Multi-omic analysis suggests tumor suppressor genes evolved specific promoter features to optimize cancer resistance

Zinc finger protein 263 upregulates interleukin 33 and suppresses autophagy to accelerate the malignant progression of non-small cell lung cancer

PURPOSE

Non-small cell lung cancer (NSCLC) is a complex disease that remains a major public health concern worldwide. One promising avenue for NSCLC treatment is the targeting of transcription factors that regulate key pathways involved in cancer progression. In this study, we investigated the role of the transcription factor ZNF263 in NSCLC and its impact on the regulation of IL33, apoptosis, and autophagy.

METHODS

Levels of ZNF263 in tissues and cell lines were identified, after which the effects of its knockdown on cellular malignant behaviors, apoptosis and autophagy were assessed. Based on bioinformatics analysis, ZNF263 was found to bind to IL33 promoter, their mutual relationship was confirmed, as well as the role of IL33 in the regulation of ZNF263. The involvement of ZNF263 in the growth of xenograft tumors was assessed using tumor-bearing nude mouse models.

RESULTS

Experimental results revealed that ZNF263 was upregulated in NSCLC tissue samples and cell lines. Its expression level is positively correlated with cellular malignant behaviors. We further demonstrated that ZNF263 upregulated IL33 expression, which, in turn, promoted the proliferation and migration, inhibited apoptosis and autophagy in NSCLC cells. Furthermore, ZNF263 knockdown reduced the growth of xenograft tumors in nude mice.

CONCLUSION

This finding suggests that the inhibition of ZNF263 or IL33 may represent a novel therapeutic strategy for NSCLC. Importantly, our results highlight the crucial role of transcription factors in NSCLC and their potential as therapeutic targets.

Adaptive risk-aware sharable and individual subspace learning for cancer survival analysis with multi-modality data

Biomedical multi-modality data (also named multi-omics data) refer to data that span different types and derive from multiple sources in clinical practices (e.g. gene sequences, proteomics and histopathological images), which can provide comprehensive perspectives for cancers and generally improve the performance of survival models. However, the performance improvement of multi-modality survival models may be hindered by two key issues as follows: (1) how to learn and fuse modality-sharable and modality-individual representations from multi-modality data; (2) how to explore the potential risk-aware characteristics in each risk subgroup, which is beneficial to risk stratification and prognosis evaluation. Additionally, learning-based survival models generally refer to numerous hyper-parameters, which requires time-consuming parameter setting and might result in a suboptimal solution. In this paper, we propose an adaptive risk-aware sharable and individual subspace learning method for cancer survival analysis. The proposed method jointly learns sharable and individual subspaces from multi-modality data, whereas two auxiliary terms (i.e. intra-modality complementarity and inter-modality incoherence) are developed to preserve the complementary and distinctive properties of each modality. Moreover, it equips with a grouping co-expression constraint for obtaining risk-aware representation and preserving local consistency. Furthermore, an adaptive-weighted strategy is employed to efficiently estimate crucial parameters during the training stage. Experimental results on three public datasets demonstrate the superiority of our proposed model.

3'untranslated regions of tumor suppressor genes evolved specific features to favor cancer resistance

Cancer-related genes have evolved specific genetic and genomic features to favor tumor suppression. Previously we reported that tumor suppressor genes (TSGs) acquired high promoter CpG dinucleotide frequencies during evolution to maintain high expression in normal tissues and resist cancer-specific downregulation. In this study, we investigated whether 3'untranslated regions (3'UTRs) of TSGs have evolved specific features to carry out similar functions. We found that 3'UTRs of TSGs, especially those involved in multiple histological types and pediatric cancers, are longer than those of non-cancer genes. 3'UTRs of TSGs also exhibit higher density of binding sites for RNA-binding proteins (RBPs), particularly those having high affinities to C-rich motifs. Both longer 3'UTR length and RBP binding sites enrichment are correlated with higher gene expression in normal tissues across tissue types. Moreover, both features together with the correlated N⁶-methyladenosine modification and the extent of protein-protein interactions are positively associated with the ability of TSGs to resist cancer-specific downregulation. These results were successfully validated with independent datasets. Collectively, these findings indicate that TSGs have evolved longer 3'UTR with increased propensity to RBP binding, N⁶-methyladenosine modification and protein-protein interactions for optimizing their tumor-suppressing functions.

Low Level of PALMD Contributes to the Metastasis of Uveal Melanoma

Uveal melanoma (UM) is a highly aggressive disease. There is an urgent need to develop the metastasis prediction markers of UM. This study aims to detect the key role of PALMD in UM metastasis. Transcriptome sequencing results of 2 sets of UM metastatic samples (GSE22138 and GSE156877) were downloaded from the Gene Expression Omnibus (GEO), and 18 overlapping differentially expressed genes were screened out, including PALMD. PALMD was significantly underexpressed in metastatic UM tissue. Low expression of PALMD was associated with poor prognosis in UM patients. The decreased expression of PALMD promoted the invasion and migration of 92-1 and Mel270 cells, while the high expression of PALMD inhibited the invasion and migration of UM cells. Furthermore, the levels of matrix metallopeptidase (MMP) 2 and MMP9 increased after transfection of siRNAs specifically targeting PALMD, whereas the levels of MMP2 and MMP9 were decreased after PALMD overexpression. However, PALMD did not affect the proliferation of UM cells. In addition, ZNF263 promoted the transcription of PALMD through the putative binding sequence using the JASPAR database, luciferase reporter gene analysis and chromatin immunoprecipitation assay. In summary, the expression of PALMD regulated by ZNF263 plays an important role in UM metastasis.

Single-Hit Inactivation Drove Tumor Suppressor Genes Out of the X Chromosome during Evolution

Cancer-related genes are under intense evolutionary pressure. In this study, we conjecture that X-linked tumor suppressor genes (TSG) are not protected by the Knudson's two-hit mechanism and are therefore subject to negative selection. Accordingly, nearly all mammalian species exhibited lower TSG-to-noncancer gene ratios on their X chromosomes compared with nonmammalian species. Synteny analysis revealed that mammalian X-linked TSGs were depleted shortly after the emergence of the XY sex-determination system. A phylogeny-based model unveiled a higher X chromosome-to-autosome relocation flux for human TSGs. This was verified in other mammals by assessing the concordance/discordance of chromosomal locations of mammalian TSGs and their orthologs in Xenopus tropicalis. In humans, X-linked TSGs are younger or larger in size. Consistently, pan-cancer analysis revealed more frequent nonsynonymous somatic mutations of X-linked TSGs. These findings suggest that relocation of TSGs out of the X chromosome could confer a survival advantage by facilitating evasion of single-hit inactivation.

SIGNIFICANCE

This work unveils extensive trafficking of TSGs from the X chromosome to autosomes during evolution, thus identifying X-linked TSGs as a genetic Achilles' heel in tumor suppression.