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Featured researches published by James Peterson.


The Journal of Urology | 2012

Succinate Dehydrogenase Kidney Cancer: An Aggressive Example of the Warburg Effect in Cancer

Christopher J. Ricketts; Brian Shuch; Cathy D. Vocke; Adam R. Metwalli; Gennady Bratslavsky; Lindsay A. Middelton; Youfeng Yang; Ming-Hui Wei; Stephen E. Pautler; James Peterson; Catherine A. Stolle; Berton Zbar; Maria J. Merino; Laura S. Schmidt; Peter A. Pinto; Ramaprasad Srinivasan; Karel Pacak; W. Marston Linehan

PURPOSE Recently, a new renal cell cancer syndrome has been linked to germline mutation of multiple subunits (SDHB/C/D) of the Krebs cycle enzyme, succinate dehydrogenase. We report our experience with the diagnosis, evaluation and treatment of this novel form of hereditary kidney cancer. MATERIALS AND METHODS Patients with suspected hereditary kidney cancer were enrolled on a National Cancer Institute institutional review board approved protocol to study inherited forms of kidney cancer. Individuals from families with germline SDHB, SDHC and SDHD mutations, and kidney cancer underwent comprehensive clinical and genetic evaluation. RESULTS A total of 14 patients from 12 SDHB mutation families were evaluated. Patients presented with renal cell cancer at an early age (33 years, range 15 to 62), metastatic kidney cancer developed in 4 and some families had no manifestation other than kidney tumors. An additional family with 6 individuals found to have clear cell renal cell cancer that presented at a young average age (47 years, range 40 to 53) was identified with a germline SDHC mutation (R133X) Metastatic disease developed in 2 of these family members. A patient with a history of carotid body paragangliomas and an aggressive form of kidney cancer was evaluated from a family with a germline SDHD mutation. CONCLUSIONS SDH mutation associated renal cell carcinoma can be an aggressive type of kidney cancer, especially in younger individuals. Although detection and management of early tumors is most often associated with a good outcome, based on our initial experience with these patients and our long-term experience with hereditary leiomyomatosis and renal cell carcinoma, we recommend careful surveillance of patients at risk for SDH mutation associated renal cell carcinoma and wide surgical excision of renal tumors.


Molecular Cancer Research | 2013

A novel germline mutation in BAP1 predisposes to familial clear-cell renal cell carcinoma

Megan N. Farley; Laura S. Schmidt; Jessica Mester; Samuel Peña-Llopis; Andrea Pavia-Jimenez; Alana Christie; Cathy D. Vocke; Christopher J. Ricketts; James Peterson; Lindsay A. Middelton; Lisa N. Kinch; Nick V. Grishin; Maria J. Merino; Adam R. Metwalli; Chao Xing; Xian Jin Xie; Patricia L M Dahia; Charis Eng; W. Marston Linehan; James Brugarolas

Renal cell carcinoma (RCC) clusters in some families. Familial RCC arises from mutations in several genes, including the von Hippel-Lindau (VHL) tumor suppressor, which is also mutated in sporadic RCC. However, a significant percentage of familial RCC remains unexplained. Recently, we discovered that the BRCA1-associated protein-1 (BAP1) gene is mutated in sporadic RCC. The BAP1 gene encodes a nuclear deubiquitinase and appears to be a classic two-hit tumor suppressor gene. Somatic BAP1 mutations are associated with high-grade, clear-cell RCC (ccRCC) and poor patient outcomes. To determine whether BAP1 predisposes to familial RCC, the BAP1 gene was sequenced in 83 unrelated probands with unexplained familial RCC. Interestingly, a novel variant (c.41T>A; p.L14H) was uncovered that cosegregated with the RCC phenotype. The p.L14H variant targets a highly conserved residue in the catalytic domain, which is frequently targeted by missense mutations. The family with the novel BAP1 variant was characterized by early-onset ccRCC, occasionally of high Fuhrman grade, and lacked other features that typify VHL syndrome. These findings suggest that BAP1 is an early-onset familial RCC predisposing gene. Implications: BAP1 mutations may drive tumor development in a subset of patients with inherited renal cell cancer. Mol Cancer Res; 11(9); 1061–71. ©2013 AACR.


Journal of Clinical Oncology | 2014

Defining Early-Onset Kidney Cancer: Implications for Germline and Somatic Mutation Testing and Clinical Management

Brian Shuch; Srinivas Vourganti; Christopher J. Ricketts; Lindsay Middleton; James Peterson; Maria J. Merino; Adam R. Metwalli; Ramaprasad Srinivasan; W. Marston Linehan

PURPOSE Approximately 5% to 8% of renal cell carcinoma (RCC) is hereditary. No guidelines exist for patient selection for RCC germline mutation testing. We evaluate how age of onset could indicate the need for germline mutation testing for detection of inherited forms of kidney cancer. PATIENTS AND METHODS We analyzed the age distribution of RCC cases in the SEER-17 program and in our institutional hereditary kidney cancer population. The age distributions were compared by sex, race, histology, and hereditary cancer syndrome. Models were established to evaluate the specific age thresholds for genetic testing. RESULTS The median age of patients with RCC in SEER-17 was 64 years, with the distribution closely approaching normalcy. Statistical differences were observed by race, sex, and subtype (P < .05). The bottom decile cutoff was ≤ 46 years of age and slightly differed by sex, race, and histology. The mean and median ages at presentation of 608 patients with hereditary kidney cancer were 39.3 years and 37 years, respectively. Although age varied by specific syndrome, 70% of these cases were found to lie at or below the bottom age decile. Modeling age-based genetic testing thresholds demonstrated that the 10th percentile maximized sensitivity and specificity. CONCLUSION Early age of onset might be a sign of hereditary RCC. Even in the absence of clinical manifestations and personal/family history, an age of onset of 46 years or younger should trigger consideration for genetic counseling/germline mutation testing and may serve as a useful cutoff when establishing genetic testing guidelines.


Pattern Recognition | 2009

Renal tumor quantification and classification in contrast-enhanced abdominal CT

Marius George Linguraru; Jianhua Yao; Rabindra Gautam; James Peterson; Zhixi Li; W. Marston Linehan; Ronald M. Summers

Kidney cancer occurs in both a hereditary (inherited) and sporadic (non-inherited) form. It is estimated that almost a quarter of a million people in the USA are living with kidney cancer and their number increases with 51,000 diagnosed with the disease every year. In clinical practice, the response to treatment is monitored by manual measurements of tumor size, which are 2D, do not reflect the 3D geometry and enhancement of tumors, and show high intra- and inter-operator variability. We propose a computer-assisted radiology tool to assess renal tumors in contrast-enhanced CT for the management of tumor diagnoses and responses to new treatments. The algorithm employs anisotropic diffusion (for smoothing), a combination of fast-marching and geodesic level-sets (for segmentation), and a novel statistical refinement step to adapt to the shape of the lesions. It also quantifies the 3D size, volume and enhancement of the lesion and allows serial management over time. Tumors are robustly segmented and the comparison between manual and semi-automated quantifications shows disparity within the limits of inter-observer variability. The analysis of lesion enhancement for tumor classification shows great separation between cysts, von Hippel-Lindau syndrome lesions and hereditary papillary renal carcinomas (HPRC) with p-values inferior to 0.004. The results on temporal evaluation of tumors from serial scans illustrate the potential of the method to become an important tool for disease monitoring, drug trials and noninvasive clinical surveillance.


The Journal of Urology | 2010

Oncological Outcomes of Partial Nephrectomy for Multifocal Renal Cell Carcinoma Greater Than 4 cm

Gopal N. Gupta; James Peterson; Kailash Thakore; Peter A. Pinto; W. Marston Linehan; Gennady Bratslavsky

PURPOSE Despite aggressive screening patients with hereditary renal cancers can present with large multifocal tumors. We present oncological outcomes in patients with hereditary renal cell carcinoma treated with partial nephrectomy for multifocal solid tumors with the largest lesion greater than 4 cm. MATERIALS AND METHODS Between 1995 and 2008 we identified 58 patients with hereditary renal cell carcinoma treated at our institution with partial nephrectomy for solid tumors greater than 4 cm. Data collected included demographic parameters, tumor size, pathological findings and laterality. Overall and metastasis-free survival was calculated based on information from the most recent followup evaluation and imaging. RESULTS The cohort included 41 patients (71%) with von Hippel-Lindau disease, 10 (17%) with Birt-Hogg-Dubé syndrome and 7 (11%) with hereditary papillary renal carcinoma. Mean age was 43.7 years (range 18 to 63) and mean largest tumor size was 5.3 cm (range 4 to 13). A mean of 6.4 kidney tumors (range 1 to 44) was resected. There was a predominance of nuclear grade 2 tumors (51 cases or 85%) and clear cell histology (44 or 73%), followed by papillary type I histology (7 or 11.7%). Overall and metastasis-free survival rates were 93% and 96.5%, respectively, at a median followup of 45 months (range 2 to 163). CONCLUSIONS Metastasis-free and overall survival of our patients is similar to that in the literature of those who undergo partial nephrectomy for T1B tumors in the sporadic population. Multifocality does not affect oncological outcomes at intermediate followup. Partial nephrectomy can be offered to patients with hereditary disease who present with multifocal tumors greater than 4 cm.


Medical Physics | 2011

Automated noninvasive classification of renal cancer on multiphase CT

Marius George Linguraru; Shijun Wang; Furhawn Shah; Rabindra Gautam; James Peterson; W. Marston Linehan; Ronald M. Summers

PURPOSE To explore the added value of the shape of renal lesions for classifying renal neoplasms. To investigate the potential of computer-aided analysis of contrast-enhanced computed-tomography (CT) to quantify and classify renal lesions. METHODS A computer-aided clinical tool based on adaptive level sets was employed to analyze 125 renal lesions from contrast-enhanced abdominal CT studies of 43 patients. There were 47 cysts and 78 neoplasms: 22 Von Hippel-Lindau (VHL), 16 Birt-Hogg-Dube (BHD), 19 hereditary papillary renal carcinomas (HPRC), and 21 hereditary leiomyomatosis and renal cell cancers (HLRCC). The technique quantified the three-dimensional size and enhancement of lesions. Intrapatient and interphase registration facilitated the study of lesion serial enhancement. The histograms of curvature-related features were used to classify the lesion types. The areas under the curve (AUC) were calculated for receiver operating characteristic curves. RESULTS Tumors were robustly segmented with 0.80 overlap (0.98 correlation) between manual and semi-automated quantifications. The method further identified morphological discrepancies between the types of lesions. The classification based on lesion appearance, enhancement and morphology between cysts and cancers showed AUC = 0.98; for BHD + VHL (solid cancers) vs. HPRC + HLRCC AUC = 0.99; for VHL vs. BHD AUC = 0.82; and for HPRC vs. HLRCC AUC = 0.84. All semi-automated classifications were statistically significant (p < 0.05) and superior to the analyses based solely on serial enhancement. CONCLUSIONS The computer-aided clinical tool allowed the accurate quantification of cystic, solid, and mixed renal tumors. Cancer types were classified into four categories using their shape and enhancement. Comprehensive imaging biomarkers of renal neoplasms on abdominal CT may facilitate their noninvasive classification, guide clinical management, and monitor responses to drugs or interventions.


international conference of the ieee engineering in medicine and biology society | 2009

Computer-aided renal cancer quantification and classification from contrast-enhanced CT via histograms of curvature-related features

Marius George Linguraru; Shijun Wang; Furhawn Shah; Rabindra Gautam; James Peterson; W. Marston Linehan; Ronald M. Summers

In clinical practice, renal cancer diagnosis is performed by manual quantifications of tumor size and enhancement, which are time consuming and show high variability. We propose a computer-assisted clinical tool to assess and classify renal tumors in contrast-enhanced CT for the management and classification of kidney tumors. The quantification of lesions used level-sets and a statistical refinement step to adapt to the shape of the lesions. Intra-patient and inter-phase registration facilitated the study of lesion enhancement. From the segmented lesions, the histograms of curvature-related features were used to classify the lesion types via random sampling. The clinical tool allows the accurate quantification and classification of cysts and cancer from clinical data. Cancer types are further classified into four categories. Computer-assisted image analysis shows great potential for tumor diagnosis and monitoring.


Genes, Chromosomes and Cancer | 2017

Comprehensive genomic and phenotypic characterization of germline FH deletion in hereditary leiomyomatosis and renal cell carcinoma

Cathy D. Vocke; Christopher J. Ricketts; Maria J. Merino; Ramaprasad Srinivasan; Adam R. Metwalli; Lindsay A. Middelton; James Peterson; Youfeng Yang; W. Marston Linehan

Hereditary leiomyomatosis and renal cell carcinoma (HLRCC) is a familial cancer syndrome associated with the development of cutaneous and uterine leiomyomas, and an aggressive form of type 2 papillary kidney cancer. HLRCC is characterized by germline mutation of the FH gene. This study evaluated the prevalence and clinical phenotype of FH deletions in HLRCC patients. Patients with phenotypic manifestations consistent with HLRCC who lacked detectable germline FH intragenic mutations were investigated for FH deletion. A series of 28 patients from 13 families were evaluated using a combination of a comparative genomic hybridization (CGH) array and/or CLIA‐approved FH deletion/duplication analyses. Thirteen distinct germline deletions were identified in the 13 UOB families, including 11 complete FH gene deletions and 2 partial FH gene deletions. The size of eight evaluated complete FH deletions varied from ∼4.74 Mb to 249 kb, with all deletions resulting in additional gene losses. Two partial FH gene deletions were identified, with one resulting in loss of exon 1 and the upstream region of the FH gene only. Kidney cancer was diagnosed in 9 (32%) of 28 patients and 7 (54%) of 13 families possessing either complete or partial FH deletions. Cutaneous and uterine leiomyomas were observed at similar rates to those in FH point mutation families. Complete or partial FH gene alterations in HLRCC families are associated with all of the canonical HLRCC manifestations, including type 2 papillary kidney cancer and should be screened for in any patient at‐risk for this disorder.


international symposium on biomedical imaging | 2009

Renal tumor quantification and classification in triple-phase contrast-enhanced abdominal CT

Marius George Linguraru; Rabindra Gautam; James Peterson; Jianhua Yao; W. Marston Linehan; Ronald M. Summers

It is estimated that a quarter of a million people in the USA are living with kidney cancer. In clinical practice, the response to treatment is monitored by manual measurements of tumor size, which are time consuming and show high intra- and inter-operator variability. We propose a computer-assisted radiology tool to assess renal tumors in contrast-enhanced CT for the management of tumor diagnoses and treatments. The algorithm employs anisotropic diffusion, a combination of fast-marching and geodesic level-sets, and a novel statistical refinement step to adapt to the shape of the lesions. It also quantifies the 3D size, volume and enhancement of the lesion and allows serial management of tumors. The comparison between manual and semi-automated quantifications shows disparity within the limits of inter-observer variability. The automated tumor classification shows great separation between cysts, von Hippel-Lindau syndrome (VHL) lesions and hereditary papillary renal carcinomas (HPRC) (p ≪ 0.004).


The Journal of Urology | 2018

PD46-07 GENOTYPE-PHENOTYPE ASSOCIATIONS IN VON HIPPEL-LINDAU

Mark W. Ball; Cathy D. Vocke; Cristiane Leite; James Peterson; Maria J. Merino; Lindsay A. Middelton; Prashant Chittiboina; Kareem A. Zaghloul; Emily Y. Chew; Ashkan A. Malayeri; Adam R. Metwalli; Berton Zbar; Laura S. Schmidt; W. Marston Linehan

RESULTS: Sorafenib/Sunitinib monotherapy, combined or alternating treatment groups demonstrated more significant anti-tumor activity, as compared to Axitinib monotherapy (P<0.05). Most interestingly, the PDX of KI2368, in contrast to KI2367, demonstrated significant anti-tumor activity to Sunitinib monotherapy, Sorafenib and Sunitinib combination and alternating treatment groups, but not to Sorafenib or Axitinib monotherapy (P<0.05). A total of 1725 genes have > 5-fold higher expression levels in KI2367 than in KI2368, including the relevant drug targets: PDGFA, PDGFB and PDGFRA. A total of 994 genes have > 5-fold higher expression in KI2368 than in KI2367. Against human reference genome, 5539 and 5827 protein change variants were respectively found in KI2367 and KI2368, 4023 common variants in both samples. We also found 20 and 4 in-frame gene fusions in KI2367 and KI2368, but no common in-frame fusion was detected. CONCLUSIONS: These results suggest the presence of the intra-tumor molecular heterogeneity in this patient, which could influence the clinical outcome of targeted therapies. Multiple biopsy and genomic analysis of intra-tumor molecular heterogeneity could potentially help guide more effective plan in selecting targeted therapies for ccRCC patients.

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W. Marston Linehan

National Institutes of Health

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Adam R. Metwalli

National Institutes of Health

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Gennady Bratslavsky

National Institutes of Health

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Maria J. Merino

National Institutes of Health

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Peter A. Pinto

National Institutes of Health

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Rabindra Gautam

National Institutes of Health

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Ramaprasad Srinivasan

National Institutes of Health

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Berton Zbar

National Institutes of Health

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Laura S. Schmidt

National Institutes of Health

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Cathy D. Vocke

National Institutes of Health

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