Project description:Gleason grade group (GG) 5 prostate cancer has been associated with an aggressive natural history, and retrospective data support a role for treatment intensification. However, clinical outcomes remain heterogeneous in this cohort, and intensified treatments carry an increased risk of adverse events. We sought to explore the transcriptomic heterogeneity of GG 5 tumors by querying transcriptomic data from the tumors of 2138 patients with GG 5 disease who underwent prostatectomy. Four distinct consensus clusters were identified with respect to differential transcriptional activation of hallmark pathways, with distinct molecular subtyping profiles and different average genomic risks (AGRs). One cluster, accounting for 325 tumors (15.2% of the population), was enriched for genes related to the cell cycle/proliferation, metabolic pathways, androgen response pathways, and DNA repair, and had a higher AGR than the other clusters (p < 0.001). This clustering, with an identification of a high genomic risk cluster, was subsequently validated in a separate cohort of 1921 patients as well as a third cohort of 201 patients. The latter cohort had outcomes available, and it was found that patients in the high genomic risk cluster had significantly worse distant metastasis-free survival than the other clusters. Tumors in this high genomic risk cluster of GG 5 disease may be particularly likely to benefit from treatment intensification. PATIENT SUMMARY: In this report, we examined differences in gene expression in tumors from men with Gleason grade group 5 prostate cancer. We identified significant diversity, with one specific subgroup of tumors associated with expression profiles that suggest a worse prognosis.
Project description:BackgroundGleason grade group (GG) upgrading is associated with increased biochemical recurrence (BCR), local progression, and decreased cancer-specific survival (CSS) in prostate cancer (PCa). However, descriptions of the risk factors of GG upgrading are scarce. The objective of this study was to identify risk factors and establish a model to predict GG upgrading.MethodsThere were 361 patients with PCa who underwent radical prostatectomy between May 2011 and February 2022 enrolled. Univariate and multivariate logistic regression analyses were identified and nomogram further narrowed down the contributing factors in GG upgrading. The correction curve and decision curve were used to assess the model.ResultsIn the overall cohort, 141 patients had GG upgrading. But the subgroup cohort (GG ≤2) showed that 68 patients had GG upgrading. Multivariate logistic regression analysis showed that in the overall cohort, total prostate-specific antigen (tPSA) ≥10 ng/mL, systemic immune-inflammation index (SII) >379.50, neutrophil-lymphocyte ratio (NLR) >2.13, the GG of biopsy ≥3, the number of positive cores >3 were independent risk factors in GG upgrading. In the cohort of biopsy GG ≤2, multivariate logistic regression showed that the tPSA ≥10 ng/mL, SII >379.50 and the number of positive cores >3 were independent risk factors in GG upgrading. A novel model predicting GG upgrading was established based on these three parameters. The area under the curve (AUC) of the prediction model was 0.759. The C-index of the nomogram was 0.768. The calibration curves of the model showed good predictive performance. Clinical decision curves indicated clinical benefit in the interval of 20% to 90% of threshold probability and good clinical utility.ConclusionsCombined levels of tPSA, SII and the positive biopsy cores distinguish patients with high-risk GG upgrading in the group of biopsy GG ≤2 and are helpful in the decision of treatment plans.
Project description:ObjectivesPelvic lymph nodal regions receive an incidental dose from conformal treatment of the prostate. This study was conducted to investigate the doses received by the different pelvic nodal regions with varying techniques used for prostate radiotherapy.Methods and materialsTwenty patients of high-risk node-negative prostate cancer treated with intensity-modulated radiotherapy to the prostate alone were studied. Replanning was done for intensity-modulated radiotherapy, 3-dimensional conformal treatment, and 2-dimensional conventional radiotherapy with additional delineation of the pelvic nodal regions, namely, common iliac (upper and lower), presacral, internal iliac, obturator, and external iliac. Dose-volume parameters such as Dmean, D100%, D66%, D33%, V40, and V50 to each of the nodal regions were estimated for all patients.ResultsThe obturator nodes received the highest dose among all nodal regions. The mean dose received by obturator nodal region was 44, 29, and 22 Gy from 2-dimensional conventional radiotherapy, 3-dimensional conformal treatment, and intensity-modulated radiotherapy, respectively. The mean dose was significantly higher when compared between 2-dimensional conventional radiotherapy and 3-dimensional conformal treatment ( P < .001), 2-dimensional conventional radiotherapy and intensity-modulated radiotherapy ( P < .001), and 3-dimensional conformal treatment and intensity-modulated radiotherapy ( P < .001). The D33% of the obturator region was 64, 39, and 37 Gy from 2-dimensional conventional radiotherapy, 3-dimensional conformal treatment, and intensity-modulated radiotherapy, respectively. The dose received by all other pelvic nodal regions was low and not clinically relevant.ConclusionThe incidental dose received by obturator regions is significant especially with 2-dimensional conventional radiotherapy and 3-dimensional conformal treatment techniques as used in the trials studying elective pelvic nodal irradiation. However, with intensity-modulated radiotherapy, this dose is lower, making elective pelvic irradiation more relevant. Advances in Knowledge: This study highlights that incidental dose received by obturator regions is significant especially with 2-dimensional conventional radiotherapy and 3-dimensional conformal treatment techniques.
Project description:BackgroundTraditional clinical target volume (CTV) definition for pelvic radiotherapy in prostate cancer consists of large volumes being treated with homogeneous doses without fully utilizing information on the probability of microscopic involvement to guide target volume design and prescription dose distribution.MethodsWe analyzed patterns of nodal involvement in 75 patients that received RT for pelvic and paraaortic lymph node metastases (LNs) from prostate cancer in regard to the new NRG-CTV recommendation. Non-rigid registration-based LN mapping and weighted three-dimensional kernel density estimation were used to visualize the average probability distribution for nodal metastases. As independent approach, the mean relative proportion of LNs observed for each level was determined manually and NRG and non-NRG levels were evaluated for frequency of involvement. Computer-automated distance measurements were used to compare LN distances in individual patients to the spatial proximity of nodal metastases at a cohort level.Results34.7% of patients had pelvic LNs outside NRG-consensus, of which perirectal was most common (25.3% of all patients) followed by left common iliac nodes near the left psoas major (6.7%). A substantial portion of patients (13.3%) had nodes at the posterior edge of the NRG obturator level. Observer-independent mapping consistently visualized high-probability hotspots outside NRG-consensus in the perirectal and left common iliac regions. Affected nodes in individual patients occurred in highly significantly closer proximity than at cohort-level (mean distance, 6.6 cm vs. 8.7 cm, p < 0.001).ConclusionsBased on this analysis, the common iliac level should extend to the left psoas major and obturator levels should extend posteriorly 5 mm beyond the obturator internus. Incomplete coverage by the NRG-consensus was mostly because of perirectal involvement. We introduce three-dimensional kernel density estimation after non-rigid registration-based mapping for the analysis of recurrence data in radiotherapy. This technique provides an estimate of the underlying probability distribution of nodal involvement and may help in addressing institution- or subgroup-specific differences. Nodal metastases in individual patients occurred in highly significantly closer proximity than at a cohort-level, which supports that personalized target volumes could be reduced in size compared to a "one-size-fits-all" approach and is an important basis for further investigation into individualized field designs.
Project description:BackgroundGrade group (GG) 4 prostate cancer (PC) is considered a single entity; however, there are questions regarding prognostic heterogeneity. This study assessed the prognostic differences among various Gleason scores (GSs) classified as GG 4 PC on biopsy before radical prostatectomy (RP).MethodsWe conducted a multicenter retrospective study, and a total of 1791 patients (GS 3 + 5: 190; GS 4 + 4: 1557; and GS 5 + 3: 44) with biopsy GG 4 were included for analysis. Biochemical recurrence (BCR)-free survival, cancer-specific survival, and overall survival were analyzed using the Kaplan-Meier method and the log-rank test. Logistic regression analysis was performed to identify factors associated with high-risk surgical pathologic features. Cox regression models were used to analyze time-dependent oncologic endpoints.ResultsOver a median follow-up of 75 months, 750 patients (41.9%) experienced BCR, 146 (8.2%) died of any causes, and 57 (3.2%) died of PC. Biopsy GS 5 + 3 was associated with significantly higher rates of GS upgrading in RP specimens than GS 3 + 5 and GS 4 + 4. On multivariable analysis adjusted for clinicopathologic features, different GSs within GG 4 were significantly associated with BCR (p = 0.03) but not PC-specific or all-cause mortality. Study limitations include the lack of central pathological specimen evaluation.ConclusionsPatients with GG 4 at biopsy exhibited some limited biological and clinical heterogeneity. Specifically, GS 5 + 3 had an increased risk of GS upgrading. This can help individualize patients' counseling and encourage further study to refine biopsy specimen-based GG classification.
Project description:One of the most precise methods to detect prostate cancer is by evaluation of a stained biopsy by a pathologist under a microscope. Regions of the tissue are assessed and graded according to the observed histological pattern. However, this is not only laborious, but also relies on the experience of the pathologist and tends to suffer from the lack of reproducibility of biopsy outcomes across pathologists. As a result, computational approaches are being sought and machine learning has been gaining momentum in the prediction of the Gleason grade group. To date, machine learning literature has addressed this problem by using features from magnetic resonance imaging images, whole slide images, tissue microarrays, gene expression data, and clinical features. However, there is a gap with regards to predicting the Gleason grade group using DNA sequences as the only input source to the machine learning models. In this work, using whole genome sequence data from South African prostate cancer patients, an application of machine learning and biological experiments were combined to understand the challenges that are associated with the prediction of the Gleason grade group. A series of machine learning binary classifiers (XGBoost, LSTM, GRU, LR, RF) were created only relying on DNA sequences input features. All the models were not able to adequately discriminate between the DNA sequences of the studied Gleason grade groups (Gleason grade group 1 and 5). However, the models were further evaluated in the prediction of tumor DNA sequences from matched-normal DNA sequences, given DNA sequences as the only input source. In this new problem, the models performed acceptably better than before with the XGBoost model achieving the highest accuracy of 74 ± 01, F1 score of 79 ± 01, recall of 99 ± 0.0, and precision of 66 ± 0.1.
Project description:ObjectiveThis study evaluated the prognostic impact of the quality of dose distribution using dosiomics in patients with prostate cancer, stratified by pretreatment prostate-specific antigen (PSA) levels and Gleason grade (GG) group.MethodsA total of 721 patients (Japanese Foundation for Cancer Research [JFCR] cohort: N = 489 and Tokyo Radiation Oncology Clinic [TROC] cohort: N = 232) with localized prostate cancer treated by intensity-modulated radiation therapy were enrolled. Two predictive dosiomic features for biochemical recurrence (BCR) were selected and patients were divided into certain groups stratified by pretreatment PSA levels and GG. Freedom from biochemical failure (FFBF) was estimated using the Kaplan-Meier method based on each dosiomic feature and univariate discrimination was evaluated using the log-rank test. As an exploratory analysis, a dosiomics hazard (DH) score was developed and its prognostic power for BCR was examined.ResultsThe dosiomic feature extracted from planning target volume (PTV) significantly distinguished the high- and low-risk groups in patients with PSA levels >10 ng/mL (7-year FFBF: 86.7% vs 76.1%, P < .01), GG 4 (92.2% vs 76.9%, P < .01), and GG 5 (83.1% vs 77.8%, P = .04). The DH score showed significant association with BCR (hazard score: 2.04; 95% confidence interval: 1.38-3.01; P < .001).ConclusionThe quality of planned dose distribution on PTV may affect the prognosis of patients with poor prognostic factors, such as PSA levels >10 ng/mL and higher GGs.Advances in knowledgeThe effects of planned dose distribution on prognosis differ depending on the patient's clinical background.
Project description:Histopathologic grading of prostate cancer using Gleason patterns (GPs) is subject to a large inter-observer variability, which may result in suboptimal treatment of patients. With the introduction of digitization and whole-slide images of prostate biopsies, computer-aided grading becomes feasible. Computer-aided grading has the potential to improve histopathological grading and treatment selection for prostate cancer. Automated detection of GPs and determination of the grade groups (GG) using a convolutional neural network. In total, 96 prostate biopsies from 38 patients are annotated on pixel-level. Automated detection of GP 3 and GP ≥ 4 in digitized prostate biopsies is performed by re-training the Inception-v3 convolutional neural network (CNN). The outcome of the CNN is subsequently converted into probability maps of GP ≥ 3 and GP ≥ 4, and the GG of the whole biopsy is obtained according to these probability maps. Differentiation between non-atypical and malignant (GP ≥ 3) areas resulted in an accuracy of 92% with a sensitivity and specificity of 90 and 93%, respectively. The differentiation between GP ≥ 4 and GP ≤ 3 was accurate for 90%, with a sensitivity and specificity of 77 and 94%, respectively. Concordance of our automated GG determination method with a genitourinary pathologist was obtained in 65% (κ = 0.70), indicating substantial agreement. A CNN allows for accurate differentiation between non-atypical and malignant areas as defined by GPs, leading to a substantial agreement with the pathologist in defining the GG.
Project description:BackgroundThe role of elective whole-pelvis radiotherapy (WPRT) remains controversial. Few studies have investigated it in Gleason grade group (GG) 5 prostate cancer (PCa), known to have a high risk of nodal metastases.ObjectiveTo assess the impact of WPRT on patients with GG 5 PCa treated with external-beam radiotherapy (EBRT) or EBRT with a brachytherapy boost (EBRT+BT).Design, setting, and participantsWe identified 1170 patients with biopsy-proven GG 5 PCa from 11 centers in the United States and one in Norway treated between 2000 and 2013 (734 with EBRT and 436 with EBRT+BT).Outcome measurements and statistical analysisBiochemical recurrence-free survival (bRFS), distant metastasis-free survival (DMFS), and prostate cancer-specific survival (PCSS) were compared using Cox proportional hazards models with propensity score adjustment.Results and limitationsA total of 299 EBRT patients (41%) and 320 EBRT+BT patients (73%) received WPRT. The adjusted 5-yr bRFS rates with WPRT in the EBRT and EBRT+BT groups were 66% and 88%, respectively. Without WPRT, these rates for the EBRT and EBRT+BT groups were 58% and 78%, respectively. The median follow-up was 5.6yr. WPRT was associated with improved bRFS among patients treated with EBRT+BT (hazard ratio [HR] 0.5, 95% confidence interval [CI] 0.2-0.9, p=0.02), but no evidence for improvement was found in those treated with EBRT (HR 0.8, 95% CI 0.6-1.2, p=0.4). WPRT was not significantly associated with improved DMFS or PCSS in the EBRT group (HR 1.1, 95% CI 0.7-1.7, p=0.8 for DMFS and HR 0.7, 95% CI 0.4-1.1, p=0.1 for PCSS), or in the EBRT+BT group (HR 0.6, 95% CI 0.3-1.4, p=0.2 for DMFS and HR 0.5 95% CI 0.2-1.2, p=0.1 for PCSS).ConclusionsWPRT was not associated with improved PCSS or DMFS in patients with GG 5 PCa who received either EBRT or EBRT+BT. However, WPRT was associated with a significant improvement in bRFS among patients receiving EBRT+BT. Strategies to optimize WPRT, potentially with the use of advanced imaging techniques to identify occult nodal disease, are warranted.Patient summaryWhen men with a high Gleason grade prostate cancer receive radiation with external radiation and brachytherapy, the addition of radiation to the pelvis results in a longer duration of prostate-specific antigen control. However, we did not find a difference in their survival from prostate cancer or in their survival without metastatic disease. We also did not find a benefit for radiation to the pelvis in men who received radiation without brachytherapy.
Project description:PurposeTo our knowledge the ideal methodology of quantifying secondary Gleason pattern 4 in men with Grade Group 2/Gleason score 3 + 4 = 7 on biopsy remains unknown. We compared various methods of Gleason pattern 4 quantification and evaluated associations with adverse pathology findings at radical prostatectomy.Materials and methodsA total of 457 men with Grade Group 2 prostate cancer on biopsy subsequently underwent radical prostatectomy at our institution. Only patients with 12 or more reviewed cores were included in analysis. We evaluated 3 methods of quantifying Gleason pattern 4, including the maximum percent of Gleason pattern 4 in any single core, the overall percent of Gleason pattern 4 (Gleason pattern 4 mm/total cancer mm) and the total length of Gleason pattern 4 in mm across all cores. Adverse pathology features at radical prostatectomy were defined as Gleason score 4 + 3 = 7 or greater (Grade Group 3 or greater), and any extraprostatic extension, seminal vesical invasion and/or lymph node metastasis. A training/test set approach and multivariable logistic regression were used to determine whether Gleason pattern 4 quantification methods could aid in predicting adverse pathology.ResultsOn multivariable analysis all Gleason pattern 4 quantification methods were significantly associated with an increased risk of adverse pathology (p <0.0001) and an increased AUC beyond the base model. The largest AUC increase was 0.044 for the total length of Gleason pattern 4 (AUC 0.728, 95% CI 0.663-0.793). Decision curve analysis demonstrated an increased clinical net benefit with the addition of Gleason pattern 4 quantification to the base model. The total length of Gleason pattern 4 clearly provided the largest net benefit.ConclusionsOur findings support the inclusion of Gleason pattern 4 quantification in the pathology reports and risk prediction models of patients with Grade Group 2/Gleason score 3 + 4 = 7 prostate cancer. The total length of Gleason pattern 4 across all cores provided the strongest benefit to predict adverse pathology features.