Hepatocellular Carcinoma: Old and Emerging Therapeutic Targets

Liver cancer, predominantly hepatocellular carcinoma (HCC), globally ranks sixth in incidence and third in cancer-related deaths. HCC risk factors include non-viral hepatitis, alcohol abuse, environmental exposures, and genetic factors. No specific genetic alterations are unequivocally linked to HCC tumorigenesis. Current standard therapies include surgical options, systemic chemotherapy, and kinase inhibitors, like sorafenib and regorafenib. Immunotherapy, targeting immune checkpoints, represents a promising avenue. FDA-approved checkpoint inhibitors, such as atezolizumab and pembrolizumab, show efficacy, and combination therapies enhance clinical responses. Despite this, the treatment of hepatocellular carcinoma (HCC) remains a challenge, as the complex tumor ecosystem and the immunosuppressive microenvironment associated with it hamper the efficacy of the available therapeutic approaches. This review explores current and advanced approaches to treat HCC, considering both known and new potential targets, especially derived from proteomic analysis, which is today considered as the most promising approach. Exploring novel strategies, this review discusses antibody drug conjugates (ADCs), chimeric antigen receptor T-cell therapy (CAR-T), and engineered antibodies. It then reports a systematic analysis of the main ligand/receptor pairs and molecular pathways reported to be overexpressed in tumor cells, highlighting their potential and limitations. Finally, it discusses TGFβ, one of the most promising targets of the HCC microenvironment.

Analysis of Breast Cancer Based on the Dysregulated Network

Breast cancer is a heterogeneous disease, and its development is closely associated with the underlying molecular regulatory network. In this paper, we propose a new way to measure the regulation strength between genes based on their expression values, and construct the dysregulated networks (DNs) for the four subtypes of breast cancer. Our results show that the key dysregulated networks (KDNs) are significantly enriched in critical breast cancer-related pathways and driver genes; closely related to drug targets; and have significant differences in survival analysis. Moreover, the key dysregulated genes could serve as potential driver genes, drug targets, and prognostic markers for each breast cancer subtype. Therefore, the KDN is expected to be an effective and novel way to understand the mechanisms of breast cancer.

Potential Applications of DNA, RNA and Protein Biomarkers in Diagnosis, Therapy and Prognosis for Colorectal Cancer: A Study from Databases to AI-Assisted Verification

In order to find out the most valuable biomarkers and pathways for diagnosis, therapy and prognosis in colorectal cancer (CRC) we have collected the published CRC biomarkers and established a CRC biomarker database (CBD: http://sysbio.suda.edu.cn/CBD/index.html). In this study, we analysed the single and multiple DNA, RNA and protein biomarkers as well as their positions in cancer related pathways and protein-protein interaction (PPI) networks to describe their potential applications in diagnosis, therapy and prognosis. CRC biomarkers were collected from the CBD. The RNA and protein biomarkers were matched to their corresponding DNAs by the miRDB database and the PubMed Gene database, respectively. The PPI networks were used to investigate the relationships between protein biomarkers and further detect the multiple biomarkers. The Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analysis and Gene Ontology (GO) annotation were used to analyse biological functions of the biomarkers. AI classification techniques were utilized to further verify the significances of the multiple biomarkers in diagnosis and prognosis for CRC. We showed that a large number of the DNA, RNA and protein biomarkers were associated with the diagnosis, therapy and prognosis in various degrees in the CRC biomarker networks. The CRC biomarkers were closely related to the CRC initiation and progression. Moreover, the biomarkers played critical roles in cellular proliferation, apoptosis and angiogenesis and they were involved in Ras, p53 and PI3K pathways. There were overlaps among the DNA, RNA and protein biomarkers. AI classification verifications showed that the combined multiple protein biomarkers played important roles to accurate early diagnosis and predict outcome for CRC. There were several single and multiple CRC protein biomarkers which were associated with diagnosis, therapy and prognosis in CRC. Further, AI-assisted analysis revealed that multiple biomarkers had potential applications for diagnosis and prognosis in CRC.

The systemic tumor response to RNase A treatment affects the expression of genes involved in maintaining cell malignancy

Recently, pancreatic RNase A was shown to inhibit tumor and metastasis growth that accompanied by global alteration of miRNA profiles in the blood and tumor tissue (Mironova et al., 2013). Here, we performed a whole transcriptome analysis of murine Lewis lung carcinoma (LLC) after treatment of tumor-bearing mice with RNase A. We identified 966 differentially expressed transcripts in LLC tumors, of which 322 were upregulated and 644 were downregulated after RNase A treatment. Many of these genes are involved in signaling pathways that regulate energy metabolism, cell-growth promoting and transforming activity, modulation of the cancer microenvironment and extracellular matrix components, and cellular proliferation and differentiation. Following RNase A treatment, we detected an upregulation of carbohydrate metabolism, inositol phosphate cascade and oxidative phosphorylation, re-arrangement of cell adhesion, cell cycle control, apoptosis, and transcription. Whereas cancer-related signaling pathways (e.g., TGF-beta, JAK/STAT, and Wnt) were downregulated following RNase A treatment, as in the case of the PI3K/AKT pathway, which is involved in the progression of non-small lung cancer. RNase A therapy resulted in the downregulation of genes that inhibit the biogenesis of some miRNAs, particularly the let-7 miRNA family.

Taken together, our data suggest that the antitumor activity and decreased invasion potential of tumor cells caused by RNase A are associated with enhanced energy cascade functioning, rearrangement of cancer-related events regulating cell growth and dissemination, and attenuation of signaling pathways having tumor-promoting activity. Thus, RNase A can be proposed as a potential component of anticancer therapy with multiple modes of action.