Abstract 3901: Identification of novel tumor suppressor candidates and characterizing their potential driver role in familial cholangiocarcinoma
Bibliographic record
Abstract
Abstract Cholangiocarcinoma (bile duct cancer) is an epithelial malignancy originating from the bile duct that connects the liver to the small intestine. This carcinoma, while rare, has an extremely poor prognosis with a 5-year survival of less than 10%. Initial clinical presentation and diagnosis is frequently at an advanced stage and while amenable to specific combination chemotherapy regimens, inevitably progresses towards distal metastasis. Only recently has the molecular genetic underpinnings of this cancer been explored with a number of genome sequencing studies of a limited number of primary tumors. For this study, we used a multi-faceted approach that integrates the genetic analysis of an extended familial cholangiocarcinoma pedigree with identification of somatic genetic aberrations discovered via primary tumor sequencing of affected family members. Our goal was to identify potential novel tumor suppressor(s) that have not yet been described and are associated with an increased familial risk of cholangiocarcinoma. The extended pedigree was characterized by multiple members with relatively young onset of cholangiocarcinoma and displayed a segregation pattern consistent with an autosomal dominant inheritance pattern. Several members of the family had undergone biopsy or resection and as a result, had primary tumor tissue available for analysis. Relying on a combination of whole genome sequencing, experimentally-derived haplotype phasing, exome sequencing and tumor subclonal identification, we performed a combined germline and somatic analysis on this pedigree. Our analysis included family members both affected and unaffected by biliary cancers. Somatic variant analysis of the tumor samples was used to identify driver mutations that may work in concert with candidate germline mutation to initiate and maintain tumorigenesis. Remarkably, the cancer genome sequencing analysis identified a number of common somatic features among primary tumors found in different family members. Analysis of tumor clonality was derived from copy number and mutation data and further informed our analysis of possible contributing drivers. To further inform the analysis of suspected candidate germline loci, we conducted experimentally-based haplotype phasing covering Megabase segments to better delineate blocks that segregated with affected members. We identified several novel candidate genes with germline mutations with a predicted deleterious effect that segregated to affected individuals and had not been previously noted as polymorphisms or rare variants. Thus, we identified several candidate genes that may be novel tumor suppressor candidates for cholangiocarcinoma and increase the susceptibility to this lethal tumor. Overall, our study has significant implications by shedding light on the genetic basis of cholangiocarcinoma. Citation Format: Stephanie Greer, Lincoln D. Nadauld, Billy Lau, Laura Miotke, Erik Hopmans, Christina M. Wood, John M. Bell, Hanlee P. Ji. Identification of novel tumor suppressor candidates and characterizing their potential driver role in familial cholangiocarcinoma. [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 3901. doi:10.1158/1538-7445.AM2015-3901
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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".