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Record W4411582115 · doi:10.3390/cells14130952

Carcinogenesis Associated with Toxin Nephropathy: Proposed Mediation by Phosphate Toxicity

2025· review· en· W4411582115 on OpenAlexaff
Ronald B. Brown, John G. Mielke

Bibliographic record

VenueCells · 2025
Typereview
Languageen
FieldMedicine
TopicParathyroid Disorders and Treatments
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsCarcinogenesisNephrotoxicityCarcinogenToxicityCancer researchCancerBiologyDNA damageChemistryMedicineInternal medicineBiochemistryGeneticsDNA

Abstract

fetched live from OpenAlex

Although cancer is often considered a genetic disease, genotoxic damage to nuclear DNA caused by carcinogens is not always sufficient to stimulate cancer cell growth, suggesting that other etiological factors are involved. Indeed, many carcinogens are also nephrotoxic and can impair kidney function. In turn, impaired renal function can dysregulate serum inorganic phosphate, leading to hyperphosphatemia and excess phosphate storage in tissues, which causes phosphate toxicity. Moreover, phosphate toxicity can contribute to cancer cell growth by activating cell signaling pathways, overexpressing sodium phosphate cotransporters, and stimulating excessive RNA biogenesis and protein synthesis. The present narrative review proposes a general underlying mechanism by which phosphate toxicity mediates the association of toxin nephropathy with carcinogenesis. This proposed pathway could explain why any factor that impairs renal function, including an overload of nontoxic substances, may indirectly contribute to excess phosphate sequestration in the tumor microenvironment which stimulates cancer cellular growth. Importantly, chemotherapy agents are often nephrotoxic, and carcinogenicity associated with such nephrotoxins could explain the occurrence of second tumors in treated cancer patients. More research is needed to investigate the mediating role of phosphate toxicity in the association of toxin nephropathy with carcinogenesis.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.828
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
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 head0.017
GPT teacher head0.285
Teacher spread0.268 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations4
Published2025
Admission routes1
Has abstractyes

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