Chen, Ying‐Bei

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

BACKGROUND: Immune checkpoint inhibitors are an important therapeutic option for urothelial carcinoma, but durable responses are achieved in a minority of patients. Identifying pre-treatment biomarkers that may predict response to these therapies or who exhibit intrinsic resistance, is of paramount importance. OBJECTIVE: To explore the prevalence of PD-L1 copy number alteration in urothelial carcinoma and correlate with response to immune checkpoint inhibitors. METHODS: We analyzed a cohort of 1050 carcinomas of the bladder and upper urinary tract that underwent targeted next generation sequencing, prospectively. We assessed PD-L1 protein expression, copy number status (next generation sequencing/FISH), and detailed treatment response. RESULTS: We identified 9 tumors with PD-L1 amplification and 9 tumors with PD-L1 deletion. PD-L1 protein expression was the highest in PD-L1 amplified tumors. Of the 9 patients whose tumors harbored PD-L1 amplification, 6 received immunotherapy with 4 deriving clinical benefit, and 2 achieving durable response. Of the 9 patients whose tumors had PD-L1 copy number losses, 4 received immunotherapy with 3 experiencing disease progression. CONCLUSIONS: PD-L1 copy number alterations may serve as potential biomarkers of response to immunotherapy in urothelial carcinoma patients, if validated in larger cohorts.

513 Background: Chromophobe renal cell carcinoma (chRCC) is the third most common histologic subtype of kidney cancer. While most of these tumors have an indolent behavior, 7% of patients with chRCC develop metastases, with no currently available standard of care. The Cancer Genome Atlas characterized chRCC, highlighting pathognomonic single copy chromosomal losses of 1, 2, 6, 10, 13 and 17, as well as a minimal mutation burden distinguishing it from all other cancer types. However, only 15% of the analyzed patients had advanced disease. We analyzed metastatic chRCC to further characterize these tumors and elucidate mechanisms leading to aggressive disease using a variety of next generation and whole genome sequencing. Methods: Our cohort of metastatic chRCC consisted of 40 patients with available clinical and pathologic data. Whole genome sequencing (WGS) was performed on 6 patients (4 primary tumors and 2 metastases), 42 additional samples from 33 patients were analyzed using targeted next-generation sequencing (MSK-IMPACT). Notably, we were able to collect and analyze matched primary and metastatic tumors from 7 patients. As control cohort 27 non-metastatic chRCC tumors were sequenced with MSK-IMPACT. Copy number patterns were computed with OncoSNP seq and FACETS. Results: The most commonly mutated genes in the aggressive chRCC tumors were TP53 and PTEN (WGS: TP53 67 %, PTEN 33%; MSK-IMPACT: TP53 61%, PTEN 27%). No other genes were mutated frequently. Primary tumor samples of chRCC did show the typical pattern of chromosomal losses in 1, 2, 6, 10, 13 and 17. Interestingly, these canonical losses could not be detected in the metastases even when accounting for tumor purity. Conclusions: TP53 and PTEN mutations are highly enriched in both primary and metastatic tumors of aggressive chRCC compared to the non-aggressive tumors and likely play a critical role in disease progression. More intriguingly, the observation of differential copy numbers in matched primary and metastatic tumors suggest whole genome or whole chromosome events in these samples. We are currently employing different bioinformatic and cytogenetic platforms to validate our novel hypothesis of chromosomal events as driver for metastatic development in chRCC.