Dataset Information

Sperm-specific COX6B2 enhances oxidative phosphorylation, proliferation, and survival in human lung adenocarcinoma.

ABSTRACT: Cancer testis antigens (CTAs) are proteins whose expression is normally restricted to the testis but anomalously activated in human cancer. In sperm, a number of CTAs support energy generation, however, whether they contribute to tumor metabolism is not understood. We describe human COX6B2, a component of cytochrome c oxidase (complex IV). COX6B2 is expressed in human lung adenocarcinoma (LUAD) and expression correlates with reduced survival time. COX6B2, but not its somatic isoform COX6B1, enhances activity of complex IV, increasing oxidative phosphorylation (OXPHOS) and NAD+ generation. Consequently, COX6B2-expressing cancer cells display a proliferative advantage, particularly in low oxygen. Conversely, depletion of COX6B2 attenuates OXPHOS and collapses mitochondrial membrane potential leading to cell death or senescence. COX6B2 is both necessary and sufficient for growth of human tumor xenografts in mice. Our findings reveal a previously unappreciated, tumor-specific metabolic pathway hijacked from one of the most ATP-intensive processes in the animal kingdom: sperm motility.

SUBMITTER: Cheng CC

PROVIDER: S-EPMC7556868 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Sperm-specific COX6B2 enhances oxidative phosphorylation, proliferation, and survival in human lung adenocarcinoma.

Cheng Chun-Chun CC Wooten Joshua J Gibbs Zane A ZA McGlynn Kathleen K Mishra Prashant P Whitehurst Angelique W AW

eLife 20200929

Cancer testis antigens (CTAs) are proteins whose expression is normally restricted to the testis but anomalously activated in human cancer. In sperm, a number of CTAs support energy generation, however, whether they contribute to tumor metabolism is not understood. We describe human COX6B2, a component of cytochrome c oxidase (complex IV). <i>COX6B2</i> is expressed in human lung adenocarcinoma (LUAD) and expression correlates with reduced survival time. COX6B2, but not its somatic isoform COX6B ...[more]

PMID: 32990599

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Project description:Accurate prognostic prediction is crucial for treatment decision-making in lung papillary adenocarcinoma (LPADC). The aim of this study was to predict cancer-specific survival in LPADC using ensemble machine learning and classical Cox regression models. Moreover, models were evaluated to provide recommendations based on quantitative data for personalized treatment of LPADC. Data of patients diagnosed with LPADC (2004-2018) were extracted from the Surveillance, Epidemiology, and End Results database. The set of samples was randomly divided into the training and validation sets at a ratio of 7:3. Three ensemble models were selected, namely gradient boosting survival (GBS), random survival forest (RSF), and extra survival trees (EST). In addition, Cox proportional hazards (CoxPH) regression was used to construct the prognostic models. The Harrell's concordance index (C-index), integrated Brier score (IBS), and area under the time-dependent receiver operating characteristic curve (time-dependent AUC) were used to evaluate the performance of the predictive models. A user-friendly web access panel was provided to easily evaluate the model for the prediction of survival and treatment recommendations. A total of 3615 patients were randomly divided into the training and validation cohorts (n = 2530 and 1085, respectively). The extra survival trees, RSF, GBS, and CoxPH models showed good discriminative ability and calibration in both the training and validation cohorts (mean of time-dependent AUC: > 0.84 and > 0.82; C-index: > 0.79 and > 0.77; IBS: < 0.16 and < 0.17, respectively). The RSF and GBS models were more consistent than the CoxPH model in predicting long-term survival. We implemented the developed models as web applications for deployment into clinical practice (accessible through https://shinyshine-820-lpaprediction-model-z3ubbu.streamlit.app/ ). All four prognostic models showed good discriminative ability and calibration. The RSF and GBS models exhibited the highest effectiveness among all models in predicting the long-term cancer-specific survival of patients with LPADC. This approach may facilitate the development of personalized treatment plans and prediction of prognosis for LPADC.

Dataset Information

Sperm-specific COX6B2 enhances oxidative phosphorylation, proliferation, and survival in human lung adenocarcinoma.

Publications

Sperm-specific COX6B2 enhances oxidative phosphorylation, proliferation, and survival in human lung adenocarcinoma.

Similar Datasets

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