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Pharmacogenomics of cisplatin-induced neurotoxicities: Hearing loss, tinnitus and peripheral sensory neuropathy.

2021· article· en· W3172478157 on OpenAlexaff
Xindi Zhang, Matthew R. Trendowski, Emma Wilkinson, Darren R. Feldman, Robert J. Hamilton, David J. Vaughn, Chunkit Fung, Christian Kollmannsberger, Robert Huddart, Neil E. Martin, Paul C. Dinh, Robert D. Frisina, Lawrence H. Einhorn, M. Eileen Dolan, Lois B. Travis

Bibliographic record

VenueJournal of Clinical Oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicCancer Treatment and Pharmacology
Canadian institutionsPrincess Margaret Cancer CentreUniversity of British ColumbiaUniversity Health Network
FundersNational Institutes of Health
KeywordsMedicineTinnitusCisplatinInternal medicineHearing lossPeripheral neuropathyPharmacogenomicsOtotoxicityConfoundingNeurotoxicityOncologyAuditory neuropathyCohortGastroenterologyChemotherapyEndocrinologyToxicityPharmacologyDiabetes mellitusAudiology

Abstract

fetched live from OpenAlex

12004 Background: Cisplatin is an essential component of first-line chemotherapy for many cancers, but causes neurotoxicity, including hearing loss (CisHL), tinnitus (CisTinn), and peripheral sensory neuropathy (CisPNeuro). However, few opportunities exist to identify risk factors and comorbidities for cisplatin-induced neurotoxicities among large numbers of homogenously treated patients without the confounding effect of cranial radiotherapy. Methods: Within a well-characterized clinical cohort of 1,680 cisplatin-treated testicular cancer survivors, linear and logistic regression analysis were utilized to analyze associations of CisHL (n = 1,258), CisTinn (n = 1,217), and CisPNeuro (n = 1,653) with non-genetic risk factors. Genome-wide association studies and gene-based analysis were performed on each phenotype. Results: Cisplatin-induced neurotoxicities (CisHL CisTinn, CisPNeuro), adjusting for age and cisplatin dose, were interdependent. Survivors with these neurotoxicities experienced more hypertension (CisTinn: OR = 2.62, p < 0.0001; CisHL: β = 0.25, p = 8.5 x10-4; CisPNeuro: OR = 1.86, p < 0.0001) and were more likely to report their health as poor (CisTinn: OR = 0.54, p < 0.0001; CisHL: β = -0.11, p < 0.0001; CisPNeuro: OR = 0.61, p < 0.0001). Persistent vertigo was significantly associated with both CisTinn (OR = 7.18, p < 0.0001) and CisPNeuro (OR = 4.29, p < 0.0001). In addition, CisTinn was significantly associated with hypercholesterolemia (OR = 1.78, p = 0.01). Importantly, gene-based association analyses identified significant associations between CisTinn and WNT8A (n = 1,037, p = 2.52x10-6) , encoding a signaling protein important in germ cell tumors; and marginal significance between CisHL and TXNRD1 (n = 1,071, p = 4.21x10-6) , thioredoxin reductase-1, which plays a key role in redox regulation. In silico analysis showed high expression levels of TXNRD1 were significantly correlated with cellular resistance to cisplatin in central nervous system tumor cells (Spearman Rho = 0.35, p = 0.04; R2= 0.14, p = 0.03), indicating TXNRD1 is protective for cisplatin-induced cytotoxicity. Previously, rs62283056 in WFS1 found to be significantly associated with CisHL (n = 511; subset of current population), was marginally significant in an independent replication cohort (p = 0.06; n = 606; subset of current population). Conclusions: Cisplatin-induced neurotoxicities are significantly associated with multiple clinical characteristics, including hypertension and self-reported poor health. WNT8A and TXNRD1 are notable risk factors for CisTinn and CisHL, respectively . Future studies should further investigate these genes and their potential impact on chemotherapy strategies. This study, based on the largest number of testicular cancer survivors investigated to date, highlights the clinical importance of these iatrogenic toxicities and their associated risk factors.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.227
GPT teacher head0.498
Teacher spread0.271 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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".

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Citations2
Published2021
Admission routes1
Has abstractyes

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