Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

Functional and translational consequences of immunometabolic coevolution in ccRCC

View through CrossRef
Abstract Background Tumor cell phenotypes and anti-tumor immune responses are shaped by local metabolite availability, but intratumoral metabolite heterogeneity (IMH) and its phenotypic consequences remain poorly understood. In vitro mechanistic studies have demonstrated that the anti-tumor activity of lymphoid and myeloid cell populations is mediated by metabolite availability and signaling in the TME, raising the possibility that the immune response and metabolism of ccRCC tumors coevolve and jointly influence the likelihood that a patient responds to therapy.. However, both the broad patterns of coordination between metabolite abundance and TME cellular composition, as well as the precise cell populations producing metabolic phenotypes of interest, remain unknown. Methods To study IMH, we multiregionally profiled the metabolome, transcriptome, and genome of 187 tumor/normal regions from 31 clear cell renal cell carcinoma (ccRCC) patients. Using these measurements and additional multimodal metabolomic/transcriptomic profiling of ccRCC and other diseases, we developed computational models that can be used to understand RNA-metabolite covariation and ultimately impute metabolite levels from RNA sequencing data. Results Analysis of intratumoral metabolite-RNA covariation revealed that the immune composition of the microenvironment, and especially the abundance of myeloid cells, drove intratumoral metabolite variation. Motivated by the strength of RNA-metabolite covariation and the clinical significance of RNA biomarkers in ccRCC, we deployed and benchmarked a machine learning method (MIRTH) to impute metabolite levels directly from RNA sequencing data of primary and metastatic ccRCC tumors. We inferred metabolomic profiles from RNA sequencing data of ccRCC patients enrolled in 6 clinical trials, ultimately identifying specific metabolite biomarkers associated with response to anti-angiogenic agents. Conclusions Local metabolic phenotypes therefore emerge in tandem with the immune microenvironment and associate with therapeutic sensitivity. CDMRP DOD Funding: yes
Title: Functional and translational consequences of immunometabolic coevolution in ccRCC
Description:
Abstract Background Tumor cell phenotypes and anti-tumor immune responses are shaped by local metabolite availability, but intratumoral metabolite heterogeneity (IMH) and its phenotypic consequences remain poorly understood.
In vitro mechanistic studies have demonstrated that the anti-tumor activity of lymphoid and myeloid cell populations is mediated by metabolite availability and signaling in the TME, raising the possibility that the immune response and metabolism of ccRCC tumors coevolve and jointly influence the likelihood that a patient responds to therapy.
However, both the broad patterns of coordination between metabolite abundance and TME cellular composition, as well as the precise cell populations producing metabolic phenotypes of interest, remain unknown.
Methods To study IMH, we multiregionally profiled the metabolome, transcriptome, and genome of 187 tumor/normal regions from 31 clear cell renal cell carcinoma (ccRCC) patients.
Using these measurements and additional multimodal metabolomic/transcriptomic profiling of ccRCC and other diseases, we developed computational models that can be used to understand RNA-metabolite covariation and ultimately impute metabolite levels from RNA sequencing data.
Results Analysis of intratumoral metabolite-RNA covariation revealed that the immune composition of the microenvironment, and especially the abundance of myeloid cells, drove intratumoral metabolite variation.
Motivated by the strength of RNA-metabolite covariation and the clinical significance of RNA biomarkers in ccRCC, we deployed and benchmarked a machine learning method (MIRTH) to impute metabolite levels directly from RNA sequencing data of primary and metastatic ccRCC tumors.
We inferred metabolomic profiles from RNA sequencing data of ccRCC patients enrolled in 6 clinical trials, ultimately identifying specific metabolite biomarkers associated with response to anti-angiogenic agents.
Conclusions Local metabolic phenotypes therefore emerge in tandem with the immune microenvironment and associate with therapeutic sensitivity.
CDMRP DOD Funding: yes.

Related Results

G6PD upregulates Cyclin E1 and MMP9 to promote clear cell renal cell carcinoma progression
G6PD upregulates Cyclin E1 and MMP9 to promote clear cell renal cell carcinoma progression
Abstract Background: Clear cell renal cell carcinoma (ccRCC) is a cell metabolic disease with high metastasis rate and poor prognosis. Our previous studies demonstrate that...
Abstract A54: Potential mechanisms of resistance to targeted agents in human clear cell renal cell carcinoma
Abstract A54: Potential mechanisms of resistance to targeted agents in human clear cell renal cell carcinoma
Abstract Targeted therapy with multiple receptor tyrosine kinase inhibitors (RTKI) has led to a substantial improvement in the standard of care for patients with adv...
Metabolic genes show excellent prognostic ability for clear cell renal cell carcinoma
Metabolic genes show excellent prognostic ability for clear cell renal cell carcinoma
Abstract Background Renal cell carcinoma (RCC) is one of the major malignant tumors of the urinary system, with a high mortality rate and a poor prognosis. Clear cell rena...
Identification of Biomarkers for Prognosis and Immunotherapy in Clear Cell Renal Cell Carcinoma
Identification of Biomarkers for Prognosis and Immunotherapy in Clear Cell Renal Cell Carcinoma
Abstract Background: Clear cell renal cell carcinoma (ccRCC) is the dominating subtype of renal cancer with high malignancy and poor prognosis, accounts for the majority of...
Abstract 1815: Transcriptomic profiling of VHL-dependent long noncoding RNAs in clear cell renal cell carcinoma
Abstract 1815: Transcriptomic profiling of VHL-dependent long noncoding RNAs in clear cell renal cell carcinoma
Abstract INTRODUCTION: Clear cell renal cell carcinoma (ccRCC), the most common subtype of kidney cancer, carries a poor prognosis, with an estimated median overa...
Longitudinal trajectories of immunometabolic marker in various mental disorders and their relationship with brain structures
Longitudinal trajectories of immunometabolic marker in various mental disorders and their relationship with brain structures
Abstract Background: Studies have identified immunometabolic biomarkers for various mental disorders, but their temporal evolution and relationship with brain structure re...

Back to Top