Histologic Growth Patterns in Clear Cell Renal Cell Carcinoma Stratify Patients into Survival Risk Groups.

INTRODUCTION

Genomic and morphologic heterogeneity in clear cell renal cell carcinoma (ccRCC) presents a barrier to prognostication and treatment decisions. Data from pathology are used with clinical markers to predict disease progression after nephrectomy. However, determining the risk of cancer recurrence, and survival with metastatic cancer remains challenging. Recently, analysis of histologic growth patterns (HGP) in ccRCC revealed promising associations with survival outcomes.

METHODS

To investigate whether HGPs can be used to predict overall survival (OS) after nephrectomy, we examined 24 HGPs in primary tumors of 147 patients that included 107 patients with metastatic disease.

RESULTS

The median number of HGPs per case was 5 and was greater in metastatic and larger tumors. After adjustment for 6 pathologic and demographic variables, HGPs were significantly associated with OS post nephrectomy. Small nests, expansile nests and nests with high nuclear to cytoplasmic ratio were associated with favorable outcomes; while spindled low grade, fused nests/solid sheets, rhabdoid, and sarcomatoid patterns were associated with unfavorable outcomes. A 3-tiered and a 2-tiered risk model were developed based on combinations of HGPs. The models performed equally well as WHO/ISUP nucleolar plus necrosis grade (necrosis grade), and better than WHO/ISUP nucleolar grade alone in predicting OS at the median OS of 6 years. Pairwise correlations between HGPs revealed 2 tumor evolutionary branches that differed in risk of metastatic disease: one with mesenchymal differentiation, and other with epithelial tubulopapillary differentiation. While 44 of 107 (41%) patients with metastatic ccRCC displayed evidence of mesenchymal differentiation, mesenchymal features were only observed in 1 of 40 (3%) patients without evidence of metastatic disease.

CONCLUSION

These findings suggest that HGPs may provide a novel path to refine the estimation of OS after nephrectomy and to determine the molecular basis of tumor evolution.