The bone ecosystem facilitates multiple myeloma relapse and the evolution of heterogeneous drug resistant disease.

Multiple myeloma (MM) is an osteolytic malignancy that is incurable due to the emergence of treatment resistant disease. Defining how, when and where myeloma cell intrinsic and extrinsic bone microenvironmental mechanisms cause relapse is challenging with current biological approaches. Here, we report a biology-driven spatiotemporal hybrid agent-based model of the MM-bone microenvironment. Results indicate MM intrinsic mechanisms drive the evolution of treatment resistant disease but that the protective effects of bone microenvironment mediated drug resistance (EMDR) significantly enhances the probability and heterogeneity of resistant clones arising under treatment. Further, the model predicts that targeting of EMDR deepens therapy response by eliminating sensitive clones proximal to stroma and bone, a finding supported by in vivo studies. Altogether, our model allows for the study of MM clonal evolution over time in the bone microenvironment and will be beneficial for optimizing treatment efficacy so as to significantly delay disease relapse.

Metabolomics by NMR Combined with Machine Learning to Predict Neoadjuvant Chemotherapy Response for Breast Cancer.

Neoadjuvant chemotherapy (NACT) is offered to patients with operable or inoperable breast cancer (BC) to downstage the disease. Clinical responses to NACT may vary depending on a few known clinical and biological features, but the diversity of responses to NACT is not fully understood. In this study, 80 women had their metabolite profiles of pre-treatment sera analyzed for potential NACT response biomarker candidates in combination with immunohistochemical parameters using Nuclear Magnetic Resonance (NMR). Sixty-four percent of the patients were resistant to chemotherapy. NMR, hormonal receptors (HR), human epidermal growth factor receptor 2 (HER2), and the nuclear protein Ki67 were combined through machine learning (ML) to predict the response to NACT. Metabolites such as leucine, formate, valine, and proline, along with hormone receptor status, were discriminants of response to NACT. The glyoxylate and dicarboxylate metabolism was found to be involved in the resistance to NACT. We obtained an accuracy in excess of 80% for the prediction of response to NACT combining metabolomic and tumor profile data. Our results suggest that NMR data can substantially enhance the prediction of response to NACT when used in combination with already known response prediction factors.

CancerCellTracker: a brightfield time-lapse microscopy framework for cancer drug sensitivity estimation.

MOTIVATION: Time-lapse microscopy is a powerful technique that relies on images of live cells cultured ex vivo that are captured at regular intervals of time to describe and quantify their behavior under certain experimental conditions. This imaging method has great potential in advancing the field of precision oncology by quantifying the response of cancer cells to various therapies and identifying the most efficacious treatment for a given patient. Digital image processing algorithms developed so far require high-resolution images involving very few cells originating from homogeneous cell line populations. We propose a novel framework that tracks cancer cells to capture their behavior and quantify cell viability to inform clinical decisions in a high-throughput manner. RESULTS: The brightfield microscopy images a large number of patient-derived cells in an ex vivo reconstruction of the tumor microenvironment treated with 31 drugs for up to 6 days. We developed a robust and user-friendly pipeline CancerCellTracker that detects cells in co-culture, tracks these cells across time and identifies cell death events using changes in cell attributes. We validated our computational pipeline by comparing the timing of cell death estimates by CancerCellTracker from brightfield images and a fluorescent channel featuring ethidium homodimer. We benchmarked our results using a state-of-the-art algorithm implemented in ImageJ and previously published in the literature. We highlighted CancerCellTracker's efficiency in estimating the percentage of live cells in the presence of bone marrow stromal cells. AVAILABILITY AND IMPLEMENTATION: https://github.com/compbiolabucf/CancerCellTracker. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

IAP and HDAC inhibitors interact synergistically in myeloma cells through noncanonical NF-κB- and caspase-8-dependent mechanisms.

Interactions between the inhibitor of apoptosis protein antagonist LCL161 and the histone deacetylase inhibitor panobinostat (LBH589) were examined in human multiple myeloma (MM) cells. LCL161 and panobinostat interacted synergistically to induce apoptosis in diverse MM cell lines, including those resistant to bortezomib (PS-R). Similar interactions were observed with other histone deacetylase inhibitors (MS-275) or inhibitors of apoptosis protein antagonists (birinapant). These events were associated with downregulation of the noncanonical (but not the canonical) NF-κB pathway and activation of the extrinsic, caspase-8-related apoptotic cascade. Coexposure of MM cells to LCL161/LBH589 induced TRAF3 upregulation and led to TRAF2 and NIK downregulation, diminished expression of BCL-XL, and induction of γH2A.X. Ectopic expression of TRAF2, NIK, or BCL-XL, or short hairpin RNA TRAF3 knock-down, significantly reduced LCL161/LBH589 lethality, as did ectopic expression of dominant-negative FADD. Stromal/microenvironmental factors failed to diminish LCL161/LBH589-induced cell death. The LCL161/LBH589 regimen significantly increased cell killing in primary CD138+ cells (N = 31) and was particularly effective in diminishing the primitive progenitor cell-enriched CD138-/19+/20+/27+ population (N = 23) but was nontoxic to normal CD34+ cells. Finally, combined LCL161/LBH589 treatment significantly increased survival compared with single-agent treatment in an immunocompetent 5TGM1 murine MM model. Together, these findings argue that LCL161 interacts synergistically with LBH589 in MM cells through a process involving inactivation of the noncanonical NF-κB pathway and activation of the extrinsic apoptotic pathway, upregulation of TRAF3, and downregulation of TRAF2/BCL-XL. Notably, this regimen overcomes various forms of resistance, is active against primary MM cells, and displays significant in vivo activity. This strategy warrants further consideration in MM.

A pharmacodynamic model of clinical synergy in multiple myeloma.

BACKGROUND: Multiagent therapies, due to their ability to delay or overcome resistance, are a hallmark of treatment in multiple myeloma (MM). The growing number of therapeutic options in MM requires high-throughput combination screening tools to better allocate treatment, and facilitate personalized therapy. METHODS: A second-order drug response model was employed to fit patient-specific ex vivo responses of 203 MM patients to single-agent models. A novel pharmacodynamic model, developed to account for two-way combination effects, was tested with 130 two-drug combinations. We have demonstrated that this model is sufficiently parameterized by single-agent and fixed-ratio combination responses, by validating model estimates with ex vivo combination responses for different concentration ratios, using a checkerboard assay. This new model reconciles ex vivo observations from both Loewe and BLISS synergy models, by accounting for the dimension of time, as opposed to focusing on arbitrary time-points or drug effect. Clinical outcomes of patients were simulated by coupling patient-specific drug combination models with pharmacokinetic data. FINDINGS: Combination screening showed 1 in 5 combinations (21.43% by LD50, 18.42% by AUC) were synergistic ex vivo with statistical significance (P < 0.05), but clinical synergy was predicted for only 1 in 10 combinations (8.69%), which was attributed to the role of pharmacokinetics and dosing schedules. INTERPRETATION: The proposed framework can inform clinical decisions from ex vivo observations, thus providing a path toward personalized therapy using combination regimens. FUNDING: This research was funded by the H. Lee Moffitt Cancer Center Physical Sciences in Oncology (PSOC) Grant (1U54CA193489-01A1) and by H. Lee Moffitt Cancer Center's Team Science Grant. This work has been supported in part by the PSOC Pilot Project Award (5U54CA193489-04), the Translational Research Core Facility at the H. Lee Moffitt Cancer Center & Research Institute, an NCI-designated Comprehensive Cancer Center (P30-CA076292), the Pentecost Family Foundation, and Miles for Moffitt Foundation.

Early metabolic response after resistance exercise with blood flow restriction in well-trained men: a metabolomics approach.

The present study aimed to compare the early metabolic response between high-load resistance exercise (HL-RE) and low-load resistance exercise with blood flow restriction (LL-BFR). Nine young, well-trained men participated in a randomized crossover design in which each subject completed LL-BFR, HL-RE, or condition control (no exercise) with a 1-week interval between them. Blood samples were taken immediately before and 5 min after the exercise sessions. Nuclear magnetic resonance spectroscopy identified and quantified 48 metabolites, 6 of which presented significant changes among the exercise protocols. The HL-RE promoted a higher increase in pyruvate, lactate, and alanine compared with the LL-BFR and the control. HL-RE and LL-BFR promoted a higher increase in succinate compared with the control; however, there was no difference between HL-RE and LL-BFR. Also, while there was no difference in acetoacetate between HL-RE and LL-BFR, a greater decrease was observed in both compared with the control. Finally, LL-BFR promoted a greater decrease in choline compared with the control. In conclusion, this study provides by metabolomics a new insight in metabolic response between LL-BFR and HL-RE by demonstrating a distinct response to some metabolites that are not commonly analyzed.

Metabolic time-course response after resistance exercise: A metabolomics approach.

This study analysed the time course of the global metabolic acute response after resistance exercise (RE), with the use of proton nuclear magnetic resonance (1H NMR) spectroscopy. Ten young healthy males performed 4 sets of 10 repetitions at 70% of one-repetition maximum in the leg press and knee extension exercises and had the serum metabolome assessed at 5, 15, 30 and 60 min post-RE. Measurements were also performed 1 h earlier and immediately before the exercises, as an attempt to characterise each participant's serum metabolome at rest. One-way ANOVA was applied and the significance level was set at P ≤ 0.05. RE promoted an increase in 2-hydroxybutyrate, 2-oxoisocaproate, 3-hydroxyisobutyrate, alanine, hypoxanthine, lactate, pyruvate and succinate concentrations. However, isoleucine, leucine, lysine, ornithine and valine had their concentrations decreased post-RE compared with at rest. This is the first study to show significant changes in serum concentration of metabolites such as 2-oxoisocaproate, 2-hydroxybutyrate, 3-hydroxyisobutyrate, lysine, hypoxanthine and pyruvate post-RE, attesting metabolomics as an interesting approach to advance in the understanding of global RE-induced metabolic changes. Moreover, the present data could influence the time point of blood collection in the future studies that aims to investigate metabolism and exercise.

Integrative analysis to select cancer candidate biomarkers to targeted validation.

Targeted proteomics has flourished as the method of choice for prospecting for and validating potential candidate biomarkers in many diseases. However, challenges still remain due to the lack of standardized routines that can prioritize a limited number of proteins to be further validated in human samples. To help researchers identify candidate biomarkers that best characterize their samples under study, a well-designed integrative analysis pipeline, comprising MS-based discovery, feature selection methods, clustering techniques, bioinformatic analyses and targeted approaches was performed using discovery-based proteomic data from the secretomes of three classes of human cell lines (carcinoma, melanoma and non-cancerous). Three feature selection algorithms, namely, Beta-binomial, Nearest Shrunken Centroids (NSC), and Support Vector Machine-Recursive Features Elimination (SVM-RFE), indicated a panel of 137 candidate biomarkers for carcinoma and 271 for melanoma, which were differentially abundant between the tumor classes. We further tested the strength of the pipeline in selecting candidate biomarkers by immunoblotting, human tissue microarrays, label-free targeted MS and functional experiments. In conclusion, the proposed integrative analysis was able to pre-qualify and prioritize candidate biomarkers from discovery-based proteomics to targeted MS.

N-(1'-naphthyl)-3,4,5-trimethoxybenzohydrazide as microtubule destabilizer: Synthesis, cytotoxicity, inhibition of cell migration and in vivo activity against acute lymphoblastic leukemia.

Tubulin-interacting agents, like vinca alkaloid and taxanes, play a fundamental role in cancer chemotherapy, making cellular microtubules (MT), one of the few validated anticancer targets. Cancer resistance to classical MT inhibitors has motivated the development of novel molecules with increased efficacy and lower toxicity. Aiming at designing structurally-simple inhibitors of MT assembly, we synthesized a series of thirty-one 3,4,5-trimethoxy-hydrazones and twenty-five derivatives or analogs. Docking simulations suggested that a representative N-acylhydrazone could adopt an appropriate stereochemistry inside the colchicine-binding domain of tubulin. Several of these compounds showed anti-leukemia effects in the nanomolar concentration range. Interference with MT polymerization was validated by the compounds' ability to inhibit MT assembly at the biochemical and cellular level. Selective toxicity investigations done with the most potent compound, a 3,4,5-trimethoxy-hydrazone with a 1-naphthyl group, showed remarkably selective toxicity against leukemia cells in comparison with stimulated normal lymphocytes, and no acute toxicity in vivo. Finally, this molecule was as active as vincristine in a murine model of human acute lymphoblastic leukemia at a weekly dose of 1 mg/kg.

Xanthan Gum Removal for 1H-NMR Analysis of the Intracellular Metabolome of the Bacteria Xanthomonas axonopodis pv. citri 306.

Xanthomonas is a genus of phytopathogenic bacteria, which produces a slimy, polysaccharide matrix known as xanthan gum, which involves, protects and helps the bacteria during host colonization. Although broadly used as a stabilizer and thickener in the cosmetic and food industries, xanthan gum can be a troubling artifact in molecular investigations due to its rheological properties. In particular, a cross-reaction between reference compounds and the xanthan gum could compromise metabolic quantification by NMR spectroscopy. Aiming at an efficient gum extraction protocol, for a 1H-NMR-based metabolic profiling study of Xanthomonas, we tested four different interventions on the broadly used methanol-chloroform extraction protocol for the intracellular metabolic contents observation. Lower limits for bacterial pellet volumes for extraction were also probed, and a strategy is illustrated with an initial analysis of X. citri's metabolism by 1H-NMR spectroscopy.

Cytotoxic 3,4,5-trimethoxychalcones as mitotic arresters and cell migration inhibitors.

Based on classical colchicine site ligands and a computational model of the colchicine binding site on beta tubulin, two classes of chalcone derivatives were designed, synthesized and evaluated for inhibition of tubulin assembly and toxicity in human cancer cell lines. Docking studies suggested that the chalcone scaffold could fit the colchicine site on tubulin in an orientation similar to that of the natural product. In particular, a 3,4,5-trimethoxyphenyl ring adjacent to the carbonyl group appeared to benefit the ligand-tubulin interaction, occupying the same subcavity as the corresponding moiety in colchicine. Consistent with modeling predictions, several 3,4,5-trimethoxychalcones showed improved cytotoxicity to murine acute lymphoblastic leukemia cells compared with a previously described parent compound, and inhibited tubulin assembly in vitro as potently as colchicine. The most potent chalcones inhibited the growth of human leukemia cell lines at nanomolar concentrations, caused microtubule destabilization and mitotic arrest in human cervical cancer cells, and inhibited human breast cancer cell migration in scratch wound and Boyden chamber assays.