Pan-cancer analysis of whole genomes

Comparison of germline and somatic structural variants in cancers reveal systematic differences in variant generating and selection processes

Although several recent studies have characterized structural variants (SVs) in germline and cancer genomes, the features of SVs in these different contexts have not been directly compared. We examined similarities and differences between 2 million germline and 115 thousand tumor SVs from a cohort of 963 patients from The Cancer Genome Atlas (TCGA). We found significant differences in features related to their genomic sequences and localization that suggest differences between SV-generating processes and selective pressures. For example, we found that transposon-mediated processes shape germline much more than somatic SVs, while somatic SVs more frequently show features characteristic of chromoanagenesis. These differences were extensive enough to enable us to develop a classifier - "the great GaTSV" - that accurately distinguishes between germline and cancer SVs in tumor samples that lack a matched normal sample.

Tracing unknown tumor origins with a biological-pathway-based transformer model

Cancer of unknown primary (CUP) represents metastatic cancer where the primary site remains unidentified despite standard diagnostic procedures. To determine the tumor origin in such cases, we developed BPformer, a deep learning method integrating the transformer model with prior knowledge of biological pathways. Trained on transcriptomes from 10,410 primary tumors across 32 cancer types, BPformer achieved remarkable accuracy rates of 94%, 92%, and 89% in primary tumors and primary and metastatic sites of metastatic tumors, respectively, surpassing existing methods. Additionally, BPformer was validated in a retrospective study, demonstrating consistency with tumor sites diagnosed through immunohistochemistry and histopathology. Furthermore, BPformer was able to rank pathways based on their contribution to tumor origin identification, which helped to classify oncogenic signaling pathways into those that are highly conservative among different cancers versus those that are highly variable depending on their origins.

Oncogenic and immunological role of EDIL3 in human tumours: From pan-cancer analysis to validation in gastric cancer

Background

Epidermal growth factor-like repeats and discoidin I-like domains 3 (EDIL3) is a secreted extracellular matrix protein implicated in diverse physiological and pathological processes including embryonic development, angiogenesis, and anti-inflammatory responses. Recent reports have indicated that EDIL3 play critical roles in carcinogenesis and progression of many cancers. Herein, we performed a pan-cancer investigation to study the potential functions of EDIL3 in various cancers and experimentally validate its function in gastric cancer (GC).

Methods

We analysed EDIL3 expression profiles in different tumours using The Cancer Genome Atlas database. The Kaplan-Meier Plotter was used to investigate the prognostic value of EDIL3, while receiver operating characteristic curve was performed to analyze its diagnostic efficacy. Several bioinformatics tools were used to study the association between EDIL3 and promoter methylation, gene enrichment analysis, immune infiltration, immune-related genes, and drug sensitivity. Molecular biology experiments were conducted to validate the tumorigenic effects of EDIL3.

Results

EDIL3 is variably expressed in different cancers and is closely associated with clinical outcomes. An inverse correlation between EDIL3 and DNA methylation has been observed in 13 cancers. Enrichment analysis indicated that EDIL3 is correlated with many cellular pathways such as extracellular matrix receptor interactions and focal adhesion. EDIL3 was tightly associated with immune infiltration and immune checkpoints. EDIL3 knockdown can promote GC calls apoptosis while preventing proliferation, migration, and invasion in vitro.

Conclusion

EDIL3 is a promising prognostic, diagnostic, and immunological biomarker in various cancers, which could be applied as a new target for cancer therapy.

Identification of nonsense-mediated decay inhibitors that alter the tumor immune landscape

Despite exciting developments in cancer immunotherapy, its broad application is limited by the paucity of targetable antigens on the tumor cell surface. As an intrinsic cellular pathway, nonsense-mediated decay (NMD) conceals neoantigens through the destruction of the RNA products from genes harboring truncating mutations. We developed and conducted a high throughput screen, based on the ratiometric analysis of transcripts, to identify critical mediators of NMD. This screen implicated disruption of kinase SMG1's phosphorylation of UPF1 as a potential disruptor of NMD. This led us to design a novel SMG1 inhibitor, KVS0001, that elevates the expression of transcripts and proteins resulting from truncating mutations in vivo and in vitro . Most importantly, KVS0001 concomitantly increased the presentation of immune-targetable HLA class I-associated peptides from NMD-downregulated proteins on the surface of cancer cells. KVS0001 provides new opportunities for studying NMD and the diseases in which NMD plays a role, including cancer and inherited diseases.

One Sentence Summary

Disruption of the nonsense-mediated decay pathway with a newly developed SMG1 inhibitor with in-vivo activity increases the expression of T-cell targetable cancer neoantigens resulting from truncating mutations.

Homologous recombination proficient subtypes of high-grade serous ovarian cancer: treatment options for a poor prognosis group

Approximately 50% of tubo-ovarian high-grade serous carcinomas (HGSCs) have functional homologous recombination-mediated (HR) DNA repair, so-called HR-proficient tumors, which are often associated with primary platinum resistance (relapse within six months after completion of first-line therapy), minimal benefit from poly(ADP-ribose) polymerase (PARP) inhibitors, and shorter survival. HR-proficient tumors comprise multiple molecular subtypes including cases with CCNE1 amplification, AKT2 amplification or CDK12 alteration, and are often characterized as "cold" tumors with fewer infiltrating lymphocytes and decreased expression of PD-1/PD-L1. Several new treatment approaches aim to manipulate these negative prognostic features and render HR-proficient tumors more susceptible to treatment. Alterations in multiple different molecules and pathways in the DNA damage response are driving new drug development to target HR-proficient cancer cells, such as inhibitors of the CDK or P13K/AKT pathways, as well as ATR inhibitors. Treatment combinations with chemotherapy or PARP inhibitors and agents targeting DNA replication stress have shown promising preclinical and clinical results. New approaches in immunotherapy are also being explored, including vaccines or antibody drug conjugates. Many approaches are still in the early stages of development and further clinical trials will determine their clinical relevance. There is a need to include HR-proficient tumors in ovarian cancer trials and to analyze them in a more targeted manner to provide further evidence for their specific therapy, as this will be crucial in improving the overall prognosis of HGSC and ovarian cancer in general.

AmplificationTimeR: an R package for timing sequential amplification events

MOTIVATION

Few methods exist for timing individual amplification events in regions of focal amplification. Current methods are also limited in the copy number states that they are able to time. Here we introduce AmplificationTimeR, a method for timing higher level copy number gains and inferring the most parsimonious order of events for regions that have undergone both single gains and whole genome duplication. Our method is an extension of established approaches for timing genomic gains.

RESULTS

We can time more copy number states, and in states covered by other methods our results are comparable to previously published methods.

AVAILABILITY AND IMPLEMENTATION

AmplificationTimer is freely available as an R package hosted at https://github.com/Wedge-lab/AmplificationTimeR.

Origins of Second Malignancies in Children and Mutational Footprint of Chemotherapy in Normal Tissues

Pediatric cancers are rare diseases, and children without known germline predisposing conditions who develop a second malignancy during developmental ages are extremely rare. We present four such clinical cases and, through whole-genome and error-correcting ultra-deep duplex sequencing of tumor and normal samples, we explored the origin of the second malignancy in four children, uncovering different routes of development. The exposure to cytotoxic therapies was linked to the emergence of a secondary acute myeloid leukemia. A common somatic mutation acquired early during embryonic development was the driver of two solid malignancies in another child. In two cases, the two tumors developed from completely independent clones diverging during embryogenesis. Importantly, we demonstrate that platinum-based therapies contributed at least one order of magnitude more mutations per day of exposure than aging to normal tissues in these children.

SIGNIFICANCE

Using whole-genome and error-correcting ultra-deep duplex sequencing, we uncover different origins for second neoplasms in four children. We also uncover the presence of platinum-related mutations across 10 normal tissues of exposed individuals, highlighting the impact that the use of cytotoxic therapies may have on cancer survivors. See related commentary by Pacyna and Nangalia, p. 900. This article is featured in Selected Articles from This Issue, p. 897.

MCDHGN: heterogeneous network-based cancer driver gene prediction and interpretability analysis

MOTIVATION

Accurately predicting the driver genes of cancer is of great significance for carcinogenesis progress research and cancer treatment. In recent years, more and more deep-learning-based methods have been used for predicting cancer driver genes. However, deep-learning algorithms often have black box properties and cannot interpret the output results. Here, we propose a novel cancer driver gene mining method based on heterogeneous network meta-paths (MCDHGN), which uses meta-path aggregation to enhance the interpretability of predictions.

RESULTS

MCDHGN constructs a heterogeneous network by using several types of multi-omics data that are biologically linked to genes. And the differential probabilities of SNV, DNA methylation, and gene expression data between cancerous tissues and normal tissues are extracted as initial features of genes. Nine meta-paths are manually selected, and the representation vectors obtained by aggregating information within and across meta-path nodes are used as new features for subsequent classification and prediction tasks. By comparing with eight homogeneous and heterogeneous network models on two pan-cancer datasets, MCDHGN has better performance on AUC and AUPR values. Additionally, MCDHGN provides interpretability of predicted cancer driver genes through the varying weights of biologically meaningful meta-paths.

AVAILABILITY AND IMPLEMENTATION

https://github.com/1160300611/MCDHGN.

Deep-Learning Model for Tumor-Type Prediction Using Targeted Clinical Genomic Sequencing Data

Tumor type guides clinical treatment decisions in cancer, but histology-based diagnosis remains challenging. Genomic alterations are highly diagnostic of tumor type, and tumor-type classifiers trained on genomic features have been explored, but the most accurate methods are not clinically feasible, relying on features derived from whole-genome sequencing (WGS), or predicting across limited cancer types. We use genomic features from a data set of 39,787 solid tumors sequenced using a clinically targeted cancer gene panel to develop Genome-Derived-Diagnosis Ensemble (GDD-ENS): a hyperparameter ensemble for classifying tumor type using deep neural networks. GDD-ENS achieves 93% accuracy for high-confidence predictions across 38 cancer types, rivaling the performance of WGS-based methods. GDD-ENS can also guide diagnoses of rare type and cancers of unknown primary and incorporate patient-specific clinical information for improved predictions. Overall, integrating GDD-ENS into prospective clinical sequencing workflows could provide clinically relevant tumor-type predictions to guide treatment decisions in real time.

SIGNIFICANCE

We describe a highly accurate tumor-type prediction model, designed specifically for clinical implementation. Our model relies only on widely used cancer gene panel sequencing data, predicts across 38 distinct cancer types, and supports integration of patient-specific nongenomic information for enhanced decision support in challenging diagnostic situations. See related commentary by Garg, p. 906. This article is featured in Selected Articles from This Issue, p. 897.

Phenotypic noise and plasticity in cancer evolution

Non-genetic alterations can produce changes in a cell's phenotype. In cancer, these phenomena can influence a cell's fitness by conferring access to heritable, beneficial phenotypes. Herein, we argue that current discussions of 'phenotypic plasticity' in cancer evolution ignore a salient feature of the original definition: namely, that it occurs in response to an environmental change. We suggest 'phenotypic noise' be used to distinguish non-genetic changes in phenotype that occur independently from the environment. We discuss the conceptual and methodological techniques used to identify these phenomena during cancer evolution. We propose that the distinction will guide efforts to define mechanisms of phenotype change, accelerate translational work to manipulate phenotypes through treatment, and, ultimately, improve patient outcomes.

Microbial nanotechnology for agriculture, food, and environmental sustainability: Current status and future perspective

The field of nanotechnology has the mysterious capacity to reform every subject it touches. Nanotechnology advancements have already altered a variety of scientific and industrial fields. Nanoparticles (NPs) with sizes ranging from 1 to 100 nm (nm) are of great scientific and commercial interest. Their functions and characteristics differ significantly from those of bulk metal. Commercial quantities of NPs are synthesized using chemical or physical methods. The use of the physical and chemical approaches remained popular for many years; however, the recognition of their hazardous effects on human well-being and conditions influenced serious world perspectives for the researchers. There is a growing need in this field for simple, non-toxic, clean, and environmentally safe nanoparticle production methods to reduce environmental impact and waste and increase energy productivity. Microbial nanotechnology is relatively a new field. Using various microorganisms, a wide range of nanoparticles with well-defined chemical composition, morphology, and size have been synthesized, and their applications in a wide range of cutting-edge technological areas have been investigated. Green synthesis of the nanoparticles is cost-efficient and requires low maintenance. The present review highlights the synthesis of the nanoparticles by different microbes, their characterization, and their biotechnological potential. It further deals with the applications in biomedical, food, and textile industries as well as its role in biosensing, waste recycling, and biofuel production.

Developmental origins shape the paediatric cancer genome

In the past two decades, technological advances have brought unprecedented insights into the paediatric cancer genome revealing characteristics distinct from those of adult cancer. Originating from developing tissues, paediatric cancers generally have low mutation burden and are driven by variants that disrupt the transcriptional activity, chromatin state, non-coding cis-regulatory regions and other biological functions. Within each tumour, there are multiple populations of cells with varying states, and the lineages of some can be tracked to their fetal origins. Genome-wide genetic screening has identified vulnerabilities associated with both the cell of origin and transcription deregulation in paediatric cancer, which have become a valuable resource for designing new therapeutic approaches including those for small molecules, immunotherapy and targeted protein degradation. In this Review, we present recent findings on these facets of paediatric cancer from a pan-cancer perspective and provide an outlook on future investigations.

Transactivation of Met signaling by oncogenic Gnaq drives the evolution of melanoma in Hgf-Cdk4 mice

Recent pan-cancer genomic analyses have identified numerous oncogenic driver mutations that occur in a cell-type and tissue-specific distribution. For example, oncogenic mutations in Braf and Nras genes arise predominantly in melanocytic neoplasms of the epidermis, while oncogenic mutations in Gnaq/11 genes arise mostly in melanocytic lesions of the dermis or the uvea. The mechanisms promoting cell-type and tissue-specific oncogenic events currently remain poorly understood. Here, we report that Gnaq/11 hotspot mutations occur as early oncogenic drivers during the evolution of primary melanomas in Hgf-Cdk4 mice. Additional single base substitutions in the Trp53 gene and structural chromosomal aberrations favoring amplifications of the chromosomal region containing the Met receptor gene accumulate during serial tumor transplantation and in cell lines established in vitro. Mechanistically, we found that the GnaqQ209L mutation transactivates the Met receptor. Overexpression of oncogenic GnaqQ209L in the immortalized melanocyte cell line promoted in vivo growth that was enhanced by transgenic Hgf expression in the tumor microenvironment. This cross-signaling mechanism explains the selection of oncogenic Gnaq/11 in primary Hgf-Cdk4 melanomas and provides an example of how oncogenic driver mutations, intracellular signaling cascades, and microenvironmental cues cooperate to drive cancer development in a tissue-specific fashion.

Reconstructing phylogenetic trees from genome-wide somatic mutations in clonal samples

Phylogenetic trees are a powerful means to display the evolutionary history of species, pathogens and, more recently, individual cells of the human body. Whole-genome sequencing of laser capture microdissections or expanded stem cells has allowed the discovery of somatic mutations in clones, which can be used as natural barcodes to reconstruct the developmental history of individual cells. Here we describe Sequoia, our pipeline to reconstruct lineage trees from clones of normal cells. Candidate somatic mutations are called against the human reference genome and filtered to exclude germline mutations and artifactual variants. These filtered somatic mutations form the basis for phylogeny reconstruction using a maximum parsimony framework. Lastly, we use a maximum likelihood framework to explicitly map mutations to branches in the phylogenetic tree. The resulting phylogenies can then serve as a basis for many subsequent analyses, including investigating embryonic development, tissue dynamics in health and disease, and mutational signatures. Sequoia can be readily applied to any clonal somatic mutation dataset, including single-cell DNA sequencing datasets, using the commands and scripts provided. Moreover, Sequoia is highly flexible and can be easily customized. Typically, the runtime of the core script ranges from minutes to an hour for datasets with a moderate number (50,000-150,000) of variants. Competent bioinformatic skills, including in-depth knowledge of the R programming language, are required. A high-performance computing cluster (one that is capable of running mutation-calling algorithms and other aspects of the analysis at scale) is also required, especially if handling large datasets.

CRISPR-Cas9 for selective targeting of somatic mutations in pancreatic cancers

Somatic mutations are desirable targets for selective elimination of cancer, yet most are found within noncoding regions. We have adapted the CRISPR-Cas9 gene editing tool as a novel, cancer-specific killing strategy by targeting the subset of somatic mutations that create protospacer adjacent motifs (PAMs), which have evolutionally allowed bacterial cells to distinguish between self and non-self DNA for Cas9-induced double strand breaks. Whole genome sequencing (WGS) of paired tumor minus normal (T-N) samples from three pancreatic cancer patients (Panc480, Panc504, and Panc1002) showed an average of 417 somatic PAMs per tumor produced from single base substitutions. Further analyses of 591 paired T-N samples from The International Cancer Genome Consortium found medians of ∼455 somatic PAMs per tumor in pancreatic, ∼2800 in lung, and ∼3200 in esophageal cancer cohorts. Finally, we demonstrated 69-99% selective cell death of three targeted pancreatic cancer cell lines using 4-9 sgRNAs designed using the somatic PAM discovery approach. We also showed no off-target activity from these tumor-specific sgRNAs in either the patient's normal cells or an irrelevant cancer using WGS. This study demonstrates the potential of CRISPR-Cas9 as a novel and selective anti-cancer strategy, and supports the genetic targeting of adult cancers.

Unveiling HOXB7 as a novel diagnostic and prognostic biomarker through pan-cancer computer screening

We attempted to investigate the role of HOXB7 in tumor progression and evolution by means of an extensive computer screening analysis of various cancer types. We performed univariate Cox regression and Kaplan-Meier survival analyses to assess the impact of HOXB7 on overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) in different types of cancer. Furthermore, we examined the relationship between HOXB7 and several clinical features: tumor microenvironment, immune regulatory genes, immune checkpoints, tumor mutational burden (TMB), and microsatellite instability (MSI). We performed gene set enrichment analysis to gain deeper insights into the potential molecular mechanisms of HOXB7, and validated our findings through functional assays in cells, including methyl thiazolyl tetrazolium cytotoxicity and Transwell invasion assays. HOXB7 expression was associated with different clinical characteristics in numerous malignancies. Higher HOXB7 expression was associated with worse OS, DSS, and PFI in some cancer types. In particular, HOXB7 expression was favorably associated with immune cell infiltration, immune regulatory genes, immunological checkpoints, TMB, and MSI in malignancies. Furthermore, we identified a strong link between copper death-associated gene expression and HOXB7 expression. According to the findings of this study, HOXB7 might serve as an appealing focus for tumor diagnosis and immunotherapy and a prospective indicator of prognosis.

Patterns of structural variants within TP53 introns and relocation of the TP53 promoter: a commentary†

Gene disruption from double-strand DNA breaks within introns is a mechanism of inactivating the tumor suppressor TP53. This occurs more frequently in osteosarcoma and biliary adenocarcinoma compared with other cancer types. The patterns of intron breakpoints within TP53 do not correlate with prevalence, intron length, or overall genome-wide levels of rearrangements. Therefore, these breakpoints appear to be selected for reasons other than to disrupt TP53. A recent article published by Saba et al in The Journal of Pathology illustrates a benefit to having breakpoints within intron 1 using high-quality matched genomic and transcriptomic osteosarcoma sequencing data as well as in vitro validation. The authors describe how the rearrangement results in relocation of the TP53 promoter region to regions upstream of genes that encode members of cartilage, growth plate development, osteoclast formation, and other TP53-related pathways. The upregulation of these genes by the TP53 promoter are gain-of-function events that are likely to promote tumor development and growth. Therefore, this article presents a potential new paradigm in which a single mutation would result in both the loss of a tumor suppressor and the gain of an oncogenic program. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Pan-Cancer Molecular Biomarkers: A Paradigm Shift in Diagnostic Pathology

The rapid adoption of next-generation sequencing in clinical oncology has enabled the detection of molecular biomarkers shared between multiple tumor types. These pan-cancer biomarkers include sequence-altering mutations, copy number changes, gene rearrangements, and mutational signatures and have been demonstrated to predict response to targeted therapy. This article reviews issues surrounding current and emerging pan-cancer molecular biomarkers in clinical oncology: technological advances that enable the broad detection of cancer mutations across hundreds of genes, the spectrum of driver and passenger mutations derived from human cancer genomes, and implications for patient care now and in the near future.

A pipeline for the development and analysis of extracellular vesicle-based transcriptomic biomarkers in molecular diagnostics

Extracellular vesicles are shed by every cell type and can be found in any biofluid. They contain different molecules that can be utilized as biomarkers, including several RNA species which they protect from degradation. Here, we present a pipeline for the development and analysis of extracellular vesicle-associated transcriptomic biomarkers that our group has successfully applied multiple times. We highlight the key steps of the pipeline and give particular emphasis to the necessary quality control checkpoints, which are linked to numerous available guidelines that should be considered along the workflow. Our pipeline starts with patient recruitment and continues with blood sampling and processing. The purification and characterization of extracellular vesicles is explained in detail, as well as the isolation and quality control of extracellular vesicle-associated RNA. We point out the possible pitfalls during library preparation and RNA sequencing and present multiple bioinformatic tools to pinpoint biomarker signature candidates from the sequencing data. Finally, considerations and pitfalls during the validation of the biomarker signature using RT-qPCR will be elaborated.

Genomic characterization and risk stratification of esophageal squamous dysplasia

Objectives

The majority of esophageal squamous dysplasia (ESD) patients progress slowly, while a subset of patients can undergo recurrence rapidly or progress to invasive cancer even after proper treatment. However, the molecular mechanisms underlying these clinical observations are still largely unknown.

Methods

By sequencing the genomic data of 160 clinical samples from 49 tumor-free ESD patients and 88 esophageal squamous cell carcinoma (ESCC) patients, we demonstrated lower somatic mutation and copy number alteration (CNA) burden in ESD compared with ESCC.

Results

Cross-species screening and functional assays identified ACSM5 as a novel driver gene for ESD progression. Furthermore, we revealed that miR-4292 promoted ESD progression and could serve as a non-invasive diagnostic marker for ESD.

Conclusions

These findings largely expanded our understanding of ESD genetics and tumorigenesis, which possessed promising significance for improving early diagnosis, reducing overtreatment, and identifying high-risk ESD patients.

Cell-type-specific consequences of mosaic structural variants in hematopoietic stem and progenitor cells

The functional impact and cellular context of mosaic structural variants (mSVs) in normal tissues is understudied. Utilizing Strand-seq, we sequenced 1,133 single-cell genomes from 19 human donors of increasing age, and discovered the heterogeneous mSV landscapes of hematopoietic stem and progenitor cells. While mSVs are continuously acquired throughout life, expanded subclones in our cohort are confined to individuals >60. Cells already harboring mSVs are more likely to acquire additional somatic structural variants, including megabase-scale segmental aneuploidies. Capitalizing on comprehensive single-cell micrococcal nuclease digestion with sequencing reference data, we conducted high-resolution cell-typing for eight hematopoietic stem and progenitor cells. Clonally expanded mSVs disrupt normal cellular function by dysregulating diverse cellular pathways, and enriching for myeloid progenitors. Our findings underscore the contribution of mSVs to the cellular and molecular phenotypes associated with the aging hematopoietic system, and establish a foundation for deciphering the molecular links between mSVs, aging and disease susceptibility in normal tissues.

Scalable and efficient DNA sequencing analysis on different compute infrastructures aiding variant discovery

DNA variation analysis has become indispensable in many aspects of modern biomedicine, most prominently in the comparison of normal and tumor samples. Thousands of samples are collected in local sequencing efforts and public databases requiring highly scalable, portable, and automated workflows for streamlined processing. Here, we present nf-core/sarek 3, a well-established, comprehensive variant calling and annotation pipeline for germline and somatic samples. It is suitable for any genome with a known reference. We present a full rewrite of the original pipeline showing a significant reduction of storage requirements by using the CRAM format and runtime by increasing intra-sample parallelization. Both are leading to a 70% cost reduction in commercial clouds enabling users to do large-scale and cross-platform data analysis while keeping costs and CO2 emissions low. The code is available at https://nf-co.re/sarek.

Germline-mediated immunoediting sculpts breast cancer subtypes and metastatic proclivity

Tumors with the same diagnosis can have different molecular profiles and response to treatment. It remains unclear when and why these differences arise. Somatic genomic aberrations occur within the context of a highly variable germline genome. Interrogating 5870 breast cancer lesions, we demonstrated that germline-derived epitopes in recurrently amplified genes influence somatic evolution by mediating immunoediting. Individuals with a high germline-epitope burden in human epidermal growth factor receptor 2 (HER2/ERBB2) are less likely to develop HER2-positive breast cancer compared with other subtypes. The same holds true for recurrent amplicons defining three aggressive estrogen receptor (ER)-positive subgroups. Tumors that overcome such immune-mediated negative selection are more aggressive and demonstrate an "immune cold" phenotype. These data show that the germline genome plays a role in dictating somatic evolution.

Aging represses lung tumorigenesis and alters tumor suppression

Most cancers are diagnosed in persons over the age of sixty, but little is known about how age impacts tumorigenesis. While aging is accompanied by mutation accumulation - widely understood to contribute to cancer risk - it is also associated with numerous other cellular and molecular changes likely to impact tumorigenesis. Moreover, cancer incidence decreases in the oldest part of the population, suggesting that very old age may reduce carcinogenesis. Here we show that aging represses tumor initiation and growth in genetically engineered mouse models of human lung cancer. Moreover, aging dampens the impact of inactivating many, but not all, tumor suppressor genes with the impact of inactivating PTEN, a negative regulator of the PI3K/AKT pathway, weakened to a disproportionate extent. Single-cell transcriptomic analysis revealed that neoplastic cells from tumors in old mice retain many age-related transcriptomic changes, showing that age has an enduring impact that persists through oncogenic transformation. Furthermore, the consequences of PTEN inactivation were strikingly age-dependent, with PTEN deficiency reducing signatures of aging in cancer cells and the tumor microenvironment. Our findings suggest that the relationship between age and lung cancer incidence may reflect an integration of the competing effects of driver mutation accumulation and tumor suppressive effects of aging.

Gene alterations in the nuclear transport receptor superfamily: A study of head and neck cancer

In cancer cells, the nuclear transport system is often disrupted, leading to abnormal localization of nuclear proteins and altered gene expression. This disruption can arise from various mechanisms such as mutations in genes that regulate nuclear transport, altered expression of transport proteins, and changes in nuclear envelope structure. Oncogenic protein build-up in the nucleus due to the disturbance in nuclear transport can also boost tumor growth and cell proliferation. In this study, we performed bioinformatic analyses of 23 key nuclear transport receptors using genomic and transcriptomic data from pancancer and head and neck squamous cell carcinoma (HNSCC) datasets from The Cancer Genome Atlas (TCGA) and Cancer Cell Line Encyclopedia and found that the total alteration frequency of 23 nuclear transport receptors in 2691 samples of the PCAWG Consortium was 42.1% and a high levels of genetic alterations was significantly associated with poor overall survival. Amplification was the most common type of genetic alterations, and results in the overexpression of nuclear transport receptors in HNSCC compared to normal tissues. Furthermore, our study revealed that seven out of eight cell cycle genes (CDK1, CDK2, CDK4, CDK6, CCNA1, CCNB1, and CCNE2) were significantly and positively correlated with nuclear transport receptor genes in TCGA pancancer and CCLE datasets. Additionally, functional enrichment analysis showed that nuclear transport receptor genes were mainly enriched in the adhesion junction, cell cycle, ERBB, MAPK, MTOR and WNT signaling pathways.

ACTL6A: unraveling its prognostic impact and paving the way for targeted therapeutics in carcinogenesis

Introduction: Increased Actin-like 6A (ACTL6A) expression is associated with various cancers, but its comprehensive investigation across different malignancies is lacking. We aimed to analyze ACTL6A as a potential oncogene and therapeutic target using bioinformatics tools. Methods: We comprehensively analyzed ACTL6A expression profiles across human malignancies, focusing on correlations with tumor grade, stage, metastasis, and patient survival. Genetic alterations were examined, and the epigenetic landscape of ACTL6A was assessed using rigorous methods. The impact of ACTL6A on immune cell infiltration in the tumor microenvironment was evaluated, along with molecular docking studies and machine learning models. Results: Our analysis revealed elevated ACTL6A expression in various tumors, correlating with poor prognostic indicators such as tumor grade, stage, metastasis, and patient survival. Genetic mutations and epigenetic modifications were identified, along with associations with immune cell infiltration and key cellular pathways. Machine learning models demonstrated ACTL6A's potential for cancer detection. Discussion: ACTL6A emerges as a promising diagnostic and therapeutic target in cancer, with implications for prognosis and therapy. Our study provides comprehensive insights into its carcinogenic actions, highlighting its potential as both a prognostic indicator and a target for anti-cancer therapy. This integrative approach enhances our understanding of ACTL6A's role in cancer pathogenesis and treatment.

Experimental Validation and Multi-omics Analysis Identified ARPC1A as a Novel Oncogene and Potential Therapeutic Target in Glioblastoma

Actin-related protein 2/3 complex subunit 1A (ARPC1A) is implicated in several cancers due to its critical role in regulating actin polymerization. However, the exact mechanism of ARPC1A in cancer remains unclear. This study aims to investigate the biological role of ARPC1A in various cancers and the regulatory role of ARPC1A in glioblastoma multiforme (GBM). We analyzed the expression differences, prognostic value, mutations, immune infiltration, immune microenvironment, and single-cell level correlations of ARPC1A in various cancers. Furthermore, we employed gene set enrichment analysis (GSEA) and functional experiments to elucidate the regulatory mechanisms of ARPC1A on GBM. Importantly, we assessed the role of ARPC1A in temozolomide (TMZ) resistance of GBM. ARPC1A expression was up-regulated in most cancer tissues and was associated with poorer prognosis. Genomic mutation analysis revealed that the predominant type of ARPC1A mutation in tumors was amplification. ARPC1A expression was negatively correlated with B-cell and immune scores in most tumors. Both GSEA and single-cell sequencing have revealed that ARPC1A promotes tumor proliferation and epithelial-mesenchymal transition. In vitro experiments confirmed that ARPC1A knockdown inhibited the proliferation and metastatic ability of GBM cells. Notably, silencing ARPC1A reduced TMZ resistance in GBM cells. This study highlights the prognostic value of ARPC1A in various tumors and its potential for application in immunotherapy. Meanwhile, the modulation of GBM malignant behavior and TMZ resistance by ARPC1A provides a new approach for personalized and precise treatment of GBM.

Efficient and multiplexed somatic genome editing with Cas12a mice

Somatic genome editing in mouse models has increased our understanding of the in vivo effects of genetic alterations in areas ranging from neuroscience to cancer biology and beyond. However, existing models are limited in their ability to create multiple targeted edits. Thus, our understanding of the complex genetic interactions that underlie development, homeostasis, and disease remains incomplete. Cas12a is an RNA-guided endonuclease with unique attributes that enable simple targeting of multiple genes with crRNA arrays containing tandem guides. To accelerate and expand the generation of complex genotypes in somatic cells, we generated transgenic mice with Cre-regulated and constitutive expression of enhanced Acidaminococcus sp. Cas12a (enAsCas12a). In these mice, enAsCas12a-mediated somatic genome editing robustly generated compound genotypes, as exemplified by the initiation of diverse cancer types driven by homozygous inactivation of trios of tumor suppressor genes. We further integrated these modular crRNA arrays with clonal barcoding to quantify the size and number of tumors with each array, as well as the efficiency of each crRNA. These Cas12a alleles will enable the rapid generation of disease models and broadly facilitate the high-throughput investigation of coincident genomic alterations in somatic cells in vivo .

Age-specific induction of mutant p53 drives clonal hematopoiesis and acute myeloid leukemia in adult mice

The investigation of the mechanisms behind p53 mutations in acute myeloid leukemia (AML) has been limited by the lack of suitable mouse models, which historically have resulted in lymphoma rather than leukemia. This study introduces two new AML mouse models. One model induces mutant p53 and Mdm2 haploinsufficiency in early development, showing the role of Mdm2 in myeloid-biased hematopoiesis and AML predisposition, independent of p53. The second model mimics clonal hematopoiesis by inducing mutant p53 in adult hematopoietic stem cells, demonstrating that the timing of p53 mutation determines AML vs. lymphoma development. In this context, age-related changes in hematopoietic stem cells (HSCs) collaborate with mutant p53 to predispose toward myeloid transformation rather than lymphoma development. Our study unveils new insights into the cooperative impact of HSC age, Trp53 mutations, and Mdm2 haploinsufficiency on clonal hematopoiesis and the development of myeloid malignancies.

HATCHet2: clone- and haplotype-specific copy number inference from bulk tumor sequencing data

Bulk DNA sequencing of multiple samples from the same tumor is becoming common, yet most methods to infer copy-number aberrations (CNAs) from this data analyze individual samples independently. We introduce HATCHet2, an algorithm to identify haplotype- and clone-specific CNAs simultaneously from multiple bulk samples. HATCHet2 extends the earlier HATCHet method by improving identification of focal CNAs and introducing a novel statistic, the minor haplotype B-allele frequency (mhBAF), that enables identification of mirrored-subclonal CNAs. We demonstrate HATCHet2's improved accuracy using simulations and a single-cell sequencing dataset. HATCHet2 analysis of 10 prostate cancer patients reveals previously unreported mirrored-subclonal CNAs affecting cancer genes.

Previously reported CCDC26 risk variant and novel germline variants in GALNT13, AR, and MYO10 associated with familial glioma in Finland

Predisposing factors underlying familial aggregation of non-syndromic gliomas are still to be uncovered. Whole-exome sequencing was performed in four Finnish families with brain tumors to identify rare predisposing variants. A total of 417 detected exome variants and 102 previously reported glioma-related variants were further genotyped in 19 Finnish families with brain tumors using targeted sequencing. Rare damaging variants in GALNT13, MYO10 and AR were identified. Two families carried either c.553C>T (R185C) or c.1214T>A (L405Q) on GALNT13. Variant c.553C>T is located on the substrate-binding site of GALNT13. AR c.2180G>T (R727L), which is located on a ligand-binding domain of AR, was detected in two families, one of which also carried a GALNT13 variant. MYO10 c.4448A>G (N1483S) was detected in two families and c.1511C>T (A504V) variant was detected in one family. Both variants are located on functional domains related to MYO10 activity in filopodia formation. In addition, affected cases in six families carried a known glioma risk variant rs55705857 in CCDC26 and low-risk glioma variants. These novel findings indicate polygenic inheritance of familial glioma in Finland and increase our understanding of the genetic contribution to familial glioma susceptibility.

Analyzing the functional effects of DNA variants with gene editing

Continual advancements in genomics have led to an ever-widening disparity between the rate of discovery of genetic variants and our current understanding of their functions and potential roles in disease. Systematic methods for phenotyping DNA variants are required to effectively translate genomics data into improved outcomes for patients with genetic diseases. To make the biggest impact, these approaches must be scalable and accurate, faithfully reflect disease biology, and define complex disease mechanisms. We compare current methods to analyze the function of variants in their endogenous DNA context using genome editing strategies, such as saturation genome editing, base editing and prime editing. We discuss how these technologies can be linked to high-content readouts to gain deep mechanistic insights into variant effects. Finally, we highlight key challenges that need to be addressed to bridge the genotype to phenotype gap, and ultimately improve the diagnosis and treatment of genetic diseases.

The mutagenic forces shaping the genomic landscape of lung cancer in never smokers

Lung cancer in never smokers (LCINS) accounts for up to 25% of all lung cancers and has been associated with exposure to secondhand tobacco smoke and air pollution in observational studies. Here, we evaluate the mutagenic exposures in LCINS by examining deep whole-genome sequencing data from a large international cohort of 871 treatment-naïve LCINS recruited from 28 geographical locations within the Sherlock-Lung study. KRAS mutations were 3.8-fold more common in adenocarcinomas of never smokers from North America and Europe, while a 1.6-fold higher prevalence of EGFR and TP53 mutations was observed in adenocarcinomas from East Asia. Signature SBS40a, with unknown cause, was found in most samples and accounted for the largest proportion of single base substitutions in adenocarcinomas, being enriched in EGFR-mutated cases. Conversely, the aristolochic acid signature SBS22a was almost exclusively observed in patients from Taipei. Even though LCINS exposed to secondhand smoke had an 8.3% higher mutational burden and 5.4% shorter telomeres, passive smoking was not associated with driver mutations in cancer driver genes or the activities of individual mutational signatures. In contrast, patients from regions with high levels of air pollution were more likely to have TP53 mutations while exhibiting shorter telomeres and an increase in most types of somatic mutations, including a 3.9-fold elevation of signature SBS4 (q-value=3.1 × 10-5), previously linked mainly to tobacco smoking, and a 76% increase of clock-like signature SBS5 (q-value=5.0 × 10-5). A positive dose-response effect was observed with air pollution levels, which correlated with both a decrease in telomere length and an elevation in somatic mutations, notably attributed to signatures SBS4 and SBS5. Our results elucidate the diversity of mutational processes shaping the genomic landscape of lung cancer in never smokers.

ANOS1 accelerates the progression of esophageal cancer identified by multi-omic approaches

To assess the role of ANOS1 in esophageal cancer (ESCA) progression, multi-omic analysis and experimental validation were employed. It was revealed that ANOS1 expression is significantly enhanced in ESCA patients and cell lines. The expression level of ANOS1 in ESCA patients can distinguish the malignancy from normal tissue with an area under curve (AUC) >0.75. Moreover, increased expression of ANOS1 is associated with advanced T stage and worse disease-free survival of ESCA patients. Therefore, a clinically applicable nomogram with ANOS1 was established with strong predictive power. Furthermore, high expression of ANOS1 in ESCA is correlated with (i) the enrichment of epithelial-mesenchymal transition by gene set enrichment analysis, (ii) the involvement in hypoxia, angiogenesis, WNT signaling pathway, and TGFβ signaling pathway by gene set variation analysis, (iii) the presence of the small insertion and deletion mutational signature ID9, associated with chromothripsis, in the single-nucleotide polymorphism analysis, (iv) the amplification of 11q13.3 in the copy number variants analysis, (v) the enrichment of cancer-associated fibroblasts and mesenchymal stromal cells in the tumor microenvironment. All the results from multi-omic analysis indicate that ANOS1 plays a pivotal role in accelerating the progression of ESCA. Results from in vivo and in vitro experiments show that the knockdown of ANOS1 hampers the proliferation of ESCA cells, further validating the oncogenic role of ANOS1 in ESCA. Additionally, potential chemotherapeutics with sensitivity were identified in the high-ANOS1 group. In conclusion, ANOS1 accelerates the progression of ESCA.

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

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

Disentangling oncogenic amplicons in esophageal adenocarcinoma

Esophageal adenocarcinoma is a prominent example of cancer characterized by frequent amplifications in oncogenes. However, the mechanisms leading to amplicons that involve breakage-fusion-bridge cycles and extrachromosomal DNA are poorly understood. Here, we use 710 esophageal adenocarcinoma cases with matched samples and patient-derived organoids to disentangle complex amplicons and their associated mechanisms. Short-read sequencing identifies ERBB2, MYC, MDM2, and HMGA2 as the most frequent oncogenes amplified in extrachromosomal DNAs. We resolve complex extrachromosomal DNA and breakage-fusion-bridge cycles amplicons by integrating of de-novo assemblies and DNA methylation in nine long-read sequenced cases. Complex amplicons shared between precancerous biopsy and late-stage tumor, an enrichment of putative enhancer elements and mobile element insertions are potential drivers of complex amplicons' origin. We find that patient-derived organoids recapitulate extrachromosomal DNA observed in the primary tumors and single-cell DNA sequencing capture extrachromosomal DNA-driven clonal dynamics across passages. Prospectively, long-read and single-cell DNA sequencing technologies can lead to better prediction of clonal evolution in esophageal adenocarcinoma.

Characterization of zinc finger protein 536, a neuroendocrine regulator, using pan-cancer analysis

BACKGROUND

Previous studies suggested that zinc finger protein 536 (ZNF536) was abundant in the central brain and regulated neuronal differentiation. However, the role of ZNF536 in cancer has remained unclear.

METHODS

ZNF536 mutation, copy number alteration, DNA methylation, and RNA expression were explored using public portals. Data from The Cancer Genome Atlas (TCGA) were utilized to analyze pathways and tumor microenvironment (TME), with a focus on prognosis in both TCGA and immunotherapy pan-cancer cohorts. Methylated ZNF536 from small cell lung cancer (SCLC) cell lines were utilized to train with probes for conducting enrichment analysis. Single-cell RNA profile demonstrated the sublocalization and co-expression of ZNF536, and validated its targets by qPCR.

RESULTS

Genetic alterations in ZNF536 were found to be high-frequency and a single sample could harbor different variations. ZNF536 at chromosome 19q12 exerted a bypass effect on CCNE1, supported by CRISPR data. For lung cancer, ZNF536 mutation was associated with longer survival in primary lung adenocarcinoma (LUAD), but its prognosis was poor in metastatic LUAD and SCLC. Importantly, ZNF536 mutation and amplification had opposite prognoses in Stand Up To Cancer-Mark Foundation (SU2C-MARK) LUAD cohort. ZNF536 mutation altered the patterns of genomic alterations in tumors, and had distinct impacts on the signaling pathways and TME compared to ZNF536 amplification. Additionally, ZNF536 expression was predominantly in endocrine tumors and brain tissues. High-dimensional analysis supported this finding and further revealed regulators of ZNF536. Considering that the methylation of ZNF536 was involved in the synaptic pathway associated with neuroendocrine neoplasms, demonstrating both diagnostic and prognostic value. Moreover, we experimentally verified ZNF536 upregulated neuroendocrine markers.

CONCLUSIONS

Our results showed that ZNF536 alterations in cancer, including variations in copy number, mutation, and methylation. We proved the involvement of ZNF536 in neuroendocrine regulation, and identified highly altered ZNF536 as a potential biomarker for immunotherapy.

Mutation rate heterogeneity at the sub-gene scale due to local DNA hypomethylation

Local mutation rates in human are highly heterogeneous, with known variability at the scale of megabase-sized chromosomal domains, and, on the other extreme, at the scale of oligonucleotides. The intermediate, kilobase-scale heterogeneity in mutation risk is less well characterized. Here, by analyzing thousands of somatic genomes, we studied mutation risk gradients along gene bodies, representing a genomic scale spanning roughly 1-10 kb, hypothesizing that different mutational mechanisms are differently distributed across gene segments. The main heterogeneity concerns several kilobases at the transcription start site and further downstream into 5' ends of gene bodies; these are commonly hypomutated with several mutational signatures, most prominently the ubiquitous C > T changes at CpG dinucleotides. The width and shape of this mutational coldspot at 5' gene ends is variable across genes, and corresponds to variable interval of lowered DNA methylation depending on gene activity level and regulation. Such hypomutated loci, at 5' gene ends or elsewhere, correspond to DNA hypomethylation that can associate with various landmarks, including intragenic enhancers, Polycomb-marked regions, or chromatin loop anchor points. Tissue-specific DNA hypomethylation begets tissue-specific local hypomutation. Of note, direction of mutation risk is inverted for AID/APOBEC3 cytosine deaminase activity, whose signatures are enriched in hypomethylated regions.

Luminal breast epithelial cells from wildtype and BRCA mutation carriers harbor copy number alterations commonly associated with breast cancer

Cancer-associated mutations have been documented in normal tissues, but the prevalence and nature of somatic copy number alterations and their role in tumor initiation and evolution is not well understood. Here, using single cell DNA sequencing, we describe the landscape of CNAs in >42,000 breast epithelial cells from women with normal or high risk of developing breast cancer. Accumulation of individual cells with one or two of a specific subset of CNAs (e.g. 1q gain and 16q, 22q, 7q, and 10q loss) is detectable in almost all breast tissues and, in those from BRCA1 or BRCA2 mutations carriers, occurs prior to loss of heterozygosity (LOH) of the wildtype alleles. These CNAs, which are among the most common associated with ductal carcinoma in situ (DCIS) and malignant breast tumors, are enriched almost exclusively in luminal cells not basal myoepithelial cells. Allele-specific analysis of the enriched CNAs reveals that each allele was independently altered, demonstrating convergent evolution of these CNAs in an individual breast. Tissues from BRCA1 or BRCA2 mutation carriers contain a small percentage of cells with extreme aneuploidy, featuring loss of TP53 , LOH of BRCA1 or BRCA2 , and multiple breast cancer-associated CNAs in addition to one or more of the common CNAs in 1q, 10q or 16q. Notably, cells with intermediate levels of CNAs are not detected, arguing against a stepwise gradual accumulation of CNAs. Overall, our findings demonstrate that chromosomal alterations in normal breast epithelium partially mirror those of established cancer genomes and are chromosome- and cell lineage-specific.

KDM7A-DT induces genotoxic stress, tumorigenesis, and progression of p53 missense mutation-associated invasive breast cancer

Stress-induced promoter-associated and antisense lncRNAs (si-paancRNAs) originate from a reservoir of oxidative stress (OS)-specific promoters via RNAPII pausing-mediated divergent antisense transcription. Several studies have shown that the KDM7A divergent transcript gene (KDM7A-DT), which encodes a si-paancRNA, is overexpressed in some cancer types. However, the mechanisms of this overexpression and its corresponding roles in oncogenesis and cancer progression are poorly understood. We found that KDM7A-DT expression is correlated with highly aggressive cancer types and specific inherently determined subtypes (such as ductal invasive breast carcinoma (BRCA) basal subtype). Its regulation is determined by missense TP53 mutations in a subtype-specific context. KDM7A-DT transcribes several intermediate-sized ncRNAs and a full-length transcript, exhibiting distinct expression and localization patterns. Overexpression of KDM7A-DT upregulates TP53 protein expression and H2AX phosphorylation in nonmalignant fibroblasts, while in semi-transformed fibroblasts, OS superinduces KDM7A-DT expression in a TP53-dependent manner. KDM7A-DT knockdown and gene expression profiling in TP53-missense mutated luminal A BRCA variant, where it is abundantly expressed, indicate its significant role in cancer pathways. Endogenous over-expression of KDM7A-DT inhibits DNA damage response/repair (DDR/R) via the TP53BP1-mediated pathway, reducing apoptosis and promoting G2/M checkpoint arrest. Higher KDM7A-DT expression in BRCA is associated with KDM7A-DT locus gain/amplification, higher histologic grade, aneuploidy, hypoxia, immune modulation scores, and activation of the c-myc pathway. Higher KDM7A-DT expression is associated with relatively poor survival outcomes in patients with luminal A or Basal subtypes. In contrast, it is associated with favorable outcomes in patients with HER2+ER- or luminal B subtypes. KDM7A-DT levels are coregulated with critical transcripts and proteins aberrantly expressed in BRCA, including those involved in DNA repair via non-homologous end joining and epithelial-to-mesenchymal transition pathway. In summary, KDM7A-DT and its si-lncRNA exhibit several intrinsic biological and clinical characteristics that suggest important roles in invasive BRCA and its subtypes. KDM7A-DT-defined mRNA and protein subnetworks offer resources for identifying clinically relevant RNA-based signatures and prospective targets for therapeutic intervention.

Gastric cancer actionable genomic alterations across diverse populations worldwide and pharmacogenomics strategies based on precision oncology

Introduction: Gastric cancer is one of the most prevalent types of cancer worldwide. The World Health Organization (WHO), the International Agency for Research on Cancer (IARC), and the Global Cancer Statistics (GLOBOCAN) reported an age standardized global incidence rate of 9.2 per 100,000 individuals for gastric cancer in 2022, with a mortality rate of 6.1. Despite considerable progress in precision oncology through the efforts of international consortia, understanding the genomic features and their influence on the effectiveness of anti-cancer treatments across diverse ethnic groups remains essential. Methods: Our study aimed to address this need by conducting integrated in silico analyses to identify actionable genomic alterations in gastric cancer driver genes, assess their impact using deleteriousness scores, and determine allele frequencies across nine global populations: European Finnish, European non-Finnish, Latino, East Asian, South Asian, African, Middle Eastern, Ashkenazi Jewish, and Amish. Furthermore, our goal was to prioritize targeted therapeutic strategies based on pharmacogenomics clinical guidelines, in silico drug prescriptions, and clinical trial data. Results: Our comprehensive analysis examined 275,634 variants within 60 gastric cancer driver genes from 730,947 exome sequences and 76,215 whole-genome sequences from unrelated individuals, identifying 13,542 annotated and predicted oncogenic variants. We prioritized the most prevalent and deleterious oncogenic variants for subsequent pharmacogenomics testing. Additionally, we discovered actionable genomic alterations in the ARID1A, ATM, BCOR, ERBB2, ERBB3, CDKN2A, KIT, PIK3CA, PTEN, NTRK3, TP53, and CDKN2A genes that could enhance the efficacy of anti-cancer therapies, as suggested by in silico drug prescription analyses, reviews of current pharmacogenomics clinical guidelines, and evaluations of phase III and IV clinical trials targeting gastric cancer driver proteins. Discussion: These findings underline the urgency of consolidating efforts to devise effective prevention measures, invest in genomic profiling for underrepresented populations, and ensure the inclusion of ethnic minorities in future clinical trials and cancer research in developed countries.

MUSE-XAE: MUtational Signature Extraction with eXplainable AutoEncoder enhances tumour types classification

MOTIVATION

Mutational signatures are a critical component in deciphering the genetic alterations that underlie cancer development and have become a valuable resource to understand the genomic changes during tumorigenesis. Therefore, it is essential to employ precise and accurate methods for their extraction to ensure that the underlying patterns are reliably identified and can be effectively utilized in new strategies for diagnosis, prognosis, and treatment of cancer patients.

RESULTS

We present MUSE-XAE, a novel method for mutational signature extraction from cancer genomes using an explainable autoencoder. Our approach employs a hybrid architecture consisting of a nonlinear encoder that can capture nonlinear interactions among features, and a linear decoder which ensures the interpretability of the active signatures. We evaluated and compared MUSE-XAE with other available tools on both synthetic and real cancer datasets and demonstrated that it achieves superior performance in terms of precision and sensitivity in recovering mutational signature profiles. MUSE-XAE extracts highly discriminative mutational signature profiles by enhancing the classification of primary tumour types and subtypes in real world settings. This approach could facilitate further research in this area, with neural networks playing a critical role in advancing our understanding of cancer genomics.

AVAILABILITY AND IMPLEMENTATION

MUSE-XAE software is freely available at https://github.com/compbiomed-unito/MUSE-XAE.

DistSNE: Distributed computing and online visualization of DNA methylation-based central nervous system tumor classification

The current state-of-the-art analysis of central nervous system (CNS) tumors through DNA methylation profiling relies on the tumor classifier developed by Capper and colleagues, which centrally harnesses DNA methylation data provided by users. Here, we present a distributed-computing-based approach for CNS tumor classification that achieves a comparable performance to centralized systems while safeguarding privacy. We utilize the t-distributed neighborhood embedding (t-SNE) model for dimensionality reduction and visualization of tumor classification results in two-dimensional graphs in a distributed approach across multiple sites (DistSNE). DistSNE provides an intuitive web interface (https://gin-tsne.med.uni-giessen.de) for user-friendly local data management and federated methylome-based tumor classification calculations for multiple collaborators in a DataSHIELD environment. The freely accessible web interface supports convenient data upload, result review, and summary report generation. Importantly, increasing sample size as achieved through distributed access to additional datasets allows DistSNE to improve cluster analysis and enhance predictive power. Collectively, DistSNE enables a simple and fast classification of CNS tumors using large-scale methylation data from distributed sources, while maintaining the privacy and allowing easy and flexible network expansion to other institutes. This approach holds great potential for advancing human brain tumor classification and fostering collaborative precision medicine in neuro-oncology.

Pan-Cancer Comparative and Integrative Analyses of Driver Alterations Using Japanese and International Genomic Databases

Using 48,627 samples from the Center for Cancer Genomics and Advanced Therapeutics (C-CAT), we present a pan-cancer landscape of driver alterations and their clinical actionability in Japanese patients. Comparison with White patients in Genomics Evidence Neoplasia Information Exchange (GENIE) demonstrates high TP53 mutation frequencies in Asian patients across multiple cancer types. Integration of C-CAT, GENIE, and The Cancer Genome Atlas data reveals many cooccurring and mutually exclusive relationships between driver mutations. At pathway level, mutations in epigenetic regulators frequently cooccur with PI3K pathway molecules. Furthermore, we found significant cooccurring mutations within the epigenetic pathway. Accumulation of mutations in epigenetic regulators causes increased proliferation-related transcriptomic signatures. Loss-of-function of many epigenetic drivers inhibits cell proliferation in their wild-type cell lines, but this effect is attenuated in those harboring mutations of not only the same but also different epigenetic drivers. Our analyses dissect various genetic properties and provide valuable resources for precision medicine in cancer.

SIGNIFICANCE

We present a genetic landscape of 26 principal cancer types/subtypes, including Asian-prevalent ones, in Japanese patients. Multicohort data integration unveils numerous cooccurring and exclusive relationships between driver mutations, identifying cooccurrence of multiple mutations in epigenetic regulators, which coordinately cause transcriptional and phenotypic changes. These findings provide insights into epigenetic regulator-driven oncogenesis. This article is featured in Selected Articles from This Issue, p. 695.

Decoding the interplay between genetic and non-genetic drivers of metastasis

Metastasis is a multistep process by which cancer cells break away from their original location and spread to distant organs, and is responsible for the vast majority of cancer-related deaths. Preventing early metastatic dissemination would revolutionize the ability to fight cancer. Unfortunately, the relatively poor understanding of the molecular underpinnings of metastasis has hampered the development of effective anti-metastatic drugs. Although it is now accepted that disseminating tumour cells need to acquire multiple competencies to face the many obstacles they encounter before reaching their metastatic site(s), whether these competencies are acquired through an accumulation of metastasis-specific genetic alterations and/or non-genetic events is often debated. Here we review a growing body of literature highlighting the importance of both genetic and non-genetic reprogramming events during the metastatic cascade, and discuss how genetic and non-genetic processes act in concert to confer metastatic competencies. We also describe how recent technological advances, and in particular the advent of single-cell multi-omics and barcoding approaches, will help to better elucidate the cross-talk between genetic and non-genetic mechanisms of metastasis and ultimately inform innovative paths for the early detection and interception of this lethal process.

Fusion genes in pancreatic tumors

Gene fusions and rearrangements play a crucial role in tumor biology. They are rare events typically detected in KRAS wild-type (WT) pancreatic tumors. Their identification can inform clinical management by enabling precision oncology, as fusions involving BRAF, FGFR2, RET, NTRK, NRG1, and ALK represent actionable targets in KRAS-WT cancers, and serve diagnostic purposes since fusions involving PRKACA/B represent the diagnostic hallmark of intraductal oncocytic papillary neoplasms (IOPNs). Although they are rare, the therapeutic and diagnostic importance of these genomic events should not be underestimated, highlighting the need for quality-ensured molecular diagnostics in the management of cancer. Herein we review the existing literature on the role of fusion genes in pancreatic tumors and their clinical potential as effective biomarkers and therapeutic targets.

Comparative transcriptomic analysis reveals differences in gene expression and regulatory pathways between nonacral and acral melanoma in Asian individuals

Melanoma predominantly occurs in White individuals, which is associated with factors such as exposure to UV radiation and skin pigmentation. Despite its low incidence, melanoma is the primary cause of skin cancer-related death in Asia, typically in areas with low sun exposure. In our previous whole-exome sequencing study, we identified mutational signature 12 as the most prevalent variant in Asian patients, differing from the common UV-associated mutational signature 7 observed in White individuals. We also observed major differences between acral melanoma (AM) and nonacral melanoma (NAM) in terms of signatures 7, 21, and 22. Notably, few studies have investigated the genomic differences between AM and NAM in Asian individuals. Therefore, in this study, we conducted transcriptomic sequencing to examine the disparities in RNA expression between AM and NAM. Ribosomal RNA depletion was performed to enhance the detection of functionally relevant coding and noncoding transcripts. Ingenuity pathway analysis revealed significant differences in gene expression and regulatory pathways between AM and NAM. The results also indicate that the genes involved in cell cycle signaling or immune modulation and programmed cell death protein 1/programmed cell death 1 ligand 1 signaling were differentially expressed in NAM and AM. In addition, high CDK4 expression and cell cycle variability were observed in AM, with high immunogenicity in NAM. Overall, these findings provide further insights into the pathogenesis of melanoma and serve as a reference for future research on this major malignant disease.

Geographic variation of mutagenic exposures in kidney cancer genomes

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

Artificial Intelligence in Oncology: Current Landscape, Challenges, and Future Directions

Artificial intelligence (AI) in oncology is advancing beyond algorithm development to integration into clinical practice. This review describes the current state of the field, with a specific focus on clinical integration. AI applications are structured according to cancer type and clinical domain, focusing on the four most common cancers and tasks of detection, diagnosis, and treatment. These applications encompass various data modalities, including imaging, genomics, and medical records. We conclude with a summary of existing challenges, evolving solutions, and potential future directions for the field.

SIGNIFICANCE

AI is increasingly being applied to all aspects of oncology, where several applications are maturing beyond research and development to direct clinical integration. This review summarizes the current state of the field through the lens of clinical translation along the clinical care continuum. Emerging areas are also highlighted, along with common challenges, evolving solutions, and potential future directions for the field.