Abstract 2145: Identification of genomic alterations and integrated gene expression profiles for MSS colon tumors
Bibliographic record
Abstract
Abstract Colon cancer is the result of a multi-step process involving the accumulation of genetic and epigenetic alterations leading to the transformation of normal colon epithelium to adenocarcinoma. Identification of characteristic genetic alterations is of critical importance to increase our understanding of the transformation process. We focused our analysis on the most common molecular sub-type of colon cancers, microsatellite stable (MSS) and CpG island methylator phenotype (CIMP)-negative, to identify characteristic copy number alteration (CNA) events and associated gene expression profiles using high-resolution genome-wide microarrays. DNA and RNA were extracted from 41 fresh-frozen paired colon tumors and adjacent normal tissue collected by the Colon Cancer Family Registry. Genomic profiles, such as CNAs and loss of heterozygosity (LOH), were identified with the Affymetrix Genome-Wide Human SNP 6.0 array for both tumor and adjacent normal tissue. Gene expression profiles of tumors and adjacent normal tissue were identified with the Affymetrix GeneChip Human Exon 1.0 ST array. Partek Genomics Suite software was used for analysis and data integration. We identified recurrent (>25%) CNAs in several chromosomal regions: gain in 1q, 7p, 7q, 8q, 13q, 20p, 20q, Xp, Xq and loss in 5q, 8p, 14q, 16p, 17p, 18p, and 18q. In addition, based on the allele information from the SNP arrays, we found a subset of these recurrent CNAs were associated with LOH. Preliminary results from the integration of CNA and gene expression data in tumors indicate that a subset of these recurrent CNAs is associated with the disruption of gene expression. For example, we observed recurrent copy number gain in 8q24.21, the genomic region containing the c-MYC gene, and associated up-regulation of c-MYC gene expression in tumors compared to adjacent normal tissue. In another example, recurrent copy number loss at 5q22.2 was associated with down-regulation of APC gene expression; loss of function of this tumor suppressor is associated with both hereditary and sporadic colon cancer. This genome-wide characterization of both genomic alterations and gene expression may help identify key genes and pathways that are disrupted in this common molecular subtype of colon cancer. We will present detailed results from this integrated and comprehensive genetic profiling of MSS and CIMP-negative colon cancers. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2145.
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 | 0.001 | 0.001 |
| 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".