Carolina Pereira de Souza Melo

Introdução: A Leucemia Mieloide Aguda (LMA) é uma neoplasia hematológica com alta mortalidade precoce. Devido à sua heterogeneidade genética, a caracterização molecular é essencial para o prognóstico e o direcionamento terapêutico. O Sequenciamento de Nova Geração (NGS) tem se mostrado fundamental identificando mutações clinicamente relevantes não detectadas por métodos convencionais. Objetivo: O presente estudo avalia o perfil genético de pacientes com LMA antes do tratamento quimioterápico, buscando variantes com potencial impacto prognóstico e terapêutico. Metodologia: DNA foi obtido de amostras ao diagnóstico de medula óssea de pacientes com LMA utilizando-se o kit EZ1&2 DNA Blood 350 µL Kit (48) (Qiagen). As bibliotecas foram preparadas com o painel CMYS_B_v1 (35 genes) da SOPHiA Genetics e sequenciadas na plataforma MiniSeq (Illumina™). As sequências foram processadas na plataforma SOPHiA DDM™. O efeito funcional e a acionabilidade clínica das variantes foram determinados por meio do VEP (Ensembl) e do OncoPortal™, respectivamente. Consideraram-se variantes com cobertura >30x e fração alélica >4%. O estudo foi aprovado pelo Comitê de Ética em Pesquisa (CAAE: 79433324.0.0000.5121). Resultados: A análise molecular dos cinco pacientes sequenciados até o momento revelou um perfil genético heterogêneo. A maior parte (85,20%) das variantes detectadas foi classificada como benigna ou provavelmente benigna. 6,73% (n=15) das variantes foram consideradas clinicamente significativas (patogênicas ou provavelmente patogênicas). Dessas, seis possuem implicações clínicas conhecidas: TP53:p.P72R (Todos os pacientes), TP53:p.G317* (LMA03) e ASXL1:p.G669Wfs*2 (LMA05) associadas à resistência quimioterápica; NPM1:p.W290Rfs*10 (LMA02), que confere um prognóstico favorável na ausência de FLT3-ITD; IDH1:p.R132C (LMA05) e BRAF:p.V600E (LMA01), que representam alvos diretos para inibidores específicos (ivosidenibe e dabrafenibe, respectivamente); e DNMT3A:p.V882H (LMA02), que pode ser um potencial alvo de inibidores de metiltransferases. Estes marcadores são essenciais para a estratificação de risco segundo as diretrizes da European Leukemia Net (ELN), subsidiando decisões clínicas futuras. Conclusão: A devolutiva estruturada dos perfis genéticos viabiliza a farmacogenética no SUS, otimizando a seleção de terapias-alvo e a assertividade clínica, reduzindo a toxicidade inerente a tratamentos não indicados.

O câncer de mama triplo-negativo (CMTN) é um subtipo agressivo de câncer, caracterizado pela ausência de expressão de receptores de estrógeno, progesterona e HER2, limitando suas opções terapêuticas. O gene repressor transcricional da família spen (SPEN) é considerado um supressor tumoral, participando de vias fundamentais de controle do ciclo celular, como a via Notch e a via de sinalização do estrogênio, na qual atua como modulador negativo deste hormônio por meio da repressão do receptor de estrogênio α (ERα). Ambas as vias estão envolvidas na proliferação e diferenciação celular, fatores importantes para estudos de processos de oncogênese. Estudos mostram que mutações de perda de função do gene SPEN podem estar associadas a uma disfunção no controle do ciclo celular, levando ao início de processos patológicos. Por esta razão, este estudo investigou a hipótese de uma possível associação entre mutações no gene SPEN e a progressão e a ocorrência de metástase no CMTN.

Background: This study aimed to evaluate the association between genetic variants and haplotypes of ERAP1 and clinical outcomes in cervical cancer patients, utilizing data from the TCGA‐CESC and a cohort of Brazilian patients. Methods: ERAP1 variants and haplotypes were evaluated in two distinct cohorts: whole‐exome sequencing (WES) data from 173 cervical cancer cases in the TCGA‐CESC dataset, and Sanger sequencing data from 52 Brazilian cervical cancer patients. The TCGA‐CESC data were employed for in silico analysis to identify significant ERAP1 variants and haplotypes, which were subsequently evaluated in Brazilian cervical cancer samples. The Tumor IMmune Estimation Resource (TIMER) tool was used to assess the association between ERAP1 expression and immune cell infiltration. Results: Haplotype analysis of ERAP1 in the TCGA‐CESC dataset revealed that H005 (rs26653—rs2287987—rs30187—rs10050860—rs17482078—rs27044) and H023 (rs26653—rs27895—rs30187—rs27044) haplotypes were significantly associated with poorer survival outcomes. Homozygosity for H005 and the presence of H023 were strongly associated with both overall survival (OS) (HR = 9.591, p = 0.00384; HR = 10.183, p = 0.02862, respectively) and disease‐specific survival (DSS) (HR = 12.851, p = 0.00162; HR = 15.183, p = 0.01191, respectively). TCGA‐CESC data showed that homozygosity for rs2287987 (p.Met349Val) was associated with an increased risk of death in both overall survival (OS) (HR = 11.043, p = 0.00376) and disease‐specific survival (DSS) (HR = 13.833, p = 0.00255), whereas rs30187 (p.Lys528Arg) demonstrated a protective effect for DSS, reducing mortality risk in both heterozygous (HR = 0.374, p = 0.04055) and homozygous (HR = 0.346, p = 0.03845) forms. However, although these variants were individually associated with survival outcomes in the dataset, this association was not retained in the multivariate analysis, suggesting that these variants may not have an independent prognostic effect. Similarly, no associations were found for these variants in the Brazilian cervical cancer cohort, suggesting that the impact of these variants on the prognosis of cervical cancer patients may be primarily influenced by the combination of variants. Furthermore, ERAP1 expression levels were positively correlated with CD8 ⁺ T cell infiltration (correlation coefficient = 0.264, p = 0.00000960), which was associated with improved survival outcomes (HR = 0.006, p = 0.049). Conclusion: ERAP1 haplotype H005 homozygosity and the presence of H023 were linked to poorer prognosis, indicating their potential as prognostic biomarkers in cervical cancer patients. Individually, the rs2287987 variant showed a potential association with worse outcomes in the TCGA dataset; however, this finding was not replicated among Brazilian patients, suggesting the potential role of these variants when considered as haplotypes in the function of ERAP1 . Additionally, the protective role of CD8+ T cell infiltration highlights its relevance as a possible therapeutic target for improving survival in cervical cancer patients.

Introduction: Cervical cancer (CC) is one of the most common types of cancer in women and is closely associated with persistent infection by oncogenic types of the human papillomavirus (HPV). The World Health Organization (WHO) aims to eradicate CC as a public health problem by 2100. However, challenges such as vaccination limitations and the spread of misinformation hinder vaccine uptake, despite its proven efficacy (1). The prognosis of CC depends on the stage of the disease and becomes more unfavorable in advanced stages. Therefore, the search for effective biomarkers for diagnosis and monitoring is essential to improve early detection and treatment follow-up. Objectives: This study aimed to explore the role of long non-coding RNAs (lncRNAs) in CC, focusing on identifying and characterizing relevant lncRNAs, understanding their regulatory mechanisms and molecular interactions, and analyzing their expression patterns in patients with different responses to chemoradiotherapy. Methods: A retrospective observational study was conducted, analyzing RNA samples from 31 patients treated at the Mário Penna Institute (2017-2019) (2). The expression of lncRNAs was analyzed by RNA-seq, and molecular interactions were investigated using bioinformatics tools such as AnnoLnc2 and ClusterProfiler. Decision tree analyses and Kaplan-Meier survival curves were performed to assess the association between lncRNAs and clinical outcomes. Results: Among the 417 differentially expressed lncRNAs identified, three stood out: ENSG00000267838, ENSG00000266340, and FRMD6-AS1. High expression of ENSG00000267838 and ENSG00000266340 correlated with treatment resistance and a worse prognosis, while their low expression indicated a better therapeutic response. Kaplan-Meier analysis showed that high expression of these lncRNAs was associated with shorter progression-free survival. The decision tree model demonstrated high accuracy (87.09%) in distinguishing between responder and non-responder patients. Conclusions: Three lncRNAs, ENSG00000267838, ENSG00000266340, and FRMD6-AS1, were identified as being positively associated with non-response to chemoradiotherapy and poorer progression-free survival in CC patients. Specifically, the upregulation of lncRNA ENSG00000267838 was linked to treatment resistance, while its downregulation was associated with a favorable response to chemoradiotherapy.

Introdução O câncer de mama (CM) é o tipo de câncer mais prevalente entre mulheres em todo o mundo1. Globalmente, o CM foi responsável por cerca de 685 mil óbitos em 20202. No Brasil, estima-se cerca de 74 mil novos casos anuais de CM para o triênio 2023-2025, com uma taxa de mortalidade de 16,4%3. O CM representa uma alta carga de morbidade e mortalidade, com desafios como detecção tardia, barreiras socioeconômicas e baixa conscientização sobre a doença1. Neste contexto, estratégias baseadas em medicina personalizada (MP) poderão superar os desafios do manejo dessas pacientes. Objetivo Identificar variantes genômicas relacionadas à via de sinalização MAPK em uma coorte de pacientes com câncer de mama atendidas no Hospital Luxemburgo (HL). Métodos Alvos da via de sinalização MAPK1, presente no sequenciamento de 35 pacientes com CM obtido usando o QIAseq Multimodal Pan-Cancer Panel (Qiagen), foram selecionados no STRING DATABASE (anotação HSA-5684996 - intervalo de confiança ≥ 0.9). A chamada de variantes foi feita com o software QIAGEN CLC Genomics Workbench 23. Posteriormente, essas variantes foram classificadas no ClinVar para identificação de variantes associadas às vias canônicas e anotação de patogenicidade. Além disso, a associação da sobrevida das pacientes com CM e esse gene foi realizada no Kaplan-Meier Plotter (KMplot). Resultados Foram identificados 283 genes na via MAKP1. Scripts eliminaram duplicatas e definiram os genes comuns no Multimodal Panel, reduzindo a 55 genes. A chamada de variantes revelou 9.400 variantes nos 55 genes avaliados. Dos quais 11 genes foram predominantemente mutados. O IRS1 se destacou com o maior número de variantes identificadas (418), sendo: 1 provavelmente patogênica, 5 de significância incerta e 406 não reportadas. A análise no Kmplot mostrou que IRS1 mutado está associado a baixa sobrevida das pacientes com CM [HR 3,6 (1,14-11,33) p= 0,019]. Conclusão Esses resultados refletem uma elevada carga de alterações genéticas em genes-chave da via MAPK, frequentemente associados à progressão tumoral e resistência terapêutica. A classificação dessas variantes e sua relação com os desfechos clínicos das pacientes contribuirá para o entendimento das bases moleculares da CM e podem auxiliar na identificação de biomarcadores em prol da MP.

Background/Objectives: Most studies investigating prognostic biomarkers in cervical cancer (CC) analyze patients irrespective of FIGO stage, potentially masking molecular features that underlie the aggressiveness of some FIGO II tumors. To address this, we investigated differential gene expression in a FIGO II CC cohort to identify a gene signature predictive of progression-free survival (PFS) within five years of treatment initiation. Methods: Tumor samples from 15 CC patients were analyzed using RNA sequencing, bioinformatics, and machine learning to identify differentially expressed genes (DEGs) associated with prognosis. Findings were validated in an independent CC cohort (n = 174). Results: High expression of B3GALT1 (HR = 5.11), GTF3C2-AS1 (HR = 18.73), and ZKSCAN4 (HR = 5.18) was significantly associated with an increased risk of recurrence in our cohort. Elevated expression of these transcripts is also associated with shorter PFS in the external dataset. Notably, GTF3C2-AS1 expression alone was sufficient to classify all fifteen patients into their respective prognostic groups using a decision tree model, achieving 93.3% accuracy in leave-one-out cross-validation (LOOCV). Additional candidates, including RCAN2-DT, MYH9-DT, IGKC, IGHG1, and IGHG3, were associated with PFS in our cohort but could not be externally validated due to a lack of available data. Conclusions: Transcriptomic profiling revealed potential biomarkers that refine prognostic stratification in cervical cancer beyond FIGO staging. Among them, GTF3C2-AS1 consistently emerged as a potential predictor of recurrence risk. Additional candidates, including B3GALT1, ZKSCAN4, and immunoglobulin transcripts, provided complementary insights but require further validation. These preliminary results highlight intra-stage heterogeneity in FIGO II CC and underscore the promise of molecular markers to improve risk assessment.

Cervical cancer (CC) is a global public health concern, primarily caused by persistent infection with oncogenic types of human papillomavirus (HPV). The World Health Organization (WHO) has established a plan to eliminate CC as a public health issue by the year 2100. However, the implementation of the HPV vaccine is impeded by vaccine restrictions and misinformation despite its demonstrated effectiveness. The CC treatment is influenced by the disease stage, with an unfavorable prognosis for those in advanced stages. This study aimed to investigate the potential of long non-coding RNAs (lncRNAs) in CC by identifying and characterizing related lncRNAs, elucidating their regulatory mechanisms and molecular interactions, and analyzing their expression patterns in patients with diverse responses to chemoradiotherapy. Non-stem cells from CC were isolated using flow cytometry sorting and used for total RNA extraction. The RNA was used to build libraries that were subsequently sequenced using the Illumina Nextseq 550.417 lncRNAs that showed differentially expressed between CC patients who responded or not to treatment. Further analysis demonstrated that these lncRNAs significantly interact with several molecules, which play crucial roles in CC progression and therapeutic resistance. Statistical analysis correlated the expression profile of these lncRNAs with treatment efficacy. Three lncRNAs, ENSG00000267838, ENSG00000266340, and FRMD6-AS1, were identified with positive expression related to non-response to chemoradiotherapy and worse progression-free survival in CC patients. Specifically, lncRNA ENSG00000267838 has its up-regulation related to non-response and down-regulation to response to chemoradiotherapy treatment.

High-grade serous ovarian cancer (HGSOC) low overall survival rate is often attributed to platinum resistance. Recent studies suggest that the tumor associated-microenvironment (TME) is a determining factor in malignant tumor progression and DNA damage plays a crucial role in this process. Here, we sought to identify platinum resistance biomarkers associating the TME immune profile and the mutational landscape of the homologous repair pathway genes with the HGSOC patients prognosis and response to chemotherapy. Using a decision tree classifier approach, we found that platinum resistant (PR) patients were characterized by the presence of a novel deep intronic variant, the CHEK2 c.319+ 3943A > T, and higher L1 expression (p = 0.016), (100% accuracy). Chek2 protein is an important component of DNA repair and L1, also known as calprotectin, is one component of the neutrophil extracellular traps (NETs) during inflammation, previously suggested as a key contributor to the metastatic process in HGSOC. Also, PD-L2 levels were significantly higher in PR patients positive for this CHEK2 variant (p = 0.048), underscoring the need to explore its potential therapeutic role for this cancer. Our results suggest an interplay between TME and DNA repair variants that results in a multifactorial nature of HGSOC resistance to platinum chemotherapy.

Cervical cancer remains the leading cause of cancer death in 36 countries, and high-risk human papillomavirus types are responsible for most cases. Identifying strategies to make treatment more targeted and effective has become a priority. This study aims to validate a set of differentially expressed genes previously identified in cervical cancer stem cells as predictive biomarkers for response to chemoradiotherapy using minimally invasive samples. Additionally, it aims to elucidate the relationship between high-risk human papillomavirus infection and cervical cancer patients’ response to treatment. Gene expression for three differentially expressed genes (COPZ1, ILF2, and SNX2) was evaluated from 20 cervical cancer patients’ cervical cytology brushes. Unmapped reads from the same transcriptome were used to evaluate the presence of human papillomavirus in tumor tissue through qualitative screening of 13 high-risk human papillomavirus types. Our study did not clarify the relationship between high-risk human papillomavirus infection and the treatment response. However, we found downregulation of COPZ1 in patients who responded to treatment compared to non-responders, and ILF2 in patients with more advanced tumor stages. This suggests that COPZ1 and ILF2 expressions are potential cervical cancer prognostic biomarkers that can be assessed using samples commonly used in clinical practice.

In Brief Queiroz et al. showed that the application of cluster methodology for classifying gastric cancer is suitable and efficient within a Brazilian cohort, which is known for its population heterogeneity. The study highlighted the potential utilization of this method within public health services due to its low-cost, presenting a viable means to improve the diagnosis and prognosis of gastric cancer. Highlights Our Brazilian cohort with gastric cancer has a distinct distribution between mutated and normal p53. New genetic