David Spetzler

Microsecond time scale rotation measurements of single F1-ATPase molecules

A novel method for detecting F(1)-ATPase rotation in a manner sufficiently sensitive to achieve acquisition rates with a time resolution of 2.5 micros (equivalent to 400,000 fps) is reported. This is sufficient for resolving the rate at which the gamma-subunit travels from one dwell state to another (transition time). Rotation is detected via a gold nanorod attached to the rotating gamma-subunit of an immobilized F(1)-ATPase. Variations in scattered light intensity allow precise measurement of changes in the angular position of the rod below the diffraction limit of light. Using this approach, the transition time of Escherichia coli F(1)-ATPase gamma-subunit rotation was determined to be 7.62 +/- 0.15 (standard deviation) rad/ms. The average rate-limiting dwell time between rotation events observed at the saturating substrate concentration was 8.03 ms, comparable to the observed Mg(2+)-ATPase k(cat) of 130 s(-)(1) (7.7 ms). Histograms of scattered light intensity from ATP-dependent nanorod rotation as a function of polarization angle allowed the determination of the nanorod orientation with respect to the axis of rotation and plane of polarization. This information allowed the drag coefficient to be determined, which implied that the instantaneous torque generated by F(1) was 63.3 +/- 2.9 pN nm. The high temporal resolution of rotation allowed the measurement of the instantaneous torque of F(1), resulting in direct implications for its rotational mechanism.

Direct observation of stepped proteolipid ring rotation in E. coli FoF1-ATP synthase

Although single‐molecule experiments have provided mechanistic insight for several molecular motors, these approaches have proved difficult for membrane bound molecular motors like the FoF1‐ATP synthase, in which proton transport across a membrane is used to synthesize ATP. Resolution of smaller steps in Fo has been particularly hampered by signal‐to‐noise and time resolution. Here, we show the presence of a transient dwell between Fo subunits a and c by improving the time resolution to 10 μs at unprecedented S/N, and by using Escherichia coli FoF1 embedded in lipid bilayer nanodiscs. The transient dwell interaction requires 163 μs to form and 175 μs to dissociate, is independent of proton transport residues aR210 and cD61, and behaves as a leash that allows rotary motion of the c‐ring to a limit of ∼36° while engaged. This leash behaviour satisfies a requirement of a Brownian ratchet mechanism for the Fo motor where c‐ring rotational diffusion is limited to 36°.

Single Molecule Measurements of F1-ATPase Reveal an Interdependence between the Power Stroke and the Dwell Duration

Increases in the power stroke and dwell durations of single molecules of Escherichia coli F(1)-ATPase were measured in response to viscous loads applied to the motor and inhibition of ATP hydrolysis. The load was varied using different sizes of gold nanorods attached to the rotating gamma subunit and/or by increasing the viscosity of the medium using PEG-400, a noncompetitive inhibitor of ATPase activity. Conditions that increase the duration of the power stroke were found to cause 20-fold increases in the length of the dwell. These results suggest that the order of hydrolysis, product release, and substrate binding may change as the result of external load on the motor or inhibition of hydrolysis.

Mutational burden, immune checkpoint expression, and mismatch repair in glioma: Implications for immune checkpoint immunotherapy

Background Despite a multiplicity of clinical trials testing immune checkpoint inhibitors, the frequency of expression of potential predictive biomarkers is unknown in glioma. Methods In this study, we profiled the frequency of shared biomarker phenotypes. To clarify the relationships among tumor mutational load (TML), mismatch repair (MMR), and immune checkpoint expression, we profiled patients with glioma (n = 327), including glioblastoma (GBM) (n = 198), whose samples had been submitted for analysis from 2009 to 2016. The calculation algorithm for TML included nonsynonymous mutation counts per tumor, with germline mutations filtered out. Immunohistochemical analysis and next-generation sequencing were used to determine tumor-infiltrating lymphocyte expression positive for programmed cell death protein 1 (PD-1), PD ligand 1 (PD-L1) expression on tumor cells, MMR (MLH1, MSH2, MSH6, and PMS2) protein expression and mutations, and DNA polymerase epsilon (POLE) mutations. Results High TML was only found in 3.5% of GBM patients (7 of 198) and was associated with the absence of protein expression of mutL homolog 1 (MLH1) (P = .0345), mutS homolog 2 (MSH2) (P = .0099), MSH6 (P = .0022), and postmeiotic segregation increased 2 (PMS2) (P = .0345) and the presence of DNA MMR mutations. High and moderate TML GBMs did not have an enriched influx of CD8+ T cells, PD-1+ T cells, or tumor-expressed PD-L1. IDH1 mutant gliomas were not enriched for high TML, PD-1+ T cells, or PD-L1 expression. Conclusions To clarify the relationships among TML, MMR, and immune checkpoint expression, we profiled the frequency of shared biomarker phenotypes. On the basis of a variety of potential biomarkers of response to immune checkpoints, only small subsets of glioma patients are likely to benefit from monotherapy immune checkpoint inhibition.

Microsecond resolution of single-molecule rotation catalyzed by molecular motors.

Single-molecule measurements of rotation catalyzed by the F(1)-ATPase or the F(o)F(1) ATP synthase have provided new insights into the molecular mechanisms of the F(1) and F(o) molecular motors. We recently developed a method to record ATPase-driven rotation of F(1) or F(o)F(1) in a manner that solves several technical limitations of earlier approaches that were significantly hampered by time and angular resolution, and restricted the duration of data collection. With our approach it is possible to collect data for hours and obtain statistically significant quantities of data on each molecule examined with a time resolution of up to 5 μs at unprecedented signal-to-noise.

Determination of torque generation from the power stroke of Escherichia coli F1-ATPase

The torque generated by the power stroke of Escherichia coli F(1)-ATPase was determined as a function of the load from measurements of the velocity of the gamma-subunit obtained using a 0.25 micros time resolution and direct measurements of the drag from 45 to 91 nm gold nanorods. This result was compared to values of torque calculated using four different drag models. Although the gamma-subunit was able to rotate with a 20x increase in viscosity, the transition time decreased from 0.4 ms to 5.26 ms. The torque was measured to be 63+/-8 pN nm, independent of the load on the enzyme.

Microsatellite instability status determined by next-generation sequencing and compared with PD-L1 and tumor mutational burden in 11,348 patients

Microsatellite instability (MSI) testing identifies patients who may benefit from immune checkpoint inhibitors. We developed an MSI assay that uses data from a commercially available next‐generation sequencing (NGS) panel to determine MSI status. The assay is applicable across cancer types and does not require matched samples from normal tissue. Here, we describe the MSI‐NGS method and explore the relationship of MSI with tumor mutational burden (TMB) and PD‐L1. MSI examined by PCR fragment analysis and NGS was compared for 2189 matched cases. Mismatch repair status by immunohistochemistry was compared to MSI‐NGS for 1986 matched cases. TMB was examined by NGS, and PD‐L1 was determined by immunohistochemistry. Among 2189 matched cases that spanned 26 cancer types, MSI‐NGS, as compared to MSI by PCR fragment analysis, had sensitivity of 95.8% (95% confidence interval [CI] 92.24, 98.08), specificity of 99.4% (95% CI 98.94, 99.69), positive predictive value of 94.5% (95% CI 90.62, 97.14), and negative predictive value of 99.2% (95% CI, 98.75, 99.57). High MSI (MSI‐H) status was identified in 23 of 26 cancer types. Among 11,348 cases examined (including the 2189 matched cases), the overall rates of MSI‐H, TMB‐high, and PD‐L1 positivity were 3.0%, 7.7%, and 25.4%, respectively. Thirty percent of MSI‐H cases were TMB‐low, and only 26% of MSI‐H cases were PD‐L1 positive. The overlap between TMB, MSI, and PD‐L1 differed among cancer types. Only 0.6% of the cases were positive for all three markers. MSI‐H status can be determined by NGS across cancer types. MSI‐H offers distinct data for treatment decisions regarding immune checkpoint inhibitors, in addition to the data available from TMB and PD‐L1.

Plasma Exosome Profiling of Cancer Patients by a Next Generation Systems Biology Approach.

Technologies capable of characterizing the full breadth of cellular systems need to be able to measure millions of proteins, isoforms, and complexes simultaneously. We describe an approach that fulfils this criterion: Adaptive Dynamic Artificial Poly-ligand Targeting (ADAPT). ADAPT employs an enriched library of single-stranded oligodeoxynucleotides (ssODNs) to profile complex biological samples, thus achieving an unprecedented coverage of system-wide, native biomolecules. We used ADAPT as a highly specific profiling tool that distinguishes women with or without breast cancer based on circulating exosomes in their blood. To develop ADAPT, we enriched a library of ~1011 ssODNs for those associating with exosomes from breast cancer patients or controls. The resulting 106 enriched ssODNs were then profiled against plasma from independent groups of healthy and breast cancer-positive women. ssODN-mediated affinity purification and mass spectrometry identified low-abundance exosome-associated proteins and protein complexes, some with known significance in both normal homeostasis and disease. Sequencing of the recovered ssODNs provided quantitative measures that were used to build highly accurate multi-analyte signatures for patient classification. Probing plasma from 500 subjects with a smaller subset of 2000 resynthesized ssODNs stratified healthy, breast biopsy-negative, and -positive women. An AUC of 0.73 was obtained when comparing healthy donors with biopsy-positive patients.

Impact of molecular profiling on overall survival of patients with advanced ovarian cancer

Objective Patients with recurrent epithelial ovarian cancer (EOC) have limited treatment options. Studies have reported that biomarker profiling may help predict patient response to available treatments. This study sought to determine the value of biomarker profiling in recurrent EOC. Results Patients in the Matched cohort had a median OS of 36 months compared to 27 months for patients in the Unmatched cohort (HR 0.62, 95% CI 0.41-0.96; p < 0.03). Individual biomarkers were analyzed, with TUBB3, and PGP prognostic for survival. Biomarker analysis also identified a molecular subtype (positive for at least two of the following markers: ERCC1, RRM1, TUBB3, PGP) with particularly poor overall survival. Methods 224 patients from a commercial registry (NCT02678754) with stage IIIC/IV EOC at diagnosis, or restaged to IIIC/IV EOC at the time of molecular profiling, were retrospectively divided into two cohorts based on whether or not the drugs they received matched their profile recommendations. The Matched cohort received no drugs predicted to be lack-of-benefit while the Unmatched cohort received at least one drug predicted to be lack-of-benefit. Profile biomarker/drug associations were based on multiple test platforms including immunohistochemistry, fluorescent in situ hybridization and DNA sequencing. Conclusions This report demonstrates the ability of multi-platform molecular profiling to identify EOC patients at risk of inferior survival. It also suggests a potential beneficial role of avoidance of lack-of-benefit therapies which, when administered, resulted in decreased survival relative to patients who received only therapies predicted to be of benefit.

Abstract 3607: Differential protein expression and miR content of sorted subsets of circulating microvesicles from cancer patients and healthy controls

Proceedings: AACR 103rd Annual Meeting 2012‐‐ Mar 31‐Apr 4, 2012; Chicago, IL MicroRNAs (miRs) are small non-coding RNAs that are 20 to 25 nucleotides in length and regulate expression of entire families of genes. A major source of circulating miRs in cancer patients is believed to be circulating microvesicles (cMV) within biologic fluids such as blood. The transfer of these modifiers of RNA translation from diseased cells into the bloodstream can have broad impacts on disease detection, progression and/or prognosis. The goal of these studies was to determine whether there are differences in miR composition within different subpopulations of cMV based on surface protein composition. We used flow cytometry to phenotype and sort plasma-derived cMV from 20 individuals (3 breast cancer, 2 lung cancer, 6 prostate cancer, 1 bladder cancer and 6 non-cancer controls). cMV were stained for proteins associated with membranes such as tetraspanins (CD9, 63, 81) Ago2 and/or GW182 using a Beckman Coulter MoFlo XDP. For phenotypic analysis, events were gated on tetraspanin expression to distinguish cMV from nano-sized irrelevant debris, and co-expression of GW182 and Ago2 was determined. Quadrant-based sorting was performed for single- and double-positive events. miR content was determined using conventional Taqman probes with the ABI 7900 thermal cycler on extracted RNA from the sorted cMV. The results of these studies demonstrate that unfractionated cMV were not able to discriminate cancers from non-cancers using miRs-let-7a, -16, -22, -148a or -451 in this population of patients. When sorted tetraspanin+, Ago2+ and/or GW182+ populations of cMV were compared, miR expression was generally 5-fold higher in cancer patients than in healthy controls. These studies demonstrate that cMV can be consistently phenotyped, analyzed and sorted using a flow cytometer and that subpopulations of cMV contain unique miR profiles which can be useful in distinguishing cancer plasma from non-cancer plasma. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 3607. doi:1538-7445.AM2012-3607