Computer extracted gland features from H&E predicts prostate cancer recurrence comparably to a genomic companion diagnostic test: a large multi-site study

Existing tools for post-radical prostatectomy (RP) prostate cancer biochemical recurrence (BCR) prognosis rely on human pathologist-derived parameters such as tumor grade, with the resulting inter-reviewer variability. Genomic companion diagnostic tests such as Decipher tend to be tissue destructive, expensive, and not routinely available in most centers. We present a tissue non-destructive method for automated BCR prognosis, termed "Histotyping", that employs computational image analysis of morphologic patterns of prostate tissue from a single, routinely acquired hematoxylin and eosin slide. Patients from two institutions (n = 214) were used to train Histotyping for identifying high-risk patients based on six features of glandular morphology extracted from RP specimens. Histotyping was validated for post-RP BCR prognosis on a separate set of n = 675 patients from five institutions and compared against Decipher on n = 167 patients. Histotyping was prognostic of BCR in the validation set (p < 0.001, univariable hazard ratio [HR] = 2.83, 95% confidence interval [CI]: 2.03-3.93, concordance index [c-index] = 0.68, median years-to-BCR: 1.7). Histotyping was also prognostic in clinically stratified subsets, such as patients with Gleason grade group 3 (HR = 4.09) and negative surgical margins (HR = 3.26). Histotyping was prognostic independent of grade group, margin status, pathological stage, and preoperative prostate-specific antigen (PSA) (multivariable p < 0.001, HR = 2.09, 95% CI: 1.40-3.10, n = 648). The combination of Histotyping, grade group, and preoperative PSA outperformed Decipher (c-index = 0.75 vs. 0.70, n = 167). These results suggest that a prognostic classifier for prostate cancer based on digital images could serve as an alternative or complement to molecular-based companion diagnostic tests

Oncological and Functional Outcomes of Robot-Assisted Radical Prostatectomy in Kidney Transplant Recipients.

ObjectiveManagement of prostate cancer in kidney transplant recipients presents a unique surgical challenge due to the risk of direct or indirect injury to the transplanted kidney. Herein, we report the largest single center study of Robot-assisted Radical prostatectomy (RARP) in kidney transplant recipients.MethodsBetween Jan 2014-2019, 14 kidney transplant recipients with prostate cancer underwent RARP. Clinical and pathological features, perioperative and postoperative complications were retrospectively evaluated. Continence was defined as by patient utilization of zero urinary pads postoperatively.ResultsThe median (IQR) age at RARP was 60.2 (57.8-61.3) years, the interval between kidney transplant and RARP was 8.1 ± 7.5 years. The median (IQR) PSA was 6.9 (4-8.6); 10 of 14 patients had intermediate or high-risk prostate cancer. The median ASA score was 3, the mean (SD) operative time was 129.7 (26.3) minutes, and mean (SD) blood loss was 110 (44.6) ml. All cases were completed robotically, there was no graft loss or injury to transplanted ureter, and the mean length of stay was 1 (0.26) day.Final pathology demonstrated that 42.8% (6/14) of the patients had nonorgan confined disease (pT3a/T3b). 50% (7/14) of the patients were upgraded to higher risk Gleason disease on final surgical pathology. Post-RARP continence rate at 3 months, and 12 months were 45.5% (5/11) and 87.5% (7/8), respectively.ConclusionRARP following kidney transplantation represents a safe and feasible operation which does not appear to compromise oncological or transplant outcomes

Oncological and Functional Outcomes of Robot-Assisted Radical Prostatectomy in Kidney Transplant Recipients.

Management of prostate cancer in kidney transplant recipients presents a unique surgical challenge due to the risk of direct or indirect injury to the transplanted kidney. Herein, we report the largest single center study of Robot-assisted Radical prostatectomy (RARP) in kidney transplant recipients. Between Jan 2014-2019, 14 kidney transplant recipients with prostate cancer underwent RARP. Clinical and pathological features, perioperative and postoperative complications were retrospectively evaluated. Continence was defined as by patient utilization of zero urinary pads postoperatively. The median (IQR) age at RARP was 60.2 (57.8-61.3) years, the interval between kidney transplant and RARP was 8.1 ± 7.5 years. The median (IQR) PSA was 6.9 (4-8.6); 10 of 14 patients had intermediate or high-risk prostate cancer. The median ASA score was 3, the mean (SD) operative time was 129.7 (26.3) minutes, and mean (SD) blood loss was 110 (44.6) ml. All cases were completed robotically, there was no graft loss or injury to transplanted ureter, and the mean length of stay was 1 (0.26) day.Final pathology demonstrated that 42.8% (6/14) of the patients had nonorgan confined disease (pT3a/T3b). 50% (7/14) of the patients were upgraded to higher risk Gleason disease on final surgical pathology. Post-RARP continence rate at 3 months, and 12 months were 45.5% (5/11) and 87.5% (7/8), respectively. RARP following kidney transplantation represents a safe and feasible operation which does not appear to compromise oncological or transplant outcomes

A novel imaging based Nomogram for predicting post-surgical biochemical recurrence and adverse pathology of prostate cancer from pre-operative bi-parametric MRI

Background: We developed and validated an integrated radiomic-clinicopathologic nomogram (RadClip) for post-surgical biochemical recurrence free survival (bRFS) and adverse pathology (AP) prediction in men with prostate cancer (PCa). RadClip was further compared against extant prognostics tools like CAPRA and Decipher. Methods: A retrospective study of 198 patients with PCa from four institutions who underwent pre-operative 3 Tesla MRI followed by radical prostatectomy, between 2009 and 2017 with a median 35-month follow-up was performed. Radiomic features were extracted from prostate cancer regions on bi-parametric magnetic resonance imaging (bpMRI). Cox Proportional-Hazards (CPH) model warped with minimum redundancy maximum relevance (MRMR) feature selection was employed to select bpMRI radiomic features for bRFS prediction in the training set (D1, N = 71). In addition, a bpMRI radiomic risk score (RadS) and associated nomogram, RadClip, were constructed in D1 and then compared against the Decipher, pre-operative (CAPRA), and post-operative (CAPRA-S) nomograms for bRFS and AP prediction in the testing set (D2, N = 127). Findings: "RadClip yielded a higher C-index (0.77, 95% CI 0.65-0.88) compared to CAPRA (0.68, 95% CI 0.57-0.8) and Decipher (0.51, 95% CI 0.33-0.69) and was found to be comparable to CAPRA-S (0.75, 95% CI 0.65-0.85). RadClip resulted in a higher AUC (0.71, 95% CI 0.62-0.81) for predicting AP compared to Decipher (0.66, 95% CI 0.56-0.77) and CAPRA (0.69, 95% CI 0.59-0.79)." Interpretation: RadClip was more prognostic of bRFS and AP compared to Decipher and CAPRA. It could help pre-operatively identify PCa patients at low risk of biochemical recurrence and AP and who therefore might defer additional therapy. Funding: The National Institutes of Health, the U.S. Department of Veterans Affairs, and the Department of Defense. Keywords: Adverse pathology; Biochemical recurrence; MRI; Prognosis; Prostate cancer; Radiomic

Infection-Induced Intestinal Dysbiosis Is Mediated by Macrophage Activation and Nitrate Production

Toxoplasma gondii is a protozoan parasite and a leading cause of foodborne illness. Infection is initiated when the parasite invades the intestinal epithelium, and in many host species, this leads to intense inflammation and a dramatic disruption of the normal microbial ecosystem that resides in the healthy gut (the so-called microbiome). One characteristic change in the microbiome during infection with Toxoplasma—as well as numerous other pathogens—is the overgrowth of Escherichia coli or similar bacteria and a breakdown of commensal containment leading to seeding of peripheral organs with gut bacteria and subsequent sepsis. Our findings provide one clear explanation for how this process is regulated, thereby improving our understanding of the relationship between parasite infection, inflammation, and disease. Furthermore, our results could serve as the basis for the development of novel therapeutics to reduce the potential for harmful bacteria to bloom in the gut during infection.Oral infection of C57BL/6J mice with Toxoplasma gondii results in a marked bacterial dysbiosis and the development of severe pathology in the distal small intestine that is dependent on CD4+ T cells and interferon gamma (IFN-γ). This dysbiosis and bacterial translocation contribute to the development of ileal pathology, but the factors that support the bloom of bacterial pathobionts are unclear. The use of microbial community profiling and shotgun metagenomics revealed that Toxoplasma infection induces a dysbiosis dominated by Enterobacteriaceae and an increased potential for nitrate respiration. In vivo experiments using bacterial metabolic mutants revealed that during this infection, host-derived nitrate supports the expansion of Enterobacteriaceae in the ileum via nitrate respiration. Additional experiments with infected mice indicate that the IFN-γ/STAT1/iNOS axis, while essential for parasite control, also supplies a pool of nitrate that serves as a source for anaerobic respiration and supports overgrowth of Enterobacteriaceae. Together, these data reveal a trade-off in intestinal immunity after oral infection of C57BL/6J mice with T. gondii, in which inducible nitric oxide synthase (iNOS) is required for parasite control, while this host enzyme is responsible for specific modification of the composition of the microbiome that contributes to pathology

Infection-Induced Intestinal Dysbiosis Is Mediated by Macrophage Activation and Nitrate Production.

Oral infection of C57BL/6J mice with Toxoplasma gondii results in a marked bacterial dysbiosis and the development of severe pathology in the distal small intestine that is dependent on CD4+ T cells and interferon gamma (IFN-γ). This dysbiosis and bacterial translocation contribute to the development of ileal pathology, but the factors that support the bloom of bacterial pathobionts are unclear. The use of microbial community profiling and shotgun metagenomics revealed that Toxoplasma infection induces a dysbiosis dominated by Enterobacteriaceae and an increased potential for nitrate respiration. In vivo experiments using bacterial metabolic mutants revealed that during this infection, host-derived nitrate supports the expansion of Enterobacteriaceae in the ileum via nitrate respiration. Additional experiments with infected mice indicate that the IFN-γ/STAT1/iNOS axis, while essential for parasite control, also supplies a pool of nitrate that serves as a source for anaerobic respiration and supports overgrowth of Enterobacteriaceae Together, these data reveal a trade-off in intestinal immunity after oral infection of C57BL/6J mice with T. gondii, in which inducible nitric oxide synthase (iNOS) is required for parasite control, while this host enzyme is responsible for specific modification of the composition of the microbiome that contributes to pathology.IMPORTANCEToxoplasma gondii is a protozoan parasite and a leading cause of foodborne illness. Infection is initiated when the parasite invades the intestinal epithelium, and in many host species, this leads to intense inflammation and a dramatic disruption of the normal microbial ecosystem that resides in the healthy gut (the so-called microbiome). One characteristic change in the microbiome during infection with Toxoplasma-as well as numerous other pathogens-is the overgrowth of Escherichia coli or similar bacteria and a breakdown of commensal containment leading to seeding of peripheral organs with gut bacteria and subsequent sepsis. Our findings provide one clear explanation for how this process is regulated, thereby improving our understanding of the relationship between parasite infection, inflammation, and disease. Furthermore, our results could serve as the basis for the development of novel therapeutics to reduce the potential for harmful bacteria to bloom in the gut during infection

A novel imaging based Nomogram for predicting post-surgical biochemical recurrence and adverse pathology of prostate cancer from pre-operative bi-parametric MRI.

BackgroundWe developed and validated an integrated radiomic-clinicopathologic nomogram (RadClip) for post-surgical biochemical recurrence free survival (bRFS) and adverse pathology (AP) prediction in men with prostate cancer (PCa). RadClip was further compared against extant prognostics tools like CAPRA and Decipher.MethodsA retrospective study of 198 patients with PCa from four institutions who underwent pre-operative 3 Tesla MRI followed by radical prostatectomy, between 2009 and 2017 with a median 35-month follow-up was performed. Radiomic features were extracted from prostate cancer regions on bi-parametric magnetic resonance imaging (bpMRI). Cox Proportional-Hazards (CPH) model warped with minimum redundancy maximum relevance (MRMR) feature selection was employed to select bpMRI radiomic features for bRFS prediction in the training set (D1, N&nbsp;=&nbsp;71). In addition, a bpMRI radiomic risk score (RadS) and associated nomogram, RadClip, were constructed in D1 and then compared against the Decipher, pre-operative (CAPRA), and post-operative (CAPRA-S) nomograms for bRFS and AP prediction in the testing set (D2, N&nbsp;=&nbsp;127).Findings"RadClip yielded a higher C-index (0.77, 95% CI 0.65-0.88) compared to CAPRA (0.68, 95% CI 0.57-0.8) and Decipher (0.51, 95% CI 0.33-0.69) and was found to be comparable to CAPRA-S (0.75, 95% CI 0.65-0.85). RadClip resulted in a higher AUC (0.71, 95% CI 0.62-0.81) for predicting AP compared to Decipher (0.66, 95% CI 0.56-0.77) and CAPRA (0.69, 95% CI 0.59-0.79)."InterpretationRadClip was more prognostic of bRFS and AP compared to Decipher and CAPRA. It could help pre-operatively identify PCa patients at low risk of biochemical recurrence and AP and who therefore might defer additional therapy.FundingThe National Institutes of Health, the U.S. Department of Veterans Affairs, and the Department of Defense

Computationally Derived Cribriform Area Index from Prostate Cancer Hematoxylin and Eosin Images Is Associated with Biochemical Recurrence Following Radical Prostatectomy and Is Most Prognostic in Gleason Grade Group 2

BackgroundThe presence of invasive cribriform adenocarcinoma (ICC), an expanse of cells containing punched-out lumina uninterrupted by stroma, in radical prostatectomy (RP) specimens has been associated with biochemical recurrence (BCR). However, ICC identification has only moderate inter-reviewer agreement.ObjectiveTo investigate quantitative machine-based assessment of the extent and prognostic utility of ICC, especially within individual Gleason grade groups.Design, setting, and participantsA machine learning approach was developed for ICC segmentation using 70 RP patients and validated in a cohort of 749 patients from four sites whose median year of surgery was 2007 and with median follow-up of 28 mo. ICC was segmented on one representative hematoxylin and eosin RP slide per patient and the fraction of tumor area composed of ICC, the cribriform area index (CAI), was measured.Outcome measurements and statistical analysisThe association between CAI and BCR was measured in terms of the concordance index (c index) and hazard ratio (HR).Results and limitationsCAI was correlated with BCR (c index 0.62) in the validation set of 411 patients with ICC morphology, especially those with Gleason grade group 2 cancer (n = 192; c index 0.66), and was less prognostic when patients without ICC were included (c index 0.54). A doubling of CAI in the group with ICC morphology was prognostic after controlling for Gleason grade, surgical margin positivity, preoperative prostate-specific antigen level, pathological T stage, and age (HR 1.19, 95% confidence interval 1.03-1.38; p = 0.018).ConclusionsAutomated image analysis and machine learning could provide an objective, quantitative, reproducible, and high-throughput method of quantifying ICC area. The performance of CAI for grade group 2 cancer suggests that for patients with little Gleason 4 pattern, the ICC fraction has a strong prognostic role.Patient summaryMachine-based measurement of a specific cell pattern (cribriform; sieve-like, with lots of spaces) in images of prostate specimens could improve risk stratification for patients with prostate cancer. In the future, this could help in expanding the criteria for active surveillance

Computer extracted gland features from H&amp;E predicts prostate cancer recurrence comparably to a genomic companion diagnostic test: a large multi-site study.

Existing tools for post-radical prostatectomy (RP) prostate cancer biochemical recurrence (BCR) prognosis rely on human pathologist-derived parameters such as tumor grade, with the resulting inter-reviewer variability. Genomic companion diagnostic tests such as Decipher tend to be tissue destructive, expensive, and not routinely available in most centers. We present a tissue non-destructive method for automated BCR prognosis, termed "Histotyping", that employs computational image analysis of morphologic patterns of prostate tissue from a single, routinely acquired hematoxylin and eosin slide. Patients from two institutions (n = 214) were used to train Histotyping for identifying high-risk patients based on six features of glandular morphology extracted from RP specimens. Histotyping was validated for post-RP BCR prognosis on a separate set of n = 675 patients from five institutions and compared against Decipher on n = 167 patients. Histotyping was prognostic of BCR in the validation set (p &lt; 0.001, univariable hazard ratio [HR] = 2.83, 95% confidence interval [CI]: 2.03-3.93, concordance index [c-index] = 0.68, median years-to-BCR: 1.7). Histotyping was also prognostic in clinically stratified subsets, such as patients with Gleason grade group 3 (HR = 4.09) and negative surgical margins (HR = 3.26). Histotyping was prognostic independent of grade group, margin status, pathological stage, and preoperative prostate-specific antigen (PSA) (multivariable p &lt; 0.001, HR = 2.09, 95% CI: 1.40-3.10, n = 648). The combination of Histotyping, grade group, and preoperative PSA outperformed Decipher (c-index = 0.75 vs. 0.70, n = 167). These results suggest that a prognostic classifier for prostate cancer based on digital images could serve as an alternative or complement to molecular-based companion diagnostic tests