Will More of the Same Achieve Malaria Elimination? Results from an Integrated Macroeconomic Epidemiological Demographic Model

Historic levels of funding have reduced the global burden of malaria in recent years. Questions remain, however, as to whether scaling up interventions, in parallel with economic growth, has made malaria elimination more likely today than previously. The consequences of "trying but failing" to eliminate malaria are also uncertain. Reduced malaria exposure decreases the acquisition of semi-immunity during childhood, a necessary phase of the immunological transition that occurs on the pathway to malaria elimination. During this transitional period, the risk of malaria resurgence increases as proportionately more individuals across all age-groups are less able to manage infections by immune response alone. We developed a robust model that integrates the effects of malaria transmission, demography, and macroeconomics in the context of Plasmodium falciparum malaria within a hyperendemic environment. We analyzed the potential for existing interventions, alongside economic development, to achieve malaria elimination. Simulation results indicate that a 2% increase in future economic growth will increase the US$5.1 billion cumulative economic burden of malaria in Ghana to US$7.2 billion, although increasing regional insecticide-treated net coverage rates by 25% will lower malaria reproduction numbers by just 9%, reduce population-wide morbidity by -0.1%, and reduce prevalence from 54% to 46% by 2034. As scaling up current malaria control tools, combined with economic growth, will be insufficient to interrupt malaria transmission in Ghana, high levels of malaria control should be maintained and investment in research and development should be increased to maintain the gains of the past decade and to minimize the risk of resurgence, as transmission drops.

Anticipatory changes in British household purchases of soft drinks associated with the announcement of the Soft Drinks Industry Levy: A controlled interrupted time series analysis

BACKGROUND

Sugar-sweetened beverage (SSB) consumption is positively associated with obesity, type 2 diabetes, and cardiovascular disease. The World Health Organization recommends that member states implement effective taxes on SSBs to reduce consumption. The United Kingdom Soft Drinks Industry Levy (SDIL) is a two-tiered tax, announced in March 2016 and implemented in April 2018. Drinks with ≥8 g of sugar per 100 ml (higher levy tier) are taxed at £0.24 per litre, drinks with ≥5 to <8 g of sugar per 100 ml (lower levy tier) are taxed at £0.18 per litre, and drinks with <5 g sugar per 100 ml (no levy) are not taxed. Milk-based drinks, pure fruit juices, drinks sold as powder, and drinks with >1.2% alcohol by volume are exempt. We aimed to determine if the announcement of the SDIL was associated with anticipatory changes in purchases of soft drinks prior to implementation of the SDIL in April 2018. We explored differences in the volume of and amount of sugar in household purchases of drinks in each levy tier at 2 years post announcement.

METHODS AND FINDINGS

We used controlled interrupted time series to compare observed changes associated with the announcement of the SDIL to the counterfactual scenario of no announcement. We used data from Kantar Worldpanel, a commercial household purchasing panel with approximately 30,000 British members that includes linked nutritional data on purchases. We conducted separate analyses for drinks liable for the SDIL in the higher, lower, and no-levy tiers controlling with household purchase volumes of toiletries. At 2 years post announcement, there was no difference in volume of or sugar from purchases of higher-levy-tier drinks compared to the counterfactual of no announcement. In contrast, a reversal of the existing upward trend in volume (ml) of and amount of sugar (g) in purchases of lower-levy-tier drinks was seen. These changes led to a -96.1 ml (95% confidence interval [CI] -144.2 to -48.0) reduction in volume and -6.4 g (95% CI -9.8 to -3.1) reduction in sugar purchased in these drinks per household per week. There was a reversal of the existing downward trend in the amount of sugar in household purchases of the no-levy drinks but no change in volume purchased. At 2 years post announcement, these changes led to a 6.1 g (95% CI 3.9-8.2) increase in sugar purchased in these drinks per household per week. There was no evidence that volume of or amount of sugar in purchases of all drinks combined was different from the counterfactual. This is an observational study, and changes other than the SDIL may have been responsible for the results reported. Purchases consumed outside of the home were not accounted for.

CONCLUSIONS

The announcement of the UK SDIL was associated with reductions in volume and sugar purchased in lower-levy-tier drinks before implementation. These were offset by increases in sugar purchased from no-levy drinks. These findings may reflect reformulation of drinks from the lower levy to no-levy tier with removal of some but not all sugar, alongside changes in consumer attitudes and beliefs.

TRIAL REGISTRATION

ISRCTN Registry ISRCTN18042742.

Accelerated Aging of Deacidified and Untreated Book Paper in 1967 Compared with 52 Years of Natural Aging

Three copies of a book that had been optionally deacidified using two different procedures in 1967, and then subjected to accelerated aging, were tested again after 52 years of natural aging. Matched copies of the book Cooking the Greek Way, which had been printed in Czechoslovakia on acidic paper, were evaluated. Nonaqueous treatment of two of the copies with magnesium methoxide dissolved in chlorofluorocarbon solvent had been found in 1967 to have decreased the susceptibility to embrittlement, as evidenced by the results of the accelerated aging, followed by folding endurance tests. Retesting of the same books in 2019, after 52 years of room temperature storage, showed that the deacidification treatments had achieved the following benefits in comparison to the untreated book: (a) higher brightness; (b) higher folding endurance; (c) tensile breaking length higher in the cross-direction of the paper; (d) substantial alkaline reserve content, (e) an alkaline surface pH in the range 7.1–7.4, and (f) higher molecular mass of the cellulose. Remarkably, some of the folding endurance results matched those of unaged samples evaluated in 1967. Scanning electron micrographs showed no differences between the treated and untreated books.

Framing and signalling effects of taxes on sugary drinks: A discrete choice experiment among households in Great Britain

Taxes on sugar-sweetened beverages (SSBs) are in place in many countries to combat obesity with emerging evidence that these are effective in reducing purchases of SSBs. In this study, we tested whether signalling and framing the price increase from an SSB tax explicitly as a health-related, earmarked measure reduces the demand for SSBs more than an equivalent price increase. We measured the demand for non-alcoholic beverages with a discrete choice experiment (DCE) administered online to a randomly selected group of n = 603 households with children in Great Britain (GB) who regularly purchase SSBs. We find a suggestive evidence that a price increase leads to a larger reduction in the probability of choosing SSBs when it is signalled as a tax and framed as a health-related and earmarked policy. Respondents who did not support a tax on SSBs, who were also more likely to choose SSBs in the first place, were on average more responsive to a price increase framed as an earmarked tax than those who supported the tax. The predictive validity of the DCE, to capture preferences for beverages, was confirmed using actual purchase data. The findings imply that a well-signalled and earmarked tax on SSBs could improve its effectiveness at reducing the demand.

Patterns of beverage purchases amongst British households: A latent class analysis

BACKGROUND

Beverages, especially sugar-sweetened beverages (SSBs), have been increasingly subject to policies aimed at reducing their consumption as part of measures to tackle obesity. However, precision targeting of policies is difficult as information on what types of consumers they might affect, and to what degree, is missing. We fill this gap by creating a typology of beverage consumers in Great Britain (GB) based on observed beverage purchasing behaviour to determine what distinct types of beverage consumers exist, and what their socio-demographic (household) characteristics, dietary behaviours, and weight status are.

METHODS AND FINDINGS

We used cross-sectional latent class analysis to characterise patterns of beverage purchases. We used data from the 2016 GB Kantar Fast-Moving Consumer Goods (FMCG) panel, a large representative household purchase panel of food and beverages brought home, and restricted our analyses to consumers who purchase beverages regularly (i.e., >52 l per household member annually) (n = 8,675). Six categories of beverages were used to classify households into latent classes: SSBs; diet beverages; fruit juices and milk-based beverages; beer and cider; wine; and bottled water. Multinomial logistic regression and linear regression were used to relate class membership to household characteristics, self-reported weight status, and other dietary behaviours, derived from GB Kantar FMCG. Seven latent classes were identified, characterised primarily by higher purchases of 1 or 2 categories of beverages: 'SSB' (18% of the sample; median SSB volume = 49.4 l/household member/year; median diet beverage volume = 38.0 l), 'Diet' (16%; median diet beverage volume = 94.4 l), 'Fruit & Milk' (6%; median fruit juice/milk-based beverage volume = 30.0 l), 'Beer & Cider' (7%; median beer and cider volume = 36.3 l; median diet beverage volume = 55.6 l), 'Wine' (18%; median wine volume = 25.5 l; median diet beverage volume = 34.3 l), 'Water' (4%; median water volume = 46.9 l), and 'Diverse' (30%; diversity of purchases, including median SSB volume = 22.4 l). Income was positively associated with being classified in the Diverse class, whereas low social grade was more likely for households in the classes SSB, Diet, and Beer & Cider. Obesity (BMI > 30 kg/m2) was more prevalent in the class Diet (41.2%, 95% CI 37.7%-44.7%) despite households obtaining little energy from beverages in that class (17.9 kcal/household member/day, 95% CI 16.2-19.7). Overweight/obesity (BMI > 25 kg/m2) was above average in the class SSB (66.8%, 95% CI 63.7%-69.9%). When looking at all groceries, households from the class SSB had higher total energy purchases (1,943.6 kcal/household member/day, 95% CI 1,901.7-1,985.6), a smaller proportion of energy from fruits and vegetables (6.0%, 95% CI 5.8%-6.3%), and a greater proportion of energy from less healthy food and beverages (54.6%, 95% CI 54.0%-55.1%) than other classes. A greater proportion of energy from sweet snacks was observed for households in the classes SSB (18.5%, 95% CI 18.1%-19.0%) and Diet (18.8%, 95% CI 18.3%-19.3%). The main limitation of our analyses, in common with other studies, is that our data do not include information on food and beverage purchases that are consumed outside the home.

CONCLUSIONS

Amongst households that regularly purchase beverages, those that mainly purchased high volumes of SSBs or diet beverages were at greater risk of obesity and tended to purchase less healthy foods, including a high proportion of energy from sweet snacks. These households might additionally benefit from policies targeting unhealthy foods, such as sweet snacks, as a way of reducing excess energy intake.

Patterns of beverage purchases amongst British households: a latent class analysis

Background

Policies to tackle obesity have increasingly targeted drinks, in particular sugar-sweetened beverages (SSBs), as a major source of excess sugar and energy. However, precision targeting of policies is difficult as information on what types of consumers they might affect, and to what degree, is missing. To fill this gap, we categorised consumers on the basis of drink purchase behaviour and explored whether they are patterned by socio-demographic characteristics, total food purchasing and weight status.

Methods

We used latent class (LC) analysis to characterise patterns of drink purchases using the 2016 UK Kantar FMCG household purchase panel. We restricted analyses to frequent purchasers of drinks (n = 8,675) and used 6 drink categories: SSB; diet drink; fruit-/milk-based drinks; beer & cider; wine; and water. We used multinomial logistic and linear models to relate household characteristics, BMI and food purchase behaviours to LC membership.

Results

We identified 7 LCs. Disadvantaged households were more frequent in LCs with high volumes of SSBs ('SSB') and diet drinks ('Diet'). Higher BMI was more likely in LCs 'Diet' and 'SSB'. LC 'SSB' obtained higher total energy, relatively less energy from fruits and vegetables, and more energy from less healthy products, compared to others. LCs 'Diet' and 'SSB' obtained relatively more energy from sweet snacks.

Conclusions

Households who mainly purchased high volumes of SSBs or diet drinks were at greater risk of obesity and tended to purchase less healthy foods, including a high proportion of energy from sweet snacks. These households might additionally benefit from policies targeting unhealthy foods, such as sweet snacks, as a way of reducing excess energy intake.

Key messages

The effects of fiscal policies on SSB consumption is likely to vary across types of beverage consumers. Fiscal policies should be extended to sweet snacks as a major source of excess energy.

Meta-analysis of peptides to detect protein significance

Shotgun assays are widely used in biotechnologies to characterize large molecules, which are hard to be measured as a whole directly. For instance, in Liquid Chromatography - Mass Spectrometry (LC-MS) shotgun experiments, proteins in biological samples are digested into peptides, and then peptides are separated and measured. However, in proteomics study, investigators are usually interested in the performance of the whole proteins instead of those peptide fragments. In light of meta-analysis, we propose an adaptive thresholding method to select informative peptides, and combine peptide-level models to protein-level analysis. The meta-analysis procedure and modeling rationale can be adapted to data analysis of other types of shotgun assays.

Automated Coupling of Nanodroplet Sample Preparation with Liquid Chromatography-Mass Spectrometry for High-Throughput Single-Cell Proteomics

Single-cell proteomics can provide critical biological insight into the cellular heterogeneity that is masked by bulk-scale analysis. We have developed a nanoPOTS (nanodroplet processing in one pot for trace samples) platform and demonstrated its broad applicability for single-cell proteomics. However, because of nanoliter-scale sample volumes, the nanoPOTS platform is not compatible with automated LC-MS systems, which significantly limits sample throughput and robustness. To address this challenge, we have developed a nanoPOTS autosampler allowing fully automated sample injection from nanowells to LC-MS systems. We also developed a sample drying, extraction, and loading workflow to enable reproducible and reliable sample injection. The sequential analysis of 20 samples containing 10 ng tryptic peptides demonstrated high reproducibility with correlation coefficients of >0.995 between any two samples. The nanoPOTS autosampler can provide analysis throughput of 9.6, 16, and 24 single cells per day using 120, 60, and 30 min LC gradients, respectively. As a demonstration for single-cell proteomics, the autosampler was first applied to profiling protein expression in single MCF10A cells using a label-free approach. At a throughput of 24 single cells per day, an average of 256 proteins was identified from each cell and the number was increased to 731 when the Match Between Runs algorithm of MaxQuant was used. Using a multiplexed isobaric labeling approach (TMT-11plex), ∼77 single cells could be analyzed per day. We analyzed 152 cells from three acute myeloid leukemia cell lines, resulting in a total of 2558 identified proteins with 1465 proteins quantifiable (70% valid values) across the 152 cells. These data showed quantitative single-cell proteomics can cluster cells to distinct groups and reveal functionally distinct differences.

Comprehensive characterization of hepatocyte-derived extracellular vesicles identifies direct miRNA-based regulation of hepatic stellate cells and DAMP-based hepatic macrophage IL-1β and IL-17 upregulation in alcoholic hepatitis mice

Extracellular vesicles (EVs) have been growingly recognized as biomarkers and mediators of alcoholic liver disease (ALD) in human and mice. Here we characterized hepatocyte-derived EVs (HC-EVs) and their cargo for their biological functions in a novel murine model that closely resembles liver pathology observed in patients with alcoholic hepatitis (AH), the most severe spectrum of ALD. The numbers of circulating EVs and HC-EVs were significantly increased by 10-fold in AH mice compared with control mice. The miRNA (miR)-seq analysis detected 20 upregulated and 4 downregulated miRNAs (P < 0.001-0.05) in AH-HC-EVs. Treatment of murine primary hepatic stellate cells (HSCs) with AH-HC-EVs induced α-SMA (P < 0.05) and Col1a1 (P < 0.001). Smad7 and Nr1d2 genes, which were downregulated in HSCs from the AH mice, were predicted targets of 20 miRs upregulated in AH-HC-EVs. Among them were miR-27a and miR-181 which upon transfection in HSCs, indeed repressed Nr1d2, the quiescent HSC marker. AH-HC-EVs were also enriched with organelle proteins and mitochondrial DNA (10-fold, P < 0.05) and upregulated IL-1β and IL-17 production by hepatic macrophages (HMs) from AH mice in a TLR9-dependent manner. These results demonstrate HC-EV release is intensified in AH and suggest that AH-HC-EVs orchestrate liver fibrogenesis by directly targeting the quiescent HSC transcripts via a unique set of miRNAs and by amplifying HSC activation via DAMP-based induction of profibrogenic IL-1β and IL-17 by HMs. KEY MESSAGES: • Circulating EVs and HC-EVs were increased in AH mice compared with control mice • AH-HC-EVs were enriched in miRNAs, organelle proteins, and mitochondrial DNA • AH-HC-EVs increased cytokine production by AH-HMs in a TLR9-dependent manner.

Ultra-High-Resolution Ion Mobility Separations Over Extended Path Lengths and Mobility Ranges Achieved using a Multilevel Structures for Lossless Ion Manipulations Module

Over the past few years, structures for lossless ion manipulations (SLIM) have used traveling waves (TWs) to move ions over long serpentine paths that can be further lengthened by routing the ions through multiple passages of the same path. Such SLIM "multipass" separations provide unprecedentedly high ion mobility resolving powers but are ultimately limited in their ion mobility range because of the range of mobilities spanned in a single pass; that is, higher mobility ions ultimately "overtake" and "lap" lower mobility ions that have experienced fewer passes, convoluting their arrival time distribution at the detector. To achieve ultrahigh resolution separations over broader mobility ranges, we have developed a new multilevel SLIM possessing multiple stacked serpentine paths. Ions are transferred between SLIM levels through apertures (or ion escalators) in the SLIM surfaces. The initial multilevel SLIM module incorporates four levels and three interlevel ion escalator passages, providing a total path length of 43.2 m. Using the full path length and helium buffer gas, high resolution separations were achieved for Agilent tuning mixture phosphazene ions over a broad mobility range (K₀ ≈ 3.0 to 1.2 cm²/(V*s)). High sensitivity was achieved using "in-SLIM" ion accumulation over an extended trapping region of the first SLIM level. High transmission efficiency of ions over a broad mobility range (e.g., K₀ ≈ 3.0 to 1.67 cm²/(V*s)) was achieved, with transmission efficiency rolling off for the lower mobility ions (e.g., K₀ ≈ 1.2 cm²/(V*s)). Resolving powers of up to ∼560 were achieved using all four ion levels to separate reverse peptides (SDGRG¹⁺ and GRGDS¹⁺). A complex mixture of phosphopeptides showed similar coverage could be achieved using one or all four SLIM levels, and doubly charged phosphosite isomers not significantly separated using one SLIM level were well resolved when four levels were used. The new multilevel SLIM technology thus enables wider mobility range ultrahigh-resolution ion mobility separations and expands on the ability of SLIM to obtain improved separations of complex mixtures with high sensitivity.

Proteomic Tissue-Based Classifier for Early Prediction of Prostate Cancer Progression

Although ~40% of screen-detected prostate cancers (PCa) are indolent, advanced-stage PCa is a lethal disease with 5-year survival rates around 29%. Identification of biomarkers for early detection of aggressive disease is a key challenge. Starting with 52 candidate biomarkers, selected from existing PCa genomics datasets and known PCa driver genes, we used targeted mass spectrometry to quantify proteins that significantly differed in primary tumors from PCa patients treated with radical prostatectomy (RP) across three study outcomes: (i) metastasis ≥1-year post-RP, (ii) biochemical recurrence ≥1-year post-RP, and (iii) no progression after ≥10 years post-RP. Sixteen proteins that differed significantly in an initial set of 105 samples were evaluated in the entire cohort (n = 338). A five-protein classifier which combined FOLH1, KLK3, TGFB1, SPARC, and CAMKK2 with existing clinical and pathological standard of care variables demonstrated significant improvement in predicting distant metastasis, achieving an area under the receiver-operating characteristic curve of 0.92 (0.86, 0.99, p = 0.001) and a negative predictive value of 92% in the training/testing analysis. This classifier has the potential to stratify patients based on risk of aggressive, metastatic PCa that will require early intervention compared to low risk patients who could be managed through active surveillance.

Abstract A20: An essential role for Argonaute 2 in mouse models of KRAS driven cancers

In 2016, we identified a direct interaction between RAS and Argonaute 2 (AGO2), a key mediator of RNA-mediated gene silencing that is required for KRAS-driven oncogenesis using pancreatic and lung cancer cell line models. Recently, we employed the genetically engineered mouse model of pancreatic cancer to define the effects of conditional loss of AGO2 in KRASG12D driven pancreatic cancer. Genetic ablation of AGO2 did not interfere with development of the normal pancreas or KRASG12D-driven early precursor pancreatic intraepithelial neoplasia (PanIN) lesions. However, AGO2 loss prevents progression from early to late PanIN lesions, development of pancreatic ductal adenocarcinoma (PDAC), and metastatic progression. This results in a dramatic increase in survival of KRASG12D mutant mice deficient in AGO2 expression. Using validated pan-RAS and AGO2 antibodies for immunofluorescence (IF) and proximity ligation assay (PLA), we observed increased RAS and AGO2 co-localization at the plasma membrane in mouse and human pancreatic tissues associated with PDAC progression. AGO2 ablation permits PanIN initiation driven by the EGFR-RAS axis; however rather than progressing to PDAC, these lesions undergo profound oncogene-induced senescence (OIS). Since PanIN development requires EGFR and is not AGO2 dependent, we probed the effects of EGF stimulation in cell lines expressing wild-type and mutant forms of KRAS (using co-IP and PLA analyses). In wild-type RAS expressing cells, grown in media containing serum, RAS-AGO2 co-localization was limited to the intracellular regions of the cells, which dramatically increased and shifted to the plasma membrane under conditions of stress (serum starvation). Interestingly, EGF stimulation disrupted this membrane RAS-AGO2 interaction and restored it to intracellular basal levels. Using phosphorylation-deficient AGO2 mutants, we demonstrate that the disruption of wild type-RAS-AGO2 interaction is due to AGO2Y393 phosphorylation, a target of EGFR. Interestingly, the mutant KRAS-AGO2 interaction is not subject to EGFR activation, suggesting that although both the wild-type and mutant RAS bind AGO2, they are differentially regulated through growth factor receptor activation. Taken together, our study supports a biphasic model of pancreatic cancer development: an AGO2-independent early phase of PanIN formation reliant on EGFR and wild-type RAS signaling, and an AGO2-dependent phase wherein the mutant KRAS-AGO2 interaction is critical for PDAC progression. In the lung cancer mouse model, we also observed a similar dependence of AGO2 in KRAS-driven lung adenocarcinoma. Along with related abstracts detailing the mechanisms of OIS mediated by AGO2 (Ronald Siebenaler) and evidence of direct interaction between oncogenic KRAS and AGO2 with an affinity of 200nM (Jessica Waninger), we present our latest studies related to the KRAS-AGO2 interaction.

Citation Format: Sunita Shankar, Jean Ching-Yi Tien, Ronald F. Siebenaler, Vijaya L. Dommeti, Sylvia Zelenka-Wang, Jessica Waninger, Xiao-Ming Wang, Kristin M. Juckette, Alice Xu, Seema Chugh, Malay Mody, Sanjana Eyunni, Andrew Goodrum, Grace Tsaloff, Yuping Zhang, Ingrid J. Apel, Lisha Wang, Javed Siddiqui, Richard D. Smith, Heather A. Carlson, John Tesmer, Xuhong Cao, Jiaqi Shi, Chandan Kumar-Sinha, Arul M. Chinnaiyan. An essential role for Argonaute 2 in mouse models of KRAS driven cancers [abstract]. In: Proceedings of the AACR Special Conference on Targeting RAS-Driven Cancers; 2018 Dec 9-12; San Diego, CA. Philadelphia (PA): AACR; Mol Cancer Res 2020;18(5_Suppl):Abstract nr A20.

An Improved Boosting to Amplify Signal with Isobaric Labeling (iBASIL) Strategy for Precise Quantitative Single-cell Proteomics

Mass spectrometry (MS)-based proteomics has great potential for overcoming the limitations of antibody-based immunoassays for antibody-independent, comprehensive, and quantitative proteomic analysis of single cells. Indeed, recent advances in nanoscale sample preparation have enabled effective processing of single cells. In particular, the concept of using boosting/carrier channels in isobaric labeling to increase the sensitivity in MS detection has also been increasingly used for quantitative proteomic analysis of small-sized samples including single cells. However, the full potential of such boosting/carrier approaches has not been significantly explored, nor has the resulting quantitation quality been carefully evaluated. Herein, we have further evaluated and optimized our recent boosting to amplify signal with isobaric labeling (BASIL) approach, originally developed for quantifying phosphorylation in small number of cells, for highly effective analysis of proteins in single cells. This improved BASIL (iBASIL) approach enables reliable quantitative single-cell proteomics analysis with greater proteome coverage by carefully controlling the boosting-to-sample ratio (e.g. in general <100×) and optimizing MS automatic gain control (AGC) and ion injection time settings in MS/MS analysis (e.g. 5E5 and 300 ms, respectively, which is significantly higher than that used in typical bulk analysis). By coupling with a nanodroplet-based single cell preparation (nanoPOTS) platform, iBASIL enabled identification of ∼2500 proteins and precise quantification of ∼1500 proteins in the analysis of 104 FACS-isolated single cells, with the resulting protein profiles robustly clustering the cells from three different acute myeloid leukemia cell lines. This study highlights the importance of carefully evaluating and optimizing the boosting ratios and MS data acquisition conditions for achieving robust, comprehensive proteomic analysis of single cells.

Proteogenomic Characterization of Ovarian HGSC Implicates Mitotic Kinases, Replication Stress in Observed Chromosomal Instability

In the absence of a dominant driving mutation other than uniformly present TP53 mutations, deeper understanding of the biology driving ovarian high-grade serous cancer (HGSC) requires analysis at a functional level, including post-translational modifications. Comprehensive proteogenomic and phosphoproteomic characterization of 83 prospectively collected ovarian HGSC and appropriate normal precursor tissue samples (fallopian tube) under strict control of ischemia time reveals pathways that significantly differentiate between HGSC and relevant normal tissues in the context of homologous repair deficiency (HRD) status. In addition to confirming key features of HGSC from previous studies, including a potential survival-associated signature and histone acetylation as a marker of HRD, deep phosphoproteomics provides insights regarding the potential role of proliferation-induced replication stress in promoting the characteristic chromosomal instability of HGSC and suggests potential therapeutic targets for use in precision medicine trials.

Comparison of ovarian cancer and normal precursors identifies key signaling pathways

Mitotic and cyclin-dependent kinases emerge as potential therapeutic targets

Previously identified hallmarks of homologous repair status and survival are confirmed

Replication stress appears to drive increased chromosomal instability

Rapid and Simultaneous Characterization of Drug Conjugation in Heavy and Light Chains of a Monoclonal Antibody Revealed by High-Resolution Ion Mobility Separations in SLIM

Antibody-drug conjugates (ADCs) have recently gained traction in the biomedical community due to their promise for human therapeutics and an alternative to chemotherapy for cancer. Crucial metrics for ADC efficacy, safety, and selectivity are their drug-antibody ratios (DARs). However, DAR characterization (i.e., determining the average number of conjugated drugs on the antibody) through analytical methods remains challenging due to the heterogeneity of drug conjugation as well as the numerous post-translational modifications possible in the monoclonal antibody. Herein, we report on the use of high-resolution ion mobility spectrometry separations in structures for lossless ion manipulations coupled to mass spectrometry (SLIM IMS-MS) for the rapid and simultaneous characterization of the drug load profile (i.e., stoichiometric distribution of the number of conjugated drugs present on the mAb), determination of the weighted average DAR in both the heavy and light chains of a model antibody-drug conjugate, and calculation of the overall DAR of the ADC. After chemical reduction of the ADC and a subsequent 31.5 m SLIM IMS separation, the various drug-bound antibody species could be well resolved for both chains. We also show significantly higher resolution separations were possible for these large ions with SLIM IMS as compared to ones performed on a commercially available (1 m) drift tube IMS-MS platform. We expect high-resolution SLIM IMS separations will augment the existing toolbox for ADC characterization, particularly to enable the rapid optimization of DAR for a given ADC and thus better understand its potential toxicity and potency.

National Cancer Institute Think-Tank Meeting Report on Proteomic Cartography and Biomarkers at the Single-Cell Level: Interrogation of Premalignant Lesions

A Think-Tank Meeting was convened by the National Cancer Institute (NCI) to solicit experts' opinion on the development and application of multiomic single-cell analyses, and especially single-cell proteomics, to improve the development of a new generation of biomarkers for cancer risk, early detection, diagnosis, and prognosis as well as to discuss the discovery of new targets for prevention and therapy. It is anticipated that such markers and targets will be based on cellular, subcellular, molecular, and functional aberrations within the lesion and within individual cells. Single-cell proteomic data will be essential for the establishment of new tools with searchable and scalable features that include spatial and temporal cartographies of premalignant and malignant lesions. Challenges and potential solutions that were discussed included (i) The best way/s to analyze single-cells from fresh and preserved tissue; (ii) Detection and analysis of secreted molecules and from single cells, especially from a tissue slice; (iii) Detection of new, previously undocumented cell type/s in the premalignant and early stage cancer tissue microenvironment; (iv) Multiomic integration of data to support and inform proteomic measurements; (v) Subcellular organelles-identifying abnormal structure, function, distribution, and location within individual premalignant and malignant cells; (vi) How to improve the dynamic range of single-cell proteomic measurements for discovery of differentially expressed proteins and their post-translational modifications (PTM); (vii) The depth of coverage measured concurrently using single-cell techniques; (viii) Quantitation - absolute or semiquantitative? (ix) Single methodology or multiplexed combinations? (x) Application of analytical methods for identification of biologically significant subsets; (xi) Data visualization of N-dimensional data sets; (xii) How to construct intercellular signaling networks in individual cells within premalignant tumor microenvironments (TME); (xiii) Associations between intrinsic cellular processes and extrinsic stimuli; (xiv) How to predict cellular responses to stress-inducing stimuli; (xv) Identification of new markers for prediction of progression from precursor, benign, and localized lesions to invasive cancer, based on spatial and temporal changes within individual cells; (xvi) Identification of new targets for immunoprevention or immunotherapy-identification of neoantigens and surfactome of individual cells within a lesion.

Picoflow Liquid Chromatography-Mass Spectrometry for Ultrasensitive Bottom-Up Proteomics Using 2-μm-i.d. Open Tubular Columns

In many areas of application, key objectives of chemical separation and analysis are to minimize the sample quantity while maximizing the chemical information obtained. Increasing measurement sensitivity is especially critical for proteomics research, especially when processing trace samples and where multiple measurements are desired. A rich collection of technologies has been developed, but the resulting sensitivity remains insufficient for achieving in-depth coverage of proteomic samples as small as single cells. Here, we combine picoliter-scale liquid chromatography (picoLC) with mass spectrometry (MS) to address this issue. The picoLC employs a 2-μm-i.d. open tubular column to reduce the sample input needed to greatly increase the sensitivity achieved using electrospray ionization (ESI) with MS. With this picoLC-MS system, we show that we can identify ∼1000 proteins reliably using only 75 pg of tryptic peptides, representing a 10-100-fold sensitivity improvement compared with the state-of-the-art liquid chromatography (LC) or capillary electrophoresis (CE)-MS methods. PicoLC-MS extends the limit of separation science and is expected to be a powerful tool for single cell proteomics.

Proteogenomic Characterization of Endometrial Carcinoma

We undertook a comprehensive proteogenomic characterization of 95 prospectively collected endometrial carcinomas, comprising 83 endometrioid and 12 serous tumors. This analysis revealed possible new consequences of perturbations to the p53 and Wnt/β-catenin pathways, identified a potential role for circRNAs in the epithelial-mesenchymal transition, and provided new information about proteomic markers of clinical and genomic tumor subgroups, including relationships to known druggable pathways. An extensive genome-wide acetylation survey yielded insights into regulatory mechanisms linking Wnt signaling and histone acetylation. We also characterized aspects of the tumor immune landscape, including immunogenic alterations, neoantigens, common cancer/testis antigens, and the immune microenvironment, all of which can inform immunotherapy decisions. Collectively, our multi-omic analyses provide a valuable resource for researchers and clinicians, identify new molecular associations of potential mechanistic significance in the development of endometrial cancers, and suggest novel approaches for identifying potential therapeutic targets.

Traveling-Wave-Based Electrodynamic Switch for Concurrent Dual-Polarity Ion Manipulations in Structures for Lossless Ion Manipulations

We describe the development of a dual-polarity traveling-wave (TW) structures for lossless ion manipulations (SLIM) ion mobility spectrometry (IMS) device capable of switching both positive and negative ions that are traveling simultaneously along the same path to different regions of the SLIM. Through simulations, the routing efficiency of the SLIM TW switch was compared to a SLIM direct-current-based (DC) switch developed previously for IMS-MS. We also report on the initial experimental evaluation of a dual-polarity SLIM platform, which uses the TW-based ion switch to achieve higher resolution multipass serpentine ultralong path with extended routing (SUPER) IMS separations. Overall, these results show that the dual-polarity TW switch is not only as effective as DC switching in terms of routing efficiency but also is agnostic to the polarity of the ions being routed.

High-Throughput Single Cell Proteomics Enabled by Multiplex Isobaric Labeling in a Nanodroplet Sample Preparation Platform

Effective extension of mass spectrometry-based proteomics to single cells remains challenging. Herein we combined microfluidic nanodroplet technology with tandem mass tag (TMT) isobaric labeling to significantly improve analysis throughput and proteome coverage for single mammalian cells. Isobaric labeling facilitated multiplex analysis of single cell-sized protein quantities to a depth of ∼1 600 proteins with a median CV of 10.9% and correlation coefficient of 0.98. To demonstrate in-depth high throughput single cell analysis, the platform was applied to measure protein expression in 72 single cells from three murine cell populations (epithelial, immune, and endothelial cells) in <2 days instrument time with over 2 300 proteins identified. Principal component analysis grouped the single cells into three distinct populations based on protein expression with each population characterized by well-known cell-type specific markers. Our platform enables high throughput and unbiased characterization of single cell heterogeneity at the proteome level.

SLIM Ultrahigh Resolution Ion Mobility Spectrometry Separations of Isotopologues and Isotopomers Reveal Mobility Shifts due to Mass Distribution Changes

We report on separations of ion isotopologues and isotopomers using ultrahigh-resolution traveling wave-based Structures for Lossless Ion Manipulations with serpentine ultralong path and extended routing ion mobility spectrometry coupled to mass spectrometry (SLIM SUPER IMS-MS). Mobility separations of ions from the naturally occurring ion isotopic envelopes (e.g., [M], [M+1], [M+2], ... ions) showed the first and second isotopic peaks (i.e., [M+1] and [M+2]) for various tetraalkylammonium ions could be resolved from their respective monoisotopic ion peak ([M]) after SLIM SUPER IMS with resolving powers of ∼400-600. Similar separations were obtained for other compounds (e.g., tetrapeptide ions). Greater separation was obtained using argon versus helium drift gas, as expected from the greater reduced mass contribution to ion mobility described by the Mason-Schamp relationship. To more directly explore the role of isotopic substitutions, we studied a mixture of specific isotopically substituted (15N, 13C, and 2H) protonated arginine isotopologues. While the separations in nitrogen were primarily due to their reduced mass differences, similar to the naturally occurring isotopologues, their separations in helium, where higher resolving powers could also be achieved, revealed distinct additional relative mobility shifts. These shifts appeared correlated, after correction for the reduced mass contribution, with changes in the ion center of mass due to the different locations of heavy atom substitutions. The origin of these apparent mass distribution-induced mobility shifts was then further explored using a mixture of Iodoacetyl Tandem Mass Tag (iodoTMT) isotopomers (i.e., each having the same exact mass, but with different isotopic substitution sites). Again, the observed mobility shifts appeared correlated with changes in the ion center of mass leading to multiple monoisotopic mobilities being observed for some isotopomers (up to a ∼0.04% difference in mobility). These mobility shifts thus appear to reflect details of the ion structure, derived from the changes due to ion rotation impacting collision frequency or momentum transfer, and highlight the potential for new approaches for ion structural characterization.

Tandem Mass Tag Labeling Facilitates Reversed-Phase Liquid Chromatography-Mass Spectrometry Analysis of Hydrophilic Phosphopeptides

Protein phosphorylation is a critical post-translational modification (PTM). Despite recent technological advances in reversed-phase liquid chromatography (RPLC)-mass spectrometry (MS)-based proteomics, comprehensive phosphoproteomic coverage in complex biological systems remains challenging, especially for hydrophilic phosphopeptides with enriched regions of serines, threonines, and tyrosines that often orchestrate critical biological functions. To address this issue, we developed a simple, easily implemented method to introduce a commonly used tandem mass tag (TMT) to increase peptide hydrophobicity, effectively enhancing RPLC-MS analysis of hydrophilic peptides. Different from conventional TMT labeling, this method capitalizes on using a nonprimary amine buffer and TMT labeling occurring before C18-based solid phase extraction. Through phosphoproteomic analyses of MCF7 cells, we have demonstrated that this method can greatly increase the number of identified hydrophilic phosphopeptides and improve MS detection signals. We applied this method to study the peptide QPSSSR, a very hydrophilic tryptic peptide located on the C-terminus of the G protein-coupled receptor (GPCR) CXCR3. Identification of QPSSSR has never been reported, and we were unable to detect it by traditional methods. We validated our TMT labeling strategy by comparative RPLC-MS analyses of both a hydrophilic QPSSSR peptide library as well as common phosphopeptides. We further confirmed the utility of this method by quantifying QPSSSR phosphorylation abundances in HEK 293 cells under different treatment conditions predicted to alter QPSSSR phosphorylation. We anticipate that this simple TMT labeling method can be broadly used not only for decoding GPCR phosphoproteome but also for effective RPLC-MS analysis of other highly hydrophilic analytes.