45 research outputs found

    Genes Affecting the Repair and Survival of Escherichia coli Following Psoralen-Induced Damage: a DNA Interstrand Crosslinking Agent

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    Photoactivated psoralens and other agents that form DNA interstrand crosslinks are highly cytotoxic and are useful in treating a range of diseases, including vitiligo, psoriasis, and some forms of cancer. Unlike many lesions that damage only one strand of the duplex DNA, DNA interstrand crosslinks form covalent bonds with both strands. Thus, repairing these lesions is complicated both by the lack of an undamaged strand to serve as a template for resynthesis following excision, as well as the potential to form double strand breaks if both strands are incised. A number of models have proposed that repair is likely to couple nucleotide excision repair with other repair pathways such as recombination, and/or translesion synthesis. However, several aspects of these models remain speculative, and how these medically relevant lesions are repaired by cells still remains elusive. In this study, I use Escherichia coli as a model organism to characterize which gene products contribute to survival in the presence of psoralen-induced DNA interstrand crosslinks. In Chapter II, I demonstrate that although nucleotide excision repair initiates repair, not all subunits contribute equally to survival. Notably, uvrC is less sensitive to psoralen-induced damage than either uvrA or uvrB. I found that Cho, an alternative endonuclease, accounts for the increased resistance of uvrC mutants and contributes to survival in the presence of UvrABC. Cho was not required following angelicin treatment, a psoralen derivative that only forms monoadducts, suggesting that Cho function is specific for interstrand crosslink repair. However, Cho, by itself, is not required for the initial incision and only modestly enhances the rate that psoralen crosslinks are incised in vivo. Following incision, many of the intermediates in the repair process remain speculative. In Chapter III, I examine how recombination and translesion synthesis mutants contribute to survival of psoralen-induced damage. I show that both recBC and recF contribute to survival, but that neither mutant is as hypersensitive as recA, potentially suggesting that pathways involving either single strand gaps or double strand break intermediates can occur during repair. Finally, I show that Polymerase V is responsible for the translesion synthesis that contributes to survival in the case of psoralen-induced damage in E.coli

    Pitfalls in machine learning‐based assessment of tumor‐infiltrating lymphocytes in breast cancer: a report of the international immuno‐oncology biomarker working group

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    The clinical significance of the tumor-immune interaction in breast cancer (BC) has been well established, and tumor-infiltrating lymphocytes (TILs) have emerged as a predictive and prognostic biomarker for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2 negative) breast cancer (TNBC) and HER2-positive breast cancer. How computational assessment of TILs can complement manual TIL-assessment in trial- and daily practices is currently debated and still unclear. Recent efforts to use machine learning (ML) for the automated evaluation of TILs show promising results. We review state-of-the-art approaches and identify pitfalls and challenges by studying the root cause of ML discordances in comparison to manual TILs quantification. We categorize our findings into four main topics; (i) technical slide issues, (ii) ML and image analysis aspects, (iii) data challenges, and (iv) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns, or design choices in the computational implementation. To aid the adoption of ML in TILs assessment, we provide an in-depth discussion of ML and image analysis including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial- and routine clinical management of patients with TNBC

    Elective cancer surgery in COVID-19-free surgical pathways during the SARS-CoV-2 pandemic: An international, multicenter, comparative cohort study

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    PURPOSE As cancer surgery restarts after the first COVID-19 wave, health care providers urgently require data to determine where elective surgery is best performed. This study aimed to determine whether COVID-19–free surgical pathways were associated with lower postoperative pulmonary complication rates compared with hospitals with no defined pathway. PATIENTS AND METHODS This international, multicenter cohort study included patients who underwent elective surgery for 10 solid cancer types without preoperative suspicion of SARS-CoV-2. Participating hospitals included patients from local emergence of SARS-CoV-2 until April 19, 2020. At the time of surgery, hospitals were defined as having a COVID-19–free surgical pathway (complete segregation of the operating theater, critical care, and inpatient ward areas) or no defined pathway (incomplete or no segregation, areas shared with patients with COVID-19). The primary outcome was 30-day postoperative pulmonary complications (pneumonia, acute respiratory distress syndrome, unexpected ventilation). RESULTS Of 9,171 patients from 447 hospitals in 55 countries, 2,481 were operated on in COVID-19–free surgical pathways. Patients who underwent surgery within COVID-19–free surgical pathways were younger with fewer comorbidities than those in hospitals with no defined pathway but with similar proportions of major surgery. After adjustment, pulmonary complication rates were lower with COVID-19–free surgical pathways (2.2% v 4.9%; adjusted odds ratio [aOR], 0.62; 95% CI, 0.44 to 0.86). This was consistent in sensitivity analyses for low-risk patients (American Society of Anesthesiologists grade 1/2), propensity score–matched models, and patients with negative SARS-CoV-2 preoperative tests. The postoperative SARS-CoV-2 infection rate was also lower in COVID-19–free surgical pathways (2.1% v 3.6%; aOR, 0.53; 95% CI, 0.36 to 0.76). CONCLUSION Within available resources, dedicated COVID-19–free surgical pathways should be established to provide safe elective cancer surgery during current and before future SARS-CoV-2 outbreaks

    Elective Cancer Surgery in COVID-19-Free Surgical Pathways During the SARS-CoV-2 Pandemic: An International, Multicenter, Comparative Cohort Study.

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    PURPOSE: As cancer surgery restarts after the first COVID-19 wave, health care providers urgently require data to determine where elective surgery is best performed. This study aimed to determine whether COVID-19-free surgical pathways were associated with lower postoperative pulmonary complication rates compared with hospitals with no defined pathway. PATIENTS AND METHODS: This international, multicenter cohort study included patients who underwent elective surgery for 10 solid cancer types without preoperative suspicion of SARS-CoV-2. Participating hospitals included patients from local emergence of SARS-CoV-2 until April 19, 2020. At the time of surgery, hospitals were defined as having a COVID-19-free surgical pathway (complete segregation of the operating theater, critical care, and inpatient ward areas) or no defined pathway (incomplete or no segregation, areas shared with patients with COVID-19). The primary outcome was 30-day postoperative pulmonary complications (pneumonia, acute respiratory distress syndrome, unexpected ventilation). RESULTS: Of 9,171 patients from 447 hospitals in 55 countries, 2,481 were operated on in COVID-19-free surgical pathways. Patients who underwent surgery within COVID-19-free surgical pathways were younger with fewer comorbidities than those in hospitals with no defined pathway but with similar proportions of major surgery. After adjustment, pulmonary complication rates were lower with COVID-19-free surgical pathways (2.2% v 4.9%; adjusted odds ratio [aOR], 0.62; 95% CI, 0.44 to 0.86). This was consistent in sensitivity analyses for low-risk patients (American Society of Anesthesiologists grade 1/2), propensity score-matched models, and patients with negative SARS-CoV-2 preoperative tests. The postoperative SARS-CoV-2 infection rate was also lower in COVID-19-free surgical pathways (2.1% v 3.6%; aOR, 0.53; 95% CI, 0.36 to 0.76). CONCLUSION: Within available resources, dedicated COVID-19-free surgical pathways should be established to provide safe elective cancer surgery during current and before future SARS-CoV-2 outbreaks

    Spatial analyses of immune cell infiltration in cancer : current methods and future directions. A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer

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    Modern histologic imaging platforms coupled with machine learning methods have provided new opportunities to map the spatial distribution of immune cells in the tumor microenvironment. However, there exists no standardized method for describing or analyzing spatial immune cell data, and most reported spatial analyses are rudimentary. In this review, we provide an overview of two approaches for reporting and analyzing spatial data (raster versus vector-based). We then provide a compendium of spatial immune cell metrics that have been reported in the literature, summarizing prognostic associations in the context of a variety of cancers. We conclude by discussing two well-described clinical biomarkers, the breast cancer stromal tumor infiltrating lymphocytes score and the colon cancer Immunoscore, and describe investigative opportunities to improve clinical utility of these spatial biomarkers. © 2023 The Pathological Society of Great Britain and Ireland.http://www.thejournalofpathology.com/hj2024ImmunologySDG-03:Good heatlh and well-bein

    Image-based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno-oncology Biomarker Working Group on Breast Cancer

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    Recent advances in the field of immuno-oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high-throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi-marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer

    Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer

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    The clinical significance of the tumor-immune interaction in breast cancer is now established, and tumor-infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2-negative) breast cancer and HER2-positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state-of-the-art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in-depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple-negative breast cancer

    Cho Endonuclease Functions During DNA Interstrand Crosslink Repair in \u3ci\u3eEscherichia coli\u3c/i\u3e

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    DNA interstrand crosslinks are complex lesions that covalently link both strands of the duplex DNA. Lesion removal is proposed to initiate via the UvrABC nucleotide excision repair complex, however less is known about the subsequent steps of this complex repair pathway. In this study, we characterized the contribution of nucleotide excision repair mutants to survival in the presence of psoralen-induced damage. Unexpectedly, we observed that the nucleotide excision repair mutants exhibit differential sensitivity to psoralen-induced damage, with uvrC mutants being less sensitive than either uvrA or uvrB. We show that Cho, an alternative endonuclease, acts with UvrAB and is responsible for the reduced hypersensitivity of uvrC mutants. We find that Cho\u27s contribution to survival correlates with the presence of DNA interstrand crosslinks, rather than monoadducts, and operates at a step after, or independent from, the initial incision during the global repair of psoralen DNA adducts from the genome

    Terbinafine in combination with other antifungal agents for treatment of resistant or refractory mycoses : investigating optimal dosing regimens using a physiologically based pharmacokinetic model

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    Terbinafine is increasingly used in combination with other antifungal agents to treat resistant or refractory mycoses due to synergistic in vitro antifungal activity; high doses are commonly used, but limited data are available on systemic exposure, and no assessment of pharmacodynamic target attainment has been made. Using a physiologically based pharmacokinetic (PBPK) model for terbinafine, this study aimed to predict total and unbound terbinafine concentrations in plasma with a range of high-dose regimens and also calculate predicted pharmacodynamic parameters for terbinafine. Predicted terbinafine concentrations accumulated significantly during the first 28 days of treatment; the area under the concentration-time curve (AUC)/MIC ratios and AUC for the free, unbound fraction (fAUC)/MIC ratios increased by 54 to 62% on day 7 of treatment and by 80 to 92% on day 28 compared to day 1, depending on the dose regimen. Of the high-dose regimens investigated, 500 mg of terbinafine taken every 12 h provided the highest systemic exposure; on day 7 of treatment, the predicted AUC, maximum concentration (Cmax), and minimum concentration (Cmin) were approximately 4-fold, 1.9-fold, and 4.4-fold higher than with a standard-dose regimen of 250 mg once daily. Close agreement was seen between the concentrations predicted by the PBPK model and the observed concentrations, indicating good predictive performance. This study provides the first report of predicted terbinafine exposure in plasma with a range of high-dose regimens.7 page(s
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