Deciphering the Diversity of Somatic Alterations and Salmonella Infection in Gallbladder Cancer by Whole Exome Sequencing
Bibliographic record
Abstract
Introduction: Gallbladder cancer is relatively a rare lethal malignancy with dismal prognosis. While in India there is high incidence (3.9-8.6/1, 00,000) with majority of patients having advanced disease. Recent developments in next generation sequencing technologies have enabled the discovery of new molecular therapeutic targets in many human cancers. Objectives: Interrogate the landscape of somatic alterations in Indian gall bladder cancer using whole exome sequencing technology. Material and Methods: We interrogated the coding region of 27(10 paired and 7 unpaired) Indian gall bladder cancer samples using whole exome sequencing at an average coverage of 100X and above. We further validated the findings using an additional set of 27 FFPE samples. Results: Using a bioinformatics filtering approach, we identify a total of 5060 somatic variants found across 17 tumors consisted of 3239 missense, 1449 silent, 131 nonsense, 135 indels and 106 splice site mutations The average mutation rate considering the paired tumors is about 7.7 mutations/mb. We found TP53 (35.2%), ERBB2 (17.6%), SF3B1 (17.6%), ATM (17.6%) and AKAP11 (17.6%) mutations in more than two samples by exome sequencing analysis. Furthermore, we examined our exome sequencing data for identifying Salmonella sequences as well as presence of 143 HPV types using computation subtraction based on HPVDetector. Based on our evaluation we found association of typhoidal Salmonella strains in 11 of 26 gall bladder cancer samples and non-typhoidal Salmonella species in 12 of 26 samples, 6 samples were co-infected with both. Conclusions: The profiling of somatic alterations and identification of non typhoidal Salmonella traces may aid in changing the current treatment paradigm of gall bladder cancer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".