Transcriptome Analysis Reveals the Molecular Immunological Characteristics of Lesions in Patients with Halo Nevi When Compared to Stable Vitiligo, Normal Nevocytic Nevi and Cutaneous Melanoma

Analysis of granulysin expression in vitiligo and halo-nevus

Vitiligo and halo nevus are immune-mediated skin diseases that have a similar pathogenesis and involve cellular cytotoxicity mechanisms that are not yet fully understood. In this study, we investigated the expression patterns of the cytolytic molecule granulysin (GNLY) in different cytotoxic cells in skin samples of vitiligo and halo nevus. Skin biopsies were taken from perilesional and lesional skin of ten vitiligo patients, eight patients with halo nevus and ten healthy controls. We analysed the expression of GNLY by immunohistochemistry in CD8+ and CD56+ NK cells. A significantly higher accumulation of GNLY+, CD8+ GNLY+ and fewer CD56+ GNLY+ cells was found in the lesional skin of vitiligo and halo nevus than in the healthy skin. These cells were localised in the basal epidermis and papillary dermis, suggesting that GNLY may be involved in the immune response against melanocytes. Similarly, but to a lesser extent, upregulation of GNLY+ and CD8+ GNLY+ cells was observed in the perilesional skin of vitiligo and halo nevus compared to healthy controls. In this study, we demonstrated for the first time an increased expression of CD8+ GNLY+ T lymphocytes and CD56+ GNLY+ NK cells in lesions of vitiligo and halo nevus, indicating the role of GNLY in the pathogenesis of both diseases.

Immune-Related lncRNA Pairs Clinical Prognosis Model Construction for Hepatocellular Carcinoma

Background

Long non-coding RNA (lncRNA) plays an essential regulatory role in the occurrence and development of hepatocellular carcinoma (HCC). This paper aims to establish an immune-related lncRNA (irlncRNA) pairs model independent of expression level for risk assessment and prognosis prediction of HCC.

Methods

Transcriptome data and corresponding clinical data were downloaded from TCGA. HCC patients were randomly divided into training group and test group. Univariate Cox regression analysis, LASSO regression analysis, and stepwise multiple Cox regression analysis were used to establish a prognostic model. The prediction ability of the model was verified by ROC curves. Next, the patients were divided into low-risk and high-risk groups. We compared the differences between the two groups in survival rate, clinicopathological characteristics, tumor immune cell infiltration status, chemotherapeutic drug sensitivity and immunosuppressive molecules.

Results

A prognosis prediction model was established based on 7 irlncRNA pairs, namely irlncRNA pairs (IRLP). ROC curves of the training group and test group showed that the IRLP model had high sensitivity and specificity for survival prediction. Kaplan–Meier analysis showed that the survival rate of the high-risk group was significantly lower than that of the low-risk group. Immune cell infiltration analysis showed that the high-risk group was significantly correlated with various immune cell infiltration. Finally, there were statistically significant differences in chemosensitivity and molecular marker expression between the two groups.

Conclusion

The prognosis prediction model established by irlncRNA pairs has a certain guiding significance for the prognosis prediction of HCC. It may provide valuable clinical applications in antitumor immunotherapy.