Abstract
Simple Summary Adenoid cystic carcinoma of the lacrimal gland is a rare but aggressive cancer with poor long-term prognosis. Due to the rarity of this cancer, little is understood about its molecular makeup, hindering the development of targeted therapeutic options to manage the disease. In this study, we combine the power of bulk RNA sequencing and the resolution of spatial transcriptomics to uncover the transcriptomic landscape of the cancer and its surrounding microenvironment. We identified novel transcriptomic signatures for the various cellular compartments within these cancer specimens and identified a putative cancer stem cell cluster which had not previously been reported and may be related to treatment resistance responses. We uncover a specific transcriptomic signature attributable to cancer foci and distinguish it from differential signatures previously reported in these tumors which arise from stromal and other tumor microenvironmental compartments. Elucidation of a cancer specific signature can be potentially harnessed in the development of advanced treatment options. Although primary tumors of the lacrimal gland are rare, adenoid cystic carcinoma (ACC) is the most common and lethal epithelial lacrimal gland malignancy. Traditional management of lacrimal gland adenoid cystic carcinoma (LGACC) involves the removal of the eye and surrounding socket contents, followed by chemoradiation. Even with this radical treatment, the 10-year survival rate for LGACC is 20% given the propensity for recurrence and metastasis. Due to the rarity of LGACC, its pathobiology is not well-understood, leading to difficulties in diagnosis, treatment, and effective management. Here, we integrate bulk RNA sequencing (RNA-seq) and spatial transcriptomics to identify a specific LGACC gene signature that can inform novel targeted therapies. Of the 3499 differentially expressed genes identified by bulk RNA-seq, the results of our spatial transcriptomic analysis reveal 15 upregulated and 12 downregulated genes that specifically arise from LGACC cells, whereas fibroblasts, reactive fibrotic tissue, and nervous and skeletal muscle account for the remaining bulk RNA-seq signature. In light of the analysis, we identified a transitional state cell or stem cell cluster. The results of the pathway analysis identified the upregulation of PI3K-Akt signaling, IL-17 signaling, and multiple other cancer pathways. This study provides insights into the molecular and cellular landscape of LGACC, which can inform new, targeted therapies to improve patient outcomes.