Pan-cancer analysis of whole genomes

Singleton mutations in large-scale cancer genome studies: uncovering the tail of cancer genome

Singleton or low-frequency driver mutations are challenging to identify. We present a domain driver mutation estimator (DOME) to identify rare candidate driver mutations. DOME analyzes positions analogous to known statistical hotspots and resistant mutations in combination with their functional and biochemical residue context as determined by protein structures and somatic mutation propensity within conserved PFAM domains, integrating the CADD scoring scheme. Benchmarked against seven other tools, DOME exhibited superior or comparable accuracy compared to all evaluated tools in the prediction of functional cancer drivers, with the exception of one tool. DOME identified a unique set of 32 917 high-confidence predicted driver mutations from the analysis of whole proteome missense variants within domain boundaries across 1331 genes, including 1192 noncancer gene census genes, emphasizing its unique place in cancer genome analysis. Additionally, analysis of 8799 TCGA (The Cancer Genome Atlas) and in-house tumor samples revealed 847 potential driver mutations, with mutations in tyrosine kinase members forming the dominant burden, underscoring its higher significance in cancer. Overall, DOME complements current approaches for identifying novel, low-frequency drivers and resistant mutations in personalized therapy.

Genetic determinants of micronucleus formation in vivo

Genomic instability arising from defective responses to DNA damage1 or mitotic chromosomal imbalances2 can lead to the sequestration of DNA in aberrant extranuclear structures called micronuclei (MN). Although MN are a hallmark of ageing and diseases associated with genomic instability, the catalogue of genetic players that regulate the generation of MN remains to be determined. Here we analyse 997 mouse mutant lines, revealing 145 genes whose loss significantly increases (n = 71) or decreases (n = 74) MN formation, including many genes whose orthologues are linked to human disease. We found that mice null for Dscc1, which showed the most significant increase in MN, also displayed a range of phenotypes characteristic of patients with cohesinopathy disorders. After validating the DSCC1-associated MN instability phenotype in human cells, we used genome-wide CRISPR-Cas9 screening to define synthetic lethal and synthetic rescue interactors. We found that the loss of SIRT1 can rescue phenotypes associated with DSCC1 loss in a manner paralleling restoration of protein acetylation of SMC3. Our study reveals factors involved in maintaining genomic stability and shows how this information can be used to identify mechanisms that are relevant to human disease biology1.

Accurate and sensitive mutational signature analysis with MuSiCal

Mutational signature analysis is a recent computational approach for interpreting somatic mutations in the genome. Its application to cancer data has enhanced our understanding of mutational forces driving tumorigenesis and demonstrated its potential to inform prognosis and treatment decisions. However, methodological challenges remain for discovering new signatures and assigning proper weights to existing signatures, thereby hindering broader clinical applications. Here we present Mutational Signature Calculator (MuSiCal), a rigorous analytical framework with algorithms that solve major problems in the standard workflow. Our simulation studies demonstrate that MuSiCal outperforms state-of-the-art algorithms for both signature discovery and assignment. By reanalyzing more than 2,700 cancer genomes, we provide an improved catalog of signatures and their assignments, discover nine indel signatures absent in the current catalog, resolve long-standing issues with the ambiguous 'flat' signatures and give insights into signatures with unknown etiologies. We expect MuSiCal and the improved catalog to be a step towards establishing best practices for mutational signature analysis.

Optimized whole-genome sequencing workflow for tumor diagnostics in routine pathology practice

Two decades after the genomics revolution, oncology is rapidly transforming into a genome-driven discipline, yet routine cancer diagnostics is still mainly microscopy based, except for tumor type-specific predictive molecular tests. Pathology laboratories struggle to quickly validate and adopt biomarkers identified by genomics studies of new targeted therapies. Consequently, clinical implementation of newly approved biomarkers suffers substantial delays, leading to unequal patient access to these therapies. Whole-genome sequencing (WGS) can successfully address these challenges by providing a stable molecular diagnostic platform that allows detection of a multitude of genomic alterations in a single cost-efficient assay and facilitating rapid implementation, as well as by the development of new genomic biomarkers. Recently, the Whole-genome sequencing Implementation in standard Diagnostics for Every cancer patient (WIDE) study demonstrated that WGS is a feasible and clinically valid technique in routine clinical practice with a turnaround time of 11 workdays. As a result, WGS was successfully implemented at the Netherlands Cancer Institute as part of routine diagnostics in January 2021. The success of implementing WGS has relied on adhering to a comprehensive protocol including recording patient information, sample collection, shipment and storage logistics, sequencing data interpretation and reporting, integration into clinical decision-making and data usage. This protocol describes the use of fresh-frozen samples that are necessary for WGS but can be challenging to implement in pathology laboratories accustomed to using formalin-fixed paraffin-embedded samples. In addition, the protocol outlines key considerations to guide uptake of WGS in routine clinical care in hospitals worldwide.

CRUX, a platform for visualising, exploring and analysing cancer genome cohort data

To better understand how tumours develop, identify prognostic biomarkers and find new treatments, researchers have generated vast catalogues of cancer genome data. However, these datasets are complex, so interpreting their important features requires specialized computational skills and analytical tools, which presents a significant technical challenge. To address this, we developed CRUX, a platform for exploring genomic data from cancer cohorts. CRUX enables researchers to perform common analyses including cohort comparisons, biomarker discovery, survival analysis, and to create visualisations including oncoplots and lollipop charts. CRUX simplifies cancer genome analysis in several ways: (i) it has an easy-to-use graphical interface; (ii) it enables users to create custom cohorts, as well as analyse precompiled public and private user-created datasets; (iii) it allows analyses to be run locally to address data privacy concerns (though an online version is also available) and (iv) it makes it easy to use additional specialized tools by exporting data in the correct formats. We showcase CRUX's capabilities with case studies employing different types of cancer genome analysis, demonstrating how it can be used flexibly to generate valuable insights into cancer biology. CRUX is freely available at https://github.com/CCICB/CRUX and https://ccicb.shinyapps.io/crux (DOI: 10.5281/zenodo.8015714).

Scrambling the genome in cancer: causes and consequences of complex chromosome rearrangements

Complex chromosome rearrangements, known as chromoanagenesis, are widespread in cancer. Based on large-scale DNA sequencing of human tumours, the most frequent type of complex chromosome rearrangement is chromothripsis, a massive, localized and clustered rearrangement of one (or a few) chromosomes seemingly acquired in a single event. Chromothripsis can be initiated by mitotic errors that produce a micronucleus encapsulating a single chromosome or chromosomal fragment. Rupture of the unstable micronuclear envelope exposes its chromatin to cytosolic nucleases and induces chromothriptic shattering. Found in up to half of tumours included in pan-cancer genomic analyses, chromothriptic rearrangements can contribute to tumorigenesis through inactivation of tumour suppressor genes, activation of proto-oncogenes, or gene amplification through the production of self-propagating extrachromosomal circular DNAs encoding oncogenes or genes conferring anticancer drug resistance. Here, we discuss what has been learned about the mechanisms that enable these complex genomic rearrangements and their consequences in cancer.

Detection of Novel Tyrosine Kinase Fusion Genes as Potential Therapeutic Targets in Bone and Soft Tissue Sarcomas Using DNA/RNA-based Clinical Sequencing

BACKGROUND

Approximately 1% of clinically treatable tyrosine kinase fusions, including anaplastic lymphoma kinase, neurotrophic tyrosine receptor kinase, RET proto-oncogene, and ROS proto-oncogene 1, have been identified in soft tissue sarcomas via comprehensive genome profiling based on DNA sequencing. Histologic tumor-specific fusion genes have been reported in approximately 20% of soft tissue sarcomas; however, unlike tyrosine kinase fusion genes, these fusions cannot be directly targeted in therapy. Approximately 80% of tumor-specific fusion-negative sarcomas, including myxofibrosarcoma and leiomyosarcoma, that are defined in complex karyotype sarcomas remain genetically uncharacterized; this mutually exclusive pattern of mutations suggests that other mutually exclusive driver oncogenes are yet to be discovered. Tumor-specific, fusion-negative sarcomas may be associated with unique translocations, and oncogenic fusion genes, including tyrosine kinase fusions, may have been overlooked in these sarcomas.

QUESTIONS/PURPOSES

(1) Can DNA- or RNA-based analysis reveal any characteristic gene alterations in bone and soft tissue sarcomas? (2) Can useful and potential tyrosine kinase fusions in tumors from tumor-specific, fusion-negative sarcomas be detected using an RNA-based screening system? (3) Do the identified potential fusion tumors, especially in neurotrophic tyrosine receptor kinase gene fusions in bone sarcoma, transform cells and respond to targeted drug treatment in in vitro assays? (4) Can the identified tyrosine kinase fusion genes in sarcomas be useful therapeutic targets?

METHODS

Between 2017 and 2020, we treated 100 patients for bone and soft tissue sarcomas at five institutions. Any biopsy or surgery from which a specimen could be obtained was included as potentially eligible. Ninety percent (90 patients) of patients were eligible; a further 8% (8 patients) were excluded because they were either lost to follow-up or their diagnosis was changed, leaving 82% (82 patients) for analysis here. To answer our first and second questions regarding gene alterations and potential tyrosine kinase fusions in eight bone and 74 soft tissue sarcomas, we used the TruSight Tumor 170 assay to detect mutations, copy number variations, and gene fusions in the samples. To answer our third question, we performed functional analyses involving in vitro assays to determine whether the identified tyrosine kinase fusions were associated with oncogenic abilities and drug responses. Finally, to determine usefulness as therapeutic targets, two pediatric patients harboring an NTRK fusion and an ALK fusion were treated with tyrosine kinase inhibitors in clinical trials.

RESULTS

DNA/RNA-based analysis demonstrated characteristic alterations in bone and soft tissue sarcomas; DNA-based analyses detected TP53 and copy number alterations of MDM2 and CDK4 . These single-nucleotide variants and copy number variations were enriched in specific fusion-negative sarcomas. RNA-based screening detected fusion genes in 24% (20 of 82) of patients. Useful potential fusions were detected in 19% (11 of 58) of tumor-specific fusion-negative sarcomas, with nine of these patients harboring tyrosine kinase fusion genes; five of these patients had in-frame tyrosine kinase fusion genes ( STRN3-NTRK3, VWC2-EGFR, ICK-KDR, FOXP2-MET , and CEP290-MET ) with unknown pathologic significance. The functional analysis revealed that STRN3-NTRK3 rearrangement that was identified in bone had a strong transforming potential in 3T3 cells, and that STRN3-NTRK3 -positive cells were sensitive to larotrectinib in vitro. To confirm the usefulness of identified tyrosine kinase fusion genes as therapeutic targets, patients with well-characterized LMNA-NTRK1 and CLTC-ALK fusions were treated with tyrosine kinase inhibitors in clinical trials, and a complete response was achieved.

CONCLUSION

We identified useful potential therapeutic targets for tyrosine kinase fusions in bone and soft tissue sarcomas using RNA-based analysis. We successfully identified STRN3-NTRK3 fusion in a patient with leiomyosarcoma of bone and determined the malignant potential of this fusion gene via functional analyses and drug effects. In light of these discoveries, comprehensive genome profiling should be considered even if the sarcoma is a bone sarcoma. There seem to be some limitations regarding current DNA-based comprehensive genome profiling tests, and it is important to use RNA testing for proper diagnosis and accurate identification of fusion genes. Studies on more patients, validation of results, and further functional analysis of unknown tyrosine kinase fusion genes are required to establish future treatments.

CLINICAL RELEVANCE

DNA- and RNA-based screening systems may be useful for detecting tyrosine kinase fusion genes in specific fusion-negative sarcomas and identifying key therapeutic targets, leading to possible breakthroughs in the treatment of bone and soft tissue sarcomas. Given that current DNA sequencing misses fusion genes, RNA-based screening systems should be widely considered as a worldwide test for sarcoma. If standard treatments such as chemotherapy are not effective, or even if the sarcoma is of bone, RNA sequencing should be considered to identify as many therapeutic targets as possible.

Exploring the regulatory interactions between mutated genes and homeobox genes in the head and neck cancer progression

OBJECTIVE

Understanding the regulatory role of homeobox (HOX) and mutated genes in the progression of head and neck cancers is essential, although their interaction remains elusive. This study aims to decipher the critical regulation of mutation driven effects on homeobox genes to enhance our understanding of head and neck cancer progression.

METHODS

Genomic mutation data from The Cancer Genome Atlas-Head and Neck Squamous Cell Carcinoma were analyzed using VarScan2 for somatic variant detection. Mutational clustering, driver mutation identification, and cancer signaling pathway analysis were performed using the OncodriveCLUST method. Harmonizome datasets were retrieved to identify critical cancer driver genes affecting HOX genes. The effects of HPV infection on HOX and mutated genes were assessed using the oncoviral database. Altered pathway activity due to the effects of cancer drivers on HOX genes was analyzed with Gene Set Cancer Analysis. Functional enrichment analysis of gene ontology biological processes and molecular functions was conducted using the ClusterProfiler R package.

RESULTS

Significant alterations in HOX genes were observed in head and neck cancer cohorts with mutated TP53, FAT1, and CDKN2A. HOX genes were identified as functionally downstream targets of TP53, signifying transcriptionally mediated regulation. The interaction between HOX genes and mutated TP53, FAT1, and CDKN2A dysregulated the epithelial-to-mesenchymal transition, cell cycle, and apoptosis pathways in head and neck cancer progression.

CONCLUSION

The interplay between cancer driver genes and HOX genes is pivotal in regulating the oncogenic processes underlying the pathogenesis of head and neck squamous cell carcinoma.

Germline determinants of aberrant signaling pathways in cancer

Cancer is a complex disease influenced by a heterogeneous landscape of both germline genetic variants and somatic aberrations. While there is growing evidence suggesting an interplay between germline and somatic variants, and a substantial number of somatic aberrations in specific pathways are now recognized as hallmarks in many well-known forms of cancer, the interaction landscape between germline variants and the aberration of those pathways in cancer remains largely unexplored. Utilizing over 8500 human samples across 33 cancer types characterized by TCGA and considering binary traits defined using a large collection of somatic aberration profiles across ten well-known oncogenic signaling pathways, we conducted a series of GWAS and identified genome-wide and suggestive associations involving 276 SNPs. Among these, 94 SNPs revealed cis-eQTL links with cancer-related genes or with genes functionally correlated with the corresponding traits' oncogenic pathways. GWAS summary statistics for all tested traits were then used to construct a set of polygenic scores employing a customized computational strategy. Polygenic scores for 24 traits demonstrated significant performance and were validated using data from PCAWG and CCLE datasets. These scores showed prognostic value for clinical variables and exhibited significant effectiveness in classifying patients into specific cancer subtypes or stratifying patients with cancer-specific aggressive phenotypes. Overall, we demonstrate that germline genetics can describe patients' genetic liability to develop specific cancer molecular and clinical profiles.

CMC: Cancer miRNA Census - a list of cancer-related miRNA genes

A growing body of evidence indicates an important role of miRNAs in cancer; however, there is no definitive, convenient-to-use list of cancer-related miRNAs or miRNA genes that may serve as a reference for analyses of miRNAs in cancer. To this end, we created a list of 165 cancer-related miRNA genes called the Cancer miRNA Census (CMC). The list is based on a score, built on various types of functional and genetic evidence for the role of particular miRNAs in cancer, e.g. miRNA-cancer associations reported in databases, associations of miRNAs with cancer hallmarks, or signals of positive selection of genetic alterations in cancer. The presence of well-recognized cancer-related miRNA genes, such as MIR21, MIR155, MIR15A, MIR17 or MIRLET7s, at the top of the CMC ranking directly confirms the accuracy and robustness of the list. Additionally, to verify and indicate the reliability of CMC, we performed a validation of criteria used to build CMC, comparison of CMC with various cancer data (publications and databases), and enrichment analyses of biological pathways and processes such as Gene Ontology or DisGeNET. All validation steps showed a strong association of CMC with cancer/cancer-related processes confirming its usefulness as a reference list of miRNA genes associated with cancer.

Importance of targeting various cell signaling pathways in solid cancers

Most adult human cancers are solid tumors prevailing in vital organs and lead to mortality all over the globe. Genetic and epigenetic alterations in cancer genes or genes of associated signaling pathways impart the most common characteristic of malignancy, that is, uncontrolled proliferation. Unless the mechanism of action of these cells signaling pathways (involved in cell proliferation, apoptosis, metastasis, and the maintenance of the stemness of cancer stem cells and cancer microenvironment) and their physiologic alteration are extensively studied, it is challenging to understand tumorigenesis as well as develop new treatments and precision medicines. Targeted therapy is one of the most promising strategies for treating various cancers. However, cancer is an evolving disease, and most patients develop resistance to these drugs by acquired mutations or mediation of microenvironmental factors or due to tumor heterogeneity. Researchers are striving to develop novel therapeutic options like combinatorial approaches targeting multiple responsible pathways effectively. Thus, in-depth knowledge of cell signaling and its components remains a critical topic of cancer research. This chapter summarized various extensively studied pathways in solid cancer and how they are targeted for therapeutic strategies.

An immunogenetic basis for lung cancer risk

Cancer risk is influenced by inherited mutations, DNA replication errors, and environmental factors. However, the influence of genetic variation in immunosurveillance on cancer risk is not well understood. Leveraging population-level data from the UK Biobank and FinnGen, we show that heterozygosity at the human leukocyte antigen (HLA)-II loci is associated with reduced lung cancer risk in smokers. Fine-mapping implicated amino acid heterozygosity in the HLA-II peptide binding groove in reduced lung cancer risk, and single-cell analyses showed that smoking drives enrichment of proinflammatory lung macrophages and HLA-II+ epithelial cells. In lung cancer, widespread loss of HLA-II heterozygosity (LOH) favored loss of alleles with larger neopeptide repertoires. Thus, our findings nominate genetic variation in immunosurveillance as a critical risk factor for lung cancer.

Hepatocellular Carcinoma: Old and Emerging Therapeutic Targets

Liver cancer, predominantly hepatocellular carcinoma (HCC), globally ranks sixth in incidence and third in cancer-related deaths. HCC risk factors include non-viral hepatitis, alcohol abuse, environmental exposures, and genetic factors. No specific genetic alterations are unequivocally linked to HCC tumorigenesis. Current standard therapies include surgical options, systemic chemotherapy, and kinase inhibitors, like sorafenib and regorafenib. Immunotherapy, targeting immune checkpoints, represents a promising avenue. FDA-approved checkpoint inhibitors, such as atezolizumab and pembrolizumab, show efficacy, and combination therapies enhance clinical responses. Despite this, the treatment of hepatocellular carcinoma (HCC) remains a challenge, as the complex tumor ecosystem and the immunosuppressive microenvironment associated with it hamper the efficacy of the available therapeutic approaches. This review explores current and advanced approaches to treat HCC, considering both known and new potential targets, especially derived from proteomic analysis, which is today considered as the most promising approach. Exploring novel strategies, this review discusses antibody drug conjugates (ADCs), chimeric antigen receptor T-cell therapy (CAR-T), and engineered antibodies. It then reports a systematic analysis of the main ligand/receptor pairs and molecular pathways reported to be overexpressed in tumor cells, highlighting their potential and limitations. Finally, it discusses TGFβ, one of the most promising targets of the HCC microenvironment.

CAGI, the Critical Assessment of Genome Interpretation, establishes progress and prospects for computational genetic variant interpretation methods

BACKGROUND

The Critical Assessment of Genome Interpretation (CAGI) aims to advance the state-of-the-art for computational prediction of genetic variant impact, particularly where relevant to disease. The five complete editions of the CAGI community experiment comprised 50 challenges, in which participants made blind predictions of phenotypes from genetic data, and these were evaluated by independent assessors.

RESULTS

Performance was particularly strong for clinical pathogenic variants, including some difficult-to-diagnose cases, and extends to interpretation of cancer-related variants. Missense variant interpretation methods were able to estimate biochemical effects with increasing accuracy. Assessment of methods for regulatory variants and complex trait disease risk was less definitive and indicates performance potentially suitable for auxiliary use in the clinic.

CONCLUSIONS

Results show that while current methods are imperfect, they have major utility for research and clinical applications. Emerging methods and increasingly large, robust datasets for training and assessment promise further progress ahead.

The Intricate Interplay between APOBEC3 Proteins and DNA Tumour Viruses

APOBEC3 proteins are cytidine deaminases that play a crucial role in the innate immune response against viruses, including DNA viruses. Their main mechanism for restricting viral replication is the deamination of cytosine to uracil in viral DNA during replication. This process leads to hypermutation of the viral genome, resulting in loss of viral fitness and, in many cases, inactivation of the virus. APOBEC3 proteins inhibit the replication of a number of DNA tumour viruses, including herpesviruses, papillomaviruses and hepadnaviruses. Different APOBEC3s restrict the replication of different virus families in different ways and this restriction is not limited to one APOBEC3. Infection with DNA viruses often leads to the development and progression of cancer. APOBEC3 mutational signatures have been detected in various cancers, indicating the importance of APOBEC3s in carcinogenesis. Inhibition of DNA viruses by APOBEC3 proteins appears to play a dual role in this process. On the one hand, it is an essential component of the innate immune response to viral infections, and, on the other hand, it contributes to the pathogenesis of persistent viral infections and the progression of cancer. The current review examines the complex interplay between APOBEC3 proteins and DNA viruses and sheds light on the mechanisms of action, viral countermeasures and the impact on carcinogenesis. Deciphering the current issues in the interaction of APOBEC/DNA viruses should enable the development of new targeted cancer therapies.

SPATA20 deficiency enhances the metastatic and angiogenic potential of cancer cells by promoting HIF-1α synthesis

Hypoxia-inducible factors (HIFs) regulate cellular oxygen balance and play a central role in cancer metastasis and angiogenesis. Despite extensive research on HIFs, successful therapeutic strategies remain limited due to the intricate nature of their regulation. In this study, we identified SPATA20, a relatively understudied protein with a thioredoxin-like domain, as an upstream regulator of HIF-1α. Depleting SPATA20 induced HIF-1α expression, suggesting a tumor-suppressive role for SPATA20 in cancer cells. SPATA20 depletion increased HIF-1α protein levels and transcriptional activity without affecting its degradation. It appears that SPATA20 inhibits the de novo synthesis of HIF-1α, possibly by repressing the cap-dependent translation process involving AKT phosphorylation. Additionally, depletion of SPATA20 promoted cancer cell migration and invasion, which can be reversed by pharmacological inhibition of HIF-1α. Clinical data analysis revealed an inverse correlation between SPATA20 expression and colorectal cancer progression, providing evidence of its role as a potential biomarker. Utilizing SPATA20 as an indicator for HIF-1α-targeting therapy may be an attractive strategy for treating patients with hypoxia-driven cancers. In conclusion, this study demonstrates that SPATA20 deficiency promotes cancer progression by activating the HIF-1α signaling pathway.

Haplotype-specific assembly of shattered chromosomes in esophageal adenocarcinomas

The epigenetic landscape of cancer is regulated by many factors, but primarily it derives from the underlying genome sequence. Chromothripsis is a catastrophic localized genome shattering event that drives, and often initiates, cancer evolution. We characterized five esophageal adenocarcinoma organoids with chromothripsis using long-read sequencing and transcriptome and epigenome profiling. Complex structural variation and subclonal variants meant that haplotype-aware de novo methods were required to generate contiguous cancer genome assemblies. Chromosomes were assembled separately and scaffolded using haplotype-resolved Hi-C reads, producing accurate assemblies even with up to 900 structural rearrangements. There were widespread differences between the chromothriptic and wild-type copies of chromosomes in topologically associated domains, chromatin accessibility, histone modifications, and gene expression. Differential epigenome peaks were most enriched within 10 kb of chromothriptic structural variants. Alterations in transcriptome and higher-order chromosome organization frequently occurred near differential epigenetic marks. Overall, chromothripsis reshapes gene regulation, causing coordinated changes in epigenetic landscape, transcription, and chromosome conformation.

Quantitative and qualitative mutational impact of ionizing radiation on normal cells

The comprehensive genomic impact of ionizing radiation (IR), a carcinogen, on healthy somatic cells remains unclear. Using large-scale whole-genome sequencing (WGS) of clones expanded from irradiated murine and human single cells, we revealed that IR induces a characteristic spectrum of short insertions or deletions (indels) and structural variations (SVs), including balanced inversions, translocations, composite SVs (deletion-insertion, deletion-inversion, and deletion-translocation composites), and complex genomic rearrangements (CGRs), including chromoplexy, chromothripsis, and SV by breakage-fusion-bridge cycles. Our findings suggest that 1 Gy IR exposure causes an average of 2.33 mutational events per Gb genome, comprising 2.15 indels, 0.17 SVs, and 0.01 CGRs, despite a high level of inter-cellular stochasticity. The mutational burden was dependent on total irradiation dose, regardless of dose rate or cell type. The findings were further validated in IR-induced secondary cancers and single cells without clonalization. Overall, our study highlights a comprehensive and clear picture of IR effects on normal mammalian genomes.

Coexpression of TP53, BIM, and PTEN Enhances the Therapeutic Efficacy of Non-Small-Cell Lung Cancer

For non-small-cell lung cancer (NSCLC), the ubiquitous occurrence of concurrent multiple genomic alterations poses challenges to single-gene therapy. To increase therapeutic efficacy, we used the branch-PCR method to develop a multigene nanovector, NP-TP53-BIM-PTEN, that carried three therapeutic gene expression cassettes for coexpression. NP-TP53-BIM-PTEN exhibited a uniform size of 104.8 ± 24.2 nm and high serum stability. In cell transfection tests, NP-TP53-BIM-PTEN could coexpress TP53, BIM, and PTEN in NCI-H1299 cells and induce cell apoptosis with a ratio of up to 94.9%. Furthermore, NP-TP53-BIM-PTEN also inhibited cell proliferation with a ratio of up to 42%. In a mouse model bearing an NCI-H1299 xenograft tumor, NP-TP53-BIM-PTEN exhibited a stronger inhibitory effect on the NCI-H1299 xenograft tumor than the other test vectors without any detectable side effects. These results exhibited the potential of NP-TP53-BIM-PTEN as an effective and safe multigene nanovector to enhance NSCLC therapy efficacy, which will provide a framework for genome therapy with multigene combinations.

Exploiting epigenetic targets to overcome taxane resistance in prostate cancer

The development of taxane resistance remains a major challenge for castration resistant prostate cancer (CR-PCa), despite the effectiveness of taxanes in prolonging patient survival. To uncover novel targets, we performed an epigenetic drug screen on taxane (docetaxel and cabazitaxel) resistant CR-PCa cells. We identified BRPF reader proteins, along with several epigenetic groups (CBP/p300, Menin-MLL, PRMT5 and SIRT1) that act as targets effectively reversing the resistance mediated by ABCB1. Targeting BRPFs specifically resulted in the resensitization of resistant cells, while no such effect was observed on the sensitive compartment. These cells were successfully arrested at the G2/M phase of cell cycle and underwent apoptosis upon BRPF inhibition, confirming the restoration of taxane susceptibility. Pharmacological inhibition of BRPFs reduced ABCB1 activity, indicating that BRPFs may be involved in an efflux-related mechanism. Indeed, ChIP-qPCR analysis confirmed binding of BRPF1 to the ABCB1 promoter suggesting direct regulation of the ABCB1 gene at the transcriptional level. RNA-seq analysis revealed that BRPF1 knockdown affects the genes enriched in mTORC1 and UPR signaling pathways, revealing potential mechanisms underlying its functional impact, which is further supported by the enhancement of taxane response through the combined inhibition of ABCB1 and mTOR pathways, providing evidence for the involvement of multiple BRPF1-regulated pathways. Beyond clinical attributes (Gleason score, tumor stage, therapy outcome, recurrence), metastatic PCa databases further supported the significance of BRPF1 in taxane resistance, as evidenced by its upregulation in taxane-exposed PCa patients.

Small polymorphisms are a source of ancestral bias in structural variant breakpoint placement

High-quality genome assemblies and sophisticated algorithms have increased sensitivity for a wide range of variant types, and breakpoint accuracy for structural variants (SVs, ≥50 bp) has improved to near base pair precision. Despite these advances, many SV breakpoint locations are subject to systematic bias affecting variant representation. To understand why SV breakpoints are inconsistent across samples, we reanalyzed 64 phased haplotypes constructed from long-read assemblies released by the Human Genome Structural Variation Consortium (HGSVC). We identify 882 SV insertions and 180 SV deletions with variable breakpoints not anchored in tandem repeats (TRs) or segmental duplications (SDs). SVs called from aligned sequencing reads increase breakpoint disagreements by 2×-16×. Sequence accuracy had a minimal impact on breakpoints, but we observe a strong effect of ancestry. We confirm that SNP and indel polymorphisms are enriched at shifted breakpoints and are also absent from variant callsets. Breakpoint homology increases the likelihood of imprecise SV calls and the distance they are shifted, and tandem duplications are the most heavily affected SVs. Because graph genome methods normalize SV calls across samples, we investigated graphs generated by two different methods and find the resulting breakpoints are subject to other technical biases affecting breakpoint accuracy. The breakpoint inconsistencies we characterize affect ∼5% of the SVs called in a human genome and can impact variant interpretation and annotation. These limitations underscore a need for algorithm development to improve SV databases, mitigate the impact of ancestry on breakpoints, and increase the value of callsets for investigating breakpoint features.

An Epigenomic fingerprint of human cancers by landscape interrogation of super enhancers at the constituent level

Super enhancers (SE), large genomic elements that activate transcription and drive cell identity, have been found with cancer-specific gene regulation in human cancers. Recent studies reported the importance of understanding the cooperation and function of SE internal components, i.e., the constituent enhancers (CE). However, there are no pan-cancer studies to identify cancer-specific SE signatures at the constituent level. Here, by revisiting pan-cancer SE activities with H3K27Ac ChIP-seq datasets, we report fingerprint SE signatures for 28 cancer types in the NCI-60 cell panel. We implement a mixture model to discriminate active CEs from inactive CEs by taking into consideration ChIP-seq variabilities between cancer samples and across CEs. We demonstrate that the model-based estimation of CE states provides improved functional interpretation of SE-associated regulation. We identify cancer-specific CEs by balancing their active prevalence with their capability of encoding cancer type identities. We further demonstrate that cancer-specific CEs have the strongest per-base enhancer activities in independent enhancer sequencing assays, suggesting their importance in understanding critical SE signatures. We summarize fingerprint SEs based on the cancer-specific statuses of their component CEs and build an easy-to-use R package to facilitate the query, exploration, and visualization of fingerprint SEs across cancers.

Analyzing somatic mutations by single-cell whole-genome sequencing

Somatic mutations are the cause of cancer and have been implicated in other, noncancerous diseases and aging. While clonally expanded mutations can be studied by deep sequencing of bulk DNA, very few somatic mutations expand clonally, and most are unique to each cell. We describe a detailed protocol for single-cell whole-genome sequencing to discover and analyze somatic mutations in tissues and organs. The protocol comprises single-cell multiple displacement amplification (SCMDA), which ensures efficiency and high fidelity in amplification, and the SCcaller software tool to call single-nucleotide variations and small insertions and deletions from the sequencing data by filtering out amplification artifacts. With SCMDA and SCcaller at its core, this protocol describes a complete procedure for the comprehensive analysis of somatic mutations in a single cell, covering (1) single-cell or nucleus isolation, (2) single-cell or nucleus whole-genome amplification, (3) library preparation and sequencing, and (4) computational analyses, including alignment, variant calling, and mutation burden estimation. Methods are also provided for mutation annotation, hotspot discovery and signature analysis. The protocol takes 12-15 h from single-cell isolation to library preparation and 3-7 d of data processing. Compared with other single-cell amplification methods or single-molecular sequencing, it provides high genomic coverage, high accuracy in single-nucleotide variation and small insertions and deletion calling from the same single-cell genome, and fewer processing steps. SCMDA and SCcaller require basic experience in molecular biology and bioinformatics. The protocol can be utilized for studying mutagenesis and genome mosaicism in normal and diseased human and animal tissues under various conditions.

Impact of Rare Structural Variant Events in Newly Diagnosed Multiple Myeloma

PURPOSE

Whole-genome sequencing (WGS) of patients with newly diagnosed multiple myeloma (NDMM) has shown recurrent structural variant (SV) involvement in distinct regions of the genome (i.e., hotspots) and causing recurrent copy-number alterations. Together with canonical immunoglobulin translocations, these SVs are recognized as "recurrent SVs." More than half of SVs were not involved in recurrent events. The significance of these "rare SVs" has not been previously examined.

EXPERIMENTAL DESIGN

In this study, we utilize 752 WGS and 591 RNA sequencing data from patients with NDMM to determine the role of rare SVs in myeloma pathogenesis.

RESULTS

Ninety-four percent of patients harbored at least one rare SV event. Rare SVs showed an SV class-specific enrichment within genes and superenhancers associated with outlier gene expression. Furthermore, known myeloma driver genes recurrently impacted by point mutations were dysregulated by rare SVs.

CONCLUSIONS

Overall, we demonstrate the association of rare SVs with aberrant gene expression supporting a potential driver role in myeloma pathogenesis.

Lung cancer in patients who have never smoked - an emerging disease

Lung cancer is the most common cause of cancer-related deaths globally. Although smoking-related lung cancers continue to account for the majority of diagnoses, smoking rates have been decreasing for several decades. Lung cancer in individuals who have never smoked (LCINS) is estimated to be the fifth most common cause of cancer-related deaths worldwide in 2023, preferentially occurring in women and Asian populations. As smoking rates continue to decline, understanding the aetiology and features of this disease, which necessitate unique diagnostic and treatment paradigms, will be imperative. New data have provided important insights into the molecular and genomic characteristics of LCINS, which are distinct from those of smoking-associated lung cancers and directly affect treatment decisions and outcomes. Herein, we review the emerging data regarding the aetiology and features of LCINS, particularly the genetic and environmental underpinnings of this disease as well as their implications for treatment. In addition, we outline the unique diagnostic and therapeutic paradigms of LCINS and discuss future directions in identifying individuals at high risk of this disease for potential screening efforts.

Aneuploidy and complex genomic rearrangements in cancer evolution

Mutational processes that alter large genomic regions occur frequently in developing tumors. They range from simple copy number gains and losses to the shattering and reassembly of entire chromosomes. These catastrophic events, such as chromothripsis, chromoplexy and the formation of extrachromosomal DNA, affect the expression of many genes and therefore have a substantial effect on the fitness of the cells in which they arise. In this review, we cover large genomic alterations, the mechanisms that cause them and their effect on tumor development and evolution.

Everolimus for Children With Recurrent or Progressive Low-Grade Glioma: Results From the Phase II PNOC001 Trial

PURPOSE

The PNOC001 phase II single-arm trial sought to estimate progression-free survival (PFS) associated with everolimus therapy for progressive/recurrent pediatric low-grade glioma (pLGG) on the basis of phosphatidylinositol 3-kinase (PI3K)/AKT/mammalian target of rapamycin (mTOR) pathway activation as measured by phosphorylated-ribosomal protein S6 and to identify prognostic and predictive biomarkers.

PATIENTS AND METHODS

Patients, age 3-21 years, with progressive/recurrent pLGG received everolimus orally, 5 mg/m2 once daily. Frequency of driver gene alterations was compared among independent pLGG cohorts of newly diagnosed and progressive/recurrent patients. PFS at 6 months (primary end point) and median PFS (secondary end point) were estimated for association with everolimus therapy.

RESULTS

Between 2012 and 2019, 65 subjects with progressive/recurrent pLGG (median age, 9.6 years; range, 3.0-19.9; 46% female) were enrolled, with a median follow-up of 57.5 months. The 6-month PFS was 67.4% (95% CI, 60.0 to 80.0) and median PFS was 11.1 months (95% CI, 7.6 to 19.8). Hypertriglyceridemia was the most common grade ≥3 adverse event. PI3K/AKT/mTOR pathway activation did not correlate with clinical outcomes (6-month PFS, active 68.4% v nonactive 63.3%; median PFS, active 11.2 months v nonactive 11.1 months; P = .80). Rare/novel KIAA1549::BRAF fusion breakpoints were most frequent in supratentorial midline pilocytic astrocytomas, in patients with progressive/recurrent disease, and correlated with poor clinical outcomes (median PFS, rare/novel KIAA1549::BRAF fusion breakpoints 6.1 months v common KIAA1549::BRAF fusion breakpoints 16.7 months; P < .05). Multivariate analysis confirmed their independent risk factor status for disease progression in PNOC001 and other, independent cohorts. Additionally, rare pathogenic germline variants in homologous recombination genes were identified in 6.8% of PNOC001 patients.

CONCLUSION

Everolimus is a well-tolerated therapy for progressive/recurrent pLGGs. Rare/novel KIAA1549::BRAF fusion breakpoints may define biomarkers for progressive disease and should be assessed in future clinical trials.

Systematic pan-cancer analysis of RNF186 with potential implications in progression and prognosis in human cancer

AIMS

Cancer remains a significant global public health issue. There is growing proof that Ring Finger Protein 186 (RNF186) may play a function in pan-cancer, however, this has not yet been thoroughly determined. This study aims to analyze RNF186 with potential implications in progression and prognosis in human cancer.

MATERIALS AND METHODS

A comprehensive bioinformatics approaches combined with experimental verification were used across 33 types of cancers in this study to conduct a pan-cancer investigation of RNF186 from the perspectives of gene expression, prognosis, genomic alterations, immunological markers, gene set, and function.

KEY FINDINGS

RNF186 is a valuable prognostic biomarker in several cancer types, especially breast invasive carcinoma (BRCA) and uterine corpus endometrial carcinoma (UCEC). The levels of RNF186 promoter methylation and genetic alterations may be responsible for some cancers' abnormal expression. Furthermore, RNF186 expression was determined to be associated with immune checkpoint genes. Analysis of RNF186-related genes revealed that proteasome and PI3K-AKT signaling pathway were primarily involved in the cellular function of RNF186. Additionally, our research first confirmed that RNF186 may function as an oncogene and contribute to cancer proliferation, migration and invasion in UCEC. In contrast, RNF186 may play an inhibitory role in BRCA progression. This function depends on the ligase activity of RNF186.

SIGNIFICANCE

This study suggests that RNF186 is a novel critical target for tumor progression in BRCA and UCEC. It reveals that RNF186 may be associated with tumor immunotherapy, which may provide an effective predictive evaluation of the prognosis of immunotherapy.

ORAOV1, CCND1, and MIR548K Are the Driver Oncogenes of the 11q13 Amplicon in Squamous Cell Carcinoma

11q13 amplification is a frequent event in human cancer and in particular in squamous cell carcinomas (SCC). Despite almost invariably spanning 10 genes, it is unclear which genetic components of the amplicon are the key driver events in SCC. A combination of computational, in vitro, ex vivo, and in vivo models leveraging efficient primary human keratinocyte genome editing by Cas9-RNP electroporation, identified ORAOV1, CCND1, and MIR548K as the critical drivers of the amplicon in head and neck SCC. CCND1 amplification drives the cell cycle in a CDK4/6/RB1-independent fashion and may confer a novel dependency on RRM2. MIR548K contributes to epithelial-mesenchymal transition. Finally, we identify ORAOV1 as an oncogene that acts likely via its ability to modulate reactive oxygen species. Thus, the 11q13 amplicon drives SCC through at least three independent genetic elements and suggests therapeutic targets for this morbid and lethal disease.

IMPLICATIONS

This work demonstrates novel mechanisms and ways to target these mechanisms underlying the most common amplification in squamous cell carcinoma, one of the most prevalent and deadly forms of human cancer.

A Multiethnic Germline-Somatic Association Database Deciphers Multilayered and Interconnected Genetic Mutations in Cancer

Inherited germline and acquired somatic alterations can both promote human tumor development. Elucidating the cooperation between somatic and germline genetic alterations that drive tumorigenesis could help inform precision cancer prevention and treatment strategies. Here, leveraging genomic genotyping and sequencing data from 9,029 patients with cancer with European, East Asian, and African ancestry, we performed a pan-cancer analysis to evaluate the associations between germline SNPs and somatic alterations, including single-nucleotide variant and small insertion/deletion mutations, copy-number variation, tumor mutational burden, and mutational signatures. Genome-wide significant germline-somatic pairs were abundant, and most of the associations were observed in one cancer type and one ancestry group. A user-friendly interactive Multiethnic Germline-Somatic Association (MGSA) database (http://wanglab-hkust.cn:3838/MGSA/) was developed, which can be used to query, browse, and download the results of the association analyses. Moreover, the MGSA database offers additional survival analysis and functional annotation. Together, this work provides a resource for uncovering the clinical and biological roles of associations between germline variants and somatic alterations in human cancer.

SIGNIFICANCE

Comprehensive analysis of connections between germline variants and somatic events in cancer offers a resource for investigating the functional significance of genetic mutations and exploring genetic factors contributing to racial disparities.

Computational validation of clonal and subclonal copy number alterations from bulk tumor sequencing using CNAqc

Copy number alterations (CNAs) are among the most important genetic events in cancer, but their detection from sequencing data is challenging because of unknown sample purity, tumor ploidy, and general intra-tumor heterogeneity. Here, we present CNAqc, an evolution-inspired method to perform the computational validation of clonal and subclonal CNAs detected from bulk DNA sequencing. CNAqc is validated using single-cell data and simulations, is applied to over 4000 TCGA and PCAWG samples, and is incorporated into the validation process for the clinically accredited bioinformatics pipeline at Genomics England. CNAqc is designed to support automated quality control procedures for tumor somatic data validation.

MAEL in human cancers and implications in prognostication and predicting benefit from immunotherapy over VEGFR/mTOR inhibitors in clear cell renal cell carcinoma: a bioinformatic analysis

Maelstrom (MAEL), a novel cancer/testis-associated gene, may facilitate the initiation and progression of human malignancies, warranting comprehensive investigations. Single-cell and tissue-bulk transcriptomic data demonstrated higher MAEL expression in testis (spermatogonia/spermatocyte), kidney (proximal tubular cell), and brain (neuron/astrocyte), and corresponding cancers, including testicular germ cell tumor, glioma, papillary renal cell carcinoma, and clear cell renal cell carcinoma (ccRCC). Of these cancers, only in ccRCC did MAEL expression exhibit associations with both recurrence-free survival and overall survival. High MAEL expression was associated with an anti-inflammatory tumor immune microenvironment and VEGFR/mTOR activation in ccRCC tissues and high sensitivities to VEGFR/PI3K-AKT-mTOR inhibitors in ccRCC cell lines. Consistent with these, low rather than high MAEL expression indicated remarkable progression-free survival benefits from immune checkpoint inhibitor (ICI)-based immunotherapies over VEGFR/mTOR inhibitors in two large phase III trials (JAVELIN Renal 101 and CheckMate-025). MAEL is a biologically and clinically significant determinant with potential for prognostication after nephrectomy and patient selection for VEGFR/mTOR inhibitors and immunotherapy-based treatments.

Identification and characterization of CLEC11A and its derived immune signature in gastric cancer

Introduction

C-type lectin domain family 11 member A (CLEC11A) was characterized as a growth factor that mainly regulates hematopoietic function and differentiation of bone cells. However, the involvement of CLEC11A in gastric cancer (GC) is not well understood.

Methods

Transcriptomic data and clinical information pertaining to GC were obtained and analyzed from publicly available databases. The relationships between CLEC11A and prognoses, genetic alterations, tumor microenvironment (TME), and therapeutic responses in GC patients were analyzed by bioinformatics methods. A CLEC11A-derived immune signature was developed and validated, and its mutational landscapes, immunological characteristics as well as drug sensitivities were explored. A nomogram was established by combining CLEC11A-derived immune signature and clinical factors. The expression and carcinogenic effects of CLEC11A in GC were verified by qRT-PCR, cell migration, invasion, cell cycle analysis, and in vivo model analysis. Myeloid-derived suppressor cells (MDSCs), regulatory T cells (Tregs), M2 macrophages, and T cells in tumor samples extracted from mice were analyzed utilizing flow cytometry analysis.

Results

CLEC11A was over-expressed in GC, and the elevated CLEC11A expression indicated an unfavorable prognosis in GC patients. CLEC11A was involved in genomic alterations and associated with the TME in GC. Moreover, elevated CLEC11A was found to reduce the benefit of immunotherapy according to immunophenoscore (IPS) and the tumor immune dysfunction, exclusion (TIDE). After validation, the CLEC11A-derived immune signature demonstrated a consistent ability to predict the survival outcomes in GC patients. A nomogram that quantifies survival probability was constructed to improve the accuracy of prognosis prediction in GC patients. Using shRNA to suppress the expression of CLEC11A led to significant inhibitions of cell cycle progression, migration, and invasion, as well as a marked reduction of in vivo tumor growth. Moreover, the flow cytometry assay showed that the knock-down of CLEC11A increased the infiltration of cytotoxic CD8+ T cells and helper CD4+ T into tumors while decreasing the percentage of M2 macrophages, MDSCs, and Tregs.

Conclusion

Collectively, our findings revealed that CLEC11A could be a prognostic and immunological biomarker in GC, and CLEC11A-derived immune signature might serve as a new option for clinicians to predict outcomes and formulate personalized treatment plans for GC patients.

Caloric restriction leads to druggable LSD1-dependent cancer stem cells expansion

Caloric Restriction (CR) has established anti-cancer effects, but its clinical relevance and molecular mechanism remain largely undefined. Here, we investigate CR's impact on several mouse models of Acute Myeloid Leukemias, including Acute Promyelocytic Leukemia, a subtype strongly affected by obesity. After an initial marked anti-tumor effect, lethal disease invariably re-emerges. Initially, CR leads to cell-cycle restriction, apoptosis, and inhibition of TOR and insulin/IGF1 signaling. The relapse, instead, is associated with the non-genetic selection of Leukemia Initiating Cells and the downregulation of double-stranded RNA (dsRNA) sensing and Interferon (IFN) signaling genes. The CR-induced adaptive phenotype is highly sensitive to pharmacological or genetic ablation of LSD1, a lysine demethylase regulating both stem cells and dsRNA/ IFN signaling. CR + LSD1 inhibition leads to the re-activation of dsRNA/IFN signaling, massive RNASEL-dependent apoptosis, and complete leukemia eradication in ~90% of mice. Importantly, CR-LSD1 interaction can be modeled in vivo and in vitro by combining LSD1 ablation with pharmacological inhibitors of insulin/IGF1 or dual PI3K/MEK blockade. Mechanistically, insulin/IGF1 inhibition sensitizes blasts to LSD1-induced death by inhibiting the anti-apoptotic factor CFLAR. CR and LSD1 inhibition also synergize in patient-derived AML and triple-negative breast cancer xenografts. Our data provide a rationale for epi-metabolic pharmacologic combinations across multiple tumors.

Predicting response to immune checkpoint blockade therapy among mismatch repair-deficient patients using mutational signatures

Despite the overall efficacy of immune checkpoint blockade (ICB) for mismatch repair deficiency (MMRD) across tumor types, a sizable fraction of patients with MMRD still do not respond to ICB. We performed mutational signature analysis of panel sequencing data (n = 95) from MMRD cases treated with ICB. We discover that T>C-rich single base substitution (SBS) signatures-SBS26 and SBS54 from the COSMIC Mutational Signatures catalog-identify MMRD patients with significantly shorter overall survival. Tumors with a high burden of SBS26 show over-expression and enriched mutations of genes involved in double-strand break repair and other DNA repair pathways. They also display chromosomal instability (CIN), likely related to replication fork instability, leading to copy number losses that trigger immune evasion. SBS54 is associated with transcriptional activity and not with CIN, defining a distinct subtype. Consistently, cancer cell lines with a high burden of SBS26 and SBS54 are sensitive to treatments targeting pathways related to their proposed etiology. Together, our analysis offers an explanation for the heterogeneous responses to ICB among MMRD patients and supports an SBS signature-based predictor as a prognostic biomarker for differential ICB response.

[A pan-cancer analysis of TTC9A expression level and its correlation with prognosis and immune microenvironment]

OBJECTIVE

To investigate the expression level of tetratricopeptide repeat protein 9A in tumors and its association with the patients' prognosis and immune infiltration.

METHODS

TTC9A expression in different tumor tissues and its association with prognosis, DNA methylation, tumor mutation burden (TMB), and microsatellite instability (MSI) were analyzed based on data from TCGA and GTEx. TIMER and xCell were used to analyze the relationship between TTC9A expression and immune infiltration. Western blotting and RT-qPCR were used to detect the expression of TTC9A in 4 types of cancer cell lines.

RESULTS

TTC9A expressions were significantly increased in many tumors and down-regulated in a few cancer types (P < 0.05). Western blotting and RT-qPCR showed that TTC9A expressions were elevated in lung, colon and liver cancer cells but decreased in bladder cancer cells. In head and neck squamous cell carcinoma, renal clear cell carcinoma, renal papillary cell carcinoma, low-grade glioma, malignant mesothelioma, and endometrial carcinoma tumors, a high expression of TTC9A was strongly correlated with better overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) (P < 0.05), but was correlated with worse OS, DSS, and PFI in lung adenocarcinoma, pancreatic adenocarcinoma, adrenal carcinoma, and rectal adenocarcinoma (P < 0.05). TTC9A hypermethylation was associated with a more favorable prognosis of glioblastoma multiforme, low- grade glioma, uveal melanoma, and ovarian plasmacytoid cystadenocarcinoma (P < 0.05) but with poor prognosis of squamous cell carcinoma of the uterine cervix and intracervical adenocarcinoma, squamous cell carcinoma of head and neck, squamous cell carcinoma of the lungs, adrenal carcinoma, and endometrial carcinoma (P < 0.05). In most of the cancer types, TTC9A was significantly correlated with the level of immune cell infiltration (P < 0.05).

CONCLUSION

TTC9A can be used as a prognostic marker for a variety of cancers and is strongly associated with TBM, MSI and immune cell infiltration.

T proliferating cells derived autophagy signature associated with prognosis and immunotherapy resistance in a pan-cancer analysis

Despite autophagy modulating tumor immunity in the tumor microenvironment (TME), the immunotherapeutic efficacy and potential mechanism of autophagy signature was not explicit. We manually curated an autophagy gene set and defined a pan-cancer autophagy signature by comparing malignant tissues and normal tissues in The Cancer Genome Atlas (TCGA) cohort. The pan-cancer autophagy signature was derived from T proliferating cells as demonstrated in multiple single-cell RNA sequencing (scRNA-seq) datasets. The pan-cancer autophagy signature could influence the cell-cell interactions in the TME and predict the responsiveness of immune checkpoint inhibitors (ICIs) in the metastatic renal cell carcinoma, non-small cell lung cancer, bladder cancer, and melanoma cohorts. Metabolism inactivation accompanied with dysregulation of autophagy was investigated with transcriptomic and proteomic data. The immunotherapeutic predictive role and mechanism regulation of the autophagy signature was validated in an in-house cohort. Our study provides valuable insights into the mechanisms of ICI resistance.

Clinical application of tumour-in-normal contamination assessment from whole genome sequencing

The unexpected contamination of normal samples with tumour cells reduces variant detection sensitivity, compromising downstream analyses in canonical tumour-normal analyses. Leveraging whole-genome sequencing data available at Genomics England, we develop a tool for normal sample contamination assessment, which we validate in silico and against minimal residual disease testing. From a systematic review of [Formula: see text] patients with haematological malignancies and sarcomas, we find contamination across a range of cancer clinical indications and DNA sources, with highest prevalence in saliva samples from acute myeloid leukaemia patients, and sorted CD3+ T-cells from myeloproliferative neoplasms. Further exploration reveals 108 hotspot mutations in genes associated with haematological cancers at risk of being subtracted by standard variant calling pipelines. Our work highlights the importance of contamination assessment for accurate somatic variants detection in research and clinical settings, especially with large-scale sequencing projects being utilised to deliver accurate data from which to make clinical decisions for patient care.

Multi-omic analyses of m5C readers reveal their characteristics and immunotherapeutic proficiency

5-methylcytosine (m5C) is a post-transcriptional RNA modification identified, m5C readers can specifically identify and bind to m5C. ALYREF and YBX1 as members of m5C readers that have garnered increasing attention in cancer research. However, comprehensive analysis of their molecular functions across pancancer are lacking. Using the TCGA and GTEx databases, we investigated the expression levels and prognostic values of ALYREF and YBX1. Additionally, we assessed the tumor microenvironment, immune checkpoint-related genes, immunomodulators, Tumor Immune Dysfunction and Exclusion (TIDE) score and drug resistance of ALYREF and YBX1. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) analyses were performed to investigate the potential functions associated with m5C readers and coexpressed genes. Aberrant expression of ALYREF and YBX1 was observed and positively associated with prognosis in KIRP, LGG and LIHC. Furthermore, the expression levels of ALYREF and YBX1 were significantly correlated with immune infiltration of the tumor microenvironment and immune-related modulators. Last, our analysis revealed significant correlations between ALYREF, YBX1 and eIFs. Our study provides a substantial understanding of m5C readers and the intricate relationship between ALYREF, YBX1, eIFs, and mRNA dynamics. Through multidimensional analysis of immune infiltration and drug sensitivity/resistance in ALYREF and YBX1, we propose a possibility for combined modality therapy utilizing m5C readers.

Research hotspots and frontiers in acral melanoma: A bibliometric analysis from 1999 to 2023

Background

Acral melanoma (AM), an aggressive subtype of melanoma with poor prognosis, has been increasingly studied. The present study aims to discuss the current status, hotspots and future directions of AM studies through visualized analysis with bibliometrics and knowledge graph.

Method

Publications related to acral melanoma from January 1999 to May 2023 were searched and retrieved from the Web of Science. Data extraction and visualization of the top 10 publications by year of publication, journal, country and core author were performed using R Studio (Version 4.3.0) and Scimago Graphica (Version 1.0.34). Co-reference graphs regarding country/region, organization, author, and keywords, as well as reference collaborative network, co-occurrence network, and references were plotted using VOSviewer (Version 1.6.19) and CiteSpace (Version 6.2.R3).

Results

A total of 1387 articles related to AM published in English from 1999 to 2023 were included in the present study. A total of 7499 authors were from 2092 organizations in 50 countries. The articles were published in 356 journals, involving 4131 keywords and 28,200 references. The 1387 articles related to AM had been cited a total of 10,014 times by the time of this study. The result showed that Journal of the American Academy of Dermatology had the largest number of citations and citation rate, with a total of 60 publications having been cited 2191 times. Having the top three productivity institutions in the world, the US is the most productive country in this field, with a total of 361 publications. The authors with the highest number of publications were Guo Jun (n = 43) and Si Lu (n = 38) from Peking University. The keyword burstiness test found that "ipilimumab", "open label", "efficacy" and "nivolumab" appeared most frequently in recent years. The co-cited reference timeline graph showed that the clustering of "advanced melanoma" and "melanocytic lesion" has been a hotspot since 2016.

Conclusions

The number of AM-related studies has been increasing. The clinical characteristics and immunotherapy of AM are still key research directions, with the US playing a leading role in this field. This bibliometric analysis found up to 1387 publications, which not only comprehensively and quantitatively reflected the research trends and hotspots, but also provided a theoretical basis for future studies of AM. Researchers can benefit from choosing the right journals and finding potential collaborators or partner institutions.

Secrets and lies of host-microbial interactions: MHC restriction and trans-regulation of T cell trafficking conceal the role of microbial agents on the edge between health and multifactorial/complex diseases

Here we critically discuss data supporting the view that microbial agents (pathogens, pathobionts or commensals alike) play a relevant role in the pathogenesis of multifactorial diseases, but their role is concealed by the rules presiding over T cell antigen recognition and trafficking. These rules make it difficult to associate univocally infectious agents to diseases' pathogenesis using the paradigm developed for canonical infectious diseases. (Cross-)recognition of a variable repertoire of epitopes leads to the possibility that distinct infectious agents can determine the same disease(s). There can be the need for sequential infection/colonization by two or more microorganisms to develop a given disease. Altered spreading of infectious agents can determine an unwanted activation of T cells towards a pro-inflammatory and trafficking phenotype, due to differences in the local microenvironment. Finally, trans-regulation of T cell trafficking allows infectious agents unrelated to the specificity of T cell to modify their homing to target organs, thereby driving flares of disease. The relevant role of microbial agents in largely prevalent diseases provides a conceptual basis for the evaluation of more specific therapeutic approaches, targeted to prevent (vaccine) or cure (antibiotics and/or Biologic Response Modifiers) multifactorial diseases.

Conformational diversity and protein-protein interfaces in drug repurposing in Ras signaling pathway

We focus on drug repurposing in the Ras signaling pathway, considering structural similarities of protein-protein interfaces. The interfaces formed by physically interacting proteins are found from PDB if available and via PRISM (PRotein Interaction by Structural Matching) otherwise. The structural coverage of these interactions has been increased from 21 to 92% using PRISM. Multiple conformations of each protein are used to include protein dynamics and diversity. Next, we find FDA-approved drugs bound to structurally similar protein-protein interfaces. The results suggest that HIV protease inhibitors tipranavir, indinavir, and saquinavir may bind to EGFR and ERBB3/HER3 interface. Tipranavir and indinavir may also bind to EGFR and ERBB2/HER2 interface. Additionally, a drug used in Alzheimer's disease can bind to RAF1 and BRAF interface. Hence, we propose a methodology to find drugs to be potentially used for cancer using a dataset of structurally similar protein-protein interface clusters rather than pockets in a systematic way.

Large tandem duplications in cancer result from transcription and DNA replication collisions

Despite the abundance of somatic structural variations (SVs) in cancer, the underlying molecular mechanisms of their formation remain unclear. Here, we use 6,193 whole-genome sequenced tumors to study the contributions of transcription and DNA replication collisions to genome instability. After deconvoluting robust SV signatures in three independent pan-cancer cohorts, we detect transcription-dependent replicated-strand bias, the expected footprint of transcription-replication collision (TRC), in large tandem duplications (TDs). Large TDs are abundant in female-enriched, upper gastrointestinal tract and prostate cancers. They are associated with poor patient survival and mutations in TP53, CDK12, and SPOP. Upon inactivating CDK12, cells display significantly more TRCs, R-loops, and large TDs. Inhibition of G2/M checkpoint proteins, such as WEE1, CHK1, and ATR, selectively inhibits the growth of cells deficient in CDK12. Our data suggest that large TDs in cancer form due to TRCs, and their presence can be used as a biomarker for prognosis and treatment.

Evaluating topography of mutational signatures with SigProfilerTopography

The mutations found in a cancer genome are shaped by diverse processes, each displaying a characteristic mutational signature that may be influenced by the genome's architecture. While prior analyses have evaluated the effect of topographical genomic features on mutational signatures, there has been no computational tool that can comprehensively examine this interplay. Here, we present SigProfilerTopography, a Python package that allows evaluating the effect of chromatin organization, histone modifications, transcription factor binding, DNA replication, and DNA transcription on the activities of different mutational processes. SigProfilerTopography elucidates the unique topographical characteristics of mutational signatures, unveiling their underlying biological and molecular mechanisms.

Multiple DNA repair pathways prevent acetaldehyde-induced mutagenesis in yeast

Acetaldehyde is the primary metabolite of alcohol and is present in many environmental sources including tobacco smoke. Acetaldehyde is genotoxic, whereby it can form DNA adducts and lead to mutagenesis. Individuals with defects in acetaldehyde clearance pathways have increased susceptibility to alcohol-associated cancers. Moreover, a mutation signature specific to acetaldehyde exposure is widespread in alcohol and smoking-associated cancers. However, the pathways that repair acetaldehyde-induced DNA damage and thus prevent mutagenesis are vaguely understood. Here, we used Saccharomyces cerevisiae to systematically delete genes in each of the major DNA repair pathways to identify those that alter acetaldehyde-induced mutagenesis. We found that deletion of the nucleotide excision repair (NER) genes, RAD1 or RAD14, led to an increase in mutagenesis upon acetaldehyde exposure. Acetaldehyde-induced mutations were dependent on translesion synthesis as well as DNA inter-strand crosslink (ICL) repair in Δrad1 strains. Moreover, whole genome sequencing of the mutated isolates demonstrated an increase in C→A changes coupled with an enrichment of gCn→A changes in the acetaldehyde-treated Δrad1 isolates. The gCn→A mutation signature has been shown to be diagnostic of acetaldehyde exposure in yeast and in human cancers. We also demonstrated that the deletion of the two DNA-protein crosslink (DPC) repair proteases, WSS1 and DDI1, also led to increased acetaldehyde-induced mutagenesis. Defects in base excision repair (BER) led to a mild increase in mutagenesis, while defects in mismatch repair (MMR), homologous recombination repair (HR) and post replicative repair pathways did not impact mutagenesis upon acetaldehyde exposure. Our results in yeast were further corroborated upon analysis of whole exome sequenced liver cancers, wherein, tumors with defects in ERCC1 and ERCC4 (NER), FANCD2 (ICL repair) or SPRTN (DPC repair) carried a higher gCn→A mutation load than tumors with no deleterious mutations in these genes. Our findings demonstrate that multiple DNA repair pathways protect against acetaldehyde-induced mutagenesis.

A Practical Approach for Targeting Structural Variants Genome-wide in Plasma Cell-free DNA

Plasma cell-free DNA (cfDNA) is a promising source of gene mutations for cancer detection by liquid biopsy. However, no current tests interrogate chromosomal structural variants (SVs) genome-wide. Here, we report a simple molecular and sequencing workflow called Genome-wide Analysis of Palindrome Formation (GAPF-seq) to probe DNA palindromes, a type of SV that often demarcates gene amplification. With low-throughput next-generation sequencing and automated machine learning, tumor DNA showed skewed chromosomal distributions of high-coverage 1-kb bins (HCBs), which differentiated 39 breast tumors from matched normal DNA with an average Area Under the Curve (AUC) of 0.9819. A proof-of-concept liquid biopsy study using cfDNA from prostate cancer patients and healthy individuals yielded an average AUC of 0.965. HCBs on the X chromosome emerged as a determinant feature and were associated with androgen receptor gene amplification. As a novel agnostic liquid biopsy approach, GAPF-seq could fill the technological gap offering unique cancer-specific SV profiles.

Integrative Analyses of Pyrimidine Salvage Pathway-Related Genes Revealing the Associations Between UPP1 and Tumor Microenvironment

Background

The pyrimidine salvage pathway plays a critical role in tumor progression and patient outcomes. The roles of pyrimidine salvage pathway-related genes (PSPGs) in cancer, however, are not fully understood. This study aims to depict the characteristics of PSPGs across various cancers.

Methods

An integrative pan-cancer analysis of six PSPGs (CDA, UCK1, UCK2, UCKL1, UPP1, and UPP2) was conducted using TCGA data, single-cell RNA sequencing datasets, and patient samples. Single-cell transcriptome analysis and RT-qPCR were used to validate the relation between UPP1 and cytokines. Flow cytometry was performed to validate the role of UPP1 in immune checkpoint regulation. The correlation between UPP1 and tumor associated neutrophils (TAN) were investigated and validated by single-cell transcriptome analysis and tissue microarrays (TMAs).

Results

PSPGs showed low mutation rates but significant copy number variations, particularly amplifications in UCKL1, UPP1, and UCK2 across various cancers. DNA methylation patterns varied, with notable negative correlations between methylation and gene expression in UPP1. PSPGs were broadly up-regulated in multiple cancers, with correlations to clinical staging and prognosis. Proteomic data further confirmed these findings. Functional analysis revealed PSPGs' associations with tumor proliferation, metastasis, and various signaling pathways. UPP1 showed strong correlations with the tumor microenvironment (TME), particularly with cytokines, immune checkpoints, and various immune cells. Single-cell transcriptome analysis confirmed these associations, highlighting UPP1's influence on cytokine expression and immune checkpoint regulation. In esophageal squamous cell carcinoma (ESCC), UPP1-high tumor cells were significantly associated with immunosuppressive cells in the TME. Spatial analysis using TMAs revealed that UPP1+ tumor cells were predominantly located at the invasive margin and closely associated with neutrophils, correlating with poorer patient prognosis.

Conclusion

Our study depicted the multi-dimensional view of PSPGs in cancer, with a particular focus on UPP1's role in the TME. Targeting UPP1 holds promise as a potential strategy for cancer therapy.

Melvin is a conversational voice interface for cancer genomics data

Melvin is a multi-modal Amazon Alexa skill that allows users to quickly explore cancer genomics data from TCGA through simple conversations.