Genomic Hallmarks and Structural Variation in Metastatic Prostate Cancer.

While mutations affecting protein-coding regions have been examined across many cancers, structural variants at the genome-wide level are still poorly defined. Through integrative deep whole-genome and -transcriptome analysis of 101 castration-resistant prostate cancer metastases (109X tumor/38X normal coverage), we identified structural variants altering critical regulators of tumorigenesis and progression not detectable by exome approaches. Notably, we observed amplification of an intergenic enhancer region 624 kb upstream of the androgen receptor (AR) in 81% of patients, correlating with increased AR expression. Tandem duplication hotspots also occur near MYC, in lncRNAs associated with post-translational MYC regulation. Classes of structural variations were linked to distinct DNA repair deficiencies, suggesting their etiology, including associations of CDK12 mutation with tandem duplications, TP53 inactivation with inverted rearrangements and chromothripsis, and BRCA2 inactivation with deletions. Together, these observations provide a comprehensive view of how structural variations affect critical regulators in metastatic prostate cancer.

Deep whole-genome ctDNA chronology of treatment-resistant prostate cancer.

Circulating tumour DNA (ctDNA) in blood plasma is an emerging tool for clinical cancer genotyping and longitudinal disease monitoring1. However, owing to past emphasis on targeted and low-resolution profiling approaches, our understanding of the distinct populations that comprise bulk ctDNA is incomplete2-12. Here we perform deep whole-genome sequencing of serial plasma and synchronous metastases in patients with aggressive prostate cancer. We comprehensively assess all classes of genomic alterations and show that ctDNA contains multiple dominant populations, the evolutionary histories of which frequently indicate whole-genome doubling and shifts in mutational processes. Although tissue and ctDNA showed concordant clonally expanded cancer driver alterations, most individual metastases contributed only a minor share of total ctDNA. By comparing serial ctDNA before and after clinical progression on potent inhibitors of the androgen receptor (AR) pathway, we reveal population restructuring converging solely on AR augmentation as the dominant genomic driver of acquired treatment resistance. Finally, we leverage nucleosome footprints in ctDNA to infer mRNA expression in synchronously biopsied metastases, including treatment-induced changes in AR transcription factor signalling activity. Our results provide insights into cancer biology and show that liquid biopsy can be used as a tool for comprehensive multi-omic discovery.

HER2 overexpression in urothelial carcinoma with GATA3 and PPARG copy number gains.

HER2, encoded by the ERBB2 gene, is an important druggable driver of human cancer gaining increasing importance as a therapeutic target in urothelial carcinoma (UC). The genomic underpinnings of HER2 overexpression in ERBB2 nonamplified UC are poorly defined. To address this knowledge gap, we investigated 172 UC tumors from patients treated at the University of California San Francisco, using immunohistochemistry and next-generation sequencing. We found that GATA3 and PPARG copy number gains individually predicted HER2 protein expression independently of ERBB2 amplification. To validate these findings, we interrogated the Memorial Sloan Kettering/The Cancer Genome Atlas (MSK/TCGA) dataset and found that GATA3 and PPARG copy number gains individually predicted ERBB2 mRNA expression independently of ERBB2 amplification. Our findings reveal a potential link between the luminal marker HER2 and the key transcription factors GATA3 and PPARG in UC and highlight the utility of examining GATA3 and PPARG copy number states to identify UC tumors that overexpress HER2 in the absence of ERBB2 amplification. In summary, we found that an increase in copy number of GATA3 and PPARG was independently associated with higher ERBB2 expression in patient samples of UC. This finding provides a potential explanation for HER2 overexpression in UC tumors without ERBB2 amplification and a way to identify these tumors for HER2-targeted therapies.

AARDVARK: an automated reversion detector for variants affecting resistance kinetics.

SUMMARY: Resistance to two classes of FDA-approved therapies that target DNA repair-deficient tumors is caused by mutations that restore the tumor cell's DNA repair function. Identifying these "reversion" mutations currently requires manual annotation of patient tumor sequence data. Here we present AARDVARK, an R package that automatically identifies reversion mutations from DNA sequence data. AVAILABILITY AND IMPLEMENTATION: AARDVARK is implemented in R (≥3.5). It is available on GitHub at https://github.com/davidquigley/aardvark. It is licensed under the MIT license.

Understanding the impact of ammonium ion substitutions on heterogeneous ice nucleation.

Understanding the mechanisms underpinning heterogeneous ice nucleation in the presence of ionic inclusions is important for fields such as cryopreservation and for improved models of climate and weather prediction. Feldspar and ammonium are both present in significant quantities in the atmosphere, and experimental evidence has shown that feldspar can nucleate ice from ammonium-containing solutions at temperatures warmer than water alone. In recent work, Whale hypothesised that this increase in nucleation temperature is due to an increase in configurational entropy when an ammonium ion is included in the ice hydrogen bond network (T. F. Whale, J. Chem. Phys., 2022, 156, 144503). In this work, we investigate the impact of the inclusion of an ammonium ion on the hydrogen bond network by direct enumeration of the number of structures found using Rick's algorithm. We also determine the energy of these systems and thus compare the effects of enthalpy and entropy to test Whale's hypothesis. We find that the inclusion of an ammonium ion increases the total number of configurations under conditions consistent with a realistic surface charge. We also find that the enthalpic contribution is dominant in determining the location of the ammonium ion within the structure, although we note that this neglects other practicalities of ice nucleation.

Mapping the influence of impurity interaction energy on nucleation in a lattice-gas model of solute precipitation.

We study nucleation in the two dimensional Ising lattice-gas model of solute precipitation in the presence of randomly placed static and dynamic impurities. Impurity-solute and impurity-solvent interaction energies are varied whilst keeping other interaction energies fixed. In the case of static impurities, we observe a monotonic decrease in the nucleation rate when the difference between impurity-solute and impurity-solvent interaction energies is increased. The nucleation rate saturates to a minimum value with increasing interaction energy difference when the impurity density is low. However the nucleation rate does not saturate for high impurity densities. Similar behaviour is observed with dynamic impurities both at low and high densities. We explore a broad range of both symmetric and anti-symmetric interactions with impurities and map the regime for which the impurities act as a surfactant, decreasing the surface energy of the nucleating phase. We also characterise different nucleation regimes observed at different values of interaction energy. These include additional regimes where impurities play the role of inert-spectators, bulk-stabilizers or cluster together to create heterogeneous nucleation sites for solute clusters to form.

Interplay of multiple clusters and initial interface positioning for forward flux sampling simulations of crystal nucleation.

Forward flux sampling (FFS) is a path sampling technique widely used in computer simulations of crystal nucleation from the melt. In such studies, the order parameter underpinning the progress of the FFS algorithm is often the size of the largest crystalline nucleus. In this work, we investigate the effects of two computational aspects of FFS simulations, using the prototypical Lennard-Jones liquid as our computational test bed. First, we quantify the impact of the positioning of the liquid basin and first interface in the space of the order parameter. In particular, we demonstrate that these choices are key to ensuring the consistency of the FFS results. Second, we focus on the frequently encountered scenario where the population of crystalline nuclei is such that there are multiple clusters of size comparable to the largest one. We demonstrate the contribution of clusters other than the largest cluster to the initial flux; however, we also show that they can be safely ignored for the purposes of converging a full FFS calculation. We also investigate the impact of different clusters merging, a process that appears to be facilitated by substantial spatial correlations-at least at the supercooling considered here. Importantly, all of our results have been obtained as a function of system size, thus contributing to the ongoing discussion on the impact of finite size effects on simulations of crystal nucleation. Overall, this work either provides or justifies several practical guidelines for performing FFS simulations that can also be applied to more complex and/or computationally expensive models.

Transcriptional profiling identifies an androgen receptor activity-low, stemness program associated with enzalutamide resistance.

The androgen receptor (AR) antagonist enzalutamide is one of the principal treatments for men with castration-resistant prostate cancer (CRPC). However, not all patients respond, and resistance mechanisms are largely unknown. We hypothesized that genomic and transcriptional features from metastatic CRPC biopsies prior to treatment would be predictive of de novo treatment resistance. To this end, we conducted a phase II trial of enzalutamide treatment (160 mg/d) in 36 men with metastatic CRPC. Thirty-four patients were evaluable for the primary end point of a prostate-specific antigen (PSA)50 response (PSA decline ≥50% at 12 wk vs. baseline). Nine patients were classified as nonresponders (PSA decline <50%), and 25 patients were classified as responders (PSA decline ≥50%). Failure to achieve a PSA50 was associated with shorter progression-free survival, time on treatment, and overall survival, demonstrating PSA50's utility. Targeted DNA-sequencing was performed on 26 of 36 biopsies, and RNA-sequencing was performed on 25 of 36 biopsies that contained sufficient material. Using computational methods, we measured AR transcriptional function and performed gene set enrichment analysis (GSEA) to identify pathways whose activity state correlated with de novo resistance. TP53 gene alterations were more common in nonresponders, although this did not reach statistical significance (P = 0.055). AR gene alterations and AR expression were similar between groups. Importantly, however, transcriptional measurements demonstrated that specific gene sets-including those linked to low AR transcriptional activity and a stemness program-were activated in nonresponders. Our results suggest that patients whose tumors harbor this program should be considered for clinical trials testing rational agents to overcome de novo enzalutamide resistance.

Kinetic control of competing nuclei in a dimer lattice-gas model.

Nucleation is a key step in the synthesis of a new material from a solution. The well-established lattice-gas models can be used to gain insight into the basic physics of nucleation pathways involving a single nucleus type. In many situations, a solution is supersaturated with respect to more than one precipitating phase. This can generate a population of both stable and metastable nuclei on similar timescales and, hence, complex nucleation pathways involving a competition between the two. In this study, we introduce a lattice-gas model based on two types of interacting dimers representing the particles in a solution. Each type of dimer nucleates to a specific space-filling structure. Our model is tuned such that stable and metastable phases nucleate on a similar timescale. Either structure may nucleate first, with a probability sensitive to the relative rate at which a solute is replenished from their respective reservoirs. We calculate these nucleation rates via forward flux sampling and demonstrate how the resulting data can be used to infer the nucleation outcome and pathway. Possibilities include direct nucleation of the stable phase, domination of long-lived metastable crystallites, and pathways in which the stable phase nucleates only after multiple post-critical nuclei of the metastable phase have appeared.

Model-Independent Simulation Complexity of Complex Quantum Dynamics.

We present a model-independent measure of dynamical complexity based on simulation of complex quantum dynamics using stroboscopic Markovian dynamics. Tools from classical signal processing enable us to infer the Hilbert space dimension of the complex quantum system evolving under a time-independent Hamiltonian via pulsed interrogation. We illustrate this using simulated third-order pump-probe spectroscopy data for exciton transport in a toy model of a coupled dimer with vibrational levels, revealing the dimension of the singly excited manifold of the dimer. Finally, we probe the complexity of excitonic transport in light harvesting 2 (LH2) and Fenna-Matthews-Olson (FMO) complexes using data from two recent nonlinear ultrafast optical spectroscopy experiments. For the latter we make model-independent inferences that are commensurate with model-specific ones, including the estimation of the fewest number of parameters needed to fit the experimental data and identifying the spatial extent, i.e., delocalization size, of quantum states participating in this complex quantum dynamics.

Nucleation rate in the two dimensional Ising model in the presence of random impurities.

Nucleation phenomena are ubiquitous in nature and the presence of impurities in every real and experimental system is unavoidable. Yet numerical studies of nucleation are nearly always conducted for entirely pure systems. We have studied the behaviour of the droplet free energy in two dimensional Ising model in the presence of randomly positioned static and dynamic impurities. We have shown that both the free energy barrier height and critical nucleus size monotonically decreases with increasing the impurity density for the static case. We have compared the nucleation rates obtained from the Classical Nucleation Theory and the Forward Flux Sampling method for different densities of the static impurities. The results show good agreement. In the case of dynamic impurities, we observe preferential occupancy of the impurities at the boundary positions of the nucleus when the temperature is low. This further boosts enhancement of the nucleation rate due to lowering of the effective interfacial free energy.

The mutational landscapes of genetic and chemical models of Kras-driven lung cancer.

Next-generation sequencing of human tumours has refined our understanding of the mutational processes operative in cancer initiation and progression, yet major questions remain regarding the factors that induce driver mutations and the processes that shape mutation selection during tumorigenesis. Here we performed whole-exome sequencing on adenomas from three mouse models of non-small-cell lung cancer, which were induced either by exposure to carcinogens (methyl-nitrosourea (MNU) and urethane) or by genetic activation of Kras (Kras(LA2)). Although the MNU-induced tumours carried exactly the same initiating mutation in Kras as seen in the Kras(LA2) model (G12D), MNU tumours had an average of 192 non-synonymous, somatic single-nucleotide variants, compared with only six in tumours from the Kras(LA2) model. By contrast, the Kras(LA2) tumours exhibited a significantly higher level of aneuploidy and copy number alterations compared with the carcinogen-induced tumours, suggesting that carcinogen-induced and genetically engineered models lead to tumour development through different routes. The wild-type allele of Kras has been shown to act as a tumour suppressor in mouse models of non-small-cell lung cancer. We demonstrate that urethane-induced tumours from wild-type mice carry mostly (94%) Kras Q61R mutations, whereas those from Kras heterozygous animals carry mostly (92%) Kras Q61L mutations, indicating a major role for germline Kras status in mutation selection during initiation. The exome-wide mutation spectra in carcinogen-induced tumours overwhelmingly display signatures of the initiating carcinogen, while adenocarcinomas acquire additional C > T mutations at CpG sites. These data provide a basis for understanding results from human tumour genome sequencing, which has identified two broad categories of tumours based on the relative frequency of single-nucleotide variations and copy number alterations, and underline the importance of carcinogen models for understanding the complex mutation spectra seen in human cancers.

The seven deadly sins: When computing crystal nucleation rates, the devil is in the details.

The formation of crystals has proven to be one of the most challenging phase transformations to quantitatively model-let alone to actually understand-be it by means of the latest experimental technique or the full arsenal of enhanced sampling approaches at our disposal. One of the most crucial quantities involved with the crystallization process is the nucleation rate, a single elusive number that is supposed to quantify the average probability for a nucleus of critical size to occur within a certain volume and time span. A substantial amount of effort has been devoted to attempt a connection between the crystal nucleation rates computed by means of atomistic simulations and their experimentally measured counterparts. Sadly, this endeavor almost invariably fails to some extent, with the venerable classical nucleation theory typically blamed as the main culprit. Here, we review some of the recent advances in the field, focusing on a number of perhaps more subtle details that are sometimes overlooked when computing nucleation rates. We believe it is important for the community to be aware of the full impact of aspects, such as finite size effects and slow dynamics, that often introduce inconspicuous and yet non-negligible sources of uncertainty into our simulations. In fact, it is key to obtain robust and reproducible trends to be leveraged so as to shed new light on the kinetics of a process, that of crystal nucleation, which is involved into countless practical applications, from the formulation of pharmaceutical drugs to the manufacturing of nano-electronic devices.

Inflammation and Hras signaling control epithelial-mesenchymal transition during skin tumor progression.

Epithelial-mesenchymal transition (EMT) is thought to be an important, possibly essential, component of the process of tumor dissemination and metastasis. About 20%-30% of Hras mutant mouse skin carcinomas induced by chemical initiation/promotion protocols have undergone EMT. Reduced exposure to TPA-induced chronic inflammation causes a dramatic reduction in classical papillomas and squamous cell carcinomas (SCCs), but the mice still develop highly invasive carcinomas with EMT properties, reduced levels of Hras and Egfr signaling, and frequent Ink4/Arf deletions. Deletion of Hras from the mouse germline also leads to a strong reduction in squamous tumor development, but tumors now acquire activating Kras mutations and exhibit more aggressive metastatic properties. We propose that invasive carcinomas can arise by different genetic and biological routes dependent on exposure to chronic inflammation and possibly from different target cell populations within the skin. Our data have implications for the use of inhibitors of inflammation or of Ras/Egfr pathway signaling for prevention or treatment of invasive cancers.

Prostate cancer research: The next generation; report from the 2019 Coffey-Holden Prostate Cancer Academy Meeting.

INTRODUCTION: The 2019 Coffey-Holden Prostate Cancer Academy (CHPCA) Meeting, "Prostate Cancer Research: The Next Generation," was held 20 to 23 June, 2019, in Los Angeles, California. METHODS: The CHPCA Meeting is an annual conference held by the Prostate Cancer Foundation, that is uniquely structured to stimulate intense discussion surrounding topics most critical to accelerating prostate cancer research and the discovery of new life-extending treatments for patients. The 7th Annual CHPCA Meeting was attended by 86 investigators and concentrated on many of the most promising new treatment opportunities and next-generation research technologies. RESULTS: The topics of focus at the meeting included: new treatment strategies and novel agents for targeted therapies and precision medicine, new treatment strategies that may synergize with checkpoint immunotherapy, next-generation technologies that visualize tumor microenvironment (TME) and molecular pathology in situ, multi-omics and tumor heterogeneity using single cells, 3D and TME models, and the role of extracellular vesicles in cancer and their potential as biomarkers. DISCUSSION: This meeting report provides a comprehensive summary of the talks and discussions held at the 2019 CHPCA Meeting, for the purpose of globally disseminating this knowledge and ultimately accelerating new treatments and diagnostics for patients with prostate cancer.

An integrated molecular profile of endometrioid ovarian cancer.

OBJECTIVE: Endometrioid ovarian carcinoma (EOVC) is an uncommon subtype of epithelial ovarian carcinoma and its molecular characteristics have been incompletely described. Prior sequencing investigations have been limited to targeted gene panels. We performed whole-exome sequencing to build an unbiased genetic profile of molecular alterations in endometrioid ovarian tumors with a goal to better understand this disease in the context of epithelial ovarian cancer and endometrioid uterine cancers. METHODS: Whole-exome sequencing was performed on EOVC samples (n = 26) and matched normals (n = 15). Gene mutations, mutational signatures and copy number variations (CNVs) informed a multi-dimensional regression classifier allowing for comparison to endometrial carcinoma (UCEC) and high grade serous ovarian carcinoma (HGSC). RESULTS: EOVC has a distinct and heterogeneous genomic profile. Identified significantly mutated genes in EOVC (PTEN, CTNNB1, PIK3CA, KMT2D, KMT2B, PIK3R1, ARID1A and TP53) occurred at similar frequencies in UCEC. Hypermutation, resulting from both mismatch repair deficiency (MMRd) and POLE mutation, was observed in EOVC at a frequency similar to UCEC. Like UCEC, a subset of EOVC cases closely resembled HGSC, harboring TP53 mutations, homologous recombination deficiency (HRd) mutation signatures and widespread CNVs. A machine-learning classifier confirmed the heterogeneous composition of EOVC. Potential therapeutic targets were identified in 62% of EOVC cases. We validated our findings in an orthogonal clinical sequencing registry of EOVC cases. CONCLUSIONS: We identified that EOVC are a molecularly heterogeneous group of epithelial ovarian cancers with distinct mutational signatures. In an age of precision oncology, there is a pressing need to understand the unique molecular drivers in uncommon histologic subtypes to facilitate genomically driven oncologic treatments.

High density is a property of slow-cycling and treatment-resistant human glioblastoma cells.

Slow-cycling and treatment-resistant cancer cells escape therapy, providing a rationale for regrowth and recurrence in patients. Much interest has focused on identifying the properties of slow-cycling tumor cells in glioblastoma (GBM), the most common and lethal primary brain tumor. Despite aggressive ionizing radiation (IR) and treatment with the alkylating agent temozolomide (TMZ), GBM patients invariably relapse and ultimately succumb to the disease. In patient biopsies, we demonstrated that GBM cells expressing the proliferation markers Ki67 and MCM2 displayed a larger cell volume compared to rare slow-cycling tumor cells. In optimized density gradients, we isolated a minor fraction of slow-cycling GBM cells in patient biopsies and tumorsphere cultures. Transcriptional profiling, self-renewal, and tumorigenicity assays reflected the slow-cycling state of high-density GBM cells (HDGCs) compared to the tumor bulk of low-density GBM cells (LDGCs). Slow-cycling HDGCs enriched for stem cell antigens proliferated a few days after isolation to generate LDGCs. Both in vitro and in vivo, we demonstrated that HDGCs show increased treatment-resistance to IR and TMZ treatment compared to LDGCs. In conclusion, density gradients represent a non-marker based approach to isolate slow-cycling and treatment-resistant GBM cells across GBM subgroups.

Midland non-invasive ventilation score: a tool to predict non-invasive ventilation failure in people with acute hypercapnic respiratory failure.

Use of non-invasive ventilation (NIV) in patients with hypercapnic respiratory failure has clear benefits over invasive ventilation. Existing risk prediction models are complex and difficult to apply in the acute setting. We developed the Midland NIV score comprising only five parameters for use to predict NIV failure (in-hospital death or intubation) at initiation. Individuals with Midland NIV score of ≤11 (average 13% NIV failure) may be suitable for general ward care, compared to intensive care for those with Midland NIV score ≥12 (average 66% NIV failure rate). Prospective external validation is required.

The role of nuclear quantum effects in the relative stability of hexagonal and cubic ice.

At atmospheric pressure, hexagonal ice (Ih) is thermodynamically stable relative to cubic ice (Ic), although the magnitude and underlying physical origin of this stability difference are not well defined. Pure Ic crystals are not accessible experimentally, and hence computer simulations have often been used to interrogate the relative stabilities of Ih and Ic; however, these simulations are dominated by molecular interaction models that ignore the intramolecular flexibility of individual water molecules, do not describe intermolecular hydrogen-bonding with sufficient accuracy, or ignore the role of nuclear quantum effects (NQEs) such as zero-point energy. Here, we show that when comparing the relative stability of Ih and Ic using a flexible, anharmonic molecular interaction model, while also accurately accounting for NQEs, a new picture emerges: Ih is stabilized relative to Ic as a result of subtle differences in the intramolecular geometries and intermolecular interactions of water molecules which are modulated by NQEs. Our simulations hence suggest that NQEs are a major contributor to the stabilization of Ih under terrestrial conditions and thus contribute to the well-known hexagonal (sixfold) symmetry of ice crystals.