces Mitochondrial Dysfunction and Enhances the Efficacy of Radiotherapy in Glioma

Radiotherapy (RT) is commonly used to try to eliminate any remaining tumor cells following surgical resection of glioma. However, tumor recurrence is prevalent, highlighting the unmet medical need to develop therapeutic strategies to enhance the efficacy of RT in glioma. Focusing on the radiosensitizing potential of the currently approved drugs known to cross the blood-brain barrier can facilitate rapid clinical translation. Here, we assessed the role of catechol-O-methyltransferase (COMT), a key enzyme to degrade catecholamines and a drug target for Parkinson's disease, in glioma treatment. Analysis of The Cancer Genome Atlas data showed significantly higher COMT expression levels in both low-grade glioma and glioblastoma compared to normal brain tissues. Inhibition of COMT by genetic knockout or FDA-approved COMT inhibitors significantly sensitized glioma cells to RT in vitro and in vivo. Mechanistically, COMT inhibition in glioma cells led to mitochondria dysfunction and increased mitochondrial RNA release into the cytoplasm, activating the cellular antiviral double-stranded RNA sensing pathway and type I interferon (IFN) response. Elevated type I IFNs stimulated the phagocytic capacity of microglial cells, enhancing RT efficacy. Given the long-established safety record of the COMT inhibitors, these findings provide a solid rationale to evaluate them in combination with RT in patients with glioma. Significance: Inhibition of catechol-O-methyltransferase, a well-established drug target in Parkinson's disease, interferes with mitochondrial electron transport and induces mitochondrial double-stranded RNA leakage, activating type I interferon signaling and sensitizing glioma to radiotherapy.

StableLift: Optimized Germline and Somatic Variant Detection Across Genome Builds

Reference genomes are foundational to modern genomics. Our growing understanding of genome structure leads to continual improvements in reference genomes and new genome "builds" with incompatible coordinate systems. We quantified the impact of genome build on germline and somatic variant calling by analyzing tumour-normal whole-genome pairs against the two most widely used human genome builds. The average individual had a build-discordance of 3.8% for germline SNPs, 8.6% for germline SVs, 25.9% for somatic SNVs and 49.6% for somatic SVs. Build-discordant variants are not simply false-positives: 47% were verified by targeted resequencing. Build-discordant variants were associated with specific genomic and technical features in variant- and algorithm-specific patterns. We leveraged these patterns to create StableLift, an algorithm that predicts cross-build stability with AUROCs of 0.934 ± 0.029. These results call for significant caution in cross-build analyses and for use of StableLift as a computationally efficient solution to mitigate inter-build artifacts.

The non-canonical BAF chromatin remodeling complex is a novel target of spliceosome dysregulation in SF3B1-mutated chronic lymphocytic leukemia

SF3B1 mutations are recurrent in chronic lymphocytic leukemia (CLL), particularly enriched in clinically aggressive stereotyped subset #2. To investigate their impact, we conducted RNA-sequencing of 18 SF3B1MUT and 17 SF3B1WT subset #2 cases and identified 80 significant alternative splicing events (ASEs). Notable ASEs concerned exon inclusion in the non-canonical BAF (ncBAF) chromatin remodeling complex subunit, BRD9, and splice variants in eight additional ncBAF complex interactors. Long-read RNA-sequencing confirmed the presence of splice variants, and extended analysis of 139 CLL cases corroborated their association with SF3B1 mutations. Overexpression of SF3B1K700E induced exon inclusion in BRD9, resulting in a novel splice isoform with an alternative C-terminus. Protein interactome analysis of the BRD9 splice isoform revealed augmented ncBAF complex interaction, while exhibiting decreased binding of auxiliary proteins, including SPEN, BRCA2, and CHD9. Additionally, integrative multi-omics analysis identified a ncBAF complex-bound gene quartet on chromosome 1 with higher expression levels and more accessible chromatin in SF3B1MUT CLL. Finally, Cancer Dependency Map analysis and BRD9 inhibition displayed BRD9 dependency and sensitivity in cell lines and primary CLL cells. In conclusion, spliceosome dysregulation caused by SF3B1 mutations leads to multiple ASEs and an altered ncBAF complex interactome, highlighting a novel pathobiological mechanism in SF3B1MUT CLL.

Cell-free DNA assay for malignancy classification of high-risk lung nodules

OBJECTIVE

Although low-dose computed tomography has been proven effective to reduce lung cancer-specific mortality, a considerable proportion of surgically resected high-risk lung nodules were still confirmed pathologically benign. There is an unmet need of a novel method for malignancy classification in lung nodules.

METHODS

We recruited 307 patients with high-risk lung nodules who underwent curative surgery, and 247 and 60 cases were pathologically confirmed malignant and benign lung lesions, respectively. Plasma samples from each patient were collected before surgery and performed low-depth (5×) whole-genome sequencing. We extracted cell-free DNA characteristics and determined radiomic features. We built models to classify the malignancy using our data and further validated models with 2 independent lung nodule cohorts.

RESULTS

Our models using one type of profile were able to distinguish lung cancer and benign lung nodules at an area under the curve metrics of 0.69 to 0.91 in the study cohort. Integrating all the 5 base models using cell-free DNA profiles, the cell-free DNA-based ensemble model achieved an area under the curve of 0.95 (95% CI, 0.92-0.97) in the study cohort and 0.98 (95% CI, 0.96-1.00) in the validation cohort. At a specificity of 95.0%, the sensitivity reached 80.0% in the study cohort. With the same threshold, the specificity and sensitivity had similar performances in both validation cohorts. Furthermore, the performance of area under the curve reached 0.97 in both the study and validation cohorts when considering the radiomic profile.

CONCLUSIONS

The cell-free DNA profiles-based method is an efficient noninvasive tool to distinguish malignancies and high-risk but pathologically benign lung nodules.

VCAT: an integrated variant function annotation tools

The development of sequencing technology has promoted discovery of variants in the human genome. Identifying functions of these variants is important for us to link genotype to phenotype, and to diagnose diseases. However, it usually requires researchers to visit multiple databases. Here, we presented a one-stop webserver for variant function annotation tools (VCAT, https://biomed.nscc-gz.cn/zhaolab/VCAT/ ) that is the first one connecting variant to functions via the epigenome, protein, drug and RNA. VCAT is also the first one to make all annotations visualized in interactive charts or molecular structures. VCAT allows users to upload data in VCF format, and download results via a URL. Moreover, VCAT has annotated a huge number (1,262,041,068) of variants collected from dbSNP, 1000 Genomes projects, gnomAD, ICGC, TCGA, and HPRC Pangenome project. For these variants, users are able to searcher their functions, related diseases and drugs from VCAT. In summary, VCAT provides a one-stop webserver to explore the potential functions of human genomic variants including their relationship with diseases and drugs.

Developmental Dysregulation of Childhood Cancer

Most childhood cancers possess distinct clinicopathological profiles from those seen in adulthood, reflecting their divergent mechanisms of carcinogenesis. Rather than depending on the decades-long, stepwise accumulation of changes within a mature cell that defines adult carcinomas, many pediatric malignancies emerge rapidly as the consequence of random errors during development. These errors-whether they be genetic, epigenetic, or microenvironmental-characteristically block maturation, resulting in phenotypically primitive neoplasms. Only an event that falls within a narrow set of spatiotemporal parameters will forge a malignant clone; if it occurs too soon then the event might be lethal, or negatively selected against, while if it is too late or in an incorrectly primed precursor cell then the necessary intracellular conditions for transformation will not be met. The precise characterization of these changes, through the study of normal tissues and tumors from patients and model systems, will be essential if we are to develop new strategies to diagnose, treat, and perhaps even prevent childhood cancer.

The interplay of mutagenesis and ecDNA shapes urothelial cancer evolution

Advanced urothelial cancer is a frequently lethal disease characterized by marked genetic heterogeneity1. In this study, we investigated the evolution of genomic signatures caused by endogenous and external mutagenic processes and their interplay with complex structural variants (SVs). We superimposed mutational signatures and phylogenetic analyses of matched serial tumours from patients with urothelial cancer to define the evolutionary dynamics of these processes. We show that APOBEC3-induced mutations are clonal and early, whereas chemotherapy induces mutational bursts of hundreds of late subclonal mutations. Using a genome graph computational tool2, we observed frequent high copy-number circular amplicons characteristic of extrachromosomal DNA (ecDNA)-forming SVs. We characterized the distinct temporal patterns of APOBEC3-induced and chemotherapy-induced mutations within ecDNA-forming SVs, gaining new insights into the timing of these mutagenic processes relative to ecDNA biogenesis. We discovered that most CCND1 amplifications in urothelial cancer arise within circular ecDNA-forming SVs. ecDNA-forming SVs persisted and increased in complexity, incorporating additional DNA segments and contributing to the evolution of treatment resistance. Oxford Nanopore Technologies long-read whole-genome sequencing followed by de novo assembly mapped out CCND1 ecDNA structure. Experimental modelling of CCND1 ecDNA confirmed its role as a driver of treatment resistance. Our findings define fundamental mechanisms that drive urothelial cancer evolution and have important therapeutic implications.

Melanoma-specific mutation hotspots in distal, non-coding, promoter-interacting regions implicate novel candidate driver genes

BACKGROUND

To develop targeted treatments, it is crucial to identify the full spectrum of genetic drivers in melanoma, including those in non-coding regions. However, recent efforts to explore non-coding regions have primarily focused on gene-adjacent elements such as promoters and non-coding RNAs, leaving intergenic distal regulatory elements largely unexplored.

METHODS

We used Hi-C chromatin contact data from melanoma cells to map distal, non-coding, promoter-interacting regulatory elements genome-wide in melanoma. Using this "promoter-interaction network", alongside whole-genome sequence and gene expression data from the Pan Cancer Analysis of Whole Genomes, we developed multivariate linear regression models to identify distal somatic mutation hotspots that affect promoter activity.

RESULTS

We identified eight recurrently mutated hotspots that are novel, melanoma-specific, located in promoter-interacting distal regulatory elements, alter transcription factor binding motifs, and affect the expression of genes (e.g., HSPB7, CLDN1, ADCY9 and FDXR) previously implicated as tumour suppressors/oncogenes in various cancers.

CONCLUSIONS

Our study suggests additional non-coding drivers beyond the well-characterised TERT promoter in melanoma, offering new insights into the disruption of complex regulatory networks by non-coding mutations that may contribute to melanoma development. Furthermore, our study provides a framework for integrating multiple levels of biological data to uncover cancer-specific non-coding drivers.

Highly Multiplexed Tissue Imaging in Precision Oncology and Translational Cancer Research

Precision oncology tailors treatment strategies to a patient's molecular and health data. Despite the essential clinical value of current diagnostic methods, hematoxylin and eosin morphology, immunohistochemistry, and gene panel sequencing offer an incomplete characterization. In contrast, highly multiplexed tissue imaging allows spatial analysis of dozens of markers at single-cell resolution enabling analysis of complex tumor ecosystems; thereby it has the potential to advance our understanding of cancer biology and supports drug development, biomarker discovery, and patient stratification. We describe available highly multiplexed imaging modalities, discuss their advantages and disadvantages for clinical use, and potential paths to implement these into clinical practice. Significance: This review provides guidance on how high-resolution, multiplexed tissue imaging of patient samples can be integrated into clinical workflows. It systematically compares existing and emerging technologies and outlines potential applications in the field of precision oncology, thereby bridging the ever-evolving landscape of cancer research with practical implementation possibilities of highly multiplexed tissue imaging into routine clinical practice.

Human DNA polymerase ε is a source of C>T mutations at CpG dinucleotides

C-to-T transitions in CpG dinucleotides are the most prevalent mutations in human cancers and genetic diseases. These mutations have been attributed to deamination of 5-methylcytosine (5mC), an epigenetic modification found on CpGs. We recently linked CpG>TpG mutations to replication and hypothesized that errors introduced by polymerase ε (Pol ε) may represent an alternative source of mutations. Here we present a new method called polymerase error rate sequencing (PER-seq) to measure the error spectrum of DNA polymerases in isolation. We find that the most common human cancer-associated Pol ε mutant (P286R) produces an excess of CpG>TpG errors, phenocopying the mutation spectrum of tumors carrying this mutation and deficiencies in mismatch repair. Notably, we also discover that wild-type Pol ε has a sevenfold higher error rate when replicating 5mCpG compared to C in other contexts. Together, our results from PER-seq and human cancers demonstrate that replication errors are a major contributor to CpG>TpG mutagenesis in replicating cells, fundamentally changing our understanding of this important disease-causing mutational mechanism.

Towards functional maps of non-coding variants in cancer

Large scale cancer genomic studies in patients have unveiled millions of non-coding variants. While a handful have been shown to drive cancer development, the vast majority have unknown function. This review describes the challenges of functionally annotating non-coding cancer variants and understanding how they contribute to cancer. We summarize recently developed high-throughput technologies to address these challenges. Finally, we outline future prospects for non-coding cancer genetics to help catalyze personalized cancer therapy.

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.

APOBEC3A drives metastasis of high-grade serous ovarian cancer by altering epithelial-to-mesenchymal transition

High-grade serous ovarian cancer (HGSOC) is the most prevalent and aggressive histological subtype of ovarian cancer, and often presents with metastatic disease. The drivers of metastasis in HGSOC remain enigmatic. APOBEC3A (A3A), an enzyme that generates mutations across various cancers, has been proposed as a mediator of tumor heterogeneity and disease progression. However, the role of A3A in HGSOC has not been explored. Through analysis of genome sequencing from primary HGSOC, we observed an association between high levels of APOBEC3 mutagenesis and poor overall survival. We experimentally addressed this correlation by modeling A3A activity in HGSOC cell lines and mouse models which resulted in increased metastatic behavior of HGSOC cells in culture and distant metastatic spread in vivo . A3A activity in both primary and cultured HGSOC cells yielded consistent alterations in expression of epithelial-mesenchymal-transition (EMT) genes resulting in hybrid EMT and mesenchymal signatures, and providing a mechanism for their increased metastatic potential. Our findings define the prevalence of A3A mutagenesis in HGSOC and implicate A3A as a driver of HGSOC metastasis via EMT, underscoring its clinical relevance as a potential prognostic biomarker. Our study lays the groundwork for the development of targeted therapies aimed at mitigating the deleterious impact of A3A-driven EMT in HGSOC.

ROBUST DISCOVERY OF MUTATIONAL SIGNATURES USING POWER POSTERIORS

Mutational processes, such as the molecular effects of carcinogenic agents or defective DNA repair mechanisms, are known to produce different mutation types with characteristic frequency profiles, referred to as mutational signatures. Non-negative matrix factorization (NMF) has successfully been used to discover many mutational signatures, yielding novel insights into cancer etiology and targeted therapies. However, the NMF model is only a rough approximation to reality, and even small departures from this assumed model can have large negative effects on the accuracy and reliability of the results. We propose a new approach to mutational signatures analysis that improves robustness to misspecification by using a power posterior for a fully Bayesian NMF model, while employing a sparsity-inducing prior to automatically infer the number of active signatures. In extensive simulation studies, we find that our proposed approach recovers more true signatures with greater accuracy than current leading methods. On whole-genome sequencing data for six cancer types from the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium, we find that our method is able to accurately recover more signatures than the current state-of-the-art.

Tumor organoids improve mutation detection of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) presents challenges in detecting somatic mutations due to its complex cellular composition. This study investigated the utility of patient-derived organoids (PDOs) to overcome these obstacles and enhance somatic mutation identification. Surgically resected PDAC tumors and their paired PDOs from 21 patients were examined. Whole-exome sequencing (WES) of tumor tissue, organoids, and peripheral blood mononuclear cells was performed to identify somatic mutations. Our findings demonstrate that PDOs retained about 80% of the somatic mutations from the original tumors, showing high concordance in mutation types. PDOs exhibited increased tumor purity and uncovered key driver mutations, aiding in identifying clinically relevant genomic alterations. Moreover, eight cycles of FOLFIRINOX treatment did not significantly alter the mutational landscape at the DNA level, indicating the stability of the mutational profile after therapeutic pressure in patients. In conclusion, PDOs are potentially important tools for exploring the somatic mutational landscape of PDAC. While they can reveal mutations that may be challenging to detect through traditional biopsy sequencing due to the inherently low tumor purity of PDAC, it is important to note that PDOs may not always fully recapitulate all mutations found in primary tumors. Despite this limitation, PDOs can still offer critical insights into the genomic complexities of PDAC, which is crucial for the development of personalized vaccines and therapies for this disease.

The prominent pervasive oncogenic role and tissue specific permissiveness of RAS gene mutations

In cancer research, RAS biology has been focused on only a handful of tumor types. While RAS genes have long been suspected as common contributors to a wide spectrum of cancer types, robust evidence is required to firmly establish their critical oncogenic significance. We present a data mining study using DepMap genome-wide CRISPR screening data, which provide substantial evidence to support the prominent pervasive oncogenic role and tissue-specific permissiveness of RAS gene mutations. Differential analysis of CRISPR effect scores identifies K- or N-RAS genes as the most differential gene in contrasts of (K-, N-, combined) RAS mutant versus wild-type cell lines across multiple tissue types. The distinguished tissue-specific pattern of KRAS vs. NRAS as top differential genes in subsets of tissue types and evidence from genome data supported the idea of KRAS- and NRAS-engaged tissue types. To our knowledge, this is the first report of prominent pervasive oncogenic role of RAS mutations revealed by gene dependency data that is beyond the current understanding of the oncogenic role of RAS genes and their well-known involved tissue types. Our findings strongly support RAS mutations as primary oncogenic drivers beyond traditionally recognized cancer types and offer insights into their tissue-specific permissiveness.

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.

Insight of Employing Molecular Junctions for Sensor Applications

Molecular junctions (MJs) exhibit distinct charge transport properties and have the potential to become the next generation of electronic devices. Advancing molecular electronics for practical uses, such as sensors, is crucial to propel its progress to the next level. In this review, we discussed how MJs can serve as a sensor for detecting a wide range of analytes with exceptional sensitivity and specificity. The primary advances and potential of molecular junctions for the various kinds of sensors including photosensors, explosives (DNTs, TNTs), cancer biomarker detection (DNA, mRNA), COVID detection, biogases (CO, NO, NH), environmental pH, practical chemicals, and water pollutants are listed and examined here. The fundamental ideas of molecular junction formation as well as the sensing mechanism have been examined here. This review demonstrates that MJ-based sensors hold significant promise for real-time and on-site detection. It provides valuable insights into current research and outlines potential future directions for advancing molecular junction-based sensors for practical applications.

NRXN1 as a Prognostic Biomarker: Linking Copy Number Variation to EMT and Survival in Colon Cancer

The role of biomarkers in cancer treatment varies significantly depending on the cancer stage. Thus, in clinical practice, tailoring biomarkers to meet the specific needs and challenges of each cancer stage can increase the precision of treatment. Because they reflect underlying genetic alterations that influence cancer progression, copy number variation (CNV) biomarkers can play crucial prognostic roles. In our previous study, we identified potential survival-related genes for colorectal cancer (CRC) by analyzing CNV and gene expression data using a machine-learning approach. To further investigate the biological function of NRXN1, we assessed the use of RNA sequencing, phosphokinase assays, real-time quantitative PCR, and Western blot analysis. We found that NRXN1 copy number deletion was significantly associated with poor overall survival (OS) and recurrence-free survival (RFS), even in patients who received adjuvant chemotherapy. Compared with its expression in normal tissues, NRXN1 expression was lower in tumors, suggesting its potential role as a tumor suppressor. NRXN1 knockdown enhanced CRC cell viability and invasion, and transcriptome analysis indicated that the increased invasion was caused by GSK3β-mediated epithelial-mesenchymal transition. These findings highlight NRXN1 copy number deletion as a novel biomarker for predicting recurrence and survival in patients with resected colon cancer.

Droplet Hi-C enables scalable, single-cell profiling of chromatin architecture in heterogeneous tissues

Current methods for analyzing chromatin architecture are not readily scalable to heterogeneous tissues. Here we introduce Droplet Hi-C, which uses a commercial microfluidic device for high-throughput, single-cell chromatin conformation profiling in droplets. Using Droplet Hi-C, we mapped the chromatin architecture of the mouse cortex and analyzed gene regulatory programs in major cortical cell types. In addition, we used this technique to detect copy number variations, structural variations and extrachromosomal DNA in human glioblastoma, colorectal and blood cancer cells, revealing clonal dynamics and other oncogenic events during treatment. We refined the technique to allow joint profiling of chromatin architecture and transcriptome in single cells, facilitating exploration of the links between chromatin architecture and gene expression in both normal tissues and tumors. Thus, Droplet Hi-C both addresses critical gaps in chromatin analysis of heterogeneous tissues and enhances understanding of gene regulation.

Comprehensive evaluation and guidance of structural variation detection tools in chicken whole genome sequence data

BACKGROUND

Structural variations (SVs) are widespread across genome and have a great impact on evolution, disease, and phenotypic diversity. Despite the development of numerous bioinformatic tools, commonly referred to as SV callers, tailored for detecting SVs using whole genome sequence (WGS) data and employing diverse algorithms, their performance necessitates rigorous evaluation with real data and validated SVs. Moreover, a considerable proportion of these tools have been primarily designed and optimized using human genome data. Consequently, their applicability and performance in Avian species, characterized by smaller genomes and distinct genomic architectures, remain inadequately assessed.

RESULTS

We performed a comprehensive assessment of the performance of ten widely used SV callers using population-level real genomic data with the validated five common types of SVs. The performance of SV callers varies with the types and sizes of SVs. As compared with other tools, GRIDSS, Lumpy, Wham, and Manta present better detection accuracy. Pindel can detect more small SVs than others. CNVnator and CNVkit can detect more medium and large copy number variations. Given the poor consistency among different SV callers, the combination calling strategy is not recommended. All tools show poor ability in the detection of insertions (especially with size > 150 bp). At least 50× read depth is required to detect more than 80% of the SVs for most tools.

CONCLUSIONS

This study highlights the importance and necessity of using real sequencing data, rather than simulated data only, with validated SVs for SV caller evaluation. Some practical guidance and suggestions are provided for SV detection in future researches.

Modeling lung adenocarcinoma metastases using patient-derived organoids

Approximately 50% of patients with surgically resected early-stage lung cancer develop distant metastasis. At present, there is no in vivo metastasis model to investigate the biology of human lung cancer metastases. Using well-characterized lung adenocarcinoma (LUAD) patient-derived organoids (PDOs), we establish an in vivo metastasis model that preserves the biologic features of human metastases. Results of whole-genome and RNA sequencing establish that our in vivo PDO metastasis model can be used to study clonality and tumor evolution and to identify biomarkers related to organotropism. Investigation of the response of KRASG12C PDOs to sotorasib demonstrates that the model can examine the efficacy of treatments to suppress metastasis and identify mechanisms of drug resistance. Finally, our PDO model cocultured with autologous peripheral blood mononuclear cells can potentially be used to determine the optimal immune-priming strategy for individual patients with LUAD.

Pan-cancer Analysis Reveals m6A Variation and Cell-specific Regulatory Network in Different Cancer Types

As the most abundant messenger RNA (mRNA) modification, N6-methyladenosine (m6A) plays a crucial role in RNA fate, impacting cellular and physiological processes in various tumor types. However, our understanding of the role of the m6A methylome in tumor heterogeneity remains limited. Herein, we collected and analyzed m6A methylomes across nine human tissues from 97 m6A sequencing (m6A-seq) and RNA sequencing (RNA-seq) samples. Our findings demonstrate that m6A exhibits different heterogeneity in most tumor tissues compared to normal tissues, which contributes to the diverse clinical outcomes in different cancer types. We also found that the cancer type-specific m6A level regulated the expression of different cancer-related genes in distinct cancer types. Utilizing a novel and reliable method called "m6A-express", we predicted m6A-regulated genes and revealed that cancer type-specific m6A-regulated genes contributed to the prognosis, tumor origin, and infiltration level of immune cells in diverse patient populations. Furthermore, we identified cell-specific m6A regulators that regulate cancer-specific m6A and constructed a regulatory network. Experimental validation was performed, confirming that the cell-specific m6A regulator CAPRIN1 controls the m6A level of TP53. Overall, our work reveals the clinical relevance of m6A in various tumor tissues and explains how such heterogeneity is established. These results further suggest the potential of m6A in cancer precision medicine for patients with different cancer types.

Somatic mosaicism in schizophrenia brains reveals prenatal mutational processes

Germline mutations modulate the risk of developing schizophrenia (SCZ). Much less is known about the role of mosaic somatic mutations in the context of SCZ. Deep (239×) whole-genome sequencing (WGS) of brain neurons from 61 SCZ cases and 25 controls postmortem identified mutations occurring during prenatal neurogenesis. SCZ cases showed increased somatic variants in open chromatin, with increased mosaic CpG transversions (CpG>GpG) and T>G mutations at transcription factor binding sites (TFBSs) overlapping open chromatin, a result not seen in controls. Some of these variants alter gene expression, including SCZ risk genes and genes involved in neurodevelopment. Although these mutational processes can reflect a difference in factors indirectly involved in disease, increased somatic mutations at developmental TFBSs could also potentially contribute to SCZ.

A comprehensive proteogenomic pipeline for neoantigen discovery to advance personalized cancer immunotherapy

The accurate identification and prioritization of antigenic peptides is crucial for the development of personalized cancer immunotherapies. Publicly available pipelines to predict clinical neoantigens do not allow direct integration of mass spectrometry immunopeptidomics data, which can uncover antigenic peptides derived from various canonical and noncanonical sources. To address this, we present an end-to-end clinical proteogenomic pipeline, called NeoDisc, that combines state-of-the-art publicly available and in-house software for immunopeptidomics, genomics and transcriptomics with in silico tools for the identification, prediction and prioritization of tumor-specific and immunogenic antigens from multiple sources, including neoantigens, viral antigens, high-confidence tumor-specific antigens and tumor-specific noncanonical antigens. We demonstrate the superiority of NeoDisc in accurately prioritizing immunogenic neoantigens over recent prioritization pipelines. We showcase the various features offered by NeoDisc that enable both rule-based and machine-learning approaches for personalized antigen discovery and neoantigen cancer vaccine design. Additionally, we demonstrate how NeoDisc's multiomics integration identifies defects in the cellular antigen presentation machinery, which influence the heterogeneous tumor antigenic landscape.

STARD7 could be an immunological and prognostic biomarker: from pan-cancer analysis to hepatocellular carcinoma validation

BACKGROUND

As the emergence of technologies such as sequencing and gene mapping, significant advancements have been made in understanding the landscape of tumors. However, the effective treatment of tumors continues to pose a tremendous challenge in clinical practice, which highlights the importance of predicting tumor markers and studying drug resistance mechanisms. The prognosis and differential expression of STARD7 in human pan-cancer were investigated by bioinformatic methods and experimental verification.

METHODS

The expression, diagnostic, and prognostic significance of the STARD7 gene were comprehensive analyzed using bioinformatics techniques. Furthermore, we validated our projected outcomes in liver cancer through experimental methodologies, including the use of qRT-PCR, CCK8 and transwell assays.

RESULTS

The STARD7 gene exhibits differential expression in 25 tumors, with high expression observed in 22 tumors. These distinct expression patterns within different tumor types are closely associated with poor prognosis and diagnosis. Furthermore, the STARD7 gene plays a role in regulating the tumor immune microenvironment. Methylation levels of STARD7 vary among 20 types of tumors and are correlated with survival outcomes. Furthermore, the experiment results demonstrated that STARD7 is highly expressed in hepatocellular carcinoma cells. Suppression of STARD7 significantly impedes the proliferation, migration, and invasion of HepG-2 and SMMC-7721 cells.

CONCLUSIONS

STARD7 has the potential to function as a crucial prognostic biomarker and exhibit correlation with tumor immunity in various types of human cancers. The implications of our findings extend to informing cancer immune-therapy and promoting the advancement of precision immune-oncology.

The History of Chromosomal Instability in Genome-Doubled Tumors

Tumors frequently display high chromosomal instability and contain multiple copies of genomic regions. Here, we describe Gain Route Identification and Timing In Cancer (GRITIC), a generic method for timing genomic gains leading to complex copy number states, using single-sample bulk whole-genome sequencing data. By applying GRITIC to 6,091 tumors, we found that non-parsimonious evolution is frequent in the formation of complex copy number states in genome-doubled tumors. We measured chromosomal instability before and after genome duplication in human tumors and found that late genome doubling was followed by an increase in the rate of copy number gain. Copy number gains often accumulate as punctuated bursts, commonly after genome doubling. We infer that genome duplications typically affect the landscape of copy number losses, while only minimally impacting copy number gains. In summary, GRITIC is a novel copy number gain timing framework that permits the analysis of copy number evolution in chromosomally unstable tumors. Significance: Complex genomic gains are associated with whole-genome duplications, which are frequent across tumors, span a large fraction of their genomes, and are linked to poorer outcomes. GRITIC infers when these gains occur during tumor development, which will help to identify the genetic events that drive tumor evolution. See related commentary by Taylor, p. 1766.

Topography of mutational signatures in non-small cell lung cancer: emerging concepts, clinical applications, and limitations

The genome of a cell is continuously battered by a plethora of exogenous and endogenous processes that can lead to damaged DNA. Repair mechanisms correct this damage most of the time, but failure to do so leaves mutations. Mutations do not occur in random manner, but rather typically follow a more or less specific pattern due to known or imputed mutational processes. Mutational signature analysis is the process by which the predominant mutational process can be inferred for a cancer and can be used in several contexts to study both the genesis of cancer and its response to therapy. Recent pan-cancer genomic efforts such as "The Cancer Genome Atlas" have identified numerous mutational signatures that can be categorized into single base substitutions, doublet base substitutions, or small insertions/deletions. Understanding these mutational signatures as they occur in non-small lung cancer could improve efforts at prevention, predict treatment response to personalized treatments, and guide the development of therapies targeting tumor evolution. For non-small cell lung cancer, several mutational signatures have been identified that correlate with exposures such as tobacco smoking and radon and can also reflect endogenous processes such as aging, APOBEC activity, and loss of mismatch repair. Herein, we provide an overview of the current knowledge of mutational signatures in non-small lung cancer.

A genetic basis for sex differences in Xp11 translocation renal cell carcinoma

Xp11 translocation renal cell carcinoma (tRCC) is a rare, female-predominant cancer driven by a fusion between the transcription factor binding to IGHM enhancer 3 (TFE3) gene on chromosome Xp11.2 and a partner gene on either chromosome X (chrX) or an autosome. It remains unknown what types of rearrangements underlie TFE3 fusions, whether fusions can arise from both the active (chrXa) and inactive X (chrXi) chromosomes, and whether TFE3 fusions from chrXi translocations account for the female predominance of tRCC. To address these questions, we performed haplotype-specific analyses of chrX rearrangements in tRCC whole genomes. We show that TFE3 fusions universally arise as reciprocal translocations and that oncogenic TFE3 fusions can arise from chrXi:autosomal translocations. Female-specific chrXi:autosomal translocations result in a 2:1 female-to-male ratio of TFE3 fusions involving autosomal partner genes and account for the female predominance of tRCC. Our results highlight how X chromosome genetics constrains somatic chrX alterations and underlies cancer sex differences.

The baseline hemoglobin level is a positive biomarker for immunotherapy response and can improve the predictability of tumor mutation burden for immunotherapy response in cancer

Purpose

Because only a subset of cancer patients can benefit from immunotherapy, identifying predictive biomarkers of ICI therapy response is of utmost importance.

Methods

We analyzed the association between hemoglobin (HGB) levels and clinical outcomes in 1,479 ICIs-treated patients across 16 cancer types. We explored the dose-dependent associations between HGB levels and survival and immunotherapy response using the spline-based cox regression analysis. Furthermore, we investigated the associations across subgroups of patients with different clinicopathological characteristics, treatment programs and cancer types using the bootstrap resampling method.

Results

HGB levels correlated positively with clinical outcomes in cancer patients receiving immunotherapy but not in those without immunotherapy. Moreover, this association was independent of other clinicopathological characteristics (such as sex, age, tumor stage and tumor mutation burden (TMB)), treatment program and cancer type. Also, this association was independent of the established biomarkers of immunotherapy response, including TMB, PD-L1 expression and microsatellite instability. The combination of TMB and HGB level are more powerful in predicting immunotherapy response than TMB alone. Multi-omics analysis showed that HGB levels correlated positively with antitumor immune signatures and negatively with tumor properties directing antitumor immunosuppression, such as homologous recombination defect, stemness and intratumor heterogeneity.

Conclusion

The HGB measure has the potential clinical value as a novel biomarker of immunotherapy response that is easily accessible from clinically routine examination. The combination of TMB and HGB measures have better predictive performance for immunotherapy response than TMB.

Prevalence of S-methyl-5'-thioadenosine Phosphorylase (MTAP) Deficiency in Human Cancer: A Tissue Microarray Study on 13,067 Tumors From 149 Different Tumor Types

Loss of S-methyl-5'-thioadenosine phosphorylase (MTAP) expression is a common event in cancer leading to a critical vulnerability of cancer cells towards anti-cancer drugs. Homozygous MTAP deletions result in a complete expression loss that can be detected by immunohistochemistry (IHC). In this study, a tissue microarray containing 17,078 samples from 149 different tumor entities was analyzed by IHC, and complete MTAP loss was validated by fluorescence in situ hybridization. MTAP loss was observed in 83 of 149 tumor categories, including neuroendocrine neoplasms (up to 80%), Hodgkin lymphoma (50.0%), mesothelioma (32.0% to 36.8%), gastro-intestinal adenocarcinoma (4.0% to 40.5%), urothelial neoplasms (10.5% to 36.7%), squamous cell carcinomas (up to 38%), and various types of sarcomas (up to 20%) and non-Hodgkin lymphomas (up to 14%). Homozygous MTAP deletion was found in 90% to 100% of cases with MTAP expression loss in most tumor categories. However, neuroendocrine tumors, Hodgkin lymphomas, and other lymphomas lacked MTAP deletions. MTAP deficiency was significantly linked to unfavorable tumor phenotype in selected tumor entities and the presence of PD-L1 expression on tumor cells, absence of PD-L1 expression on immune cells, and a low density of CD8 + lymphocytes. In summary, MTAP deficiency can occur in various tumor entities and is linked to unfavorable tumor phenotype and noninflamed tumor microenvironment, but is not always related to deletions. MTAP IHC is of considerable diagnostic value for the detection of neoplastic transformation in multiple different applications.

Whole-genome Mutational Analysis for Tumor-informed Detection of Circulating Tumor DNA in Patients with Urothelial Carcinoma

BACKGROUND AND OBJECTIVE

Circulating tumor DNA (ctDNA) can be used for sensitive detection of minimal residual disease (MRD). However, the probability of detecting ctDNA in settings of low tumor burden is limited by the number of mutations analyzed and the plasma volume available. We used a whole-genome sequencing (WGS) approach for ctDNA detection in patients with urothelial carcinoma.

METHODS

We used a tumor-informed WGS approach for ctDNA-based detection of MRD and evaluation of treatment responses. We analyzed 916 longitudinally collected plasma samples from 112 patients with localized muscle-invasive bladder cancer who received neoadjuvant chemotherapy (NAC) before radical cystectomy. Recurrence-free survival (primary endpoint), overall survival, and ctDNA dynamics during NAC were assessed.

KEY FINDINGS AND LIMITATIONS

We found that WGS-based ctDNA detection is prognostic for patient outcomes with a median lead time of 131 d over radiographic imaging. WGS-based ctDNA assessment after radical cystectomy identified recurrence with sensitivity of 91% and specificity of 92%. In addition, genomic characterization of post-treatment plasma samples with a high ctDNA level revealed acquisition of platinum therapy-associated mutational signatures and copy number variations not present in the primary tumors. The sequencing depth is a limitation for studying tumor evolution.

CONCLUSIONS AND CLINICAL IMPLICATIONS

Our results support the use of WGS for ultrasensitive ctDNA detection and highlight the possibility of plasma-based tracking of tumor evolution. WGS-based ctDNA detection represents a promising option for clinical use owing to the low volume of plasma needed and the ease of performing WGS, eliminating the need for personalized assay design.

Oncogenic Control of Metabolism

A cell committed to proliferation must reshape its metabolism to enable robust yet balanced production of building blocks for the assembly of proteins, lipids, nucleic acids, and other macromolecules, from which two functional daughter cells can be produced. The metabolic remodeling associated with proliferation is orchestrated by a number of pro-proliferative signaling nodes, which include phosphatidylinositol-3 kinase (PI3K), the RAS family of small GTPases, and transcription factor c-myc In metazoan cells, these signals are activated in a paracrine manner via growth factor-mediated activation of receptor (or receptor-associated) tyrosine kinases. Such stimuli are limited in duration and therefore allow the metabolism of target cells to return to the resting state once the proliferation demands have been satisfied. Cancer cells acquire activating genetic alterations within common pro-proliferative signaling nodes. These alterations lock cellular nutrient uptake and utilization into a perpetual progrowth state, leading to the aberrant accumulation and spread of cancer cells.

Fluorescence in situ hybridization-negative intra-articular myxoid liposarcoma with complex rearrangements involving EWSR1::DDIT3 detected using nanopore sequencing

Myxoid liposarcoma (MLPS) is a rare sarcoma, typically arising in deep soft tissues during the fourth to fifth decades of life. Histologically, MLPS is composed of uniform oval cells within a background of myxoid stroma and chicken-wire capillaries. Genetically, MLPS is characterized by the FUS/EWSR1::DDIT3 fusion gene, which generally results from balanced interchromosomal translocation and is detectable via DDIT3 break-apart fluorescence in situ hybridization (FISH). Here, we report an unusual intra-articular MLPS case, negative for DDIT3 break-apart FISH but positive for EWSR1::DDIT3. An 18-year-old female was referred to our hospital complaining of an intra-articular mass in the right knee joint. Histologically, the tumor was mainly composed of mature adipocytes, brown fat-like cells, and lipoblasts. Nanopore sequencing detected DNA rearrangements between EWSR1 and DDIT3 and clustered complex rearrangements involving multiple chromosomes, suggesting chromoplexy. Methylation classification using random forest, t-distributed stochastic neighbor embedding, and unsupervised hierarchical clustering correctly classified the tumor as MLPS. The copy number was almost flat. The TERT promoter C-124T was also detected. This report highlights, for the first time, the potential value of a fast and low-cost nanopore sequencer for diagnosing sarcomas.