Abstract IA35: Novel biological insights into colorectal cancer from West Africa
Bibliographic record
Abstract
Abstract The burden of colorectal cancer (CRC) is increasing in West Africa. Understanding the molecular and clinicopathologic profile of the region’s CRC patients is vital to optimizing early detection and therapeutic regimens. Clinicopathologic data from consecutive patients from a multicenter, prospectively maintained Nigerian CRC database were compared to a contemporary cohort from Memorial Sloan Kettering Cancer Center (MSKCC). Fresh-frozen tissue from Nigerian patients was analyzed with a multigene, next-generation sequencing assay, along with immunohistochemistry and methylation analyses; data were compared to molecular data from MSKCC and The Cancer Genome Atlas (TCGA) cohorts. Adult patients with histologically confirmed colorectal adenocarcinoma enrolled in a Nigerian CRC database from April 2013-November 2018 were included. All adult patients with colorectal adenocarcinoma diagnosed from January-June 2013 were included in the MSKCC cohort. Somatic and germline next-generation sequencing of cancer-associated genes, immunohistochemistry, and methylation analyses were performed. The primary outcomes were microsatellite instability status, somatic and germline mutation frequency, and overall survival. The median age at diagnosis was 55.8 years in the Nigerian cohort (n=380) and 60.0 years in the MSKCC cohort (n=458) (p<0.001). The rate of microsatellite instability was 28.1% in the Nigerian cohort (18/64), compared to 14.2% and 8.5% in the TCGA (65/459) and MSKCC (97/1145) cohorts, respectively (p<0.001). In microsatellite-stable cases, tumors from Nigerian patients were less likely to have APC mutations (39.1% vs. 76.0% p<0.001) and WNT pathway alterations (47.8% vs. 81.9%, p<0.001), and more likely to have RAS pathway alterations (76.1% vs. 59.6%, p=0.03) compared to MSKCC patients. Overall survival was significantly longer for MSKCC vs. Nigerian patients (not reached vs. 12 months, p<0.001). The biology of CRC in Nigeria appears to be distinct from that in high-income countries, emphasizing the need for regional data to guide diagnostic and treatment approaches for patients in West Africa. Citation Format: Olusegun I. Alatise, Gregory C. Knapp, Avinash Sharma, Walid K. Chatila, Olalekan Olasehinde, Adeleye D. Omisore, Aba Katung, Samuel A. Olatoke, T.Peter Kingham. Novel biological insights into colorectal cancer from West Africa [abstract]. In: Proceedings of the AACR Virtual Conference: Thirteenth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2020 Oct 2-4. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(12 Suppl):Abstract nr IA35.
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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 | 0.001 |
| 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 | 0.001 | 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".