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Archive for the ‘Metabolomics’ Category

The drug efflux pump MDR1 promotes intrinsic and acquired resistance to PROTACs in cancer cells

Reporter: Stephen J. Williams, PhD.
Below is one of the first reports  on the potential mechanisms of intrinsic and acquired resistance to PROTAC therapy in cancer cells.
Proteolysis-targeting chimeras (PROTACs) are a promising new class of drugs that selectively degrade cellular proteins of interest. PROTACs that target oncogene products are avidly being explored for cancer therapies, and several are currently in clinical trials. Drug resistance is a substantial challenge in clinical oncology, and resistance to PROTACs has been reported in several cancer cell models. Here, using proteomic analysis, we found intrinsic and acquired resistance mechanisms to PROTACs in cancer cell lines mediated by greater abundance or production of the drug efflux pump MDR1. PROTAC-resistant cells were resensitized to PROTACs by genetic ablation of ABCB1 (which encodes MDR1) or by coadministration of MDR1 inhibitors. In MDR1-overexpressing colorectal cancer cells, degraders targeting either the kinases MEK1/2 or the oncogenic mutant GTPase KRASG12C synergized with the dual epidermal growth factor receptor (EGFR/ErbB)/MDR1 inhibitor lapatinib. Moreover, compared with single-agent therapies, combining MEK1/2 degraders with lapatinib improved growth inhibition of MDR1-overexpressing KRAS-mutant colorectal cancer xenografts in mice. Together, our findings suggest that concurrent blockade of MDR1 will likely be required with PROTACs to achieve durable protein degradation and therapeutic response in cancer.

INTRODUCTION

Proteolysis-targeting chimeras (PROTACs) have emerged as a revolutionary new class of drugs that use cancer cells’ own protein destruction machinery to selectively degrade essential tumor drivers (1). PROTACs are small molecules with two functional ends, wherein one end binds to the protein of interest, whereas the other binds to an E3 ubiquitin ligase (23), bringing the ubiquitin ligase to the target protein, leading to its ubiquitination and subsequent degradation by the proteasome. PROTACs have enabled the development of drugs against previously “undruggable” targets and require neither catalytic activity nor high-affinity target binding to achieve target degradation (4). In addition, low doses of PROTACs can be highly effective at inducing degradation, which can reduce off-target toxicity associated with high dosing of traditional inhibitors (3). PROTACs have been developed for a variety of cancer targets, including oncogenic kinases (5), epigenetic proteins (6), and, recently, KRASG12C proteins (7). PROTACs targeting the androgen receptor or estrogen receptor are avidly being evaluated in clinical trials for prostate cancer (NCT03888612) or breast cancer (NCT04072952), respectively.
However, PROTACs may not escape the overwhelming challenge of drug resistance that befalls so many cancer therapies (8). Resistance to PROTACs in cultured cells has been shown to involve genomic alterations in their E3 ligase targets, such as decreased expression of Cereblon (CRBN), Von Hippel Lindau (VHL), or Cullin2 (CUL2) (911). Up-regulation of the drug efflux pump encoded by ABCB1—MDR1 (multidrug resistance 1), a member of the superfamily of adenosine 5′-triphosphate (ATP)–binding cassette (ABC) transporters—has been shown to convey drug resistance to many anticancer drugs, including chemotherapy agents, kinase inhibitors, and other targeted agents (12). Recently, PROTACs were shown to be substrates for MDR1 (1013), suggesting that drug efflux represents a potential limitation for degrader therapies. Here, using degraders (PROTACs) against bromodomain and extraterminal (BET) bromodomain (BBD) proteins and cyclin-dependent kinase 9 (CDK9) as a proof of concept, we applied proteomics to define acquired resistance mechanisms to PROTAC therapies in cancer cells after chronic exposure. Our study reveals a role for the drug efflux pump MDR1 in both acquired and intrinsic resistance to protein degraders in cancer cells and supports combination therapies involving PROTACs and MDR1 inhibitors to achieve durable protein degradation and therapeutic responses.

Fig. 1. Proteomic characterization of degrader-resistant cancer cell lines.
(A) Workflow for identifying protein targets up-regulated in degrader-resistant cancer cells. Single-run proteome analysis was performed, and changes in protein levels among parent and resistant cells were determined by LFQ. m/z, mass/charge ratio. (B and C) Cell viability assessed by CellTiter-Glo in parental and dBET6- or Thal SNS 032–resistant A1847 cells treated with increasing doses of dBET6 (B) or Thal SNS 032 (C) for 5 days. Data were analyzed as % of DMSO control, presented as means ± SD of three independent assays. Growth inhibitory 50% (GI50) values were determined using Prism software. (D to G) Immunoblotting for degrader targets and downstream signaling in parental A1847 cells and their derivative dBET6-R or Thal-R cells treated with increasing doses of dBET6 or Thal SNS 032 for 4 hours. The dBET6-R and Thal-R cells were continuously cultured in 500 nM PROTAC. Blots are representative, and densitometric analyses are means ± SD from three blots, each normalized to the loading control, GAPDH. DC50 values, quantitating either (E) the dose of dBET6 that reduces BRD2, BRD3, or BRD4 or (G) the dose of Thal SNS 032 that reduces CDK9 protein levels 50% of the DMSO control treatment, were determined with Prism software. Pol II, polymerase II. (H to K) Volcano plot of proteins with increased or reduced abundance in dBET6-R (H) or Thal-R (I) A1847 cells relative to parental cells. Differences in protein log2 LFQ intensities among degrader-resistant and parental cells were determined by paired t test permutation-based adjusted P values at FDR of <0.05 using Perseus software. The top 10 up-regulated proteins in each are shown in (J) and (K), respectively. FC, fold change. (L and M) ABCB1 log2 LFQ values in dBET6-R cells from (H) and Thal-R cells from (I) compared with those in parental A1847 cells. Data are presented as means ± SD from three independent assays. By paired t test permutation-based adjusted P values at FDR of <0.05 using Perseus software, ***P ≤ 0.001. (N) Cell viability assessed by CellTiter-Glo in parental and MZ1-resistant SUM159 cells treated with increasing doses of MZ1 for 5 days. Data were analyzed as % of DMSO control, presented as means of three independent assays. GI50 values were determined using Prism software. (O and P) Immunoblotting for degrader targets and downstream signaling in parental or MZ1-R SUM159 cells treated with increasing doses of MZ1 for 24 hours. The MZ1-R cells were continuously cultured in 500 nM MZ1. Blots are representative, and densitometric analyses are means ± SD from three blots, each normalized to the loading control, GAPDH. DC50 values were determined in Prism software. (Q and R) Top 10 up-regulated proteins (Q) and ABCB1 log2 LFQ values (R) in MZ1-R cells relative to parental SUM159 cells

Fig. 2. Chronic exposure to degraders induces MDR1 expression and drug efflux activity.
(A) ABCB1 mRNA levels in parental and degrader-resistant cell lines as determined by qRT-PCR. Data are means ± SD of three independent experiments. ***P ≤ 0.001 by Student’s t test. (B) Immunoblot analysis of MDR1 protein levels in parental and degrader-resistant cell lines. Blots are representative of three independent experiments. (C to E) Immunofluorescence (“IF”) microscopy of MDR1 protein levels in A1847 dBET6-R (C), SUM159 MZ1-R (D), and Thal-R A1847 cells (E) relative to parental cells. Nuclear staining by DAPI. Images are representative of three independent experiments. Scale bars, 100 μm. (F) Drug efflux activity in A1847 dBET6-R, SUM159 MZ1-R, and Thal-R A1847 cells relative to parental cells (Par.) using rhodamine 123 efflux assays. Bars are means ± SD of three independent experiments. ***P ≤ 0.001 by Student’s t test. (G) Intracellular dBET6 levels in parental or dBET-R A1847 cells transfected with a CRBN sensor and treated with increasing concentrations of dBET6. Intracellular dBET6 levels measured using the CRBN NanoBRET target engagement assay. Data were analyzed as % of DMSO control, presented as means ± SD of three independent assays. *P ≤ 0.05, **P ≤ 0.01, and ***P ≤ 0.001 by Student’s t test. (H and I) FISH analysis of representative drug-sensitive parental and drug-resistant A1847 (H) and SUM159 (I) cells using ABCB1 and control XCE 7 centromere probes. Images of interphase nuclei were captured with a Metasystems Metafer microscope workstation, and the raw images were extracted and processed to depict ABCB1 signals in magenta, centromere 7 signals in cyan, and DAPI-stained nuclei in blue. (J and K) CpG methylation status of the ABCB1 downstream promoter (coordinates: chr7.87,600,166-87,601,336) by bisulfite amplicon sequencing in parent and degrader-resistant A1847 (J) and SUM159 (K) cells. Images depict the averaged percentage of methylation for each region of the promoter, where methylation status is depicted by color as follows: red, methylated; blue, unmethylated. Schematic of the ABCB1 gene with the location of individual CpG sites is shown. Graphs are representative of three independent experiments. (L and M) Immunoblot analysis of MDR1 protein levels after short-term exposure [for hours (h) or days (d) as indicated] to BET protein degraders dBET6 or MZ1 (100 nM) in A1847 (L) and SUM159 (M) cells, respectively. Blots are representative of three independent experiments. (N to P) Immunoblot analysis of MDR1 protein levels in A1847 and SUM159 cells after long-term exposure (7 to 30 days) to BET protein degraders dBET6 (N), Thal SNS 032 (O), or MZ1 (P), each at 500 nM. Blots are representative of three independent experiments. (Q and R) Immunoblot analysis of MDR1 protein levels in degrader-resistant A1847 (Q) and SUM159 (R) cells after PROTAC removal for 2 or 7 days. Blots are representative of three independent experiments.

 

Fig. 3. Blockade of MDR1 activity resensitizes degrader-resistant cells to PROTACs.
(A and B) Cell viability by CellTiter-Glo assay in parental and degrader-resistant A1847 (A) and SUM159 (B) cells transfected with control siRNA or siRNAs targeting ABCB1 and cultured for 120 hours. Data were analyzed as % of control, presented as means ± SD of three independent assays. ***P ≤ 0.001 by Student’s t test. (C and D) Immunoblot analysis of degrader targets after ABCB1 knockdown in parental and degrader-resistant A1847 (C) and SUM159 (D) cells. Blots are representative, and densitometric analyses using ImageJ are means ± SD of three blots, each normalized to the loading control, GAPDH. (E) Drug efflux activity, using the rhodamine 123 efflux assay, in degrader-resistant cells after MDR1 inhibition by tariquidar (0.1 μM). Data are means ± SD of three independent experiments. ***P ≤ 0.001 by Student’s t test. (F to H) Cell viability by CellTiter-Glo assay in parental and dBET6-R (F) or Thal-R (G) A1847 cells or MZ1-R SUM159 cells (H) treated with increasing concentrations of tariquidar. Data are % of DMSO control, presented as means ± SD of three independent assays. GI50 value determined with Prism software. (I to K) Immunoblot analysis of degrader targets after MDR1 inhibition (tariquidar, 0.1 μM for 24 hours) in parental and degrader-resistant A1847 cells (I and J) and SUM159 cells (K). Blots are representative, and densitometric analyses are means ± SD from three blots, each normalized to the loading control, GAPDH. (L and M) A 14-day colony formation assessed by crystal violet staining of (L) A1847 cells or (M) SUM159 cells treated with degrader (0.1 μM; dBET6 or MZ1, respectively) and MDR1 inhibitor tariquidar (0.1 μM). Images are representative of three biological replicates. (N) Immunoblotting for MDR1 in SUM159 cells stably expressing FLAG-MDR1 after selection with hygromycin. (O) Long-term 14-day colony formation assay of SUM159 cells expressing FLAG-MDR1 that were treated with DMSO, MZ1 (0.1 μM), or MZ1 and tariquidar (0.1 μM) for 14 days, assessed by crystal violet staining. Representative images of three biological replicates are shown. (P and Q) RT-PCR (P) and immunoblot (Q) analysis of ABCB1 mRNA and MDR1 protein levels, respectively, in parental or MZ1-R HCT116, OVCAR3, and MOLT4 cells.

 

Fig. 4. Overexpression of MDR1 conveys intrinsic resistance to degrader therapies in cancer cells.
(A) Frequency of ABCB1 mRNA overexpression in a panel of cancer cell lines, obtained from cBioPortal for Cancer Genomics using Z-score values of >1.2 for ABCB1 mRNA levels (30). (B) Immunoblot for MDR1 protein levels in a panel of 10 cancer cell lines. Blots are representative of three independent experiments. (C) Cell viability by CellTiter-Glo assay in cancer cell lines expressing high or low MDR1 protein levels and treated with Thal SNS 032 for 5 days. Data were analyzed as % of DMSO control, presented as means ± SD of three independent assays. GI50 values were determined with Prism software. (D to F) Immunoblot analysis of CDK9 in MDR1-low (D) or MDR1-high (E) cell lines after Thal SNS 032 treatment for 4 hours. Blots are representative, and densitometric analyses using ImageJ are means ± SD from three blots, each normalized to the loading control, GAPDH. DC50 value determined with Prism. (G and H) Immunoblotting of control and MDR1-knockdown DLD-1 cells treated for 4 hours with increasing concentrations of Thal SNS 032 [indicated in (H)]. Blots are representative, and densitometric analysis data are means ± SD from three blots, each normalized to the loading control, GAPDH. DC50 value determined with Prism. (I) Drug efflux activity using rhodamine 123 efflux assays in DLD-1 cells treated with DMSO or 0.1 μM tariquidar. Data are means ± SD of three independent experiments. ***P ≤ 0.001 by Student’s t test. (J) Intracellular Thal SNS 032 levels, using the CRBN NanoBRET target engagement assay, in MDR1-overexpressing DLD-1 cells treated with DMSO or 0.1 μM tariquidar and increasing doses of Thal SNS 032. Data are % of DMSO control, presented as means ± SD of three independent assays. **P ≤ 0.01 and ***P ≤ 0.001 by Student’s t test. (K to N) Immunoblotting in DLD-1 cells treated with increasing doses of Thal SNS 032 (K and L) or dBET6 (M and N) alone or with tariquidar (0.1 μM) for 4 hours. Blots are representative, and densitometric analyses are means ± SD from three blots, each normalized to the loading control, GAPDH. DC50 value of Thal SNS 032 for CDK9 reduction (L) or of dBET6 for BRD4 reduction (N) determined with Prism. (O to T) Bliss synergy scores based on cell viability by CellTiter-Glo assay, colony formation, and immunoblotting in DLD-1 cells treated with the indicated doses of Thal SNS 032 (O to Q) or dBET6 (R to T) alone or with tariquidar. Cells were treated for 14 days for colony formation assays and 24 hours for immunoblotting.

 

Fig. 5. Repurposing dual kinase/MDR1 inhibitors to overcome degrader resistance in cancer cells.
(A and B) Drug efflux activity by rhodamine 123 efflux assays in degrader-resistant [dBET-R (A) or Thal-R (B)] A1847 cells after treatment with tariquidar, RAD001, or lapatinib (each 2 μM). Data are means ± SD of three independent experiments. *P ≤ 0.05 by Student’s t test. (C and D) CellTiter-Glo assay for the cell viability of parental, dBET6-R, or Thal-R A1847 cells treated with increasing concentrations of RAD001 (C) or lapatinib (D). Data were analyzed as % of DMSO control, presented as means ± SD of three independent assays. GI50 values were determined with Prism software. (E to I) Immunoblot analysis of degrader targets in parental (E), dBET6-R (F and G), and Thal-R (H and I) A1847 cells treated with increasing concentrations of RAD001 or lapatinib for 4 hours. Blots are representative, and densitometric analyses are means ± SD from three blots, each normalized to the loading control, GAPDH. DC50 value of dBET6 for BRD4 reduction (G) or of Thal SNS 032 for CDK9 reduction (I) determined with Prism. (J) Immunoblotting for cleaved PARP in dBET6-R or Thal-R A1847 cells treated with RAD001, lapatinib, or tariquidar (each 2 μM) for 24 hours. Blots are representative of three independent blots. (K to N) Immunoblotting for BRD4 in DLD-1 cells treated with increasing doses of dBET6 alone or in combination with either RAD001 or lapatinib [each 2 μM (K and L)] or KU-0063794 or afatinib [each 2 μM (M and N)] for 4 hours. Blots are representative of three independent experiments and, in (L), are means ± SD from three blots, each normalized to the loading control, GAPDH. DC50 value for BRD4 reduction (L) determined in Prism. (O) Colony formation by DLD-1 cells treated with DMSO, dBET6 (0.1 μM), lapatinib (2 μM), afatinib (2 μM), RAD001 (2 μM), KU-0063794 (2 μM), or the combination of inhibitor and dBET6 for 14 days. Images representative of three independent assays. (P and Q) Immunoblotting for CDK9 in DLD-1 cells treated with increasing doses of Thal SNS 032 and/or RAD001 (2 μM) or lapatinib (2 μM) for 4 hours. Blots are representative, and densitometric analyses are means ± SD from three blots, each normalized to the loading control, GAPDH. DC50 value for CDK9 reduction determined with Prism (Q). (R) Colony formation in DLD-1 cells treated with DMSO, Thal SNS 032 (0.5 μM), lapatinib (2 μM), and/or RAD001 (2 μM) as indicated for 14 days.

 

Fig. 6. Combining MEK1/2 degraders with lapatinib synergistically kills MDR1-overexpressing KRAS-mutant CRC cells and tumors.
(A and B) ABCB1 expression in KRAS-mutant CRC cell lines from cBioPortal (30) (A) and MDR1 abundance in select KRAS-mutant CRC cell lines (B). (C) Cell viability assessed by CellTiter-Glo in CRC cells treated with increasing doses of MS432 for 5 days, analyzed as % of DMSO control. GI50 value determined with Prism software. (D) Colony formation by CRC cells 14 days after treatment with 1 μM MS432. (E) MEK1/2 protein levels assessed by immunoblot in CRC lines SKCO1 (low MDR1) or LS513 (high MDR1) treated with increasing doses of MS432 for 4 hours. (F) Rhodamine 123 efflux in LS513 cells treated with DMSO, 2 μM tariquidar, or 2 μM lapatinib. (G and H) Immunoblotting analysis in LS513 cells treated with increasing doses of MS432 alone or in combination with tariquidar (0.1 μM) or lapatinib (5 μM) for 24 hours. DC50 value for MEK1 levels determined with Prism. (I) Immunoblotting in LS513 cells treated with DMSO, PD0325901 (0.01 μM), lapatinib (5 μM), or the combination for 48 hours. (J and K) Immunoblotting in LS513 cells treated either with DMSO, MS432 (1 μM), tariquidar (0.1 μM) (J), or lapatinib (5 μM) (K), alone or in combination. (L) Bliss synergy scores determined from cell viability assays (CellTiter-Glo) in LS513 cells treated with increasing concentrations of MS432, lapatinib, or the combination. (M and N) Colony formation by LS513 cells (M) and others (N) treated with DMSO, lapatinib (2 μM), MS432 (1 μM), or the combination for 14 days. (O and P) Immunoblotting in LS513 cells treated with increasing doses of MS934 alone (O) or combined with lapatinib (5 μM) (P) for 24 hours. (Q and R) Tumor volume of LS513 xenografts (Q) and the body weights of the tumor-bearing nude mice (R) treated with vehicle, MS934 (50 mg/kg), lapatinib (100 mg/kg), or the combination. n = 5 mice per treatment group. In (A) to (R), blots and images are representative of three independent experiments, and quantified data are means ± SD [SEM in (Q) and (R)] of three independent experiments; ***P ≤ 0.001 by Student’s t test.

 

Fig. 7. Lapatinib treatment improves KRASG12C degrader therapies in MDR1-overexpressing CRC cell lines.
(A and B) Colony formation by SW1463 (A) or SW837 (B) cells treated with DMSO, LC-2 (1 μM), or MRTX849 (1 μM) for 14 days. Images representative of three independent assays. (C to E) Immunoblotting in SW1463 cells (C and D) and SW837 cells (E) treated with DMSO, LC-2 (1 μM), tariquidar (0.1 μM) (C), or lapatinib (5 μM) (D and E) alone or in combination for 48 hours. Blots are representative of three independent experiments. (F and G) Bliss synergy scores based on CellTiter-Glo assay for the cell viability of SW1463 (F) or SW837 (G) cells treated with increasing concentrations of LC-2, lapatinib, or the combination. Data are means of three experiments ± SD. (H and I) Colony formation of SW1463 (H) or SW837 (I) cells treated as indicated (−, DMSO; LC-2, 1 μM; lapatinib, 2 μM; tariquidar, 0.1 μM) for 14 days. Images representative of three independent assays. (J) Rationale for combining lapatinib with MEK1/2 or KRASG12C degraders in MDR1-overexpressing CRC cell lines. Simultaneous blockade of MDR1 and ErbB receptor signaling overcomes degrader resistance and ErbB receptor kinome reprogramming, resulting in sustained inhibition of KRAS effector signaling.

SOURCE

Other articles in this Open Access Scientific Journal on PROTAC therapy in cancer include

Accelerating PROTAC drug discovery: Establishing a relationship between ubiquitination and target protein degradation

The Vibrant Philly Biotech Scene: Proteovant Therapeutics Using Artificial Intelligence and Machine Learning to Develop PROTACs

The Map of human proteins drawn by artificial intelligence and PROTAC (proteolysis targeting chimeras) Technology for Drug Discovery

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Live Conference Coverage AACR 2020 in Real Time: Monday June 22, 2020 Mid Day Sessions

Reporter: Stephen J. Williams, PhD

This post will be UPDATED during the next two days with notes from recordings from other talks

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Register for FREE at https://www.aacr.org/

 

AACR VIRTUAL ANNUAL MEETING II

 

June 22-24: Free Registration for AACR Members, the Cancer Community, and the Public
This virtual meeting will feature more than 120 sessions and 4,000 e-posters, including sessions on cancer health disparities and the impact of COVID-19 on clinical trials

 

This Virtual Meeting is Part II of the AACR Annual Meeting.  Part I was held online in April and was centered only on clinical findings.  This Part II of the virtual meeting will contain all the Sessions and Abstracts pertaining to basic and translational cancer research as well as clinical trial findings.

 

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Pezcoller Foundation-AACR International Award for Extraordinary Achievement in Cancer Research

The prestigious Pezcoller Foundation-AACR International Award for Extraordinary Achievement in Cancer Research was established in 1997 to annually recognize a scientist of international renown who has made a major scientific discovery in basic cancer research OR who has made significant contributions to translational cancer research; who continues to be active in cancer research and has a record of recent, noteworthy publications; and whose ongoing work holds promise for continued substantive contributions to progress in the field of cancer. For more information regarding the 2020 award recipient go to aacr.org/awards.

John E. Dick, Enzo Galligioni, David A Tuveson

DETAILS

Awardee: John E. Dick
Princess Anne Margaret Cancer Center, Toronto, Ontario
For determining how stem cells contribute to normal and leukemic hematopoeisis
  • not every cancer cell equal in their Cancer Hallmarks
  • how do we monitor and measure clonal dynamics
  • Barnie Clarkson did pivotal work on this
  • most cancer cells are post mitotic but minor populations of cells were dormant and survive chemotherapy
  •  only one cell is 1 in a million can regenerate and transplantable in mice and experiments with flow cytometry resolved the question of potency and repopulation of only small percentage of cells and undergo long term clonal population
  • so instead of going to cell lines and using thousands of shRNA looked at clinical data and deconvoluted the genetic information (RNASeq data) to determine progenitor and mature populations (how much is stem and how much is mature populations)
  • in leukemic patients they have seen massive expansion of a single stem cell population so only need one cell in AML if the stem cells have the mutational hits early on in their development
  • finding the “seeds of relapse”: finding the small subpopulation of stem cells that will relapse
  • they looked in BALL;;  there are cells resistant to l-aspariginase, dexamethasone, and vincristine
  • a lot of OXPHOS related genes (in DRIs) that may be the genes involved in this resistance
  • it a wonderful note of acknowledgement he dedicated this award to all of his past and present trainees who were the ones, as he said, made this field into what it is and for taking it into directions none of them could forsee

Monday, June 22

1:30 PM – 3:30 PM EDT

Virtual Educational Session

Experimental and Molecular Therapeutics, Drug Development, Cancer Chemistry

Chemistry to the Clinic: Part 1: Lead Optimization Case Studies in Cancer Drug Discovery

How can one continue to deliver innovative medicines to patients when biological targets are becoming ever scarcer and less amenable to therapeutic intervention? Are there sound strategies in place that can clear the path to targets previously considered “undruggable”? Recent advances in lead finding methods and novel technologies such as covalent screening and targeted protein degradation have enriched the toolbox at the disposal of drug discovery scientists to expand the druggable ta

Stefan N Gradl, Elena S Koltun, Scott D Edmondson, Matthew A. Marx, Joachim Rudolph

DETAILS

Monday, June 22

1:30 PM – 3:30 PM EDT

Virtual Educational Session

Bioinformatics and Systems Biology, Molecular and Cellular Biology/Genetics

Informatics Technologies for Cancer Research

Cancer researchers are faced with a deluge of high-throughput data. Using these data to advance understanding of cancer biology and improve clinical outcomes increasingly requires effective use of computational and informatics tools. This session will introduce informatics resources that support the data management, analysis, visualization, and interpretation. The primary focus will be on high-throughput genomic data and imaging data. Participants will be introduced to fundamental concepts

Rachel Karchin, Daniel Marcus, Andriy Fedorov, Obi Lee Griffith

DETAILS

  • Variant analysis is the big bottleneck, especially interpretation of variants
  • CIVIC resource is a network for curation, interpretation of genetic variants
  • CIVIC curators go through multiple rounds of editors review
  • gene summaries, variant summaries
  • curation follows ACSME guidelines
  • evidences are accumulated, categories by various ontologies and is the heart of the reports
  • as this is a network of curators the knowledgebase expands
  • CIVIC is linked to multiple external informatic, clinical, and genetic databases
  • they have curated 7017 clinical interpretations, 2527 variants, using 2578 papers, and over 1000 curators
  • they are currently integrating with COSMIC ClinVar, and UniProt
  • they are partnering with ClinGen to expand network of curators and their curation effort
  • CIVIC uses a Python interface; available on website

https://civicdb.org/home

The Precision Medicine Revolution

Precision medicine refers to the use of prevention and treatment strategies that are tailored to the unique features of each individual and their disease. In the context of cancer this might involve the identification of specific mutations shown to predict response to a targeted therapy. The biomedical literature describing these associations is large and growing rapidly. Currently these interpretations exist largely in private or encumbered databases resulting in extensive repetition of effort.

CIViC’s Role in Precision Medicine

Realizing precision medicine will require this information to be centralized, debated and interpreted for application in the clinic. CIViC is an open access, open source, community-driven web resource for Clinical Interpretation of Variants in Cancer. Our goal is to enable precision medicine by providing an educational forum for dissemination of knowledge and active discussion of the clinical significance of cancer genome alterations. For more details refer to the 2017 CIViC publication in Nature Genetics.

U24 funding announced: We are excited to announce that the Informatics Technology for Cancer Research (ICTR) program of the National Cancer Institute (NCI) has awarded funding to the CIViC team! Starting this year, a five-year, $3.7 million U24 award (CA237719), will support CIViC to develop Standardized and Genome-Wide Clinical Interpretation of Complex Genotypes for Cancer Precision Medicine.

Informatics tools for high-throughput analysis of cancer mutations

Rachel Karchin
  • CRAVAT is a platform to determine, categorize, and curate cancer mutations and cancer related variants
  • adding new tools used to be hard but having an open architecture allows for modular growth and easy integration of other tools
  • so they are actively making an open network using social media

Towards FAIR data in cancer imaging research

Andriy Fedorov, PhD

Towards the FAIR principles

While LOD has had some uptake across the web, the number of databases using this protocol compared to the other technologies is still modest. But whether or not we use LOD, we do need to ensure that databases are designed specifically for the web and for reuse by humans and machines. To provide guidance for creating such databases independent of the technology used, the FAIR principles were issued through FORCE11: the Future of Research Communications and e-Scholarship. The FAIR principles put forth characteristics that contemporary data resources, tools, vocabularies and infrastructures should exhibit to assist discovery and reuse by third-parties through the web. Wilkinson et al.,2016. FAIR stands for: Findable, Accessible, Interoperable and Re-usable. The definition of FAIR is provided in Table 1:

Number Principle
F Findable
F1 (meta)data are assigned a globally unique and persistent identifier
F2 data are described with rich metadata
F3 metadata clearly and explicitly include the identifier of the data it describes
F4 (meta)data are registered or indexed in a searchable resource
A Accessible
A1 (meta)data are retrievable by their identifier using a standardized communications protocol
A1.1 the protocol is open, free, and universally implementable
A1.2 the protocol allows for an authentication and authorization procedure, where necessary
A2 metadata are accessible, even when the data are no longer available
I Interoperable
I1 (meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation.
I2 (meta)data use vocabularies that follow FAIR principles
I3 (meta)data include qualified references to other (meta)data
R Reusable
R1 meta(data) are richly described with a plurality of accurate and relevant attributes
R1.1 (meta)data are released with a clear and accessible data usage license
R1.2 (meta)data are associated with detailed provenance
R1.3 (meta)data meet domain-relevant community standards

A detailed explanation of each of these is included in the Wilkinson et al., 2016 article, and the Dutch Techcenter for Life Sciences has a set of excellent tutorials, so we won’t go into too much detail here.

  • for outside vendors to access their data, vendors would need a signed Material Transfer Agreement but NCI had formulated a framework to facilitate sharing of data using a DIACOM standard for imaging data

Monday, June 22

1:30 PM – 3:01 PM EDT

Virtual Educational Session

Experimental and Molecular Therapeutics, Cancer Chemistry, Drug Development, Immunology

Engineering and Physical Sciences Approaches in Cancer Research, Diagnosis, and Therapy

The engineering and physical science disciplines have been increasingly involved in the development of new approaches to investigate, diagnose, and treat cancer. This session will address many of these efforts, including therapeutic methods such as improvements in drug delivery/targeting, new drugs and devices to effect immunomodulation and to synergize with immunotherapies, and intraoperative probes to improve surgical interventions. Imaging technologies and probes, sensors, and bioma

Claudia Fischbach, Ronit Satchi-Fainaro, Daniel A Heller

DETAILS

Monday, June 22

1:30 PM – 3:30 PM EDT

Virtual Educational Session

Survivorship

Exceptional Responders and Long-Term Survivors

How should we think about exceptional and super responders to cancer therapy? What biologic insights might ensue from considering these cases? What are ways in which considering super responders may lead to misleading conclusions? What are the pros and cons of the quest to locate exceptional and super responders?

Alice P Chen, Vinay K Prasad, Celeste Leigh Pearce

DETAILS

Monday, June 22

1:30 PM – 3:30 PM EDT

Virtual Educational Session

Tumor Biology, Immunology

Exploiting Metabolic Vulnerabilities in Cancer

The reprogramming of cellular metabolism is a hallmark feature observed across cancers. Contemporary research in this area has led to the discovery of tumor-specific metabolic mechanisms and illustrated ways that these can serve as selective, exploitable vulnerabilities. In this session, four international experts in tumor metabolism will discuss new findings concerning the rewiring of metabolic programs in cancer that support metabolic fitness, biosynthesis, redox balance, and the reg

Costas Andreas Lyssiotis, Gina M DeNicola, Ayelet Erez, Oliver Maddocks

DETAILS

Monday, June 22

1:30 PM – 3:30 PM EDT

Virtual Educational Session

Other Articles on this Open Access  Online Journal on Cancer Conferences and Conference Coverage in Real Time Include

Press Coverage

Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Symposium: New Drugs on the Horizon Part 3 12:30-1:25 PM

Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Session on NCI Activities: COVID-19 and Cancer Research 5:20 PM

Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Session on Evaluating Cancer Genomics from Normal Tissues Through Metastatic Disease 3:50 PM

Live Notes, Real Time Conference Coverage 2020 AACR Virtual Meeting April 28, 2020 Session on Novel Targets and Therapies 2:35 PM

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The Journey of Antibiotic Discovery

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

The term ‘antibiotic’ was introduced by Selman Waksman as any small molecule, produced by a microbe, with antagonistic properties on the growth of other microbes. An antibiotic interferes with bacterial survival via a specific mode of action but more importantly, at therapeutic concentrations, it is sufficiently potent to be effective against infection and simultaneously presents minimal toxicity. Infectious diseases have been a challenge throughout the ages. From 1347 to 1350, approximately one-third of Europe’s population perished to Bubonic plague. Advances in sanitary and hygienic conditions sufficed to control further plague outbreaks. However, these persisted as a recurrent public health issue. Likewise, infectious diseases in general remained the leading cause of death up to the early 1900s. The mortality rate shrunk after the commercialization of antibiotics, which given their impact on the fate of mankind, were regarded as a ‘medical miracle’. Moreover, the non-therapeutic application of antibiotics has also greatly affected humanity, for instance those used as livestock growth promoters to increase food production after World War II.

 

Currently, more than 2 million North Americans acquire infections associated with antibiotic resistance every year, resulting in 23,000 deaths. In Europe, nearly 700 thousand cases of antibiotic-resistant infections directly develop into over 33,000 deaths yearly, with an estimated cost over €1.5 billion. Despite a 36% increase in human use of antibiotics from 2000 to 2010, approximately 20% of deaths worldwide are related to infectious diseases today. Future perspectives are no brighter, for instance, a government commissioned study in the United Kingdom estimated 10 million deaths per year from antibiotic resistant infections by 2050.

 

The increase in antibiotic-resistant bacteria, alongside the alarmingly low rate of newly approved antibiotics for clinical usage, we are on the verge of not having effective treatments for many common infectious diseases. Historically, antibiotic discovery has been crucial in outpacing resistance and success is closely related to systematic procedures – platforms – that have catalyzed the antibiotic golden age, namely the Waksman platform, followed by the platforms of semi-synthesis and fully synthetic antibiotics. Said platforms resulted in the major antibiotic classes: aminoglycosides, amphenicols, ansamycins, beta-lactams, lipopeptides, diaminopyrimidines, fosfomycins, imidazoles, macrolides, oxazolidinones, streptogramins, polymyxins, sulphonamides, glycopeptides, quinolones and tetracyclines.

 

The increase in drug-resistant pathogens is a consequence of multiple factors, including but not limited to high rates of antimicrobial prescriptions, antibiotic mismanagement in the form of self-medication or interruption of therapy, and large-scale antibiotic use as growth promotors in livestock farming. For example, 60% of the antibiotics sold to the USA food industry are also used as therapeutics in humans. To further complicate matters, it is estimated that $200 million is required for a molecule to reach commercialization, with the risk of antimicrobial resistance rapidly developing, crippling its clinical application, or on the opposing end, a new antibiotic might be so effective it is only used as a last resort therapeutic, thus not widely commercialized.

 

Besides a more efficient management of antibiotic use, there is a pressing need for new platforms capable of consistently and efficiently delivering new lead substances, which should attend their precursors impressively low rates of success, in today’s increasing drug resistance scenario. Antibiotic Discovery Platforms are aiming to screen large libraries, for instance the reservoir of untapped natural products, which is likely the next antibiotic ‘gold mine’. There is a void between phenotanypic screening (high-throughput) and omics-centered assays (high-information), where some mechanistic and molecular information complements antimicrobial activity, without the laborious and extensive application of various omics assays. The increasing need for antibiotics drives the relentless and continuous research on the foreground of antibiotic discovery. This is likely to expand our knowledge on the biological events underlying infectious diseases and, hopefully, result in better therapeutics that can swing the war on infectious diseases back in our favor.

 

During the genomics era came the target-based platform, mostly considered a failure due to limitations in translating drugs to the clinic. Therefore, cell-based platforms were re-instituted, and are still of the utmost importance in the fight against infectious diseases. Although the antibiotic pipeline is still lackluster, especially of new classes and novel mechanisms of action, in the post-genomic era, there is an increasingly large set of information available on microbial metabolism. The translation of such knowledge into novel platforms will hopefully result in the discovery of new and better therapeutics, which can sway the war on infectious diseases back in our favor.

 

References:

 

https://www.mdpi.com/2079-6382/8/2/45/htm

 

https://www.ncbi.nlm.nih.gov/pubmed/19515346

 

https://www.ajicjournal.org/article/S0196-6553(11)00184-2/fulltext

 

https://www.ncbi.nlm.nih.gov/pubmed/21700626

 

http://www.med.or.jp/english/journal/pdf/2009_02/103_108.pdf

 

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Celiac Disease Breakthrough: (1) 472 genes regulated differently in organoids reflecting celiac disease than in non-celiac control organoids (2) bio-products derived from gut microorganisms can be employed to modify the epithelial response to gluten, a finding that could lead to future treatment strategies.

 

Reporter: Aviva Lev-Ari, PhD, RN

“These results confirm our hypothesis that genes and exposure to gluten are necessary but not sufficient, since changes in both the composition and function of the gut microbiome are also needed to switch from genetic predisposition to clinical outcome, as shown by our data,” said Alessio Fasano, HMS professor of pediatrics at Mass General, director of MIBRC and co-senior author of the paper.

https://hms.harvard.edu/news/major-shift?utm_source=Silverpop&utm_medium=email&utm_term=field_news_item_3&utm_content=HMNews05132019

 

 

Image Source: iStock/wildpixel

Article OPEN Published: 

Human gut derived-organoids provide model to study gluten response and effects of microbiota-derived molecules in celiac disease

Scientific Reports volume 9, Article number: 7029 (2019Download Citation

Abstract

Celiac disease (CD) is an immune-mediated disorder triggered by gluten exposure. The contribution of the adaptive immune response to CD pathogenesis has been extensively studied, but the absence of valid experimental models has hampered our understanding of the early steps leading to loss of gluten tolerance. Using intestinal organoids developed from duodenal biopsies from both non-celiac (NC) and celiac (CD) patients, we explored the contribution of gut epithelium to CD pathogenesis and the role of microbiota-derived molecules in modulating the epithelium’s response to gluten. When compared to NC, RNA sequencing of CD organoids revealed significantly altered expression of genes associated with gut barrier, innate immune response, and stem cell functions. Monolayers derived from CD organoids exposed to gliadin showed increased intestinal permeability and enhanced secretion of pro-inflammatory cytokines compared to NC controls. Microbiota-derived bioproducts butyrate, lactate, and polysaccharide A improved barrier function and reduced gliadin-induced cytokine secretion. We concluded that: (1) patient-derived organoids faithfully express established and newly identified molecular signatures characteristic of CD. (2) microbiota-derived bioproducts can be used to modulate the epithelial response to gluten. Finally, we validated the use of patient-derived organoids monolayers as a novel tool for the study of CD.

Mass. General researchers develop 3D “mini-gut” model to study autoimmune response to gluten in celiac and non-celiac patient tissue

Gene expression of intestinal organoids reflects functional differences found in celiac disease

In pursuit of a novel tool for the research and treatment of celiac disease, scientists at the Mucosal Immunology and Biology Research Center (MIBRC) at Massachusetts General Hospital (MGH) have validated the use of intestinal organoids. These three-dimensional tissue cultures are miniature, simplified versions of the intestine produced in vitro. Taking tissue from duodenal biopsies of celiac and non-celiac patients, researchers created the “mini-guts” to explore how the gut epithelium and microbiota-derived molecules respond to gluten, a complex class of proteins found in wheat and other grains.

“We currently have no animal model that can recapitulate the response to gluten that we see in humans,” says Stefania Senger, PhD, co-senior author of the study published in Scientific Reports this week. “Using this human tissue model, we observed that intestinal organoids express the same molecular markers as actual epithelium in the celiac tissue, and the signature gene expression reflects the functional differences that occur when epithelia of celiac disease patients are exposed to gliadin.” Gliadin and glutenin proteins are main components of gluten.

Celiac disease is triggered when genetically predisposed individuals consume gluten. The condition affects approximately 1 percent of the U.S. population. Based on current data, the onset of celiac disease is thought to be preceded by the release of the protein zonulin, which is triggered by the activation of undigested gliadin to induce an autoimmune response. This leads to increased intestinal permeability and a disrupted barrier function. Novel evidence suggests that the microorganisms in the gastrointestinal tract may play a role in the onset of celiac disease.

Earlier studies from the MIBRC group and others have shown that human organoids “retain a gene expression that recapitulates the expression of the tissue of origin, including a diseased state,” the authors write. Through RNA sequencing, the new findings validate the organoid model as a “faithful in vitro model for celiac disease,” Senger says.
Using whole-transcriptome analysis, the researchers identified 472 genes regulated differently in organoids reflecting celiac disease than in non-celiac control organoids. These included novel genes associated with epithelial functions related to the pathogenesis of celiac disease – including gut barrier maintenance, stem cell regeneration and innate immune response. A second finding of the study shows that bioproducts derived from gut microorganisms can be employed to modify the epithelial response to gluten, a finding that could lead to future treatment strategies.

“These results confirm our hypothesis that genes and exposure to gluten are necessary but not sufficient, since changes in both the composition and function of the gut microbiome are also needed to switch from genetic predisposition to clinical outcome, as shown by our data,” says Alessio Fasano, MD, director of the Mucosal Immunology and Biology Research Center and co-senior author.

Senger adds, “We believe our observations represent a major shift in the study of celiac disease. We are confident that with adequate funding we could achieve major goals that include the development and implementation of high-throughput drug screenings to quickly identify new treatments for patients and expand the organoid repository to develop more complex models and pursue personalized treatment.”
Additional co-authors of the paper are first author Rachel Freire, PhD, along with Laura Ingano and Gloria Serena, PhD, of the MGH MIBRC; Murat Cetinbas, PhD, and Ruslan Sadreyev, PhD, MGH Department of Molecular Biology; Anthony Anselmo, PhD, formerly of MGH Molecular Biology and now with PatientsLikeMe, Cambridge, Mass.; and Anna Sapone, MD, PhD, Takeda Pharmaceuticals International. Support for the study includes National Institutes of Health grants RO1 DK104344-01A1 and 1U19 AI082655-02 and the Egan Family Foundation.

SOURCE

https://www.massgeneral.org/about/pressrelease.aspx?id=2403

 

Other related articles and e-Books by LPBI Group’s Authors published on this Open Access Online Scientific Journal include the following:

 

Series D: e-Books on BioMedicine – Metabolomics, Immunology, Infectious Diseases

  • Metabolomics 

VOLUME 1: Metabolic Genomics and Pharmaceutics. On Amazon.com since 7/21/2015

http://www.amazon.com/dp/B012BB0ZF0

Gluten-free Diets

Writer and Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2015/03/01/gluten-free-diets/

 

Breakthrough Digestive Disorders Research: Conditions affecting the Gastrointestinal Tract.

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2012/12/12/breakthrough-digestive-disorders-research-conditions-affecting-the-gastrointestinal-tract/

 

Collagen-binding Molecular Chaperone HSP47: Role in Intestinal Fibrosis – colonic epithelial cells and subepithelial myofibroblasts

Curators: Larry H Bernstein, MD, FCAP and Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2016/01/25/collagen-binding-molecular-chaperone-hsp47-role-in-intestinal-fibrosis-colonic-epithelial-cells-and-subepithelial-myofibroblasts/

Expanding area of Tolerance-inducing Autoimmune Disease Therapeutics: Key Players

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2017/01/17/expanding-area-of-tolerance-inducing-autoimmune-disease-therapeutics-key-players/

 

What is the key method to harness Inflammation to close the doors for many complex diseases?

Author and Curator: Larry H Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2014/03/21/what-is-the-key-method-to-harness-inflammation-to-close-the-doors-for-many-complex-diseases/

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The second annual PureTech Health BIG (Brain-Immune-Gut) Summit 2019 – By invitation only –

Selected Tweets from  #BIGAxisSummit

by @pharma_BI @AVIVA1950

for @pharmaceuticalintelligence.com

Reporter: Aviva Lev-Ari, PhD, RN

 

January 30 – February 1, 2019

The second annual PureTech Health BIG Summit brings together an elite ensemble of leading scientific researchers, investors, and CEOs and R&D leaders from major pharmaceutical, technology, and biotech companies.

The BIG Summit is designed to stimulate ideas that will have an impact on existing pipelines and catalyze future interactions among a group of delegates that represent leaders and innovators in their fields.

Please follow the discussion on Twitter using #BIGAxisSummit

By invitation only; registration is non-transferable.

For more information, please contact PureTechHealthSummit@PureTechHealth.com

 

HOST COMMITTEE

Participants

 

BIG SUMMIT AGENDA

(Subject to Change)

PureTech Health BIG Summit 2019 Agenda_FINALv2_WEBSITE.jpg

“Almost starting to understand immunology at this thought-provoking @PureTechh #BIGAxisSummit. Great Speakers.”

-tweet by Simone Fishburn, BioCentury @SimoneFishburn

SOURCE

https://bigsummit2019.com/agenda/

 

Selected Tweets from  #BIGAxisSummit

by @pharma_BI @AVIVA1950

for @pharmaceuticalintelligence.com

Gail S. Thornton Selections

Luke Timmerman‏ @ldtimmerman 7h7 hours ago

Back for final sessions at #BIGAxisSummit. @PureTechH Jim Harper of Sonde Health talking about how voice data — pacing, fine motor articulation, oscillation — can point the way to objective, quantitative measures for detecting and monitoring depression.

 

Eddie Martucci

 @EddieMartucci 5h5 hours ago

Paul Biondi at #BIGAxisSummit : What makes big deals happen is financial, and *deep conviction* of a big future fit. Disproportionate valuation from bidders is expected.

Love this. We often reduce everything to mathematical analyses to champion or ridicule deals. Not that simple

 

PureTech Health Plc‏ @PureTechH Jan 31

Bob Langer (@MIT) asks how #lymphatics affected by #aging. Santambrogio: typically blame aging #immune cells for increased disease, but aging affects lymphatics too (less efficient trafficking shown). Rejuvenating these could affect several aging-related diseases #BigAxisSummit

 

PureTech Health Plc‏ @PureTechH Jan 31

Viviane Labrie (@VAInstitute) discusses why the appendix has been identified as a potential starting point for #parkinsons #BIGAxisSummit

 

PureTech Health Plc‏ @PureTechH Jan 31

Chris Porter (@MIPS_Australia) notes #lymphatics is major route for trafficking #immune cells that surveil gut and respond to immune & #autoimmune stimuli. This is key in #BIGAxis interactions and why lymphatics-targeted therapies could enhance #immunomodulation #BIGAxisSummit

 

Dr. Stephen J. Williams Selections

1.

2.

3.

4.

5.

Dr. Irina Robu Selection

1.

2.

3.

4.

5.

Dr. Sudipta Saha Selection

1.

2.

3.

4.

5.

 

 

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Ability of gut microbiota to influence the bioavailability of in Parkinson’s disease – The presence of more bacteria producing the tyrosine decarboxylase (TDC) enzyme means less levodopa in the bloodstream

 

Reporter: Aviva Lev-Ari, PhD, RN

 

Decarboxylase enzymes can convert levodopa into dopamine. In contrast to levodopa, dopamine cannot cross the , so patients are also given a decarboxylase inhibitor. “But the levels of levodopa that will reach the brain vary strongly among Parkinson’s disease patients.

The bacterial  decarboxylase enzyme, which normally converts tyrosine into tyramine, but was found to also convert levodopa into . “We then determined that the source of this decarboxylase was Enterococcus bacteria.” The researchers also showed that the conversion of levodopa was not inhibited by a high concentration of the amino acid tyrosine, the main substrate of the bacterial tyrosine decarboxylase enzyme.

  • Carbidopa is over 10,000 times more potent in inhibiting the human decarboxylase,
  • the higher abundance of bacterial enzyme in the small intestines of rats reduced levels of levodopa in the bloodstream,
  • positive correlation between disease duration and levels of bacterial tyrosine decarboxylase.
  • Some Parkinson’s disease patients develop an overgrowth of small intestinal bacteria including Enterococci due to frequent uptake of proton pump inhibitors, which they use to treat gastrointestinal symptoms associated with the disease.
  • Altogether, these factors result in a vicious circle leading to an increased levodopa/decarboxylase inhibitor dosage requirement in a subset of patients.El Aidy concludes that
  • the presence of the bacterial tyrosine decarboxylase enzyme can explain why some patients need more frequent dosages of levodopa to treat their motor fluctuations. “This is considered to be a problem for Parkinson’s disease patients, because a higher dose will result in dyskinesia, one of the major side effects of levodopa treatment.

SOURCE

https://www.rdmag.com/news/2019/01/how-gut-bacteria-affect-treatment-parkinsons-disease?type=cta&et_cid=6585419&et_rid=461755519&linkid=Mobius_Link

Article OPEN Published: 

Gut bacterial tyrosine decarboxylases restrict levels of levodopa in the treatment of Parkinson’s disease

Nature Communications volume 10, Article number: 310 (2019) Download Citation

Abstract

Human gut microbiota senses its environment and responds by releasing metabolites, some of which are key regulators of human health and disease. In this study, we characterize gut-associated bacteria in their ability to decarboxylate levodopa to dopamine via tyrosine decarboxylases. Bacterial tyrosine decarboxylases efficiently convert levodopa to dopamine, even in the presence of tyrosine, a competitive substrate, or inhibitors of human decarboxylase. In situ levels of levodopa are compromised by high abundance of gut bacterial tyrosine decarboxylase in patients with Parkinson’s disease. Finally, the higher relative abundance of bacterial tyrosine decarboxylases at the site of levodopa absorption, proximal small intestine, had a significant impact on levels of levodopa in the plasma of rats. Our results highlight the role of microbial metabolism in drug availability, and specifically, that abundance of bacterial tyrosine decarboxylase in the proximal small intestine can explain the increased dosage regimen of levodopa treatment in Parkinson’s disease patients.

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RELATED READS

 

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Live 11:00 AM- 12:00 Mediterranean Diet and Lifestyle: A Symposium on Diet and Human Health : Opening Remarks October 19, 2018

Reporter: Stephen J. Williams, Ph.D.

11:00 Welcome

 

 

Prof. Antonio Giordano, MD, PhD.

Director and President of the Sbarro Health Research Organization, College of Science and Technology, Temple University

Welcome to this symposium on Italian lifestyle and health.  This is similar to a symposium we had organized in New York.  A year ago Bloomberg came out with a study on higher longevity of the italian population and this study was concluded that this increased longevity was due to the italian lifestyle and diet especially in the southern part of Italy, a region which is older than Rome (actually founded by Greeks and Estonians).  However this symposium will delve into the components of this healthy Italian lifestyle which contributes to this longevity effect.  Some of this work was done in collaboration with Temple University and sponsored by the Italian Consulate General in Philadelphia ( which sponsors programs in this area called Ciao Philadelphia).

Greetings: Fucsia Nissoli Fitzgerald, Deputy elected in the Foreign Circumscription – North and Central America Division

Speaking for the Consulate General is Francesca  Cardurani-Meloni.   I would like to talk briefly about the Italian cuisine and its evolution, from the influence of the North and South Italy, economic factors, and influence by other cultures.  Italian cooking is about simplicity, cooking with what is in season and freshest.  The meal is not about the food but about comfort around the table, and comparible to a cullinary heaven, about sharing with family and friends, and bringing the freshest ingredients to the table.

Consul General, Honorable Pier Attinio Forlano, General Consul of Italy in Philadelphia

 

11:30 The Impact of Environment and Life Style in Human Disease

Prof. Antonio Giordano MD, PhD.

 

 

 

To follow or Tweet on Twitter please use the following handles (@) and hashtags (#):

@ handles


@S_H_R_O 

@SbarroHealth

@Pharma_BI 

@ItalyinPhilly

@WHO_Europe

@nutritionorg

# hashtags


#healthydiet

#MediterraneanDiet

#health

#nutrition

Please see related articles on Live Coverage of Previous Meetings on this Open Access Journal

Real Time Conference Coverage for Scientific and Business Media: Unique Twitter Hashtags and Handles per Conference Presentation/Session

LIVE – Real Time – 16th Annual Cancer Research Symposium, Koch Institute, Friday, June 16, 9AM – 5PM, Kresge Auditorium, MIT

Real Time Coverage and eProceedings of Presentations on 11/16 – 11/17, 2016, The 12th Annual Personalized Medicine Conference, HARVARD MEDICAL SCHOOL, Joseph B. Martin Conference Center, 77 Avenue Louis Pasteur, Boston

Tweets Impression Analytics, Re-Tweets, Tweets and Likes by @AVIVA1950 and @pharma_BI for 2018 BioIT, Boston, 5/15 – 5/17, 2018

BIO 2018! June 4-7, 2018 at Boston Convention & Exhibition Center

LIVE 2018 The 21st Gabay Award to LORENZ STUDER, Memorial Sloan Kettering Cancer Center, contributions in stem cell biology and patient-specific, cell-based therapy

HUBweek 2018, October 8-14, 2018, Greater Boston – “We The Future” – coming together, of breaking down barriers, of convening across disciplinary lines to shape our future

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Benefits of Fiber in Diet

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

UPDATED on 1/15/2019

This is How Much Daily Fiber to Eat for Better Health – More appears better in meta-analysis — as in more than 30 g/day

by Ashley Lyles, Staff Writer, MedPage Today

In the systematic review, observational data showed a 15% to 30% decline in cardiovascular-related death, all-cause mortality, and incidence of stroke, coronary heart disease, type 2 diabetes, and colorectal cancer among people who consumed the most dietary fiber compared to those consuming the lowest amounts.

Whole grain intake yielded similar findings.

Risk reduction associated with a range of critical outcomes was greatest when daily intake of dietary fibre was between 25 g and 29 g. Dose-response curves suggested that higher intakes of dietary fibre could confer even greater benefit to protect against cardiovascular diseases, type 2 diabetes, and colorectal and breast cancer.

https://www.thelancet.com/pdfs/journals/lancet/PIIS0140-6736(18)31809-9.pdf

Eating more dietary fiber was linked with lower risk of disease and death, a meta-analysis showed.

According to observational studies, risk was reduced most for a range of critical outcomes from all-cause mortality to stroke when daily fiber consumption was between 25 grams and 29 grams, reported Jim Mann, PhD, of University of Otago in Dunedin, New Zealand, and colleagues in The Lancet.

By upping daily intake to 30 grams or more, people had even greater prevention of certain conditions: colorectal and breast cancer, type 2 diabetes, and cardiovascular diseases, according to dose-response curves the authors created.

Quantitative guidelines relating to dietary fiber have not been available, the researchers said. With the GRADE method, they determined that there was moderate and low-to-moderate certainty of evidence for the benefits of dietary fiber consumption and whole grain consumption, respectively.

Included in the systematic review were 58 clinical trials and 185 prospective studies for a total of 4,635 adult participants with 135 million person-years of information (one trial in children was included, but analyzed separately from adults). Trials and prospective studies assessing weight loss, supplement use, and participants with a chronic disease were excluded.

 

Food is digested by bathing in enzymes that break down its molecules. Those molecular fragments then pass through the gut wall and are absorbed in our intestines. But our bodies make a limited range of enzymes, so that we cannot break down many of the tough compounds in plants. The term “dietary fiber” refers to those indigestible molecules. These dietary fibers are indigestible only to us. The gut is coated with a layer of mucus, on which sits a carpet of hundreds of species of bacteria, part of the human microbiome. Some of these microbes carry the enzymes needed to break down various kinds of dietary fibers.

 

Scientists at the University of Gothenburg in Sweden are running experiments that are yielding some important new clues about fiber’s role in human health. Their research indicates that fiber doesn’t deliver many of its benefits directly to our bodies. Instead, the fiber we eat feeds billions of bacteria in our guts. Keeping them happy means our intestines and immune systems remain in good working order. The scientists have recently reported that the microbes are involved in the benefits obtained from the fruits-and-vegetables diet. Research proved that low fiber diet decreases the gut bacteria population by tenfold.

 

Along with changes to the microbiome there were also rapid changes observed in the experimental mice. Their intestines got smaller, and its mucus layer thinner. As a result, bacteria wound up much closer to the intestinal wall, and that encroachment triggered an immune reaction. After a few days on the low-fiber diet, mouse intestines developed chronic inflammation. After a few weeks, they started putting on fat and developing higher blood sugar levels. Inflammation can help fight infections, but if it becomes chronic, it can harm our bodies. Among other things, chronic inflammation may interfere with how the body uses the calories in food, storing more of it as fat rather than burning it for energy.

 

In a way fiber benefits human health is by giving, indirectly, another source of food. When bacteria finished harvesting the energy in the dietary fiber, they cast off the fragments as waste. That waste — in the form of short-chain fatty acids — is absorbed by intestinal cells, which use it as fuel. But the gut’s microbes do more than just make energy. They also send messages. Intestinal cells rely on chemical signals from the bacteria to work properly. The cells respond to the signals by multiplying and making a healthy supply of mucus. They also release bacteria-killing molecules. By generating these responses, gut bacteria help to maintain a peaceful coexistence with the immune system. They rest on the gut’s mucus layer at a safe distance from the intestinal wall. Any bacteria that wind up too close get wiped out by antimicrobial poisons.

 

A diet of fiber-rich foods, such as fruits and vegetables, reduces the risk of developing diabetes, heart disease and arthritis. Eating more fiber seems to lower people’s mortality rate, whatever be the cause. Researchers hope that they will learn more about how fiber influences the microbiome to use it as a way to treat disorders. Lowering inflammation with fiber may also help in the treatment of immune disorders such as inflammatory bowel disease. Fiber may also help reverse obesity. They found that fiber supplements helped obese people to lose weight. It’s possible that each type of fiber feeds a particular set of bacteria, which send their own important signals to our bodies.

 

References:

 

https://www.nytimes.com/2018/01/01/science/food-fiber-microbiome-inflammation.html

 

 

https://www.ncbi.nlm.nih.gov/pubmed/29276171

 

https://www.ncbi.nlm.nih.gov/pubmed/29276170

 

https://www.ncbi.nlm.nih.gov/pubmed/29486139

 

https://www.mayoclinic.org/healthy-lifestyle/nutrition-and-healthy-eating/in-depth/fiber/art-20043983

 

https://nutritiouslife.com/eat-empowered/high-fiber-diet/

 

http://www.eatingwell.com/article/287742/10-amazing-health-benefits-of-eating-more-fiber/

 

http://www.cookinglight.com/eating-smart/nutrition-101/what-is-a-high-fiber-diet

 

https://www.helpguide.org/articles/healthy-eating/high-fiber-foods.htm

 

https://www.gicare.com/diets/high-fiber-diet/

 

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Highlighted Progress in Science – 2017

Reporter: Sudipta Saha, PhD

 

  1. Lungs can supply blood stem cells and also produce platelets: Lungs, known primarily for breathing, play a previously unrecognized role in blood production, with more than half of the platelets in a mouse’s circulation produced there. Furthermore, a previously unknown pool of blood stem cells has been identified that is capable of restoring blood production when bone marrow stem cells are depleted.

 

  1. A new drug for multiple sclerosis: A new multiple sclerosis (MS) drug, which grew out of the work of UCSF (University of California, San Francisco) neurologist was approved by the FDA. Ocrelizumab, the first drug to reflect current scientific understanding of MS, was approved to treat both relapsing-remitting MS and primary progressive MS.

 

  1. Marijuana legalized – research needed on therapeutic possibilities and negative effects: Recreational marijuana will be legal in California starting in January, and that has brought a renewed urgency to seek out more information on the drug’s health effects, both positive and negative. UCSF scientists recognize marijuana’s contradictory status: the drug has proven therapeutic uses, but it can also lead to tremendous public health problems.

 

  1. Source of autism discovered: In a finding that could help unlock the fundamental mysteries about how events early in brain development lead to autism, researchers traced how distinct sets of genetic defects in a single neuronal protein can lead to either epilepsy in infancy or to autism spectrum disorders in predictable ways.

 

  1. Protein found in diet responsible for inflammation in brain: Ketogenic diets, characterized by extreme low-carbohydrate, high-fat regimens are known to benefit people with epilepsy and other neurological illnesses by lowering inflammation in the brain. UCSF researchers discovered the previously undiscovered mechanism by which a low-carbohydrate diet reduces inflammation in the brain. Importantly, the team identified a pivotal protein that links the diet to inflammatory genes, which, if blocked, could mirror the anti-inflammatory effects of ketogenic diets.

 

  1. Learning and memory failure due to brain injury is now restorable by drug: In a finding that holds promise for treating people with traumatic brain injury, an experimental drug, ISRIB (integrated stress response inhibitor), completely reversed severe learning and memory impairments caused by traumatic brain injury in mice. The groundbreaking finding revealed that the drug fully restored the ability to learn and remember in the brain-injured mice even when the animals were initially treated as long as a month after injury.

 

  1. Regulatory T cells induce stem cells for promoting hair growth: In a finding that could impact baldness, researchers found that regulatory T cells, a type of immune cell generally associated with controlling inflammation, directly trigger stem cells in the skin to promote healthy hair growth. An experiment with mice revealed that without these immune cells as partners, stem cells cannot regenerate hair follicles, leading to baldness.

 

  1. More intake of good fat is also bad: Liberal consumption of good fat (monounsaturated fat) – found in olive oil and avocados – may lead to fatty liver disease, a risk factor for metabolic disorders like type 2 diabetes and hypertension. Eating the fat in combination with high starch content was found to cause the most severe fatty liver disease in mice.

 

  1. Chemical toxicity in almost every daily use products: Unregulated chemicals are increasingly prevalent in products people use every day, and that rise matches a concurrent rise in health conditions like cancers and childhood diseases, Thus, researcher in UCSF is working to understand the environment’s role – including exposure to chemicals – in health conditions.

 

  1. Cytomegalovirus found as common factor for diabetes and heart disease in young women: Cytomegalovirus is associated with risk factors for type 2 diabetes and heart disease in women younger than 50. Women of normal weight who were infected with the typically asymptomatic cytomegalovirus, or CMV, were more likely to have metabolic syndrome. Surprisingly, the reverse was found in those with extreme obesity.

 

References:

 

https://www.ucsf.edu/news/2017/12/409241/most-popular-science-stories-2017

 

https://www.ucsf.edu/news/2017/03/406111/surprising-new-role-lungs-making-blood

 

https://www.ucsf.edu/news/2017/03/406296/new-multiple-sclerosis-drug-ocrelizumab-could-halt-disease

 

https://www.ucsf.edu/news/2017/06/407351/dazed-and-confused-marijuana-legalization-raises-need-more-research

 

https://www.ucsf.edu/news/2017/01/405631/autism-researchers-discover-genetic-rosetta-stone

 

https://www.ucsf.edu/news/2017/09/408366/how-ketogenic-diets-curb-inflammation-brain

 

https://www.ucsf.edu/news/2017/07/407656/drug-reverses-memory-failure-caused-traumatic-brain-injury

 

https://www.ucsf.edu/news/2017/05/407121/new-hair-growth-mechanism-discovered

 

https://www.ucsf.edu/news/2017/06/407536/go-easy-avocado-toast-good-fat-can-still-be-bad-you-research-shows

 

https://www.ucsf.edu/news/2017/06/407416/toxic-exposure-chemicals-are-our-water-food-air-and-furniture

 

https://www.ucsf.edu/news/2017/02/405871/common-virus-tied-diabetes-heart-disease-women-under-50

 

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Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

The trillions of microbes in the human gut are known to aid the body in synthesizing key vitamins and other nutrients. But this new study suggests that things can sometimes be more adversarial.

 

Choline is a key nutrient in a range of metabolic processes, as well as the production of cell membranes. Researchers identified a strain of choline-metabolizing E. coli that, when transplanted into the guts of germ-free mice, consumed enough of the nutrient to create a choline deficiency in them, even when the animals consumed a choline-rich diet.

 

This new study indicate that choline-utilizing bacteria compete with the host for this nutrient, significantly impacting plasma and hepatic levels of methyl-donor metabolites and recapitulating biochemical signatures of choline deficiency. Mice harboring high levels of choline-consuming bacteria showed increased susceptibility to metabolic disease in the context of a high-fat diet.

 

DNA methylation is essential for normal development and has been linked to everything from aging to carcinogenesis. This study showed changes in DNA methylation across multiple tissues, not just in adult mice with a choline-consuming gut microbiota, but also in the pups of those animals while they developed in utero.

 

Bacterially induced reduction of methyl-donor availability influenced global DNA methylation patterns in both adult mice and their offspring and engendered behavioral alterations. This study reveal an underappreciated effect of bacterial choline metabolism on host metabolism, epigenetics, and behavior.

 

The choline-deficient mice with choline-consuming gut microbes also showed much higher rates of infanticide, and exhibited signs of anxiety, with some mice over-grooming themselves and their cage-mates, sometimes to the point of baldness.

 

Tests have also shown as many as 65 percent of healthy individuals carry genes that encode for the enzyme that metabolizes choline in their gut microbiomes. This work suggests that interpersonal differences in microbial metabolism should be considered when determining optimal nutrient intake requirements.

 

References:

 

https://news.harvard.edu/gazette/story/2017/11/harvard-research-suggests-microbial-menace/

 

http://www.cell.com/cell-host-microbe/fulltext/S1931-3128(17)30304-9

 

https://www.ncbi.nlm.nih.gov/pubmed/23151509

 

https://www.ncbi.nlm.nih.gov/pubmed/25677519

 

http://mbio.asm.org/content/6/2/e02481-14

 

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