Low‐grade oncocytic tumour of the kidney is characterised by genetic alterations of <i>TSC1</i>, <i>TSC2</i>, <i>MTOR</i> or <i>PIK3CA</i> and consistent <scp>GATA3</scp> positivity
Bibliographic record
Abstract
Low-grade oncocytic tumour (LOT) of the kidney has recently emerged as a potential novel tumour type. Despite similarity to oncocytoma or eosinophilic chromophobe renal cell carcinoma, it shows diffuse keratin 7 immunohistochemistry (IHC) and negative KIT (CD117), which differs from both. We aimed to identify the molecular characteristics of these tumours. Seventeen tumours (one male, 16 female, nine previously published) fitting the original description of this entity (solid eosinophilic cell morphology, often with areas of tumour cells loosely stretched in oedematous stroma, and the above IHC features) were analysed with a next-generation sequencing panel of 324 cancer-associated genes from formalin-fixed, paraffin-embedded tissue. All tumours harboured at least one alteration in either TSC1 (n = 7, 41%), TSC2 (n = 2, 12%), MTOR (n = 5, 29%) or PIK3CA (n = 4, 24%). Four tumours harboured a second alteration, including two NF2, one each in conjunction with MTOR and TSC2 alterations, one PTEN with TSC1 alteration and one tumour with both MTOR and TSC1 alterations. No other renal cancer-related or recurring gene alterations were identified. In addition to the previously described IHC findings, 16 of 16 were positive for GATA3. Eleven patients with follow-up had no metastases or recurrent tumours. Recurrent tuberous sclerosis/MTOR pathway gene alterations in LOT support its consideration as a distinct morphological, immunohistochemical and genetic entity. PIK3CA is another pathway member that may be altered in these tumours. Further study will be necessary to determine whether tumour behaviour or syndromic associations differ from those of oncocytoma and chromophobe carcinoma, warranting different clinical consideration.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".