Identification of proteins associated with development of metastasis from cutaneous squamous cell carcinomas (cSCCs) via proteomic analysis of primary cSCCs

Background Cutaneous squamous cell carcinoma (cSCC) is one of the most common cancers capable of metastasising. Proteomic analysis of cSCCs can provide insight into biological processes responsible for metastasis as well as future therapeutic targets and prognostic biomarkers.Objectives This study aimed to identify proteins associated with development of metastasis in cSCC. Methods A proteomic-based approach was employed on 105 completely-excised, primary cSCCs, comprising 52 which metastasised (P-M) and 53 which had not metastasised at 5 years post-surgery (P-NM). Formalin-fixed, paraffin-embedded cSCCs were microdissected and subjected to proteomic profiling after one dimensional (1D), and separately two dimensional (2D), liquid chromatography fractionation. Results A discovery set of 24 P-Ms and 24 P-NMs identified 144 significantly differentially expressed proteins, including 33 proteins identified via both 1D and 2D separation, between P-Ms and P-NMs. Several differentially expressed proteins were also associated with survival in SCCs of other organs. Findings were verified by multiple reaction monitoring on 6 peptides from 2 proteins, Annexin A5 (ANXA5) and Dolichyl-diphosphooligosaccahride-protein glycosyltransferase non-catalytic subunit (DDOST), in the discovery group and validated on a separate cohort (n=57). Increased expression of ANXA5 and DDOST was associated with reduced time to metastasis in cSCC and decreased survival in cervical and oropharyngeal cancer. A prediction model using ANXA5 and DDOST had an area under the curve (AUC) of 0.929 (CI=0.8277-1), an accuracy of 91.18% and higher sensitivity and specificity than cSCC staging systems currently in clinical use.Conclusions This study highlights that increased expression of two proteins, ANXA5 and DDOST, is significantly associated with poorer clinical outcomes in cSCC.<br/

CD8+CD103+ tissue-resident memory T cells convey reduced protective immunity in cutaneous squamous cell carcinoma

Background Tumor infiltrating lymphocytes play a key role in antitumor responses; however, while several memory T-cell subtypes have been reported in inflammatory and neoplastic conditions, the proportional representation of the different subsets of memory T cells and their functional significance in cancer is unclear. Keratinocyte skin cancer is one of the most common cancers globally, with cutaneous squamous cell cancer (cSCC) among the most frequent malignancies capable of metastasis.Methods Memory T-cell subsets were delineated in human cSCCs and, for comparison, in non-lesional skin and blood using flow cytometry. Immunohistochemistry was conducted to quantify CD103+ cells in primary human cSCCs which had metastasized (P-M) and primary cSCCs which had not metastasized (P-NM). TIMER2.0 (timer.cistrome.org) was used to analyze TCGA cancer survival data based on ITGAE expression. Immunofluorescence microscopy was performed to determine frequencies of CD8+CD103+ cells in P-M and P-NM cSCCs.Results Despite intertumoral heterogeneity, most cSCC T cells were CCR7−/CD45RA− effector/resident memory (TRM) lymphocytes, with naive, CD45RA+/CCR7− effector memory re-expressing CD45RA, CCR7+/L-selectin+ central memory and CCR7+/L-selectin− migratory memory lymphocytes accounting for smaller T-cell subsets. The cSCC CD8+ T-cell population contained a higher proportion of CD69+/CD103+ TRMs than that in non-lesional skin and blood. These cSCC CD69+/CD103+ TRMs exhibited increased IL-10 production, and higher CD39, CTLA-4 and PD-1 expression compared with CD103− TRMs in the tumor. CD103+ cells were more frequent in P-M than P-NM cSCCs. Analysis of TCGA data demonstrated that high expression of ITGAE (encoding CD103) was associated with reduced survival in primary cutaneous melanoma, breast carcinoma, renal cell carcinoma, kidney chromophobe cancer, adrenocortical carcinoma and lower grade glioma. Immunofluorescence microscopy showed that the majority of CD103 was present on CD8+ T cells and that CD8+CD103+ cells were significantly more frequent in P-M than P-NM cSCCs.Conclusion These results highlight CD8+CD103+ TRMs as an important functional T-cell subset associated with poorer clinical outcome in this cancer

CD8+CD103+ tissue-resident memory T cells convey reduced protective immunity in cutaneous squamous cell carcinoma

Background Tumor infiltrating lymphocytes play a key role in antitumor responses; however, while several memory T-cell subtypes have been reported in inflammatory and neoplastic conditions, the proportional representation of the different subsets of memory T cells and their functional significance in cancer is unclear. Keratinocyte skin cancer is one of the most common cancers globally, with cutaneous squamous cell cancer (cSCC) among the most frequent malignancies capable of metastasis. Methods Memory T-cell subsets were delineated in human cSCCs and, for comparison, in non-lesional skin and blood using flow cytometry. Immunohistochemistry was conducted to quantify CD103+ cells in primary human cSCCs which had metastasized (P-M) and primary cSCCs which had not metastasized (P-NM). TIMER2.0 (timer.cistrome.org) was used to analyze TCGA cancer survival data based on ITGAE expression. Immunofluorescence microscopy was performed to determine frequencies of CD8+CD103+ cells in P-M and P-NM cSCCs. Results Despite intertumoral heterogeneity, most cSCC T cells were CCR7-/CD45RA- effector/resident memory (TRM) lymphocytes, with naive, CD45RA+/CCR7- effector memory re-expressing CD45RA, CCR7+/L-selectin+ central memory and CCR7+/L-selectin- migratory memory lymphocytes accounting for smaller T-cell subsets. The cSCC CD8+ T-cell population contained a higher proportion of CD69+/CD103+ TRMs than that in non-lesional skin and blood. These cSCC CD69+/CD103+ TRMs exhibited increased IL-10 production, and higher CD39, CTLA-4 and PD-1 expression compared with CD103- TRMs in the tumor. CD103+ cells were more frequent in P-M than P-NM cSCCs. Analysis of TCGA data demonstrated that high expression of ITGAE (encoding CD103) was associated with reduced survival in primary cutaneous melanoma, breast carcinoma, renal cell carcinoma, kidney chromophobe cancer, adrenocortical carcinoma and lower grade glioma. Immunofluorescence microscopy showed that the majority of CD103 was present on CD8+ T cells and that CD8+CD103+ cells were significantly more frequent in P-M than P-NM cSCCs. Conclusion These results highlight CD8+CD103+ TRMs as an important functional T-cell subset associated with poorer clinical outcome in this cancer.</p

Blood gene expression predicts intensive care unit admission in hospitalised patients with COVID-19

Background: The COVID-19 pandemic has created pressure on healthcare systems worldwide. Tools that can stratify individuals according to prognosis could allow for more efficient allocation of healthcare resources and thus improved patient outcomes. It is currently unclear if blood gene expression signatures derived from patients at the point of admission to hospital could provide useful prognostic information.Methods: Gene expression of whole blood obtained at the point of admission from a cohort of 78 patients hospitalised with COVID-19 during the first wave was measured by high resolution RNA sequencing. Gene signatures predictive of admission to Intensive Care Unit were identified and tested using machine learning and topological data analysis, TopMD.RResults: The best gene expression signature predictive of ICU admission was defined using topological data analysis with an accuracy: 0.72 and ROC AUC: 0.76. The gene signature was primarily based on differentially activated pathways controlling epidermal growth factor receptor (EGFR) presentation, Peroxisome proliferator-activated receptor alpha (PPAR-α) signalling and Transforming growth factor beta (TGF-β) signalling.Conclusions: Gene expression signatures from blood taken at the point of admission to hospital predicted ICU admission of treatment naïve patients with COVID-19

DataSheet_1_Blood gene expression predicts intensive care unit admission in hospitalised patients with COVID-19.docx

BackgroundThe COVID-19 pandemic has created pressure on healthcare systems worldwide. Tools that can stratify individuals according to prognosis could allow for more efficient allocation of healthcare resources and thus improved patient outcomes. It is currently unclear if blood gene expression signatures derived from patients at the point of admission to hospital could provide useful prognostic information.MethodsGene expression of whole blood obtained at the point of admission from a cohort of 78 patients hospitalised with COVID-19 during the first wave was measured by high resolution RNA sequencing. Gene signatures predictive of admission to Intensive Care Unit were identified and tested using machine learning and topological data analysis, TopMD.ResultsThe best gene expression signature predictive of ICU admission was defined using topological data analysis with an accuracy: 0.72 and ROC AUC: 0.76. The gene signature was primarily based on differentially activated pathways controlling epidermal growth factor receptor (EGFR) presentation, Peroxisome proliferator-activated receptor alpha (PPAR-α) signalling and Transforming growth factor beta (TGF-β) signalling.ConclusionsGene expression signatures from blood taken at the point of admission to hospital predicted ICU admission of treatment naïve patients with COVID-19.</p