Primary hepatic pleomorphic liposarcoma: Case report and literature review / Liposarcoma pleomorfo hepático primario: presentación de un caso y revisión bibliográfica

Primary hepatic liposarcoma is an extremely rare malignant tumour derived from adipocytes and is part of the group of mesenchymal tumours. We present the case of a 43-year-old Hispanic male patient with a pleomorphic hepatic liposarcoma and absence of MDM2 gene amplification. Two years and six months after surgery, the patient is asymptomatic. The present case is the first report of this entity with positive immunohistochemical testing for p16, p53, S100, vimentin and absence of MDM2 gene amplification. (AU)

El liposarcoma hepático primario es un tumor maligno extremadamente raro, derivado de adipocitos, y forma parte del grupo de tumores mesenquimales. Presentamos el caso de un paciente masculino de 43 años con diagnóstico de liposarcoma hepático pleomorfo con ausencia de amplificación del gen MDM2. Dos años y 6 meses después de la cirugía el paciente se encuentra asintomático. El presente caso es el primer informe de esta entidad con estudio inmunohistoquímico positivo para p16, p53, S100, vimentina y ausencia de amplificación del gen MDM2. (AU)

Tumor fibroso calcificante intestinal: reporte de caso / Intestinal calcifying fibrous tumor: case report

El tumor fibroso calcificante (TFC) es una inusual lesión benigna de origen mesenquimal que puede presentar características similares a otros tumores más comunes. El caso involucra a una mujer de 36 años con un tumor en el yeyuno proximal, inicialmente sospechoso de ser un tumor del estroma gastrointestinal (GIST). Se realiza una resección quirúrgica, revelando un nódulo bien delimitado en el borde antimesentérico con características microscópicas típicas de TFC. Las células tumorales presentaban positividad para CD34 y negatividad para demás marcadores, diferenciándolo de otras neoplasias. El TFC puede confundirse con tumores más comunes debido a su apariencia, pero un diagnóstico preciso respaldado por inmunohistoquímica es esencial. La extirpación quirúrgica completa suele ser curativa. (AU)

Calcifying fibrous tumor (CFT) is a rare benign lesion of mesenchymal origin that may present similar characteristics to other more common tumors. We present the case of a 36-year-old woman with a tumor in the proximal jejunum, initially suspected to be a gastrointestinal stromal tumor (GIST). Surgical resection was performed, revealing a well-demarcated nodule at the anti-mesenteric border with microscopic features typical of a calcifying fibrous tumor. The tumor cells were positive for CD34 and negative for other markers, differentiating it from other neoplasms. Calcifying fibrous tumors can be confused with more common tumors because of its appearance, but an accurate diagnosis supported by immunohistochemistry is essential. Complete surgical excision is usually curative. (AU)

INCA DE PORTAS ABERTAS 2023: Enfermagem, Fisioterapia e Nutricionista

O INCA de Portas Abertas irá apresentar o Instituto, a atuação de profissionais de diferentes áreas do INCA e de seus alunos dos cursos técnicos, programas de residência, mestrado e doutorado, divulgando relevantes informações sobre saúde e oncologia para profissionais e estudantes que possuem interesse nos programas de ensino da instituição.

Controle do Câncer no Estado de São Paulo (ConeCta-SP)

É uma instituição pública vinculada à Secretaria da Saúde do Governo do Estado de São Paulo, com a proposta de incentivar a pesquisa, o ensino e a assistência em oncologia, estimulando as atividades de prevenção e detecção precoce do câncer.

Decoding long non­coding RNAs: Friends and foes in cancer development (Review).

Cancer remains a formidable adversary, challenging medical advancements with its dismal prognosis, low cure rates and high mortality rates. Within this intricate landscape, long non­coding RNAs (lncRNAs) emerge as pivotal players, orchestrating proliferation and migration of cancer cells. Harnessing the potential of lncRNAs as therapeutic targets and prognostic markers holds immense promise. The present comprehensive review delved into the molecular mechanisms underlying the involvement of lncRNAs in the onset and progression of the top five types of cancer. By meticulously examining lncRNAs across diverse types of cancer, it also uncovered their distinctive roles, highlighting their exclusive oncogenic effects or tumor suppressor properties. Notably, certain lncRNAs demonstrate diverse functions across different cancers, confounding the conventional understanding of their roles. Furthermore, the present study identified lncRNAs exhibiting aberrant expression patterns in numerous types of cancer, presenting them as potential indicators for cancer screening and diagnosis. Conversely, a subset of lncRNAs manifests tissue­specific expression, hinting at their specialized nature and untapped significance in diagnosing and treating specific types of cancer. The present comprehensive review not only shed light on the intricate network of lncRNAs but also paved the way for further research and clinical applications. The unraveled molecular mechanisms offer a promising avenue for targeted therapeutics and personalized medicine, combating cancer proliferation, invasion and metastasis.

Aggregation-enhanced photothermal therapy of organic dyes.

Photothermal therapy (PTT) represents a groundbreaking approach to targeted disease treatment by harnessing the conversion of light into heat. The efficacy of PTT heavily relies on the capabilities of photothermal agents (PTAs). Among PTAs, those based on organic dyes exhibit notable characteristics such as adjustable light absorption wavelengths, high extinction coefficients, and high compatibility in biological systems. However, a challenge associated with organic dye-based PTAs lies in their efficiency in converting light into heat while maintaining stability. Manipulating dye aggregation is a key aspect in modulating non-radiative decay pathways, aiming to augment heat generation. This review delves into various strategies aimed at improving photothermal performance through constructing aggregation. These strategies including protecting dyes from photodegradation, inhibiting non-photothermal pathways, maintaining space within molecular aggregates, and introducing intermolecular photophysical processes. Overall, this review highlights the precision-driven assembly of organic dyes as a promising frontier in enhancing PTT-related applications. This article is categorized under: Therapeutic Approaches and Drug Discovery > Emerging Technologies Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease Diagnostic Tools > In Vivo Nanodiagnostics and Imaging.

Prognostic awareness and prognostic information preferences among advanced cancer patients in Kenya.

BACKGROUND:  Cancer is the third leading cause of death in Kenya. Yet, little is known about prognostic awareness and preferences for prognostic information. AIM:  To assess the prevalence of prognostic awareness and preference for prognostic information among advanced cancer patients in Kenya. SETTING:  Outpatient medical oncology and palliative care clinics and inpatient medical and surgical wards of Moi Teaching and Referral Hospital (MTRH) in Eldoret, Kenya. METHODS:  The authors surveyed 207 adults with advanced solid cancers. The survey comprised validated measures developed for a multi-site study of end-of-life care in advanced cancer patients. Outcome variables included prognostic awareness and preference for prognostic information. RESULTS:  More than one-third of participants (36%) were unaware of their prognosis and most (67%) preferred not to receive prognostic information. Increased age (OR = 1.04, 95% CI: 1.02, 1.07) and education level (OR: 1.18, CI: 1.08, 1.30) were associated with a higher likelihood of preference to receive prognostic information, while increased symptom burden (OR= 0.94, CI: 0.90, 0.99) and higher perceived household income levels (lower-middle vs low: OR= 0.19; CI: 0.09, 0.44; and upper middle- or high vs low: OR= 0.22, CI: 0.09, 0.56) were associated with lower odds of preferring prognostic information. CONCLUSION:  Results reveal low levels of prognostic awareness and little interest in receiving prognostic information among advanced cancer patients in Kenya.Contribution: Given the important role of prognostic awareness in providing patient-centred care, efforts to educate patients in Kenya on the value of this information should be a priority, especially among younger patients.

Uncovering novel therapeutic targets in glucose, nucleotides and lipids metabolism during cancer and neurological diseases.

BACKGROUND: Cell metabolism functions without a stop in normal and pathological cells. Different metabolic changes occur in the disease. Cell metabolism influences biochemical and metabolic processes, signaling pathways, and gene regulation. Knowledge regarding disease metabolism is limited. OBJECTIVE: The review examines the cell metabolism of glucose, nucleotides, and lipids during homeostatic and pathological conditions of neurotoxicity, neuroimmunological disease, Parkinson's disease, thymoma in myasthenia gravis, and colorectal cancer. METHODS: Data collection includes electronic databases, the National Center for Biotechnology Information, and Google Scholar, with several inclusion criteria: cell metabolism, glucose metabolism, nucleotide metabolism, and lipid metabolism in health and disease patients suffering from neurotoxicity, neuroinflammation, Parkinson's disease, thymoma in myasthenia gravis. The initial number of collected and analyzed papers is 250. The final analysis included 150 studies out of 94 selected papers. After the selection process, 62.67% remains useful. RESULTS AND CONCLUSION: A literature search shows that signaling molecules are involved in metabolic changes in cells. Differences between cancer and neuroimmunological diseases are present in the result section. Our finding enables insight into novel therapeutic targets and the development of scientific approaches for cancer and neurological disease onset, outcome, progression, and treatment, highlighting the importance of metabolic dysregulation. Current understanding, emerging research technologies and potential therapeutic interventions in metabolic programming is disucussed and highlighted.

Cancer patient satisfaction regarding the quality of information received: psychometric validity of EORTC QLQ-INFO25.

OBJECTIVES: to psychometrically validate the European Organization for Research and Treatment of Cancer Core Quality of Life Questionnaire EORTC QLQ-INFO25 instrument and identify the domains that influence patients' perception of the information received. METHODS: a cross-sectional methodology with cancer patients in a Brazilian philanthropic hospital institution. Sociodemographic and clinical instruments, EORTC QLQ-C30, EORTC QLQ-INFO25 and Supportive Care Needs Survey - Short Form 34 were used. Analysis occurred using Cronbach's alpha coefficients, intraclass correlation, test-retest and exploratory factor analysis. RESULTS: 128 respondents participated. Cronbach's alpha coefficient was 0.85. The test-retest obtained p-value=0.21. In the factor analysis, one item was excluded. Satisfaction with the information received was 74%, with three areas with averages below 70%. In open-ended questions, there was a greater desire for information. CONCLUSIONS: validity evidence was obtained with instrument reliability, consistency and stability. Respondents expressed satisfaction with the information received.

Plasma proteome profiling reveals dynamic of cholesterol marker after dual blocker therapy.

Dual blocker therapy (DBT) has the enhanced antitumor benefits than the monotherapy. Yet, few effective biomarkers are developed to monitor the therapy response. Herein, we investigate the DBT longitudinal plasma proteome profiling including 113 longitudinal samples from 22 patients who received anti-PD1 and anti-CTLA4 DBT therapy. The results show the immune response and cholesterol metabolism are upregulated after the first DBT cycle. Notably, the cholesterol metabolism is activated in the disease non-progressive group (DNP) during the therapy. Correspondingly, the clinical indicator prealbumin (PA), free triiodothyronine (FT3) and triiodothyronine (T3) show significantly positive association with the cholesterol metabolism. Furthermore, by integrating proteome and radiology approach, we observe the high-density lipoprotein partial remodeling are activated in DNP group and identify a candidate biomarker APOC3 that can reflect DBT response. Above, we establish a machine learning model to predict the DBT response and the model performance is validated by an independent cohort with balanced accuracy is 0.96. Thus, the plasma proteome profiling strategy evaluates the alteration of cholesterol metabolism and identifies a panel of biomarkers in DBT.

Impacts of socioeconomic and environmental factors on neoplasms incidence rates using machine learning and GIS: a cross-sectional study in Iran.

Neoplasm is an umbrella term used to describe either benign or malignant conditions. The correlations between socioeconomic and environmental factors and the occurrence of new-onset of neoplasms have already been demonstrated in a body of research. Nevertheless, few studies have specifically dealt with the nature of relationship, significance of risk factors, and geographic variation of them, particularly in low- and middle-income communities. This study, thus, set out to (1) analyze spatiotemporal variations of the age-adjusted incidence rate (AAIR) of neoplasms in Iran throughout five time periods, (2) investigate relationships between a collection of environmental and socioeconomic indicators and the AAIR of neoplasms all over the country, and (3) evaluate geographical alterations in their relative importance. Our cross-sectional study design was based on county-level data from 2010 to 2020. AAIR of neoplasms data was acquired from the Institute for Health Metrics and Evaluation (IHME). HotSpot analyses and Anselin Local Moran's I indices were deployed to precisely identify AAIR of neoplasms high- and low-risk clusters. Multi-scale geographically weight regression (MGWR) analysis was worked out to evaluate the association between each explanatory variable and the AAIR of neoplasms. Utilizing random forests (RF), we also examined the relationships between environmental (e.g., UV index and PM2.5 concentration) and socioeconomic (e.g., Gini coefficient and literacy rate) factors and AAIR of neoplasms. AAIR of neoplasms displayed a significant increasing trend over the study period. According to the MGWR, the only factor that significantly varied spatially and was associated with the AAIR of neoplasms in Iran was the UV index. A good accuracy RF model was confirmed for both training and testing data with correlation coefficients R2 greater than 0.91 and 0.92, respectively. UV index and Gini coefficient ranked the highest variables in the prediction of AAIR of neoplasms, based on the relative influence of each variable. More research using machine learning approaches taking the advantages of considering all possible determinants is required to assess health strategies outcomes and properly formulate policy planning.

PD-1/CD80+ small extracellular vesicles from immunocytes induce cold tumours featured with enhanced adaptive immunosuppression.

Only a minority of cancer patients benefit from immune checkpoint blockade therapy. Sophisticated cross-talk among different immune checkpoint pathways as well as interaction pattern of immune checkpoint molecules carried on circulating small extracellular vesicles (sEV) might contribute to the low response rate. Here we demonstrate that PD-1 and CD80 carried on immunocyte-derived sEVs (I-sEV) induce an adaptive redistribution of PD-L1 in tumour cells. The resulting decreased cell membrane PD-L1 expression and increased sEV PD-L1 secretion into the circulation contribute to systemic immunosuppression. PD-1/CD80+ I-sEVs also induce downregulation of adhesion- and antigen presentation-related molecules on tumour cells and impaired immune cell infiltration, thereby converting tumours to an immunologically cold phenotype. Moreover, synchronous analysis of multiple checkpoint molecules, including PD-1, CD80 and PD-L1, on circulating sEVs distinguishes clinical responders from those patients who poorly respond to anti-PD-1 treatment. Altogether, our study shows that sEVs carry multiple inhibitory immune checkpoints proteins, which form a potentially targetable adaptive loop to suppress antitumour immunity.

Integrated approach to generate artificial samples with low tumor fraction for somatic variant calling benchmarking.

BACKGROUND: High-throughput sequencing (HTS) has become the gold standard approach for variant analysis in cancer research. However, somatic variants may occur at low fractions due to contamination from normal cells or tumor heterogeneity; this poses a significant challenge for standard HTS analysis pipelines. The problem is exacerbated in scenarios with minimal tumor DNA, such as circulating tumor DNA in plasma. Assessing sensitivity and detection of HTS approaches in such cases is paramount, but time-consuming and expensive: specialized experimental protocols and a sufficient quantity of samples are required for processing and analysis. To overcome these limitations, we propose a new computational approach specifically designed for the generation of artificial datasets suitable for this task, simulating ultra-deep targeted sequencing data with low-fraction variants and demonstrating their effectiveness in benchmarking low-fraction variant calling. RESULTS: Our approach enables the generation of artificial raw reads that mimic real data without relying on pre-existing data by using NEAT, a fine-grained read simulator that generates artificial datasets using models learned from multiple different datasets. Then, it incorporates low-fraction variants to simulate somatic mutations in samples with minimal tumor DNA content. To prove the suitability of the created artificial datasets for low-fraction variant calling benchmarking, we used them as ground truth to evaluate the performance of widely-used variant calling algorithms: they allowed us to define tuned parameter values of major variant callers, considerably improving their detection of very low-fraction variants. CONCLUSIONS: Our findings highlight both the pivotal role of our approach in creating adequate artificial datasets with low tumor fraction, facilitating rapid prototyping and benchmarking of algorithms for such dataset type, as well as the important need of advancing low-fraction variant calling techniques.

A comparison of RNA-Seq data preprocessing pipelines for transcriptomic predictions across independent studies.

BACKGROUND: RNA sequencing combined with machine learning techniques has provided a modern approach to the molecular classification of cancer. Class predictors, reflecting the disease class, can be constructed for known tissue types using the gene expression measurements extracted from cancer patients. One challenge of current cancer predictors is that they often have suboptimal performance estimates when integrating molecular datasets generated from different labs. Often, the quality of the data is variable, procured differently, and contains unwanted noise hampering the ability of a predictive model to extract useful information. Data preprocessing methods can be applied in attempts to reduce these systematic variations and harmonize the datasets before they are used to build a machine learning model for resolving tissue of origins. RESULTS: We aimed to investigate the impact of data preprocessing steps-focusing on normalization, batch effect correction, and data scaling-through trial and comparison. Our goal was to improve the cross-study predictions of tissue of origin for common cancers on large-scale RNA-Seq datasets derived from thousands of patients and over a dozen tumor types. The results showed that the choice of data preprocessing operations affected the performance of the associated classifier models constructed for tissue of origin predictions in cancer. CONCLUSION: By using TCGA as a training set and applying data preprocessing methods, we demonstrated that batch effect correction improved performance measured by weighted F1-score in resolving tissue of origin against an independent GTEx test dataset. On the other hand, the use of data preprocessing operations worsened classification performance when the independent test dataset was aggregated from separate studies in ICGC and GEO. Therefore, based on our findings with these publicly available large-scale RNA-Seq datasets, the application of data preprocessing techniques to a machine learning pipeline is not always appropriate.

Factors influencing presentation delay among cancer patients: a cross-sectional study in Malaysia.

BACKGROUND: Cancer represents a significant global public health challenge, with escalating incidence rates straining healthcare systems. Malaysia, like many nations, has witnessed a rise in cancer cases, particularly among the younger population. This study aligns with Malaysia's National Strategic Plan for Cancer Control Programme 2021-2025, emphasizing primary prevention and early detection to address cancer's impact. Therefore, we aim to describe the timeliness of cancer care for symptom presentation, socio-demographic, patient, as well as organizational-related factors among patients in Malaysia diagnosed with breast, colorectal, nasopharyngeal, and cervical cancer. METHODS: This cross-sectional study enrolled adult cancer patients diagnosed with breast, cervical, colorectal, or nasopharyngeal cancer from 2015 to 2020 in seven public hospitals/oncology centres across Malaysia. Data were collected through patient-administered surveys and medical records. Presentation delay, defined as the duration between symptom onset and the patient's first visit to a healthcare professional exceeding 30 days, was the primary outcome. Statistical analysis included descriptive statistics and chi-square tests. RESULTS: The study included 476 cancer patients, with breast cancer (41.6%), colorectal cancer (26.9%), nasopharyngeal cancer (22.1%), and cervical cancer (9.5%). Over half (54.2%) experienced presentation delays with a median interval of 60 days. Higher proportions of presentation delay were observed among nasopharyngeal cancer patients, employed patients with lower socioeconomic statuses, and those without family history of cancer. Most patients self-discovered their first cancer symptoms (80%), while only one-third took immediate action for medical check-ups. Emotional and organizational factors, such as long waiting times during doctor's visits (47%), were potential barriers to seeking cancer care. CONCLUSION: This study highlights the significant problem of presentation delay among cancer patients in Malaysia. The delay is influenced by various factors encompassing sociodemographic characteristics, health-seeking behaviours, and healthcare system-related issues. A comprehensive approach addressing both individual barriers and institutional obstacles is imperative to mitigate this presentation delay and improve cancer outcomes.

Greatly isolated heterogeneous circulating tumor cells using hybrid engineered cell membrane-camouflaged magnetic nanoparticles.

BACKGROUND: Circulating tumor cells (CTCs) are considered as a useful biomarker for early cancer diagnosis, which play a crucial role in metastatic process. Unfortunately, the tumor heterogeneity and extremely rare occurrence rate of CTCs among billions of interfering leukocytes seriously hamper the sensitivity and purity of CTCs isolation. METHODS: To address these, we firstly used microfluidic chips to detect the broad-spectrum of triple target combination biomarkers in CTCs of 10 types of cancer patients, including EpCAM, EGFR and Her2. Then, we constructed hybrid engineered cell membrane-camouflaged magnetic nanoparticles (HE-CM-MNs) for efficient capture of heterogeneous CTCs with high-purity, which was enabled by inheriting the recognition ability of HE-CM for various CTCs and reducing homologous cell interaction with leukocytes. Compared with single E-CM-MNs, HE-CM-MNs showed a significant improvement in the capture efficiency for a cell mixture, with an efficiency of 90%. And the capture efficiency of HE-CM-MNs toward 12 subpopulations of tumor cells was ranged from 70 to 85%. Furthermore, by using HE-CM-MNs, we successfully isolated heterogeneous CTCs with high purity from clinical blood samples. Finally, the captured CTCs by HE-CM-MNs could be used for gene mutation analysis. CONCLUSIONS: This study demonstrated the promising potential of HE-CM-MNs for heterogeneous CTCs detection and downstream analysis.

Roles of post-translational modifications of UHRF1 in cancer.

UHRF1 as a member of RING-finger type E3 ubiquitin ligases family, is an epigenetic regulator with five structural domains. It has been involved in the regulation of a series of biological functions, such as DNA replication, DNA methylation, and DNA damage repair. Additionally, aberrant overexpression of UHRF1 has been observed in over ten cancer types, indicating that UHRF1 is a typical oncogene. The overexpression of UHRF1 repressed the transcription of such tumor-suppressor genes as CDKN2A, BRCA1, and CDH1 through DNMT1-mediated DNA methylation. In addition to the upstream transcription factors regulating gene transcription, post-translational modifications (PTMs) also contribute to abnormal overexpression of UHRF1 in cancerous tissues. The types of PTM include phosphorylation, acetylation, methylationand ubiquitination, which regulate protein stability, histone methyltransferase activity, intracellular localization and the interaction with binding partners. Recently, several novel PTM types of UHRF1 have been reported, but the detailed mechanisms remain unclear. This comprehensive review summarized the types of UHRF1 PTMs, as well as their biological functions. A deep understanding of these crucial mechanisms of UHRF1 is pivotal for the development of novel UHRF1-targeted anti-cancer therapeutic strategies in the future.

Seleno-amino Acid Metabolism Reshapes the Tumor Microenvironment: from Cytotoxicity to Immunotherapy.

Selenium (Se) is an essential trace element for biological processes. Seleno-amino acids (Se-AAs), known as the organic forms of Se, and their metabolic reprogramming have been increasingly recognized to regulate antioxidant defense, enzyme activity, and tumorigenesis. Therefore, there is emerging interest in exploring the potential application of Se-AAs in antitumor therapy. In addition to playing a vital role in inhibiting tumor growth, accumulating evidence has revealed that Se-AA metabolism could reshape the tumor microenvironment (TME) and enhance immunotherapy responses. This review presents a comprehensive overview of the current progress in multifunctional Se-AAs for antitumor treatment, with a particular emphasis on elucidating the crosstalk between Se-AA metabolism and various cell types in the TME, including tumor cells, T cells, macrophages, and natural killer cells. Furthermore, novel applications integrating Se-AAs are also discussed alongside prospects to provide new insights into this emerging field.

Glycosylation Targeting: A Paradigm Shift in Cancer Immunotherapy.

Immunotherapy has shown great potential in cancer treatment. However, even with the intervention of techniques such as immune checkpoint inhibitor therapy, tumors can still achieve immune escape, leading to a low response rate. Abnormal glycosylation is a widely recognized hallmark of cancer. The development of a complex "glyco-code" on the surface of tumor cells can potentially influence the immune system's ability to monitor tumors and can impact the anti-tumor immune response. Therefore, abnormal glycosylation has emerged as a promising target for immunotherapy. Many recent studies have shown that targeted glycosylation can reshape the tumor microenvironment (TME) and promote the immune response, thereby improving the response to immunotherapy. This review summarizes how glycosylation affects anti-tumor immune function in the TME and synthesizes the latest research progress on targeted glycosylation in immunotherapy. It is hoped that by elucidating the basic laws and biological connotations of glycosylation, this review will enable researcher to thoroughly analyze the mechanism of its influence on the immune metabolic regulation network, which will provide a theoretical tool for promoting the clinical application of glycosylation codes.