Diagnosis and management of axillary lymph node metastasis from an unknown primary carcinoma: a case report

Carcinoma of unknown primary (CUP) represents a heterogeneous group of metastatic malignancies in which the primary tumor site remains unidentified despite comprehensive diagnostic evaluation. Accurate determination of tissue origin is essential for guiding treatment and improving clinical outcomes. The Canhelp^®-Origin gene expression profiling (GEP) assay, combined with specific immunohistochemical markers, has emerged as a valuable tool for identifying the origin of metastatic carcinomas. However, its clinical application in challenging cases, particularly those with atypical presentation and limited lineage-specific markers, warrants further documentation.

We present a case of a patient with right axillary metastatic carcinoma, in which the primary site remained undetermined after extensive imaging and initial immunohistochemical workup. Integrated application of the Canhelp^®-Origin GEP assay and immunohistochemical staining for lineage-specific markers, including TRPS1 and SOX10 (+), supported a probable diagnosis of metastatic triple-negative breast cancer, though melanoma and synovial sarcoma could not be fully excluded given overlapping immunophenotype and limited available tissue for additional confirmatory molecular testing. The patient subsequently received an AC-based chemotherapy regimen combined with immunotherapy and sequential radiotherapy. According to RECIST 1.1 criteria, the therapeutic effect was confirmed as complete response (CR), with complete remission of axillary and cervical lymph node metastases. Notably, treatment response is non-specific and cannot serve as retrospective proof of tumor tissue-of-origin.

This case highlights the potential adjunct value of the Canhelp^®-Origin assay in identifying the tissue of origin in CUP and underscores the supportive diagnostic role of TRPS1 immunohistochemistry in triple-negative breast cancer. These findings demonstrate the clinical utility of an integrated diagnostic strategy for the probabilistic classification of CUP, supporting its potential to guide effective treatment decisions in this challenging clinical setting.