Dataset Information

Transcriptional inhibition by CDK7/9 inhibitor SNS-032 abrogates oncogene addiction and reduces liver metastasis in uveal melanoma.

ABSTRACT:

Background

Life of patients with uveal melanoma (UM) is largely threatened by liver metastasis. Little is known about the drivers of liver organotropic metastasis in UM. The elevated activity of transcription of oncogenes is presumably to drive aspects of tumors. We hypothesized that inhibition of transcription by cyclin-dependent kinase 7/9 (CDK7/9) inhibitor SNS-032 diminished liver metastasis by abrogating the putative oncogenes in charge of colonization, stemness, cell motility of UM cells in host liver microenvironment.

Methods

The effects of SNS-032 on the expression of the relevant oncogenes were examined by qRT-PCR and Western blotting analysis. Proliferative activity, frequency of CSCs and liver metastasis were evaluated by using NOD-SCID mouse xenograft model and NOG mouse model, respectively.

Results

The results showed that CDK7/9 were highly expressed in UM cells, and SNS-032 significantly suppressed the cellular proliferation, induced apoptosis, and inhibited the outgrowth of xenografted UM cells and PDX tumors in NOD-SCID mice, repressed the cancer stem-like cell (CSC) properties through transcriptional inhibition of stemness-related protein Krüppel-like factor 4 (KLF4), inhibited the invasive phonotypes of UM cells through matrix metalloproteinase 9 (MMP9). Mechanistically, SNS-032 repressed the c-Myc-dependent transcription of RhoA gene, and thereby lowered the RhoA GTPase activity and actin polymerization, and subsequently inhibited cell motility and liver metastasis.

Conclusions

In conclusion, we validate a set of transcription factors which confer metastatic traits (e.g., KLF4 for CSCs, c-Myc for cell motility) in UM cells. Our results identify SNS-032 as a promising therapeutic agent, and warrant a clinical trial in patients with metastatic UM.

SUBMITTER: Zhang J

PROVIDER: S-EPMC6745806 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Simple Summary This study pursued the proteomic analysis of primary uveal melanoma (pUM) for insights into the mechanisms of metastasis and protein biomarkers. Liquid chromatography tandem mass spectrometry quantitative proteomic technology was used to analyze 53 metastasizing and 47 non-metastasizing pUM. The determined proteome of 3935 proteins was very similar between the metastasizing and non-metastasizing pUM, but included the identification of 402 differentially expressed (DE) proteins. Bioinformatic analyses suggest significant differences in the immune response between metastasizing and non-metastasizing pUM. Immune protein profiling results were consistent with transcriptomic studies, showing the immune-suppressive nature and low abundance of immune checkpoint regulators in pUM, and suggest CDH1, HLA-DPA1, and several DE immune kinases and phosphatases as potential targets for immune therapy checkpoint blockade. Prediction modeling of the proteomic data identified 32 proteins capable of predicting metastasizing versus non-metastasizing pUM with 93% discriminatory accuracy. Abstract Uveal melanoma metastases are lethal and remain incurable. A quantitative proteomic analysis of 53 metastasizing and 47 non-metastasizing primary uveal melanoma (pUM) was pursued for insights into UM metastasis and protein biomarkers. The metastatic status of the pUM specimens was defined based on clinical data, survival histories, prognostic analyses, and liver histopathology. LC MS/MS iTRAQ technology, the Mascot search engine, and the UniProt human database were used to identify and quantify pUM proteins relative to the normal choroid excised from UM donor eyes. The determined proteomes of all 100 tumors were very similar, encompassing a total of 3935 pUM proteins. Proteins differentially expressed (DE) between metastasizing and non-metastasizing pUM (n = 402) were employed in bioinformatic analyses that predicted significant differences in the immune system between metastasizing and non-metastasizing pUM. The immune proteins (n = 778) identified in this study support the immune-suppressive nature and low abundance of immune checkpoint regulators in pUM, and suggest CDH1, HLA-DPA1, and several DE immune kinases and phosphatases as possible candidates for immune therapy checkpoint blockade. Prediction modeling identified 32 proteins capable of predicting metastasizing versus non-metastasizing pUM with 93% discriminatory accuracy, supporting the potential for protein-based prognostic methods for detecting UM metastasis.