Machine learning-derived immunosenescence index for predicting outcome and drug sensitivity in patients with skin cutaneous melanoma.

The functions of immunosenescence are closely related to skin cutaneous melanoma (SKCM). The aim of this study is to uncover the characteristics of immunosenescence index (ISI) to identify novel biomarkers and potential targets for treatment. Firstly, integrated bioinformatics analysis was carried out to identify risk prognostic genes, and their expression and prognostic value were evaluated. Then, we used the computational algorithm to estimate ISI. Finally, the distribution characteristics and clinical significance of ISI in SKCM by using multi-omics analysis. Patients with a lower ISI had a favorable survival rate, lower chromosomal instability, lower somatic copy-number alterations, lower somatic mutations, higher immune infiltration, and sensitive to immunotherapy. The ISI exhibited robust, which was validated in multiple datasets. Besides, the ISI is more effective than other published signatures in predicting survival outcomes for patients with SKCM. Single-cell analysis revealed higher ISI was specifically expressed in monocytes, and correlates with the differentiation fate of monocytes in SKCM. Besides, individuals exhibiting elevated ISI levels could potentially receive advantages from chemotherapy, and promising compounds with the potential to target high ISI were recognized. The ISI model is a valuable tool in categorizing SKCM patients based on their prognosis, gene mutation signatures, and response to immunotherapy.

Machine learning-derived identification of tumor-infiltrating immune cell-related signature for improving prognosis and immunotherapy responses in patients with skin cutaneous melanoma.

BACKGROUND: Immunoblockade therapy based on the PD-1 checkpoint has greatly improved the survival rate of patients with skin cutaneous melanoma (SKCM). However, existing anti-PD-1 therapeutic efficacy prediction markers often exhibit a poor situation of poor reliability in identifying potential beneficiary patients in clinical applications, and an ideal biomarker for precision medicine is urgently needed. METHODS: 10 multicenter cohorts including 4 SKCM cohorts and 6 immunotherapy cohorts were selected. Through the analysis of WGCNA, survival analysis, consensus clustering, we screened 36 prognostic genes. Then, ten machine learning algorithms were used to construct a machine learning-derived immune signature (MLDIS). Finally, the independent data sets (GSE22153, GSE54467, GSE59455, and in-house cohort) were used as the verification set, and the ROC index standard was used to evaluate the model. RESULTS: Based on computing framework, we found that patients with high MLDIS had poor overall survival and has good prediction performance in all cohorts and in-house cohort. It is worth noting that MLDIS performs better in each data set than almost all models which from 51 prognostic signatures for SKCM. Meanwhile, high MLDIS have a positive prognostic impact on patients treated with anti-PD-1 immunotherapy by driving changes in the level of infiltration of immune cells in the tumor microenvironment. Additionally, patients suffering from SKCM with high MLDIS were more sensitive to immunotherapy. CONCLUSIONS: Our study identified that MLDIS could provide new insights into the prognosis of SKCM and predict the immunotherapy response in patients with SKCM.

Knockdown of circular RNA VANGL1 inhibits TGF-ß-induced epithelial-mesenchymal transition in melanoma cells by sponging miR-150-5p.

Melanoma is one of the most aggressive and life-threatening skin cancers, and in this research, we aimed to explore the functional role of circular RNA VANGL1 (circVANGL1) in melanoma progression. The expression levels of circVANGL1 were observed to be significantly increased in clinical melanoma tissues and cell lines. Moreover, circVANGL1 knockdown suppressed, while circVANGL1 overexpression promoted the proliferation, migration and invasion abilities of melanoma cells. Further investigations confirmed the direct binding relation between circVANGL1 and miR-150-5p in melanoma, and restoration of miR-150-5p blocked the effects of circVANGL1 overexpression in melanoma cells. We further found that circVANGL1 was up-regulated by TGF-ß treatment, and the enhanced EMT of TGF-ß-treated melanoma cells was blocked by circVANGL1 knockdown. In conclusion, these results indicated that circVANGL1 might serve as a promising therapeutic target for melanoma.

Cupric-polymeric nanoreactors integrate into copper metabolism to promote chronic diabetic wounds healing.

Given multifunction of copper (Cu) contributing to all stages of the physiology of wound healing, Cu-based compounds have great therapeutic potentials to accelerate the wound healing, but they must be limited to a very low concentration range to avoid detrimental accumulation. Additionally, the cellular mechanism of Cu-based compounds participating the healing process remains elusive. In this study, copper oxide nanoparticles (CuONPs) were synthesized to mimic the multiple natural enzymes and trapped into PEG-b-PCL polymersomes (PS) to construct cupric-polymeric nanoreactors (CuO@PS) via a direct hydration method, thus allowing to compartmentalize Cu-based catalytic reactions in an isolated space to improve the efficiency, selectivity, recyclability as well as biocompatibility. While nanoreactors trafficked to lysosomes following endocytosis, the released Cu-based compounds in lysosomal lumen drove a cytosolic Cu+ influx to mobilize Cu metabolism mostly via Atox1-ATP7a/b-Lox axis, thereby activating the phosphorylation of mitogen-activated protein kinase 1 and 2 (MEK1/2) to initiate downstream signaling events associated with cell proliferation, migration and angiogenesis. Moreover, to facilitate to lay on wounds, cupric-polymeric nanoreactors were finely dispersed into a thermosensitive Pluronic F127 hydrogel to form a composite hydrogel sheet that promoted the healing of chronic wounds in diabetic rat models. Hence, cupric-polymeric nanoreactors represented an attractive translational strategy to harness cellular Cu metabolism for chronic wounds healing.

Enhancing cell pyroptosis with biomimetic nanoparticles for melanoma chemo-immunotherapy.

Despite the fact that immunotherapy has significantly improved the prognosis of melanoma patients, the non-response rate of monoimmunotherapy is considerably high due to insufficient tumor immunogenicity. Therefore, it is necessary to develop alternative methods of combination therapy with enhanced antitumor efficiency and less systemic toxicity. In this study, we reported a cancer cell membrane-coated zeolitic imidazole framework-8 (ZIF-8) encapsulating pyroptosis-inducer oxaliplatin (OXA) and immunomodulator imiquimod (R837) for chemoimmunotherapy. With the assistance of DNA methyltransferase inhibitor decitabine (DCT), upregulated Gasdermin E (GSDME) was cleaved by OXA-activated caspase-3, further inducing tumor cell pyroptosis, then localized antitumor immunity was enhanced by immune adjuvant R837, followed by triggering systemic antitumor immune responses. These results provided a proof-of-concept for the use of cell membrane-coated biomimetic nanoparticles as a promising drug carrier of combination therapy and a potential insight for pyroptosis-based melanoma chemo-immunotherapy.

circRNA-AKT1 Sequesters miR-942-5p to Upregulate AKT1 and Promote Cervical Cancer Progression.

Statistics show that the prognosis of cervical cancer (CC) is poor, and the death rate of CC in advanced stage has been rising in recent years. Increasing evidence has demonstrated that circular RNAs (circRNAs) serve as promising biomarkers in human cancers, including CC. The present study planned to find out the circRNA involved in CC and to explore its regulatory mechanism in CC. We discovered the new circRNA, circ-0033550, upregulated in CC. Its associated gene was AKT (also known as protein kinase B) serine/threonine kinase 1 (AKT1), so we renamed circ-0033550 as circ-AKT1. We confirmed the high expression of circ-AKT1 in CC samples and cell lines, as well as the circle structure of circ-AKT1. Functionally, gain- and loss-of-function experiments indicated that circ-AKT1 and AKT1 promoted CC cell proliferation and invasion. Moreover, circ-AKT1 and AKT1 were induced by transforming growth factor beta (TGF-ß) and facilitated EMT (epithelial-mesenchymal transition) in CC. Mechanically, we illustrated that circ-AKT1 upregulated AKT1 by sponging miR-942-5p. Rescue assays confirmed the role of the circ-AKT1/miR-942-5p/AKT1 axis in CC progression. In vivo assays validated that circ-AKT1 promoted tumor growth in CC. Overall, circRNA-AKT1 sequestered miR-942-5p to upregulate AKT1 and promote CC progression, which may offer a new molecular target for the treatment improvement of CC.