RESUMEN
Kindler syndrome (KS) is a rare genodermatosis resulting from loss-of-function mutations in FERMT1, the gene that encodes Kindlin-1. KS patients have a high propensity to develop aggressive and metastatic cutaneous squamous cell carcinoma (cSCC). Here we show in non-KS-associated patients that elevation of FERMT1 expression is increased in actinic keratoses compared to normal skin, with a further increase in cSCC supporting a pro-tumorigenic role in this population. In contrast, we show that loss of Kindlin-1 leads to increased SCC tumor growth in vivo and in 3D spheroids, which was associated with the development of a hypoxic tumor environment and increased glycolysis. The metalloproteinase Mmp13 was upregulated in Kindlin-1-depleted tumors, and increased expression of MMP13 was responsible for driving increased invasion of the Kindlin-1-depleted SCC cells. These results provide evidence that Kindlin-1 loss in SCC can promote invasion through the upregulation of MMP13, and offer novel insights into how Kindlin-1 loss leads to the development of a hypoxic environment that is permissive for tumor growth.
RESUMEN
The molecular basis of disease progression from UV-induced precancerous actinic keratosis (AK) to malignant invasive cutaneous squamous cell carcinoma (cSCC) and potentially lethal metastatic disease remains unclear. DNA sequencing studies have revealed a massive mutational burden but have yet to illuminate mechanisms of disease progression. Here we perform RNAseq transcriptomic profiling of 110 patient samples representing normal sun-exposed skin, AK, primary and metastatic cSCC and reveal a disease continuum from a differentiated to a progenitor-like state. This is accompanied by the orchestrated suppression of master regulators of epidermal differentiation, dynamic modulation of the epidermal differentiation complex, remodelling of the immune landscape and an increase in the preponderance of tumour specific keratinocytes. Comparative systems analysis of human cSCC coupled with the generation of genetically engineered murine models reveal that combinatorial sequential inactivation of the tumour suppressor genes Tgfbr2, Trp53, and Notch1 coupled with activation of Ras signalling progressively drives cSCC progression along a differentiated to progenitor axis. Taken together we provide a comprehensive map of the cSCC disease continuum and reveal potentially actionable events that promote and accompany disease progression.
Asunto(s)
Carcinoma de Células Escamosas , Queratosis Actínica , Neoplasias Cutáneas , Humanos , Animales , Ratones , Carcinoma de Células Escamosas/genética , Neoplasias Cutáneas/genética , Diferenciación Celular , Progresión de la Enfermedad , Perfilación de la Expresión GénicaRESUMEN
BACKGROUND: Metastasis of cutaneous squamous cell carcinoma (cSCC) is uncommon. Current staging methods are reported to have sub-optimal performances in metastasis prediction. Accurate identification of patients with tumors at high risk of metastasis would have a significant impact on management. OBJECTIVE: To develop a robust and validated gene expression profile signature for predicting primary cSCC metastatic risk using an unbiased whole transcriptome discovery-driven approach. METHODS: Archival formalin-fixed paraffin-embedded primary cSCC with perilesional normal tissue from 237 immunocompetent patients (151 nonmetastasizing and 86 metastasizing) were collected retrospectively from four centers. TempO-seq was used to probe the whole transcriptome and machine learning algorithms were applied to derive predictive signatures, with a 3:1 split for training and testing datasets. RESULTS: A 20-gene prognostic model was developed and validated, with an accuracy of 86.0%, sensitivity of 85.7%, specificity of 86.1%, and positive predictive value of 78.3% in the testing set, providing more stable, accurate prediction than pathological staging systems. A linear predictor was also developed, significantly correlating with metastatic risk. LIMITATIONS: This was a retrospective 4-center study and larger prospective multicenter studies are now required. CONCLUSION: The 20-gene signature prediction is accurate, with the potential to be incorporated into clinical workflows for cSCC.