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The tumor microenvironment (TME) promotes tumor cell invasion and metastasis. An important step in the shift to a pro-cancerous microenvironment is the transformation of normal stromal fibroblasts to carcinoma-associated fibroblasts (CAFs). CAFs are present in a majority of solid tumors and can directly promote tumor cell motility via cytokine, chemokine and growth factor secretion into the TME. The exact effects that the TME has upon cytoskeletal regulation in motile tumor cells remain enigmatic. The conserved formin family of cytoskeleton regulating proteins plays an essential role in the assembly and/or bundling of unbranched actin filaments. Mammalian Diaphanous-related formin 2 (mDia2/DIAPH3/Drf3/Dia) assembles a dynamic F-actin cytoskeleton that underlies tumor cell migration and invasion. We therefore sought to understand whether CAF-derived chemokines impact breast tumor cell motility through modification of the formin-assembled F-actin cytoskeleton. In MDA-MB-231 cells, conditioned media (CM) from WS19T CAFs, a human breast tumor-adjacent CAF line, significantly and robustly increased wound closure and invasion relative to normal human mammary fibroblast (HMF)-CM. WS19T-CM also promoted proteasome-mediated mDia2 degradation in MDA-MB-231 cells relative to control HMF-CM and WS21T CAF-CM, a breast CAF cell line that failed to promote robust MDA-MB-231 migration. Cytokine array analysis of CM identified up-regulated secreted factors in WS19T relative to control WS21T CM. We identified CXCL12 as a CM factor influencing loss of mDia2 protein while increasing MDA-MB-231 cell migration. Our data suggest a mechanism whereby CAFs promote tumor cell migration and invasion through CXCL12 secretion to regulate the mDia2-directed cytoskeleton in breast tumor cells.

Multi-cellular spheroids are enriched in ascites of epithelial ovarian cancer (OvCa) patients. They represent an invasive and chemoresistant cellular population fundamental to metastatic dissemination. The molecular mechanisms triggering single cell invasive egress from spheroids remain enigmatic. mDia formins are Rho GTPase effectors that are key regulators of F-actin cytoskeletal dynamics. We hypothesized that mDia2-driven F-actin dynamics promote single cell invasive transitions in clinically relevant three-dimensional (3D) OvCa spheroids. The current study is a dissection of the contribution of the F-actin assembly factor mDia2 formin in invasive transitions and using a clinically relevant ovarian cancer spheroid model. We show that RhoA-directed mDia2 activity is required for tight spheroid organization, and enrichment of mDia2 in the invasive cellular protrusions of collagen-embedded OVCA429 spheroids. Depleting mDia2 in ES-2 spheroids enhanced invasive dissemination of single amoeboid-shaped cells. This contrasts with spheroids treated with control siRNA, where a mesenchymal invasion program predominated. Inhibition of another RhoA effector, ROCK, had no impact on ES-2 spheroid formation but dramatically inhibited spheroid invasion through induction of a highly elongated morphology. Concurrent inhibition of ROCK and mDia2 blocked single cell invasion from ES-2 spheroids more effectively than inhibition of either protein alone, indicating that invasive egress of amoeboid cells from mDia2-depleted spheroids is ROCK-dependent. Our findings indicate that multiple GTPase effectors must be suppressed in order to fully block invasive egress from ovarian cancer spheroids. Furthermore, tightly regulated interplay between ROCK and mDia2 signaling pathways dictates the invasive capacities and the type of invasion program utilized by motile spheroid-derived ovarian cancer cells. As loss of the gene encoding mDia2, DRF3, has been linked to cancer progression and metastasis, our results set the stage for understanding molecular mechanisms involved in mDia2-dependent egress of invasive cells from primary epithelial tumors.

Glioblastoma (GBM) is a progressive and lethal brain cancer. Malignant control of actin and microtubule cytoskeletal mechanics facilitates two major GBM therapeutic resistance strategies—diffuse invasion and tumor microtube network formation. Actin and microtubule reorganization is controlled by Rho-GTPases, which exert their effects through downstream effector protein activation, including Rho-associated kinases (ROCK) 1 and 2 and mammalian diaphanous-related (mDia) formins (mDia1, 2, and 3). Precise spatial and temporal balancing of the activity between these effectors dictates cell shape, adhesion turnover, and motility. Using small molecules targeting mDia, we demonstrated that global agonism (IMM02) was superior to antagonism (SMIFH2) as anti-invasion strategies in GBM spheroids. Here, we use IDH-wild-type GBM patient-derived cell models and a novel semi-adherent in vitro system to investigate the relationship between ROCK and mDia in invasion and tumor microtube networks. IMM02-mediated mDia agonism disrupts invasion in GBM patient-derived spheroid models, in part by inducing mDia expression loss and tumor microtube network collapse. Pharmacological disruption of ROCK prevented invasive cell-body movement away from GBM spheres, yet induced ultralong, phenotypically abnormal tumor microtube formation. Simultaneously targeting mDia and ROCK did not enhance the anti-invasive/-tumor microtube effects of IMM02. Our data reveal that targeting mDia is a viable GBM anti-invasion/-tumor microtube networking strategy, while ROCK inhibition is contraindicated.

This article documents the muon reconstruction and identification efficiency obtained by the ATLAS experiment for 139 fb-1 of pp collision data at s=13 TeV collected between 2015 and 2018 during Run 2 of the LHC. The increased instantaneous luminosity delivered by the LHC over this period required a reoptimisation of the criteria for the identification of prompt muons. Improved and newly developed algorithms were deployed to preserve high muon identification efficiency with a low misidentification rate and good momentum resolution. The availability of large samples of Z→μμ and J/ψ→μμ decays, and the minimisation of systematic uncertainties, allows the efficiencies of criteria for muon identification, primary vertex association, and isolation to be measured with an accuracy at the per-mille level in the bulk of the phase space, and up to the percent level in complex kinematic configurations. Excellent performance is achieved over a range of transverse momenta from 3 GeV to several hundred GeV, and across the full muon detector acceptance of |η|<2.7.

Jet energy scale and resolution measurements with their associated uncertainties are reported for jets using 36–81 fb-1 of proton–proton collision data with a centre-of-mass energy of s=13 TeV collected by the ATLAS detector at the LHC. Jets are reconstructed using two different input types: topo-clusters formed from energy deposits in calorimeter cells, as well as an algorithmic combination of charged-particle tracks with those topo-clusters, referred to as the ATLAS particle-flow reconstruction method. The anti-kt jet algorithm with radius parameter R=0.4 is the primary jet definition used for both jet types. This result presents new jet energy scale and resolution measurements in the high pile-up conditions of late LHC Run 2 as well as a full calibration of particle-flow jets in ATLAS. Jets are initially calibrated using a sequence of simulation-based corrections. Next, several in situ techniques are employed to correct for differences between data and simulation and to measure the resolution of jets. The systematic uncertainties in the jet energy scale for central jets (|η|<1.2) vary from 1% for a wide range of high-pT jets (2502.5TeV). The relative jet energy resolution is measured and ranges from (24±1.5)% at 20 GeV to (6±0.5)% at 300 GeV.

The luminosity determination for the ATLAS detector at the LHC during Run 2 is presented, with pp collisions at a centre-of-mass energy s = 13  TeV. The absolute luminosity scale is determined using van der Meer beam separation scans during dedicated running periods in each year, and extrapolated to the physics data-taking regime using complementary measurements from several luminosity-sensitive detectors. The total uncertainties in the integrated luminosity for each individual year of data-taking range from 0.9% to 1.1%, and are partially correlated between years. After standard data-quality selections, the full Run 2 pp data sample corresponds to an integrated luminosity of 140.1 ± 1.2   fb - 1 , i.e. an uncertainty of 0.83%. A dedicated sample of low-pileup data recorded in 2017–2018 for precision Standard Model physics measurements is analysed separately, and has an integrated luminosity of 338.1 ± 3.1   pb - 1 .

The ATLAS experiment has developed extensive software and distributed computing systems for Run 3 of the LHC. These systems are described in detail, including software infrastructure and workflows, distributed data and workload management, database infrastructure, and validation. The use of these systems to prepare the data for physics analysis and assess its quality are described, along with the software tools used for data analysis itself. An outlook for the development of these projects towards Run 4 is also provided.

The flavour-tagging algorithms developed by the ATLAS Collaboration and used to analyse its dataset of s = 13  TeV pp collisions from Run 2 of the Large Hadron Collider are presented. These new tagging algorithms are based on recurrent and deep neural networks, and their performance is evaluated in simulated collision events. These developments yield considerable improvements over previous jet-flavour identification strategies. At the 77% b -jet identification efficiency operating point, light-jet (charm-jet) rejection factors of 170 (5) are achieved in a sample of simulated Standard Model t t ¯ events; similarly, at a c -jet identification efficiency of 30%, a light-jet ( b -jet) rejection factor of 70 (9) is obtained.

Electron and photon triggers covering transverse energies from 5  GeV to several TeV are essential for the ATLAS experiment to record signals for a wide variety of physics: from Standard Model processes to searches for new phenomena in both proton–proton and heavy-ion collisions. To cope with a fourfold increase of peak LHC luminosity from 2015 to 2018 (Run 2), to 2.1 × 10 34 cm - 2 s - 1 , and a similar increase in the number of interactions per beam-crossing to about 60, trigger algorithms and selections were optimised to control the rates while retaining a high efficiency for physics analyses. For proton–proton collisions, the single-electron trigger efficiency relative to a single-electron offline selection is at least 75% for an offline electron of 31  GeV , and rises to 96% at 60  GeV ; the trigger efficiency of a 25  GeV leg of the primary diphoton trigger relative to a tight offline photon selection is more than 96% for an offline photon of 30  GeV . For heavy-ion collisions, the primary electron and photon trigger efficiencies relative to the corresponding standard offline selections are at least 84% and 95%, respectively, at 5  GeV above the corresponding trigger threshold.

A search for the electroweak production of charginos and sleptons decaying into final states with two electrons or muons is presented. The analysis is based on 139 fb−1 of proton–proton collisions recorded by the ATLAS detector at the Large Hadron Collider at s√=13 TeV. Three R-parity-conserving scenarios where the lightest neutralino is the lightest supersymmetric particle are considered: the production of chargino pairs with decays via either W bosons or sleptons, and the direct production of slepton pairs. The analysis is optimised for the first of these scenarios, but the results are also interpreted in the others. No significant deviations from the Standard Model expectations are observed and limits at 95% confidence level are set on the masses of relevant supersymmetric particles in each of the scenarios. For a massless lightest neutralino, masses up to 420 GeV are excluded for the production of the lightest-chargino pairs assuming W-boson-mediated decays and up to 1 TeV for slepton-mediated decays, whereas for slepton-pair production masses up to 700 GeV are excluded assuming three generations of mass-degenerate sleptons.