MétaCan
Menu
← Back to cohort
Record W4393057081 · doi:10.1158/1538-7445.am2024-4357

Abstract 4357: Examining the role of end-stage kidney as a potential intermediate stage in the development of renal cell carcinomas; understanding the pathogenesis allowing for early detection

2024· article· en· W4393057081 on OpenAlexaff
Mingyuan Wan, Vincent Castillo, Rola Saleeb

Bibliographic record

VenueCancer Research · 2024
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsSt. Michael's HospitalUniversity of Toronto
Fundersnot available
KeywordsStage (stratigraphy)PathogenesisKidneyMedicineRenal cell carcinomaPathologyInternal medicineBiology

Abstract

fetched live from OpenAlex

Abstract Introduction: Clear cell renal cell carcinoma (CCRCC) and papillary renal cell carcinoma (PRCC) are both thought to arise from the renal proximal tubules. End stage renal disease (ESRD) patients have an increased incidence of developing PRCC and CCRCC. Some studies showed a progenitor cell population that is inherently present in renal tubules, and is significantly increased after renal injury. The studies have also illustrated similarities between these progenitor cells and PRCC & CCRCC; hypothesizing that they are the cell of origin of these tumors. This trend was not observed in other renal cell carcinomas such as chromophobe renal cell carcinoma (chRCC). This study aims to further examine the possible role of ESRD in the development of PRCC and CCRCC to understand this initial step of renal cell carcinoma pathogenesis. Methods: A cohort of n = 39 PRCC, 25 CCRCC, 63 normal, 10 end-stage and 18 chRCC cases were selected. RNA sequencing was performed and differential-gene-expression analysis was conducted between normal, ESRD and tumor using DESeq2 software. Pathway analysis was performed using GSEA. Genes from oncogenic pathways that have been studied to be involved in renal cancer development were selected to perform consensus clustering analysis on Genepattern. Results: Oncogenic and developmental pathways enriched in ESRD are consistently overlapping with that of CCRCC and PRCC tumors. 50% of end-stage developmental pathways are found in both CCRCC and PRCC but only 4.5% in chRCC. 62.4% and 46.4% of end-stage oncogenic pathways are found in CCRCC and PRCC respectively but only 16% in chRCC. Clustering analysis showed ESRD cases clustered together with CCRCC and PRCC groups and not with chRCC. Overall, the ESRD cases exhibited a gene expression profile more closely resembling that of CCRCC and PRCC than chRCC. Conclusion: Our findings support the hypothesis that ESRD provides a favorable environment for tumor growth promoting pathogenesis of both PRCC and CCRCC. The enrichment of the same developmental pathways in both ESRD and the tumors suggests that the progenitor cell population in the renal tubules, mentioned above, could be the origin of both PRCC and CCRCC lesions. Further analysis would allow the uncovering of the pathways that lead to tumor progression from these cells of origin, and can be used to determine biomarkers for early detection of CCRCC and PRCC. This is of particular benefit for those with increased risk as the ESRD patients. Citation Format: Mingyuan Wan, Vincent Castillo, Rola Saleeb. Examining the role of end-stage kidney as a potential intermediate stage in the development of renal cell carcinomas; understanding the pathogenesis allowing for early detection [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4357.

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)0.000
metaresearch head score (Gemma)0.000
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: Other · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0030.001

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 head0.117
GPT teacher head0.360
Teacher spread0.243 · 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
GenreOther

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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueCancer Research→Same topicRenal cell carcinoma treatment→French-language works237,207→