Genomic and Clinical Correlates of Adrenocortical Carcinoma in an Adult Patient with Li-Fraumeni Syndrome: A Case Report
Bibliographic record
Abstract
Li-Fraumeni Syndrome (LFS) is defined by germline mutations of the p53 tumour suppressor gene. Adrenocortical carcinoma (ACC) is a rare aggressive malignancy that is commonly associated with LFS. Most LFS-linked ACC cases occur in children, and limited research has been dedicated to the clinical outcomes and genomics of adult cases with LFS-linked ACC. We report on a 34-year-old female who was diagnosed with three separate malignancies: stage III invasive ductal carcinoma of the right breast, metastatic ACC from the right adrenal gland, and grade 2 pleomorphic sarcoma of the left hand. Her invasive breast ductal carcinoma was treated with neoadjuvant chemotherapy, and she received a bilateral mastectomy after her LFS was confirmed with genetic blood testing. Adrenal ACC was initially treated with a right nephrectomy and adrenalectomy, followed by adjuvant mitotane and two lines of chemotherapy after disease recurrence. Her hand sarcoma was treated by second ray amputation. Further, we conducted deep next-generation sequencing of each of her unique tumour tissue samples using FoundationONE CDx. A whole-genome shot capture followed by in vitro sequencing performed by the Illumina® HiSeq platform revealed a germline P191fs*18 TP53 mutation across all three tissue samples. This case provides insight into the genomics and clinical characteristics of LFS-linked adult-onset ACC and demonstrated that p53 mutations were preserved throughout each malignancy, without apparent treatment pressures on genomic profiling. This case reinforces the critical importance of adopting best practices for LFS, which include the implementation of highly vigilant screening and management of care in a multidisciplinary setting.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".