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Mutational activation of KRAS promotes the initiation and progression of cancers, especially in the colorectum, pancreas, lung, and blood plasma, with varying prevalence of specific activating missense mutations. Although epidemiological studies connect specific alleles to clinical outcomes, the mechanisms underlying the distinct clinical characteristics of mutant KRAS alleles are unclear. Here, we analyze 13,492 samples from these four tumor types to examine allele- and tissue-specific genetic properties associated with oncogenic KRAS mutations. The prevalence of known mutagenic mechanisms partially explains the observed spectrum of KRAS activating mutations. However, there are substantial differences between the observed and predicted frequencies for many alleles, suggesting that biological selection underlies the tissue-specific frequencies of mutant alleles. Consistent with experimental studies that have identified distinct signaling properties associated with each mutant form of KRAS, our genetic analysis reveals that each KRAS allele is associated with a distinct tissue-specific comutation network. Moreover, we identify tissue-specific genetic dependencies associated with specific mutant KRAS alleles. Overall, this analysis demonstrates that the genetic interactions of oncogenic KRAS mutations are allele- and tissue-specific, underscoring the complexity that drives their clinical consequences. The KRAS gene is often mutated at several hotspot codons in cancer, resulting in similar, yet distinct, functional impacts on the KRAS protein. Here, the authors examine the genetic interactions of the different KRAS mutations across multiple cancer types and discover that KRAS mutations have allele- and tissue-specific mutagenic origins, comutation patterns, and dependency interactions.

Mutations in BRCA1 and/or BRCA2 ( BRCA1/2 ) are the most common indication of deficiency in the homologous recombination (HR) DNA repair pathway. However, recent genome-wide analyses have shown that the same pattern of mutations found in BRCA1 / 2 -mutant tumors is also present in several other tumors. Here, we present a new computational tool called Signature Multivariate Analysis (SigMA), which can be used to accurately detect the mutational signature associated with HR deficiency from targeted gene panels. Whereas previous methods require whole-genome or whole-exome data, our method detects the HR-deficiency signature even from low mutation counts, by using a likelihood-based measure combined with machine-learning techniques. Cell lines that we identify as HR deficient show a significant response to poly (ADP-ribose) polymerase (PARP) inhibitors; patients with ovarian cancer whom we found to be HR deficient show a significantly longer overall survival with platinum regimens. By enabling panel-based identification of mutational signatures, our method substantially increases the number of patients that may be considered for treatments targeting HR deficiency. Signature Multivariate Analysis is a new computational tool that detects the mutational signature of homologous-recombination deficiency in clinical samples sequenced with targeted panels, enabling the identification of patients who are responsive to poly (ADP-ribose) polymerase inhibition therapy.

A bstract Within the context of a hybrid strong/weak coupling model of jet quenching, we study the modification of the angular distribution of the energy within jets in heavy ion collisions, as partons within jet showers lose energy and get kicked as they traverse the strongly coupled plasma produced in the collision. To describe the dynamics transverse to the jet axis, we add the effects of transverse momentum broadening into our hybrid construction, introducing a parameter K ≡ q ^ / T 3 that governs its magnitude. We show that, because of the quenching of the energy of partons within a jet, even when K ≠ 0 the jets that survive with some specified energy in the final state are narrower than jets with that energy in proton-proton collisions. For this reason, many standard observables are rather insensitive to K . We propose a new differential jet shape ratio observable in which the effects of transverse momentum broadening are apparent. We also analyze the response of the medium to the passage of the jet through it, noting that the momentum lost by the jet appears as the momentum of a wake in the medium. After freezeout this wake becomes soft particles with a broad angular distribution but with net momentum in the jet direction, meaning that the wake contributes to what is reconstructed as a jet. This effect must therefore be included in any description of the angular structure of the soft component of a jet. We show that the particles coming from the response of the medium to the momentum and energy deposited in it leads to a correlation between the momentum of soft particles well separated from the jet in angle with the direction of the jet momentum, and find qualitative but not quantitative agreement with experimental data on observables designed to extract such a correlation. More generally, by confronting the results that we obtain upon introducing transverse momentum broadening and the response of the medium to the jet with available jet data, we highlight the importance of these processes for understanding the internal, soft, angular structure of high energy jets.

Distilling biologically meaningful information from cancer genome sequencing data requires comprehensive identification of somatic alterations using rigorous computational methods. As the amount and complexity of sequencing data have increased, so has the number of tools for analysing them. Here, we describe the main steps involved in the bioinformatic analysis of cancer genomes, review key algorithmic developments and highlight popular tools and emerging technologies. These tools include those that identify point mutations, copy number alterations, structural variations and mutational signatures in cancer genomes. We also discuss issues in experimental design, the strengths and limitations of sequencing modalities and methodological challenges for the future.In this Review the authors provide an overview of key algorithmic developments, popular tools and emerging technologies used in the bioinformatic analysis of genomes. They also describe how such analysis can identify point mutations, copy number alterations, structural variations and mutational signatures in cancer genomes.

Many visualisations used in the climate communication field aim to present the scientific models of climate change to the public. However, relatively little research has been conducted on how such data are visually processed, particularly from a behavioural science perspective. This study examines trends in visual attention to climate change predictions in world maps using mobile eye-tracking while participants engage with the visualisations. Our primary aim is to assess engagement with the maps, as indicated by gaze metrics. Secondary analyses assess whether social context (as social viewing compared to solitary viewing) affects these trends, the relationship between projection types and visual attention, compare gaze metrics between scientific map and artwork viewing, and explore correlations between self-reported climate anxiety scores and attention patterns. We employed wearable, head-mounted eye-tracking to collect data in relatively naturalistic conditions, aiming to enhance ecological validity. In this research, participants engaged with ten world maps displaying near- and far-term climate projections across five data categories, adapted from the online interactive atlas provided by the International Panel on Climate Change (IPCC). To compare scientific information processing with aesthetic perception, participants also viewed two large-scale artworks. Responses to the Climate Change Anxiety Scale (CCAS) were also collected. Participants viewed the displays alone (single-viewing condition, N = 35) or together with a partner (paired-viewing condition, N = 12). Results revealed that the upper parts of the maps, particularly the continental Europe, received significant attention, suggesting a Euro-centric bias in viewing patterns. Spatial gaze patterns were similar between single and paired conditions, indicating that the visual attributes of the maps predominantly shaped attention locations. Although dwell times were comparable, the paired condition showed higher fixation counts, shorter average fixation durations, and longer scanpaths, suggesting a potentially dissociable viewing strategy and more exploratory viewing patterns influenced by social interaction. No substantial differences were observed in attention across projection timeframes or types, although individual variations were noted. Artwork viewing exhibited notably shorter average fixation durations compared to climate map viewing, potentially reflecting different visual engagement styles. Despite positive linear correlations among the four CCAS subscales, there was no apparent correlation between CCAS scores and main gaze metrics, indicating a lack of a direct relationship between self-reported anxiety and gaze behaviour. In summary, visual attention to climate change visualisations appears to be mainly influenced by the inherent visual attributes of the maps, but the social context may subtly influence visual attention. Additionally, the comparison with aesthetic viewing highlights relatively distinct attentional patterns in scientific versus aesthetic engagements.

An experiment was conducted to compare museum visitors’ gaze patterns using mobile eye-trackers, whilst they were engaging with a physical and a virtual reality (VR) installation of Piet Mondrian’s Neo-plasticist room design. Visitors’ eye movements produced approximately 25,000 fixations and were analysed using linear mixed-effects models. Absolute and area-normalized dwell time analyses yielded mostly non-significant main effects of the environment, indicating similarity of visual exploration patterns between physical and VR settings. One major difference observed was the decrease of average fixation duration in VR, where visitors tended to more rapidly switch focus in this environment with shorter bursts of attentional focus. The experiment demonstrated the ability to compare gaze data between physical and virtual environments as a proxy to measure the similarity of aesthetic experience. Similarity of viewing patterns along with questionnaire results suggested that virtual galleries can be treated as ecologically valid environments that are parallel to physical art galleries.

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

Focal copy-number amplification is an oncogenic event. Although recent studies have revealed the complex structure 1 – 3 and the evolutionary trajectories 4 of oncogene amplicons, their origin remains poorly understood. Here we show that focal amplifications in breast cancer frequently derive from a mechanism—which we term translocation–bridge amplification—involving inter-chromosomal translocations that lead to dicentric chromosome bridge formation and breakage. In 780 breast cancer genomes, we observe that focal amplifications are frequently connected to each other by inter-chromosomal translocations at their boundaries. Subsequent analysis indicates the following model: the oncogene neighbourhood is translocated in G1 creating a dicentric chromosome, the dicentric chromosome is replicated, and as dicentric sister chromosomes segregate during mitosis, a chromosome bridge is formed and then broken, with fragments often being circularized in extrachromosomal DNAs. This model explains the amplifications of key oncogenes, including ERBB2 and CCND1 . Recurrent amplification boundaries and rearrangement hotspots correlate with oestrogen receptor binding in breast cancer cells. Experimentally, oestrogen treatment induces DNA double-strand breaks in the oestrogen receptor target regions that are repaired by translocations, suggesting a role of oestrogen in generating the initial translocations. A pan-cancer analysis reveals tissue-specific biases in mechanisms initiating focal amplifications, with the breakage–fusion–bridge cycle prevalent in some and the translocation–bridge amplification in others, probably owing to the different timing of DNA break repair. Our results identify a common mode of oncogene amplification and propose oestrogen as its mechanistic origin in breast cancer. An analysis of 780 breast cancer genomes shows that focal amplifications are frequently preceded by dicentric chromosome formation from inter-chromosomal translocations associated with oestrogen receptor binding, which leads to chromosome bridge formation and breakage, initiating the amplification process.

Combined PARP and immune checkpoint inhibition has yielded encouraging results in ovarian cancer, but predictive biomarkers are lacking. We performed immunogenomic profiling and highly multiplexed single-cell imaging on tumor samples from patients enrolled in a Phase I/II trial of niraparib and pembrolizumab in ovarian cancer (NCT02657889). We identify two determinants of response; mutational signature 3 reflecting defective homologous recombination DNA repair, and positive immune score as a surrogate of interferon-primed exhausted CD8 + T-cells in the tumor microenvironment. Presence of one or both features associates with an improved outcome while concurrent absence yields no responses. Single-cell spatial analysis reveals prominent interactions of exhausted CD8 + T-cells and PD-L1 + macrophages and PD-L1 + tumor cells as mechanistic determinants of response. Furthermore, spatial analysis of two extreme responders shows differential clustering of exhausted CD8 + T-cells with PD-L1 + macrophages in the first, and exhausted CD8 + T-cells with cancer cells harboring genomic PD-L1 and PD-L2 amplification in the second. A Phase I/II trial previously revealed variable anti-tumor efficacy of the PARP inhibitor niraparib in combination with the PD-1 inhibitor pembrolizumab in platinum-resistant ovarian cancer patients. Here, the authors perform an integrated genomic and immunomics analysis of tumor samples from the same patients and find potential predictive biomarkers of response to such combination therapy.

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. This study examines karyotypic selection and evolution in vitro using immortalized mammary and kidney epithelial cell lines, observing aneuploidy patterns specific to each origin tissue that are correlated with frequencies in patient tumors and independent of drivers such as TP53 mutation.