A Four-Gene-Based Prognostic Model Predicts Overall Survival in Patients With Cutaneous Melanoma

Tong, Xiaoxia; Qu, Xiaofei; Wang, Mengyun

doi:10.3389/fonc.2021.639874

Cited by 13 publications

(9 citation statements)

References 30 publications

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“…The macrophages and B cells express PU.1, which is required for myeloid cell differentiation ( Klemsz et al, 1990 ; Valledor et al, 1998 ). As reported by ( Tong et al, 2021 ), high ADAMDEC1 expression was significantly correlated with better prognosis. MARCO was also identified as one of six diagnostic and prognostic biomarkers for patients with lung adenocarcinoma ( Shang et al, 2017 ).…”

Section: Discussionsupporting

confidence: 66%

Identification of mRNA Signature for Predicting Prognosis Risk of Rectal Adenocarcinoma

Jiang

Wang

et al. 2022

Front. Genet.

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Background: The immune system plays a crucial role in rectal adenocarcinoma (READ). Immune-related genes may help predict READ prognoses.Methods: The Cancer Genome Atlas dataset and GSE56699 were used as the training and validation datasets, respectively, and differentially expressed genes (DEGs) were identified. The optimal DEG combination was determined, and the prognostic risk model was constructed. The correlation between optimal DEGs and immune infiltrating cells was evaluated.Results: Nine DEGs were selected for analysis. Moreover, ADAMDEC1 showed a positive correlation with six immune infiltrates, most notably with B cells and dendritic cells. F13A1 was also positively correlated with six immune infiltrates, particularly macrophage and dendritic cells, whereas LGALS9C was negatively correlated with all immune infiltrates except B cells. Additionally, the prognostic risk model was strongly correlated with the actual situation. We retained only three prognosis risk factors: age, pathologic stage, and prognostic risk model. The stratified analysis revealed that lower ages and pathologic stages have a better prognosis with READ. Age and mRNA prognostic factors were the most important factors in determining the possibility of 3- and 5-year survival.Conclusion: In summary, we identified a nine-gene prognosis risk model that is applicable to the treatment of READ. Altogether, characteristics such as the gene signature and age have a strong predictive value for prognosis risk.

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Section: Discussionsupporting

confidence: 66%

Identification of mRNA Signature for Predicting Prognosis Risk of Rectal Adenocarcinoma

Jiang

Wang

et al. 2022

Front. Genet.

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“…This antitumor activity of recombinant GRNLY was also demonstrated in vivo, initially by intratumoral injection in several tumors types: mammary carcinoma, multiple myeloma and melanoma [15,16]. There are abundant data that relate granulysin expression to an active antitumor immune response and to a good prognosis [31][32][33][34]. Although mice do not express a granulysin homologue, the Alan Krensky group generated transgenic mice that expressed human granulysin and showed an increased resistance to tumor development [35].…”

Section: Discussionmentioning

confidence: 97%

Preclinical Studies of Granulysin-Based Anti-Tn Immunotoxins as A New Antitumoral Treatment

Guerrero-Ochoa¹,

Ibáñez-Pérez²,

Berbegal-Pinilla³

et al. 2022

Preprint

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Two granulysin (GRNLY) based immunotoxins were generated, one containing the scFv of the SM3 mAb (SM3GRNLY) and the other the scFv of the AR20.5 mAb (AR20.5GRNLY). These mAb recognize different amino acid sequences of aberrantly O-glycosilated MUC1, also known as the Tn antigen, expressed in a variety of tumor cell types. We first demonstrated the affinity of these immunotoxins for their antigen using surface plasmon resonance for the purified antigen and flow cytometry for the antigen expressed on the surface of living tumor cells. The induction of cell death of tumor cell lines of different origin positive for Tn antigen expression was stronger in the cases of the immunotoxins than that induced by GRNLY alone. The mechanism of cell death induced by the immunotoxins was studied, showing that the apoptotic component demonstrated previously for GRNLY was also present, but that cell death induced by the immunotoxins included also necroptotic and necrotic components. Finally, we demonstrated the in vivo tumor targeting by the immunotoxins after systemic injection using a xenograft model of the human pancreatic adenocarcinoma CAPAN-2 in athymic mice. While GRNLY alone did not have a therapeutic effect, SM3GRNLY and AR20.5GRNLY reduced tumor volume by 42 and 60%, respectively, compared with untreated tumor-bearing mice, although the results were not statistically significant in the case of AR20.5GRNLY. Histological studies of tumors obtained from treated mice demonstrated reduced cellularity, nuclear morphology compatible with apoptosis induction and active caspase-3 detection by immunohistochemistry. Overall, our results exemplify that these immunotoxins are potential drugs to treat Tn-expressing cancers.

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“…Just recently, survival prognosis in melanoma was correlated with immune-related gene signatures (70)(71)(72). Of note, Danaher et al (73) found that TIS was also highly statistically significantly prognostic in TCGA-SKCM, limiting its predictive value in melanoma patients.…”

Section: Discussionmentioning

confidence: 99%

The Prognostic and Predictive Role of Xeroderma Pigmentosum Gene Expression in Melanoma

et al. 2022

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BackgroundAssessment of immune-specific markers is a well-established approach for predicting the response to immune checkpoint inhibitors (ICIs). Promising candidates as ICI predictive biomarkers are the DNA damage response pathway genes. One of those pathways, which are mainly responsible for the repair of DNA damage caused by ultraviolet radiation, is the nucleotide excision repair (NER) pathway. Xeroderma pigmentosum (XP) is a hereditary disease caused by mutations of eight different genes of the NER pathway, or POLH, here together named the nine XP genes. Anecdotal evidence indicated that XP patients with melanoma or other skin tumors responded impressively well to anti-PD-1 ICIs. Hence, we analyzed the expression of the nine XP genes as prognostic and anti-PD-1 ICI predictive biomarkers in melanoma.MethodsWe assessed mRNA gene expression in the TCGA-SKCM dataset (n = 445) and two pooled clinical melanoma cohorts of anti-PD-1 ICI (n = 75). In TCGA-SKCM, we applied hierarchical clustering on XP genes to reveal clusters, further utilized as XP cluster scores. In addition, out of 18 predefined genes representative of a T cell inflamed tumor microenvironment, the TIS score was calculated. Besides these scores, the XP genes, immune-specific single genes (CD8A, CXCL9, CD274, and CXCL13) and tumor mutational burden (TMB) were cross-correlated. Survival analysis in TCGA-SKCM was conducted for the selected parameters. Lastly, the XP response prediction value was calculated for the two pooled anti-PD-1 cohorts by classification models.ResultsIn TCGA-SKCM, expression of the XP genes was divided into two clusters, inversely correlated with immune-specific markers. A higher ERCC3 expression was associated with improved survival, particularly in younger patients. The constructed models utilizing XP genes, and the XP cluster scores outperformed the immune-specific gene-based models in predicting response to anti-PD-1 ICI in the pooled clinical cohorts. However, the best prediction was achieved by combining the immune-specific gene CD274 with three XP genes from both clusters.ConclusionOur results suggest pre-therapeutic XP gene expression as a potential marker to improve the prediction of anti-PD-1 response in melanoma.

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A Four-Gene-Based Prognostic Model Predicts Overall Survival in Patients With Cutaneous Melanoma

Cited by 13 publications

References 30 publications

Identification of mRNA Signature for Predicting Prognosis Risk of Rectal Adenocarcinoma

Identification of mRNA Signature for Predicting Prognosis Risk of Rectal Adenocarcinoma

Preclinical Studies of Granulysin-Based Anti-Tn Immunotoxins as A New Antitumoral Treatment

The Prognostic and Predictive Role of Xeroderma Pigmentosum Gene Expression in Melanoma

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