The diversity and breadth of cancer cell fatty acid metabolism

Tumor cellular metabolism exhibits distinguishing features that collectively enhance biomass synthesis while maintaining redox balance and cellular homeostasis. These attributes reflect the complex interactions between cell-intrinsic factors such as genomic-transcriptomic regulation and cell-extrinsic influences, including growth factor and nutrient availability. Alongside glucose and amino acid metabolism, fatty acid metabolism supports tumorigenesis and disease progression through a range of processes including membrane biosynthesis, energy storage and production, and generation of signaling intermediates. Here, we highlight the complexity of cellular fatty acid metabolism in cancer, the various inputs and outputs of the intracellular free fatty acid pool, and the numerous ways that these pathways influence disease behavior.Shilpa R. Nagarajan, Lisa M. Butler, and Andrew J. Ho

Cancer-associated fibroblasts—heroes or villains?

Cancer-associated fibroblasts (CAFs) were originally presumed to represent a homogeneous population uniformly driving tumorigenesis, united by their morphology and peritumoural location. Our understanding of CAFs has since been shaped by sophisticated in vitro and in vivo experiments, pathological association and, more recently, ablation, and it is now widely appreciated that CAFs form a group of highly heterogeneous cells with no single overarching marker. Studies have demonstrated that the CAF population contains different subtypes based on the expression of marker proteins with the capacity to promote or inhibit cancer, with their biological role as accomplices or adversaries dependent on many factors, including the cancer stage. So, while CAFs have been endlessly shown to promote the growth, survival and spread of tumours via improvements in functionality and an altered secretome, they are also capable of retarding tumorigenesis via largely unknown mechanisms. It is important to reconcile these disparate results so that the functions of, or factors produced by, tumour-promoting subtypes can be specifically targeted to improve cancer patient outcomes. This review will dissect out CAF complexity and CAF-directed cancer treatment strategies in order to provide a case for future, rational therapies.Krystyna A. Gieniec, Lisa M. Butler, Daniel L. Worthley and Susan L. Wood

An Up-to-date Assessment of US Prostate Cancer Incidence Rates by Stage and Race: A Novel Approach Combining Multiple Imputation with Age and Delay Adjustment

Background: In the USA, it is unknown whether metastatic prostate cancer incidence has continued to increase and whether racial differences have persisted. Objective: Combining multiple imputation with age and delay adjustment, we provide an up-to-date, comprehensive assessment of US prostate cancer incidence trends by stage and race. Design, setting, and participants: From Surveillance Epidemiology and End Results (SEER)-18, 774 240 prostate cancer cases were diagnosed during 2004–2017. Outcome measurements and statistical analysis: Multiple imputation assigned prostate cancer stage to the 4.7% of cases with missing stage, which varied by year and race-ethnicity. SEER delay factors adjusted case counts to anticipated future data corrections. Twenty datasets were imputed, and Rubin's rules were used for summary estimation. Overall and stage-specific rates were estimated and stratified by race and age group. Joinpoint software identified significant temporal changes and estimated annual percentage changes. We compared these estimates without multiple imputation and delay adjustment. Results and limitations: Metastatic prostate cancer incidence increased during 2011–2017, with an annual percentage change of 5.5. This was followed by increases in localized and regional disease since 2014. Non-Hispanic black men continued to have the highest incidence, especially for metastatic disease. The increasing rate of metastatic prostate cancer in non-Hispanic white men aged 50–74 yr accelerated recently, and the incidence was 56% higher in 2017 than in 2004. Rates without multiple imputation and delay adjustment were quantitatively and qualitatively different. This observational study is unable to assign causes to observed changes in prostate cancer incidence. Conclusions: Multiple imputation and delay adjustment are essential for portraying accurately stage- and race-specific prostate cancer incidence as clinical practice evolves. Patient summary: In the USA, diagnosis of prostate cancer that has spread to distant sites (metastatic disease) continues to increase. Black men continue to have higher risks of being diagnosed with metastatic prostate cancer than other race-ethnicities. In the USA, metastatic prostate cancer incidence rates have continued to increase through 2017, and local and regional disease rates have also increased since 2014. Racial differences persist, with non-Hispanic Black men being at the highest risk

Lipogenic effects of androgen signaling in normal and malignant prostate

Prostate cancer is an androgen-dependent cancer with unique metabolic features compared to many other solid tumors, and typically does not exhibit the “Warburg effect”. During malignant transformation, an early metabolic switch diverts the dependence of normal prostate cells on aerobic glycolysis for the synthesis of and secretion of citrate towards a more energetically favorable metabolic phenotype, whereby citrate is actively oxidised for energy and biosynthetic processes (i.e. de novo lipogenesis). It is now clear that lipid metabolism is one of the key androgen-regulated processes in prostate cells and alterations in lipid metabolism are a hallmark of prostate cancer, whereby increased de novo lipogenesis accompanied by over expression of lipid metabolic genes are characteristic of primary and advanced disease. Despite recent advances in our understanding of altered lipid metabolism in prostate tumorigenesis and cancer progression, the intermediary metabolism of the normal prostate and its relationship to androgen signaling remains poorly understood. In this review, we discuss the fundamental metabolic relationships that are distinctive in normal versus malignant prostate tissues, and the role of androgens in the regulation of lipid metabolism at different stages of prostate tumorigenesis.Chui YanMah, Zeyad D.Nassar, Johannes V.Swinnen, Lisa M.Butle

The role of RHAMM in cancer: Exposing novel therapeutic vulnerabilities

PUBLISHED 10 August 2022Receptor for hyaluronic acid-mediated motility (RHAMM) is a cell surface receptor for hyaluronic acid that is critical for cell migration and a cell cycle protein involved in microtubule assembly and stability. These functions of RHAMM are required for cellular stress responses and cell cycle progression but are also exploited by tumor cells for malignant progression and metastasis. RHAMM is often overexpressed in tumors and is an independent adverse prognostic factor for a number of cancers such as breast and prostate. Interestingly, pharmacological or genetic inhibition of RHAMM in vitro and in vivo ablates tumor invasiveness and metastatic spread, implicating RHAMM as a potential therapeutic target to restrict tumor growth and improve patient survival. However, RHAMM's pro-tumor activity is dependent on its subcellular distribution, which complicates the design of RHAMM-directed therapies. An alternative approach is to identify downstream signaling pathways that mediate RHAMM-promoted tumor aggressiveness. Herein, we discuss the pro-tumoral roles of RHAMM and elucidate the corresponding regulators and signaling pathways mediating RHAMM downstream events, with a specific focus on strategies to target the RHAMM signaling network in cancer cells.Josephine A. Hinneh, Joanna L. Gillis, Nicole L. Moore, Lisa M. Butler and Margaret M. Centener

Aspects of Nucleon Compton Scattering

We consider the spin-averaged nucleon forward Compton scattering amplitude in heavy baryon chiral perturbation theory including all terms to order ${\cal O} (q^4)$. The chiral prediction for the spin-averaged forward Compton scattering amplitude is in good agreement with the data for photon energies $\omega \le 110$ MeV. We also evaluate the nucleon electric and magnetic Compton polarizabilities to this order and discuss the uncertainties of the various counter terms entering the chiral expansion of these quantities.Comment: 17 pp, TeX, 7 figures available from the authors, preprint CRN-93/5

Spectral hardness evolution characteristics of tracking Gamma-ray Burst pulses

Employing a sample presented by Kaneko et al. (2006) and Kocevski et al. (2003), we select 42 individual tracking pulses (here we defined tracking as the cases in which the hardness follows the same pattern as the flux or count rate time profile) within 36 Gamma-ray Bursts (GRBs) containing 527 time-resolved spectra and investigate the spectral hardness, $E_{peak}$ (where $E_{peak}$ is the maximum of the $\nu F_{\nu}$ spectrum), evolutionary characteristics. The evolution of these pulses follow soft-to-hard-to-soft (the phase of soft-to-hard and hard-to-soft are denoted by rise phase and decay phase, respectively) with time. It is found that the overall characteristics of $E_{peak}$ of our selected sample are: 1) the $E_{peak}$ evolution in the rise phase always start on the high state (the values of $E_{peak}$ are always higher than 50 keV); 2) the spectra of rise phase clearly start at higher energy (the median of $E_{peak}$ are about 300 keV), whereas the spectra of decay phase end at much lower energy (the median of $E_{peak}$ are about 200 keV); 3) the spectra of rise phase are harder than that of the decay phase and the duration of rise phase are much shorter than that of decay phase as well. In other words, for a complete pulse the initial $E_{peak}$ is higher than the final $E_{peak}$ and the duration of initial phase (rise phase) are much shorter than the final phase (decay phase). This results are in good agreement with the predictions of Lu et al. (2007) and current popular view on the production of GRBs. We argue that the spectral evolution of tracking pulses may be relate to both of kinematic and dynamic process even if we currently can not provide further evidences to distinguish which one is dominant. Moreover, our statistical results give some witnesses to constrain the current GRB model.Comment: 32 pages, 26 figures, 3 tables, accepted for publication in New Astronom

Harnessing the Heterogeneity of Prostate Cancer for Target Discovery Using Patient-Derived Explants

Prostate cancer is a complex and heterogeneous disease, but a small number of cell lines have dominated basic prostate cancer research, representing a major obstacle in the field of drug and biomarker discovery. A growing lack of confidence in cell lines has seen a shift toward more sophisticated pre-clinical cancer models that incorporate patient-derived tumors as xenografts or explants, to more accurately reflect clinical disease. Not only do these models retain critical features of the original tumor, and account for the molecular diversity and cellular heterogeneity of prostate cancer, but they provide a unique opportunity to conduct research in matched tumor samples. The challenge that accompanies these complex tissue models is increased complexity of analysis. With over 10 years of experience working with patient-derived explants (PDEs) of prostate cancer, this study provides guidance on the PDE method, its limitations, and considerations for addressing the heterogeneity of prostate cancer PDEs that are based on statistical modeling. Using inhibitors of the molecular chaperone heat shock protein 90 (Hsp90) as an example of a drug that induces robust proliferative response, we demonstrate how multi-omics analysis in prostate cancer PDEs is both feasible and essential for identification of key biological pathways, with significant potential for novel drug target and biomarker discovery.Margaret M. Centenera, Andrew D. Vincent, Max Moldovan, Hui-Ming Lin, David J. Lynn, Lisa G. Horvath, and Lisa M. Butle

A Boolean-based machine learning framework identifies predictive biomarkers of HSP90-targeted therapy response in prostate cancer

Precision medicine has emerged as an important paradigm in oncology, driven by the significant heterogeneity of individual patients' tumour. A key prerequisite for effective implementation of precision oncology is the development of companion biomarkers that can predict response to anti-cancer therapies and guide patient selection for clinical trials and/or treatment. However, reliable predictive biomarkers are currently lacking for many anti-cancer therapies, hampering their clinical application. Here, we developed a novel machine learning-based framework to derive predictive multi-gene biomarker panels and associated expression signatures that accurately predict cancer drug sensitivity. We demonstrated the power of the approach by applying it to identify response biomarker panels for an Hsp90-based therapy in prostate cancer, using proteomic data profiled from prostate cancer patient-derived explants. Our approach employs a rational feature section strategy to maximise model performance, and innovatively utilizes Boolean algebra methods to derive specific expression signatures of the marker proteins. Given suitable data for model training, the approach is also applicable to other cancer drug agents in different tumour settings.Sung-Young Shin, Margaret M. Centenera, Joshua T. Hodgson, Elizabeth V. Nguyen, Lisa M. Butler, Roger J. Daly and Lan K. Nguye

Effects of sea temperature and stratification changes on seabird breeding success

As apex predators in marine ecosystems, seabirds may primarily experience climate change impacts indirectly, via changes to their food webs. Observed seabird population declines have been linked to climate-driven oceanographic and food web changes. However, relationships have often been derived from relatively few colonies and consider only sea surface temperature (SST), so important drivers, and spatial variation in drivers, could remain undetected. Further, explicit climate change projections have rarely been made, so longer-term risks remain unclear. Here, we use tracking data to estimate foraging areas for eleven black-legged kittiwake (Rissa tridactyla) colonies in the UK and Ireland, thus reducing reliance on single colonies and allowing calculation of colony-specific oceanographic conditions. We use mixed models to consider how SST, the potential energy anomaly (indicating density stratification strength) and the timing of seasonal stratification influence kittiwake productivity. Across all colonies, higher breeding success was associated with weaker stratification before breeding and lower SSTs during the breeding season. Eight colonies with sufficient data were modelled individually: higher productivity was associated with later stratification at three colonies, weaker stratification at two, and lower SSTs at one, whilst two colonies showed no significant relationships. Hence, key drivers of productivity varied among colonies. Climate change projections, made using fitted models, indicated that breeding success could decline by 21 – 43% between 1961-90 and 2070-99. Climate change therefore poses a longer-term threat to kittiwakes, but as this will be mediated via availability of key prey species, other marine apex predators could also face similar threats