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The mammalian epigenome contains thousands of heterochromatin nanodomains (HNDs) marked by di- and trimethylation of histone H3 at lysine 9 (H3K9me2/3), which have a typical size of 3–10 nucleosomes. However, what governs HND location and extension is only partly understood. Here, we address this issue by introducing the chromatin hierarchical lattice framework (ChromHL) that predicts chromatin state patterns with single-nucleotide resolution. ChromHL is applied to analyse four HND types in mouse embryonic stem cells that are defined by histone methylases SUV39H1/2 or GLP, transcription factor ADNP or chromatin remodeller ATRX. We find that HND patterns can be computed from PAX3/9, ADNP and LINE1 sequence motifs as nucleation sites and boundaries that are determined by DNA sequence (e.g. CTCF binding sites), cooperative interactions between nucleosomes as well as nucleosome-HP1 interactions. Thus, ChromHL rationalizes how patterns of H3K9me2/3 are established and changed via the activity of protein factors in processes like cell differentiation. The ability to predict epigenetic regulation is an important challenge in biology. Here the authors describe heterochromatin nanodomains (HNDs) and compare four different types of H3K9me2/3-marked HNDs in mouse embryonic stem cells. They further develop a computational framework to predict genome-wide HND maps from DNA sequence and protein concentrations, at single-nucleotide resolution.

Background The utility of circulating tumour DNA (ctDNA) for longitudinal tumour monitoring in pancreatic ductal adenocarcinoma (PDAC) has not been explored beyond mutations in the KRAS proto-oncogene. Here, we aimed to characterise and track patient-specific somatic ctDNA variants, to assess longitudinal changes in disease burden and explore the landscape of actionable alterations. Methods We followed 3 patients with resectable disease and 4 patients with unresectable disease, including 4 patients with ≥ 3 serial follow-up samples, of whom 2 were rare long survivors (> 5 years). We performed whole exome sequencing of tumour gDNA and plasma ctDNA ( n  = 20) collected over a ~ 2-year period from diagnosis through treatment to death or final follow-up. Plasma from 3 chronic pancreatitis cases was used as a comparison for analysis of ctDNA mutations. Results We detected > 55% concordance between somatic mutations in tumour tissues and matched serial plasma. Mutations in ctDNA were detected within known PDAC driver genes ( KRAS, TP53, SMAD4 , CDKN2A ), in addition to patient-specific variants within alternative cancer drivers (NRAS, HRAS, MTOR, ERBB2, EGFR, PBRM1 ), with a trend towards higher overall mutation loads in advanced disease. ctDNA alterations with potential for therapeutic actionability were identified in all 7 patients, including DNA damage response (DDR) variants co-occurring with hypermutation signatures predictive of response to platinum chemotherapy. Longitudinal tracking in 4 patients with follow-up > 2 years demonstrated that ctDNA mutant allele fractions and clonal trends were consistent with CA19-9 measurements and/or clinically reported disease burden. The estimated prevalence of ‘stem clones’ was highest in an unresectable patient where changes in ctDNA dynamics preceded CA19-9 levels. Longitudinal evolutionary trajectories revealed ongoing subclonal evolution following chemotherapy. Conclusion These results provide proof-of-concept for the use of exome sequencing of serial plasma to characterise patient-specific ctDNA profiles, and demonstrate the sensitivity of ctDNA in monitoring disease burden in PDAC even in unresectable cases without matched tumour genotyping. They reveal the value of tracking clonal evolution in serial ctDNA to monitor treatment response, establishing the potential of applied precision medicine to guide stratified care by identifying and evaluating actionable opportunities for intervention aimed at optimising patient outcomes for an otherwise intractable disease.

Addressing existing racial disparity in breast cancer is crucial to ensure equitable benefit across diverse communities. We evaluate the molecular and clinical effects of genetic ancestry in African and South Asian women compared to European using a combined cohort of 7136 breast cancer patients. We find that non-European patients present significantly earlier and die at a younger age. The African group has an increased prevalence of higher grade and hormone receptor negative disease. The South Asian group shows tendency towards lower stage at diagnosis and tumour mutational burden. We observe differences and similarities in the somatic mutational landscape, and differences in germline mutation rates relevant to genetic testing and breast cancer predisposition. Potential therapeutic candidates are identified, with a higher propensity for homologous recombination deficiency serving as a therapy response indicator. We harness breast cancer multimodal data to improve understanding of ancestry-associated differences and highlight opportunities to advance health equity. Breast cancer diagnosis and outcomes are affected by racial disparities. Here, the authors evaluate effects of genetic ancestry in African and South Asian breast cancer patients, finding disparities in diagnosis, mortality, and tumour grade compared to patients with European ancestry; they also find potential population-specific genomic targets.

Clinically, osteoarthritis (OA) pain is significantly associated with synovial inflammation. Identification of the mechanisms driving inflammation could reveal new targets to relieve this prevalent pain state. Herein, a role of polyadenylation in OA synovial samples was investigated, and the potential of the polyadenylation inhibitor cordycepin (3’ deoxyadenosine) to inhibit inflammation as well as to reduce pain and structural OA progression were studied. Joint tissues from people with OA with high or low grade inflammation and non-arthritic post-mortem controls were analysed for the polyadenylation factor CPSF4 and inflammatory markers. Effects of cordycepin on pain behavior and joint pathology were studied in models of OA (intra-articular injection of monosodium iodoacetate in rats and surgical destabilisation of the medial meniscus in mice). Human monocyte-derived macrophages and a mouse macrophage cell line were used to determine effects of cordycepin on nuclear localisation of the inflammatory transcription factor NFĸB and polyadenylation factors (WDR33 and CPSF4). CPSF4 and NFκB expression were increased in synovia from OA patients with high grade inflammation. Cordycepin reduced pain behaviour, synovial inflammation and joint pathology in both OA models. Stimulation of macrophages induced nuclear localisation of NFĸB and polyadenylation factors, effects inhibited by cordycepin. Knockdown of polyadenylation factors also prevented nuclear localisation of NFĸB. The increased expression of polyadenylation factors in OA synovia indicates a new target for analgesia treatments. This is supported by the finding that polyadenylation factors are required for inflammation in macrophages and by the fact that the polyadenylation inhibitor cordycepin attenuates pain and pathology in models of OA.

Background Nucleosome repositioning in cancer is believed to cause many changes in genome organisation and gene expression. Understanding these changes is important to elucidate fundamental aspects of cancer. It is also important for medical diagnostics based on cell-free DNA (cfDNA), which originates from genomic DNA regions protected from digestion by nucleosomes. Results We have generated high-resolution nucleosome maps in paired tumour and normal tissues from the same breast cancer patients using MNase-assisted histone H3 ChIP-seq and compared them with the corresponding cfDNA from blood plasma. This analysis has detected single-nucleosome repositioning at key regulatory regions in a patient-specific manner and common cancer-specific patterns across patients. The nucleosomes gained in tumour versus normal tissue were particularly informative of cancer pathways, with ~ 20-fold enrichment at CpG islands, a large fraction of which marked promoters of genes encoding DNA-binding proteins. The tumour tissues were characterised by a 5–10 bp decrease in the average distance between nucleosomes (nucleosome repeat length, NRL), which is qualitatively similar to the differences between pluripotent and differentiated cells. This effect was correlated with gene activity, differential DNA methylation and changes in local occupancy of linker histone variants H1.4 and H1X. Conclusions Our study offers a novel resource of high-resolution nucleosome maps in breast cancer patients and reports for the first time the effect of systematic decrease of NRL in paired tumour versus normal breast tissues from the same patient. Our findings provide a new mechanistic understanding of nucleosome repositioning in tumour tissues that can be valuable for patient diagnostics, stratification and monitoring.

This paper reports on insights from the OPTIMA (Optimal Treatment for Patients with Solid Tumours in Europe Through Artificial Intelligence) prototyping workshop held in Berlin from November 6 to November 8, 2024. Through integrated analysis of clinical, genomic, imaging and pathology data, we addressed the following key challenges in breast and lung cancer management: utility of comprehensive genomic profiling in metastatic breast cancer settings; relevance of tumor heterogeneity for predicting treatment response; development of less invasive technologies for assessing tumor biology; and treatment outcomes in early stages of small cell lung cancer. Our findings demonstrate the potential of computational analysis using multiple data modalities to identify cancer molecular subtypes and enhance treatment selection and monitoring while highlighting important areas for future development to achieve the research objectives of the OPTIMA consortium.

Random walks are used to model movement in a wide variety of contexts: from the movement of cells undergoing chemotaxis to the migration of animals. In a two-dimensional biased random walk, the diffusion about the mean drift position is entirely dependent on the moments of the angular distribution used to determine the movement direction at each step. Here we consider biased random walks using several different angular distributions and derive expressions for the diffusion coefficients in each direction based on either a fixed or variable movement speed, and we use these to generate a probability density function for the long-time spatial distribution. We demonstrate how diffusion is typically anisotropic around the mean drift position and illustrate these theoretical results using computer simulations. We relate these results to earlier studies of swimming microorganisms and explain how the results can be generalized to other types of animal movement.

In response to changing extracellular pH levels, phosphate-limited continuous cultures of Clostridium acetobutylicum reversibly switches its metabolism from the dominant formation of acids to the prevalent production of solvents. Previous experimental and theoretical studies have revealed that this pH-induced metabolic switch involves a rearrangement of the intracellular transcriptomic, proteomic and metabolomic composition of the clostridial cells. However, the influence of the population dynamics on the observations reported has so far been neglected. Here, we present a method for linking the pH shift, clostridial growth and the acetone–butanol–ethanol fermentation metabolic network systematically into a model which combines the dynamics of the external pH and optical density with a metabolic model. Furthermore, the recently found antagonistic expression pattern of the aldehyde/alcohol dehydrogenases AdhE1/2 and pH-dependent enzyme activities have been included into this combined model. Our model predictions reveal that the pH-induced metabolic shift under these experimental conditions is governed by a phenotypic switch of predominantly acidogenic subpopulation towards a predominantly solventogenic subpopulation. This model-driven explanation of the pH-induced shift from acidogenesis to solventogenesis by population dynamics casts an entirely new light on the clostridial response to changing pH levels. Moreover, the results presented here underline that pH-dependent growth and pH-dependent specific enzymatic activity play a crucial role in this adaptation. In particular, the behaviour of AdhE1 and AdhE2 seems to be the key factor for the product formation of the two phenotypes, their pH-dependent growth, and thus, the pH-induced metabolic switch in C. acetobutylicum .

Widespread mammographic screening programs and improved self-monitoring allow for breast cancer to be detected earlier than ever before. Breast-conserving surgery is a successful treatment for select women. However, up to 40% of women develop local recurrence after surgery despite apparently tumor-free margins. This suggests that morphologically normal breast may harbor early alterations that contribute to increased risk of cancer recurrence. We conducted a comprehensive transcriptomic and proteomic analysis to characterize 57 fresh-frozen tissues from breast cancers and matched histologically normal tissues resected proximal to (<2 cm) and distant from (5–10 cm) the primary tumor, using tissues from cosmetic reduction mammoplasties as baseline. Four distinct transcriptomic subtypes are identified within matched normal tissues: metabolic; immune; matrisome/epithelial–mesenchymal transition, and non-coding enriched. Key components of the subtypes are supported by proteomic and tissue composition analyses. We find that the metabolic subtype is associated with poor prognosis (p < 0.001, HR6.1). Examination of genes representing the metabolic signature identifies several genes able to prognosticate outcome from histologically normal tissues. A subset of these have been reported for their predictive ability in cancer but, to the best of our knowledge, these have not been reported altered in matched normal tissues. This study takes an important first step toward characterizing matched normal tissues resected at pre-defined margins from the primary tumor. Unlocking the predictive potential of unexcised tissue could prove key to driving the realization of personalized medicine for breast cancer patients, allowing for more biologically-driven analyses of tissue margins than morphology alone.

In response to changing extracellular pH levels, phosphate-limited continuous cultures of Clostridium acetobutylicum reversibly switches its metabolism from the dominant formation of acids to the prevalent production of solvents. Previous experimental and theoretical studies have revealed that this pH-induced metabolic switch involves a rearrangement of the intracellular transcriptomic, proteomic and metabolomic composition of the clostridial cells. However, the influence of the population dynamics on the observations reported has so far been neglected. Here, we present a method for linking the pH shift, clostridial growth and the acetone-butanol-ethanol fermentation metabolic network systematically into a model which combines the dynamics of the external pH and optical density with a metabolic model. Furthermore, the recently found antagonistic expression pattern of the aldehyde/alcohol dehydrogenases AdhE1/2 and pH-dependent enzyme activities have been included into this combined model. Our model predictions reveal that the pH-induced metabolic shift under these experimental conditions is governed by a phenotypic switch of predominantly acidogenic subpopulation towards a predominantly solventogenic subpopulation. This model-driven explanation of the pH-induced shift from acidogenesis to solventogenesis by population dynamics casts an entirely new light on the clostridial response to changing pH levels. Moreover, the results presented here underline that pH-dependent growth and pH-dependent specific enzymatic activity play a crucial role in this adaptation. In particular, the behaviour of AdhE1 and AdhE2 seems to be the key factor for the product formation of the two phenotypes, their pH-dependent growth, and thus, the pH-induced metabolic switch in C. acetobutylicum.