The diagnosis and treatment of HCC remain a compelling challenge in the field of oncology. Bioinformatics-based approaches can offer effective strategies for diagnostic and therapeutic marker screening of tumors24, 25. PDCL3 is initially recognized in the retina owing to its connection to the purified transducer protein Gbg and the visual system26, 27, and its expression properties are also present in a variety of other tissues, such as the brain, liver, pineal gland, and olfactory epithelium28. In this study, we characterized that PDCL3 was a novel biomarker with high expression in HCC tissues, which was strictly implicated in poor prognosis of HCC. In addition, PDCL3 was able to enhance the proliferation, migration, and invasion of HCC cells and correlated with the Hippo pathway and YAP expression.
Bioinformatics mining-based genomic strategies offer the possibility of seeking reliable predictive and therapeutic HCC markers. Based on a single biomarker or a combination of multiple markers can provide abundant information for tumor diagnosis, including early diagnosis, therapeutic monitoring, prognostic assessment, and even immune infiltration information and drug resistance evaluation. PDCL3 is a poorly studied indicator, and its role and value in oncology are rarely reported. By conducting multiple bioinformatics analyses and siRNA experiments, we determined that PDCL3 could be used as an independent prognostic evaluator for HCC, which was an innovative discovery.
HCC is an immunologically heterogeneous entity that is subject to multiple modulations by a variety of immune cells, stromal cells, and HCC cells29, 30. Local infiltration of immune cells in tumors, such as macrophages and T cells, is an important ingredient of the tumor immune microenvironment31, 32. To further understand the pathological mechanism of PDCL3 in the development of HCC, the effect of PDCL3 on the tumor cycle and tumor microenvironment was investigated by immune cell infiltration analysis. Here, HCC patients were categorized into PDCL3 high and low expression groups, and activated dendritic cells (aDC), dendritic cells (DCs), induced dendritic cells (iDCs), macrophages, mast_cells, natural killer (NK) cells, follicular helper T cells (Tfhs), Th2_cells, and Tregs between these two groups were significantly different, while other immune cells displayed little significant changes. Notably, macrophages and Tregs were more numerous in the high-expression group than in the low-expression group, suggesting downregulation of immunoreactivity in high-risk patients. The macrophage M1 phenotype secretes pro-inflammatory cytokines and chemokines that cause inflammatory diseases and inhibit tumorigenesis, whereas the M2 phenotype promotes tumor development33–35. CD8 + T cells can inhibit tumor development by indirectly attacking tumor cells through secreting cytokines36, 37. In addition, APC co-inhibition, CCR, checkpoint, HLA, inflammatory paracrine response, and T-cell co-stimulation scores, were higher in the high-risk group than in the low-risk group, whereas type II IFN response signaling showed the opposite result. It indicates that the poor prognosis of HCC is inevitably and directly related to impaired immune function. These immunologic analyses further demonstrated the relevance of PDCL3 to the suppressive immune microenvironment of HCC, consistent with the previous finding that PDCL3 was a marker of poor prognosis.
Meanwhile, mutation analysis revealed that the mutation rate was considerably higher in HCC patients with a high abundance of PDCL3. TP53 is a comparatively frequently mutated phenotype in HCC and influences the malignant phenotype of HCC38. Mutant TP53 induces cells to suffer DNA damage to evade apoptosis and turn into carcinogenic cells. Furthermore, mutant TP53 downregulates the killing response of immune cells to cancer cells within the HCC microenvironment 39 Therefore, reducing the mutated level of TP53 by down-regulating the expression level of PDCL3 could potentially provide a viable option for inhibiting HCC.
YAP is engaged in modulating various malignant phenotypes of cancer cells and has a vital role in cancer progression40, 41. In HCC, the Hippo signaling pathway is an important tumor suppressor pathway by inhibiting hepatocyte bioactivity42. Studies have shown that low OS in HCC patients is associated with increased expression of the Hippo signaling pathway effector YAP43, 44. Furthermore, in hypoxic stress conditions, YAP binds to HIF-1α protein to enhance glycolysis in HCC cells45. Therefore, targeting YAP may be a futuristic approach for the management of HCC. In this study, enrichment analysis showed that those genes strongly correlated with PDCL3 were enriched to the Hippo pathway, and the expression of PDCL3 genes was positively correlated with key proteins of this pathway. Accordingly, we hypothesize that PDCL3 could regulate YAP activity, which in turn affects the development of HCC.
Of course, there are still some insufficient points in this study that are questionable. First, this study mainly used publicly available databases to analyze the potential HCC targets but lacked our databases and cohorts for analysis and validation. It also means that the acquisition and analysis of external real data is a necessity for bioinformatics research. Second, we have only identified the function of PDCL3 in promoting HCC by some basic biological experiments, but the detailed mechanism and the potential function of YAP have not been determined in many aspects. Finally, in vivo studies can be further conducted by taking genetically engineered mice and edited cells to determine the PDCL3-targeted therapeutic effect.