Familial Renal Cancer: Molecular Genetics and Surgical Management

Familial renal cancer (FRC) is a heterogeneous disorder comprised of a variety of subtypes. Each subtype is known to have unique histologic features, genetic alterations, and response to therapy. Through the study of families affected by hereditary forms of kidney cancer, insights into the genetic basis of this disease have been identified. This has resulted in the elucidation of a number of kidney cancer gene pathways. Study of these pathways has led to the development of novel targeted molecular treatments for patients affected by systemic disease. As a result, the treatments for families affected by von Hippel-Lindau (VHL), hereditary papillary renal carcinoma (HPRC), hereditary leiomyomatosis renal cell carcinoma (HLRCC), and Birt-Hogg-Dubé (BHD) are rapidly changing. We review the genetics and contemporary surgical management of familial forms of kidney cancer

Development and validation of circulating CA125 prediction models in postmenopausal women.

BACKGROUND: Cancer Antigen 125 (CA125) is currently the best available ovarian cancer screening biomarker. However, CA125 has been limited by low sensitivity and specificity in part due to normal variation between individuals. Personal characteristics that influence CA125 could be used to improve its performance as screening biomarker. METHODS: We developed and validated linear and dichotomous (≥35 U/mL) circulating CA125 prediction models in postmenopausal women without ovarian cancer who participated in one of five large population-based studies: Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO, n = 26,981), European Prospective Investigation into Cancer and Nutrition (EPIC, n = 861), the Nurses' Health Studies (NHS/NHSII, n = 81), and the New England Case Control Study (NEC, n = 923). The prediction models were developed using stepwise regression in PLCO and validated in EPIC, NHS/NHSII and NEC. RESULT: The linear CA125 prediction model, which included age, race, body mass index (BMI), smoking status and duration, parity, hysterectomy, age at menopause, and duration of hormone therapy (HT), explained 5% of the total variance of CA125. The correlation between measured and predicted CA125 was comparable in PLCO testing dataset (r = 0.18) and external validation datasets (r = 0.14). The dichotomous CA125 prediction model included age, race, BMI, smoking status and duration, hysterectomy, time since menopause, and duration of HT with AUC of 0.64 in PLCO and 0.80 in validation dataset. CONCLUSIONS: The linear prediction model explained a small portion of the total variability of CA125, suggesting the need to identify novel predictors of CA125. The dichotomous prediction model showed moderate discriminatory performance which validated well in independent dataset. Our dichotomous model could be valuable in identifying healthy women who may have elevated CA125 levels, which may contribute to reducing false positive tests using CA125 as screening biomarker

Alkaline Phosphatase Kinetics Predict Metastasis among Prostate Cancer Patients Who Experience Relapse following Radical Prostatectomy

Introduction. Metastasis prostate cancer (CaP) occurs in a small fraction of patients. Improved prognostication of disease progression is a critical challenge. This study examined alkaline phosphatase velocity (APV) in predicting distant metastasis-free survival (DMFS). Materials and Methods. This retrospective cohort study examined CaP patients enrolled in the Center for Prostate Disease Research (CPDR) multicenter national database who underwent RP and experienced BCR (n=1783). BCR was defined as a PSA ≥ 0.2 ng/mL at ≥ 8 weeks post-RP, followed by at least one confirmatory PSA ≥ 0.2 ng/mL or initiation of salvage therapy. APV was computed as the slope of the linear regression line of all alkaline phosphatase (AP) values after BCR and prior to distant metastasis. APV values in the uppermost quartile were defined as “rapid” and compared to the lower three quartiles combined (“slower”). Unadjusted Kaplan Meier (KM) estimation curves and multivariable Cox proportional hazards analysis were used to examine predictors of DMFS. Results. Of the 1783 eligible patients who experienced post-RP BCR, 701 (39.3%) had necessary AP data for APV calculation. PSA doubling time (PSADT) and APV were strongly associated (p=0.008). No differences in APV were observed across race. In KM analysis, significantly poorer DMFS was observed among the rapid versus slower APV group (Log-rank p=0.003). In multivariable analysis, a rapid APV was predictive of a twofold increased probability of DMFS (HR = 2.2; 95% CI = 1.2, 3.9; p = 0.008), controlling for key study covariates. Conclusions. Building on previous work, this study found that rapid APV was a strong predictor of DMFS for a broader group of CaP patients, those who undergo post-RP BCR who were enrolled in a longitudinal cohort with long-term follow-up and equal health care access. APV is worth considering as a complementary clinical factor for predicting DMFS