ArticleJournal of translational medicine2006
A gene expression signature associated with survival in metastatic melanoma.
Article in Journal of translational medicine, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
44 citing papers in PubMed, 1 synthesis or guideline pooled it, 112 citations in OpenAlex.
- Gene signature of the metastatic potential of cutaneous melanoma: too much for too little?Clinical & experimental metastasis · 2010Pooled it
- AnInternational journal of molecular sciences · 2025Article
- EFHD1 expression is correlated with tumor-infiltrating neutrophils and predicts prognosis in gastric cancer.Heliyon · 2023Article
- Targets of Immune Escape Mechanisms in Cancer: Basis for Development and Evolution of Cancer Immune Checkpoint Inhibitors.Biology · 2023Review
- EFHD1 ablation inhibits cardiac mitoflash activation and protects cardiomyocytes from ischemia.Journal of molecular and cellular cardiology · 2022Article
- The mechanobiome: a goldmine for cancer therapeutics.American journal of physiology. Cell physiology · 2021Review
- Expressions of HLA Class II Genes in Cutaneous Melanoma Were Associated with Clinical Outcome: Bioinformatics Approaches and Systematic Analysis of Public Microarray and RNA-Seq Datasets.Diagnostics (Basel, Switzerland) · 2019Article
- A targeted genomic alteration analysis predicts survival of melanoma patients under BRAF inhibitors.Oncotarget · 2019Article
- Immunomagnetic-Enriched Subpopulations of Melanoma Circulating Tumour Cells (CTCs) Exhibit Distinct Transcriptome Profiles.Cancers · 2019Article
- Immune cell profiling in the age of immune checkpoint inhibitors: implications for biomarker discovery and understanding of resistance mechanisms.Mammalian genome : official journal of the International Mammalian Genome Society · 2018Review
- Human αβ and γδ T Cells in Skin Immunity and Disease.Frontiers in immunology · 2018Review
- Article
- Minimal residual disease in melanoma: circulating melanoma cells and predictive role of MCAM/MUC18/MelCAM/CD146.Cell death discovery · 2017Review
- Article
- Non-muscle myosin II in disease: mechanisms and therapeutic opportunities.Disease models & mechanisms · 2015Review
- Co-clinical assessment identifies patterns of BRAF inhibitor resistance in melanoma.The Journal of clinical investigation · 2015Article
- Tissue prognostic biomarkers in primary cutaneous melanoma.Virchows Archiv : an international journal of pathology · 2014Review
- Transcriptome profiling identifies HMGA2 as a biomarker of melanoma progression and prognosis.The Journal of investigative dermatology · 2013Article
- Tyrosinase-related protein 1 mRNA expression in lymph node metastases predicts overall survival in high-risk melanoma patients.British journal of cancer · 2013Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCurrent clinical and histopathological criteria used to define the prognosis of melanoma patients are inadequate for accurate prediction of clinical outcome. We investigated whether genome screening by means of high-throughput gene microarray might provide clinically useful information on patient survival.
methodsForty-three tumor tissues from 38 patients with stage III and stage IV melanoma were profiled with a 17,500 element cDNA microarray. Expression data were analyzed using significance analysis of microarrays (SAM) to identify genes associated with patient survival, and supervised principal components (SPC) to determine survival prediction.
resultsSAM analysis revealed a set of 80 probes, corresponding to 70 genes, associated with survival, i.e. 45 probes characterizing longer and 35 shorter survival times, respectively. These transcripts were included in a survival prediction model designed using SPC and cross-validation which allowed identifying 30 predicting probes out of the 80 associated with survival.
conclusionThe longer-survival group of genes included those expressed in immune cells, both innate and acquired, confirming the interplay between immunological mechanisms and the natural history of melanoma. Genes linked to immune cells were totally lacking in the poor-survival group, which was instead associated with a number of genes related to highly proliferative and invasive tumor cells.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.