Yoo, A. | bioRxiv Science

bioRxiv2021

Genomic and Metabolic Hallmarks of SDH- and FH-Deficient Renal Cell Carcinomas

PurposeSuccinate dehydrogenase-deficient and fumarate hydratase-deficient renal cell carcinomas (SDHRCC and FHRCC) are rare kidney cancers driven by loss of metabolically proximal enzymes. We sought to define and compare the genomic and metabolomic hallmarks of these entities. Experimental DesignWe analyzed SDHRCC and FHRCC tumors with either immunohistochemical evidence of loss of protein expression or genomically-confirmed biallelic inactivation of SDHA/B/C/D/AF2 or FH. Somatic alterations were identified using clinical pipelines, and allele-specific copy number changes were identified using FACETS. Mass-spectrometry-based metabolomic profiling was performed on available SDHRCC and FHRCC tumors. ResultsForty two patients were analyzed (25 FHRCC, 17 SDHRCC). In the germline analysis, 16/17 SDHRCC harbored a germline alteration in SDHB, whereas only 17/22 FHRCC had pathogenic germline FH variants. SDHRCC had a lower mutation burden (p = 0.02) and copy number alteration burden (p = 0.0002) than FHRCC. All SDHRCC presented with deletion of chromosome 1p (overlapping SDHB), whereas FHRCC demonstrated high but not ubiquitous loss of 1q (FH locus). Both SDHRCC and FHRCC demonstrated significant, idiopathic accumulation of the metabolite guanine. FHRCC tumors had elevated levels of urea cycle metabolites (argininosuccinate, citrulline, and fumarate), whereas SDHRCC had elevation of numerous acylcarnitines. These characteristic metabolic changes enabled the identification of a previously unrecognized SDH-deficient RCC. ConclusionDespite sharing similar genetic etiology, SDHRCC and FHRCC represent distinct molecular entities with unique genetic and metabolic abnormalities. Translational RelevanceMutations to the TCA cycle enzymes Succinate Dehydrogenase (SDH) and Fumarate Hydratase (FH) predispose individuals to unique subtypes of renal cell carcinoma (SDHRCC and FHRCC, respectively). Defining the genetic and metabolic hallmarks of these diseases is critical for advancing new diagnostic and therapeutic approaches for these rare but biologically intriguing entities. Despite a superficially similar genetic etiology, SDHRCC and FHRCC demonstrated significantly fewer secondary mutations to other cancer-associated genes and copy number aberrations than FHRCC, and was distinguished by universal loss-of-heterozygosity of chromosome 1p. Metabolomic analysis identified pathways disrupted in both SDHRCC and FHRCC, including the massive accumulation of free guanine, as well as pathways uniquely disrupted in each of the two entities. These metabolomic findings enabled the identification of a previously unidentified case of unclassified RCC with SDH deficiency, suggesting that metabolomic profiling may aid in phenotypic classification of tumors and uncover novel therapeutic targets.

cancer biology↗

bioRxiv2021

Resource-efficient pooled sequencing expands translational impact in solid tumors

Intratumoral genetic heterogeneity (ITH) poses a significant challenge to utilizing sequencing for decision making in the management of cancer. Although sequencing of multiple tumor regions can address the pitfalls of ITH, it does so at a significant increase in cost and resource utilization. We propose a pooled multiregional sequencing strategy, whereby DNA aliquots from multiple tumor regions are mixed prior to sequencing, as a cost-effective strategy to boost translational value by addressing ITH while preserving valuable residual tissue for secondary analysis. Focusing on kidney cancer, we demonstrate that DNA pooling from as few as two regions significantly increases mutation detection while reducing clonality misattribution. This leads to an increased fraction of patients identified with therapeutically actionable mutations, improved patient risk stratification, and improved inference of evolutionary trajectories with an accuracy comparable to bona fide multiregional sequencing. The same approach applied to non-small-cell lung cancer data substantially improves tumor mutational burden (TMB) detection. Our findings demonstrate that pooled DNA sequencing strategies are a cost-effective alternative to address intrinsic genetic heterogeneity in clinical settings.

genomics↗

bioRxiv2021

Joint representation of working memory and uncertainty in human cortex

Neural representations of visual working memory (VWM) are noisy, and thus, decisions based on VWM are inevitably subject to uncertainty. However, the mechanisms by which the brain simultaneously represents the content and uncertainty of memory remain largely unknown. Here, inspired by the theory of probabilistic population codes, we test the hypothesis that the human brain represents an item maintained in VWM as a probability distribution over stimulus feature space, thereby capturing both its content and uncertainty. We used a neural generative model to decode probability distributions over memorized locations from fMRI activation patterns. We found that the mean of the probability distribution decoded from retinotopic cortical areas predicted memory reports on a trial-by-trial basis. Moreover, in several of the same mid-dorsal stream areas the spread of the distribution predicted subjective trial-by-trial uncertainty judgments. These results provide evidence that VWM content and uncertainty are jointly represented by probabilistic neural codes.

neuroscience↗