Strong immunoexpression of dickkopf-1 is associated with response to bortezomib in multiple myeloma

Dickkopf-1 Promotes Angiogenesis and is a Biomarker for Hepatic Stem Cell-like Hepatocellular Carcinoma

Cancer stemness evinces interest owing to the resulting malignancy and poor prognosis. We previously demonstrated that hepatic stem cell-like hepatocellular carcinoma (HpSC-HCC) is associated with high vascular invasion and poor prognosis. Dickkopf-1 (DKK-1), a Wnt signaling regulator, is highly expressed in HpSC-HCC. Here, we assessed the diagnostic and prognostic potential of serum DKK-1. Its levels were significantly higher in 391 patients with HCC compared with 205 patients with chronic liver disease. Receiver operating characteristic curve analysis revealed the optimal cutoff value of DKK-1 to diagnose HCC and predict the 3-year survival as 262.2 and 365.9 pg/mL, respectively. HCC patients with high-serum DKK-1 levels showed poor prognosis. We evaluated the effects of anti-DKK-1 antibody treatment on tumor growth in vivo and of recombinant DKK-1 on cell proliferation, invasion, and angiogenesis in vitro. DKK-1 knockdown decreased cancer cell proliferation, migration, and invasion. DKK-1 supplementation promoted angiogenesis in vitro; this effect was abolished by an anti-DKK-1 antibody. Co-injection of the anti-DKK-1 antibody with Huh7 cells inhibited their growth in NOD/SCID mice. Thus, DKK-1 promotes proliferation, migration, and invasion of HCC cells and activates angiogenesis in vascular endothelial cells. DKK-1 is a prognostic biomarker for HCC and a functional molecule for targeted therapy.

HMGB1 enhances chemotherapy resistance in multiple myeloma cells by activating the nuclear factor-κB pathway

Chemotherapy resistance is a main obstacle in the clinical chemotherapeutic treatment of multiple myeloma (MM). High-mobility group box 1 (HMGB1) has been revealed to be associated with the sensitivity of MM cells to chemotherapy, but how HMGB1 regulates chemotherapy resistance in MM has yet to be fully elucidated. In the present study, the exact molecular mechanism underlying HMGB1-mediated drug resistance in MM was explored using three chemotherapy-resistant MM cells (RPMI8226/ADR, RPMI8226/BOR and RPMI8226/DEX) that were successfully established. Reverse transcription-quantitative polymerase chain reaction revealed that the three chemotherapy-resistant MM cells exhibited a higher release of HMGB1 compared with the parental RPMI8226 cells. Interference with endogenous HMGB1 increased the sensitivity of drug-resistant MM cells to chemotherapy, which was supported by the low IC₅₀ value and the enlargement of cell apoptosis. Furthermore, short hairpin (sh)RNA-transfected MM cells showed an obvious elevation in phosphorylated (p)-IKKα/β, p-IκBα and p-p65 in whole cell lysate and/or nucleus, and treatment of nuclear factor (NF)-κB activator reversed the effect of shHMGB1-mediated cell viability and apoptosis in MM cells. In conclusion, HMGB1 regulates drug resistance in MM cells by regulating NF-κB signaling pathway, suggesting that HMGB1 has the potential to serve as a target for MM treatment.

Proteomic Profiling and Artificial Intelligence for Hepatocellular Carcinoma Translational Medicine

Hepatocellular carcinoma (HCC) is the most common primary cancer of the liver with high morbidity and mortality rates worldwide. Since 1963, when alpha-fetoprotein (AFP) was discovered as a first HCC serum biomarker, several other protein biomarkers have been identified and introduced into clinical practice. However, insufficient specificity and sensitivity of these biomarkers dictate the necessity of novel biomarker discovery. Remarkable advancements in integrated multiomics technologies for the identification of gene expression and protein or metabolite distribution patterns can facilitate rising to this challenge. Current multiomics technologies lead to the accumulation of a huge amount of data, which requires clustering and finding correlations between various datasets and developing predictive models for data filtering, pre-processing, and reducing dimensionality. Artificial intelligence (AI) technologies have an enormous potential to overcome accelerated data growth, complexity, and heterogeneity within and across data sources. Our review focuses on the recent progress in integrative proteomic profiling strategies and their usage in combination with machine learning and deep learning technologies for the discovery of novel biomarker candidates for HCC early diagnosis and prognosis. We discuss conventional and promising proteomic biomarkers of HCC such as AFP, lens culinaris agglutinin (LCA)-reactive L3 glycoform of AFP (AFP-L3), des-gamma-carboxyprothrombin (DCP), osteopontin (OPN), glypican-3 (GPC3), dickkopf-1 (DKK1), midkine (MDK), and squamous cell carcinoma antigen (SCCA) and highlight their functional significance including the involvement in cell signaling such as Wnt/β-catenin, PI3K/Akt, integrin αvβ3/NF-κB/HIF-1α, JAK/STAT3 and MAPK/ERK-mediated pathways dysregulated in HCC. We show that currently available computational platforms for big data analysis and AI technologies can both enhance proteomic profiling and improve imaging techniques to enhance the translational application of proteomics data into precision medicine.

Diagnostic accuracy of serum dickkopf-1 protein in diagnosis hepatocellular carcinoma: An updated meta-analysis

BACKGROUND

To verify the accuracy of serum dickkopf-1 protein (DKK-1) in the diagnosis of hepatocellular carcinoma (HCC) by an updated meta-analysis.

METHODS

We searched potential eligible studies in PubMed and Embase before July 8, 2018. Sensitivity (SN), specificity (SP), positive likelihood ratio (PLR), negative likelihood ratio (NLR), summary receiver operating characteristics curve (sROC), and diagnostic odds ratio (DOR) were pooled with their 95% confidence intervals CIs) using a bivariate random-effects model.

RESULTS

A total of 8 articles contained 10 studies on diagnosis of HCC with DKK-1 alone,7 articles contained 9 studies on diagnosis of HCC with a-fetoprotein (AFP) alone and 5 articles contained 7 studies on diagnosis of HCC with DKK-1 + AFP were identified. The pooled SN, SP, PLR, NLR, and DOR of DKK-1 alone, AFP alone and DKK-1 + AFP were 0.72 (95% CI: 0.70-0.75), 0.62 (95% CI:0.59-0.64) and 0.80 (95% CI:0.78-0.83), 0.86 (95% CI: 0.84-0.87), 0.82 (95% CI:0.80-0.84) and 0.87 (95% CI: 0.85-0.88), 4.91 (95% CI: 2.73-8.83), 3.60 (95% CI:2.01-6.44) and 6.18 (95% CI: 4.68-8.16), 0.32 (95% CI: 0.22-0.47), 0.49 (95% CI:0.40-0.60) and 0.20 (95% CI: 0.15-0.26), and 17.21 (95% CI: 9.10-32.57), 7.45 (95% CI:3.69-15.01) and 31.39 (95% CI: 23.59-43.20), respectively. The area under the sROC was 0.88, 0.70, and 0.92 for the 3 diagnostic methods.

CONCLUSIONS

Serum DKK-1 + AFP showed a high accuracy for diagnosis of HCC, and serum DKK-1 alone had moderate accuracy as compared to a previous meta-analysis, while AFP alone owned an unsatisfied diagnostic behavior for HCC. Due to the limitations of the current analysis, further well-designed studies are needed to confirm the diagnostic value of DKK-1 and DKK-1 + AFP in HCC diagnosis.

LncRNA H19 overexpression induces bortezomib resistance in multiple myeloma by targeting MCL-1 via miR-29b-3p

Radiotherapy, chemotherapy, autologous/allogeneic stem cell transplantation, and targeted drug therapy are currently available therapeutic options for multiple myeloma (MM), but the clinical outcome remains unsatisfactory owing to frequent occurrence of drug resistance. Anti apoptosis is one of the main mechanisms to mediate drug resistance. Studies have shown that MCL-1 plays a key role in the growth of cancer cells “escaping” drug attacks, but the underlying mechanism remains unclear. Our previous study demonstrated that lncRNA H19 was highly expressed in the serum of MM patients. Bioinformatics predicts that miR-29b-3p is the downstream target gene, and MCL-1 is the downstream target protein of miR-29b-3p. Therefore, we speculated that MCL-1 may be involved in the occurrence of drug resistance through epigenetics. On the basis of these previous findings, the present study was intended to explore the biological function of H19, interactions between the downstream target genes, and the effect of H19 on BTZ resistance of myeloma cells. In addition, in vivo experiments we have also confirmed that H19 promoted tumor growth and may develop resistance to bortezomib partly. It was found that H19 reduced cell sensitivity to the chemotherapeutic drug BTZ by working as a miRNA sponge to inhibit the expression of miR-29b-3p, enhance MCL-1 transcriptional translation and inhibit apoptosis. These findings may help gain insights into the molecular mechanism of acquired BTZ resistance and develop new drug targets for the clinical treatment of MM.