Independent primary cutaneous and mammary apocrine carcinomas with neuroendocrine differentiation: Report of a case and literature review
Bibliographic record
Abstract
Cutaneous apocrine carcinomas share common features with their counterparts in the breast; hence, metastatic mammary carcinoma must be excluded before such lesions can be designated primary cutaneous neoplasms. Primary tumors from either source rarely exhibit neuroendocrine differentiation. We report a case of a 72-year-old female with a painless 1.2-cm scalp nodule. An incisional biopsy revealed dermal involvement by an invasive apocrine carcinoma juxtaposed to a benign apocrine cystic lesion. Immunohistochemically, the carcinoma expressed neuroendocrine proteins including synaptophysin, chromogranin, and CD56. A primary cutaneous apocrine carcinoma with neuroendocrine differentiation was favored, but additional investigations to exclude breast origin were recommended. These revealed a 1.1-cm nodule in the right breast, which proved to be an invasive ductal carcinoma, morphologically and immunophenotypically similar to the scalp lesion. This confounded the case, yet factors militating against metastatic breast carcinoma to skin included (a) the small size of the mammary tumor, (b) absence of other metastatic disease, and (c) juxtaposition of the scalp carcinoma to a putative benign precursor. Molecular studies were undertaken to resolve the diagnostic quandary. Single nucleotide polymorphism microarray analysis revealed distinct patterns of chromosomal copy number alterations in the two tumors, supporting the concept of synchronous and unusual primary neoplasms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".