Background: Cutaneous squamous skin cell carcinoma (SCC) is the second most frequent type of non- melanoma skin cancer and the second cause of death by skin cancer in caucasian population. However, at present it is difficult to predict patients with worst SCC prognosis. Objective: To identify proteins whose expression level could predict SCC infiltration in SCC arising from actinic keratosis (AC). Methods: A total of 20 biopsies of 20 different patients were studied, 10 were from SCC-AK samples and 10 from normal skin. Early infiltrated SCC-AK were selected on histological examination and to determine the expression of proteins fresh skin samples were processed by 2DE-electrophoresis Results: The expression levels of three proteins namely alpha-hemoglobin, heat shock protein (Hsp)-27 and 70 were significantly increased in SCC-AK samples with respect to normal control skin. However, only the expression level of Hsp70 protein positively correlated with the level of SCC-AK dermis infiltration. Immnunohistological examination suggested that the increased expression of Hsp70 proteins seems to mainly occur in the keratinocytes cytoplasm. The increased cytoplasmic Hsp70 expression in SCC-AK was confirmed by Western-blot experiments. Conclusion: Cytoplasmic expression of Hsp70 could be potential biomarker of early infiltration of SCC arising from an AK. Keywords: actinic keratosis, cutaneous squamous cell carcinoma; cytoplasm, skin cancer; heat shock protein.

AK is a common precancerous skin condition that requires effective detection and treatment monitoring. To improve the monitoring of AK burden in clinical settings with enhanced automation and precision, the present study evaluates the application of semantic segmentation based on the U-Net architecture (AKU-Net). AKU-Net employs transfer learning to compensate for the relatively small dataset of annotated images and integrates a recurrent process based on convLSTM to exploit contextual information and address the challenges related to low contrast and ambiguous boundaries of AK-affected skin regions. We used an annotated dataset of 569 clinical photographs from 115 patients with actinic keratosis to train and evaluate the model. From each photograph, patches of 512x512 pixels were extracted using translation lesion boxes that encompass lesions in different positions and capture different contexts of perilesional skin. In total, 16488 translation augmented crops were used for training the model, and 403 lesion center crops were used for testing. To demonstrate the improvements in AK detection, AKU-net was compared with plain U-Net and U-Net++ architectures. The experimental results highlighted the effectiveness of AKU-Net, improving both automation and precision over existing approaches, paving the way for more effective and reliable evaluation of actinic keratosis in clinical settings.

Given the importance of peroxisome proliferator-activated receptor (PPAR)-gamma in epidermal inflammation and carcinogenesis, we analyzed transcriptomic changes observed in epidermal PPARγ deficient mice (Pparg-/-epi). Gene set enrichment analysis revealed a close association with epithelial malignancy, inflammatory cell chemotaxis and cell survival. Single cell sequencing of Pparg-/-epi mice verified changes to the stromal compartment, including increased inflammatory cell infiltrates, particularly neutrophils and an increase in fibroblasts expressing myofibroblast marker genes. A comparison of transcriptomic data from Pparg-/-epi and publicly available human and or mouse actinic keratoses (AK) and cutaneous squamous cell carcinomas (SCCs) revealed strong correlation between the datasets. Importantly, PPAR signaling was the top common inhibited canonical pathway in AK and SCC. Both AKs and SCCs also had significantly reduced PPARG expression and PPARγ activity z-scores. Smaller reductions in PPARA expression and PPARα activity and increased PPARD expression but reduced PPARδ activation were also observed. Reduced PPAR activity was also associated with reduced PPARα/RXRα activity while LPS/IL1-mediated inhibition of RXR activity was significantly activated in the tumor datasets. Notably. these changes are not observed in normal sun-exposed skin relative to non-exposed skin. Finally, Ppara and Pparg were heavily expressed in sebocytes while Ppard was highly expressed in myofibroblasts, suggesting a role for PPARδ in myofibroblast differentiation. In conclusion, these data indicate PPARγ and possibly PPARα represent key tumor suppressors by acting as master inhibitors of the inflammatory changes found in AKs and SCCs.