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

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

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

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.Gilead Breast Cancer Research Grant; Breast Cancer Research Foundation; Susan G Komen Leadership; Interne Fondsen KU Leuven/Internal Funds KU Leuven; Swedish Society for Medical Research; Swedish Breast Cancer Association; Cancer Research Program; US Department of Defense; Mayo Clinic Breast Cancer; Marie Sklodowska Curie; NHMRC; National Institutes of Health; Cancer Research UK; Japan Society for the Promotion of Science; Horizon 2020 European Union Research and Innovation Programme National Cancer Institute; National Heart, Lung and Blood Institute; National Institute of Biomedical Imaging and Bioengineering; VA Merit Review Award; US Department of Veterans Affairs Biomedical Laboratory Research Breast Cancer Research Program; Prostate Cancer Research Program; Lung Cancer Research Program; Kidney Precision Medicine Project (KPMP) Glue Grant; EPSRC; Melbourne Research Scholarship; Peter MacCallum Cancer Centre; KWF Kankerbestrijding; Dutch Ministry of Health, Welfare and Sport the Breast Cancer Research Foundation; Agence Nationale de la Recherche; Q-Life; National Breast Cancer Foundation of Australia; National Health and Medical Council of Australia; All-Island Cancer Research Institute; Irish Cancer Society; Science Foundation Ireland Investigator Programme; Science Foundation Ireland Strategic Partnership Programme. Open access funding provided by IReL.https://pathsocjournals.onlinelibrary.wiley.com/journal/10969896hj2024ImmunologySDG-03:Good heatlh and well-bein

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

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

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

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

A Taxonomy of DDoS Attack Mitigation Approaches Featured by SDN Technologies in IoT Scenarios

The Internet of Things (IoT) has attracted much attention from the Information and Communication Technology (ICT) community in recent years. One of the main reasons for this is the availability of techniques provided by this paradigm, such as environmental monitoring employing user data and everyday objects. The facilities provided by the IoT infrastructure allow the development of a wide range of new business models and applications (e.g., smart homes, smart cities, or e-health). However, there are still concerns over the security measures which need to be addressed to ensure a suitable deployment. Distributed Denial of Service (DDoS) attacks are among the most severe virtual threats at present and occur prominently in this scenario, which can be mainly owed to their ease of execution. In light of this, several research studies have been conducted to find new strategies as well as improve existing techniques and solutions. The use of emerging technologies such as those based on the Software-Defined Networking (SDN) paradigm has proved to be a promising alternative as a means of mitigating DDoS attacks. However, the high granularity that characterizes the IoT scenarios and the wide range of techniques explored during the DDoS attacks make the task of finding and implementing new solutions quite challenging. This problem is exacerbated by the lack of benchmarks that can assist developers when designing new solutions for mitigating DDoS attacks for increasingly complex IoT scenarios. To fill this knowledge gap, in this study we carry out an in-depth investigation of the state-of-the-art and create a taxonomy that describes and characterizes existing solutions and highlights their main limitations. Our taxonomy provides a comprehensive view of the reasons for the deployment of the solutions, and the scenario in which they operate. The results of this study demonstrate the main benefits and drawbacks of each solution set when applied to specific scenarios by examining current trends and future perspectives, for example, the adoption of emerging technologies based on Cloud and Edge (or Fog) Computing

Cytotoxicity of Extracts from <i>Petiveria alliacea</i> Leaves on Yeast

Petiveria alliacea L. is a plant used in traditional medicine harboring pharmacological properties with anti-inflammatory, antinociceptive, hypoglycemiant and anesthetic activities. This study assessed the potential cytotoxic, genotoxic and mutagenic effects of ethanolic extract of P. alliacea on Saccharomyces cerevisiae strains. S. cerevisiae FF18733 (wild type) and CD138 (ogg1) strains were exposed to fractioned ethanolic extracts of P. alliacea in different concentrations. Three experimental assays were performed: cellular inactivation, mutagenesis (canavanine resistance system) and loss of mitochondrial function (petites colonies). The chemical analyses revealed a rich extract with phenolic compounds such as protocatechuic acid, cinnamic and catechin epicatechin. A decreased cell viability in wild-type and ogg1 strains was demonstrated. All fractions of the extract exerted a mutagenic effect on the ogg1 strain. Only ethyl acetate and n-butanol fractions increased the rate of petites colonies in the ogg1 strain, but not in the wild-type strain. The results indicate that fractions of mid-polarity of the ethanolic extract, at the studied concentrations, can induce mutagenicity mediated by oxidative lesions in the mitochondrial and genomic genomes of the ogg1-deficient S. cerevisiae strain. These findings indicate that the lesions caused by the fractions of P. alliacea ethanolic extract can be mediated by reactive oxygen species and can reach multiple molecular targets to exert their toxicity

Characterization of Biocatalysts Prepared with Thermomyces lanuginosus Lipase and Different Silica Precursors, Dried using Aerogel and Xerogel Techniques

The use of lipases in industrial processes can result in products with high levels of purity and at the same time reduce pollutant generation and improve both selectivity and yields. In this work, lipase from Thermomyces lanuginosus was immobilized using two different techniques. The first involves the hydrolysis/polycondensation of a silica precursor (tetramethoxysilane (TMOS)) at neutral pH and ambient temperature, and the second one uses tetraethoxysilane (TEOS) as the silica precursor, involving the hydrolysis and polycondensation of the alkoxide in appropriate solvents. After immobilization, the enzymatic preparations were dried using the aerogel and xerogel techniques and then characterized in terms of their hydrolytic activities using a titrimetric method with olive oil and by the formation of 2-phenylethyl acetate in a transesterification reaction. The morphological properties of the materials were characterized using scanning electron microscopy, measurements of the surface area and pore size and volume, thermogravimetric analysis, and exploratory differential calorimetry. The results of the work indicate that the use of different silica precursors (TEOS or TMOS) and different drying techniques (aerogel or xerogel) can significantly affect the properties of the resulting biocatalyst. Drying with supercritical CO2 provided higher enzymatic activities and pore sizes and was therefore preferable to drying, using the xerogel technique. Thermogravimetric analysis and differential scanning calorimetry analyses revealed differences in behavior between the two biocatalyst preparations due to the compounds present

Doctors' awareness concerning primary immunodeficiencies in Brazil

Background: PIDs are a heterogeneous group of genetic illnesses, and delay in their diagnosis is thought to be caused by a lack of awareness among physicians concerning PIDs. the latter is what we aimed to evaluate in Brazil.Methods: Physicians working at general hospitals all over the country were asked to complete a 14-item questionnaire. One of the questions described 25 clinical situations that could be associated with PIDs and a score was created based on percentages of appropriate answers.Results: A total of 4026 physicians participated in the study: 1628 paediatricians (40.4%), 1436 clinicians (35.7%), and 962 surgeons (23.9%). About 67% of the physicians had learned about PIDs in medical school or residency training, 84.6% evaluated patients who frequently took antibiotics, but only 40.3% of them participated in the immunological evaluation of these patients. Seventy-seven percent of the participating physicians were not familiar with the warning signs for PIDs. the mean score of correct answers for the 25 clinical situations was 48.08% (+/- 16.06). Only 18.3% of the paediatricians, 7.4% of the clinicians, and 5.8% of the surgeons answered at least 2/3 of these situations appropriately.Conclusions: There is a lack of medical awareness concerning PIDs, even among paediatricians, who have been targeted with PID educational programmes in recent years in Brazil. An increase in awareness with regard to these disorders within the medical community is an important step towards improving recognition and treatment of PIDs. (C) 2014 SEICAP. Published by Elsevier Espana, S.L.U. All rights reserved.Jeffrey Modell FoundationBrazilian Jeffrey Modell CentreUniversidade Federal de São Paulo, São Paulo, BrazilUniv Fed Pernambuco, Recife, PE, BrazilUniv Hosp, Brasilia, DF, BrazilChildrens Hosp, Brasilia, DF, BrazilAlbert Sabin Childrens Hosp, Fortaleza, Ceara, BrazilUniv Estadual Montes Claros, Montes Claros, BrazilUniv Fed Parana, BR-80060000 Curitiba, Parana, BrazilUniv São Paulo, Fac Med Ribeirao Preto, BR-14049 Ribeirao Preto, BrazilFac Med Sao Jose Rio Preto, Sao Jose Do Rio Preto, BrazilUniv Hosp Sao Vicente Paulo, Passo Fundo, BrazilJoana Gusmao Childrens Hosp, Florianopolis, SC, BrazilUniv Hosp Muller, Fac Med, Cuiaba, BrazilUniv Fed Mato Grosso, Cuiaba, BrazilNipo Brasileiro Hosp, São Paulo, BrazilHosp lsraelita Albert Einstein, São Paulo, BrazilUniv Fed Rio Grande do Norte, Natal, RN, BrazilUniv Fed Uberlandia, BR-38400 Uberlandia, MG, BrazilUniv Fed Bahia, Complexo Hosp Univ Prof Edgar Santos, Salvador, BA, BrazilUniv Estadual Piaui, Teresina, BrazilABC, Fac Med, Santo Andre, BrazilUniv Fed Minas Gerais, Belo Horizonte, MG, BrazilUniv Ctr Para, Belem, Para, BrazilMed Course Lusiada Univ Ctr UNILUS, Dept Pediat, Santos, BrazilUniv Fed Sergipe, Aracaju, BrazilHosp Servidor Publ Municipal, São Paulo, BrazilUniv São Paulo, Inst Biomed Sci, BR-05508 São Paulo, BrazilUniv Estadual Campinas, Sch Med, Dept Pediat, Campinas, BrazilPrivate Off, Macapa, BrazilHosp Ministro Costa Cavalcanti, Foz Do Iguacu, BrazilChildrens Hosp Cosme & Damitio, Rondonia, BrazilUniv Fed Rio de Janeiro, Rio de Janeiro, BrazilUniversidade Federal de São Paulo, São Paulo, BrazilWeb of Scienc