Effect of Cryptorchidism on Human Testicular Transcriptome.
Bibliographic record
Abstract
Cryptorchidism is the most common congenital disorder in boys. One major consequence of this anomaly is male infertility due to undescended testis to which an increased risk of testicular cancer is associated. The genetic cause of cryptorchidism remains to be elucidated. The objective of this study was to compare the transcriptome of human cryptorchid testis with normal tissues. Seminoma tissues were used as a positive control of genes known to be expressed in testicular cancer. Normal tissues were obtained with collaboration of our local organ transplantation program; the five donors were from 23 to 53 years of age. Cryptorchid testes were obtained by surgical orchidectomy performed on 4 patients from 29 to 43 years of age presenting with inguinal testis. Donors of seminoma tissues were from 22 to 34 years of age and were obtained through the pathological tissues bank of our institution. Tissues samples were kept on ice and snap freeze immediately upon arrival in the research lab. Total RNA was extracted from the tissues and used to probe Affymetrix GeneChip Human Gene 1.0 ST arrays which include 28,869 genes with 764,885 distinct probes. In normal and cryptorchid tissues 2278 and 589 genes were up-regulated, respectively. As expected, transcripts known to be associated with spermatogenesis characterized the normal tissues whereas, in cryptorchid testes, transcripts of Leydig and Sertoli cells were found in higher amount. For example, PRM1 and ADAM2 transcripts associated to germ cells were in higher quantity in normal than cryptorchid testes, but CYP17A1, LHR and HSD17B3 transcripts of Leydig cells as well as GATA4, INHA and INHBA transcripts of Sertoli cells were higher in cryptorchid than normal testes. Some transcripts known to be associated with testicular cancer, such as CALR3 and PIWIL1, were up-regulated in normal tissues whereas KITLG and CCND2 were more expressed in cryptorchid testes. In seminoma tissues, PIWIL1 transcript was more expressed in cryptorchid but less in normal testicular cancer; the CALR3 and KITLG were less expressed in seminoma than in other tissues whereas the CCND2 was much more expressed in cancer tissues. Markers for testicular descent were more expressed in cryptorchids than in normal and seminomas as expected. These transcript expression patterns from the microarray results were confirmed by quantitative real-time PCR. Differences in transcriptome due to cryptorchidism will give us a clue to find the genetic cause of this disease. This work was supported by Canadian Institute of Health Research grant to Robert Sullivan. (poster)
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".