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Liquid biopsy approaches offer a promising technology for early and minimally invasive cancer detection. Tumor-educated platelets (TEPs) have emerged as a promising liquid biopsy biosource for the detection of various cancer types. In this study, we processed and analyzed the TEPs collected from 466 Non-small Cell Lung Carcinoma (NSCLC) patients and 410 asymptomatic individuals (controls) using the previously established thromboSeq protocol. We developed a novel particle-swarm optimization machine learning algorithm which enabled the selection of an 881 RNA biomarker panel (AUC 0.88). Herein we propose and validate in an independent cohort of samples (n = 558) two approaches for blood samples testing: one with high sensitivity (95% NSCLC detected) and another with high specificity (94% controls detected). Our data explain how TEP-derived spliced RNAs may serve as a biomarker for minimally-invasive clinical blood tests, complement existing imaging tests, and assist the detection and management of lung cancer patients.

Resumo: Introdução: O diagnóstico de glioblastoma continua a ser associado a um prognóstico reservado. Os sinais e sintomas de fim de vida destas pessoas diferem da restante população oncológica. Objetivo: Identificar os principais sinais e sintomas presentes nos últimos sete dias de vida do doente com glioblastoma num serviço de neurologia oncológica. Métodos: Estudo descritivo e retrospetivo. A amostra inclui pessoas com diagnóstico de glioblastoma com registo médico e de enfermagem nos últimos sete dias de vida, internados no serviço de Neurologia e admitidos na instituição pela consulta de neuro-oncologia entre 2019/2020. A colheita de dados foi realizada através da análise dos processos. Resultados: A amostra é composta por 17 pessoas. Os principais sinais e sintomas presentes nos últimos sete dias de vida foram: “diminuição do nível de consciência” (94%); “acontecimentos raros e inesperados” (94%); “disfunção respiratória” (88%) e “perda da capacidade de engolir” (76%). Conclusões: O estudo realizado permitiu dar resposta ao objetivo definido. Contudo, considera-se importante a realização de estudos nesta população com amostras mais representativas, uma vez que a maioria da literatura se encontra centrada na população oncológica em geral.

Introdução: O diagnóstico de glioblastoma continua a associado a um prognóstico reservado. Os sinais e sintomas de fim de vida destas pessoas diferem da restante população oncológica. Objetivo: Identificar os principais sinais e sintomas presentes nos últimos sete dias de vida do doente com glioblastoma num serviço de neurologia oncológica. Métodos: Estudo descritivo e retrospectivo. A amostra inclui pessoas com diagnóstico de glioblastoma com registo médico e de enfermagem nos últimos sete dias de vida, internados no serviço de Neurologia e admitidos na instituição pela consulta de neuro-oncologia entre 2019/2020. A colheita de dados foi realizada através da análise dos processos. Resultados: A amostra é composta por 17 pessoas. Os principais sinais e sintomas presentes nos últimos sete dias de vida foram: “diminuição do nível de consciência” (94%); “acontecimentos raros e inesperados” (94%); “disfunção respiratória” (88%) e “perda da capacidade de engolir” (76%). Conclusões: O estudo realizado permitiu dar resposta ao objetivo definido. Contudo, considera-se importante a realização de estudos nesta população com amostras mais representativas, uma vez que a maioria da literatura se encontra centrada na população oncológica em geral., Onco.News, N.º 46 (2023): Revista Onco.News

Lesbian, gay, bisexual, trans and intersex (LGBTI) people are more likely to be exposed to domestic violence than the rest of the population. Using a descriptive qualitative methodology, 28 professionals from the educational sector, aged between 28 and 64 years old (M = 44.5), were interviewed to describe and understand their perspectives on the sector’s ability to support, intervene and get involved with LGBTI people and, particularly, with victims or former victims of domestic violence. Through a thematic content analysis, three main themes emerged: (i) life trajectories of LGBTI people; (ii) domestic violence perpetrated against LGBTI people; and (iii) training of the educational sector to intervene with LGBTI people. The results show that Portuguese education professionals are not trained to recognize and intervene with LGBTI people and, in particular, with those who are victims of domestic violence, since they are unaware of the existence of protocols and/or guidelines for detecting and preventing risk situations among students. Furthermore, the curricular plan fails in the coverage of domestic violence and LGBTI-related topics, although the National Strategy for Citizenship Education has been implemented in Portugal since 2017. Findings suggest the need to invest in education professionals’ training. The authors declare that this study is part of a greater research project entitled ÍRIS which was co-funded by Programa Operational para a Inclusão Social e Emprego [Operational Program for Social Inclusion and Employment] (POISE), with the following funding number: POISE-03-4436-FSE-000943. info:eu-repo/semantics/publishedVersion

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms24054881/s1., Despite the diversity of liquid biopsy transcriptomic repertoire, numerous studies often exploit only a single RNA type signature for diagnostic biomarker potential. This frequently results in insufficient sensitivity and specificity necessary to reach diagnostic utility. Combinatorial biomarker approaches may offer a more reliable diagnosis. Here, we investigated the synergistic contributions of circRNA and mRNA signatures derived from blood platelets as biomarkers for lung cancer detection. We developed a comprehensive bioinformatics pipeline permitting an analysis of platelet- circRNA and mRNA derived from non-cancer individuals and lung cancer patients. An optimal selected signature is then used to generate the predictive classification model using machine learning algorithm. Using an individual signature of 21 circRNA and 28 mRNA, the predictive models reached an area under the curve (AUC) of 0.88 and 0.81, respectively. Importantly, combinatorial analysis including both types of RNAs resulted in an 8-target signature (6 mRNA and 2 circRNA), enhancing the differentiation of lung cancer from controls (AUC of 0.92). Additionally, we identified five biomarkers potentially specific for early-stage detection of lung cancer. Our proof-of-concept study presents the first multi-analyte-based approach for the analysis of platelets-derived biomarkers, providing a potential combinatorial diagnostic signature for lung cancer detection., European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie 765492.

Medicina Interna, Vol. 29 N.º 4 (2022): Outubro/Dezembro