The role of distinct APOBEC/ADAR mRNA levels in mutational signatures linked to aging and ultraviolet radiation.

The APOBEC/AID family is known for its mutator activity, and recent evidence also supports the potential impact of ADARs. Furthermore, the mutator impacts of APOBEC/ADAR mutations have not yet been investigated. Assessment of pancancer TCGA exomes identified enriched somatic variants among exomes with nonsynonymous APOBEC1, APOBEC3B, APOBEC3C, ADAR, and ADARB1 mutations, compared to exomes with synonymous ones. Principal component (PC) analysis reduced the number of potential players to eight in cancer exomes/genomes, and to five in cancer types. Multivariate regression analysis was used to assess the impact of the PCs on each COSMIC mutational signature among pancancer exomes/genomes and particular cancers, identifying several novel links, including SBS17b, SBS18, and ID7 mainly determined by APOBEC1 mRNA levels; SBS40, ID1, and ID2 by age; SBS3 and SBS16 by APOBEC3A/APOBEC3B mRNA levels; ID5 and DBS9 by DNA repair/replication (DRR) defects; and SBS7a-d, SBS38, ID4, ID8, ID13, and DBS1 by ultraviolet (UV) radiation/ADARB1 mRNA levels. APOBEC/ADAR mutations appeared to potentiate the impact of DRR defects on several mutational signatures, and some factors seemed to inversely affect certain signatures. These findings potentially implicate certain APOBEC/ADAR mutations/mRNA levels in distinct mutational signatures, particularly APOBEC1 mRNA levels in aging-related signatures and ADARB1 mRNA levels in UV radiation-related signatures.

Are Next-Generation Pathogenicity Predictors Applicable to Cancer?

Next-generation pathogenicity predictors are designed to identify pathogenic mutations in genetic disorders but are increasingly used to detect driver mutations in cancer. Despite this, their suitability for cancer is not fully established. Here we have assessed the effectiveness of next-generation pathogenicity predictors when applied to cancer by using a comprehensive experimental benchmark of cancer driver and neutral mutations. Our findings indicate that state-of-the-art methods AlphaMissense and VARITY demonstrate commendable performance despite generally underperforming compared to cancer-specific methods. This is notable considering that these methods do not explicitly incorporate cancer-related data in their training and have made concerted efforts to prevent data leakage from the human-curated training and test sets. Nevertheless, it should be mentioned that a significant limitation of using pathogenicity predictors for cancer arises from their inability to detect cancer potential driver mutations specific for a particular cancer type.

The mutagenic consequences of defective DNA repair.

Multiple separate repair mechanisms safeguard the genome against various types of DNA damage, and their failure can increase the rate of spontaneous mutagenesis. The malfunction of distinct repair mechanisms leads to genomic instability through different mutagenic processes. For example, defective mismatch repair causes high base substitution rates and microsatellite instability, whereas homologous recombination deficiency is characteristically associated with deletions and chromosome instability. This review presents a comprehensive collection of all mutagenic phenotypes associated with the loss of each DNA repair mechanism, drawing on data from a variety of model organisms and mutagenesis assays, and placing greatest emphasis on systematic analyses of human cancer datasets. We describe the latest theories on the mechanism of each mutagenic process, often explained by reliance on an alternative repair pathway or the error-prone replication of unrepaired, damaged DNA. Aided by the concept of mutational signatures, the genomic phenotypes can be used in cancer diagnosis to identify defective DNA repair pathways.

Deciphering principles of nucleosome interactions and impact of cancer-associated mutations from comprehensive interaction network analysis.

Nucleosomes represent hubs in chromatin organization and gene regulation and interact with a plethora of chromatin factors through different modes. In addition, alterations in histone proteins such as cancer mutations and post-translational modifications have profound effects on histone/nucleosome interactions. To elucidate the principles of histone interactions and the effects of those alterations, we developed histone interactomes for comprehensive mapping of histone-histone interactions (HHIs), histone-DNA interactions (HDIs), histone-partner interactions (HPIs) and DNA-partner interactions (DPIs) of 37 organisms, which contains a total of 3808 HPIs from 2544 binding proteins and 339 HHIs, 100 HDIs and 142 DPIs across 110 histone variants. With the developed networks, we explored histone interactions at different levels of granularities (protein-, domain- and residue-level) and performed systematic analysis on histone interactions at a large scale. Our analyses have characterized the preferred binding hotspots on both nucleosomal/linker DNA and histone octamer and unraveled diverse binding modes between nucleosome and different classes of binding partners. Last, to understand the impact of histone cancer-associated mutations on histone/nucleosome interactions, we complied one comprehensive cancer mutation dataset including 7940 cancer-associated histone mutations and further mapped those mutations onto 419,125 histone interactions at the residue level. Our quantitative analyses point to histone cancer-associated mutations' strongly disruptive effects on HHIs, HDIs and HPIs. We have further predicted 57 recurrent histone cancer mutations that have large effects on histone/nucleosome interactions and may have driver status in oncogenesis.

Hotspot Cancer Mutation Impairs KAT8-mediated Nucleosomal Histone Acetylation.

KAT8 is an evolutionarily conserved lysine acetyltransferase that catalyzes histone acetylation at H4K16 or H4K5 and H4K8 through distinct protein complexes. It plays a pivotal role in male X chromosome dosage compensation in Drosophila and is implicated in the regulation of diverse cellular processes in mammals. Mutations and dysregulation of KAT8 have been reported in human neurodevelopmental disorders and various cancers. However, the precise mechanisms by which these mutations disrupt KAT8's normal function, leading to disease pathogenesis, remain largely unknown. In this study, we focus on a hotspot missense cancer mutation, the R98W point mutation within the Tudor-knot domain. Our study reveals that the R98W mutation leads to a reduction in global H4K16ac levels in cells and downregulates the expression of target genes. Mechanistically, we demonstrate that R98 is essential for KAT8-mediated acetylation of nucleosomal histones by modulating substrate accessibility.

Molecular Mechanism of Mutational Disruption of DCLK1 Autoinhibition Provides a Rationale for Inhibitor Screening.

Doublecortin-like kinase 1 (DCLK1) is a prominent kinase involved in carcinogenesis, serving as a diagnostic marker for early cancer detection and prevention, as well as a target for cancer therapy. Extensive research efforts have been dedicated to understanding its role in cancer development and designing selective inhibitors. In our previous work, we successfully determined the crystal structure of DCLK1 while it was bound to its autoinhibitory domain (AID) at the active site. By analyzing this structure, we were able to uncover the intricate molecular mechanisms behind specific cancer-causing mutations in DCLK1. Utilizing molecular dynamics simulations, we discovered that these mutations disrupt the smooth assembly of the AID, particularly affecting the R2 helix, into the kinase domain (KD). This disruption leads to the exposure of the D533 residue of the DFG (Asp-Phe-Gly) motif in the KD, either through steric hindrance, the rearrangement of electrostatic interactions, or the disruption of local structures in the AID. With these molecular insights, we conducted a screening process to identify potential small-molecule inhibitors that could bind to DCLK1 through an alternative binding mode. To assess the binding affinity of these inhibitors to the KD of DCLK1, we performed calculations on their binding energy and conducted SPR experiments. We anticipate that our study will contribute novel perspectives to the field of drug screening and optimization, particularly in targeting DCLK1.

SASH1: A Novel Eph Receptor Partner and Insights into SAM-SAM Interactions.

The Eph (erythropoietin-producing human hepatocellular) receptor family, the largest subclass of receptor tyrosine kinases (RTKs), plays essential roles in embryonic development and neurogenesis. The intracellular Sterile Alpha Motif (SAM) domain presents a critical structural feature that distinguishes Eph receptors from other RTKs and participates in recruiting and binding downstream molecules. This study identified SASH1 (SAM and SH3 domain containing 1) as a novel Eph receptor-binding partner through SAM-SAM domain interactions. Our comprehensive biochemical analyses revealed that SASH1 selectively interacts with Eph receptors via its SAM1 domain, displaying the highest affinity for EphA8. The high-resolution crystal structure of the EphA8-SASH1 complex provided insights into the specific intermolecular interactions between these proteins. Cellular assays confirmed that EphA8 and SASH1 co-localize and co-precipitate in mammalian cells, with cancer mutations (EphA8 R942H or G978D) impairing this interaction. We demonstrated that SAM-SAM interaction is critical for SASH1-mediated regulation of EphA8 kinase activity, shedding new light on the Eph signaling pathway and expanding our understanding of the molecular basis of the tumor suppressor gene SASH1.

Leveraging Gene Redundancy to Find New Histone Drivers in Cancer.

Histones play a critical role in chromatin function but are susceptible to mutagenesis. In fact, numerous mutations have been observed in several cancer types, and a few of them have been associated with carcinogenesis. Histones are peculiar, as they are encoded by a large number of genes, and the majority of them are clustered in three regions of the human genome. In addition, their replication and expression are tightly regulated in a cell. Understanding the etiology of cancer mutations in histone genes is impeded by their functional and sequence redundancy, their unusual genomic organization, and the necessity to be rapidly produced during cell division. Here, we collected a large data set of histone gene mutations in cancer and used it to investigate their distribution over 96 human histone genes and 68 different cancer types. This analysis allowed us to delineate the factors influencing the probability of mutation accumulation in histone genes and to detect new histone gene drivers. Although no significant difference in observed mutation rates between different histone types was detected for the majority of cancer types, several cancers demonstrated an excess or depletion of mutations in histone genes. As a consequence, we identified seven new histone genes as potential cancer-specific drivers. Interestingly, mutations were found to be distributed unevenly in several histone genes encoding the same protein, pointing to different factors at play, which are specific to histone function and genomic organization. Our study also elucidated mutational processes operating in genomic regions harboring histone genes, highlighting POLE as a factor of potential interest.

Tracking and blocking interdependencies of cellular BRAF-MEK oncokinase activities.

The selective targeting of mutated kinases in cancer therapies has the potential to improve therapeutic success and thereby the survival of patients. In the case of melanoma, the constitutively active MAPK pathway is targeted by a combinatorial inhibition of BRAF and MEK activities. These MAPK pathway players may display patient-specific differences in the onco-kinase mutation spectrum, which needs to be considered for the design of more efficient personalized therapies. Here, we extend a bioluminescence-based kinase conformation biosensor (KinCon) to allow for live-cell tracking of interconnected kinase activity states. First, we show that common MEK1 patient mutations promote a structural rearrangement of the kinase to an opened and active conformation. This effect was reversible by the binding of MEK inhibitors to mutated MEK1, as shown in biosensor assays and molecular dynamics simulations. Second, we implement a novel application of the KinCon technology for tracking the simultaneous, vertical targeting of the two functionally linked kinases BRAF and MEK1. Thus, we demonstrate that, in the presence of constitutively active BRAF-V600E, specific inhibitors of both kinases are efficient in driving MEK1 into a closed, inactive conformation state. We compare current melanoma treatments and show that combinations of BRAFi and MEKi display a more pronounced structural change of the drug sensor than the respective single agents, thereby identifying synergistic effects among these drug combinations. In summary, we depict the extension of the KinCon biosensor technology to systematically validate, anticipate, and personalize tailored drug arrangements using a multiplexed setup.

MYO10 regulates genome stability and cancer inflammation through mediating mitosis.

Genomic instability can promote inflammation and tumor development. Previous research revealed an unexpected layer of regulation of genomic instability by a cytoplasmic protein MYO10; however, the underlying mechanism remained unclear. Here, we report a protein stability-mediated mitotic regulation of MYO10 in controlling genome stability. We characterized a degron motif and phosphorylation residues in the degron that mediate ß-TrCP1-dependent MYO10 degradation. The level of phosphorylated MYO10 protein transiently increases during mitosis, which is accompanied by a spatiotemporal cellular localization change first accumulating at the centrosome then at the midbody. Depletion of MYO10 or expression of MYO10 degron mutants, including those found in cancer patients, disrupts mitosis, increases genomic instability and inflammation, and promotes tumor growth; however, they also increase the sensitivity of cancer cells to Taxol. Our studies demonstrate a critical role of MYO10 in mitosis progression, through which it regulates genome stability, cancer growth, and cellular response to mitotic toxins.

Breast cancer genetics and risk assessment: an overview for the clinician.

Breast cancer is the most common cancer in women globally with enormous associated morbidity, mortality and economic impact. Prevention of breast cancer is a global public health imperative. To date, most of our global efforts have been directed at expanding population breast cancer screening programs for early cancer detection and not at breast cancer prevention efforts. It is imperative that we change the paradigm. As with other diseases, prevention of breast cancer starts with identification of individuals at high risk, and for breast cancer this requires improved identification of individuals who carry a hereditary cancer mutation associated with an elevated risk of breast cancer, and identification of others who are at high risk due to non-genetic, established modifiable and non-modifiable factors. This article will review basic breast cancer genetics and the most common hereditary breast cancer mutations associated with increased risk. We will also discuss the other non-genetic modifiable and non-modifiable breast cancer risk factors, available risk assessment models and an approach to incorporating screening for genetic mutation carriers and identifying high-risk women in clinical practice. A discussion of guidelines for enhanced screening, chemoprevention and surgical management of high-risk women is beyond the scope of this review.

The R736H cancer mutation in DNMT3A modulates the properties of the FF-subunit interface.

The DNMT3A DNA methyltransferase is an important epigenetic enzyme that is frequently mutated in cancers, particularly in AML. The heterozygous R736H mutation in the FF-interface of the tetrameric enzyme is the second most frequently observed DNMT3A cancer mutation, but its pathogenic mechanism is unclear. We show here that R736H leads to a moderate reduction in catalytic activity of 20-40% depending on the substrate, but no changes in CpG specificity, flanking sequence preferences and subnuclear localization. Strikingly, R736H showed a very strong stimulation by DNMT3L and the R736H/DNMT3L complex was 3-fold more active than WT/DNMT3L. Similarly, formation of mixed R736H/DNMT3A WT FF-interfaces led to an increased activity. R736H/DNMT3L and mixed R736H/DNMT3A WT FF-interfaces were less stable than interfaces not involving R736H, suggesting that an increased flexibility of the mixed interfaces stimulates catalytic activity. Our data suggest that aberrant activity of DNMT3A R736H may lead to DNA hypermethylation in cancer cells which could cause changes in gene expression.

Functional and embedding feature analysis for pan-cancer classification.

With the increasing number of people suffering from cancer, this illness has become a major health problem worldwide. Exploring the biological functions and signaling pathways of carcinogenesis is essential for cancer detection and research. In this study, a mutation dataset for eleven cancer types was first obtained from a web-based resource called cBioPortal for Cancer Genomics, followed by extracting 21,049 features from three aspects: relationship to GO and KEGG (enrichment features), mutated genes learned by word2vec (text features), and protein-protein interaction network analyzed by node2vec (network features). Irrelevant features were then excluded using the Boruta feature filtering method, and the retained relevant features were ranked by four feature selection methods (least absolute shrinkage and selection operator, minimum redundancy maximum relevance, Monte Carlo feature selection and light gradient boosting machine) to generate four feature-ranked lists. Incremental feature selection was used to determine the optimal number of features based on these feature lists to build the optimal classifiers and derive interpretable classification rules. The results of four feature-ranking methods were integrated to identify key functional pathways, such as olfactory transduction (hsa04740) and colorectal cancer (hsa05210), and the roles of these functional pathways in cancers were discussed in reference to literature. Overall, this machine learning-based study revealed the altered biological functions of cancers and provided a reference for the mechanisms of different cancers.

m6A-TSHub: Unveiling the Context-specific m6A Methylation and m6A-affecting Mutations in 23 Human Tissues.

As the most pervasive epigenetic marker present on mRNA and lncRNA, N6-methyladenosine (m6A) RNA methylation has been shown to participate in essential biological processes. Recent studies have revealed the distinct patterns of m6A methylome across human tissues, and a major challenge remains in elucidating the tissue-specific presence and circuitry of m6A methylation. We present here a comprehensive online platform m6A-TSHub for unveiling the context-specific m6A methylation and genetic mutations that potentially regulate m6A epigenetic mark. m6A-TSHub consists of four core components, including: (1) m6A-TSDB, a comprehensive database of 184,554 functionally annotated m6A sites derived from 23 human tissues and 499,369 m6A sites from 25 tumor conditions, respectively; (2) m6A-TSFinder, a web server for high-accuracy prediction of m6A methylation sites within a specific tissue from RNA sequences, which was constructed using multi-instance deep neural networks with gated attention; (3) m6A-TSVar, a web server for assessing the impact of genetic variants on tissue-specific m6A RNA modifications; and (4) m6A-CAVar, a database of 587,983 The Cancer Genome Atlas (TCGA) cancer mutations (derived from 27 cancer types) that were predicted to affect m6A modifications in the primary tissue of cancers. The database should make a useful resource for studying the m6A methylome and the genetic factors of epitranscriptome disturbance in a specific tissue (or cancer type). m6A-TSHub is accessible at www.xjtlu.edu.cn/biologicalsciences/m6ats.

i-CRISPR: a personalized cancer therapy strategy through cutting cancer-specific mutations.

Developing a strategy to specifically kill cancer cells without inducing obvious damage to normal cells may be of great clinical significance for cancer treatment. In the present study, we developed a new precise personalized strategy named "i-CRISPR" for cancer treatment through adding DNA damage repair inhibitors(i) and inducing cancer cell-specific DNA double strand breaks by CRISPR. Through in vitro and in vivo experiments, we confirmed the efficacy of this strategy in multiple cancer models and revealed the mechanism of cell death. Our strategy might provide a novel concept for precise cancer therapy.

Radioresistance of Non-Small Cell Lung Cancers and Therapeutic Perspectives.

Survival in unresectable locally advanced stage non-small cell lung cancer (NSCLC) patients remains poor despite chemoradiotherapy. Recently, adjuvant immunotherapy improved survival for these patients but we are still far from curing most of the patients with only a 57% survival remaining at 3 years. This poor survival is due to the resistance to chemoradiotherapy, local relapses, and distant relapses. Several biological mechanisms have been found to be involved in the chemoradioresistance such as cancer stem cells, cancer mutation status, or the immune system. New drugs to overcome this radioresistance in NSCLCs have been investigated such as radiosensitizer treatments or immunotherapies. Different modalities of radiotherapy have also been investigated to improve efficacity such as dose escalation or proton irradiations. In this review, we focused on biological mechanisms such as the cancer stem cells, the cancer mutations, the antitumor immune response in the first part, then we explored some strategies to overcome this radioresistance in stage III NSCLCs with new drugs or radiotherapy modalities.

Cancer mutation profiles predict ICIs efficacy in patients with non-small cell lung cancer.

Although immune checkpoint inhibitors (ICIs) have produced remarkable responses in non-small cell lung cancer (NSCLC) patients, receivers still have a relatively low response rate. Initial response assessment by conventional imaging and evaluation criteria is often unable to identify whether patients can achieve durable clinical benefit from ICIs. Overall, there are sparse effective biomarkers identified to screen NSCLC patients responding to this therapy. A lot of studies have reported that patients with specific gene mutations may benefit from or resist to immunotherapy. However, the single gene mutation may be not effective enough to predict the benefit from immunotherapy for patients. With the advancement in sequencing technology, further studies indicate that many mutations often co-occur and suggest a drastic transformation of tumour microenvironment phenotype. Moreover, co-mutation events have been reported to synergise to activate or suppress signalling pathways of anti-tumour immune response, which also indicates a potential target for combining intervention. Thus, the different mutation profile (especially co-mutation) of patients may be an important concern for predicting or promoting the efficacy of ICIs. However, there is a lack of comprehensive knowledge of this field until now. Therefore, in this study, we reviewed and elaborated the value of cancer mutation profile in predicting the efficacy of immunotherapy and analysed the underlying mechanisms, to provide an alternative way for screening dominant groups, and thereby, optimising individualised therapy for NSCLC patients.

Detection of Cancer Mutations by Urine Liquid Biopsy as a Potential Tool in the Clinical Management of Bladder Cancer Patients.

The standard diagnostic and follow-up examination for bladder cancer is diagnostic cystoscopy, an invasive test that requires compliance for a long period. Urine cytology and recent biomarkers come short of replacing cystoscopy. Urine liquid biopsy promises to solve this problem and potentially allows early detection, evaluation of treatment efficacy, and surveillance. A previous study reached 52-68% sensitivity using small-panel sequencing but could increase sensitivity to 68-83% by adding aneuploidy and promoter mutation detection. Here, we explore whether a large 127-gene panel alone is sufficient to detect tumor mutations in urine from bladder cancer patients. We recruited twelve bladder cancer patients, obtained preoperative and postoperative urine samples, and successfully analyzed samples from eleven patients. In ten patients, we found at least one mutation in bladder-cancer-associated genes, i.e., a promising sensitivity of 91%. In total, we identified 114 variants, of which 90 were predicted as nonbenign, 30% were associated with cancer, and 13% were actionable according to the CIViC database. Sanger sequencing of the patients' formalin-fixed, paraffin-embedded (FFPE) tumor tissues confirmed the findings. We concluded that incorporating urine liquid biopsy is a promising strategy in the management of bladder cancer patients.

Interdisciplinary Study of the Effects of Dipeptidyl-Peptidase III Cancer Mutations on the KEAP1-NRF2 Signaling Pathway.

Dipeptidyl peptidase III (DPP III) is associated with cancer progression via interaction with KEAP1, leading to upregulation of the KEAP1-NRF2 oxidative stress pathway. Numerous DPP III mutations have been found in human tumor genomes, and it is suggested that some of them may alter affinity for KEAP1. One such example is the DPP III-R623W variant, which in our previous study showed much higher affinity for the Kelch domain of KEAP1 than the wild-type protein. In this work, we have investigated the effects of this mutation in cultured cells and the effects of several other DPP III mutations on the stability of KEAP1-DPP III complex using an interdisciplinary approach combining biochemical, biophysical and molecular biology methods with computational studies. We determined the affinity of the DPP III variants for the Kelch domain experimentally and by molecular modeling, as well as the effects of the R623W on the expression of several NRF2-controlled genes. We confirmed that the R623W variant upregulates NQO1 expression at the transcriptional level. This supports the hypothesis from our previous study that the increased affinity of the R623W variant for KEAP1 leads to upregulation of the KEAP1-NRF2 pathway. These results provide a new perspective on the involvement of DPP III in cancer progression and prognosis.

Diagnostic and economic value of biomarker testing for targetable mutations in non-small-cell lung cancer: a literature review.

We aimed to assess the diagnostic and economic value of next-generation sequencing (NGS) versus single-gene testing, and of liquid biopsy (LBx) versus tissue biopsy (TBx) in non-small-cell lung cancer biomarker testing through literature review. Embase and MEDLINE were searched to identify relevant studies (n = 43) from 2015 to 2020 in adults with advanced non-small-cell lung cancer. For NGS versus single-gene testing, concordance was 70-99% and sensitivity was 86-100%. For LBx versus TBx, specificity was 43-100% and sensitivity was ≥60%. Turnaround times were longer for NGS versus single-gene testing (but not vs sequential testing) and faster for LBx versus TBx. NGS was cost-effective, and LBx reduced US per-patient costs. NGS versus single-gene testing and LBx versus TBx were concordant. NGS and LBx may be cost-effective for initial screening.

Plain language summary Patients with lung cancer with specific genetic mutations can benefit from medications that are specific to those mutations, known as targetable mutations. There are many methods to test for specific genetic mutations in patients with lung cancer. To detect genetic mutations, doctors can test the blood or urine, or they can test biopsy tissue; a small piece of the tumor removed from the lung. These tests can either look for mutations in one specific gene at a time, or they can use technology that reads the entire DNA sequence to observe multiple genes at once. In this review, we examined scientific reports to answer important questions about using genetic testing to find targetable mutations in patients with lung cancer. How accurate are different genetic tests? How fast can doctors get results from different genetic tests? How much do different genetic tests cost? We found that reading the entire DNA sequence was as accurate as testing one specific gene. Reading the entire DNA sequence takes more time than testing one specific gene, but it might reduce overall costs. Testing blood or urine was not as accurate as testing tissue, but it took less time for doctors to receive genetic test results and reduced costs.