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A wide variety of enzymatic pathways that produce specialized metabolites in bacteria, fungi and plants are known to be encoded in biosynthetic gene clusters. Information about these clusters, pathways and metabolites is currently dispersed throughout the literature, making it difficult to exploit. To facilitate consistent and systematic deposition and retrieval of data on biosynthetic gene clusters, we propose the Minimum Information about a Biosynthetic Gene cluster (MIBiG) data standard.
The spatial configuration of initial partons in high multiplicity proton–proton scatterings at 14 TeV is assumed as three randomly positioned “hot spots”. The parton momentum distribution in the hot spots is calculated by HIJING2.0 with some modifications. This initial condition causes not only large eccentricity ϵ2 but also triangularity ϵ3 and the correlation of ϵ2−ϵ3 event-plane angles. The final elliptic flow v2, triangular flow v3, and the correlation of v2−v3 event-plane angles are calculated by using the parton cascade model BAMPS to simulate the space–time parton evolution. Our results show that the v2−v3 correlation is different from that of ϵ2−ϵ3. This finding indicates that translations of different Fourier components of the initial spatial asymmetry to the final flow components are not independent. A dynamical correlation between the elliptic and triangular flow appears during the collective expansion.
Background: This study aims to test the effect of the 10 most common nonurological primary cancers (skin, rectal, colon, lymphoma, leukemia, pancreas, stomach, esophagus, liver, lung) on overall mortality (OM) after secondary prostate cancer (PCa). Material and Methods: Within the Surveillance, Epidemiology, and End Results (SEER) database, patients with 10 most common primary cancers and concomitant secondary PCa (diagnosed 2004–2016) were identified and were matched in 1:4 fashion (age, year at diagnosis, race/ethnicity, treatment type, TNM stage) with primary PCa controls. OM was compared between secondary and primary PCa patients and was stratified according to primary cancer type, as well as according to time interval between primary cancer vs. secondary PCa diagnoses. Results: We identified 24,848 secondary PCa patients (skin, n = 3,871; rectal, n = 798; colon, n = 3,665; lymphoma, n = 2,583; leukemia, n = 1,102; pancreatic, n = 118; stomach, n = 361; esophagus, n = 219; liver, n = 160; lung, n = 1,328) vs. 531,732 primary PCa patients. Secondary PCa characteristics were less favorable than those of primary PCa patients (PSA and grade), and smaller proportions of secondary PCa patients received active treatment. After 1:4 matching, all secondary PCa exhibited worse OM than primary PCa patients. Finally, subgroup analyses showed that the survival disadvantage of secondary PCa patients decreased with longer time interval since primary cancer diagnosis and subsequent secondary PCa. Conclusion: Patients with secondary PCa are diagnosed with less favorable PSA and grade. Even after matching for PCa characteristics, secondary PCa patients still exhibit worse survival. However, the survival disadvantage is attenuated, when secondary PCa diagnosis is made after longer time interval, since primary cancer diagnosis.
Purpose: To compare Cancer-specific mortality (CSM) in patients with Squamous cell carcinoma (SCC) vs. non-SCC penile cancer, since survival outcomes may differ between histological subtypes. Methods: Within the Surveillance, Epidemiology and End Results database (2004–2016), penile cancer patients of all stages were identified. Temporal trend analyses, cumulative incidence and Kaplan–Meier plots, multivariable Cox regression and Fine and Gray competing-risks regression analyses tested for CSM differences between non-SCC vs. SCC penile cancer patients. Results: Of 4,120 eligible penile cancer patients, 123 (3%) harbored non-SCC vs. 4,027 (97%) SCC. Of all non-SCC patients, 51 (41%) harbored melanomas, 42 (34%) basal cell carcinomas, 10 (8%) adenocarcinomas, eight (6.5%) skin appendage malignancies, six (5%) epithelial cell neoplasms, two (1.5%) neuroendocrine tumors, two (1.5%) lymphomas, two (1.5%) sarcomas. Stage at presentation differed between non-SCC vs. SCC. In temporal trend analyses, non-SCC diagnoses neither decreased nor increased over time (p > 0.05). After stratification according to localized, locally advanced, and metastatic stage, no CSM differences were observed between non-SCC vs. SCC, with 5-year survival rates of 11 vs 11% (p = 0.9) for localized, 33 vs. 37% (p = 0.4) for locally advanced, and 1-year survival rates of 37 vs. 53% (p = 0.9) for metastatic penile cancer, respectively. After propensity score matching for patient and tumor characteristics and additional multivariable adjustment, no CSM differences between non-SCC vs. SCC were observed. Conclusion: Non-SCC penile cancer is rare. Although exceptions exist, on average, non-SCC penile cancer has comparable CSM as SCC penile cancer patients, after stratification for localized, locally invasive, and metastatic disease.
Purpose: To compare Cancer-specific mortality (CSM) in patients with Squamous cell carcinoma (SCC) vs. non-SCC penile cancer, since survival outcomes may differ between histological subtypes. Methods: Within the Surveillance, Epidemiology and End Results database (2004–2016), penile cancer patients of all stages were identified. Temporal trend analyses, cumulative incidence and Kaplan–Meier plots, multivariable Cox regression and Fine and Gray competing-risks regression analyses tested for CSM differences between non-SCC vs. SCC penile cancer patients. Results: Of 4,120 eligible penile cancer patients, 123 (3%) harbored non-SCC vs. 4,027 (97%) SCC. Of all non-SCC patients, 51 (41%) harbored melanomas, 42 (34%) basal cell carcinomas, 10 (8%) adenocarcinomas, eight (6.5%) skin appendage malignancies, six (5%) epithelial cell neoplasms, two (1.5%) neuroendocrine tumors, two (1.5%) lymphomas, two (1.5%) sarcomas. Stage at presentation differed between non-SCC vs. SCC. In temporal trend analyses, non-SCC diagnoses neither decreased nor increased over time (p > 0.05). After stratification according to localized, locally advanced, and metastatic stage, no CSM differences were observed between non-SCC vs. SCC, with 5-year survival rates of 11 vs 11% (p = 0.9) for localized, 33 vs. 37% (p = 0.4) for locally advanced, and 1-year survival rates of 37 vs. 53% (p = 0.9) for metastatic penile cancer, respectively. After propensity score matching for patient and tumor characteristics and additional multivariable adjustment, no CSM differences between non-SCC vs. SCC were observed. Conclusion: Non-SCC penile cancer is rare. Although exceptions exist, on average, non-SCC penile cancer has comparable CSM as SCC penile cancer patients, after stratification for localized, locally invasive, and metastatic disease.
Background: To test the effect of urological primary cancers (bladder, kidney, testis, upper tract, penile, urethral) on overall mortality (OM) after secondary prostate cancer (PCa). Methods: Within the Surveillance, Epidemiology and End Results (SEER) database, patients with urological primary cancers and concomitant secondary PCa (diagnosed 2004-2016) were identified and were matched in 1:4 fashion with primary PCa controls. OM was compared between secondary and primary PCa patients and stratified according to primary urological cancer type, as well as to time interval between primary urological cancer versus secondary PCa diagnoses. Results: We identified 5,987 patients with primary urological and secondary PCa (bladder, n = 3,287; kidney, n = 2,127; testis, n = 391; upper tract, n = 125; penile, n = 47; urethral, n = 10) versus 531,732 primary PCa patients. Except for small proportions of Gleason grade group and age at diagnosis, PCa characteristics between secondary and primary PCa were comparable. Conversely, proportions of secondary PCa patients which received radical prostatectomy were smaller (29.0 vs. 33.5%), while no local treatment rates were higher (34.2 vs. 26.3%). After 1:4 matching, secondary PCa patients exhibited worse OM than primary PCa patients, except for primary testis cancer. Here, no OM differences were recorded. Finally, subgroup analyses showed that the survival disadvantage of secondary PCa patients decreased with longer time interval since primary cancer diagnosis. Conclusions: After detailed matching for PCa characteristics, secondary PCa patients exhibit worse survival, except for testis cancer patients. The survival disadvantage is attenuated, when secondary PCa diagnosis is made after longer time interval, since primary urological cancer diagnosis.
Aim: To compare overall mortality (OM), cancer-specific mortality (CSM), and other cause mortality (OCM) rates between radical prostatectomy (RP) versus radiotherapy (RT) in clinical node-positive (cN1) prostate cancer (PCa).
Materials and Methods: Within Surveillance, Epidemiology, End Results (SEER) (2004–2016), we identified 4685 cN1 PCa patients, of whom 3589 (76.6%) versus 1096 (24.4%) were treated with RP versus RT. After 1:1 propensity score matching (PSM), Kaplan–Meier plots and Cox regression models tested the effect of RP versus RT on OM, while cumulative incidence plots and competing-risks regression (CRR) models addressed CSM and OCM between RP and RT patients. All analyses were repeated after the inverse probability of treatment weighting (IPTW). For CSM and OCM analyses, the propensity score was used as a covariate in the regression model.
Results: Overall, RT patients were older, harbored higher prostate-specific antigen values, higher clinical T and higher Gleason grade groups. PSM resulted in two equally sized groups of 894 RP versus 894 RT patients. After PSM, 5-year OM, CSM, and OCM rates were, respectively, 15.4% versus 25%, 9.3% versus 17%, and 6.1% versus 8% for RP versus RT (all p < 0.001) and yielded respective multivariate hazard ratios (HRs) of 0.63 (0.52–0.78, p < 0.001), 0.66 (0.52–0.86, p < 0.001), 0.71 (0.5–1.0, p = 0.05), all favoring RP. After IPTW, Cox regression models yielded HR of 0.55 (95% confidence interval [CI] = 0.46–0.66) for OM, and CRR yielded HRs of 0.49 (0.34–0.70) and 0.54 (0.36–0.79) for, respectively, CSM and OCM, all favoring RP (all p < 0.001).
Conclusions: RP may hold a CSM advantage over RT in cN1 PCa patients.
Purpose: We assessed contemporary incidence rates and trends of primary urethral cancer.
Methods: We identified urethral cancer patients within Surveillance, Epidemiology and End Results registry (SEER, 2004–2016). Age-standardized incidence rates per 1,000,000 (ASR) were calculated. Log linear regression analyses were used to compute average annual percent change (AAPC).
Results: From 2004 to 2016, 1907 patients with urethral cancer were diagnosed (ASR 1.69; AAPC: -0.98%, p = 0.3). ASR rates were higher in males than in females (2.70 vs. 0.55), respectively and did not change over the time (both p = 0.3). Highest incidence rates were recorded in respectively ≥75 (0.77), 55–74 (0.71) and ≤54 (0.19) years of age categories, in that order. African Americans exhibited highest incidence rate (3.33) followed by Caucasians (1.72), other race groups (1.57) and Hispanics (1.57), in that order. A significant decrease occurred over time in Hispanics, but not in other race groups. In African Americans, male and female sex-stratified incidence rates were higher than in any other race group. Urothelial histological subtype exhibited highest incidence rate (0.92), followed by squamous cell carcinoma (0.41), adenocarcinoma (0.29) and other histologies (0.20). In stage stratified analyses, T1N0M0 stage exhibited highest incidence rate. However, it decreased over time (−3.00%, p = 0.02) in favor of T1-4N1-2M0 stage (+ 2.11%, p = 0.02).
Conclusion: Urethral cancer is rare. Its incidence rates are highest in males, elderly patients, African Americans and in urothelial histological subtype. Most urethral cancer cases are T1N0M0, but over time, the incidence of T1N0M0 decreased in favor of T1-4N1-2M0.
Background: The most recent overall survival (OS) and adverse event (AE) data have not been compared for the three guideline-recommended high-risk non-metastatic castration-resistant prostate cancer (nmCRPC) treatment alternatives.
Methods: We performed a systematic review and network meta-analysis focusing on OS and AE according to the most recent apalutamide, enzalutamide, and darolutamide reports. We systematically examined and compared apalutamide vs. enzalutamide vs. darolutamide efficacy and toxicity, relative to ADT according to PRISMA. We relied on PubMed search for most recent reports addressing prospective randomized trials with proven predefined OS benefit, relative to ADT: SPARTAN, PROSPER, and ARAMIS. OS represented the primary outcome and AEs represented secondary outcomes.
Results: Overall, data originated from 4117 observations made within the three trials that were analyzed. Regarding OS benefit relative to ADT, darolutamide ranked first, followed by enzalutamide and apalutamide, in that order. In the subgroup of PSA-doubling time (PSA-DT) ≤ 6 months patients, enzalutamide ranked first, followed by darolutamide and apalutamide in that order. Conversely, in the subgroup of PSA-DT 6–10 months patients, darolutamide ranked first, followed by apalutamide and enzalutamide, in that order. Regarding grade 3+ AEs, darolutamide was most favorable, followed by enzalutamide and apalutamide, in that order.
Conclusion: The current network meta-analysis suggests the highest OS efficacy and lowest grade 3+ toxicity for darolutamide. However, in the PSA-DT ≤ 6 months subgroup, the highest efficacy was recorded for enzalutamide. It is noteworthy that study design, study population, and follow-up duration represent some of the potentially critical differences that distinguish between the three studies and remained statistically unaccounted for using the network meta-analysis methodology. Those differences should be strongly considered in the interpretation of the current and any network meta-analyses.
Background: To test the effect of urological primary cancers (bladder, kidney, testis, upper tract, penile, urethral) on overall mortality (OM) after secondary prostate cancer (PCa). Methods: Within the Surveillance, Epidemiology and End Results (SEER) database, patients with urological primary cancers and concomitant secondary PCa (diagnosed 2004-2016) were identified and were matched in 1:4 fashion with primary PCa controls. OM was compared between secondary and primary PCa patients and stratified according to primary urological cancer type, as well as to time interval between primary urological cancer versus secondary PCa diagnoses. Results: We identified 5,987 patients with primary urological and secondary PCa (bladder, n = 3,287; kidney, n = 2,127; testis, n = 391; upper tract, n = 125; penile, n = 47; urethral, n = 10) versus 531,732 primary PCa patients. Except for small proportions of Gleason grade group and age at diagnosis, PCa characteristics between secondary and primary PCa were comparable. Conversely, proportions of secondary PCa patients which received radical prostatectomy were smaller (29.0 vs. 33.5%), while no local treatment rates were higher (34.2 vs. 26.3%). After 1:4 matching, secondary PCa patients exhibited worse OM than primary PCa patients, except for primary testis cancer. Here, no OM differences were recorded. Finally, subgroup analyses showed that the survival disadvantage of secondary PCa patients decreased with longer time interval since primary cancer diagnosis. Conclusions: After detailed matching for PCa characteristics, secondary PCa patients exhibit worse survival, except for testis cancer patients. The survival disadvantage is attenuated, when secondary PCa diagnosis is made after longer time interval, since primary urological cancer diagnosis.
