Increased level of circulating U2 small nuclear RNA fragments indicates metastasis in melanoma patients

AbstractMelanoma is the most aggressive skin cancer and, despite recent advances in therapy, about 20% of the patients die of their disease. Early relapse detection and monitoring of therapy response are crucial for efficient treatment of advanced melanoma. Thus, there is a need for blood-based biomarkers in melanoma management. Serum-derived U2 small nuclear RNA fragments (RNU2-1f) were previously shown to be blood-based biomarkers for gastrointestinal and gynecologic malignancies. Here we examined whether RNU2-1f may also serve as diagnostic biomarker in advanced melanoma.Circulating RNU2-1f levels were quantified by comparative reverse transcription PCR in a training cohort of patients with metastatic melanoma (n=33, thereof regionally metastasized to skin and lymph nodes, n=23, and distantly metastasized, n=10) vs. patients with benign naevi (n=16) vs. healthy controls (n=39). Results were validated in an independent patient cohort with distant metastasis (n=16) vs. controls (n=18).Circulating RNU2-1f levels in the training cohort were significantly increased in serum of regionally and distantly metastatic patients, compared with patients with benign naevi or healthy controls (p<0.0001) and allowed accurate detection of regional (AUC 0.80) as well as distant (AUC 0.84) metastasis. In the validation cohort, increased RNU2-1f levels were confirmed and enabled highly specific detection of distant metastasis (sensitivity 81%, specificity 100%, AUC 0.94).This is the first report to suggest a blood-based snRNA serving as a diagnostic biomarker for melanoma metastasis. Our data provide a rationale for further defining clinical utility of circulating RNU2-1f in metastasis detection in the management of melanoma patients at risk of relapse and/or with advanced disease.

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Circulating U2 small nuclear RNA fragments as a novel diagnostic biomarker for pancreatic and colorectal adenocarcinoma

International Journal of Cancer ◽

10.1002/ijc.27791 ◽

2012 ◽

Vol 132 (2) ◽

pp. E48-E57 ◽

Cited By ~ 92

Author(s):

Alexander Baraniskin ◽

Stefanie Nöpel-Dünnebacke ◽

Maike Ahrens ◽

Steffen Grann Jensen ◽

Hannah Zöllner ◽

...

Keyword(s):

Colorectal Adenocarcinoma ◽

Small Nuclear Rna ◽

Diagnostic Biomarker ◽

Nuclear Rna ◽

Rna Fragments

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Circulating U2 small nuclear RNA fragments as a novel diagnostic biomarker for primary central nervous system lymphoma

Neuro-Oncology ◽

10.1093/neuonc/nov144 ◽

2015 ◽

Vol 18 (3) ◽

pp. 361-367 ◽

Cited By ~ 22

Author(s):

Alexander Baraniskin ◽

Elena Zaslavska ◽

Stefanie Nöpel-Dünnebacke ◽

Guido Ahle ◽

Sabine Seidel ◽

...

Keyword(s):

Central Nervous System ◽

Nervous System ◽

Central Nervous System Lymphoma ◽

Small Nuclear Rna ◽

Diagnostic Biomarker ◽

Nuclear Rna ◽

Rna Fragments

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Analysis of U2 Small Nuclear RNA Fragments in the Bile Differentiates Cholangiocarcinoma from Primary Sclerosing Cholangitis and Other Benign Biliary Disorders

Digestive Diseases and Sciences ◽

10.1007/s10620-014-3034-5 ◽

2014 ◽

Vol 59 (7) ◽

pp. 1436-1441 ◽

Cited By ~ 10

Author(s):

Alexander Baraniskin ◽

Stefanie Nöpel-Dünnebacke ◽

Brigitte Schumacher ◽

Christian Gerges ◽

Thilo Bracht ◽

...

Keyword(s):

Primary Sclerosing Cholangitis ◽

Sclerosing Cholangitis ◽

Small Nuclear Rna ◽

Nuclear Rna ◽

Rna Fragments

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Circulating U2 small nuclear RNA fragments as a diagnostic and prognostic biomarker in lung cancer patients

Journal of Cancer Research and Clinical Oncology ◽

10.1007/s00432-015-2095-y ◽

2015 ◽

Vol 142 (4) ◽

pp. 795-805 ◽

Cited By ~ 16

Author(s):

Jens Köhler ◽

Martin Schuler ◽

Thomas Christoph Gauler ◽

Stefanie Nöpel-Dünnebacke ◽

Maike Ahrens ◽

...

Keyword(s):

Lung Cancer ◽

Cancer Patients ◽

Prognostic Biomarker ◽

Small Nuclear Rna ◽

Lung Cancer Patients ◽

Nuclear Rna ◽

Rna Fragments

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Down-regulation of lncRNA SNHG5 relieves sepsis-induced acute kidney injury by regulating the miR-374a-3p/TLR4/NF-κB pathway

The Journal of Biochemistry ◽

10.1093/jb/mvab008 ◽

2021 ◽

Author(s):

Min Wang ◽

Jilou Wei ◽

Futai Shang ◽

Kui Zang ◽

Peng Zhang

Keyword(s):

Acute Kidney Injury ◽

Noncoding Rna ◽

Kidney Injury ◽

Nuclear Factor Κb ◽

Nuclear Factor ◽

Healthy Controls ◽

Small Nuclear Rna ◽

Multiple Organs ◽

Nuclear Rna ◽

Insight Into

Abstract Sepsis is an acute systemic infectious disease engendered by infectious factors, which can cause the dysfunction of multiple organs, including acute kidney injury (AKI). Recently, more and more researchers are focussing on long noncoding RNA (lncRNA) that is closely associated with the development and progression of various diseases; however, the role and mechanism of lncRNA in sepsis-induced AKI are not fully understood. Here, we found a significant increase in the expression of lncRNA small nuclear RNA host gene 5 (SNHG5) in the serum of patients with sepsis than healthy controls. Similar results were obtained from mouse model of sepsis. Further investigations revealed that knockdown of SNHG5 improves the viability and reduces the rate of apoptosis and the generation of inflammatory cytokines in HK-2 and TCMK-1 cells treated with lipopolysaccharide. Mechanistically, we showed that SNHG5 can combine with microRNA-374a-3p (miR-374a-3p), which inhibits nuclear factor-κB (NF-κB) activity by targeting TLR4. In conclusion, our results demonstrate that SNHG5 may regulate sepsis-induced AKI via the miR-374a-3p/TLR4/NF-κB pathway, therefore providing a new insight into the treatment of this disease.

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The prognostic significance of distant metastasis free interval (DMFI) in BRAF mutant advanced melanoma patients treated with first line targeted therapy

Annals of Oncology ◽

10.1093/annonc/mdx377.029 ◽

2017 ◽

Vol 28 ◽

pp. v441

Author(s):

D. Bafaloukos ◽

H. Linardou ◽

P. Diamantopoulos ◽

T. Sergentanis ◽

A. Laskarakis ◽

...

Keyword(s):

Targeted Therapy ◽

Distant Metastasis ◽

Prognostic Significance ◽

Advanced Melanoma ◽

First Line ◽

Free Interval ◽

Melanoma Patients ◽

Braf Mutant

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Identification of 15 lncRNAs Signature for Predicting Survival Benefit of Advanced Melanoma Patients Treated with Anti-PD-1 Monotherapy

Cells ◽

10.3390/cells10050977 ◽

2021 ◽

Vol 10 (5) ◽

pp. 977

Author(s):

Jian-Guo Zhou ◽

Bo Liang ◽

Jian-Guo Liu ◽

Su-Han Jin ◽

Si-Si He ◽

...

Keyword(s):

Network Analysis ◽

Differentially Expressed Genes ◽

Survival Benefit ◽

Validation Cohort ◽

Enrichment Analysis ◽

Advanced Melanoma ◽

Differentially Expressed ◽

Training Cohort ◽

Melanoma Patients ◽

Selection Operator

The blockade of programmed cell death protein 1 (PD-1) as monotherapy has been widely used in melanoma, but to identify melanoma patients with survival benefit from anti-PD-1 monotherapy is still a big challenge. There is an urgent need for prognostic signatures improving the prediction of immunotherapy responses of these patients. We analyzed transcriptomic data of pre-treatment tumor biopsies and clinical profiles in advanced melanoma patients receiving only anti-PD-1 monotherapy (nivolumab or pembrolizumab) from the PRJNA356761 and PRJEB23709 data sets as the training and validation cohort, respectively. Weighted gene co-expression network analysis was used to identify the key module, then least absolute shrinkage and selection operator was conducted to determine prognostic-related long noncoding RNAs (lncRNAs). Subsequently, the differentially expressed genes between different clusters were identified, and their function and pathway annotation were performed. In this investigation, 92 melanoma patients with complete survival information (51 from training cohort and 41 from validation cohort) were included in our analyses. We initiallyidentified the key module (skyblue) by weighted gene co-expression network analysis, and then identified a 15 predictive lncRNAs (AC010904.2, LINC01126, AC012360.1, AC024933.1, AL442128.2, AC022211.4, AC022211.2, AC127496.5, NARF-AS1, AP000919.3, AP005329.2, AC023983.1, AC023983.2, AC139100.1, and AC012615.4) signature in melanoma patients treated with anti-PD-1 monotherapy by least absolute shrinkage and selection operator in the training cohort. These results were then validated in the validation cohort. Finally, enrichment analysis showed that the functions of differentially expressed genes between two consensus clusters were mainly related to the immune process and treatment. In summary, the 15 lncRNAs signature is a novel effective predictor for prognosis in advanced melanoma patients treated with anti-PD-1 monotherapy.

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Faculty of 1000 evaluation for A phase IB study on intravenous synthetic mRNA electroporated dendritic cell immunotherapy in pretreated advanced melanoma patients.

F1000 - Post-publication peer review of the biomedical literature ◽

10.3410/f.718056364.793482065 ◽

2013 ◽

Author(s):

Mark Faries

Keyword(s):

Dendritic Cell ◽

Advanced Melanoma ◽

Phase Ib ◽

Cell Immunotherapy ◽

Melanoma Patients ◽

Synthetic Mrna

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673 Precision microbiome mapping identifies a microbiome signature predictive of Immune checkpoint inhibitor response across multiple research study cohorts

Journal for ImmunoTherapy of Cancer ◽

10.1136/jitc-2020-sitc2020.0673 ◽

2020 ◽

Vol 8 (Suppl 3) ◽

pp. A711-A711

Author(s):

Matthew Robinson ◽

Kevin Vervier ◽

Simon Harris ◽

David Adams ◽

Doreen Milne ◽

...

Keyword(s):

Gut Microbiome ◽

Immune Checkpoint ◽

Immune Checkpoint Inhibitor ◽

Checkpoint Inhibitor ◽

Advanced Melanoma ◽

List Type ◽

Metagenomic Sequencing ◽

Genome Database ◽

Sequencing Platform ◽

Melanoma Patients

BackgroundThe gut microbiome of cancer patients appears to be associated with response to Immune Checkpoint Inhibitor (ICIs) treatment.1–4 However, the bacteria linked to response differ between published studies.MethodsLongitudinal stool samples were collected from 69 patients with advanced melanoma receiving approved ICIs in the Cambridge (UK) MELRESIST study. Pretreatment samples were analysed by Microbiotica, using shotgun metagenomic sequencing. Microbiotica’s sequencing platform comprises the world’s leading Reference Genome Database and advanced Microbiome Bioinformatics to give the most comprehensive and precise mapping of the gut microbiome. This has enabled us to identify gut bacteria associated with ICI response missed using public reference genomes. Published microbiome studies in advanced melanoma,1–3renal cell carcinoma (RCC) and non-small cell lung cancer (NSCLC)4 were reanalysed with the same platform.ResultsAnalysis of the MELRESIST samples showed an overall change in the microbiome composition between advanced melanoma patients and a panel of healthy donor samples, but not between patients who subsequently responded or did not respond to ICIs. However, we did identify a discrete microbiome signature which correlated with response. This signature predicted response with an accuracy of 93% in the MELRESIST cohort, but was less predictive in the published melanoma cohorts.1–3 Therefore, we developed a bioinformatic analytical model, incorporating an interactive random forest model and the MELRESIST dataset, to identify a microbiome signature which was consistent across all published melanoma studies. This model was validated three times by accurately predicting the outcome of an independent cohort. A final microbiome signature was defined using the validated model on MELRESIST and the three published melanoma cohorts. This was very accurate at predicting response in all four studies combined (91%), or individually (82–100%). This signature was also predictive of response in a NSCLC study and to a lesser extent in RCC. The core of this signature is nine bacteria significantly increased in abundance in responders.ConclusionsAnalysis of the MELRESIST study samples, precision microbiome profiling by the Microbiotica Platform and a validated bioinformatic analysis, have enabled us to identify a unique microbiome signature predictive of response to ICI therapy in four independent melanoma studies. This removes the challenge to the field of different bacteria apparently being associated with response in different studies, and could represent a new microbiome biomarker with clinical application. Nine core bacteria may be driving response and hold potential for co-therapy with ICIs.Ethics ApprovalThe study was approved by Newcastle & North Tyneside 2 Research Ethics Committee, approval number 11/NE/0312.ReferencesMatson V, Fessler J, Bao R, et al. The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients. Science 2018;359(6371):104–108.Gopalakrishnan V, Spencer CN, Nezi L, et al. Gut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients. Science 2018;359(6371):97–103.Frankel AE, Coughlin LA, Kim J, et al. Metagenomic shotgun sequencing and unbiased metabolomic profiling identify specific human gut microbiota and metabolites associated with immune checkpoint therapy efficacy in melanoma patients. Neoplasia 2017;19(10):848–855.Routy B, Le Chatelier E, Derosa L, et al. Gut microbiome influences efficacy of PD-1-based immunotherapy against epithelial tumors. Science 2018;359(6371):91–97.

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