Cancers最新文献

Uveal melanoma (UM), recognized as the most prevalent primary intraocular malignancy in adults, is primarily driven by mutations in the GNAQ and GNA11 genes. These genetic alterations are also implicated in other conditions, which exhibit distinct morphological characteristics. In this article, we investigate the role of GNAQ and GNA11 mutations across varied disorders (e.g., UM, skin blue nevi, and hemangiomas), emphasizing the shared pathogenic mechanisms that connect them despite their differing clinical manifestations. By investigating the molecular pathways affected by these mutations, we provide insights into the potential for targeted therapies that could address not only UM but also other disorders associated with GNAQ/GNA11 mutations. Moreover, we discuss the role of SOX10-positive perivascular cells that may be implicated in the complex pathophysiology of GNAQ/GNA11-related entities. Understanding the common molecular foundation of these conditions opens new ways for research and treatment opportunities, potentially leading to more effective, personalized therapeutic strategies.

Introduction: Epidemiological data are crucial for adopting primary and secondary prevention strategies and to develop screening protocols against prostate cancer (PCa). Despite the comprehensive characterization of PCa across White and Black men, there is a lack of data from the Mexican population. This manuscript presents data from the Can.Prost registry that captures PCa trends over the past two decades in Mexico City; furthermore, we aimed to compare clinical differences and oncological outcomes before and after the promotion of early detection actions through a campaign against PCa that occurred in 2014.

Methods: A retrospective observational study on newly diagnosed Mexican PCa patients was carried out at the Instituto Nacional de Cancerología (INCan) in Mexico City. During 2014 and 2015, a project for the early diagnosis of PCa ("OPUS program") was launched in the aforementioned tertiary hospital. Starting at the age of 45 years, all men were invited for a PSA measurement and a specialist urologist consultation. All individuals with clinical or biochemical suspicion of PCa (PSA > 4 ng/mL), in the context of age and prostate volume, underwent ultrasound-guided transrectal prostate biopsy. Then, patients with pathologically confirmed prostate cancer were stratified according to the year of diagnosis: Group A accounted for those diagnosed between 2000 and 2014 and Group B for those patients diagnosed in the timeframe of 2015-2021. Comparisons of PCa characteristics, treatment modalities and oncologic outcomes between Group A and B were performed.

Results: Overall, we collected data from 2759 PCa patients from 2000 to 2021. The median PSA at baseline was 32 ng/mL, and 25% had a family history of PCa. Overall, 25.8% were asymptomatic and 46% had a non-metastatic presentation. After the OPUS campaign, PSA at diagnosis was significantly lower across all age groups. The incidence of PCa diagnosis in asymptomatic men was higher (31.4% vs. 19.9%) and a higher proportion of men were diagnosed with organ-confined, palpable disease (46% vs. 28%) (p < 0.001). The rate of patients eligible for active/radical treatment was higher after the OPUS campaign (patients who received surgery increased from 12.78% to 32.41%; patients who underwent radiation increased from 28.38% to 49.61%). The proportion of patients diagnosed with non-clinically significant disease was negligible and remained stable across time.

Conclusions: PCa in Mexican patients displays aggressive features at diagnosis, whereas the rate of non-significant disease is negligible. The introduction of early detection strategies may lead to lower symptomatic and metastatic PCa and higher opportunities for radical treatment. This emphasizes the need for public awareness and for adjustment of screening strategies to the peculiarities of the Mexican population.

Background/objectives: The aim of this study was to examine the expression of TYK2 in colorectal cancer (CRC) and to determine the potential diagnostic and prognostic significance of this kinase.

Methods: Digital image analysis was performed to assess immunohistochemical TYK2 reactivity.

Results: There were significant differences for all positive pixels between CRC and normal colonic mucosa, with higher TYK2 expression levels observed in surgical margins than in adenocarcinomas (p = 0.0004). Paired t tests showed elevated immunoreactivity for overall TYK2 expression in matched pairs of CRC with adjacent surgical margins (p < 0.0001). Higher percentages of weak (p < 0.0001) and strong pixels (p = 0.0260) were detected in normal colonic mucosa than in cancer tissues. To distinguish cancer from normal intestinal mucosa, the following cutoffs for the TYK2 immune score were found: 29.5% for all cases and 31% for matched pairs. Tumor budding (Bd) was negatively correlated with the percentage of strong pixels for TYK2 (ρ = -0.270, p = 0.0096). The percentage of strong pixels was significantly elevated for the T parameter (p = 0.0428). There was a positive correlation between the number of involved lymph nodes and weak pixels (ρ = 0.239, p = 0.0242). Immunofluorescence staining showed significantly higher signal intensities in colonic mucosa than in CRC. The protein level of TYK2 was significantly higher in controls than in cancer tissues. TEM imaging showed lower levels of TYK2 in cancer than in ulcerative colitis.

Conclusions: TYK2 protein expression may bring diagnostic value in patients diagnosed with CRC.

Background/Objectives: Prostate cancer (PCa) is a prevalent malignancy, necessitating accurate diagnostic methods to distinguish it from benign conditions such as benign prostatic hyperplasia (BPH). Current diagnostic tools, relying primarily on serum prostate-specific antigen (PSA) levels, lack specificity, leading to an over-diagnosis and unnecessary treatment of patients with benign conditions. This study explores G-protein-coupled receptor-associated sorting protein 1 (GASP-1) as a more sensitive biomarker for PCa detection. Methods: Prostate tissue microarrays of healthy, BPH, and prostate cancer patients with different Gleason scores were studied. Polyclonal antibodies targeted against GASP-1 were used for routine immunohistochemistry (IHC) and enzyme-linked immunosorbent assay (ELISA) analyses. Results: The results indicated a 5-fold difference in serum GASP-1 levels between BPH and PCa, which was validated through GASP-1 IHC. Furthermore, a novel scoring system, the H-score, assesses GASP-1 granules' intensity and size, revealing a clear distinction between BPH and PCa. An additional analysis of GASP-1 expression between PCa cases with different Gleason scores reveals that GASP-1 overexpression correlates with PCa severity, providing insights into disease progression. Conclusions: The study supports GASP-1's role as a promising diagnostic marker, supplementing PSA testing, and offering improved risk stratification for PCa. Additionally, an open-source software system is introduced for an efficient GASP-1 granule color analysis, enhancing diagnostic accuracy.

Kinase inhibitors are potent therapeutic agents in cancer treatment, but their effectiveness is frequently restricted by the inability to image the tumor microenvironment. To address this constraint, kinase inhibitor-fluorophore conjugates have emerged as promising theranostic agents, allowing for simultaneous cancer diagnosis and treatment. These conjugates are gaining attention for their ability to visualize malignant tissues and concurrently enhance therapeutic interventions. This review explores the design principles governing the development of multimodal inhibitors, highlighting their potential as platforms for kinase tracking and inhibition via bioimaging. The structural aspects of constructing such theranostic agents are critically analyzed. This work could shed light on this intriguing field and provide adequate impetus for developing novel theranostic compounds based on small molecule inhibitors and fluorophores.

Background: The invasion of glioblastoma cells beyond the visible tumor margin depicted by conventional neuroimaging is believed to mediate recurrence and predict poor survival. Radiomic biomarkers that are associated with the direction and extent of tumor infiltration are, however, non-existent.

Methods: Patients from a single center with newly diagnosed glioblastoma (n = 7) underwent preoperative Q-space magnetic resonance imaging (QSI; 3T, 64 gradient directions, b = 1000 s/mm²) between 2018 and 2019. Tumors were manually segmented, and patterns of inter-voxel coherence spatially intersecting each segmentation were generated to represent tumor-associated tractography. One patient additionally underwent regional biopsy of diffusion tract- versus non-tract-associated tissue during tumor resection for RNA sequencing. Imaging data from this cohort were compared with a historical cohort of n = 66 glioblastoma patients who underwent similar QSI scans. Associations of tractography-derived metrics with survival were assessed using t-tests, linear regression, and Kaplan-Meier statistics. Patient-derived glioblastoma xenograft (PDX) mice generated with the sub-hippocampal injection of human-derived glioblastoma stem cells (GSCs) were scanned under high-field conditions (QSI, 7T, 512 gradient directions), and tumor-associated tractography was compared with the 3D microscopic reconstruction of immunostained GSCs.

Results: In the principal enrollment cohort of patients with glioblastoma, all cases displayed tractography patterns with tumor-intersecting tract bundles extending into brain parenchyma, a phenotype which was reproduced in PDX mice as well as in a larger comparison cohort of glioblastoma patients (n = 66), when applying similar methods. Reconstructed spatial patterns of GSCs in PDX mice closely mirrored tumor-associated tractography. On a Kaplan-Meier survival analysis of n = 66 patients, the calculated intra-tumoral mean diffusivity predicted the overall survival (p = 0.037), as did tractography-associated features including mean tract length (p = 0.039) and mean projecting tract length (p = 0.022). The RNA sequencing of human tissue samples (n = 13 tumor samples from a single patient) revealed the overexpression of transcripts which regulate cell motility in tract-associated samples.

Conclusions: QSI discriminates tumor-specific patterns of inter-voxel coherence believed to represent white matter pathways which may be susceptible to glioblastoma invasion. These findings may lay the groundwork for future work on therapeutic targeting, patient stratification, and prognosis in glioblastoma.

Background: Accurate delineation of tumors and organs at risk (OARs) is crucial for intensity-modulated radiation therapy. This study aimed to evaluate the performance of OncoStudio, an AI-based auto-segmentation tool developed for Korean patients, compared with Protégé AI, a globally developed tool that uses data from Korean cancer patients.

Methods: A retrospective analysis of 1200 Korean cancer patients treated with radiotherapy was conducted. Auto-contours generated via OncoStudio and Protégé AI were compared with manual contours across the head and neck and thoracic, abdominal, and pelvic organs. Accuracy was assessed using the Dice similarity coefficient (DSC), mean surface distance (MSD), and 95% Hausdorff distance (HD). Feedback was obtained from 10 participants, including radiation oncologists, residents, and radiation therapists, via an online survey with a Turing test component.

Results: OncoStudio outperformed Protégé AI in 85% of the evaluated OARs (p < 0.001). For head and neck organs, OncoStudio achieved a similar DSC (0.70 vs. 0.70, p = 0.637) but significantly lower MSD and 95% HD values (p < 0.001). In thoracic organs, OncoStudio performed excellently in 90% of cases, with a significantly greater DSC (male: 0.87 vs. 0.82, p < 0.001; female: 0.95 vs. 0.87, p < 0.001). OncoStudio also demonstrated superior accuracy in abdominal (DSC 0.88 vs. 0.81, p < 0.001) and pelvic organs (male: DSC 0.95 vs. 0.85, p < 0.001; female: DSC 0.82 vs. 0.73, p < 0.001). Clinicians favored OncoStudio in 70% of cases, with 90% endorsing its clinical suitability for Korean patients.

Conclusions: OncoStudio, which is tailored for Korean patients, demonstrated superior segmentation accuracy across multiple anatomical regions, suggesting its suitability for radiotherapy planning in this population.

Artificial intelligence (AI), encompassing several tools and platforms such as artificial "general" intelligence (AGI) and generative artificial intelligence (GenAI), has facilitated cancer research, enhancing productivity in terms of research publications and translational value for cancer patients. AGI tools, such as ChatGPT, assist preclinical and clinical scientists in identifying tumor heterogeneity, predicting therapy outcomes, and streamlining research publications. However, this perspective review also explores the potential of AI's influence on cancer research with regard to its impact on disruptive sciences and discoveries by preclinical and clinical scientists. The increasing reliance on AI tools may compromise biological intelligence, disrupting abstraction, creativity, and critical thinking. This could contribute to the declining trend of disruptive sciences, hindering landmark discoveries and innovations. This perspective review narrates the role of different forms of AI in the potentiation of productive cancer research and the potential disruption of disruptive sciences due to AI's influence.

Background: Non-Small Cell Lung Cancer (NSCLC) remains a challenging disease to manage with effectiveness. Early detection and precise monitoring are crucial for improving patient outcomes. Circulating tumor DNA (ctDNA) offers a non-invasive cancer detection and monitoring method. Emerging biomarkers, such as ctDNA methylation, have shown promise in enhancing diagnostic accuracy and prognostic assessment in NSCLC. In this review, we examined the current evidence regarding ctDNA methylation's role in NSCLC detection through a systematic review of the existing literature and meta-analysis. Methods: We systematically searched PubMed, Medline, Embase, and Web of Science databases up to 26 June 2024 for studies on the role of ctDNA methylation analysis in NSCLC patients. We included studies from 2010 to 2024 on NSCLC patients. We excluded case reports, non-English articles, studies on cell lines or artificial samples, those without cfDNA detection, prognostic studies, and studies with non-extractable data or mixed cancer types. Funnel plots were visually examined for potential publication bias, with a p value < 0.05 indicating bias. Meta-analysis was conducted using R packages (meta, forestplot, and mada). Combined sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR-), positive and negative predictive values, diagnostic odds ratio (DOR), and 95% confidence intervals (95% CI) were calculated. A summary receiver operating characteristic curve (SROC) and area under the curve (AUC) with related Standard Error (SE) were used to evaluate the overall diagnostic performance. Additionally, RASSF1A, APC, SOX17, SEPT9, and RARβ2 were analyzed, since their methylation was assessed in two or more studies. Results: From 38 candidate papers, we finally identified 12 studies, including 472 NSCLC patients. The pooled sensitivity was 0.62 (0.47-0.77) and the specificity was 0.90 (0.85-0.94). The diagnostic odds ratio was 15.6 (95% CI 9.36-26.09) and the area under the curve was 0.249 (SE = 0.138). The positive and negative predictive values were 5.38 (95% CI 3.89-7.44) and 0.34 (95% CI 0.22-0.54), respectively. For single genes, the specificity reached 0.83~0.96, except for RARβ2, but the sensitivity was relatively low for each gene. Significant heterogeneity across the included studies, the potential publication bias for specificity (p = 0.0231), and the need to validate the clinical utility of ctDNA methylation for monitoring treatment response and predicting outcomes in NSCLC patients represent the main limitations of this study. Conclusions: These results provide evidence of the significant potential of ctDNA methylation as a valuable biomarker for improving the diagnosis of NSCLC, advocating for its integration into clinical practice to enhance patient management.

Recent advancements in oncology have led to the development of histology-agnostic therapies, which target genetic alterations irrespective of the tumor's tissue of origin. This review aimed to provide a comprehensive update on the current state of histology-agnostic drug development, focusing on key therapies, including pembrolizumab, larotrectinib, entrectinib, dostarlimab, dabrafenib plus trametinib, selpercatinib, trastuzumab deruxtecan, and reprotrectinib. We performed a detailed analysis of each therapy's mechanism of action, clinical trial outcomes, and associated biomarkers. The review further explores challenges in drug resistance, such as adaptive signaling pathways and neoantigen variability, as well as diagnostic limitations in identifying optimal patient populations. While these therapies have demonstrated efficacy in various malignancies, significant hurdles remain, including intratumoral heterogeneity and resistance mechanisms that diminish treatment effectiveness. We propose considerations for refining trial designs and emerging biomarkers, such as tumor neoantigen burden, to enhance patient selection. These findings illustrate the transformative potential of histology-agnostic therapies in precision oncology but highlight the need for continued research to optimize their use and overcome existing barriers.