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Record W2515733173 · doi:10.1242/dmm.023374

Systematic identification of genes involved in metabolic acid stress resistance in yeast and their potential as cancer targets

2016· article· en· W2515733173 on OpenAlexafffund
John J. H. Shin, Qurratulain Aftab, Pamela Austin, Jennifer McQueen, Tak Poon, Shu Chen Li, Barry P. Young, Calvin D. Roskelley, Christopher Loewen

Bibliographic record

VenueDisease Models & Mechanisms · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Cancer Society Research InstituteCanadian Institutes of Health Research
KeywordsBiologyIntracellularMitochondrionCancer cellGlycolysisBiochemistryCell biologyRespiratory chainMetabolismGeneticsCancer

Abstract

fetched live from OpenAlex

A hallmark of all primary and metastatic tumours is their high rate of glucose uptake and glycolysis. A consequence of the glycolytic phenotype is the accumulation of metabolic acid; hence, tumour cells experience considerable intracellular acid stress. To compensate, tumour cells upregulate acid pumps, which expel the metabolic acid into the surrounding tumour environment, resulting in alkalization of intracellular pH and acidification of the tumour microenvironment. Nevertheless, we have only a limited understanding of the consequences of altered intracellular pH on cell physiology, or of the genes and pathways that respond to metabolic acid stress. We have used yeast as a genetic model for metabolic acid stress with the rationale that the metabolic changes that occur in cancer that lead to intracellular acid stress are likely fundamental. Using a quantitative systems biology approach we identified 129 genes required for optimal growth under conditions of metabolic acid stress. We identified six highly conserved protein complexes with functions related to oxidative phosphorylation (mitochondrial respiratory chain complex III and IV), mitochondrial tRNA biosynthesis [glutamyl-tRNA(Gln) amidotransferase complex], histone methylation (Set1C-COMPASS), lysosome biogenesis (AP-3 adapter complex), and mRNA processing and P-body formation (PAN complex). We tested roles for two of these, AP-3 adapter complex and PAN deadenylase complex, in resistance to acid stress using a myeloid leukaemia-derived human cell line that we determined to be acid stress resistant. Loss of either complex inhibited growth of Hap1 cells at neutral pH and caused sensitivity to acid stress, indicating that AP-3 and PAN complexes are promising new targets in the treatment of cancer. Additionally, our data suggests that tumours may be genetically sensitized to acid stress and hence susceptible to acid stress-directed therapies, as many tumours accumulate mutations in mitochondrial respiratory chain complexes required for their proliferation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.110
Threshold uncertainty score0.528

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.228
Teacher spread0.220 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2016
Admission routes2
Has abstractyes

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