No abstract

SUMMARY Renal cell carcinoma (RCC) is not a single disease, but several histologically defined cancers with different genetic drivers, clinical courses, and therapeutic responses. The current study evaluated 843 RCC from the three major histologic subtypes, including 488 clear cell RCC, 274 papillary RCC, and 81 chromophobe RCC. Comprehensive genomic and phenotypic analysis of the RCC subtypes reveals distinctive features of each subtype that provide the foundation for the development of subtype-specific therapeutic and management strategies for patients affected with these cancers. Somatic alteration of BAP1, PBRM1, and PTEN and altered metabolic pathways correlated with subtype-specific decreased survival, while CDKN2A alteration, increased DNA hypermethylation, and increases in the immune-related Th2 gene expression signature correlated with decreased survival within all major histologic subtypes. CIMP-RCC demonstrated an increased immune signature, and a uniform and distinct metabolic expression pattern identified a subset of metabolically divergent (MD) ChRCC that associated with extremely poor survival.

Immunotherapy holds tremendous promise for improving cancer treatment1. Administering radiotherapy with immunotherapy has been shown to improve immune responses and can elicit an “abscopal effect”2. Unfortunately, response rates for this strategy remain low3. Herein, we report an improved cancer immunotherapy approach that utilizes antigen-capturing nanoparticles (AC-NPs). We engineered several AC-NPs formulations and demonstrated that the set of protein antigens captured by each AC-NP formulation is dependent upon NP surface properties. We showed that AC-NPs deliver tumor specific proteins to antigen-presenting cells and significantly improve the efficacy of αPD-1 treatment using the B16F10 melanoma model, generating up to 20% cure rate as compared to 0% without AC-NPs. Mechanistic studies revealed that AC-NPs induced an expansion of CD8+ cytotoxic T cells and increased both CD4+/Treg and CD8+/Treg ratios. Our work presents a novel strategy for improving cancer immunotherapy with nanotechnology.

In the originally published version of this article, the author list contained two errors. Specifically, David J. Kwiatkowski was misspelled as David J. Kwaitkowski, and William Y. Kim was inadvertently written as William T. Kim. Both names have been corrected online.

We have profiled, for the first time, an evolving human metastatic microenvironment, measuring gene expression, matrisome proteomics, cytokine and chemokine levels, cellularity, ECM organization and biomechanical properties, all on the same sample. Using biopsies of high-grade serous ovarian cancer (HGSOC) metastases that ranged from minimal to extensive disease, we show how non-malignant cell densities and cytokine networks evolve with disease progression. Multivariate integration of the different components allowed us to define for the first time, gene and protein profiles that predict extent of disease and tissue stiffness, whilst also revealing the complexity and dynamic nature of matrisome remodeling during development of metastases. Although we studied a single metastatic site from one human malignancy, a pattern of expression of 22 matrisome genes distinguished patients with a shorter overall survival in ovarian and twelve other primary solid cancers, suggesting that there may be a common matrix response to human cancer.