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Brakenhoff, R. H.

Publications and source records attributed to Brakenhoff, R. H..

2 recordsLinked to original sources

Glutamine-derived NADH fuels lactate production to maximize ATP yield under oxygen consumption constraints in head and neck cancer

Metabolic reprogramming is one of the hallmarks of cancer. A well-known change is the Warburg effect: glucose is consumed at increased rates and fermented to lactate instead of being respired to carbon dioxide, despite the presence of sufficient oxygen (O2). We show that head and neck squamous cell carcinoma (HNSCC) cells excrete more carbon in the form of lactate than is consumed as glucose, indicating the presence of additional carbon sources for lactate. Amino acid uptake and [U-13C]-glutamine labelling data show that glutamine is highly consumed and oxidized in the tricarboxylic acid (TCA) cycle, but remarkably does not contribute to lactate carbon. To explain these observations, we generated a cell-line specific metabolic model to understand the link between lactate production and glutamine metabolism. In the model, we show how low cellular O2 consumption capacity can cause increased lactate production with glutamine as NADH source. The model suggests that ATP production under limited O2 consumption is augmented by increased glutamine oxidation which yields ATP, FADH2 and NADH. FADH2 can only be respired, despite yielding less ATP than NADH respiration. NADH can be exported from the mitochondrion to be reoxidized by lactate dehydrogenase, permitting more cycles of glutamine oxidation, thereby increasing the total ATP yield. By experimentally inhibiting mitochondrial respiration, we confirmed that non-glucose carbon sources are used for lactate production under decreased O2 consumption capacity. This unexpected feature of O2-constrained ATP production provides a credible mechanism for the increased lactate production via a novel redox cycle in HNSCC cells.

systems biology↗

DPHL: A pan-human protein mass spectrometry library for robust biomarker discovery using Data-Independent Acquisition and Parallel Reaction Monitoring

To answer the increasing need for detecting and validating protein biomarkers in clinical specimens, proteomic techniques are required that support the fast, reproducible and quantitative analysis of large clinical sample cohorts. Targeted mass spectrometry techniques, specifically SRM, PRM and the massively parallel SWATH/DIA technique have emerged as a powerful method for biomarker research. For optimal performance, they require prior knowledge about the fragment ion spectra of targeted peptides. In this report, we describe a mass spectrometric (MS) pipeline and spectral resource to support data-independent acquisition (DIA) and parallel reaction monitoring (PRM) based biomarker studies. To build the spectral resource we integrated common open-source MS computational tools to assemble an open source computational workflow based on Docker. It was then applied to generate a comprehensive DIA pan-human library (DPHL) from 1,096 data dependent acquisition (DDA) MS raw files, and it comprises 242,476 unique peptide sequences from 14,782 protein groups and 10,943 SwissProt-annotated proteins expressed in 16 types of cancer samples. In particular, tissue specimens from patients with prostate cancer, cervical cancer, colorectal cancer, hepatocellular carcinoma, gastric cancer, lung adenocarcinoma, squamous cell lung carcinoma, diseased thyroid, glioblastoma multiforme, sarcoma and diffuse large B-cell lymphoma (DLBCL), as well as plasma samples from a range of hematologic malignancies were collected from multiple clinics in China, the Netherlands and Singapore and included in the resource. This extensive spectral resource was then applied to a prostate cancer cohort of 17 patients, consisting of 8 patients with prostate cancer (PCa) and 9 with benign prostate hyperplasia (BPH), respectively. Data analysis of DIA data from these samples identified differential expressions of FASN, TPP1 and SPON2 in prostate tumors. Thereafter, PRM validation was applied to a larger PCa cohort of 57 patients and the differential expressions of FASN, TPP1 and SPON2 in prostate tumors were validated. As a second application, the DPHL spectral resource was applied to a patient cohort consisting of samples from 19 DLBCL patients and 18 healthy individuals. Differential expressions of CRP, CD44 and SAA1 between DLBCL cases and healthy controls were detected by DIA-MS and confirmed by PRM. These data demonstrate that the DPHL supported that DIA-PRM MS pipeline enables robust protein biomarker discoveries.

bioinformatics↗