Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

The integration of single-cell sequencing, TCGA, and GEO data analysis revealed that PRRT3-AS1 is a biomarker and therapeutic target of SKCM

23 Sept 2022

Abstract excerpt

Introduction Skin cutaneous melanoma (SKCM) is the world’s fourth deadliest cancer, and advanced SKCM leads to a poor prognosis. Novel biomarkers for SKCM diagnosis and prognosis are urgently needed. Long non-coding RNAs (lncRNAs) provide various biological functions and have been proved to play a significant role in tumor progression. Single-cell RNA sequencing (scRNA-seq) enables genome analysis at the...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Cancer-related molecular mechanisms research
Share to Epigenetics and DNA Methylation
Share to Ferroptosis and cancer prognosis

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 36211371
DOI: 10.3389/fimmu.2022.919145

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

The integration of single-cell sequencing, TCGA, and GEO data analysis revealed that PRRT3-AS1 is a biomarker and therapeutic target of SKCMPMID 36211371Read ↗

Integration of single-cell and bulk RNA sequencing data reveals that CYTOR is a potential prognostic and immunotherapeutic response marker for skin cutaneous melanomaSemantic proximity Read ↗

Combining single-cell and bulk RNA sequencing to identify CAF-related signature for prognostic prediction and treatment response in patients with melanomaSemantic proximity Read ↗

The combination of single-cell and bulk RNA sequencing analysis decodes the melanoma tumor microenvironment and identifies novel T cell-associated signature genesSemantic proximity Read ↗

A cross-scale multimodal framework identifies clinically actionable immunotherapy biomarkers in melanoma through bulk to single-cell and spatial transcriptomics integrationSemantic proximity Read ↗

Identification of Transcriptional Heterogeneity and Construction of a Prognostic Model for Melanoma Based on Single-Cell and Bulk Transcriptome AnalysisSemantic proximity Read ↗

Construction of a tumor mutational burden-derived LncRNA prognostic computational framework associated with therapy sensitivity in skin cutaneous melanoma.Semantic proximity Read ↗

Mapping the single-cell landscape of acral melanoma and analysis of the molecular regulatory network of the tumor microenvironmentsSemantic proximity Read ↗

Single-cell RNA sequencing unveils tumor heterogeneity and immune microenvironment between subungual and plantar melanomaSemantic proximity Read ↗

Single-cell analysis unveils cell subtypes of acral melanoma cells at the early and late differentiation stagesSemantic proximity Read ↗

Single-cell sequencing analysis related to sphingolipid metabolism guides immunotherapy and prognosis of skin cutaneous melanomaSemantic proximity Read ↗

Single-cell RNA-sequencing analyses along with abundant machine learning methods develop and validate a novel metabolism-related prognostic model in SKCMSemantic proximity Read ↗

RARRES1 identified by comprehensive bioinformatic analysis and experimental validation as a promising biomarker in Skin Cutaneous MelanomaSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.