Search Results (29)

Background/Objectives: Increasing evidence suggests that lncRNAs are core regulators in the field of tumor progression, with context-specific functions in oncogenic tumorigenesis. LINC01133, a lncRNA that has been identified as both an oncogene and a tumor suppressor, remains largely unexplored in terms of its molecular mechanisms. The purpose of this study was to conduct an in silico analysis, incorporating literature research on various cancer types, to investigate the structural and functional duality of LINC01133. This analysis aimed to identify pathways influenced by LINC01133 and evaluate its mechanism of action as a potential therapeutic target and diagnostic biomarker. Methods: In silico analyses and a narrative review of the literature were performed to predict conserved structural elements, functional internal loops, and overall conservation of the LINC01133 sequence among different vertebrate organisms, summarizing the empirical evidence regarding its roles as a tumor suppressor and tumor-promoting roles in various types of tumors. Results: LINC01133 harbors the evolutionarily conserved structural regions that might allow for binding to relevant driver signaling pathways, substantiating its specific functionality. Its action extends beyond classical tumor mechanisms, affecting proliferation, migration, invasion, and epigenetic pathways in various types of tumors, as indicated by the in silico results and narrative review of the literature we present here. Clinical outcome associations pointed to its potential as a biomarker. Conclusions: The dual character of LINC01133 in tumor biology further demonstrates its prospective therapeutic value, but complete elucidation of its mechanisms of action requires further investigation. This study establishes LINC01133 as a multifaceted lncRNA, supporting context-specific strategies in targeting its pathways, and calls for expanded research to harness its full potential in oncology. Full article

Human papillomavirus (HPV) infection remains a principal cause of cervical cancer worldwide. Although large-scale vaccination efforts have substantially lowered HPV infection rates and precancerous lesions, not all regions have achieved high coverage. In Japan, proactive HPV vaccine recommendations were suspended from 2013 to 2022 due to concerns over alleged adverse events, causing vaccination rates to drop from over 70% to below 1%. This narrative review synthesized research published from 2014 to 2025 in PubMed, Cochrane Library, and Google Scholar, focusing on English-language studies. Inclusion criteria encompassed analyses of HPV vaccine efficacy or safety, policies related to vaccination in Japan or other countries, and investigations into vaccine hesitancy or media influences. Data were categorized into five thematic areas: historical and policy contexts, evidence of vaccine safety and efficacy, societal drivers of hesitancy, communication strategies, and administrative or clinical interventions. Evidence robustly confirms the HPV vaccine’s favorable safety profile, with severe adverse events appearing exceedingly rare. Nonetheless, media sensationalism and limited risk communication in Japan perpetuated mistrust, impeding vaccination uptake. Comparisons with Denmark and Ireland indicate that transparent, interactive risk communication can restore coverage to near-pre-suspension levels. Japan’s recent policy reforms, including reinstating proactive recommendations and catch-up initiatives, have begun to reverse vaccination hesitancy. Sustained policy support, evidence-based messaging, and empathetic engagement with communities are central to rebuilding trust in the HPV vaccine. Lessons from best international practices emphasize the importance of multifaceted interventions, collaborative stakeholder engagement, and transparent risk communication to reduce the burden of HPV-related malignancies. Full article

Chronic inflammation is increasingly recognized as a key driver of tumorigenesis, affecting both the tumor microenvironment and host response. In this context, circulating inflammatory proteins may provide valuable insights into cancer activity. This study evaluated the diagnostic performance of the inflammatory protein ratio (IPR), a composite index derived from serum protein electrophoresis, in detecting active cancer among hospitalized patients. We retrospectively analyzed clinical and laboratory data from 312 adult patients admitted to the Internal Medicine and Aging Department at Policlinico Foggia, Italy, between November 2023 and July 2024. Patients were stratified according to the presence of active cancer, defined by NICE criteria. The diagnostic accuracy of the IPR was compared with that of conventional inflammatory markers, including C-reactive protein (CRP) and the neutrophil–lymphocyte ratio (NLR), platelet–lymphocyte ratio (PLR), monocyte–lymphocyte ratio (MLR), and systemic immune–inflammation index (SII). The IPR showed the highest diagnostic performance, with a sensitivity of 88.1%, a specificity of 75.2%, and an area under the receiver operating characteristic curve (AUC) of 0.868. Its negative predictive value reached 97.6%, underscoring its potential as a rule-out tool for malignancy in hospitalized patients. These findings support the IPR as a promising and cost-effective inflammation-based biomarker for cancer detection, warranting further validation in prospective and molecularly characterized cohorts. Full article

Background and Objectives: Invasive breast cancer (BC) was traditionally investigated visually, and no technique could identify the key molecular drivers of patient survival. However, essential molecular drivers of invasive BC have now been discovered using innovative genomic, transcriptomic, and proteomic methodologies. Nevertheless, few evaluations of the prognostic factors of BC in Saudi Arabia have been performed. Evaluating the biomarkers associated with the development of early-stage BC could help determine the risk of metastasis and guide treatment decisions. In a previous study, using large BC cohorts and artificial neural network techniques, DNA replication and sister chromatid cohesion 1 (DSCC1) was found to be one of the principal genes in invasive BC samples. To date, no studies have addressed the prognostic significance of DSCC1 in invasive BC and its association with aggressive tumor behavior. This research aimed to address this gap. Materials and Methods: The association of clinicopathological features and patient outcomes with DSCC1 expression at the mRNA level was assessed using the Molecular Taxonomy Breast Cancer International Consortium (METABRIC; n = 1980) and The Cancer Genome Atlas (TCGA; n = 854) cohorts. DSCC1 was also evaluated at the protein level using immunohistochemistry on samples from invasive BC patients (n = 100) presenting to King Abdul Aziz Specialist Hospital in Saudi Arabia. The association of clinicopathological parameters (including patient age, tumor grade, tumor size, and patient outcome) with protein level was also evaluated. Results: In both METABRIC and TCGA cohorts, high expression of DSCC1 was significantly associated with high histological grade, large tumor size, lymphovascular invasion positivity, and hormone receptor negativity (all p < 0.001). A high DSCC1 mRNA level was associated with poor outcomes (p < 0.001 for METABRIC, p = 0.23 for TCGA). At the protein level, high DSCC1 expression was associated with high histological grade (p = 0.001), lymph node presence (p = 0.008), hormone receptor negativity (p = 0.005), high Ki67 expression (p = 0.036), and shorter survival (p = 0.008). Conclusions: This study confirmed the prognostic significance of DSCC1 in invasive BC patients. DSCC1 could be a therapeutic target in BC cases with poor outcomes. Full article

All 189 World Bank member countries are classified by their capita gross national income into one of four income groups. In this review, we aim to explore the economic burden and management of urologic oncology conditions in low- and middle-income countries (LMICs), emphasizing disparities and challenges in treatment access. The current World Bank classification system highlights economic stratification, showing significant health outcome disparities, particularly in urologic oncology conditions including kidney, bladder, and prostate cancer. First, this review focuses on the management of advanced prostate cancer in Asian LMICs, revealing higher mortality-to-incidence ratios and a greater prevalence of metastatic disease compared to high-income countries (HICs). The prohibitive costs of novel hormonal therapies (NHTs) like abiraterone and enzalutamide limit their use and exacerbate outcome disparities. Second, we review Wilms tumor treatment with chemotherapy in African countries, noting significant price variations for adapted and non-adapted regimens across different economic settings. The cost of chemotherapy agents, particularly dactinomycin, acts as a primary driver of treatment expenses, underscoring the economic challenges in providing high-quality care. Lastly, bladder cancer treatment costs in Brazil and Middle Eastern countries are examined, highlighting how detrimental the economic burden of intravesical therapies, like mitomycin C and Bacillus Calmette–Guérin (BCG), is on treatment accessibility. Overall, this literature review emphasizes the financial strain on healthcare systems and patients, particularly in regions facing economic instability and drug shortages, and underscores the need for international cooperation and effective resource allocation to address the economic barriers to urologic care in LMICs, aiming to improve health outcomes and ensure equitable access to advanced treatments. Full article

Recent developments in biomimetic hydrogel research have expanded the scope of biomedical technologies that can be used to model, diagnose, and treat a wide range of medical conditions. Cancer presents one of the most intractable challenges in this arena due to the surreptitious mechanisms that it employs to evade detection and treatment. In order to address these challenges, biomimetic design principles can be adapted to beat cancer at its own game. Biomimetic design strategies are inspired by natural biological systems and offer promising opportunities for developing life-changing methods to model, detect, diagnose, treat, and cure various types of static and metastatic cancers. In particular, focusing on the cellular and subcellular phenomena that serve as fundamental drivers for the peculiar behavioral traits of cancer can provide rich insights into eradicating cancer in all of its manifestations. This review highlights promising developments in biomimetic nanocomposite hydrogels that contribute to cancer therapies via enhanced drug delivery strategies and modeling cancer mechanobiology phenomena in relation to metastasis and synergistic sensing systems. Creative efforts to amplify biomimetic design research to advance the development of more effective cancer therapies will be discussed in alignment with international collaborative goals to cure cancer. Full article

Spinal metastasis is exceedingly common in patients with cancer and its prevalence is expected to increase. Surgical management of symptomatic spinal metastasis is indicated for pain relief, preservation or restoration of neurologic function, and mechanical stability. The overall prognosis is a major driver of treatment decisions; however, clinicians’ ability to accurately predict survival is limited. In this narrative review, we first discuss the NOMS decision framework used to guide decision making in the treatment of patients with spinal metastasis. Given that decision making hinges on prognosis, multiple scoring systems have been developed over the last three decades to predict survival in patients with spinal metastasis; these systems have largely been developed using expert opinions or regression modeling. Although these tools have provided significant advances in our ability to predict prognosis, their utility is limited by the relative lack of patient-specific survival probability. Machine learning models have been developed in recent years to close this gap. Employing a greater number of features compared to models developed with conventional statistics, machine learning algorithms have been reported to predict 30-day, 6-week, 90-day, and 1-year mortality in spinal metastatic disease with excellent discrimination. These models are well calibrated and have been externally validated with domestic and international independent cohorts. Despite hypothesized and realized limitations, the role of machine learning methodology in predicting outcomes in spinal metastatic disease is likely to grow. Full article

Small-cell neuroendocrine cervical carcinoma (SCNCC) is a rare yet aggressive gynecological malignancy associated with dismal clinical outcomes. Its rarity has led to a limited number of retrospective studies and an absence of prospective research, posing significant challenges for evidence-based treatment approaches. As a result, most gynecologic oncology centers have limited experience with this tumor, emphasizing the urgent need for a comprehensive review and summary. This article systematically reviews the pathogenesis, immunohistochemical and molecular characteristics, prognostic factors, and clinical management of gynecologic SCNCC. We specifically focused on reviewing the distinct genomic characteristics of SCNCC identified via next-generation sequencing technologies, including loss of heterozygosity (LOH), somatic mutations, structural variations (SVs), and microRNA alterations. The identification of these actionable genomic events offers promise for discovering new molecular targets for drug development and enhancing therapeutic outcomes. Additionally, we delve deeper into key clinical challenges, such as determining the optimal treatment modality between chemoradiation and surgery for International Federation of Gynecology and Obstetrics (FIGO) stage I phase patients within a precision stratification framework, as well as the role of targeted therapy within the homologous recombination (HR) pathway, immune checkpoint inhibitors (ICIs), and prophylactic cranial irradiation (PCI) in the management of SCNCC. Finally, we anticipate the utilization of multiple SCNCC models, including cancer tissue-originated spheroid (CTOS) lines and patient-derived xenografts (PDXs), to decipher driver events and develop individualized therapeutic strategies for clinical application. Full article

Lung cancer ranks as the second most prevalent cancer globally and is the primary contributor to neoplastic-related deaths. The approach to its treatment relies on both tumour staging and histological type determination. Data indicate that the prognosis of lung cancer is strongly linked to its clinical stage, underscoring the importance of early diagnosis in enhancing patient outcomes. Consequently, the choice of an appropriate diagnostic method holds significant importance in elevating both the early detection rate and prognosis of lung cancer. This paper aims to assess computer tomography features specific to the most common lung cancer types (adenocarcinoma, squamous cell carcinomas and small cell lung cancer). Data were collected retrospectively from CT scans of 58 patients pathologically diagnosed with lung cancer. The following CT features were evaluated and recorded for each case: location, margins, structure, lymph node involvement, cavitation, vascular bundle-thickening, bronchial obstruction, and pleural involvement. Squamous cell carcinoma (SQCC) and small cell lung cancer (SCLC) showed a higher incidence of central location, while adenocarcinoma (ADC) showed a significant predilection for a peripheral location. Internal cavitation was mostly observed in SQCC, and a solid structure was observed in almost all cases of ADC. These features can provide information about the prognosis of the patient, considering that NSCLCs are more frequent but tend to demonstrate positive results for targetable driver mutations, such as EGFR, thereby increasing the overall survival. In addition, SCLC presents with early distant spreads, which limits the opportunity to investigate the evolution of tumorigenesis and gene alterations at early stages but can have a rapidly positively response to chemotherapy. The location of the lung cancer exhibits distinct forecasts, with several studies suggesting that peripheral lung tumours offer a more favourable prognosis. Cavity formation appears correlate with a poorer prognosis. Histopathological analysis is the gold standard for diagnosing the type of lung cancer; however, using CT scanning for the purpose of a rough, but fast, preliminary diagnosis has the potential to shorten the waiting time for treatment by helping clinicians and patients to know more about the diagnosis and prognosis. Full article

The epidermal growth factor receptor (EGFR) is a common driver of non-small cell lung cancer (NSCLC). Clathrin-mediated internalization (CMI) sustains EGFR signaling. AXL is associated with resistance to EGFR-tyrosine kinase inhibitors (TKIs) in EGFR-mutated (EGFR^M) NSCLC. We investigated the effects of Leucine zipper downregulated in cancer-1 (LDOC1) on EGFR CMI and NSCLC treatment. Coimmunoprecipitation, double immunofluorescence staining, confocal microscopy analysis, cell surface labelling assays, and immunohistochemistry studies were conducted. We revealed that LDOC1 interacts with clathrin adaptors through binding motifs. LDOC1 depletion promotes internalization and plasma membrane recycling of EGFR in EGFR^M NSCLC PC9 and HCC827 cells. Membranous and cytoplasmic EGFR decreased and increased, respectively, in LDOC1 (−) NSCLC tumors. LDOC1 depletion enhanced and sustained activation of EGFR, AXL, and HER2 and enhanced activation of HER3 in PC9 and HCC827 cells. Sensitivity to first-generation EGFR-TKIs (gefitinib and erlotinib) was significantly reduced in LDOC1-depleted PC9 and HCC827 cells. Moreover, LDOC1 downregulation was significantly associated (p < 0.001) with poor overall survival in patients with EGFR^M NSCLC receiving gefitinib (n = 100). In conclusion, LDOC1 may regulate the efficacy of first-generation EGFR-TKIs by participating in the CMI of EGFR. Accordingly, LDOC1 may function as a prognostic biomarker for EGFR^M NSCLC. Full article

For humans, the parallel processing capability of visual recognition allows for faster comprehension of complex scenes and patterns. This is essential, especially for clinicians interpreting big data for whom the visualization tools play an even more vital role in transforming raw big data into clinical decision making by managing the inherent complexity and monitoring patterns interactively in real time. The Cancer Genome Atlas (TCGA) database’s size and data variety challenge the effective utilization of this valuable resource by clinicians and biologists. We re-analyzed the five molecular data types, i.e., mutation, transcriptome profile, copy number variation, miRNA, and methylation data, of ~11,000 cancer patients with all 33 cancer types and integrated the existing TCGA patient cohorts from the literature into a free and efficient web application: TCGAnalyzeR. TCGAnalyzeR provides an integrative visualization of pre-analyzed TCGA data with several novel modules: (i) simple nucleotide variations with driver prediction; (ii) recurrent copy number alterations; (iii) differential expression in tumor versus normal, with pathway and the survival analysis; (iv) TCGA clinical data including metastasis and survival analysis; (v) external subcohorts from the literature, curatedTCGAData, and BiocOncoTK R packages; (vi) internal patient clusters determined using an iClusterPlus R package or signature-based expression analysis of five molecular data types. TCGAnalyzeR integrated the multi-omics, pan-cancer TCGA with ~120 subcohorts from the literature along with clipboard panels, thus allowing users to create their own subcohorts, compare against existing external subcohorts (MSI, Immune, PAM50, Triple Negative, IDH1, miRNA, metastasis, etc.) along with our internal patient clusters, and visualize cohort-centric or gene-centric results interactively using TCGAnalyzeR. Full article

DNA is an organic molecule that is highly vulnerable to chemical alterations and breaks caused by both internal and external factors. Cells possess complex and advanced mechanisms, including DNA repair, damage tolerance, cell cycle checkpoints, and cell death pathways, which together minimize the potentially harmful effects of DNA damage. However, in cancer cells, the normal DNA damage tolerance and response processes are disrupted or deregulated. This results in increased mutagenesis and genomic instability within the cancer cells, a known driver of cancer progression and therapeutic resistance. On the other hand, the inherent instability of the genome in rapidly dividing cancer cells can be exploited as a tool to kill by imposing DNA damage with radiopharmaceuticals. As the field of targeted radiopharmaceutical therapy (RPT) is rapidly growing in oncology, it is crucial to have a deep understanding of the impact of systemic radiation delivery by radiopharmaceuticals on the DNA of tumors and healthy tissues. The distribution and activation of DNA damage and repair pathways caused by RPT can be different based on the characteristics of the radioisotope and molecular target. Here we provide a comprehensive discussion of the biological effects of RPTs, with the main focus on the role of varying radioisotopes in inducing direct and indirect DNA damage and activating DNA repair pathways. Full article

Oligometastatic disease (OMD) is currently known as an intermediate state of cancer, characterized by a limited number of systemic metastatic lesions for which local ablative therapy could be curative. Indeed, data from multiple clinical trials have illustrated an increase in overall survival (OS) for cancer patients when local ablative therapy was included in the systemic adjuvant therapy. Given that no driver and somatic mutations specific to OMD are currently established, the diagnosis of OMD is mainly based on the results of X-ray studies. In 2020, 20 international experts from the European Society for Radiotherapy and Oncology (ESTRO) and the European Organization for Research and Treatment of Cancer (EORTC) developed a comprehensive system for the characterization and classification of OMD. They identified 17 OMD characteristics that needed to be assessed in all patients who underwent radical local treatment. These characteristics reflect the tumor biology and clinical features of the disease underlying the development of OMD independently of the primary tumor type and the number of metastatic lesions. In particular, the system involves the characteristics of the primary tumor (e.g., localization, histology, TNM stage, mutational status, specific tumor markers), clinical parameters (e.g., disease-free interval, treatment-free interval), therapies (e.g., local, radical or palliative treatment, the numbers of the therapeutic regimens), and type of OMD (e.g., invasive). Based on the aforementioned criteria, an algorithm was introduced into the clinic to classify OMDs collectively according to their nomenclature. A history of polymetastatic disease (PMD) prior to OMD is used as a criterion to delineate between induced OMD (previous history of PMD after successful therapy) and genuine OMD (no history of PMD). Genuine OMD is divided into two states: recurrent OMD (i.e., after a previous history of OMD) and de novo OMD (i.e., a first newly diagnosed oligometastatic disease). de novo OMD is differentiated into synchronous and metachronous forms depending on the length of time from the primary diagnosis to the first evidence of OMD. In the case of synchronous OMD, this period is less than 6 months. Lastly, metachronous and induced OMD are divided into oligorecurrence, oligoprogression, and oligopersistence, depending on whether OMD is firstly diagnosed during an absence (oligo recurrence) or presence (oligoprogression or oligopersistence) of active systemic therapy. This classification and nomenclature of OMD are evaluated prospectively in the OligoCare study. In this article, we present a practical review of the current concept of OMD and discuss the available prospective clinical trials and potential future directions. Full article

RNA polymerase III (Pol III) subunit RPC7α, which is encoded by POLR3G in humans, has been linked to both tumor growth and metastasis. Accordantly, high POLR3G expression is a negative prognostic factor in multiple cancer subtypes. To date, the mechanisms underlying POLR3G upregulation have remained poorly defined. We performed a large-scale genomic survey of mRNA and chromatin signatures to predict drivers of POLR3G expression in cancer. Our survey uncovers positive determinants of POLR3G expression, including a gene-internal super-enhancer bound with multiple transcription factors (TFs) that promote POLR3G expression, as well as negative determinants that include gene-internal DNA methylation, retinoic-acid induced differentiation, and MXD4-mediated disruption of POLR3G expression. We show that novel TFs identified in our survey, including ZNF131 and ZNF207, functionally enhance POLR3G expression, whereas MXD4 likely obstructs MYC-driven expression of POLR3G and other growth-related genes. Integration of chromatin architecture and gene regulatory signatures identifies additional factors, including histone demethylase KDM5B, as likely influencers of POLR3G gene activity. Taken together, our findings support a model in which POLR3G expression is determined with multiple factors and dynamic regulatory programs, expanding our understanding of the circuitry underlying POLR3G upregulation and downstream consequences in cancer. Full article

Gene fusions are a form of structural rearrangement well established as driver events in pediatric and adult cancers. The identification of such events holds clinical significance in the refinement, prognostication, and provision of treatment in cancer. Structural rearrangements also extend beyond fusions to include intragenic rearrangements, such as internal tandem duplications (ITDs) or exon-level deletions. These intragenic events have been increasingly implicated as cancer-promoting events. However, the detection of intragenic rearrangements may be challenging to resolve bioinformatically with short-read sequencing technologies and therefore may not be routinely assessed in panel-based testing. Within an academic clinical laboratory, over three years, a total of 608 disease-involved samples (522 hematologic malignancy, 86 solid tumors) underwent clinical testing using Anchored Multiplex PCR (AMP)-based RNA sequencing. Hematologic malignancies were evaluated using a custom Pan-Heme 154 gene panel, while solid tumors were assessed using a custom Pan-Solid 115 gene panel. Gene fusions, ITDs, and intragenic deletions were assessed for diagnostic, prognostic, or therapeutic significance. When considering gene fusions alone, we report an overall diagnostic yield of 36% (37% hematologic malignancy, 41% solid tumors). When including intragenic structural rearrangements, the overall diagnostic yield increased to 48% (48% hematologic malignancy, 45% solid tumor). We demonstrate the clinical utility of reporting structural rearrangements, including gene fusions and intragenic structural rearrangements, using an AMP-based RNA sequencing panel. Full article