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Scientific Reports Jun 2024Prostate cancer is one of the most common and fatal diseases among men, and its early diagnosis can have a significant impact on the treatment process and prevent...
Prostate cancer is one of the most common and fatal diseases among men, and its early diagnosis can have a significant impact on the treatment process and prevent mortality. Since it does not have apparent clinical symptoms in the early stages, it is difficult to diagnose. In addition, the disagreement of experts in the analysis of magnetic resonance images is also a significant challenge. In recent years, various research has shown that deep learning, especially convolutional neural networks, has appeared successfully in machine vision (especially in medical image analysis). In this research, a deep learning approach was used on multi-parameter magnetic resonance images, and the synergistic effect of clinical and pathological data on the accuracy of the model was investigated. The data were collected from Trita Hospital in Tehran, which included 343 patients (data augmentation and learning transfer methods were used during the process). In the designed model, four different types of images are analyzed with four separate ResNet50 deep convolutional networks, and their extracted features are transferred to a fully connected neural network and combined with clinical and pathological features. In the model without clinical and pathological data, the maximum accuracy reached 88%, but by adding these data, the accuracy increased to 96%, which shows the significant impact of clinical and pathological data on the accuracy of diagnosis.
Topics: Humans; Deep Learning; Prostatic Neoplasms; Male; Middle Aged; Aged; Neural Networks, Computer; Magnetic Resonance Imaging; Multiparametric Magnetic Resonance Imaging; Image Processing, Computer-Assisted; Image Interpretation, Computer-Assisted; Iran
PubMed: 38942817
DOI: 10.1038/s41598-024-65354-0 -
Cancer Medicine Jul 2024The Cancer Health Awareness through screeNinG and Education (CHANGE) initiative delivers cancer awareness education with an emphasis on modifiable risk factors and...
BACKGROUND
The Cancer Health Awareness through screeNinG and Education (CHANGE) initiative delivers cancer awareness education with an emphasis on modifiable risk factors and navigation to screening for prostate, breast, and colorectal cancers to residents of public housing communities who experience significant negative social determinants of health.
METHODS
Residents of five communities participated. Community advisory board members were recruited and provided feedback to local environmental change projects, recruitment, and community engagement at each site. At each site, four education sessions were provided by trained facilitators on cancer risk factors and etiology, racial disparities, eligibility for cancer screening, and participation in clinical trials. Attendance, knowledge, attitudes and beliefs about cancer, and height, weight, and waist circumference were measured at baseline and 1-week post-CHANGE sessions.
RESULTS
90 residents (60% 65 and older years old, 33% male, 60% High School education, 93% AA) participated in the program. 95% completed post-intervention evaluation. Participants were eligible for breast (n = 12), prostate (n = 15), and colorectal screening (n = 25) based on American Cancer Society guidelines, and 22 for tobacco cessation; 21 participants accepted navigation assistance for these services. At post-test, participants significantly increased in knowledge and behaviors around obesity/overweight risk for cancer, nutrition, and physical activity. Colorectal, prostate, and breast cancer knowledge scores also increased, but were not significant.
CONCLUSIONS
CHANGE participants demonstrated improved health knowledge and intentions to improve their modifiable health behaviors. Participants reported being motivated and confident in seeking preventive care and satisfaction with community engagement efforts. Replication of this project in similar communities may improve knowledge and health equity among underserved populations.
Topics: Humans; Male; Female; Early Detection of Cancer; Aged; Health Knowledge, Attitudes, Practice; Middle Aged; Health Equity; Prostatic Neoplasms; Health Education; Neoplasms; Breast Neoplasms; Colorectal Neoplasms; Adult; Risk Factors
PubMed: 38940418
DOI: 10.1002/cam4.7357 -
Frontiers in Bioscience (Landmark... Jun 2024Transcription factors (TFs) are essential proteins regulating gene expression by binding to specific nucleotide sequences upstream of genes. Among TF families, the... (Review)
Review
Transcription factors (TFs) are essential proteins regulating gene expression by binding to specific nucleotide sequences upstream of genes. Among TF families, the forkhead box (FOX) proteins, characterized by a conserved DNA-binding domain, play vital roles in various cellular processes, including cancer. The FOXA subfamily, encompassing FOXA1, FOXA2, and FOXA3, stands out for its pivotal role in mammalian development. FOXA1, initially identified in the liver, exhibits diverse expression across multiple organ tissues and plays a critical role in cell proliferation, differentiation, and tumor development. Its structural composition includes transactivation domains and a DNA-binding domain, facilitating its function as a pioneer factor, which is crucial for chromatin interaction and the recruitment of other transcriptional regulators. The involvement of FOXA1 in sex hormone-related tumors underscores its significance in cancer biology. This review provides an overview of multifaceted roles of FOXA1 in normal development and its implications in the pathogenesis of hormone-related cancers, particularly breast cancer and prostate cancer.
Topics: Humans; Hepatocyte Nuclear Factor 3-alpha; Male; Female; Breast Neoplasms; Prostatic Neoplasms; Gonadal Steroid Hormones; Neoplasms; Animals; Gene Expression Regulation, Neoplastic
PubMed: 38940052
DOI: 10.31083/j.fbl2906225 -
Open Veterinary Journal May 2024Canine prostatic carcinoma (cPC) is a urogenital tumour with a poor prognosis, for which no effective treatment has been established. Recently, it has been shown that...
BACKGROUND
Canine prostatic carcinoma (cPC) is a urogenital tumour with a poor prognosis, for which no effective treatment has been established. Recently, it has been shown that human epidermal growth factor receptor type 2 (HER2) is overexpressed in cPC cells; however, the efficacy of HER2-targeted therapy remains unclear.
AIM
Investigate the anti-tumour effect of lapatinib on HER2-positive cPC cell lines.
METHODS
Two cell lines (muPC and bePC) were established from two dogs with cPC and the effects of lapatinib treatment on cell proliferation, apoptosis, and HER2 downstream signalling were investigated. Furthermore, muPC was used to generate tumour-bearing mice, and the anti-tumour effects of lapatinib were examined .
RESULTS
Lapatinib treatment inhibited the proliferation and phosphorylation of Erk1/2 and Akt, which are downstream signals of HER2. Furthermore, the TUNEL assay showed that lapatinib induced apoptosis in both cell lines. The muPC-engrafted nude mouse model showed that lapatinib significantly inhibited tumour growth and increased the area of necrotic tumour tissue compared to the vehicle-treated groups.
CONCLUSION
Lapatinib exerts anti-tumour effects on cPC cells by inhibiting HER-2 signalling.
Topics: Lapatinib; Animals; Dogs; Male; Cell Line, Tumor; Dog Diseases; Prostatic Neoplasms; Antineoplastic Agents; Receptor, ErbB-2; Mice; Mice, Nude; Apoptosis; Cell Proliferation; Quinazolines
PubMed: 38938437
DOI: 10.5455/OVJ.2024.v14.i5.21 -
Journal of Translational Medicine Jun 2024Over the last two decades, tumor-derived RNA expression signatures have been developed for the two most commonly diagnosed tumors worldwide, namely prostate and breast...
BACKGROUND
Over the last two decades, tumor-derived RNA expression signatures have been developed for the two most commonly diagnosed tumors worldwide, namely prostate and breast tumors, in order to improve both outcome prediction and treatment decision-making. In this context, molecular signatures gained by main components of the tumor microenvironment, such as cancer-associated fibroblasts (CAFs), have been explored as prognostic and therapeutic tools. Nevertheless, a deeper understanding of the significance of CAFs-related gene signatures in breast and prostate cancers still remains to be disclosed.
METHODS
RNA sequencing technology (RNA-seq) was employed to profile and compare the transcriptome of CAFs isolated from patients affected by breast and prostate tumors. The differentially expressed genes (DEGs) characterizing breast and prostate CAFs were intersected with data from public datasets derived from bulk RNA-seq profiles of breast and prostate tumor patients. Pathway enrichment analyses allowed us to appreciate the biological significance of the DEGs. K-means clustering was applied to construct CAFs-related gene signatures specific for breast and prostate cancer and to stratify independent cohorts of patients into high and low gene expression clusters. Kaplan-Meier survival curves and log-rank tests were employed to predict differences in the outcome parameters of the clusters of patients. Decision-tree analysis was used to validate the clustering results and boosting calculations were then employed to improve the results obtained by the decision-tree algorithm.
RESULTS
Data obtained in breast CAFs allowed us to assess a signature that includes 8 genes (ITGA11, THBS1, FN1, EMP1, ITGA2, FYN, SPP1, and EMP2) belonging to pro-metastatic signaling routes, such as the focal adhesion pathway. Survival analyses indicated that the cluster of breast cancer patients showing a high expression of the aforementioned genes displays worse clinical outcomes. Next, we identified a prostate CAFs-related signature that includes 11 genes (IL13RA2, GDF7, IL33, CXCL1, TNFRSF19, CXCL6, LIFR, CXCL5, IL7, TSLP, and TNFSF15) associated with immune responses. A low expression of these genes was predictive of poor survival rates in prostate cancer patients. The results obtained were significantly validated through a two-step approach, based on unsupervised (clustering) and supervised (classification) learning techniques, showing a high prediction accuracy (≥ 90%) in independent RNA-seq cohorts.
CONCLUSION
We identified a huge heterogeneity in the transcriptional profile of CAFs derived from breast and prostate tumors. Of note, the two novel CAFs-related gene signatures might be considered as reliable prognostic indicators and valuable biomarkers for a better management of breast and prostate cancer patients.
Topics: Humans; Prostatic Neoplasms; Male; Breast Neoplasms; Female; Cancer-Associated Fibroblasts; Gene Expression Regulation, Neoplastic; Prognosis; Transcriptome; Gene Expression Profiling; Cluster Analysis; Treatment Outcome; Middle Aged; Kaplan-Meier Estimate
PubMed: 38937754
DOI: 10.1186/s12967-024-05413-2 -
Causal relationship between prostatic diseases and prostate cancer: a mendelian randomization study.BMC Cancer Jun 2024Although it is thought that prostatitis or benign prostatic hyperplasia (BPH) is related to prostate cancer (PCa), the underlying causal effects of these diseases are...
BACKGROUND
Although it is thought that prostatitis or benign prostatic hyperplasia (BPH) is related to prostate cancer (PCa), the underlying causal effects of these diseases are unclear.
METHODS
We assessed the causal relationship between prostatitis or BPH and PCa using a two-sample Mendelian randomization (MR) approach. The data utilized in this study were sourced from genome-wide association study. The association of genetic variants from cohorts of prostatitis or BPH and PCa patients was determined using inverse-variance weighted and MR Egger regression techniques. The direction of chance was determined using independent genetic variants with genome-wide significance (P < 5 × 10). The accuracy of the results was confirmed using sensitivity analyses.
RESULTS
MR analysis showed that BPH had a significant causal effect on PCa (Odds Ratio = 1.209, 95% Confidence Interval: 0.098-0.281, P = 5.079 × 10) while prostatitis had no significant causal effect on PCa (P > 0.05). Additionally, the pleiotropic test and leave-one-out analysis showed the two-sample MR analyses were valid and reliable.
CONCLUSIONS
This MR study supports that BPH has a positive causal effect on PCa, while genetically predicted prostatitis has no causal effect on PCa. Nonetheless, further studies should explore the underlying biochemical mechanism and potential therapeutic targets for the prevention of these diseases.
Topics: Humans; Male; Mendelian Randomization Analysis; Prostatic Neoplasms; Genome-Wide Association Study; Prostatic Hyperplasia; Prostatitis; Polymorphism, Single Nucleotide; Genetic Predisposition to Disease
PubMed: 38937672
DOI: 10.1186/s12885-024-12551-9 -
Scientific Reports Jun 2024The prognostic significance of unconventional histology (UH) subtypes including intraductal carcinoma of the prostate (IDC-P), ductal adenocarcinoma, and cribriform...
The prognostic significance of unconventional histology (UH) subtypes including intraductal carcinoma of the prostate (IDC-P), ductal adenocarcinoma, and cribriform pattern has been investigated for prostate cancer (PCa). However, little is known about magnetic resonance imaging (MRI) features and the oncological impact of tumor localization in localized PCa with UH. Clinical data of 211 patients with acinar adenocarcinoma (conventional histology [CH]) and 82 patients with UH who underwent robotic-assisted radical prostatectomy (RARP) were reviewed. Patients with UH are more likely to be older and have higher Gleason grade group, higher Prostate Imaging-Reporting and Data System (PI-RADS) v2.1 score, and larger tumor volume (TV) than those with CH. Multivariate analysis identified the presence of UH as an independent prognostic factor for progression-free survival (PFS) (hazard ration (HR) 2.41, 95% confidence interval (CI) 0.22-0.79, P = 0.0073). No significant difference in PFS was seen regarding tumor localization (transition zone [TZ] or peripheral zone [PZ]) in patients with UH (P = 0.8949), whereas PZ cancer showed shorter PFS in patients with CH (P = 0.0174). PCa with UH was associated with higher progression than PCa with CH among resection margin (RM)-negative cases (P < 0.0001). Further, increased PI-RADS v2.1 score did not correlate with larger TV in UH (P = 0.991), whereas a significant difference in TV was observed in CH (P < 0.0001). The prognostic significance of UH tumor was independent of tumor localization, and shorter PFS was observed even in RM-negative cases, indicating an aggressive subtype with micro-metastatic potential. Furthermore, UH tumors are more likely to harbor a large TV despite PI-RADS v2.1 score ≤ 3. These findings will help optimal perioperative management for PCa with UH.
Topics: Humans; Male; Prostatectomy; Prostatic Neoplasms; Magnetic Resonance Imaging; Aged; Middle Aged; Neoplasm Grading; Prognosis; Retrospective Studies; Prostate; Robotic Surgical Procedures
PubMed: 38937563
DOI: 10.1038/s41598-024-65681-2 -
Scientific Data Jun 2024Bone metastasis is an essential factor affecting the prognosis of prostate cancer (PCa), and circulating tumor cells (CTCs) are closely related to distant tumor...
Bone metastasis is an essential factor affecting the prognosis of prostate cancer (PCa), and circulating tumor cells (CTCs) are closely related to distant tumor metastasis. Here, the protein-protein interaction (PPI) networks and Cytoscape application were used to identify diagnostic markers for metastatic events in PCa. We screened ten hub genes, eight of which had area under the ROC curve (AUC) values > 0.85. Subsequently, we aim to develop a bone metastasis-related model relying on differentially expressed genes in CTCs for accurate risk stratification. We developed an integrative program based on machine learning algorithm combinations to construct reliable bone metastasis-related genes prognostic index (BMGPI). On the basis of BMGPI, we carefully evaluated the prognostic outcomes, functional status, tumor immune microenvironment, somatic mutation, copy number variation (CNV), response to immunotherapy and drug sensitivity in different subgroups. BMGPI was an independent risk factor for disease-free survival in PCa. The high risk group demonstrated poor survival as well as higher immune scores, higher tumor mutation burden (TMB), more frequent co-occurrence mutation, and worse efficacy of immunotherapy. This study highlights a new prognostic signature, the BMGPI. BMGPI is an independent predictor of prognosis in PCa patients and is closely associated with the immune microenvironment and the efficacy of immunotherapy.
Topics: Humans; Algorithms; Biomarkers, Tumor; Bone Neoplasms; Machine Learning; Neoplastic Cells, Circulating; Prognosis; Prostatic Neoplasms; Protein Interaction Maps; Tumor Microenvironment
PubMed: 38937469
DOI: 10.1038/s41597-024-03551-2 -
European Radiology Jun 2024To review the components of past and present active surveillance (AS) protocols, provide an overview of the current studies employing artificial intelligence (AI) in AS... (Review)
Review
OBJECTIVE
To review the components of past and present active surveillance (AS) protocols, provide an overview of the current studies employing artificial intelligence (AI) in AS of prostate cancer, discuss the current challenges of AI in AS, and offer recommendations for future research.
METHODS
Research studies on the topic of MRI-based AI were reviewed to summarize current possibilities and diagnostic accuracies for AI methods in the context of AS. Established guidelines were used to identify possibilities for future refinement using AI.
RESULTS
Preliminary results show the role of AI in a range of diagnostic tasks in AS populations, including the localization, follow-up, and prognostication of prostate cancer. Current evidence is insufficient to support a shift to AI-based AS, with studies being limited by small dataset sizes, heterogeneous inclusion and outcome definitions, or lacking appropriate benchmarks.
CONCLUSION
The AI-based integration of prostate MRI is a direction that promises substantial benefits for AS in the future, but evidence is currently insufficient to support implementation. Studies with standardized inclusion criteria and standardized progression definitions are needed to support this. The increasing inclusion of patients in AS protocols and the incorporation of MRI as a scheduled examination in AS protocols may help to alleviate these challenges in future studies.
CLINICAL RELEVANCE STATEMENT
This manuscript provides an overview of available evidence for the integration of prostate MRI and AI in active surveillance, addressing its potential for clinical optimizations in the context of established guidelines, while highlighting the main challenges for implementation.
KEY POINTS
Active surveillance is currently based on diagnostic tests such as PSA, biopsy, and imaging. Prostate MRI and AI demonstrate promising diagnostic accuracy across a variety of tasks, including the localization, follow-up and risk estimation in active surveillance cohorts. A transition to AI-based active surveillance is not currently realistic; larger studies using standardized inclusion criteria and outcomes are necessary to improve and validate existing evidence.
PubMed: 38937295
DOI: 10.1007/s00330-024-10869-3 -
In Vivo (Athens, Greece) 2024When hormone therapy (HT) is combined with radiotherapy, understanding the recovery of testosterone levels after the end of HT becomes crucial for considering subsequent...
BACKGROUND/AIM
When hormone therapy (HT) is combined with radiotherapy, understanding the recovery of testosterone levels after the end of HT becomes crucial for considering subsequent therapy. The aim of this study was to determine the factors influencing the time to recovery of testosterone levels after discontinuation of HT and the likelihood of recovery.
PATIENTS AND METHODS
The study included a total of 108 patients with prostate cancer who were treated with GnRH agonist in combination with radiotherapy and followed up for at least 12 months after discontinuation of the GnRH agonist. The presence of recovery of testosterone levels and the time to recovery were investigated. Univariate and multivariate analyses were performed on several factors contributing to testosterone recovery, including age at initiation of HT, and the duration of HT.
RESULTS
Testosterone levels recovered in 61 cases (56.5%). The median time to recovery was 14.8 months. There was a significant difference in the recovery of testosterone levels between patients aged ≥71 years and those aged <71 years at the start of HT (p=0.002), and between those who had been on HT for ≥34 months and those for <34 months (p=0.031). In both univariate and multivariate analyses, age at initiation of HT and duration of HT contributed to the recovery of testosterone levels.
CONCLUSION
The rate of recovery of testosterone levels after long-term (median 34.3 months) HT was lower in patients who were older than 71 years at the start of HT.
Topics: Humans; Testosterone; Male; Aged; Prostatic Neoplasms; Middle Aged; Aged, 80 and over; Gonadotropin-Releasing Hormone; Combined Modality Therapy; Treatment Outcome; Antineoplastic Agents, Hormonal
PubMed: 38936898
DOI: 10.21873/invivo.13666