Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Transcriptional profiling of skin cancer NK cells reveals the elevated glucocorticoid receptor activity alters their pro-inflammatory features.

ABSTRACT: The interplay between natural killer (NK) cells and tumor microenvironment (TME) is closely associated with tumor progression. We showed NK cells are common constituents in the tissue of skin cancers including basal cell carcinoma (BCC), cutaneous squamous cell carcinoma (cSCC), extramammary paget disease (EMPD) and acral melanoma (aMM). scRNA-Seq revealed an inter and intra-tumor transcriptional heterogeneity of NK cells in different skin TMEs. Unexpectedly, compared to peri-tumor, skin tumor NK cells down regulated the production of anti-tumor cytokines, IFN-γ and TNF-α, and up regulated the production of amphiregulin (AREG), a ligand of epidermal growth factor receptor (EGFR), which functions in promoting skin tumor growth and mediating immune tolerance.

ORGANISM(S): Homo sapiens

PROVIDER: GSE242941 | GEO | 2026/01/14

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Differential expression analysis of cutaneous squamous cell carcinoma and basal cell carcinoma proteomic profiles sampled with e-biopsy

Project description:Clinical misdiagnosis between cutaneous squamous cell carcinoma (cSCC) and basal cell carcinoma (BCC) affects treatment plans and carries risks of potential for recurrence, metastases, morbidity and mortality. We report the development of a novel tissue sampling approach with molecular biopsy using electroporation. This method, coined e-biopsy, enables non-destructive non-thermal permeabilization of cells in the skin for efficient vacuum-assisted extraction of informative biomolecules for rapid diagnosis. We used e-biopsy for ex vivo proteome extraction from 3 locations per patient in 21 cSCC and 20 BCC pathologically validated human tissue samples. The total 123 extracted proteomes were profiled using LC/MS/MS. The obtained mass spectra presented significantly different proteome profiles for cSCC and BCC with several hundreds of proteins significantly differentially expressed in each tumor in comparison to the other. Notably, our study showed that proteomes sampled with e-biopsy from cSCC and BCC lesions are different, and that 7 proteins were significantly overexpressed in BCC in comparison to cSCC even after the Bonferroni correction (FDR=7.1e-03). Our results provide evidence that the e-biopsy approach could potentially be used as a tool to support cutaneous tumors classification with rapid molecular profiling.

2024-08-22 | PXD046711 | Pride

Deciphering dermatological distinctions: Cornulin as a discriminant biomarker between Basal Cell Carcinoma and Squamous Cell Carcinoma detected through E-biopsy and Machine Learning

Project description:Background: Clinical misdiagnosis between cutaneous squamous cell carcinoma (cSCC) and basal cell carcinoma (BCC) poses treatment challenges and carries risks of recurrence, metastases, and increased morbidity and mortality. Objective: We aimed to identify discriminant proteins markers for cSCC and BCC using a minimally invasive proteome sampling method called e-biopsy, employing electroporation for non-thermal cell permeabilization and machine learning. Methods: E-biopsy facilitated ex vivo proteome extraction from 21 cSCC and 21 BCC pathologically validated human cancers. LC/MS/MS profiling of 126 proteomes was followed by Machine Learning analysis to identify proteins distinguishing cSCC from BCC. For identified panel validation, we used proteomes sampled by e-biopsy from unrelated 20 cSCC and 46 BCC human cancers, and differential expression analysis of published transcriptomics. The most commonly chosen discriminant biomarker by machine learning models, cornulin, was also validated using fluorescent immunohistochemistry. Results: 192 proteomes sampled from 108 patients were analyzed. Machine Learning-based approaches resulted in a set of 11 potential biomarker proteins that can be used to construct a model with 95.2% average cross-validation accuracy, BCC precision of 93.6±14.5%, cSCC precision of 98.4±7.2%, specificity of 97.7±11.8%, and per-patient sensitivity 92.7±15.3%. Protein-protein interaction analysis revealed a novel interaction network connecting 10 of the 11 resulted proteins. Histological and transcriptomic validation confirmed cornulin as a discriminant marker significantly lower in cSCC than in BCC. Conclusions: E-biopsy combined with machine learning provides a novel approach to molecular biomarkers sampling from skin for biomarker detection and differential expression analysis between cSCC and BCC

2024-08-22 | PXD050713 | Pride

The secretome of skin cancer cells HaCat and A431

Project description:Cutaneous squamous cell carcinoma (cSCC) is the most prominent tumor of non-melanoma skin cancers and the most aggressive tumor among keratinocyte carcinoma of the skin, showing a high potential for local invasion and metastasis. The cSCC incidences increased dramatically in recent years and the disease occurs more commonly than any other malignancy. The secretome of cancer cells is currently the focus of many studies in order to identify new marker proteins for different types of cancer and to investigate its influence on the tumor microenvironment. In our study we evaluated whether the secretome of cSCC cells has an impact on keratinocytes, the surrounding tissue cells of cSCC. Therefore, we analyzed and compared the secretome of human A431 cancer cells and of HaCaT keratinocytes by mass spectrometry.

2020-04-15 | PXD017536 | Pride

Analysis of the gene expression profile in normal human epidermal keratinocytes and cutaneous squamous cell carcinoma cell lines

Project description:The incidence of keratinocyte-derived skin cancer, cutaneous squamous cell carcinoma (cSCC) is increasing worldwide making it the second most common metastatic skin cancer. We used microarrays to characterize gene expression profile in normal human epidermal keratinocytes (NHEK) and cSCC cell lines. Total RNAs from normal human epidermal keratinocytes (n=5) and cSCC cell lines (n=8) were extracted. The samples were processed for Affymetrix 3´ IVT Express Kit according to manufacture’s protocol.

2015-08-27 | E-GEOD-66359 | biostudies-arrayexpress

RNA-Seq whole transcriptome analysis of normal human epidermal keratinocytes and cutaneous squamous cell carcinoma cell lines.

Project description:The incidence of keratinocyte-derived skin cancer, cutaneous squamous cell carcinoma (cSCC) is increasing worldwide making it the second most common metastatic skin cancer. In this project we used SOLiD next generation sequencing to characterize gene expression profiles in normal human epidermal keratinocytes (NHEKs) and cSCC cell lines. Total RNAs from normal human epidermal keratinocytes (NHEKs) (n=4) and cSCC cell lines (n=8) were extracted. The samples were sequenced using SOLiD next generation sequencing.

2015-08-27 | E-GEOD-66412 | biostudies-arrayexpress

Molecular classification of non-melanoma skin cancer by gene expression profiling

Project description:Non-melanoma skin cancers (NMSC) including basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) are more common kinds of skin cancer. Although these tumors share common pathological and clinical features, their similarity and heterogeneity at molecular levels are not fully elaborated yet. Here, by performing comparative analysis of gene expression profiling of BCC, SCC, and normal skin tissues, we could classify the BCC into three subtypes of classical, SCC-like, and normal-like BCCs. Functional enrichment and pathway analyses revealed the molecular characteristics of each subtype. The analysis of gene expression profiling among non-melanoma skin cancer types

2014-12-13 | E-GEOD-53462 | biostudies-arrayexpress

Investigation of potential tumour suppressor or tumour promoter roles in cutaneous squamous cell carcinoma progression

Project description:Analysis of the combined dataset of normal skin, actinic keratosis and cutaneous squamous cell carcinoma (cSCC) previously submitted in (GSE45216) at genomic/transciptomic level. We identified potential cSCC driver genes significantly mutated and upregulated in cSCC relative to normal skin.

2018-06-14 | GSE98774 | GEO

In Silico Analysis Validates Proteomic Findings of Formalin-fixed Paraffin Embedded Cutaneous Squamous Cell Carcinoma Tissue

Project description:Background: Cutaneous squamous cell carcinoma (cSCC) is a common type of skin cancer but there are no comprehensive proteomic studies on this entity. Materials and Methods: We employed liquid chromatography coupled with tandem mass spectrometry (MS/MS) using formalin-fixed paraffin-embedded (FFPE) cSCC material to study the tumor and normal skin tissue proteomes. Ingenuity Pathway Analysis (IPA) was used to interpret the role of altered proteins in cSCC pathophysiology. Results were validated using the Human Protein Atlas and Oncomine database in silico. Results: Of 1,310 unique proteins identified, expression of an average of 144 and 88 proteins were significantly (p<0.05) increased and decreased, respectively, in the tumor samples compared to their normal counterparts. IPA analysis revealed disruptions in proteins associated with cell proliferation, apoptosis, and migration. In silico analysis confirmed that proteins corresponding to 12 antibodies, and genes corresponding to 18 proteins were differentially expressed between the two categories, validating our proteomic measurements. Conclusion: Label-free MS-based proteomics is useful for analyzing FFPE cSCC tissues.

2018-11-07 | PXD011492 | Pride

Molecular classification of non-melanoma skin cancer by gene expression profiling

2014-12-13 | GSE53462 | GEO

Single cell transcriptomics reveals dysregulated immnue homeostasis in different stages in HPV-induced cutaneous squamous cell carcinoma

Project description:Cutaneous squamous cell carcinoma (cSCC) is a common skin cancer in humans. HPV persistence in the epidermis and excessive wart or squamous is associated with cancer development. Various viral warts can be found on the skin infected with HPV, like condyloma acuminatum and bowenoid papulosis (BP). At present, it is believed that BP is a potential malignant squamous cell carcinoma in situ. In this study, we reported a very rare case of HPV-positive patient with concurrence of BP and cSCC. This patient progressed at a very fast rate and transferred to death quickly. To reveal the cell microenvironment changes from normal skin (NS) to BP and cSCC after HPV infection, we performed scRNA-seq on four pathological lesions skin (NS, BP, paracancerous squamous cell carcinoma (pc-cSCC) and cSCC) from this patient. Among immune cells, CD52+ macrophages were only detected in pc-cSCC and cSCC tissue, and two clusters of T cells, CD8+ Tex cells and CD4+ Tregs as well as matrix cells like MMP1+, MMP11+ fibroblasts were increased in pc-cSCC and cSCC tissue. Widely interactions were also found among specific T cells/macrophages and keratinocytes, which might be involve in the cSCC progress. Targeting these cells or their interactions may be beneficial for the diagnosis and treatment of cSCC.

2024-04-05 | GSE262947 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data