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Li Ding, Feng Chen and colleagues report a pan-cancer analysis using a new computational tool, HotSpot3D, to identify mutational hotspots in the encoded three-dimensional protein structure, which suggest their functional involvement in cancer. They use a mutation–drug cluster analysis to predict more than 800 potentially druggable mutations. Local concentrations of mutations are well known in human cancers. However, their three-dimensional spatial relationships in the encoded protein have yet to be systematically explored. We developed a computational tool, HotSpot3D, to identify such spatial hotspots (clusters) and to interpret the potential function of variants within them. We applied HotSpot3D to >4,400 TCGA tumors across 19 cancer types, discovering >6,000 intra- and intermolecular clusters, some of which showed tumor and/or tissue specificity. In addition, we identified 369 rare mutations in genes including TP53 , PTEN , VHL , EGFR , and FBXW7 and 99 medium-recurrence mutations in genes such as RUNX1 , MTOR , CA3 , PI3 , and PTPN11 , all mapping within clusters having potential functional implications. As a proof of concept, we validated our predictions in EGFR using high-throughput phosphorylation data and cell-line-based experimental evaluation. Finally, mutation–drug cluster and network analysis predicted over 800 promising candidates for druggable mutations, raising new possibilities for designing personalized treatments for patients carrying specific mutations.

We present analysis of new configurational bias Monte Carlo and molecular dynamics simulation data for bilayers of dipalmitoyl phosphatidyl choline and cholesterol for dipalmitoyl phosphatidyl choline:cholesterol ratios of 24:1, 47:3, 11.5:1, 8:1, 7:1, 4:1, 3:1, 2:1, and 1:1, using long molecular dynamics runs and interspersed configurational bias Monte Carlo to ensure equilibration and enhance sampling. In all cases with cholesterol concentrations above 12.5% the area per molecule of the heterogeneous membrane varied linearly with cholesterol fraction. By extrapolation to pure cholesterol, we find the cross-sectional area of cholesterol in these mixtures is ∼22.3 Å 2. From the slope of the area/molecule relationship, we also find that the phospholipid in these mixtures is in a liquid ordered state with an average cross-sectional area per lipid of 50.7 Å 2, slightly above the molecular area of a pure phospholipid gel. For lower concentrations of cholesterol, the molecular area rises above the straight line, indicating the “melting” of at least some of the phospholipid into a fluid state. Analysis of the lateral distribution of cholesterol molecules in the leaflets reveals peaks in radial distributions of cholesterols at multiples of ∼5 Å. These peaks grow in size as the simulation progresses, suggesting a tendency for small subunits of one lipid plus one cholesterol, hydrogen bonded together, to act as one composite particle, and perhaps to aggregate with other composites. Our results are consistent with experimentally observed effects of cholesterol, including the condensation effect of cholesterol in phospholipid monolayers and the tendency of cholesterol-rich domains to form in cholesterol-lipid bilayers. We are continuing to analyze this tendency on longer timescales and for larger bilayer patches.

We have carried out an atomic-level molecular dynamics simulation of a system of nanoscopic size containing a domain of 18:0 sphingomyelin and cholesterol embedded in a fully hydrated dioleylposphatidylcholine (DOPC) bilayer. To analyze the interaction between the domain and the surrounding phospholipid, we calculate order parameters and area per molecule as a function of molecule type and proximity to the domain. We propose an algorithm based on Voronoi tessellation for the calculation of the area per molecule of various constituents in this ternary mixture. The calculated areas per sphingomyelin and cholesterol are in agreement with previous simulations. The simulation reveals that the presence of the liquid-ordered domain changes the packing properties of DOPC bilayer at a distance as large as ∼8 nm. We calculate electron density profiles and also calculate the difference in the thickness between the domain and the surrounding DOPC bilayer. The calculated difference in thickness is consistent with data obtained in atomic force microscopy experiments.

Viruses drive carcinogenesis in human cancers through diverse mechanisms that have not been fully elucidated but include promoting immune escape. Here we investigated associations between virus-positivity and immune pathway alteration for 2009 tumors across six virus-related cancer types. Analysis revealed that for 3 of 72 human papillomavirus (HPV)-positive head and neck squamous cell carcinoma (HNSC) the HPV genome integrated in immune checkpoint genes PD-L1 or PD-L2 , driving elevated expression in the corresponding gene. In addition to the previously described upregulation of the PD-1 immunosuppressive pathway in Epstein-Barr virus (EBV)-positive stomach tumors, we also observed upregulation of the PD-1 pathway in cytomegalovirus (CMV)-positive tumors. Furthermore, we found signatures of T-cell and B-cell response in HPV-positive HNSC and EBV-positive stomach tumors and HPV-positive HNSC patients were associated with better survival when T-cell signals were detected. Our work reveals that viral infection may recruit immune effector cells, and upregulate PD-1 and CTLA-4 immunosuppressive pathways. Cao et al. show that human papillomavirus-positive, head and neck squamous cell carcinoma patients are associated with better survival when T-cells are activated. This study suggests that viral infection may recruit immune effector cells and that it may activate PD-1 and CTLA-4 immunosuppressive pathways.

Pancreatic ductal adenocarcinoma is a lethal disease with limited treatment options and poor survival. We studied 83 spatial samples from 31 patients (11 treatment-naïve and 20 treated) using single-cell/nucleus RNA sequencing, bulk-proteogenomics, spatial transcriptomics and cellular imaging. Subpopulations of tumor cells exhibited signatures of proliferation, KRAS signaling, cell stress and epithelial-to-mesenchymal transition. Mapping mutations and copy number events distinguished tumor populations from normal and transitional cells, including acinar-to-ductal metaplasia and pancreatic intraepithelial neoplasia. Pathology-assisted deconvolution of spatial transcriptomic data identified tumor and transitional subpopulations with distinct histological features. We showed coordinated expression of TIGIT in exhausted and regulatory T cells and Nectin in tumor cells. Chemo-resistant samples contain a threefold enrichment of inflammatory cancer-associated fibroblasts that upregulate metallothioneins. Our study reveals a deeper understanding of the intricate substructure of pancreatic ductal adenocarcinoma tumors that could help improve therapy for patients with this disease. A multi-omic analysis of pancreatic cancer identifies spatially resolved, heterogeneous cell populations including transitional cell types. Analysis of primary samples identifies treatment-related changes in cross-talk between tumor and stromal cells.

We have carried out a molecular dynamics simulation of a hydrated 18:0 sphingomyelin lipid bilayer. The bilayer contained 1600 sphingomyelin (SM) molecules, and 50,592 water molecules. After construction and initial equilibration, the simulation was run for 3.8 ns at a constant temperature of 50°C and a constant pressure of 1 atm. We present properties of the bilayer calculated from the simulation, and compare with experimental data and with properties of dipalmitoyl phosphatidylcholine (DPPC) bilayers. The SM bilayers are significantly more ordered and compact than DPPC bilayers at the same temperature. SM bilayers also exhibit significant intramolecular hydrogen bonding between phosphate ester oxygen and hydroxyl hydrogen atoms. This results in a decreased hydration in the polar region of the SM bilayer compared with DPPC. Since our simulation system is very large we have calculated the power spectrum of bilayer undulation and peristaltic modes, and we compare these data with similar calculations for DPPC bilayers. We find that the SM bilayer has significantly larger bending modulus and area compressibility compared to DPPC.

The structure and dynamics of the lipid and water components of dioleoylphosphatidylcholine bilayers at various levels of hydration were studied using molecular dynamics (MD) simulations. Equilibration of these systems proceeded by use of a hybrid MD and configurational-bias Monte Carlo technique using one atmosphere of pressure normal to the membrane and a set point for the lateral area derived from experimental Bragg spacings, combined with experimentally derived specific volumes for each of the system components. Membrane surface tensions were observed to be of the order of tens of dyn/cm. The transbilayer molecular fragment peak positions at low hydration were found to agree with experimental neutron and x-ray scattering profiles and previously published simulations. For hydration levels of 5.4, 11.4, and 16 waters/lipid, molecular fragment distributions and order parameters for the headgroup, lipid chains, and water were quantified. Spin-lattice relaxation rates and lateral self-diffusion coefficients of water agreed well with results from experimental nuclear magnetic resonance studies. Relaxation rates of the choline segments and chemical shift anisotropies for the phosphate and carbonyls were computed. Headgroup orientation, as measured by the P-N vector, showed enhanced aligment with the membrane surface at low hydration. The sign of the membrane dipole potential reversed at low hydration, with the membrane interior negative relative to the interlamellar region. Calculation of the number of water molecules in the headgroup hydration shell, as a function of hydration level, supports the hypothesis that the break point in the curve of Bragg spacing versus hydration level near 12 waters/lipid, observed experimentally by Hristova and White (1998. Biophys. J. 74:2419–2433), marks the completion of the first hydration shell.

A hierarchical computational strategy combining molecular modeling, electrostatics calculations, molecular dynamics, and Brownian dynamics simulations is developed and implemented to compute electrophysiologically measurable properties of the KcsA potassium channel. Models for a series of channels with different pore sizes are developed from the known x-ray structure, using insights into the gating conformational changes as suggested by a variety of published experiments. Information on the pH dependence of the channel gating is incorporated into the calculation of potential profiles for K + ions inside the channel, which are then combined with K + ion mobilities inside the channel, as computed by molecular dynamics simulations, to provide inputs into Brownian dynamics simulations for computing ion fluxes. The open model structure has a conductance of ∼110 pS under symmetric 250 mM K + conditions, in reasonable agreement with experiments for the largest conducting substate. The dimensions of this channel are consistent with electrophysiologically determined size dependence of quaternary ammonium ion blocking from the intracellular end of this channel as well as with direct structural evidence that tetrabutylammonium ions can enter into the interior cavity of the channel. Realistic values of Ussing flux ratio exponents, distribution of ions within the channel, and shapes of the current-voltage and current-concentration curves are obtained. The Brownian dynamics calculations suggest passage of ions through the selectivity filter proceeds by a “knock-off” mechanism involving three ions, as has been previously inferred from functional and structural studies of barium ion blocking. These results suggest that the present calculations capture the essential nature of K + ion permeation in the KcsA channel and provide a proof-of-concept for the integrated microscopic/mesoscopic multitiered approach for predicting ion channel function from structure, which can be applied to other channel structures.

Ion channels are part of nature’s solution for regulating biological environments. Every ion channel consists of a chain of amino acids carrying a strong and sharply varying permanent charge, folded in such a way that it creates a nanoscopic aqueous pore spanning the otherwise mostly impermeable membranes of biological cells. These naturally occurring proteins are particularly interesting to device engineers seeking to understand how such nanoscale systems realize device-like functions. Availability of high-resolution structural information from X-ray crystallography, as well as large-scale computational resources, makes it possible to conduct realistic ion channel simulations. In general, a hierarchy of simulation methodologies is needed to study different aspects of a biological system like ion channels. Biology Monte Carlo (BioMOCA), a three-dimensional coarse-grained particle ion channel simulator, offers a powerful and general approach to study ion channel permeation. BioMOCA is based on the Boltzmann Transport Monte Carlo (BTMC) and Particle-Particle-Particle-Mesh (P 3 M) methodologies developed at the University of Illinois at Urbana-Champaign. In this paper we briefly discuss the various approaches to simulating ion flow in channel systems that are currently being pursued by the biophysics and engineering communities, and present the effect of having anisotropic dielectric constants on ion flow through a number of nanopores with different effective diameters.

Background Distinct prevalence of inherited genetic predisposition may partially explain the difference of cancer risks across ancestries. Ancestry-specific analyses of germline genomes are required to inform cancer genetic risk and prognosis of diverse populations. Methods We conducted analyses using germline and somatic sequencing data generated by The Cancer Genome Atlas. Collapsing pathogenic and likely pathogenic variants to cancer predisposition genes (CPG), we analyzed the association between CPGs and cancer types within ancestral groups. We also identified the predisposition-associated two-hit events and gene expression effects in tumors. Results Genetic ancestry analysis classified the cohort of 9899 cancer cases into individuals of primarily European ( N  = 8184, 82.7%), African ( N  = 966, 9.8%), East Asian ( N  = 649, 6.6%), South Asian ( N  = 48, 0.5%), Native/Latin American ( N  = 41, 0.4%), and admixed ( N  = 11, 0.1%) ancestries. In the African ancestry, we discovered a potentially novel association of BRCA2 in lung squamous cell carcinoma (OR = 41.4 [95% CI, 6.1–275.6]; FDR = 0.002) previously identified in Europeans, along with a known association of BRCA2 in ovarian serous cystadenocarcinoma (OR = 8.5 [95% CI, 1.5–47.4]; FDR = 0.045). In the East Asian ancestry, we discovered one previously known association of BRIP1 in stomach adenocarcinoma (OR = 12.8 [95% CI, 1.8–90.8]; FDR = 0.038). Rare variant burden analysis further identified 7 suggestive associations in African ancestry individuals previously described in European ancestry, including SDHB in pheochromocytoma and paraganglioma, ATM in prostate adenocarcinoma, VHL in kidney renal clear cell carcinoma, FH in kidney renal papillary cell carcinoma, and PTEN in uterine corpus endometrial carcinoma. Most predisposing variants were found exclusively in one ancestry in the TCGA and gnomAD datasets. Loss of heterozygosity was identified for 7 out of the 15 African ancestry carriers of predisposing variants. Further, tumors from the SDHB or BRCA2 carriers showed simultaneous allelic-specific expression and low gene expression of their respective affected genes, and FH splice-site variant carriers showed mis-splicing of FH . Conclusions While several CPGs are shared across patients, many pathogenic variants are found to be ancestry-specific and trigger somatic effects. Studies using larger cohorts of diverse ancestries are required to pinpoint ancestry-specific genetic predisposition and inform genetic screening strategies.