Clonal haematopoiesis of indeterminate potential (CHIP) has been associated with many adverse health outcomes. However, further research is required to understand the critical genes and pathways relevant to CHIP subtypes, evaluate how CHIP clones evolve with time, and further advance functional characterisation and therapeutic studies. Large epidemiological studies are well placed to address these questions but often collect saliva rather than blood from participants. Paired saliva- and blood-derived DNA samples from 94 study participants were sequenced using a targeted CHIP-gene panel. The ten genes most frequently identified to carry CHIP-associated variants were analysed. Fourteen unique variants associated with CHIP, ten in DNMT3A, two in TP53 and two in TET2, were identified with a variant allele fraction (VAF) between 0.02 and 0.2 and variant depth ≥ 5 reads. Eleven of these CHIP-associated variants were detected in both the blood- and saliva-derived DNA sample. Three variants were detected in blood with a VAF > 0.02 but fell below this threshold in the paired saliva sample (VAF 0.008-0.013). Saliva-derived DNA is suitable for detecting CHIP-associated variants. Saliva can offer a cost-effective biospecimen that could both advance CHIP research and facilitate clinical translation into settings such as risk prediction, precision prevention, and treatment monitoring.

The number of somatic mutations among all tissues increases along with age. This process was well-studied in hematopoietic stem cells (HSCs). Some mutations lead to a proliferative advantage and expansion of HSCs to form a dominant clone. Clonal hematopoiesis is general in the elderly population. Clonal hematopoiesis of indeterminate potential (CHIP) is a more common phenomenon in the elderly and is defined as somatic mutations in clonal blood cells without any other hematological malignancies. The development of CHIP is an independent risk factor for hematological malignancies, cardiovascular diseases, and reduced overall survival. CHIP is frequently associated with mutations in DNMT3A and TET2 genes involved in DNA methylation. The epigenetic human body clocks have been developed based on the age-related changes in methylation, making it possible to detect epigenetic aging. The combination of epigenetic aging and CHUP is associated with adverse health outcomes. Further research will reveal the significance of clonal hematopoiesis and CHIP in aging, acquiring various diseases, and determining the feasibility of influencing the mutagenic potential of clones.
С возрастом во всех тканях увеличивается количество соматических мутаций. Лучше всего этот процесс изучен в стволовых кроветворных клетках. Некоторые мутации могут привести к пролиферативному преимуществу и экспансии стволовых кроветворных клеток с образованием клона. Клональное кроветворение широко распространено у пожилых людей. Клональный гемопоэз неопределенного потенциала (КГНП) — феномен, который чаще встречается в пожилом возрасте и характеризуется соматическими мутациями в клетках-предшественницах гемопоэза с формированием нескольких минорных клонов, экспансия которых способна постепенно вытеснить нормальный гемопоэз. Развитие КГНП является независимым фактором риска опухолей системы крови, сердечно-сосудистых заболеваний и общей летальности. При КГНП чаще всего мутируют гены DNMT3A и TET2, которые участвуют в метилировании ДНК. На основании возрастного изменения метилирования разработаны эпигенетические часы организма человека, позволяющие выявить эпигенетическое старение. Сочетание последнего и КГНП связано с неблагоприятными исходами для здоровья. Дальнейшее исследования позволят понять значение клонального гемопоэза и КГНП в процессе старения и развитии различных заболеваний, определить возможности целенаправленного воздействия на мутировавшие клоны.

Accurate detection and analysis of somatic variants in cancer involve multiple third-party tools with complex dependencies and configurations, leading to laborious, error-prone, and time-consuming data conversions. This approach lacks accuracy, reproducibility, and portability, limiting clinical application. Musta was developed to address these issues as an end-to-end pipeline for detecting, classifying, and interpreting cancer mutations. Musta is based on a Python command-line tool designed to manage tumor-normal samples for precise somatic mutation analysis. The core is a Snakemake-based workflow that covers all key cancer genomics steps, including variant calling, mutational signature deconvolution, variant annotation, driver gene detection, pathway analysis, and tumor heterogeneity estimation. Musta is easy to install on any system via Docker, with a Makefile handling installation, configuration, and execution, allowing for full or partial pipeline runs. Musta has been validated at the CRS4-NGS Core facility and tested on large datasets from The Cancer Genome Atlas and the Beijing Institute of Genomics. Musta has proven robust and flexible for somatic variant analysis in cancer. It is user-friendly, requiring no specialized programming skills, and enables data processing with a single command line. Its reproducibility ensures consistent results across users following the same protocol.

Excision repair cross-complementation group 2 (ERCC2) encodes the DNA helicase xeroderma pigmentosum group D, which functions in transcription and nucleotide excision repair. Point mutations in ERCC2 are putative drivers in around 10% of bladder cancers (BLCAs) and a potential positive biomarker for cisplatin therapy response. Nevertheless, the prognostic significance directly attributed to ERCC2 mutations and its pathogenic role in genome instability remain poorly understood. We first demonstrated that mutant ERCC2 is an independent predictor of prognosis in BLCA. We then examined its impact on the somatic mutational landscape using a cohort of ERCC2 wild-type (n = 343) and mutant (n = 39) BLCA whole genomes. The genome-wide distribution of somatic mutations is significantly altered in ERCC2 mutants, including T[C>T]N enrichment, altered replication time correlations, and CTCF-cohesin binding site mutation hotspots. We leverage these alterations to develop a machine learning model for predicting pathogenic ERCC2 mutations, which may be useful to inform treatment of patients with BLCA.

Advancements in micropropagation techniques have made it easier to produce large numbers of cannabis clones, but these methods may also introduce genetic instability over successive generations. This instability often manifests as somaclonal variation, characterized by the progressive accumulation of genetic mutations or epigenetic alterations with each subculture. In this study, we examined how mutations accumulate in cannabis clones subjected to 6-11 subcultures. Using genotyping-by-sequencing, we identified 9405 polymorphic variants across 70 clones. The analysis revealed a correlation between the number of subcultures and the frequency of these mutations, revealing that genetic changes accumulate over successive subcultures despite clones sharing the same chronological age. Furthermore, we evaluated the functional impacts of accumulated mutations, with particular attention to implications on gene function and overall plant health. While rare, 14 high-impact variants were identified in genes that are important for plant development. Notably, six variants were also found in genes related to cannabinoid and terpene synthesis pathways, potentially affecting the plant\'s biochemical composition. These findings highlight the need for genetic assessments in micropropagation protocols, impacting plant breeding and conservation. Understanding genetic variations in clonally propagated plants optimizes practices for stability. Crucial for cannabis and horticultural plants, it emphasizes techniques to prevent genetic decay and ensure viability.

BACKGROUND: Plant meristems are structured organs consisting of distinct layers of stem cells, which differentiate into new plant tissue. Mutations in meristematic layers can propagate into large sectors of the plant. However, the characteristics of meristematic mutations remain unclear, limiting our understanding of the genetic basis of somaclonal phenotypic variation.
RESULTS: Here, we analyse the frequency and distribution of somatic mutations in an apricot tree. We separately sequence the epidermis (developing from meristem layer 1) and the flesh (developing from meristem layer 2) of several fruits sampled across the entire tree. We find that most somatic mutations (> 90%) are specific to individual layers. Interestingly, layer 1 shows a higher mutation load than layer 2, implying different mutational dynamics between the layers. The distribution of somatic mutations follows the branching of the tree. This suggests that somatic mutations are propagated to developing branches through axillary meristems. In turn, this leads us to the unexpected observation that the genomes of layer 1 of distant branches are more similar to each other than to the genomes of layer 2 of the same branches. Finally, using single-cell RNA sequencing, we demonstrate that layer-specific mutations were only transcribed in the cells of the respective layers and can form the genetic basis of somaclonal phenotypic variation.
CONCLUSIONS: Here, we analyse the frequency and distribution of somatic mutations with meristematic origin. Our observations on the layer specificity of somatic mutations outline how they are distributed, how they propagate, and how they can impact clonally propagated crops.

OBJECTIVE: To perform a molecular profiling of the metastases from papillary thyroid carcinomas (PTCs) and poorly differentiated thyroid carcinomas (PDTCs).
METHODS: We retrieved and analyzed the molecular and clinical features of 136 metastases from PTCs and 35 metastases from PDTCs subjected to targeted DNA sequencing, from cBioPortal. The clinicopathological data included the number and location of the metastases, and genomic data included mutations, translocations, copy number alterations and fraction of the genome altered (FGA).
RESULTS: Bone metastases from PTCs had a lower frequency of BRAF mutations than the lymph node metastases (LNMs) (43% vs 88%, p < 0.01), and a higher frequency of RBM10 and NRAS mutations than the LNMs (21% vs 3% for both, p < 0.05). The FGA of the bone metastases was higher than the FGA of the lung metastases (5.6% vs 1.3%, p < 0.05). The frequency of RET translocations was higher in the lung metastases from PTCs than the LNMs (15% vs 3%, p < 0.05). The LNMs from PTC patients harboring 4 or more distant metastases (DMs) had a higher frequency of TERT promoter mutations than the LNMs from patients harboring less than 4 DMs (96% vs 65%, p < 0.001). SDHA gene amplifications were enriched in the bone metastases from PDTCs and absent in the LNMs (38% vs 0%, p < 0.05).
CONCLUSIONS: Metastases from PTCs and PDTCs harbor clinically relevant alterations affecting distinct body locations, such as NRAS and RBM10 mutations, RET translocations and SDHA amplifications that may be explored therapeutically.

BACKGROUND: Folate is involved in multiple genetic, epigenetic, and metabolic processes, and inadequate folate intake has been associated with an increased risk of cancer.
OBJECTIVE: We examined whether folate intake is differentially associated with colorectal cancer (CRC) risk according to somatic mutations in genes linked to CRC using targeted sequencing.
METHODS: Participants within 2 large CRC consortia with available information on dietary folate, supplemental folic acid, and total folate intake were included. Colorectal tumor samples from cases were sequenced for the presence of nonsilent mutations in 105 genes and 6 signaling pathways (IGF2/PI3K, MMR, RTK/RAS, TGF-β, WNT, and TP53/ATM). Multinomial logistic regression models were analyzed comparing mutated/nonmutated CRC cases to controls to compute multivariable-adjusted odds ratios (ORs) with 95% confidence interval (CI). Heterogeneity of associations of mutated compared with nonmutated CRC cases was tested in case-only analyses using logistic regression. Analyses were performed separately in hypermutated and nonhypermutated tumors, because they exhibit different clinical behaviors.
RESULTS: We included 4339 CRC cases (702 hypermutated tumors, 16.2%) and 11,767 controls. Total folate intake was inversely associated with CRC risk (OR = 0.93; 95% CI: 0.90, 0.96). Among hypermutated tumors, 12 genes (AXIN2, B2M, BCOR, CHD1, DOCK3, FBLN2, MAP3K21, POLD1, RYR1, TET2, UTP20, and ZNF521) showed nominal statistical significance (P < 0.05) for heterogeneity by mutation status, but none remained significant after multiple testing correction. Among these genetic subtypes, the associations between folate variables and CRC were mostly inverse or toward the null, except for tumors mutated for DOCK3 (supplemental folic acid), CHD1 (total folate), and ZNF521 (dietary folate) that showed positive associations. We did not observe differential associations in analyses among nonhypermutated tumors, or according to the signaling pathways.
CONCLUSIONS: Folate intake was not differentially associated with CRC risk according to mutations in the genes explored. The nominally significant differential mutation effects observed in a few genes warrants further investigation.

BACKGROUND: Somatic mutations have been observed to induce aldosterone-producing adenomas (APAs). These may be accelerated during pregnancy. Somatic PRKACA mutations are common in cortisol-producing adenomas (CPAs). However, their role in APAs, particularly aldosterone- and cortisol-producing adenomas (A/CPAs), is not well understood. This study aims to investigate the association between PRKACA mutations and the accelerated development of A/CPAs during pregnancy.
METHODS: A patient with primary aldosteronism (PA) associated with severe Cushing\'s syndrome (CS) underwent surgical resection of an adrenal tumor one year after delivery. Pathologic examination revealed an adrenocortical adenoma characterized primarily by zona glomerulosa hyperplasia. Somatic mutation analysis revealed the presence of the somatic PRKACA mutation, which was validated as a deleterious mutation by various computational databases. Immunohistochemical results showed positive staining for cytochrome P450 family 11 subfamily B member 1 (CYP11B1), cytochrome P450 family 11 subfamily B member 2 (CYP11B2), and luteinizing hormone/chorionic gonadotropin receptor (LHCGR). Our study included a review of 20 previously documented cases of aldosterone- and cortisol-producing adenomas (A/CPAs), two of which were concurrently positive for both CYP11B1 and CYP11B2, consistent with our findings.
CONCLUSIONS: Somatic mutations in PRKACA may correlate with the upregulation of LHCGR, which synergistically drives the accelerated growth of co-secretion tumors during pregnancy, thereby exacerbating disease progression.

Purpose: Bone metastasis (BoM) has been closely associated with increased morbidity and poor survival outcomes in patients with non-small cell lung cancer (NSCLC). Given its significant implications, this study aimed to systematically compare the biological characteristics between advanced NSCLC patients with and without BoM. Methods: In this study, the genomic alterations from the tumor tissue DNA of 42 advanced NSCLC patients without BoM and 67 patients with BoM and were analyzed by a next-generation sequencing (NGS) panel. The serum concentrations of 18 heavy metals were detected by inductively coupled plasma emission spectrometry (ICP-MS). Results: A total of 157 somatic mutations across 18 mutated genes and 105 somatic mutations spanning 16 mutant genes were identified in 61 out of 67 (91.05%) patients with BoM and 37 of 42 (88.10%) patients without BoM, respectively. Among these mutated genes, NTRK1, FGFR1, ERBB4, NTRK3, and FGFR2 stood out exclusively in patients with BoM, whereas BRAF, GNAS, and AKT1 manifested solely in those without BoM. Moreover, both co-occurring sets of genes and mutually exclusive sets of genes in patients with BoM were different from those in patients without BoM. In addition, the serum concentrations of Cu and Sr in patients with BoM were significantly higher than in patients without BoM. One of our aims was to explore how these heavy metals associated with BoM interacted with other heavy metals, and significant positive correlations were observed between Cu and Co, between Cu and Cr, between Sr and Ba, and between Sr and Ni in patients with BoM. Given the significant impacts of molecular characteristics on patients\' prognosis, we also observed a noteworthy negative correlation between EGFR mutations and Co, alongside a significant positive correlation between TP53 mutations and Cd. Conclusions: The genomic alterations, somatic interactions, key signaling pathways, functional biological information, and accumulations of serum heavy metals were markedly different between advanced NSCLC patients with and without BoM, and certain heavy metals (e.g., Cu, Sr) might have potentials to identify high-risk patients with BoM.