41 research outputs found

    The impact of surgical delay on resectability of colorectal cancer: An international prospective cohort study

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    AIM: The SARS-CoV-2 pandemic has provided a unique opportunity to explore the impact of surgical delays on cancer resectability. This study aimed to compare resectability for colorectal cancer patients undergoing delayed versus non-delayed surgery. METHODS: This was an international prospective cohort study of consecutive colorectal cancer patients with a decision for curative surgery (January-April 2020). Surgical delay was defined as an operation taking place more than 4 weeks after treatment decision, in a patient who did not receive neoadjuvant therapy. A subgroup analysis explored the effects of delay in elective patients only. The impact of longer delays was explored in a sensitivity analysis. The primary outcome was complete resection, defined as curative resection with an R0 margin. RESULTS: Overall, 5453 patients from 304 hospitals in 47 countries were included, of whom 6.6% (358/5453) did not receive their planned operation. Of the 4304 operated patients without neoadjuvant therapy, 40.5% (1744/4304) were delayed beyond 4 weeks. Delayed patients were more likely to be older, men, more comorbid, have higher body mass index and have rectal cancer and early stage disease. Delayed patients had higher unadjusted rates of complete resection (93.7% vs. 91.9%, P = 0.032) and lower rates of emergency surgery (4.5% vs. 22.5%, P < 0.001). After adjustment, delay was not associated with a lower rate of complete resection (OR 1.18, 95% CI 0.90-1.55, P = 0.224), which was consistent in elective patients only (OR 0.94, 95% CI 0.69-1.27, P = 0.672). Longer delays were not associated with poorer outcomes. CONCLUSION: One in 15 colorectal cancer patients did not receive their planned operation during the first wave of COVID-19. Surgical delay did not appear to compromise resectability, raising the hypothesis that any reduction in long-term survival attributable to delays is likely to be due to micro-metastatic disease

    Down-regulation and alternative splicing of methionine synthase as an adaptive response to oxidative stress in aging and neurological disorders

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    The folate and cobalamin-dependent enzyme methionine synthase converts homocysteine to methionine, but oxidation of its cobalamin cofactor halts activity, leading to increased levels of homocysteine. Homocysteine can be converted to cystathionine through the transsulfuration pathway, via the enzyme cystathionine β-synthase, resulting in glutathione synthesis. The enzymes methionine synthase and cystathionine β-synthase flank homocysteine, and their relative enzymatic activities determine the proportion of homocysteine that can enter the methylation or transsulfuration pathways. Prevailing redox conditions may adjust this flux by modulating the enzyme via multiple mechanisms. Glutathione is the principal intracellular antioxidant, and adequate levels of its reduced form are essential for survival in an oxidative metabolic environment. The thiol-containing amino acid cysteine is rate-limiting for glutathione synthesis and can be provided through either cellular uptake or conversion through transsulfuration. Methionine synthase possesses a linker domain termed 'cap' that is responsible for covering the susceptible cobalamin from oxidation, and loss of this domain may lead to enzyme inactivation. Oxidative stress, associated with lower glutathione levels, is an important contributor to neurodevelopmental and neurodegenerative disorders such as autism, Alzheimer's disease, and schizophrenia. I used qRT-PCR to evaluate the level of methionine synthase mRNA in post-mortem human cortex and found a significant decrease with age, from 28 weeks of fetal gestation to greater than 80 years. Domain-specific PCR showed that the cap/cobalamin ratio is significantly decreased in subjects over the age of 60, implying age-dependent alternative splicing of the cap domain. Further studies revealed the deletion of exons 19 and 20 of the cap domain, which would reduce the domain size and possibly favor inactivation of MS, leading to increased flux of homocysteine into the transsulfuration pathway and glutathione formation. A comparison study between autistic subjects and age-matched controls, age 4 to 30 years, revealed significantly lower levels of methionine synthase mRNA in autistic subjects. The greatest decrease occurred in the youngest subjects, when levels in control subjects were normally at their highest, implying an adaptive response to elevated levels of oxidative stress. Thus, autism likely results from a disruption of both normal redox regulation and methylation status. Exon-specific studies probing folate-binding and cap domain exons in SH-SY5Y human neuroblastoma cells highlighted a combinatorial approach to MS composition. It is likely that different isoforms are generated, depending on the cellular redox status, as an adaptive response to oxidative stress. Non-neuronal cell lines HEK, HepG2 and LN-18 do not show similar splicing modifications, suggesting that redox-dependent splicing is not a feature of all cell types and is more prominent in neuronal cells. Tumor necrosis factor-alpha, a pro-inflammatory cytokine, is able to induce neuroinflammation, which is a common underlying problem in autism. Tumor necrosis factoralpha treatment significantly reduced both cobalamin-binding and cap domain mRNA in SHSY5Y human neuroblastoma cells, while increasing homocysteine levels. Additionally, cysteine and glutathione levels were increased, despite lower cysteine uptake, indicating an increase in transsulfuration. Methionine synthase activity was inhibited by tumor necrosis factor-alpha, which, when coupled with the mRNA data, indicates transcriptional changes in methionine synthase that can affect cellular redox and methylation activity. Alternative splicing of the cap domain may reflect previously unrecognized alterations in methionine synthase in response to oxidative stress and aging. The resultant link between redox status and methylation activity is likely to be an important factor in neurodevelopmental, neuropsychiatric and neurodegenerative disorders. These findings represent an important adaptive response to counter progressive oxidation with aging and further indicate that autism may be a neurometabolic redox disorder in which lower levels of methionine synthase activity play an important role

    Data from: Comparison and optimization of hiPSC forebrain cortical differentiation protocols

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    Several protocols have been developed for human induced pluripotent stem cell neuronal differentiation. We compare several methods for forebrain cortical neuronal differentiation by assessing cell morphology, immunostaining and gene expression. We evaluate embryoid aggregate vs. monolayer with dual SMAD inhibition differentiation protocols, manual vs. AggreWell aggregate formation, plating substrates, neural progenitor cell (NPC) isolation methods, NPC maintenance and expansion, and astrocyte co-culture. The embryoid aggregate protocol, using a Matrigel substrate, consistently generates a high yield and purity of neurons. NPC isolation by manual selection, enzymatic rosette selection, or FACS all are efficient, but exhibit some differences in resulting cell populations. Expansion of NPCs as neural aggregates yields higher cell purity than expansion in a monolayer. Finally, co-culture of iPSC-derived neurons with astrocytes increases neuronal maturity by day 40. This study directly compares commonly employed methods for neuronal differentiation of iPSCs, and can be used as a resource for choosing between various differentiation protocols

    Data from: Comparison and optimization of hiPSC forebrain cortical differentiation protocols

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    Several protocols have been developed for human induced pluripotent stem cell neuronal differentiation. We compare several methods for forebrain cortical neuronal differentiation by assessing cell morphology, immunostaining and gene expression. We evaluate embryoid aggregate vs. monolayer with dual SMAD inhibition differentiation protocols, manual vs. AggreWell aggregate formation, plating substrates, neural progenitor cell (NPC) isolation methods, NPC maintenance and expansion, and astrocyte co-culture. The embryoid aggregate protocol, using a Matrigel substrate, consistently generates a high yield and purity of neurons. NPC isolation by manual selection, enzymatic rosette selection, or FACS all are efficient, but exhibit some differences in resulting cell populations. Expansion of NPCs as neural aggregates yields higher cell purity than expansion in a monolayer. Finally, co-culture of iPSC-derived neurons with astrocytes increases neuronal maturity by day 40. This study directly compares commonly employed methods for neuronal differentiation of iPSCs, and can be used as a resource for choosing between various differentiation protocols

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    Excel file with all data from "Comparison and Optimization of hiPSC Forebrain Cortical Differentiation Protocols"

    Comparison of Plating Substrates.

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    <p>Aggregates were plated on either Matrigel or poly-o/laminin (POL) coated plates at days 7 or 24. A, B) Aggregates plated at day 7 (D7) and imaged at day 10 (D10) on Matrigel (A) formed typical neuroepithelial structures, while aggregates plates on POL (B) failed to adhere after two days. C, D) Aggregates were plated on either Matrigel or POL coated plates for final differentiation on day 24 (D24) and imaged at day 40 (D40). Aggregates plated on Matrigel (C) exhibited an increased density of processes, while aggregates plates on POL (D) displayed increased cell body migration from the plated aggregate. E, F) Neural aggregates were dissociated at day 24 and plated on either Matrigel (E) or POL (F). G) Aggregates were plated on either Matrigel (top row) or POL (bottom row) at day 24 and allowed to mature until day 40, followed by immunostaining and confocal microscopy for neuronal markers. Scale bars = 100 µm. Representative images are shown. H) qPCR was performed using RNA harvested from day 40 cultures. Data normalized to <i>GAPDH</i> expression. Matrigel n = 10, POL n = 10. I) Aggregates were single-cell dissociated and plated on either Matrigel (top row) or POL (bottom row) at day 24 and allowed to mature until day 40, followed by immunostaining and confocal microscopy for neuronal markers. Scale bars = 100 µm. Representative images are shown. J) qPCR was performed using RNA harvested from day 40 cultures. Data normalized to <i>GAPDH</i> expression. Matrigel n = 22, POL n = 22. For H and I, significance determined by student’s t-test: **, p<0.01; ***, p<0.001. Data are represented as mean ± SEM.</p

    Comparison of Embryoid Body Formation.

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    <p>A, B) Embryoid bodies were either formed by dissociating iPSCs (using dispase and trituration) or by AggreWell plate technology, followed by culture in non-adherent flasks. B) Quantification of aggregate size from manually-formed or 3,000- or 8,000-cell aggregates. Mean diameter for manually formed aggregates = 118.3 µm; mean diameter for 3,000 cells/aggregate = 183.1 µm; mean diameter for 8,000 cells/aggregate = 195.2 µm. Scale bars = 200 µm. Data are represented as mean ± SEM, from 4 independent differentiations, n = 21–43. Significance determined by one-way ANOVA with a Tukey’s post-test: ***, p<0.0001. F-tests between groups showed significantly different variances, with p<0.05 between manual vs. 3,000 cells/aggregate and manual vs. 8,000 cells/aggregate. C) Immunostaining of day 40 (D40) neurons, following differentiation using either manual formation or AggreWell plates. TOPRO, nuclear marker. Scale bars = 100 µm. Representative images are shown. D) qPCR was performed using RNA harvested from day 40 cultures. Data normalized to <i>GAPDH</i> expression. Manual n = 10, AggreWell n = 10. Data are represented as mean ± SEM. Significance was determined by student's t-test: ***, p<0.0001.</p

    Number of iPSC lines, differentiations and well numbers contributing to each figure.

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    <p>*10/10 differentiations without dissociation failed. 3/5 differentiations with dissociation yielded MAP2+ cells.</p><p>Number of iPSC lines, differentiations and well numbers contributing to each figure.</p
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