Downregulation of liver-intestine cadherin enhances cisplatin-induced apoptosis in human gastric cancer BGC823 cells

A state-of-art of underlying molecular mechanisms and pharmacological interventions/nanotherapeutics for cisplatin resistance in gastric cancer

The fourth common reason of death among patients is gastric cancer (GC) and it is a dominant tumor type in Ease Asia. One of the problems in GC therapy is chemoresistance. Cisplatin (CP) is a platinum compound that causes DNA damage in reducing tumor progression and viability of cancer cells. However, due to hyperactivation of drug efflux pumps, dysregulation of genes and interactions in tumor microenvironment, tumor cells can develop resistance to CP chemotherapy. The current review focuses on the CP resistance emergence in GC cells with emphasizing on molecular pathways, pharmacological compounds for reversing chemoresistance and the role of nanostructures. Changes in cell death mechanisms such as upregulation of pro-survival autophagy can prevent CP-mediated apoptosis that results in drug resistance. Moreover, increase in metastasis via EMT induction induces CP resistance. Dysregulation of molecular pathways such as PTEN, PI3K/Akt, Nrf2 and others result in changes in CP response of GC cells. Non-coding RNAs determine CP response of GC cells and application of pharmacological compounds with activity distinct of CP can result in sensitivity in tumor cells. Due to efficacy of exosomes in transferring bioactive molecules such as RNA and DNA molecules among GC cells, exosomes can also result in CP resistance. One of the newest progresses in overcoming CP resistance in GC is application of nanoplatforms for delivery of CP in GC therapy that they can increase accumulation of CP at tumor site and by suppressing carcinogenic factors and overcoming biological barriers, they increase CP toxicity on cancer cells.

Integrated transcriptomics and proteomics data analysis identifies CDH17 as a key cell surface target in colorectal cancer

Immunotherapy development against colorectal cancer (CRC) is hindered by the lack of cell surface target highly expressed in cancer cells but with restricted presence in normal tissues to minimize off-tumor toxicities. In this in silico analysis, a longlist of genes (n = 13,488) expressed in CRCs according to the Human Protein Atlas (HPA) database were evaluated to shortlist for potential surface targets based on the following prerequisites: (i) Absent from the brain and lung tissues to minimize the likelihood of neurologic and pulmonary toxicities; (ii) Restricted expression profile in other normal human tissues; (iii) Genes that potentially encode cell surface proteins and; (iv) At least moderately expressed in CRC cases. Fifteen potential targets were shortlisted and subsequently ranked according to the combination of their transcript and protein expression levels in CRCs derived from multiple datasets (i.e. DepMap, TCGA, CPTAC-2, and HPA CRCs). The top-ranked target with the highest and homogenous expression in CRCs was cadherin 17 (CDH17). Downstream analysis of CRC transcriptomics and proteomics datasets showed that CDH17 was significantly correlated with carcinoembryonic antigen expression. Moreover, CDH17 expression was significantly lower in CRC cases with high microsatellite instability, as well as negatively associated with immune response gene sets and the expression of MHC class I and II molecules. CDH17 represents an optimal target for therapeutic development against CRCs, and this study provides a novel framework to identify key cell surface targets for therapeutic development against other malignancies.

Gene regulatory network analysis with drug sensitivity reveals synergistic effects of combinatory chemotherapy in gastric cancer

The combination of docetaxel, cisplatin, and fluorouracil (DCF) is highly synergistic in advanced gastric cancer. We aimed to explain these synergistic effects at the molecular level. Thus, we constructed a weighted correlation network using the differentially expressed genes between Stage I and IV gastric cancer based on The Cancer Genome Atlas (TCGA), and three modules were derived. Next, we investigated the correlation between the eigengene of the expression of the gene network modules and the chemotherapeutic drug response to DCF from the Genomics of Drug Sensitivity in Cancer (GDSC) database. The three modules were associated with functions related to cell migration, angiogenesis, and the immune response. The eigengenes of the three modules had a high correlation with DCF (−0.41, −0.40, and −0.15). The eigengenes of the three modules tended to increase as the stage increased. Advanced gastric cancer was affected by the interaction the among modules with three functions, namely cell migration, angiogenesis, and the immune response, all of which are related to metastasis. The weighted correlation network analysis model proved the complementary effects of DCF at the molecular level and thus, could be used as a unique methodology to determine the optimal combination of chemotherapy drugs for patients with gastric cancer.