Abstract 60: Genotranscriptomic meta-analysis of centromere protein A (CENPA): An essential role in human cancer progression
Bibliographic record
Abstract
Abstract Background: As the cancer hallmark, genetic instability caused by abnormal cell division, is characterized with the gain or loss of entire chromosomes. The specific histone-H3 variant, centromere protein-A (CENPA), plays essential role in regulating kinetochore assembly, centromere activity and chromosome stability during cell division. However, the biological function of CENPA in human cancer remains largely uncharacterized. This study aims to determine the prognostic value of CENPA expression in cancer patients and the potential therapeutic target in cancer treatment via the genotranscriptomic meta-analysis. Methods: In order to well address the issue, a comprehensive and unbiased genotranscriptomic meta-analysis of CENPA in human cancers was performed with the clinical patient information databases, i.e. COSMIC, Oncomine and cBioPortal. Results: Based on the analysis, it strongly indicated the widespread cancer promoting role of CENPA. There are no gene fusion, very low point mutation (0.15%) and very rare copy number variation (CNV) gain (0.09%) at the CENPA locus in 15214 patient samples across 33 cancer types. However, transcriptomic analyses indicated high correlation of increased CENPA mRNA levels in various solid cancer tissues compared with normal tissues. Furthermore, the poor clinical outcome among 51 clinical cohorts with different cancer types shows significantly correlation with CENPA up-regulation, especially in breast cancer. More importantly, the CENPA up-regulation is also significantly correlated with the metastasis progression and pathology-assessment in breast cancer patients. The high rank of metastatic related genes correlated with CENPA up-regulation is also confirmed in TCGA breast cancer cohorts. Conclusions: The current study highly indicates the essential cancer promoting role of CENPA in human cancer and its value as prognostic marker in clinical use. It also provides rationale for further investigation of CENPA as potential therapeutic target in breast cancer treatment. Citation Format: Xia Sun, Sifeng Qu. Genotranscriptomic meta-analysis of centromere protein A (CENPA): An essential role in human cancer progression. [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 60. doi:10.1158/1538-7445.AM2015-60
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 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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".