Cayce Nawaf

Genomic characterization of sarcomatoid transformation in clear cell renal cell carcinoma

Significance Parts of clear cell renal cell carcinomas (ccRCCs) sometimes have histologic features characteristic of a sarcoma. So-called sarcomatoid tumors are more aggressive, difficult to treat, and associated with a poor prognosis. Their pathogenesis has been uncertain. Through separate exome sequencing of carcinomatous and sarcomatoid components, we show that these components share many somatic mutations, including many in genes characteristic of ccRCC. Sarcomatoid elements had significantly more new somatic mutations, particularly in cancer driver genes, than carcinomatous components. In particular, tumor protein p53, AT-rich interaction domain 1A, and BRCA1 associated protein 1 had sarcomatoid-specific homozygous mutation in 10 tumors and were all mutually exclusive, implicating these genes in sarcomatoid degeneration. The presence of sarcomatoid features in clear cell renal cell carcinoma (ccRCC) confers a poor prognosis and is of unknown pathogenesis. We performed exome sequencing of matched normal-carcinomatous-sarcomatoid specimens from 21 subjects. Two tumors had hypermutation consistent with mismatch repair deficiency. In the remainder, sarcomatoid and carcinomatous elements shared 42% of somatic single-nucleotide variants (SSNVs). Sarcomatoid elements had a higher overall SSNV burden (mean 90 vs. 63 SSNVs, P = 4.0 × 10−4), increased frequency of nonsynonymous SSNVs in Pan-Cancer genes (mean 1.4 vs. 0.26, P = 0.002), and increased frequency of loss of heterozygosity (LOH) across the genome (median 913 vs. 460 Mb in LOH, P < 0.05), with significant recurrent LOH on chromosomes 1p, 9, 10, 14, 17p, 18, and 22. The most frequent SSNVs shared by carcinomatous and sarcomatoid elements were in known ccRCC genes including von Hippel–Lindau tumor suppressor (VHL), polybromo 1 (PBRM1), SET domain containing 2 (SETD2), phosphatase and tensin homolog (PTEN). Most interestingly, sarcomatoid elements acquired biallelic tumor protein p53 (TP53) mutations in 32% of tumors (P = 5.47 × 10−17); TP53 mutations were absent in carcinomatous elements in nonhypermutated tumors and rare in previously studied ccRCCs. Mutations in known cancer drivers AT-rich interaction domain 1A (ARID1A) and BRCA1 associated protein 1 (BAP1) were significantly mutated in sarcomatoid elements and were mutually exclusive with TP53 and each other. These findings provide evidence that sarcomatoid elements arise from dedifferentiation of carcinomatous ccRCCs and implicate specific genes in this process. These findings have implications for the treatment of patients with these poor-prognosis cancers.

Negative Multiparametric Magnetic Resonance Imaging of the Prostate Predicts Absence of Clinically Significant Prostate Cancer on 12-Core Template Prostate Biopsy

OBJECTIVE To determine the negative predictive value of multiparametric magnetic resonance imaging (mpMRI), we evaluated the frequency of prostate cancer detection by 12-core template mapping biopsy in men whose mpMRI showed no suspicious regions. METHODS Six hundred seventy patients underwent mpMRI followed by transrectal ultrasound (TRUS)-guided systematic prostate biopsy from December 2012 to June 2016. Of this cohort, 100 patients had a negative mpMRI. mpMRI imaging sequences included T2-weighted and diffusion-weighted imaging, and dynamic contrast enhancement sequences. RESULTS The mean age, prostate-specific antigen, and prostate volume of the 100 men included were 64.3 years, 7.2 ng/mL, and 71 mL, respectively. Overall cancer detection was 27% (27 of 100). Prostate cancer was detected in 26.3% (10 of 38) of patients who were biopsy-naïve, 12.1% (4 of 33) of patients who had a prior negative biopsy, and in 44.8% (13 of 29) of patients previously on active surveillance; Gleason grade ≥7 was detected in 3% of patients overall (3 of 100). The negative predictive value of a negative mpMRI was 73% for all prostate cancer and 97% for Gleason ≥7 prostate cancer. CONCLUSION There is an approximately 3% chance of detecting clinically significant prostate cancer with systematic TRUS-guided biopsy in patients with no suspicious findings on mpMRI. This information should help guide recommendations to patients about undergoing systematic TRUS-guided biopsy when mpMRI is negative.

Racial disparities in renal cell carcinoma: a single‐payer healthcare experience

Significant racial disparities in survival for renal cell carcinoma (RCC) exist between white and black patients. Differences in access to care and comorbidities are possible contributors. To investigate if racial disparities persist when controlling for access to care, we analyzed data from a single‐payer healthcare system. As part of a case–control study within the Kaiser Permanente Northern California system, pathologic and clinical records were obtained for RCC cases (2152 white, 293 black) diagnosed from 1998 to 2008. Patient demographics, comorbidities, tumor characteristics, and treatment status were compared. Overall survival and disease‐specific survival (DSS) were calculated by the Kaplan–Meier method. A Cox proportion hazards model estimated the independent associations of race, comorbidity, and clinicopathologic variables with DSS. We found that compared to white patients, black patients were diagnosed at a younger age (median 62 vs. 66 years, P < 0.001), were more likely to have papillary RCC (15% vs. 5.2%, P < 0.001), and had similar rates of surgical treatment (78.8% vs. 77.9%, P = 0.764). On multivariate analysis, advanced American Joint Committee on Cancer (AJCC) stage, lack of surgical treatment, larger tumor size, and higher grade were predictors of worse DSS. Race was not an independent predictor of survival. Therefore, we conclude that within a single healthcare system, differences in characteristics of black and white patients with RCC persist; black patients had different comorbidities, were younger, and had decreased tumor stage. However, unlike other series, race was not an independent predictor of DSS, suggesting that survival differences in large registries may result from barriers to healthcare access and/or comorbidity rather than disease biology.

Prostate zonal anatomy correlates with the detection of prostate cancer on multiparametric magnetic resonance imaging/ultrasound fusion–targeted biopsy in patients with a solitary PI-RADS v2–scored lesion

PURPOSE To evaluate the positive predictive value (PPV) of the Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) assessment method in patients with a single suspicious finding on prostate multiparametric magnetic resonance imaging (mpMRI). PATIENTS AND METHODS A total of 176 patients underwent MRI/ultrasound fusion-targeted prostate biopsy after the detection of a single suspicious finding on mpMRI. The PPV for cancer detection was determined based on PI-RADS v2 assessment score and location. RESULTS Fusion biopsy detected prostate cancer in 60.2% of patients. Of these patients, 69.8% had Gleason score (GS) ≥7 prostate cancer. Targeted biopsy detected 90.5% of all GS≥7 prostate cancer. The PPV for GS≥7 detection of PI-RADS v2 category 5 (P5) and category 4 (P4) lesions was 70.2% and 37.7%, respectively. This increased to 88% and 38.5% for P5 and P4 lesions in the peripheral zone (PZ), respectively. Targeted biopsy did not miss GS≥7 disease compared with systematic biopsy in P5 lesions in the PZ and transition zone. CONCLUSION The PPV of PI-RADS v2 for prostate cancer in patients with a single lesion on mpMRI is dependent on PI-RADS assessment category and location. The highest PPV was for a P5 lesion in the PZ.

Learning Non-rigid Deformations for Robust, Constrained Point-based Registration in Image-Guided MR-TRUS Prostate Intervention

HighlightsModel non‐rigid deformations typically encountered when fusing pre‐procedure MR and intra‐procedure TRUS images for image‐guided prostate biopsy.A large database of clinical prostate biopsy interventions is used to train a statistical deformation model (SDM).The SDM prevents the registration process from failing in the presence of prostate gland segmentation errors.Rigorous validation using synthetic data and clinical landmarks demonstrates accurate, reliable, robust, and consistent registration results. Graphical abstract Figure. No Caption available. ABSTRACT Accurate and robust non‐rigid registration of pre‐procedure magnetic resonance (MR) imaging to intra‐procedure trans‐rectal ultrasound (TRUS) is critical for image‐guided biopsies of prostate cancer. Prostate cancer is one of the most prevalent forms of cancer and the second leading cause of cancer‐related death in men in the United States. TRUS‐guided biopsy is the current clinical standard for prostate cancer diagnosis and assessment. State‐of‐the‐art, clinical MR‐TRUS image fusion relies upon semi‐automated segmentations of the prostate in both the MR and the TRUS images to perform non‐rigid surface‐based registration of the gland. Segmentation of the prostate in TRUS imaging is itself a challenging task and prone to high variability. These segmentation errors can lead to poor registration and subsequently poor localization of biopsy targets, which may result in false‐negative cancer detection. In this paper, we present a non‐rigid surface registration approach to MR‐TRUS fusion based on a statistical deformation model (SDM) of intra‐procedural deformations derived from clinical training data. Synthetic validation experiments quantifying registration volume of interest overlaps of the PI‐RADS parcellation standard and tests using clinical landmark data demonstrate that our use of an SDM for registration, with median target registration error of 2.98 mm, is significantly more accurate than the current clinical method. Furthermore, we show that the low‐dimensional SDM registration results are robust to segmentation errors that are not uncommon in clinical TRUS data.

Decision forests for learning prostate cancer probability maps from multiparametric MRI

Objectives: Advances in multiparametric magnetic resonance imaging (mpMRI) and ultrasound/MRI fusion imaging offer a powerful alternative to the typical undirected approach to diagnosing prostate cancer. However, these methods require the time and expertise needed to interpret mpMRI image scenes. In this paper, a machine learning framework for automatically detecting and localizing cancerous lesions within the prostate is developed and evaluated. Methods: Two studies were performed to gather MRI and pathology data. The 12 patients in the first study underwent an MRI session to obtain structural, diffusion-weighted, and dynamic contrast enhanced image vol- umes of the prostate, and regions suspected of being cancerous from the MRI data were manually contoured by radiologists. Whole-mount slices of the prostate were obtained for the patients in the second study, in addition to structural and diffusion-weighted MRI data, for pathology verification. A 3-D feature set for voxel-wise appear- ance description combining intensity data, textural operators, and zonal approximations was generated. Voxels in a test set were classified as normal or cancer using a decision forest-based model initialized using Gaussian discriminant analysis. A leave-one-patient-out cross-validation scheme was used to assess the predictions against the expert manual segmentations confirmed as cancer by biopsy. Results: We achieved an area under the average receiver-operator characteristic curve of 0.923 for the first study, and visual assessment of the probability maps showed 21 out of 22 tumors were identified while a high level of specificity was maintained. In addition to evaluating the model against related approaches, the effects of the individual MRI parameter types were explored, and pathological verification using whole-mount slices from the second study was performed. Conclusions: The results of this paper show that the combination of mpMRI and machine learning is a powerful tool for quantitatively diagnosing prostate cancer.

Bacillus Calmette–Guérin therapy-induced granulomatous prostatitis on multiparametric magnetic resonance imaging: a case report

Multiparametric magnetic resonance imaging (MRI) has emerged as a diagnostic tool for the detection of prostate cancer. Studies have demonstrated a significant correlation between suspicious MRI lesions and positive prostate biopsy.1,2 Intravesical bacillus Calmette–Guérin (BCG) therapy is routinely performed as a treatment for patients with non-muscle invasive bladder cancer, which may result in granulomatous prostatitis (GP) as a side effect.3–5 Currently, the only way to distinguish GP from prostate cancer is by biopsy confirmation.

MRI-US fusion targeted biopsy results in patients with a history of a prior negative biopsy.

90 Background: Patients with an elevated PSA but negative prostate biopsy present a diagnostic and management dilemma. We evaluated the capability of multi-parametric (MP) MRI and MRI-USG Fusion prostate biopsy to detect clinically significant (CS) prostate cancer in men who have had a prior negative 12-core standard biopsy. Methods: Between 12/2012 and 06/2015, 374 men with an indication for prostate biopsy underwent pre-biopsy mpMRI followed by 12-core standard trans-rectal mapping biopsy (Mbx) and MRI-Ultrasound fusion targeted biopsy (Tbx) of lesions identified on mpMRI. The combination of Mbx and Tbx, when both occurred, constitutes a fusion biopsy (Fbx). Men who underwent both Mbx with or without Tbx using the Artemis/Pro-Fuse system with a previous biopsy but no diagnosis of prostate cancer were included. Patients without a lesion on MRI underwent Mbx only. Maximum Gleason scores (GS) was assigned on a per patient basis with Mbx GS available for all patients in the cohort and Tbx GS available only ...

MRI-US fusion targeted biopsy results in men with a history of prior cancer.

88 Background: Appropriate risk stratification of men on active surveillance for prostate cancer is essential to identify men in whom it is safe to take this deferred treatment approach. This study evaluates upstaging rates using MRI-US fusion targeted biopsy in men who have had a prior positive standard 12-core biopsy. Methods: Between 12/2012 and 06/2015, 374 men with an indication for prostate biopsy underwent pre-biopsy mpMRI followed by 12-core standard trans-rectal mapping biopsy (Mbx) and MRI-Ultrasound fusion targeted biopsy (Tbx) of lesions identified on mpMRI. The combination of Mbx and Tbx, when both occurred, constitutes a fusion biopsy (Fbx). Men who underwent both Mbx with or without Tbx using the Artemis/Pro-Fuse system with a previous non-MRI-guided biopsy and a diagnosis of prior Gleason 6 prostate cancer were included. Patients without a lesion on MRI underwent Mbx only. Maximum Gleason scores (GS) were assigned on a per patient basis with Mbx GS available for all patients in the cohort ...

The incidence of adverse pathologic characteristics in small renal masses as size increases.

596 Background: The AUA guidelines include active surveillance (AS) as an option for patients with the cT1a renal mass (≤4 cm). We evaluate how increasing tumor size (≤4 cm) correlates to the incidence of adverse pathologic features (APF) found on nephrectomy. Methods: We queried a single institution database of nephrectomy specimens from subjects undergoing surgery for renal cell carcinoma (RCC). From a total of 898 consecutive cases, 389 patients had primary tumors that were ≤4 cm and N0, M0. All cases were centrally reviewed for the following adverse pathologic features: high nuclear grade (Fuhrman grade 3 or 4), lymphovascular invasion (LVI), histologic tumor necrosis, sarcomatoid features, rhabdoid features, papillary type II histology and advanced stage (≥pT3). Tumor size categories were compared in 1 cm increments. Relationships between the variables were analyzed by chi-square, Fisher’s exact, and ANOVA tests. Results: There was a significant increase in tumor grade (p=0.006) and stage (p=0.04) se...