SHC1 sensitizes cancer cells to the 8-Cl-cAMP treatment

Pan-Cancer Study of SHC-Adaptor Protein 1 (SHC1) as a Diagnostic, Prognostic and Immunological Biomarker in Human Cancer

Background: Recent studies highlight the carcinogenesis role of SHC-adaptor protein 1 (SHC1) in cancer initiation, development, and progression. However, its aberrant expression, diagnostic and prognostic value remain unknown in a variety of tumors.

Methods: The SHC1 expression profiles were analyzed using GTEx database, TCGA database, Oncomine and CPTAC database. The survival analysis was conducted using GEPIA2, Kaplan-Meier Plotter, UALCAN, and PrognoScan. The diagnostic values of SHC1 were calculated with the “pROC” package in R software. The genetic alteration of SHC1 and mutations were analyzed using cBioPortal. TIMER2 was employed to estimate the correlations between SHC1 expression and tumor-infiltrating immune cells in the TCGA cohort. Enrichment analysis of SHC1 was conducted using the R package “clusterProfiler.”

Results: SHC1 was ubiquitously highly expressed and closely associated with worse prognosis of multiple major cancer types (all p < 0.05). Further, SHC1 gene mutations were strongly linked to poor OS and DFS in SKCM (all p < 0.05). An enhanced phosphorylation level of SHC1 at the S139 site was observed in clear cell RCC. Additionally, the results revealed SHC1 expression was strongly linked to TMB, MMRs, MSI, TAMs, DNA methylation, m6A RNA methylation, tumor-associated immune infiltration, and immune checkpoints in multiple cancers (all p < 0.05). In addition, the results of the ROC analysis indicated the SHC1 exhibited strong diagnostic capability for KICH (AUC = 0.92), LIHC (AUC = 0.95), and PAAD (AUC = 0.95). Finally, enrichment analysis indicated that SHC1 may potentially involve in the regulation of numerous signaling pathways in cancer metabolism and protein phosphorylation-related functions.

Conclusions: These findings highlight that SHC1 plays an important role in the tumor immune microenvironment, and SHC1 has been identified to have prognostic and diagnostic value in multiple cancers. Thus, SHC1 is a potential target for cancer immunotherapy and effective prognostic and diagnostic biomarker.

Identifying the biomarkers and pathways associated with hepatocellular carcinoma based on an integrated analysis approach

BACKGROUND AND AIMS

Hepatocellular carcinoma (HCC) is one of the most common causes of cancer-related death worldwide. The molecular mechanism underlying HCC is still unclear. In this study, we conducted a comprehensive analysis to explore the genes, pathways and their interactions involved in HCC.

METHODS

We analysed the gene expression datasets corresponding to 488 samples from 10 studies on HCC and identified the genes differentially expressed in HCC samples. Then, the genes were compared against Phenolyzer and GeneCards to screen those potentially associated with HCC. The features of the selected genes were explored by mapping them onto the human protein-protein interaction network, and a subnetwork related to HCC was constructed. Hub genes in this HCC specific subnetwork were identified, and their relevance with HCC was investigated by survival analysis.

RESULTS

We identified 444 differentially expressed genes (177 upregulated and 267 downregulated) related to HCC. Functional enrichment analysis revealed that pathways like p53 signalling and chemical carcinogenesis were eriched in HCC genes. In the subnetwork related to HCC, five disease modules were detected. Further analysis identified six hub genes from the HCC specific subnetwork. Survival analysis showed that the expression levels of these genes were negatively correlated with survival rate of HCC patients.

CONCLUSIONS

Based on a systems biology framework, we identified the genes, pathways, as well as the disease specific network related to HCC. We also found novel biomarkers whose expression patterns were correlated with progression of HCC, and they could be candidates for further investigation.

DEPDC1B is a tumor promotor in development of bladder cancer through targeting SHC1

Bladder cancer is one of the most commonly diagnosed malignant tumors in the urinary system and causes a massive cancer-related death. DEPDC1B is a DEP domain-containing protein that has been found to be associated with a variety of human cancers. This study aimed to explore the role and mechanism of DEPDC1B in the development of bladder cancer. The analysis of clinical specimens revealed the upregulated expression of DEPDC1B in bladder cancer, which was positively related to tumor grade. In vitro and in vivo studies showed that DEPDC1B knockdown could inhibit the growth of bladder cancer cells or xenografts in mice. The suppression of bladder cancer by DEPDC1B was executed through inhibiting cell proliferation, cell migration, and promoting cell apoptosis. Moreover, a mechanistic study found that SHC1 may be an important route through which DEPDC1B regulates the development of bladder cancer. Knockdown of SHC1 in DEPDC1B-overexpressed cancer cells could abolish the promotion effects induced by DEPDC1B. In conclusion, DEPDC1B was identified as a key regulator in the development of bladder cancer, which may be used as a potential therapeutic target in the treatment of bladder cancer.

Microcystin-LR-induced changes of hepatopancreatic transcriptome, intestinal microbiota, and histopathology of freshwater crayfish (Procambarus clarkii)

As a hepatotoxin, microcystin-LR (MC-LR) poses a great threat to aquatic organisms. In this research, the hepatopancreatic transcriptome, intestinal microbiota, and histopathology of Procambarus clarkii (P. clarkii) in response to acute MC-LR exposure were studied. RNA-seq analysis of hepatopancreas identified 372 and 781 differentially expressed genes (DEGs) after treatment with 10 and 40 μg/L MC-LR, respectively. Among the DEGs, 23 genes were immune-related and 21 genes were redox-related. GO functional enrichment analysis revealed that MC-LR could impact nuclear-transcribed mRNA catabolic process, cobalamin- and heme-related processes, and sirohydrochlorin cobaltochelatase activity of P. clarkii. In addition, the only significantly enriched KEGG pathway induced by MC-LR was galactose metabolism pathway. Meanwhile, sequencing of the bacterial 16S rRNA gene demonstrated that MC-LR decreased bacterial richness and diversity, and altered the intestinal microbiota composition. At the phylum level, after 96 h, the abundance of Verrucomicrobia decreased after treatment with 10 and 40 μg/L MC-LR, while Firmicutes increased in the 40 μg/L MC-LR-treated group. At the genus level, the abundances of 15 genera were significantly altered after exposure to MC-LR. Our research demonstrated that MC-LR exposure caused histological alterations such as structural damage of hepatopancreas and intestines. This research provides an insight into the mechanisms associated with MC-LR toxicity in aquatic crustaceans.

Identification of Targetable Pathways in Oral Cancer Patients via Random Forest and Chemical Informatics

Treatment of head and neck cancer has been slow to change with epidermal growth factor receptor (EGFR) inhibitors, PD1 inhibitors, and taxane-/plant-alkaloid-derived chemotherapies being the only therapies approved by the U.S. Food and Drug Administration (FDA) in the last 10 years for the treatment of head and neck cancers. Head and neck cancer is a relatively rare cancer compared to breast or lung cancers. However, it is possible that existing therapies for more common solid tumors or for the treatment of other diseases could also prove effective against oral cancers. Many therapies have molecular targets that could be appropriate in oral cancer as well as the cancer in which the drug gained initial FDA approval. Also, there may be targets in oral cancer for which existing FDA-approved drugs could be applied. This study describes informatics methods that use machine learning to identify influential gene targets in patients receiving platinum-based chemotherapy, non-platinum-based chemotherapy, and genes influential in both groups of patients. This analysis yielded 6 small molecules that had a high Tanimoto similarity (>50%) to ligands binding genes shown to be highly influential in determining treatment response in oral cancer patients. In addition to influencing treatment response, these genes were also found to act as gene hubs connected to more than 100 other genes in pathways enriched with genes determined to be influential in treatment response by a random forest classifier with 20 000 trees trying 320 variables at each tree node. This analysis validates the use of multiple informatics methods to identify small molecules that have a greater likelihood of efficacy in a given cancer of interest.

Yarrow supercritical extract exerts antitumoral properties by targeting lipid metabolism in pancreatic cancer

Metabolic reprogramming is considered a hallmark of cancer. Currently, the altered lipid metabolism in cancer is a topic of interest due to the prominent role of lipids regulating the progression of various types of tumors. Lipids and lipid-derived molecules have been shown to activate growth regulatory pathways and to promote malignancy in pancreatic cancer. In a previous work, we have described the antitumoral properties of Yarrow (Achillea Millefolium) CO₂ supercritical extract (Yarrow SFE) in pancreatic cancer. Herein, we aim to investigate the underlaying molecular mechanisms by which Yarrow SFE induces cytotoxicity in pancreatic cancer cells. Yarrow SFE downregulates SREBF1 and downstream molecular targets of this transcription factor, such as fatty acid synthase (FASN) and stearoyl-CoA desaturase (SCD). Importantly, we demonstrate the in vivo effect of Yarrow SFE diminishing the tumor growth in a xenograft mouse model of pancreatic cancer. Our data suggest that Yarrow SFE can be proposed as a complementary adjuvant or nutritional supplement in pancreatic cancer therapy.