Cancers

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: 5-Aminolevulinic acid-guided surgery for adult gliomas has been approved by the European Medicines Agency and the US Food and Drug Administration, becoming a reliable tool for improving gross total resection rates and patient outcomes. This has led several medical centers to explore the off-label use of 5-ALA in the resection of pediatric brain tumors, assessing its efficacy and safety across various tumor types. However, given the differences between children and adults, the appropriateness of 5-ALA use in pediatric populations has not yet been fully established. Methods: We collected eligible publications from Embase, Scopus, PubMed, and Proquest, ultimately selecting 27 studies. Data extraction and retrospective analysis of 249 surgical cases were conducted to determine the current efficacy and safety of 5-ALA in pediatric brain tumors. The fluorescence rate and utility stratified by several clinical features, including WHO grade, tumor classification, and tumor location, were analyzed. Results: Most studies suggest that 5-ALA can enhance tumor identification in high-grade tumors, including glioblastomas and anaplastic astrocytomas. Changes in survival or recurrence rates associated with 5-ALA-guided resection have not been reported. None of the cases reported significant postoperative complications related to the use of 5-ALA. Conclusions: 5-ALA can aid in the resection of high-grade gliomas in pediatric patients. The efficacy of 5-ALA in low-grade gliomas and other tumors may require enhancement with additional tools or modified administration protocols. The safety of 5-ALA has reached a preliminary consensus, although further randomized controlled trials and data on survival and molecular characteristics are needed.

Background: The KRAS G12C mutation, prevalent in various malignancies, including non-small cell lung cancer (NSCLC), represents a unique therapeutic target. Adagrasib and sotorasib, two FDA-approved agents specifically targeting this mutation, have shown promise in clinical trials. This study aims to compare their efficacy in treating KRAS G12C-mutated NSCLC, drawing insights from pivotal clinical trials. Methods: We analyzed data from three key clinical trials: KRYSTAL-1, CodeBreak100, and CodeBreak200. Our methodology involved reconstructing individual patient data from published Kaplan–Meier curves using the IPDfromKM tool (Version 0.1.10). The primary endpoints were progression-free survival (PFS) and overall survival (OS), evaluated through hazard ratios (HRs) and the restricted mean survival time (RMST) method. Results: The HR for PFS favored adagrasib (HR: 0.90 [95% CI: 0.69, 1.19], p = 0.473), suggesting a non-significant trend toward better disease control compared to sotorasib. For OS, the HR was 0.99 [95% CI: 0.75, 1.33] (p = 0.969), indicating no significant difference between the two drugs. RMST analysis supported these findings, with adagrasib showing a consistently higher RMST in PFS at 6, 12, and 18 months. However, OS benefits converged over time, with adagrasib marginally surpassing sotorasib by the 18-month mark. Conclusions: This comprehensive analysis reveals that while adagrasib may offer a slight advantage in PFS, both drugs demonstrate comparable efficacy in OS for KRAS G12C-mutated NSCLC. The subtle differences observed, particularly in PFS, could inform clinical decision-making, emphasizing the need for personalized treatment strategies. Future research should focus on long-term effects and identifying patient subgroups that may benefit more from one drug over the other.

Breast cancer (BCa) poses a severe threat to women’s health worldwide as it is the most frequently diagnosed type of cancer and the primary cause of death for female patients. The biopsy procedure remains the gold standard for accurate and effective diagnosis of BCa. However, its adverse effects, such as invasiveness, bleeding, infection, and reporting time, keep this procedure as a last resort for diagnosis. A mammogram is considered the routine noninvasive imaging-based procedure for diagnosing BCa, mitigating the need for biopsies; however, it might be prone to subjectivity depending on the radiologist’s experience. Therefore, we propose a novel, mammogram image-based BCa explainable AI (BCaXAI) model with a deep learning-based framework for precise, noninvasive, objective, and timely manner diagnosis of BCa. The proposed BCaXAI leverages the Inception-ResNet V2 architecture, where the integration of explainable AI components, such as Grad-CAM, provides radiologists with valuable visual insights into the model’s decision-making process, fostering trust and confidence in the AI-based system. Based on using the DDSM and CBIS-DDSM mammogram datasets, BCaXAI achieved exceptional performance, surpassing traditional models such as ResNet50 and VGG16. The model demonstrated superior accuracy (98.53%), recall (98.53%), precision (98.40%), F1-score (98.43%), and AUROC (0.9933), highlighting its effectiveness in distinguishing between benign and malignant cases. These promising results could alleviate the diagnostic subjectivity that might arise as a result of the experience-variability between different radiologists, as well as minimize the need for repetitive biopsy procedures.

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.

The gut microbiome has emerged as a crucial player in modulating cancer therapies, including radiotherapy. In the case of breast cancer, the interplay between the microbiome and radiotherapy-derived metabolites may enhance therapeutic outcomes and minimize adverse effects. In this review, we explore the bidirectional relationship between the gut microbiome and breast cancer. We explain how gut microbiome composition influences cancer progression and treatment response, and how breast cancer and its treatments influence microbiome composition. A dual role for radiotherapy-derived metabolites is explored in this article, highlighting both their therapeutic benefits and potential hazards. By integrating genomics, metabolomics, and bioinformatics tools, we present a comprehensive overview of these interactions. The study provides real-world insight through case studies and clinical trials, while therapeutic innovations such as probiotics, and dietary interventions are examined for their potential to modulate the microbiome and enhance treatment effectiveness. Moreover, ethical considerations and patient perspectives are discussed, ensuring a comprehensive understanding of the subject. Towards revolutionizing treatment strategies and improving patient outcomes, the review concludes with future research directions. It also envisions integrating microbiome and metabolite research into personalized breast cancer therapy.

Background: Metabolic syndrome increases the risk of developing various systemic cancers. The prevalence of metabolic syndrome in newly diagnosed glioblastoma patients is unknown. Further, there have been contradictory reports about how metabolic syndrome affects clinical outcomes. Therefore, the purpose of this study is to test the hypothesis that metabolic syndrome is associated with an increased prevalence of glioblastoma and worsened survival outcomes. Methods: This retrospective cohort study examines seventy-three patients with isocitrate dehydrogenase (IDH)-wild-type glioblastoma as it provides a relatively homogeneous population to examine. Patient characteristics, vital signs, lab results, tumor molecular markers, and overall survival were analyzed. Patients with metabolic syndrome and individual risk factors were identified, and survival outcomes were examined. Results: Our results demonstrate that there is a higher prevalence of metabolic syndrome in our cohort of patients with glioblastoma than in the general population (41% vs. 33%), though this effect is confounded by older age. We also demonstrate that after correction for confounding variables, metabolic syndrome is not significantly associated with overall survival (p = 0.1). When analyzing individual metabolic risk factors, we demonstrate that there is a significant association between the accumulation of metabolic risk factors and decreased survival (p = 0.03), and hyperglycemia emerges as a significant independent risk factor for decreased survival (p = 0.05). Conclusions: These results suggest that metabolic risk factors can affect survival in patients with glioblastoma, which can have significant implications for clinical practice. These findings need to be further explored through further clinical and mechanistic studies.

Background: Breast cancer (BC) is the most common cancer among women in Palestine, where the need for supportive care frequently goes unmet. Therefore, this study aims to assess the supportive care services provided at the governmental hospitals in the southern area of the West Bank and to determine the factors associated with the unmet needs of these services. Methods: A cross-sectional study was conducted on 362 women with BC. Data were collected using a face-to-face questionnaire that included the Supportive Care Needs Survey (SCNS-SF34), patients’ sociodemographic, economic, and clinical characteristics, as well as familial history of cancer and social support. Results: The study revealed that 61% of participants had unmet supportive care needs, with health system information, physical support, and psychological support being the most unmet needs. Factors contributing to unmet needs included age, marital status, familial support, and a family history of cancer. Chemotherapy and surgery increased the probability of physical care needs by fivefold, while hormone therapy reduced the probability of psychological needs (AOR = 0.36, p < 0.001) and patient care and support needs (AOR = 0.49, p = 0.01). Additionally, radiotherapy reduced sexual care needs by 58% and biological therapy by 60%. Conclusions: There is an urgent need for enhanced supportive care services for BC patients in the West Bank, especially regarding health system information, physical care, and psychological support. Addressing these needs through targeted interventions could significantly improve patients’ quality of life.