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Abstract Long non-coding RNAs (lncRNAs) have emerged as important players in cancer progression. Cutaneous squamous cell carcinoma (cSCC) is the most common metastatic skin cancer with increasing incidence worldwide. The prognosis of the metastatic cSCC is poor, and currently there are no established biomarkers to predict metastasis risk or specific therapeutic targets for advanced or metastatic cSCC. To elucidate the role of lncRNAs in cSCC, RNA sequencing of patient derived cSCC cell lines and normal human epidermal keratinocytes was performed. The correlation analysis of differentially expressed lncRNAs and protein-coding genes revealed six distinct gene clusters with one of the upregulated clusters featuring genes associated with cell motility. Upregulation of the expression of lncRNAs linked to cSCC cell motility in cSCC and head and neck SCC (HNSCC) cells was confirmed using qRT-PCR. Elevated expression of HOTTIP and LINC00543 was also noted in SCC tumors in vivo and was associated with poorer prognosis in HNSCC and lung SCC cohorts within TCGA data, respectively. Altogether, these findings uncover a novel set of lncRNAs implicated in cSCC cell locomotion. These lncRNAs may serve as potential novel biomarkers and as putative therapeutic targets for locally advanced and metastatic cSCC.

Abstract Cutaneous squamous cell carcinoma (cSCC) is the most common metastatic skin cancer. The incidence of cSCC is increasing globally and the prognosis of metastatic disease is poor. Currently there are no specific targeted therapies for advanced or metastatic cSCC. We have previously shown abundant expression of the complement classical pathway C1 complex components, serine proteases C1r and C1s in tumor cells in invasive cSCCs in vivo, whereas the expression of C1r and C1s was lower in cSCCs in situ, actinic keratoses and in normal skin. We have also shown that knockdown of C1s expression results in decreased viability and growth of cSCC cells by promoting apoptosis both in culture and in vivo. Here, we have studied the effect of specific IgG2a mouse monoclonal antibodies TNT003 and TNT005 targeting human C1s in five primary non-metastatic and three metastatic cSCC cell lines that show intracellular expression of C1s and secretion of C1s into the cell culture media. Treatment of cSCC cells with TNT003 and TNT005 significantly inhibited their growth and viability and promoted apoptosis of cSCC cells. These data indicate that TNT003 and TNT005 inhibit cSCC cell growth in culture and warrant further investigation of C1s targeted inhibition in additional in vitro and in vivo models of cSCC.

Abstract Cutaneous squamous cell carcinoma (cSCC) harbors metastatic potential and causes mortality. However, clinical assessment of metastasis risk is challenging. We approached this challenge by harnessing artificial intelligence (AI) algorithm to identify metastatic primary cSCCs. Residual neural network-architectures were trained with cross-validation to identify metastatic tumors on clinician annotated, hematoxylin and eosin-stained whole slide images representing primary non-metastatic and metastatic cSCCs (n = 104). Metastatic primary tumors were divided into two subgroups, which metastasize rapidly (≤ 180 days) (n = 22) or slowly (> 180 days) (n = 23) after primary tumor detection. Final model was able to predict whether primary tumor was non-metastatic or rapidly metastatic with slide-level area under the receiver operating characteristic curve (AUROC) of 0.747. Furthermore, risk factor (RF) model including prediction by AI, Clark’s level and tumor diameter provided higher AUROC (0.917) than other RF models and predicted high 5-year disease specific survival (DSS) for patients with cSCC with 0 or 1 RFs (100% and 95.7%) and poor DSS for patients with cSCCs with 2 or 3 RFs (41.7% and 40.0%). These results indicate, that AI recognizes unknown morphological features associated with metastasis and may provide added value to clinical assessment of metastasis risk and prognosis of primary cSCC.