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Record W2563684930 · doi:10.1158/1538-7445.am2015-4960

Abstract 4960: ERp46 (thioredoxin domain-containing protein 5, TXND5) promotes prostate cancer growth in vitro and in vivo

2015· article· en· W2563684930 on OpenAlexaffabout
Jehonathan H. Pinthus, Sarah Hopmans, Stephanie Federov, Wilhelmina Duivenvoorden

Bibliographic record

VenueCancer Research · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEndoplasmic Reticulum Stress and Disease
Canadian institutionsMcMaster University
Fundersnot available
KeywordsProstate cancerProstateGene knockdownCancer researchIn vivoPCA3LNCaPBiologyCancerPathologyMedicineCell cultureInternal medicine

Abstract

fetched live from OpenAlex

Abstract We have recently demonstrated that endoplasmic reticulum protein ERp46, a member of the protein disulfide isomerase family of oxidoreductases, TXND5, is overexpressed in human metastatic renal cell carcinoma. The expression and function of ERp46 in prostate cancer has not been studied. Using both in vitro and in vivo approaches, we explore the suitability of ERp46 as a potential therapeutic target in prostate cancer. Tissue microarray containing normal prostate epithelium (n = 9) and prostate cancer specimens from 57 patients was stained for ERp46 and the staining intensity (H-score) was determined. Human prostate adenocarcinoma 22Rv1 cells were used to generate gain- and loss-of-function models by stable ERp46 shRNA knockdown and ERp46 overexpression, respectively. In vitro, the doubling time and PSA production were determined. In vivo, xenografts of each subclone were established in nude mice (n = 10/group) to determine the longitudinal tumor growth and serum PSA values. Gene expression profiling of RNA isolated from 22Rv1 xenografts was performed using human whole genome HT-12 V4 BeadChip array (Illumina). Our results demonstrated that human prostate carcinoma samples of Gleason scores ≥7 showed strong cytoplasmic ERp46 staining which was significantly increased compared to normal prostatic tissue (p = 0.02). ERp46 staining in prostate tumors of Gleason scores ≤6, however, was not different compared to normal prostate tissue. The stably transfected human prostate carcinoma 22Rv1 cells expressed 89% knockdown of ERp46 protein expression (shERp46) or a 4-fold increase in ERp46 protein expression (ERp46+) compared to the respective control cells. In vitro, shERp46 cells proliferated slower, whereas ERp46+ cells exhibited accelerated growth compared to corresponding control cells (p<0.05). Similarly, the tumor volume of subcutaneously growing shERp46 cells in nude mice led to significantly slower tumor growth (p<0.0005, ANOVA). Vice versa, tumors from ERp46+ cells were significantly larger than the tumor volume of shControl-cell injected mice (p = 0.02, ANOVA). Gene expression analysis confirmed the downregulation and upregulation of ERp46 in the corresponding xenografts and also showed several candidate genes, including NAAA, SH3BP4 and ID1 that were reciprocally up-and downregulated. In conclusion, this is the first report to suggest a role for ERp46 as an oncogenic protein and potential therapeutic target in prostate cancer given its expression profile in human prostate cancer samples and its effect on prostate cancer cell growth. Funding was provided by Prostate Cancer Canada and McMaster Surgical Associates (JHP and WCMD) Citation Format: Jehonathan H. Pinthus, Sarah N. Hopmans, Stephanie Federov, Wilhelmina C. Duivenvoorden. ERp46 (thioredoxin domain-containing protein 5, TXND5) promotes prostate cancer growth in vitro and in vivo. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4960. doi:10.1158/1538-7445.AM2015-4960

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.031
GPT teacher head0.346
Teacher spread0.315 · 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 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

Citations1
Published2015
Admission routes2
Has abstractyes

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