The COSMIC (Catalogue of Somatic Mutations in Cancer) database and website

Targeted genetic and small molecule disruption of N-Ras CaaX cleavage alters its localization and oncogenic potential

Ras GTPases and other CaaX proteins undergo multiple post-translational modifications at their carboxyl-terminus. These events initiate with prenylation of a cysteine and are followed by endoproteolytic removal of the 'aaX' tripeptide and carboxylmethylation. Some CaaX proteins are only subject to prenylation, however, due to the presence of an uncleavable sequence. In this study, uncleavable sequences were used to stage Ras isoforms in a farnesylated and uncleaved state to address the impact of CaaX proteolysis on protein localization and function. This targeted strategy is more specific than those that chemically inhibit the Rce1 CaaX protease or delete the RCE1 gene because global abrogation of CaaX proteolysis impacts the entire CaaX protein proteome and effects cannot be attributed to any specific CaaX protein of the many concurrently affected. With this targeted strategy, clear mislocalization and reduced activity of farnesylated and uncleaved Ras isoforms was observed. In addition, new peptidomimetics based on cleavable Ras CaaX sequences and the uncleavable CAHQ sequence were synthesized and tested as Rce1 inhibitors using in vitro and cell-based assays. Consistently, these non-hydrolyzable peptidomimetic Rce1 inhibitors recapitulate Ras mislocalization effects when modeled on cleavable but not uncleavable CaaX sequences. These findings indicate that a prenylated and uncleavable CaaX sequence, which can be easily applied to a wide range of mammalian CaaX proteins, can be used to probe the specific impact of CaaX proteolysis on CaaX protein properties under conditions of an otherwise normally processed CaaX protein proteome.

Genomic landscape of comprehensive genomic profiling in patients with malignant solid tumors in Japan

BACKGROUND

Comprehensive genomic profiling (CGP) can aid the discovery of clinically useful, candidate antitumor agents; however, the variant annotations sometimes differ among the various types of CGP tests as well as the public database. The aim of this study is to clarify the genomic landscape of evaluating detected variants in patients with a malignant solid tumor.

METHODS

The present, cross-sectional study used data from 57,084 patients with a malignant solid tumor who underwent CGP at the Center for Cancer Genomics and Advanced Therapeutics (C-CAT) between June 1, 2019 and August 18, 2023. The pathogenicity of the variants was annotated using public databases.

RESULTS

As a result of re-annotation of the detected variants, 20.1% were pathogenic and 1.4% were benign. The mean number of pathogenic variants was 4.30 (95% confidence interval: 4.27-4.32) per patient. Of the entire cohort, 5.7% had no pathogenic variant. The co-occurrence of the genes depended on the tumor type. Germline findings were detected in 6.2%, 8.8%, and 15.8% of the patients using a tumor/normal panel, tumor-only panel, and liquid panel, respectively, with the most common gene being BRCA2 followed by TP53 and BRCA1.

CONCLUSIONS

The detected variants should be re-annotated because several benign variants or variants of unknown significance were included in the CGP, and the genomic landscape derived from these results will help researchers and physicians interpret the results of CGP tests. The method of extracting presumptive, germline, pathogenic variants from patients using a tumor-only panel or circulating tumor DNA panel requires improvement.

Context dependent activity of p63-bound gene regulatory elements

The p53 family of transcription factors regulate numerous organismal processes including the development of skin and limbs, ciliogenesis, and preservation of genetic integrity and tumor suppression. p53 family members control these processes and gene expression networks through engagement with DNA sequences within gene regulatory elements. Whereas p53 binding to its cognate recognition sequence is strongly associated with transcriptional activation, p63 can mediate both activation and repression. How the DNA sequence of p63-bound gene regulatory elements is linked to these varied activities is not yet understood. Here, we use massively parallel reporter assays (MPRA) in a range of cellular and genetic contexts to investigate the influence of DNA sequence on p63-mediated transcription. Most regulatory elements with a p63 response element motif (p63RE) activate transcription, with those sites bound by p63 more frequently or adhering closer to canonical p53 family response element sequences driving higher transcriptional output. The most active regulatory elements are those also capable of binding p53. Elements uniquely bound by p63 have varied activity, with p63RE-mediated repression associated with lower overall GC content in flanking sequences. Comparison of activity across cell lines suggests differential activity of elements may be regulated by a combination of p63 abundance or context-specific cofactors. Finally, changes in p63 isoform expression dramatically alters regulatory element activity, primarily shifting inactive elements towards a strong p63-dependent activity. Our analysis of p63-bound gene regulatory elements provides new insight into how sequence, cellular context, and other transcription factors influence p63-dependent transcription. These studies provide a framework for understanding how p63 genomic binding locally regulates transcription. Additionally, these results can be extended to investigate the influence of sequence content, genomic context, chromatin structure on the interplay between p63 isoforms and p53 family paralogs.

Chromosome evolution screens recapitulate tissue-specific tumor aneuploidy patterns

Whole chromosome and arm-level copy number alterations occur at high frequencies in tumors, but their selective advantages, if any, are poorly understood. Here, utilizing unbiased whole chromosome genetic screens combined with in vitro evolution to generate arm- and subarm-level events, we iteratively selected the fittest karyotypes from aneuploidized human renal and mammary epithelial cells. Proliferation-based karyotype selection in these epithelial lines modeled tissue-specific tumor aneuploidy patterns in patient cohorts in the absence of driver mutations. Hi-C-based translocation mapping revealed that arm-level events usually emerged in multiples of two via centromeric translocations and occurred more frequently in tetraploids than diploids, contributing to the increased diversity in evolving tetraploid populations. Isogenic clonal lineages enabled elucidation of pro-tumorigenic mechanisms associated with common copy number alterations, revealing Notch signaling potentiation as a driver of 1q gain in breast cancer. We propose that intrinsic, tissue-specific proliferative effects underlie tumor copy number patterns in cancer.

Missense variants in phospholamban and cardiac myosin binding protein identified in patients with a family history and clinical diagnosis of dilated cardiomyopathy

As the genetic landscape of cardiomyopathies continues to expand, the identification of missense variants in disease-associated genes frequently leads to a classification of variant of uncertain significance (VUS). For the proper reclassification of such variants, functional characterization is an important contributor to the proper assessment of pathogenic potential. Several missense variants in the calcium transport regulatory protein phospholamban have been associated with dilated cardiomyopathy. However, >40 missense variants in this transmembrane peptide are currently known and most remain classified as VUS with little clinical information. Similarly, missense variants in cardiac myosin binding protein have been associated with hypertrophic cardiomyopathy. However, hundreds of variants are known and many have low penetrance and are often found in control populations. Herein, we focused on novel missense variants in phospholamban, an Ala15-Thr variant found in a 4-year-old female and a Pro21-Thr variant found in a 60-year-old female, both with a family history and clinical diagnosis of dilated cardiomyopathy. The patients also harbored a Val896-Met variant in cardiac myosin binding protein. The phospholamban variants caused defects in the function, phosphorylation, and dephosphorylation of this calcium transport regulatory peptide, and we classified these variants as potentially pathogenic. The variant in cardiac myosin binding protein alters the structure of the protein. While this variant has been classified as benign, it has the potential to be a low-risk susceptibility variant because of the structural change in cardiac myosin binding protein. Our studies provide new biochemical evidence for missense variants previously classified as benign or VUS.

Factor VIII as a Novel Biomarker for Diagnosis, Prognosis, and Therapy Prediction in Human Cancer and Other Disorders

Coagulation factor VIII (FVIII) is an essential cofactor in the coagulation cascade, encoded by the F8 gene on the long arm of chromosome X (Xq28). FVIII is normally circulated in complex with Von Willebrand factor (VWF) and has relevant emerging extracoagulative functions. Dysregulation of FVIII is associated with tumor progression, and could be used as a novel biomarker for tumor screening and monitoring. In breast cancer, bladder cancer, colorectal carcinoma, esophageal carcinoma, hepatocellular carcinoma and lung cancer, F8 is regarded as an oncogene. In coronary heart disease, hemophilia A and liver disease, F8 dysregulation has been recognized as a potential biomarker for disease diagnosis and prognosis. However, the basis of these differential expression levels remains to be understood. In this review, which is a mixture of literature review and bioinformatics analysis we described the biological functions and characteristics of FVIII, and also its expression level in non-malignant disorders and various cancers.

Biochemistry of the hypoxia-inducible factor hydroxylases

The hypoxia-inducible factors are α,β-heterodimeric transcription factors that mediate the chronic response to hypoxia in humans and other animals. Protein hydroxylases belonging to two different structural subfamilies of the Fe(II) and 2-oxoglutarate (2OG)-dependent oxygenase superfamily modify HIFα. HIFα prolyl-hydroxylation, as catalysed by the PHDs, regulates HIFα levels and, consequently, α,β-HIF levels. HIFα asparaginyl-hydroxylation, as catalysed by factor inhibiting HIF (FIH), regulates the transcriptional activity of α,β-HIF. The activities of the PHDs and FIH are regulated by O2 availability, enabling them to act as hypoxia sensors. We provide an overview of the biochemistry of the HIF hydroxylases, discussing evidence that their kinetic and structural properties may be tuned to their roles in the HIF system. Avenues for future research and therapeutic modulation are discussed.

Preclinical Evaluation of the ATR Inhibitor BAY 1895344 as a Radiosensitizer for Head and Neck Squamous Cell Carcinoma

PURPOSE

Despite aggressive multimodal treatment that typically includes definitive or adjuvant radiation therapy (RT), locoregional recurrence rates approach 50% for patients with locally advanced human papillomavirus (HPV)-negative head and neck squamous cell carcinoma (HNSCC). Thus, more effective therapeutics are needed to improve patient outcomes. We evaluated the radiosensitizing effects of ataxia telangiectasia and RAD3-related (ATR) inhibitor (ATRi) BAY 1895344 in preclinical models of HNSCC.

METHODS AND MATERIALS

Murine and human HPV-negative HNSCC cells (MOC2, MOC1, JHU-012) were treated with vehicle or ATRi with or without 4 Gy. Checkpoint kinase 1 phosphorylation and DNA damage (γH2AX) were evaluated by Western blot, and ATRi half-maximal inhibitory concentration was determined by MTT assay for HNSCC cells and immortalized murine oral keratinocytes. In vitro radiosensitization was tested by clonogenic assay. Cell cycle distribution and mitotic catastrophe were evaluated by flow cytometry. Mitotic aberrations were quantified by fluorescent microscopy. Tumor growth delay and survival were assessed in mice bearing MOC2 or JHU-012 transplant tumors treated with vehicle, ATRi, RT (10 Gy × 1 or 8 Gy × 3), or combined ATRi + RT.

RESULTS

ATRi caused dose-dependent reduction in checkpoint kinase 1 phosphorylation at 1 hour post-RT (4 Gy) and dose-dependent increase in γH2AX at 18 hours post-RT. Addition of RT to ATRi led to decreased BAY 1895344 half-maximal inhibitory concentration in HNSCC cell lines but not in normal tissue surrogate immortalized murine oral keratinocytes. Clonogenic assays demonstrated radiosensitization in the HNSCC cell lines. ATRi abrogated the RT-induced G2/M checkpoint, leading to mitosis with unrepaired DNA damage and increased mitotic aberrations (multinucleated cells, micronuclei, nuclear buds, nucleoplasmic bridges). ATRi and RT significantly delayed tumor growth in MOC2 and JHU-012 in vivo models, with improved overall survival in the MOC2 model.

CONCLUSIONS

These findings demonstrated that BAY 1895344 increased in vitro and in vivo radiosensitivity in HPV-negative HNSCC preclinical models, suggesting therapeutic potential warranting evaluation in clinical trials for patients with locally advanced or recurrent HPV-negative HNSCC.

Literature mining discerns latent disease-gene relationships

MOTIVATION

Dysregulation of a gene's function, either due to mutations or impairments in regulatory networks, often triggers pathological states in the affected tissue. Comprehensive mapping of these apparent gene-pathology relationships is an ever-daunting task, primarily due to genetic pleiotropy and lack of suitable computational approaches. With the advent of high throughput genomics platforms and community scale initiatives such as the Human Cell Landscape project, researchers have been able to create gene expression portraits of healthy tissues resolved at the level of single cells. However, a similar wealth of knowledge is currently not at our finger-tip when it comes to diseases. This is because the genetic manifestation of a disease is often quite diverse and is confounded by several clinical and demographic covariates.

RESULTS

To circumvent this, we mined ∼18 million PubMed abstracts published till May 2019 and automatically selected ∼4.5 million of them that describe roles of particular genes in disease pathogenesis. Further, we fine-tuned the pretrained bidirectional encoder representations from transformers (BERT) for language modeling from the domain of natural language processing to learn vector representation of entities such as genes, diseases, tissues, cell-types, etc., in a way such that their relationship is preserved in a vector space. The repurposed BERT predicted disease-gene associations that are not cited in the training data, thereby highlighting the feasibility of in silico synthesis of hypotheses linking different biological entities such as genes and conditions.

AVAILABILITY AND IMPLEMENTATION

PathoBERT pretrained model: https://github.com/Priyadarshini-Rai/Pathomap-Model. BioSentVec-based abstract classification model: https://github.com/Priyadarshini-Rai/Pathomap-Model. Pathomap R package: https://github.com/Priyadarshini-Rai/Pathomap.

D3EGFR: a webserver for deep learning-guided drug sensitivity prediction and drug response information retrieval for EGFR mutation-driven lung cancer

As key oncogenic drivers in non-small-cell lung cancer (NSCLC), various mutations in the epidermal growth factor receptor (EGFR) with variable drug sensitivities have been a major obstacle for precision medicine. To achieve clinical-level drug recommendations, a platform for clinical patient case retrieval and reliable drug sensitivity prediction is highly expected. Therefore, we built a database, D3EGFRdb, with the clinicopathologic characteristics and drug responses of 1339 patients with EGFR mutations via literature mining. On the basis of D3EGFRdb, we developed a deep learning-based prediction model, D3EGFRAI, for drug sensitivity prediction of new EGFR mutation-driven NSCLC. Model validations of D3EGFRAI showed a prediction accuracy of 0.81 and 0.85 for patients from D3EGFRdb and our hospitals, respectively. Furthermore, mutation scanning of the crucial residues inside drug-binding pockets, which may occur in the future, was performed to explore their drug sensitivity changes. D3EGFR is the first platform to achieve clinical-level drug response prediction of all approved small molecule drugs for EGFR mutation-driven lung cancer and is freely accessible at https://www.d3pharma.com/D3EGFR/index.php.

Evolving copy number gains promote tumor expansion and bolster mutational diversification

The timing and fitness effect of somatic copy number alterations (SCNA) in cancer evolution remains poorly understood. Here we present a framework to determine the timing of a clonal SCNA that encompasses multiple gains. This involves calculating the proportion of time from its last gain to the onset of population expansion (lead time) as well as the proportion of time prior to its first gain (initiation time). Our method capitalizes on the observation that a genomic segment, while in a specific copy number (CN) state, accumulates point mutations proportionally to its CN. Analyzing 184 whole genome sequenced samples from 75 patients across five tumor types, we commonly observe late gains following early initiating events, occurring just before the clonal expansion relevant to the sampling. These include gains acquired after genome doubling in more than 60% of cases. Notably, mathematical modeling suggests that late clonal gains may contain final-expansion drivers. Lastly, SCNAs bolster mutational diversification between subpopulations, exacerbating the circle of proliferation and increasing heterogeneity.

Circulating cell-free DNA-based biomarkers for prognostication and disease monitoring in adrenocortical carcinoma

OBJECTIVE

Adrenocortical carcinoma (ACC) is a rare aggressive cancer with heterogeneous behaviour. Disease surveillance relies on frequent imaging, which comes with significant radiation exposure. The aim of the study was to investigate the role of circulating cell-free DNA (ccfDNA)-related biomarkers (BMs) for prognostication and monitoring of ACC.

DESIGN AND METHODS

We investigated 34 patients with ACC and 23 healthy subjects (HSs) as controls. Circulating cell-free DNA was extracted by commercial kits and ccfDNA concentrations were quantified by fluorimeter (BM1). Targeted sequencing was performed using a customized panel of 27 ACC-specific genes. Leucocyte DNA was used to discriminate somatic variants (BM2), while tumour DNA was sequenced in 22/34 cases for comparison. Serial ccfDNA samples were collected during follow-up in 19 ACC patients (median period 9 months) and analysed in relationship with standard radiological imaging.

RESULTS

Circulating cell-free DNA concentrations were higher in ACC than HS (mean ± SD, 1.15 ± 1.56 vs 0.05 ± 0.05 ng/µL, P < .0001), 96% of them being above the cut-off of 0.146 ng/µL (mean HS + 2 SD, positive BM1). At ccfDNA sequencing, 47% of ACC showed at least 1 somatic mutation (positive BM2). A combined ccfDNA-BM score was strongly associated with both progression-free and overall survival (hazard ratio [HR] = 2.63; 95% CI, 1.13-6.13; P = .010, and HR = 5.98; 95% CI, 2.29-15.6; P = .0001, respectively). During disease monitoring, positive BM2 showed the best specificity (100%) and sensitivity (67%) to detect ACC recurrence or progress compared with BM1.

CONCLUSION

ccfDNA-related BMs are frequently detected in ACC patients and represent a promising, minimally invasive tool to predict clinical outcome and complement surveillance imaging. Our findings will be validated in a larger cohort of ACCs with long-term follow-up.

Cancer-Associated Fibroblasts Together with a Decline in CD8+ T Cells Predict a Worse Prognosis for Breast Cancer Patients

BACKGROUND

Cancer-associated fibroblasts (CAFs) play a crucial role in tumor microenvironment regulation and cancer progression. This study assessed the significance and predictive potential of CAFs in breast cancer prognosis.

METHODS

The study included 1503 breast cancer patients. Cancer-associated fibroblasts were identified using morphologic features from hematoxylin and eosin slides. The study analyzed clinicopathologic parameters, survival rates, immune cells, gene sets, and prognostic models using gene-set enrichment analysis, in silico cytometry, pathway analysis, in vitro drug-screening, and gradient-boosting machine (GBM)-learning.

RESULTS

The presence of CAFs correlated significantly with young age, lymphatic invasion, and perineural invasion. In silico cytometry showed altered leukocyte subsets in the presence of CAFs, with decreased CD8+ T cells. Gene-set enrichment analysis showed associations with critical processes such as the epithelial-mesenchymal transition and immune modulation. Drug sensitivity analysis in breast cancer cell lines with varying fibroblast activation protein-α expression suggested that CAF-targeted therapies might enhance the efficacy of certain anticancer drugs including ARRY-520, ispinesib-mesylate, paclitaxel, and docetaxel. Integrating CAF presence with machine-learning improved survival prediction. For breast cancer patients, CAFs were independent prognostic markers for worse disease-specific survival and disease-free survival.

CONCLUSION

This study highlighted the significance of CAFs in breast cancer biology and provided compelling evidence of their impact on patient outcomes and treatment response. The findings offer valuable insights into the potential of CAFs as prognostic and predictive biomarkers and support the development of CAF-targeted therapies to improve breast cancer management.

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.

Tetraspanin CD82 Correlates with and May Regulate S100A7 Expression in Oral Cancer

Many metastatic cancers with poor prognoses correlate to downregulated CD82, but exceptions exist. Understanding the context of this correlation is essential to CD82 as a prognostic biomarker and therapeutic target. Oral squamous cell carcinoma (OSCC) constitutes over 90% of oral cancer. We aimed to uncover the function and mechanism of CD82 in OSCC. We investigated CD82 in human OSCC cell lines, tissues, and healthy controls using the CRISPR-Cas9 gene knockout, transcriptomics, proteomics, etc. CD82 expression is elevated in CAL 27 cells. Knockout CD82 altered over 300 genes and proteins and inhibited cell migration. Furthermore, CD82 expression correlates with S100 proteins in CAL 27, CD82KO, SCC-25, and S-G cells and some OSCC tissues. The 37-50 kDa CD82 protein in CAL 27 cells is upregulated, glycosylated, and truncated. CD82 correlates with S100 proteins and may regulate their expression and cell migration. The truncated CD82 explains the invasive metastasis and poor outcome of the CAL 27 donor. OSCC with upregulated truncated CD82 and S100A7 may represent a distinct subtype with a poor prognosis. Differing alternatives from wild-type CD82 may elucidate the contradictory functions and pave the way for CD82 as a prognostic biomarker and therapeutic target.

BRD9 status is a major contributor for cysteine metabolic remodeling through MST and EAAT3 modulation in malignant melanoma

Cutaneous melanoma (CM) is the most aggressive skin cancer, showing globally increasing incidence. Hereditary CM accounts for a significant percentage (5-15 %) of all CM cases. However, most familial cases remain without a known genetic cause. Even though, BRD9 has been associated to CM as a susceptibility gene. The molecular events following BRD9 mutagenesis are still not completely understood. In this study, we disclosed BRD9 as a key regulator in cysteine metabolism and associated altered BRD9 to increased cell proliferation, migration and invasiveness, as well as to altered melanin levels, inducing higher susceptibility to melanomagenesis. It is evident that BRD9 WT and mutated BRD9 (c.183G>C) have a different impact on cysteine metabolism, respectively by inhibiting and activating MPST expression in the metastatic A375 cell line. The effect of the mutated BRD9 variant was more evident in A375 cells than in the less invasive WM115 line. Our data point out novel molecular and metabolic mechanisms dependent on BRD9 status that potentially account for the increased risk of developing CM and enhancing CM aggressiveness. Moreover, our findings emphasize the role of cysteine metabolism remodeling in melanoma progression and open new queues to follow to explore the role of BRD9 as a melanoma susceptibility or cancer-related gene.

Toward robust clinical genome interpretation: Developing a consistent terminology to characterize Mendelian disease-gene relationships-allelic requirement, inheritance modes, and disease mechanisms

PURPOSE

The terminology used for gene-disease curation and variant annotation to describe inheritance, allelic requirement, and both sequence and functional consequences of a variant is currently not standardized. There is considerable discrepancy in the literature and across clinical variant reporting in the derivation and application of terms. Here, we standardize the terminology for the characterization of disease-gene relationships to facilitate harmonized global curation and to support variant classification within the ACMG/AMP framework.

METHODS

Terminology for inheritance, allelic requirement, and both structural and functional consequences of a variant used by Gene Curation Coalition members and partner organizations was collated and reviewed. Harmonized terminology with definitions and use examples was created, reviewed, and validated.

RESULTS

We present a standardized terminology to describe gene-disease relationships, and to support variant annotation. We demonstrate application of the terminology for classification of variation in the ACMG SF 2.0 genes recommended for reporting of secondary findings. Consensus terms were agreed and formalized in both Sequence Ontology (SO) and Human Phenotype Ontology (HPO) ontologies. Gene Curation Coalition member groups intend to use or map to these terms in their respective resources.

CONCLUSION

The terminology standardization presented here will improve harmonization, facilitate the pooling of curation datasets across international curation efforts and, in turn, improve consistency in variant classification and genetic test interpretation.

COSMIC: a curated database of somatic variants and clinical data for cancer

The Catalogue Of Somatic Mutations In Cancer (COSMIC), https://cancer.sanger.ac.uk/cosmic, is an expert-curated knowledgebase providing data on somatic variants in cancer, supported by a comprehensive suite of tools for interpreting genomic data, discerning the impact of somatic alterations on disease, and facilitating translational research. The catalogue is accessed and used by thousands of cancer researchers and clinicians daily, allowing them to quickly access information from an immense pool of data curated from over 29 thousand scientific publications and large studies. Within the last 4 years, COSMIC has substantially expanded its utility by adding new resources: the Mutational Signatures catalogue, the Cancer Mutation Census, and Actionability. To improve data accessibility and interoperability, somatic variants have received stable genomic identifiers that are associated with their genomic coordinates in GRCh37 and GRCh38, and new export files with reduced data redundancy have been made available for download.

Leveraging Tissue-Specific Enhancer-Target Gene Regulatory Networks Identifies Enhancer Somatic Mutations That Functionally Impact Lung Cancer

Enhancers are noncoding regulatory DNA regions that modulate the transcription of target genes, often over large distances along with the genomic sequence. Enhancer alterations have been associated with various pathological conditions, including cancer. However, the identification and characterization of somatic mutations in noncoding regulatory regions with a functional effect on tumorigenesis and prognosis remain a major challenge. Here, we present a strategy for detecting and characterizing enhancer mutations in a genome-wide analysis of patient cohorts, across three lung cancer subtypes. Lung tissue-specific enhancers were defined by integrating experimental data and public epigenomic profiles, and the genome-wide enhancer-target gene regulatory network of lung cells was constructed by integrating chromatin three-dimensional architecture data. Lung cancers possessed a similar mutation burden at tissue-specific enhancers and exons but with differences in their mutation signatures. Functionally relevant alterations were prioritized on the basis of the pathway-level integration of the effect of a mutation and the frequency of mutations on individual enhancers. The genes enriched for mutated enhancers converged on the regulation of key biological processes and pathways relevant to tumor biology. Recurrent mutations in individual enhancers also affected the expression of target genes, with potential relevance for patient prognosis. Together, these findings show that noncoding regulatory mutations have a potential relevance for cancer pathogenesis and can be exploited for patient classification.

SIGNIFICANCE

Mapping enhancer-target gene regulatory interactions and analyzing enhancer mutations at the level of their target genes and pathways reveal convergence of recurrent enhancer mutations on biological processes involved in tumorigenesis and prognosis.

Complex Genomic Rearrangement Patterns in Malignant Pleural Mesothelioma due to Environmental Asbestos Exposure

Malignant pleural mesothelioma (MPM) is a rare type of cancer, and its main risk factor is exposure to asbestos. Accordingly, our knowledge of the genomic structure of an MPM tumor is limited when compared to other cancers. In this study, we aimed to characterize complex genomic rearrangement patterns and variations to better understand the genomics of MPM tumors. We comparatively scanned 3 MPM tumor genomes by Whole-Genome Sequencing and High-Resolution SNP array. We also used various computational algorithms to detect both CNAs and complex chromosomal rearrangements. Genomic data obtained from each bioinformatics tool are interpreted comparatively to better understand CNAs and cancer-related Nucleotide variations in MPM tumors. In patients 1 and 2, we found pathogenic nucleotide variants of BAP1, RB1, and TP53. These two MPM genomes exhibited a highly rearranged chromosomal rearrangement pattern resembling Chromomanagesis particularly in the form of Chromoanasynthesis. In patient 3, we found nucleotide variants of important cancer-related genes, including TGFBR1, KMT2C, and PALLD, to have lower chromosomal rearrangement complexity compared with patients 1 and 2. We also detected several actionable nucleotide variants including XRCC1, ERCC2. We also discovered the SKA3-DDX10 fusion in two MPM genomes, which is a novel finding for MPM. We found that MPM genomes are very complex, suggesting that this highly rearranged pattern is strongly related to driver mutational status like BAP1, TP53 and RB1.

The Abundance of KRAS and RAS Gene Mutations in Cancer

Mutant forms of the RAS genes KRAS, NRAS, and HRAS are important and common drivers of cancer. Recently, two independent teams that integrated cancer genomics with cancer epidemiology estimated that approximately 15-20% of all human cancers harbor a mutation in one of these three RAS genes. These groups also estimate KRAS mutations occur in 11-14% of all human cancers. Although these estimates are lower than many commonly encountered values, these estimates continue to rank KRAS and the ensemble of RAS oncogenes among the most common genetic drivers of cancer across all forms of malignancy.

Inferring Markov Chains to Describe Convergent Tumor Evolution With CIMICE

The field of tumor phylogenetics focuses on studying the differences within cancer cell populations. Many efforts are done within the scientific community to build cancer progression models trying to understand the heterogeneity of such diseases. These models are highly dependent on the kind of data used for their construction, therefore, as the experimental technologies evolve, it is of major importance to exploit their peculiarities. In this work we describe a cancer progression model based on Single Cell DNA Sequencing data. When constructing the model, we focus on tailoring the formalism on the specificity of the data. We operate by defining a minimal set of assumptions needed to reconstruct a flexible DAG structured model, capable of identifying progression beyond the limitation of the infinite site assumption. Our proposal is conservative in the sense that we aim to neither discard nor infer knowledge which is not represented in the data. We provide simulations and analytical results to show the features of our model, test it on real data, show how it can be integrated with other approaches to cope with input noise. Moreover, our framework can be exploited to produce simulated data that follows our theoretical assumptions. Finally, we provide an open source R implementation of our approach, called CIMICE, that is publicly available on BioConductor.

Low CDKN1B Expression Associated with Reduced CD8+ T Lymphocytes Predicts Poor Outcome in Breast Cancer in a Machine Learning Analysis

The cyclin-dependent kinase inhibitor 1B (CDKN1B) gene, which encodes the p27Kip1 protein, is important in regulating the cell cycle process and cell proliferation. Its role in breast cancer prognosis is controversial. We evaluated the significance and predictive role of CDKN1B expression in breast cancer prognosis. We investigated the clinicopathologic factors, survival rates, immune cells, gene sets, and prognostic models according to CDKN1B expression in 3794 breast cancer patients. We performed gene set enrichment analysis (GSEA), in silico cytometry, pathway network analyses, gradient boosting machine (GBM) learning, and in vitro drug screening. High CDKN1B expression levels in breast cancer correlated with high lymphocyte infiltration signature scores and increased CD8+ T cells, both of which were associated with improved prognosis in breast cancer. which were associated with a better prognosis. CDKN1B expression was associated with gene sets for the upregulation of T-cell receptor signaling pathways and downregulation of CD8+ T cells. Pathway network analysis revealed a direct link between CDKN1B and the pathway involved in the positive regulation of the protein catabolic process pathway. In addition, an indirect link was identified between CDKN1B and the T-cell receptor signaling pathway. In in vitro drug screening, BMS-345541 demonstrated efficacy as a therapeutic targeting of CDKN1B, effectively impeding the growth of breast cancer cells characterized by low CDKN1B expression. The inclusion of CDKN1B expression in GBM models increased the accuracy of survival predictions. CDKN1B expression plays a significant role in breast cancer progression, implying that targeting CDKN1B might be a promising strategy for treating breast cancer.

Methylation Array Signals are Predictive of Chronological Age Without Bisulfite Conversion

DNA methylation data has been used to make "epigenetic clocks" which attempt to measure chronological and biological aging. These models rely on data derived from bisulfite-based measurements, which exploit a semi-selective deamination and a genomic reference to determine methylation states. Here, we demonstrate how another hallmark of aging, genomic instability, influences methylation measurements in both bisulfite sequencing and methylation arrays. We found that non-methylation factors lead to "pseudomethylation" signals that are both confounding of epigenetic clocks and uniquely age predictive. Quantifying these covariates in aging studies will be critical to building better clocks and designing appropriate studies of epigenetic aging.

Comprehensive genomic profiling of breast cancers characterizes germline-somatic mutation interactions mediating therapeutic vulnerabilities

Germline-somatic mutation interactions are universal and associated with tumorigenesis, but their role in breast cancer, especially in non-Caucasians, remains poorly characterized. We performed large-scale prospective targeted sequencing of matched tumor-blood samples from 4079 Chinese females, coupled with detailed clinical annotation, to map interactions between germline and somatic alterations. We discovered 368 pathogenic germline variants and identified 5 breast cancer DNA repair-associated genes (BCDGs; BRCA1/BRCA2/CHEK2/PALB2/TP53). BCDG mutation carriers, especially those with two-hit inactivation, demonstrated younger onset, higher tumor mutation burden, and greater clinical benefits from platinum drugs, PARP inhibitors, and immune checkpoint inhibitors. Furthermore, we leveraged a multiomics cohort to reveal that clinical benefits derived from two-hit events are associated with increased genome instability and an immune-activated tumor microenvironment. We also established an ethnicity-specific tool to predict BCDG mutation and two-hit status for genetic evaluation and therapeutic decisions. Overall, this study leveraged the large sequencing cohort of Chinese breast cancers, optimizing genomics-guided selection of DNA damaging-targeted therapy and immunotherapy within a broader population.

iMUT-seq: high-resolution DSB-induced mutation profiling reveals prevalent homologous-recombination dependent mutagenesis

DNA double-strand breaks (DSBs) are the most mutagenic form of DNA damage, and play a significant role in cancer biology, neurodegeneration and aging. However, studying DSB-induced mutagenesis is limited by our current approaches. Here, we describe iMUT-seq, a technique that profiles DSB-induced mutations at high-sensitivity and single-nucleotide resolution around endogenous DSBs. By depleting or inhibiting 20 DSB-repair factors we define their mutational signatures in detail, revealing insights into the mechanisms of DSB-induced mutagenesis. Notably, we find that homologous-recombination (HR) is more mutagenic than previously thought, inducing prevalent base substitutions and mononucleotide deletions at distance from the break due to DNA-polymerase errors. Simultaneously, HR reduces translocations, suggesting a primary role of HR is specifically the prevention of genomic rearrangements. The results presented here offer fundamental insights into DSB-induced mutagenesis and have significant implications for our understanding of cancer biology and the development of DDR-targeting chemotherapeutics.

Characterization of 164 patients with NRAS mutated non-small cell lung cancer (NSCLC)

BACKGROUND

NRAS mutations are observed in less than 1% of non-small cell lung cancer (NSCLC). Clinical data regarding this rare subset of lung cancer are scarce and response to systemic treatment such as chemotherapy or immune checkpoint inhibitors (ICI) has never been reported.

METHODS

All consecutive patients with an NRAS mutated NSCLC, diagnosed between August 2014 and November 2020 in 14 French centers, were included. Clinical and molecular data were collected and reviewed from medical records.

RESULTS

Out of the 164 included patients, 106 (64.6%) were men, 150 (91.5%) were current or former smokers, and 104 (63.4%) had stage IV NSCLC at diagnosis. The median age was 62 years, and the most frequent histology was adenocarcinoma (81.7%). NRAS activating mutations were mostly found in codon 61 (70%), while codon 12 and 13 alterations were observed in 16.5% and 4.9% of patients, respectively. Programmed death ligand-1 expression level <1%/1-49%/≥50% were respectively found in 30.8%/27.1%/42.1% of tumors. With a median follow-up of 12.5 months, median overall survival (OS) of stage IV patients was 15.3 months (95% CI 9.9-27.6). No significant difference in OS was found according to the type of mutation (codon 61 vs. other), HR = 1.12 (95% CI 0.65-1.95). Among stage IV patients treated with platinum-based doublet (n = 66), ICI (n = 48), or combination of both (n = 10), objective response rate, and median progression free survival were respectively 45% and 5.8 months, 35% and 6.9 months, 70% and 8.6 months.

CONCLUSION

NRAS mutated NSCLC are characterized by a high frequency of smoking history and codon 61 mutations. Further studies are needed to confirm the encouraging outcome of immunotherapy in combination with chemotherapy.

Novel Method for Detection of PIK3CA Mutations in Circulating Tumor DNA of Patients with Colorectal Cancer

The PIK3CA mutation is considered a potential target for treatment of colorectal cancer. We evaluated a PIK3CA mutation assay on plasma cell-free DNA (cfDNA) using a newly developed PCR with restriction digestion integrated and followed by Sanger's sequencing. We analyzed PIK3CA mutation in plasma with our newly developed assays and in matching tumor tissues by routine methods. We detected the PIK3CA gene mutation status by both methods in samples from 40 colorectal cancer patients. Three H1047R mutations of PIK3CA gene were detected in the cfDNA of the 40 patients by restriction digestion PCR. Neither E545K nor H1047R mutations were detected in the cfDNA by routine PCR/sequencing. The PIK3CA H1047R and E545K mutations in cfDNA can be sensitively detected with our newly developed assays. The colorectal cancer has been used as a clinical example in testing our new assays, which indicates that the new assays may have wider applications in detecting mutations in precision oncology. Trial registration: Current Controlled Trials ChiCTR-DDT-12002848, 8 October 2012.

FBXO24 Suppresses Breast Cancer Tumorigenesis by Targeting LSD1 for Ubiquitination

Lysine-specific demethylase 1 (LSD1), a critical chromatin modulator, functions as an oncogene by demethylation of H3K4me1/2. The stability of LSD1 is governed by a complex and intricate process involving ubiquitination and deubiquitination. Several deubiquitinases preserve LSD1 protein levels. However, the precise mechanism underlying the degradation of LSD1, which could mitigate its oncogenic function, remains unknown. To gain a better understanding of LSD1 degradation, we conducted an unbiased siRNA screening targeting all the human SCF family E3 ligases. Our screening identified FBXO24 as a genuine E3 ligase that ubiquitinates and degrades LSD1. As a result, FBXO24 inhibits LSD1-induced tumorigenesis and functions as a tumor suppressor in breast cancer cells. Moreover, FBXO24 exhibits an inverse correlation with LSD1 and is associated with a favorable prognosis in breast cancer patient samples. Taken together, our study uncovers the significant role of FBXO24 in impeding breast tumor progression by targeting LSD1 for degradation.

IMPLICATIONS

Our study provides comprehensive characterization of the significant role of FBXO24 in impeding breast tumor progression by targeting LSD1 for degradation.

Dynamic RBM47 ISGylation confers broad immunoprotection against lung injury and tumorigenesis via TSC22D3 downregulation

ISGylation is a well-established antiviral mechanism, but its specific function in immune and tissue homeostasis regulation remains elusive. Here, we reveal that the RNA-binding protein RBM47 undergoes phosphorylation-dependent ISGylation at lysine 329 to regulate immune activation and maintain lung homeostasis. K329R knockin (KI) mice with defective RBM47-ISGylation display heightened susceptibility to LPS-induced acute lung injury and lung tumorigenesis, accompanied with multifaceted immunosuppression characterized by elevated pro-inflammatory factors, reduced IFNs/related chemokines, increased myeloid-derived suppressor cells, and impaired tertiary lymphoid structures. Mechanistically, RBM47-ISGylation regulation of the expression of TSC22D3 mRNA, a glucocorticoid-inducible transcription factor, partially accounts for the effects of RBM47-ISGylation deficiency due to its broad immunosuppressive activity. We further demonstrate the direct inhibitory effect of RBM47-ISGylation on TSC22D3 expression in human cells using a nanobody-targeted E3 ligase to induce site-specific ISGylation. Furthermore, epinephrine-induced S309 phosphorylation primes RBM47-ISGylation, with epinephrine treatment exacerbating dysregulated cytokine expression and ALI induction in K329R KI mice. Our findings provide mechanistic insights into the dynamic regulation of RBM47-ISGylation in supporting immune activation and maintaining lung homeostasis.

Analysis of Nucleotide Variations in Human G-Quadruplex Forming Regions Associated with Disease States

While the role of G quadruplex (G4) structures has been identified in cancers and metabolic disorders, single nucleotide variations (SNVs) and their effect on G4s in disease contexts have not been extensively studied. The COSMIC and CLINVAR databases were used to detect SNVs present in G4s to identify sequence level changes and their effect on the alteration of the G4 secondary structure. A total of 37,515 G4 SNVs in the COSMIC database and 2378 in CLINVAR were identified. Of those, 7236 COSMIC (19.3%) and 457 (19%) of the CLINVAR variants result in G4 loss, while 2728 (COSMIC) and 129 (CLINVAR) SNVs gain a G4 structure. The remaining variants potentially affect the folding energy without affecting the presence of a G4. Analysis of mutational patterns in the G4 structure shows a higher selective pressure (3-fold) in the coding region on the template strand compared to the reverse strand. At the same time, an equal proportion of SNVs were observed among intronic, promoter, and enhancer regions across strands.

Efficacy of futibatinib, an irreversible fibroblast growth factor receptor inhibitor, in FGFR-altered breast cancer

Several alterations in fibroblast growth factor receptor (FGFR) genes have been found in breast cancer; however, they have not been well characterized as therapeutic targets. Futibatinib (TAS-120; Taiho) is a novel, selective, pan-FGFR inhibitor that inhibits FGFR1-4 at nanomolar concentrations. We sought to determine futibatinib's efficacy in breast cancer models. Nine breast cancer patient-derived xenografts (PDXs) with various FGFR1-4 alterations and expression levels were treated with futibatinib. Antitumor efficacy was evaluated by change in tumor volume and time to tumor doubling. Alterations indicating sensitization to futibatinib in vivo were further characterized in vitro. FGFR gene expression between patient tumors and matching PDXs was significantly correlated; however, overall PDXs had higher FGFR3-4 expression. Futibatinib inhibited tumor growth in 3 of 9 PDXs, with tumor stabilization in an FGFR2-amplified model and prolonged regression (> 110 days) in an FGFR2 Y375C mutant/amplified model. FGFR2 overexpression and, to a greater extent, FGFR2 Y375C expression in MCF10A cells enhanced cell growth and sensitivity to futibatinib. Per institutional and public databases, FGFR2 mutations and amplifications had a population frequency of 1.1%-2.6% and 1.5%-2.5%, respectively, in breast cancer patients. FGFR2 alterations in breast cancer may represent infrequent but highly promising targets for futibatinib.

Gene regulatory Networks Reveal Sex Difference in Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) has been observed to have significant sex differences in incidence, prognosis, and response to therapy. However, the molecular mechanisms responsible for these disparities have not been investigated extensively. Sample-specific gene regulatory network methods were used to analyze RNA sequencing data from non-cancerous human lung samples from The Genotype Tissue Expression Project (GTEx) and lung adenocarcinoma primary tumor samples from The Cancer Genome Atlas (TCGA); results were validated on independent data. We observe that genes associated with key biological pathways including cell proliferation, immune response and drug metabolism are differentially regulated between males and females in both healthy lung tissue, as well as in tumor, and that these regulatory differences are further perturbed by tobacco smoking. We also uncovered significant sex bias in transcription factor targeting patterns of clinically actionable oncogenes and tumor suppressor genes, including AKT2 and KRAS. Using differentially regulated genes between healthy and tumor samples in conjunction with a drug repurposing tool, we identified several small-molecule drugs that might have sex-biased efficacy as cancer therapeutics and further validated this observation using an independent cell line database. These findings underscore the importance of including sex as a biological variable and considering gene regulatory processes in developing strategies for disease prevention and management.

A pan-cancer analysis of STAT3 expression and genetic alterations in human tumors

Combined cancer immunotherapy and targeted therapy have proven to be effective against various cancers and therefore have recently become the focus of cancer research. Signal transducer and activator of transcription 3 (STAT3) is a member of the STAT protein family of transcription factors. Several studies have shown that STAT3 can affect the prognosis of cancer patients by regulating immune microenvironment (IME). Therefore, STAT3 may have high research value for the development of combined immunotherapy/targeted therapy approaches for the treatment of cancer patients. We found differences in STAT3 expression between tumor and normal tissues. Kaplan-Meier survival and Cox regression analyses showed that high expression of STAT3 is associated with poor prognosis in low-grade glioma (LGG) patients. The results of the analysis of the area under the curve of the receiver operating characteristic curve further suggested that the expression of STAT3 is an effective way to evaluate the prognosis of patients with glioma. The results of the IME analysis revealed that the immune and matrix scores of LGGs were positively correlated with the expression of STAT3 (P < 0.05). The results of immune cell infiltration analysis showed that STAT3 was positively correlated with resting dendritic cells, eosinophils, neutrophils, M0 macrophages, M1 macrophages, CD4 memory resting T cells, and CD8 T cells in LGG patients, but negatively correlated with activated mast cells and M2 macrophages (P < 0.05). Our gene set enrichment analysis identified 384 enriched pathways. According to the enrichment scores, the top ten most significantly upregulated pathways were related to immune response. The top ten most significantly downregulated pathways were related to cell signal transduction and the regulation of cell survival, proliferation, and metabolism. Genetic alteration analysis showed that missense mutations in STAT3 account for the majority of mutations, and STAT3 mutations mostly occur in the Src homology domain. In conclusion overexpression of STAT3 can promote the development and growth of tumors by regulating IME, which is significantly related to the poor prognosis of cancer patients. Therefore, targeted inhibition of STAT3 expression may have high research value for the development of combined immunotherapy/targeted therapy approaches for the treatment of cancer patients.

Drug Discovery Targeting Nuclear Receptor Binding SET Domain Protein 2 (NSD2)

Nuclear receptor binding SET domain proteins (NSDs) catalyze the mono- or dimethylation of histone 3 lysine 36 (H3K36me1 and H3K36me2), using S-adenosyl-l-methionine (SAM) as a methyl donor. As a key member of the NSD family of proteins, NSD2 plays an important role in the pathogenesis and progression of various diseases such as cancers, inflammations, and infectious diseases, serving as a promising drug target. Developing potent and specific NSD2 inhibitors may provide potential novel therapeutics. Several NSD2 inhibitors and degraders have been discovered while remaining in the early stage of drug development. Excitingly, KTX-1001, a selective NSD2 inhibitor, has entered clinical trials. In this Perspective, the structures and functions of NSD2, its roles in various human diseases, and the recent advances in drug discovery strategies targeting NSD2 have been summarized. The challenges, opportunities, and future directions for developing NSD2 inhibitors and degraders are also discussed.

An Updated Overview of Existing Cancer Databases and Identified Needs

Our search of existing cancer databases aimed to assess the current landscape and identify key needs. We analyzed 71 databases, focusing on genomics, proteomics, lipidomics, and glycomics. We found a lack of cancer-related lipidomic and glycomic databases, indicating a need for further development in these areas. Proteomic databases dedicated to cancer research were also limited. To assess overall progress, we included human non-cancer databases in proteomics, lipidomics, and glycomics for comparison. This provided insights into advancements in these fields over the past eight years. We also analyzed other types of cancer databases, such as clinical trial databases and web servers. Evaluating user-friendliness, we used the FAIRness principle to assess findability, accessibility, interoperability, and reusability. This ensured databases were easily accessible and usable. Our search summary highlights significant growth in cancer databases while identifying gaps and needs. These insights are valuable for researchers, clinicians, and database developers, guiding efforts to enhance accessibility, integration, and usability. Addressing these needs will support advancements in cancer research and benefit the wider cancer community.

The Mutation Portraits of Oncogenes and Tumor Supressor Genes in Predicting the Overall Survival in Pancreatic Cancer: A Bayesian Network Meta-Analysis

INTRODUCTION

In pancreatic cancer, the carcinogenesis can not be separated from genetics mutations. The portraits of genes alterations majorily including oncogenes (KRAS, HER2, PD-L1) and tumor supressor genes (P53, CDKN2A, SMAD4). Besides being notorious a screening marker, the genetic mutations were related to the prognosis of pancreatic cancer. The aim of this study is to determine the genetic mutations portrait in predicting the overall survival in pancreatic cancer.

METHODS

The network meta analysis (NMA) was registered in PROSPERO (CRD42023397976) and conducted in accordance with the PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) in addition of NMA extension guidance. Comprehensive searches were done including all studies which reported the overall survival of pancreatic cancer subjects with KRAS, HER2, PD-L1, P53, CDKN2A, SMAD4. Data were collected and analysis will be done based on Bayesian method, Markov Chain Monte Carlo algorithm, using BUGSnet package in R studio. Transivity was controlled by methods and consistency of the NMA will be fitted by deviance information criterion. Data analysis in NMA were presented in Sucra plot, league table, and forest plot.

RESULTS

Twenty-four studies were included in this NMA with 4613 total subjects. The NMA was conducted in random-effects, consistent, and convergence model. Relative to control, the genetic mutation of SMAD4 (HR 1.84; 95%CI 1.39-2.46), HER2 (HR 1.76; 95%CI 1.14-2.71), and KRAS (HR 1.7; 95%CI 1.19-2.48) were significant to have worse survival. The mutations of PD-L1, P53, and CDKN2A also showed poor survival, but not statistically significant compared to control.

CONCLUSION

In pancreatic cancer, the mutation of SMAD4 predicted the worst overall survival, compared to control, also mutation of HER2, KRAS, PD-L1, P53, and CDKN2A.

Multiomic analysis of HER2-enriched and AR-positive breast carcinoma with apocrine differentiation and an oligometastatic course: a case report

Breast carcinoma is the most prevalent cancer among women globally. It has variable clinical courses depending on the stage and clinical-biological features. This case report describes a 56-year-old female with invasive breast cancer without estrogen or progesterone receptor expression, with apocrine differentiation, and with no germline variants in the BRCA1 and BRCA2 genes. Throughout the clinical course, the patient exhibited discordant results for HER2 in immunohistochemistry and in situ hybridization. During the second relapse, the disease displayed apocrine microscopic features. The tumor underwent analysis for the androgen receptor, GCDFP-15, RNA-seq, and whole-genome sequencing (WGS) to identify the breast cancer subtype and to characterize the cancer genome. Our bioinformatic analysis revealed 20,323 somatic SNV/Indels, including five mutations in cancer-related genes that are believed to be responsible for the tumor's development. Two of these mutations were found in the PIK3CA and TP53 genes. Furthermore, the tumor tissue exhibited large copy number alterations to the chromosomes, which could impact gene expression through complex mechanisms and contribute to the tumor phenotype. Clustering algorithms applied on RNA-sequencing data categorized this cancer as a HER2+ subtype. The second-line capecitabine chemotherapy treatment is ongoing, and the patient is responding well. Bioinformatic results support the current treatment decision and open the way to further treatments.

Naturally mutagenic sequence diversity in a human type II topoisomerase

Type II topoisomerases transiently cleave duplex DNA as part of a strand passage mechanism that helps control chromosomal organization and superstructure. Aberrant DNA cleavage can result in genomic instability, and how topoisomerase activity is controlled to prevent unwanted breaks is poorly understood. Using a genetic screen, we identified mutations in the beta isoform of human topoisomerase II (hTOP2β) that render the enzyme hypersensitive to the chemotherapeutic agent etoposide. Several of these variants were unexpectedly found to display hypercleavage behavior in vitro and to be capable of inducing cell lethality in a DNA repair-deficient background; surprisingly, a subset of these mutations were also observed in TOP2B sequences from cancer genome databases. Using molecular dynamics simulations and computational network analyses, we found that many of the mutations obtained from the screen map to interfacial points between structurally coupled elements, and that dynamical modeling could be used to identify other damage-inducing TOP2B alleles present in cancer genome databases. This work establishes that there is an innate link between DNA cleavage predisposition and sensitivity to topoisomerase II poisons, and that certain sequence variants of human type II topoisomerases found in cancer cells can act as DNA-damaging agents. Our findings underscore the potential for hTOP2β to function as a clastogen capable of generating DNA damage that may promote or support cellular transformation.

3DVizSNP: a tool for rapidly visualizing missense mutations identified in high throughput experiments in iCn3D

BACKGROUND

High throughput experiments in cancer and other areas of genomic research identify large numbers of sequence variants that need to be evaluated for phenotypic impact. While many tools exist to score the likely impact of single nucleotide polymorphisms (SNPs) based on sequence alone, the three-dimensional structural environment is essential for understanding the biological impact of a nonsynonymous mutation.

RESULTS

We present a program, 3DVizSNP, that enables the rapid visualization of nonsynonymous missense mutations extracted from a variant caller format file using the web-based iCn3D visualization platform. The program, written in Python, leverages REST APIs and can be run locally without installing any other software or databases, or from a webserver hosted by the National Cancer Institute. It automatically selects the appropriate experimental structure from the Protein Data Bank, if available, or the predicted structure from the AlphaFold database, enabling users to rapidly screen SNPs based on their local structural environment. 3DVizSNP leverages iCn3D annotations and its structural analysis functions to assess changes in structural contacts associated with mutations.

CONCLUSIONS

This tool enables researchers to efficiently make use of 3D structural information to prioritize mutations for further computational and experimental impact assessment. The program is available as a webserver at https://analysistools.cancer.gov/3dvizsnp or as a standalone python program at https://github.com/CBIIT-CGBB/3DVizSNP .

Genomic approaches to cancer and minimal residual disease detection using circulating tumor DNA

Liquid biopsies using cell-free circulating tumor DNA (ctDNA) are being used frequently in both research and clinical settings. ctDNA can be used to identify actionable mutations to personalize systemic therapy, detect post-treatment minimal residual disease (MRD), and predict responses to immunotherapy. ctDNA can also be isolated from a range of different biofluids, with the possibility of detecting locoregional MRD with increased sensitivity if sampling more proximally than blood plasma. However, ctDNA detection remains challenging in early-stage and post-treatment MRD settings where ctDNA levels are minuscule giving a high risk for false negative results, which is balanced with the risk of false positive results from clonal hematopoiesis. To address these challenges, researchers have developed ever-more elegant approaches to lower the limit of detection (LOD) of ctDNA assays toward the part-per-million range and boost assay sensitivity and specificity by reducing sources of low-level technical and biological noise, and by harnessing specific genomic and epigenomic features of ctDNA. In this review, we highlight a range of modern assays for ctDNA analysis, including advancements made to improve the signal-to-noise ratio. We further highlight the challenge of detecting ultra-rare tumor-associated variants, overcoming which will improve the sensitivity of post-treatment MRD detection and open a new frontier of personalized adjuvant treatment decision-making.

Unraveling the Drivers of Tumorigenesis in the Context of Evolution: Theoretical Models and Bioinformatics Tools

Cancer originates from somatic cells that have accumulated mutations. These mutations alter the phenotype of the cells, allowing them to escape homeostatic regulation that maintains normal cell numbers. The emergence of malignancies is an evolutionary process in which the random accumulation of somatic mutations and sequential selection of dominant clones cause cancer cells to proliferate. The development of technologies such as high-throughput sequencing has provided a powerful means to measure subclonal evolutionary dynamics across space and time. Here, we review the patterns that may be observed in cancer evolution and the methods available for quantifying the evolutionary dynamics of cancer. An improved understanding of the evolutionary trajectories of cancer will enable us to explore the molecular mechanism of tumorigenesis and to design tailored treatment strategies.

Candidate variants in DNA replication and repair genes in early-onset renal cell carcinoma patients referred for germline testing

BACKGROUND

Early-onset renal cell carcinoma (eoRCC) is typically associated with pathogenic germline variants (PGVs) in RCC familial syndrome genes. However, most eoRCC patients lack PGVs in familial RCC genes and their genetic risk remains undefined.

METHODS

Here, we analyzed biospecimens from 22 eoRCC patients that were seen at our institution for genetic counseling and tested negative for PGVs in RCC familial syndrome genes.

RESULTS

Analysis of whole-exome sequencing (WES) data found enrichment of candidate pathogenic germline variants in DNA repair and replication genes, including multiple DNA polymerases. Induction of DNA damage in peripheral blood monocytes (PBMCs) significantly elevated numbers of [Formula: see text]H2AX foci, a marker of double-stranded breaks, in PBMCs from eoRCC patients versus PBMCs from matched cancer-free controls. Knockdown of candidate variant genes in Caki RCC cells increased [Formula: see text]H2AX foci. Immortalized patient-derived B cell lines bearing the candidate variants in DNA polymerase genes (POLD1, POLH, POLE, POLK) had DNA replication defects compared to control cells. Renal tumors carrying these DNA polymerase variants were microsatellite stable but had a high mutational burden. Direct biochemical analysis of the variant Pol δ and Pol η polymerases revealed defective enzymatic activities.

CONCLUSIONS

Together, these results suggest that constitutional defects in DNA repair underlie a subset of eoRCC cases. Screening patient lymphocytes to identify these defects may provide insight into mechanisms of carcinogenesis in a subset of genetically undefined eoRCCs. Evaluation of DNA repair defects may also provide insight into the cancer initiation mechanisms for subsets of eoRCCs and lay the foundation for targeting DNA repair vulnerabilities in eoRCC.

Mutant-allele dispersion correlates with prognosis risk in patients with advanced non-small cell lung cancer

BACKGROUND

Intra-tumor heterogeneity (ITH) contributes to lung cancer progression and resistance to therapy. To evaluate ITH and determine whether it may be employed as a predictive biomarker of prognosis in patients with advanced non-small cell lung cancer (NSCLC), we used a novel algorithm called mutant-allele dispersion (MAD).

METHODS

In the study, 103 patients with advanced NSCLC were enrolled. Using a panel of 425 cancer-related genes, next-generation sequencing (NGS) was performed on tumor specimens that had been collected. From NGS data, we derived MAD values, and we next looked into their relationships with clinical variables and different mutation subtypes.

RESULTS

The median MAD among 103 NSCLC patients was 0.73. EGFR mutation, tyrosine kinase inhibitor (TKI) therapy, radiotherapy, and chemotherapy cycles were all substantially correlated with the MAD score. In patients with lung adenocarcinoma (LUAD), correlation analysis revealed that the MAD score was substantially linked with Notch pathway mutation (P = 0.021). A significant relationship between high MAD and shorter progression-free survival (PFS) was found (HR = 2.004, 95%CI 1.269-3.163, P = 0.003). In patients with advanced NSCLC, histological type (P = 0.004), SMARCA4 mutation (P = 0.038), and LRP1B mutation (P = 0.006) were all independently associated with prognosis. The disease control rate was considerably greater in the low MAD group compared to the high MAD group in 19 LUAD patients receiving immunotherapy (92.9% vs. 40%, P = 0.037). TKI-PFS was longer in 37 patients with low MAD who received first-line TKI therapy (P = 0.014).

CONCLUSION

Our findings suggested that MAD is a practical and simple algorithm for assessing ITH, and populations with high MAD values are more likely to have EGFR mutations. MAD can be used as a potential biomarker to predict not only the prognosis of NSCLC but also the efficacy of immunotherapy and TKI therapy in patients with advanced NSCLC.

Landscape of gene mutation in Chinese thyroid cancer patients: Construction and validation of lymph node metastasis prediction model based on clinical features and gene mutation marker

OBJECTIVES

Reporting the clinicopathological information of thyroid cancer (TC) patients from a central medical center of east China, and constructing the nomogram predicting lymph node metastasis (LNM).

METHODS

We collected the patients who underwent thyroid cancer surgery in our institute from July 1, 2019 to July 31, 2021, a total of 253 subjects were enrolled. We used HiPure FFPE DNA Kit to extract DNA and RNApure FFPE Kit to extract RNA from the paraffin sections of tumor tissue, the extracted DNA samples and RNA samples were used for NGS sequencing. The clinical and pathological information of TCGA-THCA cohort was obtained as the validation cohort. Multivariate logistic regression analysis was performed to identify the independent prognostic factor, and the nomogram was subsequently constructed by "rms" R package.

RESULTS

Secondary cases contained more mutation of BRAF (90.48% vs. 62.07%) and TERT (33.0% vs. 3.0%), as compared with primary cases. Primary patients with positive lymph node were younger (40.9 ± 10.8 vs. 45.3 ± 11.8, p = 0.0031) and contained advanced TI-RADS levels (4c: 22.8% vs. 8.3%, 5: 6.5% vs. 0/0%, p = 1.878e-03), as well as more RET genetic alteration (16.3% vs. 2.7%, p = 2.566e-03). We chose age, tumor diameter, RET fusion, and gender to construct the LNM predicting nomogram. Calibration plot, DCA curve, and the clinical impact plot verified the preferable prognostic value of the nomogram, with an AUC value of 0.724 (0.656-0.792). We successfully validated the prognostic value of the nomogram in TCGA-THCA cohort. RET fusion might impact the process of protein digestion and absorption, cytokine-cytokine receptor interaction, ECM-receptor interaction, focal adhesion.

CONCLUSION

We provide a novel nomogram to predict the LNM for TC patients, including the features of patient's age, gender, tumor diameter, and RET alteration. Further studies from multiple medical centers are essential to validate the nomogram.

OncoRTT: Predicting novel oncology-related therapeutic targets using BERT embeddings and omics features

Late-stage drug development failures are usually a consequence of ineffective targets. Thus, proper target identification is needed, which may be possible using computational approaches. The reason being, effective targets have disease-relevant biological functions, and omics data unveil the proteins involved in these functions. Also, properties that favor the existence of binding between drug and target are deducible from the protein’s amino acid sequence. In this work, we developed OncoRTT, a deep learning (DL)-based method for predicting novel therapeutic targets. OncoRTT is designed to reduce suboptimal target selection by identifying novel targets based on features of known effective targets using DL approaches. First, we created the “OncologyTT” datasets, which include genes/proteins associated with ten prevalent cancer types. Then, we generated three sets of features for all genes: omics features, the proteins’ amino-acid sequence BERT embeddings, and the integrated features to train and test the DL classifiers separately. The models achieved high prediction performances in terms of area under the curve (AUC), i.e., AUC greater than 0.88 for all cancer types, with a maximum of 0.95 for leukemia. Also, OncoRTT outperformed the state-of-the-art method using their data in five out of seven cancer types commonly assessed by both methods. Furthermore, OncoRTT predicts novel therapeutic targets using new test data related to the seven cancer types. We further corroborated these results with other validation evidence using the Open Targets Platform and a case study focused on the top-10 predicted therapeutic targets for lung cancer.

Towards robust clinical genome interpretation: developing a consistent terminology to characterize disease-gene relationships - allelic requirement, inheritance modes and disease mechanisms

PURPOSE

The terminology used for gene-disease curation and variant annotation to describe inheritance, allelic requirement, and both sequence and functional consequences of a variant is currently not standardized. There is considerable discrepancy in the literature and across clinical variant reporting in the derivation and application of terms. Here we standardize the terminology for the characterization of disease-gene relationships to facilitate harmonized global curation, and to support variant classification within the ACMG/AMP framework.

METHODS

Terminology for inheritance, allelic requirement, and both structural and functional consequences of a variant used by Gene Curation Coalition (GenCC) members and partner organizations was collated and reviewed. Harmonized terminology with definitions and use examples was created, reviewed, and validated.

RESULTS

We present a standardized terminology to describe gene-disease relationships, and to support variant annotation. We demonstrate application of the terminology for classification of variation in the ACMG SF 2.0 genes recommended for reporting of secondary findings. Consensus terms were agreed and formalized in both sequence ontology (SO) and human phenotype ontology (HPO) ontologies. GenCC member groups intend to use or map to these terms in their respective resources.

CONCLUSION

The terminology standardization presented here will improve harmonization, facilitate the pooling of curation datasets across international curation efforts and, in turn, improve consistency in variant classification and genetic test interpretation.

Genomic profiling of a metastatic anaplastic melanocytic neuroectodermal tumor arising from a mature thymic teratoma as part of a mediastinal germ cell tumor

Following chemotherapy, a mediastinal germ cell tumor can lead to a mature teratoma that is composed of tissues derived from all three germ layers. Although teratoma is usually curable, in rare cases it can give rise to various somatic tumors and exceptionally it undergoes melanocytic neuroectodermal tumor (MNT) transformation, a process that is not well-described. We report a patient with a postchemotherapy thymic teratoma associated with an MNT component who, 10 years later, additionally presented a vertebral metastasis corresponding to an anaplastic MNT. Using exome sequencing of the mature teratoma, the MNT and its metastatic vertebral anaplastic MNT components, we identified 19 somatic mutations shared by at least two components. Six mutations were common to all three components, and three of them were located in the known cancer-related genes KRAS (p.E63K), TP53 (p.P222X), and POLQ (p.S447P). Gene set enrichment analysis revealed that the melanoma tumorigenesis pathway was enriched in mutated genes including the four major driver genes KRAS, TP53, ERBB4, and KDR, indicating that these genes may be involved in the development of the anaplastic MNT transformation of the teratoma. To our knowledge, this is the first molecular study realized on MNT. Understanding the clinicopathological and molecular characteristics of these tumors is essential to better understand their development and to improve therapeutics.

Structure and functional determinants of Rad6-Bre1 subunits in the histone H2B ubiquitin-conjugating complex

The conserved complex of the Rad6 E2 ubiquitin-conjugating enzyme and the Bre1 E3 ubiquitin ligase catalyzes histone H2B monoubiquitination (H2Bub1), which regulates chromatin dynamics during transcription and other nuclear processes. Here, we report a crystal structure of Rad6 and the non-RING domain N-terminal region of Bre1, which shows an asymmetric homodimer of Bre1 contacting a conserved loop on the Rad6 'backside'. This contact is distant from the Rad6 catalytic site and is the location of mutations that impair telomeric silencing in yeast. Mutational analyses validated the importance of this contact for the Rad6-Bre1 interaction, chromatin-binding dynamics, H2Bub1 formation and gene expression. Moreover, the non-RING N-terminal region of Bre1 is sufficient to confer nucleosome binding ability to Rad6 in vitro. Interestingly, Rad6 P43L protein, an interaction interface mutant and equivalent to a cancer mutation in the human homolog, bound Bre1 5-fold more tightly than native Rad6 in vitro, but showed reduced chromatin association of Bre1 and reduced levels of H2Bub1 in vivo. These surprising observations imply conformational transitions of the Rad6-Bre1 complex during its chromatin-associated functional cycle, and reveal the differential effects of specific disease-relevant mutations on the chromatin-bound and unbound states. Overall, our study provides structural insights into Rad6-Bre1 interaction through a novel interface that is important for their biochemical and biological responses.

PIK3CA mutations and their impact on survival outcomes of patients with endometrial cancer: A systematic review and meta-analysis

Several studies have highlighted the frequent alterations of the PI3K pathway in endometrial cancer leading to increased signaling activation with potential for targeted treatment. The objective of this meta-study was to evaluate how PIK3CA exon 9/20 mutations affect survival in endometrial cancer patients, based on available literature. Topic-based search strategies were applied to databases including CENTRAL, MEDLINE, Embase, Web of Science and COSMIC. All studies assessing the impact of mutations in exon 9 and exon 20 of PIK3CA on survival rates of endometrial cancer patients were selected for inclusion. Statistical meta-analysis was performed with the 'meta' package in RStudio. Overall, 7 of 612 screened articles were included in the present study, comprising 1098 women with endometrial cancer. Meta-analysis revealed a tendency of impaired survival for patients with PIK3CA exon 9 and/or exon 20 mutations (RR 1.28; 95% CI 0.84, 1.94; p = 0.25). This tendency was consistent in subgroup analyses stratified by histologic type or -grade, with the most prominent effect in low-grade endometrial cancers (RR 2.04; 95% CI 0.90, 4.62; p = 0.09). In summary, these results suggest that PIK3CA mutations negatively influence survival outcomes of patients with endometrial cancer, including those with low-grade tumors.