Topological data analysis reveals a core gene expression backbone that defines form and function across flowering plants.

Since they emerged approximately 125 million years ago, flowering plants have evolved to dominate the terrestrial landscape and survive in the most inhospitable environments on earth. At their core, these adaptations have been shaped by changes in numerous, interconnected pathways and genes that collectively give rise to emergent biological phenomena. Linking gene expression to morphological outcomes remains a grand challenge in biology, and new approaches are needed to begin to address this gap. Here, we implemented topological data analysis (TDA) to summarize the high dimensionality and noisiness of gene expression data using lens functions that delineate plant tissue and stress responses. Using this framework, we created a topological representation of the shape of gene expression across plant evolution, development, and environment for the phylogenetically diverse flowering plants. The TDA-based Mapper graphs form a well-defined gradient of tissues from leaves to seeds, or from healthy to stressed samples, depending on the lens function. This suggests that there are distinct and conserved expression patterns across angiosperms that delineate different tissue types or responses to biotic and abiotic stresses. Genes that correlate with the tissue lens function are enriched in central processes such as photosynthetic, growth and development, housekeeping, or stress responses. Together, our results highlight the power of TDA for analyzing complex biological data and reveal a core expression backbone that defines plant form and function.

Reaction-diffusion modeling provides insights into biophysical carbon concentrating mechanisms in land plants.

Carbon concentrating mechanisms (CCMs) have evolved numerous times in photosynthetic organisms. They elevate the concentration of CO2 around the carbon-fixing enzyme rubisco, thereby increasing CO2 assimilatory flux and reducing photorespiration. Biophysical CCMs, like the pyrenoid-based CCM of Chlamydomonas reinhardtii or carboxysome systems of cyanobacteria, are common in aquatic photosynthetic microbes, but in land plants appear only among the hornworts. To predict the likely efficiency of biophysical CCMs in C3 plants, we used spatially resolved reaction-diffusion models to predict rubisco saturation and light use efficiency. We found that the energy efficiency of adding individual CCM components to a C3 land plant is highly dependent on the permeability of lipid membranes to CO2, with values in the range reported in the literature that are higher than used in previous modeling studies resulting in low light use efficiency. Adding a complete pyrenoid-based CCM into the leaf cells of a C3 land plant was predicted to boost net CO2 fixation, but at higher energetic costs than those incurred by photorespiratory losses without a CCM. Two notable exceptions were when substomatal CO2 levels are as low as those found in land plants that already employ biochemical CCMs and when gas exchange is limited, such as with hornworts, making the use of a biophysical CCM necessary to achieve net positive CO2 fixation under atmospheric CO2 levels. This provides an explanation for the uniqueness of hornworts' CCM among land plants and evolution of pyrenoids multiple times.

Reimport of carbon from cytosolic and vacuolar sugar pools into the Calvin-Benson cycle explains photosynthesis labeling anomalies.

SignificancePhotosynthesis metabolites are quickly labeled when 13CO2 is fed to leaves, but the time course of labeling reveals additional contributing processes involved in the metabolic dynamics of photosynthesis. The existence of three such processes is demonstrated, and a metabolic flux model is developed to explore and characterize them. The model is consistent with a slow return of carbon from cytosolic and vacuolar sugars into the Calvin-Benson cycle through the oxidative pentose phosphate pathway. Our results provide insight into how carbon assimilation is integrated into the metabolic network of photosynthetic cells with implications for global carbon fluxes.

Accurate flux predictions using tissue-specific gene expression in plant metabolic modeling.

MOTIVATION: The accurate prediction of complex phenotypes such as metabolic fluxes in living systems is a grand challenge for systems biology and central to efficiently identifying biotechnological interventions that can address pressing industrial needs. The application of gene expression data to improve the accuracy of metabolic flux predictions using mechanistic modeling methods such as flux balance analysis (FBA) has not been previously demonstrated in multi-tissue systems, despite their biotechnological importance. We hypothesized that a method for generating metabolic flux predictions informed by relative expression levels between tissues would improve prediction accuracy. RESULTS: Relative gene expression levels derived from multiple transcriptomic and proteomic datasets were integrated into FBA predictions of a multi-tissue, diel model of Arabidopsis thaliana's central metabolism. This integration dramatically improved the agreement of flux predictions with experimentally based flux maps from 13C metabolic flux analysis compared with a standard parsimonious FBA approach. Disagreement between FBA predictions and MFA flux maps was measured using weighted averaged percent error values, and for parsimonious FBA this was169%-180% for high light conditions and 94%-103% for low light conditions, depending on the gene expression dataset used. This fell to 10%-13% and 9%-11% upon incorporating expression data into the modeling process, which also substantially altered the predicted carbon and energy economy of the plant. AVAILABILITY AND IMPLEMENTATION: Code and data generated as part of this study are available from https://github.com/Gibberella/ArabidopsisGeneExpressionWeights.

Five-year survival outcomes for patients with advanced melanoma treated with pembrolizumab in KEYNOTE-001.

BACKGROUND: Pembrolizumab demonstrated robust antitumor activity and safety in the phase Ib KEYNOTE-001 study (NCT01295827) of advanced melanoma. Five-year outcomes in all patients and treatment-naive patients are reported herein. Patients whose disease progressed following initial response and who received a second course of pembrolizumab were also analyzed. PATIENTS AND METHODS: Patients aged ≥18 years with previously treated or treatment-naive advanced/metastatic melanoma received pembrolizumab 2 mg/kg every 3 weeks, 10 mg/kg every 3 weeks, or 10 mg/kg every 2 weeks until disease progression, intolerable toxicity, or patient/investigator decision to withdraw. Kaplan-Meier estimates of overall survival (OS) and progression-free survival (PFS) were calculated. Objective response rate and PFS were based on immune-related response criteria by investigator assessment (data cut-off, September 1, 2017). RESULTS: KEYNOTE-001 enrolled 655 patients with melanoma; median follow-up was 55 months. Estimated 5-year OS was 34% in all patients and 41% in treatment-naive patients; median OS was 23.8 months (95% CI, 20.2-30.4) and 38.6 months (95% CI, 27.2-not reached), respectively. Estimated 5-year PFS rates were 21% in all patients and 29% in treatment-naive patients; median PFS was 8.3 months (95% CI, 5.8-11.1) and 16.9 months (95% CI, 9.3-35.5), respectively. Median response duration was not reached; 73% of all responses and 82% of treatment-naive responses were ongoing at data cut-off; the longest response was ongoing at 66 months. Four patients [all with prior response of complete response (CR)] whose disease progressed during observation subsequently received second-course pembrolizumab. One patient each achieved CR and partial response (after data cut-off). Treatment-related AEs (TRAEs) occurred in 86% of patients and resulted in study discontinuation in 7.8%; 17% experienced grade 3/4 TRAE. CONCLUSIONS: This 5-year analysis of KEYNOTE-001 represents the longest follow-up for pembrolizumab to date and confirms the durable antitumor activity and tolerability of pembrolizumab in advanced melanoma. CLINICAL TRIAL REGISTRY: ClinicalTrials.gov, NCT01295827.

Meta-analysis in metastatic uveal melanoma to determine progression free and overall survival benchmarks: an international rare cancers initiative (IRCI) ocular melanoma study.

BACKGROUND: Despite the completion of numerous phase II studies, a standard of care treatment has yet to be defined for metastatic uveal melanoma (mUM). To determine benchmarks of progression free survival (PFS) and overall survival (OS), we carried out a meta-analysis using individual patient level trial data. METHODS: Individual patient variables and survival outcomes were requested from 29 trials published from 2000 to 2016. Univariable and multivariable analysis were carried out for prognostic factors. The variability between trial arms and between therapeutic agents on PFS and OS was investigated. RESULTS: OS data were available for 912 patients. The median PFS was 3.3 months (95% CI 2.9-3.6) and 6-month PFS rate was 27% (95% CI 24-30). Univariable analysis showed male sex, elevated (i.e. > versus ≤ upper limit of normal) lactate dehydrogenase (LDH), elevated alkaline phosphatase (ALP) and diameter of the largest liver metastasis (≥3 cm versus <3 cm) to be substantially associated with shorter PFS. Multivariable analysis showed male sex, elevated LDH and elevated ALP were substantially associated with shorter PFS. The most substantial factors associated with 6-month PFS rate, on both univariable and multivariable analysis were elevated LDH and ALP. The median OS was 10.2 months (95% CI 9.5-11.0) and 1 year OS was 43% (95% CI 40-47). The most substantial prognostic factors for shorter OS by univariable and multivariable analysis were elevated LDH and elevated ALP. Patients treated with liver directed treatments had statistically significant longer PFS and OS. CONCLUSION: Benchmarks of 6-month PFS and 1-year OS rates were determined accounting for prognostic factors. These may be used to facilitate future trial design and stratification in mUM.

Resource utilization and costs of managing patients with advanced melanoma: a Canadian population-based study.

BACKGROUND: The use and detailed costs of services provided for people with advanced melanoma (amel) are not well known. We conducted an analysis to determine the use of health care services and the associated costs delineated by relevant attributable costs, which we defined for subjects in the province of Ontario. METHODS: Through the Ontario Cancer Data Linkage Project, a cohort of amel patients with diagnoses between 31 August 2005 and 2012 (follow-up to 2013) and with valid International Classification of Diseases (9th revision, Clinical Modification) 172 codes and histology codes was identified. A cohort of individuals with amel having a combination of at least 1 palliative, 1 medical oncology, and 1 hospitalization code was generated. The health system services used by this population were clustered into hospitalization, palliation, physician medical visits, medication, homecare, laboratory, diagnostics, and other resources. Overall rates of use and disaggregated costs were determined by phase of care for the entire cohort. RESULTS: The mean age for the 2748 individuals in the cohort was 67 years. The greater proportion of the patients were men (65.6%) and were more than 65 years of age (>50%). In this advanced cohort, fewer than 45% of patients were alive 3 years after the malignant melanoma diagnosis. The average annual cost per patient over the time horizon was $6,551. At $15,830, year 1 after diagnosis was the most expensive, followed by year 2, at $8,166. CONCLUSIONS: Our data provide a baseline for the costs associated with amel treatment. Future studies will include newer agents and comparative effectiveness research for personalized therapies.

A prognostic index model for predicting overall survival in patients with metastatic castration-resistant prostate cancer treated with abiraterone acetate after docetaxel.

BACKGROUND: Few prognostic models for overall survival (OS) are available for patients with metastatic castration-resistant prostate cancer (mCRPC) treated with recently approved agents. We developed a prognostic index model using readily available clinical and laboratory factors from a phase III trial of abiraterone acetate (hereafter abiraterone) in combination with prednisone in post-docetaxel mCRPC. PATIENTS AND METHODS: Baseline data were available from 762 patients treated with abiraterone-prednisone. Factors were assessed for association with OS through a univariate Cox model and used in a multivariate Cox model with a stepwise procedure to identify those of significance. Data were validated using an independent, external, population-based cohort. RESULTS: Six risk factors individually associated with poor prognosis were included in the final model: lactate dehydrogenase > upper limit of normal (ULN) [hazard ratio (HR) = 2.31], Eastern Cooperative Oncology Group performance status of 2 (HR = 2.19), presence of liver metastases (HR = 2.00), albumin ≤4 g/dl (HR = 1.54), alkaline phosphatase > ULN (HR = 1.38) and time from start of initial androgen-deprivation therapy to start of treatment ≤36 months (HR = 1.30). Patients were categorized into good (n = 369, 46%), intermediate (n = 321, 40%) and poor (n = 107, 13%) prognosis groups based on the number of risk factors and relative HRs. The C-index was 0.70 ± 0.014. The model was validated by the external dataset (n = 286). CONCLUSION: This analysis identified six factors used to model survival in mCRPC and categorized patients into three distinct risk groups. Prognostic stratification with this model could assist clinical practice decisions for follow-up and monitoring, and may aid in clinical trial design. TRIAL REGISTRATION NUMBERS: NCT00638690.

Burden of illness for metastatic melanoma in Canada, 2011-2013.

BACKGROUND: Detailed epidemiology for patients with advanced metastatic melanoma in Canada is not well characterized. We conducted an analysis of patients with this disease in the province of Ontario, with the aim being to study the presentation, disease characteristics and course, and treatment patterns for malignant melanoma. METHODS: In this Canadian observational prospective and retrospective study of patients with malignant melanoma, we used data collected in the Canadian Melanoma Research Network (cmrn) Patient Registry. We identified patients who were seen at 1 of 3 cancer treatment centres between April 2011 and 30 April 2013. Patient data from 2011 and 2012 were collected retrospectively using chart records and existing registry data. Starting January 2013, data were collected prospectively. Variables investigated included age, sex, initial stage, histology, mutation type, time to recurrence, sites of metastases, resectability, and previous therapies. RESULTS: A cohort of 810 patients with melanoma was identified from the cmrn registry. Mean age was 58.7 years, and most patients were men (60% vs. 40%). Factors affecting survival included unresectable or metastatic melanoma, initial stage at diagnosis, presence of brain metastasis, and BRAF mutation status. The proportion of surviving patients decreased with higher initial disease stages. CONCLUSIONS: Using registry data, we were able to determine the detailed epidemiology of patients with melanoma in the Canadian province of Ontario, validating the comprehensive and detailed information that can be obtained from registry data.

Effect of pantoprazole to enhance activity of docetaxel against human tumour xenografts by inhibiting autophagy.

BACKGROUND: Autophagy allows recycling of cellular components and may facilitate cell survival after chemotherapy. Pantoprazole inhibits proton pumps and is reported to inhibit autophagy. Here we evaluate the effects of pantoprazole to modify cytotoxicity of the anticancer drug docetaxel, and underlying mechanisms. METHODS: Effects of docetaxel±pantoprazole were studied against wild-type and autophagy-deficient PC3 cells and against four human xenografts. Effects of pantoprazole on autophagy were evaluated by quantifying LC3-I, LC3-II and p62 proteins in western blots, and by fluorescent microscopy of cells transfected with RFP-GFP-LC3. The distribution of drug effects and of autophagy was quantified in tumour sections in relation to blood vessels and hypoxia by immunohistochemistry using γH2AX, cleaved caspase-3, Ki67 and LC3/ p62. RESULTS: Pantoprazole increased the toxicity of docetaxel in vitro, increased docetaxel-induced expression of γH2AX and cleaved caspase-3, and decreased Ki67 in tumour sections. Pantoprazole increased growth delay of four human xenografts of low, moderate and high sensitivity to docetaxel, with minimal increase in toxicity. Docetaxel led to increased autophagy throughout tumour sections. Pantoprazole inhibited autophagy, and effects of pantoprazole were reduced against genetically modified cells with decreased ability to undergo autophagy. CONCLUSIONS: Autophagy is a mechanism of resistance to docetaxel chemotherapy that may be modified by pantoprazole to improve therapeutic index.

Treatment of mCRPC in the AR-axis-targeted therapy-resistant state.

BACKGROUND: The increased use of the androgen receptor axis-targeted (ARAT) agents abiraterone and enzalutamide in first- and second-line treatment of metastatic castration-resistant prostate cancer (mCRPC) has improved patient outcomes, but resistance to these agents is inevitable. Early identification of patients with primary or secondary resistance to ARAT therapy is of increasing clinical concern. DESIGN: PubMed and conference proceedings were searched for studies of agents used after progression on abiraterone or enzalutamide. The key search terms (or aliases) used a combination of mCRPC and abiraterone or enzalutamide, and results were limited to clinical trials and comparative or validation studies. RESULTS AND CONCLUSION: This systematic review assembles current evidence and provides an approach to treatment using available clinical factors. Issues of patient selection, use of laboratory and clinical biomarkers to identify patients at risk of poor outcomes, and the timing and sequencing of available treatment options are addressed. Our findings reveal a lack of high-level evidence regarding predictive factors and treatment of patients with resistance to ARAT therapy, and a need for further research in this area. In the meantime, we suggest practical strategies to guide management of ARAT treatment-resistant patients based on available data.

Pressure distribution of intraoperative chest pad designs in patients with adolescent idiopathic scoliosis.

STUDY DESIGN: A prospective, comparative study. OBJECTIVE: To evaluate the resultant force and pressure distribution between chest pad designs for scoliosis patients while in the prone position. SUMMARY OF BACKGROUND DATA: Scoliosis affects the anatomy of the lungs and the chest wall, which can adversely affect pulmonary function. Scoliosis surgery requires that patients remain prone for several hours with their body weight supported by pads under the chest and pelvis. As a significant portion of the patient's weight is on the chest, this extrinsic pressure may further affect the pulmonary status of already compromised lungs. METHODS: Fourteen female subjects with right main thoracic adolescent idiopathic scoliosis of at least 45 degrees were evaluated. A Jackson Spinal Surgery and Imaging Table (Orthopaedic Systems Inc.) was used with commercially available (Vista Medical) pressure transducer mats that were overlaid on the chest and hip supports. Awake subjects were positioned on the table during 2 testing conditions: 1 chest pad versus 2 chest pads on the table. Over a 60-second testing period for each condition, the average and maximum pressures and resultant force were found for each pad. RESULTS: The 1 and 2 pad systems had average chest pressures of 4.51±1.07 versus 3.10±0.64 kPa (P<0.05), and maximum chest pressures of 12.9±3.1 versus 9.44±3.14 kPa (P<0.05). The 1 and 2 pad systems had average pelvic pressures of 2.67±0.57 versus 2.98±0.56 kPa (P<0.05), and maximum pelvic pressures of 15.1±7.8 versus 19.4±0.8 kPa (P<0.05). CONCLUSIONS: The 2 pad chest support system resulted in lower maximum and average pressures at the chest and higher maximum and average pressures at the pelvis as compared with the 1 pad design.

Clinical variables associated with PSA response to abiraterone acetate in patients with metastatic castration-resistant prostate cancer.

BACKGROUND: Abiraterone acetate (abiraterone) prolongs overall survival (OS) in patients with metastatic castration-resistant prostate cancer (mCRPC). This study's objective was to retrospectively identify factors associated with prostate-specific antigen (PSA) response to abiraterone and validate them in an independent cohort. We hypothesized that the neutrophil/lymphocyte ratio (NLR), thought to be an indirect manifestation of tumor-promoting inflammation, may be associated with response to abiraterone. PATIENTS AND METHODS: All patients receiving abiraterone at the Princess Margaret (PM) Cancer Centre up to March 2013 were reviewed. The primary end point was confirmed PSA response defined as PSA decline ≥50% below baseline maintained for ≥3 weeks. Potential factors associated with PSA response were analyzed using univariate and multivariable analyses to generate a score, which was then evaluated in an independent cohort from Royal Marsden (RM) NHS foundation. RESULTS: A confirmed PSA response was observed in 44 out of 108 assessable patients (41%, 95% confidence interval 31%-50%). In univariate analysis, lower pre-abiraterone baseline levels of lactate dehydrogenase, an NLR ≤ 5 and restricted metastatic spread to either bone or lymph nodes were each associated with PSA response. In multivariable analysis, only low NLR and restricted metastatic spread remained statistically significant. A score derived as the sum of these two categorical variables was associated with response to abiraterone (P = 0.007). Logistic regression analysis on an independent validation cohort of 245 patients verified that this score was associated with response to abiraterone (P = 0.003). It was also associated with OS in an exploratory analysis. CONCLUSIONS: A composite score of baseline NLR and extent of metastatic spread is associated with PSA response to abiraterone and OS. Our data may help understand the role of systemic inflammation in mCRPC and warrant further research.

Model validation and selection in metabolic flux analysis and flux balance analysis.

13C-Metabolic Flux Analysis (13C-MFA) and Flux Balance Analysis (FBA) are widely used to investigate the operation of biochemical networks in both biological and biotechnological research. Both methods use metabolic reaction network models of metabolism operating at steady state so that reaction rates (fluxes) and the levels of metabolic intermediates are constrained to be invariant. They provide estimated (MFA) or predicted (FBA) values of the fluxes through the network in vivo, which cannot be measured directly. These fluxes can shed light on basic biology and have been successfully used to inform metabolic engineering strategies. Several approaches have been taken to test the reliability of estimates and predictions from constraint-based methods and to compare alternative model architectures. Despite advances in other areas of the statistical evaluation of metabolic models, such as the quantification of flux estimate uncertainty, validation and model selection methods have been underappreciated and underexplored. We review the history and state-of-the-art in constraint-based metabolic model validation and model selection. Applications and limitations of the χ2 -test of goodness-of-fit, the most widely used quantitative validation and selection approach in 13C-MFA, are discussed, and complementary and alternative forms of validation and selection are proposed. A combined model validation and selection framework for 13C-MFA incorporating metabolite pool size information that leverages new developments in the field is presented and advocated for. Finally, we discuss how adopting robust validation and selection procedures can enhance confidence in constraint-based modeling as a whole and ultimately facilitate more widespread use of FBA in biotechnology.

Biophysical carbon concentrating mechanisms in land plants: insights from reaction-diffusion modeling.

Carbon Concentrating Mechanisms (CCMs) have evolved numerous times in photosynthetic organisms. They elevate the concentration of CO2 around the carbon-fixing enzyme rubisco, thereby increasing CO2 assimilatory flux and reducing photorespiration. Biophysical CCMs, like the pyrenoid-based CCM of Chlamydomonas reinhardtii or carboxysome systems of cyanobacteria, are common in aquatic photosynthetic microbes, but in land plants appear only among the hornworts. To predict the likely efficiency of biophysical CCMs in C3 plants, we used spatially resolved reaction-diffusion models to predict rubisco saturation and light use efficiency. We find that the energy efficiency of adding individual CCM components to a C3 land plant is highly dependent on the permeability of lipid membranes to CO2, with values in the range reported in the literature that are higher than used in previous modeling studies resulting in low light use efficiency. Adding a complete pyrenoid-based CCM into the leaf cells of a C3 land plant is predicted to boost net CO2 fixation, but at higher energetic costs than those incurred by photorespiratory losses without a CCM. Two notable exceptions are when substomatal CO2 levels are as low as those found in land plants that already employ biochemical CCMs and when gas exchange is limited such as with hornworts, making the use of a biophysical CCM necessary to achieve net positive CO2 fixation under atmospheric CO2 levels. This provides an explanation for the uniqueness of hornworts' CCM among land plants and evolution of pyrenoids multiple times.