Multi-omic profiling of clear cell renal cell carcinoma identifies metabolic reprogramming associated with disease progression

Clear cell renal cell carcinoma (ccRCC) is a complex disease with remarkable immune and metabolic heterogeneity. Here we perform genomic, transcriptomic, proteomic, metabolomic and spatial transcriptomic and metabolomic analyses on 100 patients with ccRCC from the Tongji Hospital RCC (TJ-RCC) cohort. Our analysis identifies four ccRCC subtypes including De-clear cell differentiated (DCCD)-ccRCC, a subtype with distinctive metabolic features. DCCD cancer cells are characterized by fewer lipid droplets, reduced metabolic activity, enhanced nutrient uptake capability and a high proliferation rate, leading to poor prognosis. Using single-cell and spatial trajectory analysis, we demonstrate that DCCD is a common mode of ccRCC progression. Even among stage I patients, DCCD is associated with worse outcomes and higher recurrence rate, suggesting that it cannot be cured by nephrectomy alone. Our study also suggests a treatment strategy based on subtype-specific immune cell infiltration that could guide the clinical management of ccRCC.


Statistics
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Reporting on sex and gender
This cohort contained males (n = 63) and females (n = 37), corresponding to the sex distribution of ccRCC.

Reporting on race, ethnicity, or other socially relevant groupings
Race, ethnicity, or other socially relevant information was not involved in this study.

Population characteristics
A total of 100 participants, with an age range of 27-84, were included in this study.This cohort contained males (n = 63) and females (n = 37), corresponding to the gender distribution of ccRCC.Baseline population characteristics of patients with ccRCC are detailed in Supplementary Tables 1.

Recruitment
Histopathological diagnosis was confirmed by at least two different pathologists per sample and only ccRCC cases were included in this sequencing cohort.Informed consent was obtained prior to tissue acquisition.Our cohort included treatment-naive ccRCC patients underwent surgery at Wuhan Tongji Hospital in Jul 2020 and Apr 2021 without intentional selection.

Ethics oversight
Institutional Review Board approval (Tongji Hospital) and informed consent was obtained prior to tissue acquisition and analysis.
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Sample size
Clinical characteristics are summarized in Table S1.No statistical methods were used to predetermine sample size.100 tumors with paired adjacent normal tissues (NATs) were used in whole exon sequencing.Sample size of whole transcriptome sequencing, global proteomics, nontarget metabolomics were 100 tumors and 50 NATs.The quantification of sample sizes employed in these multi-omics analyses was based on existing norms within the discipline, as established by parallel investigations in the realm of solid tumor multi-omics research (PMID: 33577785, 34534465, 33212010).20 out of 100 tumor samples were selected for single nucleic transcriptome (n=10) or 10X multiome (n=10) sequencing based on molecular subtypes.Furthermore, 10 out of these 20 tumors were randomly selected for spatial transcriptome (n=10) and spatial metabolome (n=10) profiles.A paired normal renal cortex and medulla were sequenced by single nucleic transcriptome, spatial transcriptome and spatial metabolome and was used as a normal control.
Data exclusions WES data of 5 NATs failed to pass the quality control and no more tissue was available to sequence once again.Randomization Because all treatment-naive ccRCC patients underwent surgery at Wuhan Tongji Hospital between Jul 2020 and Apr 2021 were involved, acquisition of primary patient tumor samples was not randomized.Samples were randomized by case and control status during RNA isolation or library preparation.Tumor samples involved in single nuclei sequencing and spatial sequencing were randomly selected from 100 cases.

Blinding
Blinding of the tissue was not possible.All analyses were performed in an automated manner across conditions.
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Materials
Hence, paired-tumor samples of these 5 NATs were not involved in SNA and SCNA calling.Instead, we applied GATK germline mutation calling workflow and only select 50 nature portfolio | reporting summary April 2023 most frequent SNAs occured in the other 95 tumors to stat the total mutation rate.ReplicationThe reported findings were replicated across multiple biological samples.Oil red O staining, IHC and immunofluorescenct imaging were performed on 20 different tumor samples and replicated 3 times on each sample.No other experiment was involved.