Abstract 390: Impact of loss of <i>IGF2</i> genomic imprinting on IGF1R signaling and cancer stem cell-associated biomarkers in gastric cancer
Bibliographic record
Abstract
Abstract Aim: To investigate the association between loss of genomic imprinting (LOI) of insulin-like growth factor 2 (IGF-2) gene and the expressions of genes related with insulin-like growth factor type I receptor (IGF1R) signaling and the cancer stem cell associated genes (CD133 and Musashi I), in gastric cancer (GC) and its adjacent normal mucosa in GC patients with and without IGF-2 LOI. Patients and methods: Patients with pathological diagnosis of GC and underwent surgical resection in Department of Surgery of Potuo Hospital from 2006 to 2012 were recruited. Demographic and clinical pathological data were retrieved from medical records. The IGF-2 genomic imprinting status was determined by PCR and RT-PCR followed by restrictive endonuclease (Apa I) digestion. mRNA expression of IGF1R was evaluated with reverse transcription and real time PCR. Protein expressions of IGF-2, IGF1R, phosphorylated Akt (Ser-473), CD133, and Musashi 1 in tumor and adjacent mucosa were detected by immunohistochemical staining on tissue sections cut from formalin fixed and paraffin embedded cancer tissue blocks. All staining results were assessed by a qualified pathologist and marked as positive or negative. Statistical analysis was done by using SPSS (19.0) with a significant level of p<0.05. Results:Fifty patients were found to be LOI positive, while 25 patients were LOI negative. Of 50 LOI positive patients, 48 (96%) were in advanced stage, in contrast, there were 20 patients were in advanced stage among 25 LOI negative patients (80%)(p<0.05). The positive rate of IGF1R in tumor was significantly higher in LOI positive patients (50%) as compare to LOI negative patients (16.0%)(p<0.05). Unexpectedly, the tumor mRNA expression of IGF1R in LOI positive patients was significantly lower than that in LOI negative patients (6.99±1.58 vs. 8.06±1.64, p<0.01). The positive rates of CD133 in tumors were significantly higher in patients with LOI than those without (84.0% vs. 42.0%) (p<0.05). Fifty percent of adjacent mucosa samples (25/50) from LOI positive patients were Misashi I positive, lower than that (76%, 19/25) in LOI negative patients (p<0.05). There was no difference of the protein expressions of IGF-2, phosphorylated Akt (Ser-473), IGF1R and CD133 in mucosa, and Musashi I in tumor between the patients with and without LOI. Conclusion: The significant association of IGF-2 LOI to protein expression of IGF1R, and certain cancer stem cell markers in tumor or adjacent mucosa indicates LOI may play important role in cancer initiation and could be a useful marker for clinical screening of high risk individuals and early diagnosis. The disparity of IGF1R protein and mRNA expression in tumor suggested that some post transcription factor may regulate the final IGF1R protein expression, which remained to be further studied. Citation Format: Teng Chen, Ronghua Zhao, Qinsong Zuo, Chao Chen, Menfan Li, Dianxu Feng, Han Cai. Impact of loss of IGF2 genomic imprinting on IGF1R signaling and cancer stem cell-associated biomarkers in gastric cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 390. doi:10.1158/1538-7445.AM2014-390
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 | 0.000 | 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) | 0.002 | 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".