Diagnostic and prognostic values of AKR1C3 and AKR1D1 in hepatocellular carcinoma

AKR1C3 mediates gastric cancer cell invasion and metastasis via the AKT and JNK/p-NF-κB signaling pathways

Gastric cancer (GC) is globally recognized as the fifth most common cancer and the third leading cause of cancer-related mortality. Early metastasis in GC significantly contributes to its high mortality and unfavorable prognosis. However, the underlying mechanisms of this phenomenon remain largely unexplored. Among the various factors involved, AKR1C3 has emerged as a crucial component in the pathways of tumorigenesis and metastasis across multiple cancer types. Yet, the precise significance of AKR1C3 in GC patients' prognosis and its role in GC progression remain elusive. This study illuminated the significant downregulation of AKR1C3 in GC tissues, linking it to an aggressive phenotype and poor prognosis. Interestingly, while AKR1C3 overexpression did not affect the proliferation of GC cells, it significantly inhibited their ability to invade and metastasize. The underlying mechanism appears to involve AKR1C3's inhibition of the p-JNK pathway, which leads to reduced phosphorylation of IKKα/β and IKBα, lowering p-NF-κB levels and hindering its movement into the nucleus, thereby stifling the epithelial-mesenchymal transition (EMT) process in GC cells. These insights reveal AKR1C3's tumor-suppressive effects in GC and suggest its potential as a diagnostic and prognostic biomarker, offering new avenues for targeted therapies in gastric cancer management.

Network pharmacology and bioinformatic integrative analysis reveals candidate gene targets and potential therapeutic of East Kalimantan propolis against hepatocellular carcinoma

Introduction

Hepatocellular Carcinoma (HCC) is commonly treated with surgery, liver transplantation, and chemotherapy, but recurrence and metastasis remain challenges. Natural complementary therapies like propolis, known for its hepatoprotective properties, are gaining interest due to limited efficacy and toxicity of conventional chemotherapy. This study aims to identify core targets for HCC, assess the therapeutic potential of East Kalimantan propolis (EKP) from stingless bees, and analyze the molecular interactions.

Methods

EKP compounds were analyzed using target prediction tools related to HCC, alongside clinical data from the Gene Expression Omnibus (GEO) database, to identify overlapping genes with clinical relevance. The selected genes were then subjected to protein-protein interaction (PPI), GO and KEGG enrichment, immunohistochemical comparison and survival analysis to identify potential core targets and related pathways for HCC therapy. Furthermore, molecular docking and dynamics were conducted to verify the molecular interactions and stability of EKP compounds with targets.

Results

108 genes have been selected as HCC potential targets, which mostly associated with MicroRNAs in cancer, chemical carcinogenesis, and viral carcinogenesis pathways. These targets were obtained by overlapping genes from GEO clinical databases and target predictors. PPI network analysis revealed 4 main targets of propolis in HCC. Furthermore, differential expression genes, survival analysis, and Immunohistochemical analysis from databases suggested that AKR1C3 and MAPK1 promote HCC progression and shorten survival rate of HCC patients. Molecular docking and dynamic studies confirmed strong binding affinity and stability of Baicalein, Chrysin, Quercetin, and Myricetin with receptor targets within simulation time.

Conclusions

This study provides insight into the mechanism of action of EKP on HCC and identifies AKR1C3 and MAPK1 as candidate target treatments for future drug development.

Prognostic Prediction and Immune Microenvironment Characterization in Uveal Melanoma: A Novel Mitochondrial Metabolism-Related Gene Signature

Uveal Melanoma (UM), a highly aggressive and metastatic intraocular cancer with a strong propensity for liver metastasis, presents limited therapeutic alternatives and unfavorable survival outcomes. Despite its low incidence, the underlying mechanisms of UM pathogenesis and the precise role of mitochondrial metabolism in UM remain inadequately understood. Utilizing Cox proportional hazards regression analysis was used to assess prognostic relevance, and consensus clustering was employed for molecular subtyping. A risk signature was constructed using Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression. We further conducted comparative analyses on clinicopathological characteristics, somatic mutation profiles, drug sensitivity, gene expression patterns, and tumor microenvironment features across different molecular subtypes. Moreover, a nomogram was developed and evaluated. Among 1234 mitochondria metabolism-related genes (MMRGs), 343 were identified as significantly associated with the prognosis of UM. These prognosis-associated MMRGs facilitated the classification of UM into two distinct molecular subtypes, which displayed notable differences in prognosis and pathological staging. Furthermore, an index termed the MMRGs-derived index (MMI) was derived from eight MMRGs, serving as a quantitative measure for poor prognosis risk in UM. MMI demonstrated significant associations with clinicopathological characteristics, somatic mutations, drug responsiveness, and the tumor microenvironment, where higher MMI levels corresponded to worse prognosis, advanced pathological stages, and increased immune cell infiltration. The nomogram built upon MMI provided a potential tool for clinical prognosis assessment in UM patients. This study demonstrated the potential value of MMRGs in predicting prognosis and molecular stratification within UM; however, additional clinical and basic research is warranted to validate their applicability and elucidate the related mechanisms.

Resveratrol suppresses liver cancer progression by downregulating AKR1C3: targeting HCC with HSA nanomaterial as a carrier to enhance therapeutic efficacy

The enzyme AKR1C3 plays a crucial role in hormone and drug metabolism and is associated with abnormal expression in liver cancer, leading to tumor progression and poor prognosis. Nanoparticles modified with HSA can modulate the tumor microenvironment by enhancing photodynamic therapy to induce apoptosis in tumor cells and alleviate hypoxia. Therefore, exploring the potential regulatory mechanisms of resveratrol on AKR1C3 through the construction of HSA-RSV NPs carriers holds significant theoretical and clinical implications for the treatment of liver cancer. The aim of this study is to investigate the targeted regulation of AKR1C3 expression through the loading of resveratrol (RSV) on nanomaterials HSA-RSV NPs (Nanoparticles) in order to alleviate tumor hypoxia and inhibit the progression of hepatocellular carcinoma (HCC), and to explore its molecular mechanism. PubChem database and PharmMapper server were used to screen the target genes of RSV. HCC-related differentially expressed genes (DEGs) were analyzed through the GEO dataset, and relevant genes were retrieved from the GeneCards database, resulting in the intersection of the three to obtain candidate DEGs. GO and KEGG enrichment analyses were performed on the candidate DEGs to analyze the potential cellular functions and molecular signaling pathways affected by the main target genes. The cytohubba plugin was used to screen the top 10 target genes ranked by Degree and further intersected the results of LASSO and Random Forest (RF) to obtain hub genes. The expression analysis of hub genes and the prediction of malignant tumor prognosis were conducted. Furthermore, a pharmacophore model was constructed using PharmMapper. Molecular docking simulations were performed using AutoDockTools 1.5.6 software, and ROC curve analysis was performed to determine the core target. In vitro cell experiments were carried out by selecting appropriate HCC cell lines, treating HCC cells with different concentrations of RSV, or silencing or overexpressing AKR1C3 using lentivirus. CCK-8, clone formation, flow cytometry, scratch experiment, and Transwell were used to measure cancer cell viability, proliferation, migration, invasion, and apoptosis, respectively. Cellular oxygen consumption rate was analyzed using the Seahorse XF24 analyzer. HSA-RSV NPs were prepared, and their characterization and cytotoxicity were evaluated. The biological functional changes of HCC cells after treatment were detected. An HCC subcutaneous xenograft model was established in mice using HepG2 cell lines. HSA-RSV NPs were injected via the tail vein, with a control group set, to observe changes in tumor growth, tumor targeting of NPs, and biological safety. TUNEL, Ki67, and APC-hypoxia probe staining were performed on excised tumor tissue to detect tumor cell proliferation, apoptosis, and hypoxia. Lentivirus was used to silence or overexpress AKR1C3 simultaneously with the injection of HSA-RSV NPs via the tail vein to assess the impact of AKR1C3 on the regulation of HSA-RSV NPs in HCC progression. Bioinformatics analysis revealed that AKR1C3 is an important target gene involved in the regulation of HCC by RSV, which is associated with the prognosis of HCC patients and upregulated in expression. In vitro cell experiments showed that RSV significantly inhibits the respiratory metabolism of HCC cells, suppressing their proliferation, migration, and invasion and promoting apoptosis. Silencing AKR1C3 further enhances the toxicity of RSV towards HCC cells. The characterization and cytotoxicity experiments of nanomaterials demonstrated the successful construction of HSA-RSV NPs, which exhibited stronger inhibitory effects on HCC cells. In vivo, animal experiments further confirmed that targeted downregulation of AKR1C3 by HSA-RSV NPs suppresses the progression of HCC and tumor hypoxia while exhibiting tumor targeting and biological safety. Targeted downregulation of AKR1C3 by HSA-RSV NPs can alleviate HCC tumor hypoxia and inhibit the progression of HCC.

Two-polarized roles of transcription factor FOSB in lung cancer progression and prognosis: dependent on p53 status

BACKGROUND

Activator protein-1 (AP-1) represents a transcription factor family that has garnered growing attention for its extensive involvement in tumor biology. However, the roles of the AP-1 family in the evolution of lung cancer remain poorly characterized. FBJ Murine Osteosarcoma Viral Oncogene Homolog B (FOSB), a classic AP-1 family member, was previously reported to play bewilderingly two-polarized roles in non-small cell lung cancer (NSCLC) as an enigmatic double-edged sword, for which the reasons and significance warrant further elucidation.

METHODS AND RESULTS

Based on the bioinformatics analysis of a large NSCLC cohort from the TCGA database, our current work found the well-known tumor suppressor gene TP53 served as a key code to decipher the two sides of FOSB - its expression indicated a positive prognosis in NSCLC patients harboring wild-type TP53 while a negative one in those harboring mutant TP53. By constructing a panel of syngeneically derived NSCLC cells expressing p53 in different statuses, the radically opposite prognostic effects of FOSB expression in NSCLC population were validated, with the TP53-R248Q mutation site emerging as particularly meaningful. Transcriptome sequencing showed that FOSB overexpression elicited diversifying transcriptomic landscapes across NSCLC cells with varying genetic backgrounds of TP53 and, combined with the validation by RT-qPCR, PREX1 (TP53-Null), IGFBP5 (TP53-WT), AKR1C3, and ALDH3A1 (TP53-R248Q) were respectively identified as p53-dependent transcriptional targets of FOSB. Subsequently, the heterogenous impacts of FOSB on the tumor biology in NSCLC cells via the above selective transcriptional targets were confirmed in vitro and in vivo. Mechanistic investigations revealed that wild-type or mutant p53 might guide FOSB to recognize and bind to distinct promoter sequences via protein-protein interactions to transcriptionally activate specific target genes, thereby creating disparate influences on the progression and prognosis in NSCLC.

CONCLUSIONS

FOSB expression holds promise as a novel prognostic biomarker for NSCLC in combination with a given genetic background of TP53, and the unique interactions between FOSB and p53 may serve as underlying intervention targets for NSCLC.

Structure-guided optimization of 3-hydroxybenzoisoxazole derivatives as inhibitors of Aldo-keto reductase 1C3 (AKR1C3) to target prostate cancer

AKR1C3 is an enzyme that is overexpressed in several types of radiotherapy- and chemotherapy-resistant cancers. Despite AKR1C3 is a validated target for drug development, no inhibitor has been approved for clinical use. In this manuscript, we describe our study of a new series of potent AKR1C3-targeting 3-hydroxybenzoisoxazole based inhibitors that display high selectivity over the AKR1C2 isoform and low micromolar activity in inhibiting 22Rv1 prostate cancer cell proliferation. In silico studies suggested proper substituents to increase compound potency and provided with a mechanistic explanation that could clarify their different activity, later confirmed by X-ray crystallography. Both the in-silico studies and the crystallographic data highlight the importance of 90° rotation around the single bond of the biphenyl group, in ensuring that the inhibitor can adopt the optimal binding mode within the active pocket. The p-biphenyls that bear the meta-methoxy, and the ortho- and meta-trifluoromethyl substituents (in compounds 6a, 6e and 6f respectively) proved to be the best contributors to cellular potency as they provided the best IC50 values in series (2.3, 2.0 and 2.4 μM respectively) and showed no toxicity towards human MRC-5 cells. Co-treatment with scalar dilutions of either compound 6 or 6e and the clinically used drug abiraterone led to a significant reduction in cell proliferation, and thus confirmed that treatment with both CYP171A1-and AKR1C3-targeting compounds possess the potential to intervene in key steps in the steroidogenic pathway. Taken together, the novel compounds display desirable biochemical potency and cellular target inhibition as well as good in-vitro ADME properties, which highlight their potential for further preclinical studies.

AKR1C3 in carcinomas: from multifaceted roles to therapeutic strategies

Aldo-Keto Reductase Family 1 Member C3 (AKR1C3), also known as type 5 17β-hydroxysteroid dehydrogenase (17β-HSD5) or prostaglandin F (PGF) synthase, functions as a pivotal enzyme in androgen biosynthesis. It catalyzes the conversion of weak androgens, estrone (a weak estrogen), and PGD2 into potent androgens (testosterone and 5α-dihydrotestosterone), 17β-estradiol (a potent estrogen), and 11β-PGF2α, respectively. Elevated levels of AKR1C3 activate androgen receptor (AR) signaling pathway, contributing to tumor recurrence and imparting resistance to cancer therapies. The overexpression of AKR1C3 serves as an oncogenic factor, promoting carcinoma cell proliferation, invasion, and metastasis, and is correlated with unfavorable prognosis and overall survival in carcinoma patients. Inhibiting AKR1C3 has demonstrated potent efficacy in suppressing tumor progression and overcoming treatment resistance. As a result, the development and design of AKR1C3 inhibitors have garnered increasing interest among researchers, with significant progress witnessed in recent years. Novel AKR1C3 inhibitors, including natural products and analogues of existing drugs designed based on their structures and frameworks, continue to be discovered and developed in laboratories worldwide. The AKR1C3 enzyme has emerged as a key player in carcinoma progression and therapeutic resistance, posing challenges in cancer treatment. This review aims to provide a comprehensive analysis of AKR1C3's role in carcinoma development, its implications in therapeutic resistance, and recent advancements in the development of AKR1C3 inhibitors for tumor therapies.

In vitro evaluation of the reductive carbonyl idarubicin metabolism to evaluate inhibitors of the formation of cardiotoxic idarubicinol via carbonyl and aldo-keto reductases

The most important dose-limiting factor of the anthracycline idarubicin is the high risk of cardiotoxicity, in which the secondary alcohol metabolite idarubicinol plays an important role. It is not yet clear which enzymes are most important for the formation of idarubicinol and which inhibitors might be suitable to suppress this metabolic step and thus would be promising concomitant drugs to reduce idarubicin-associated cardiotoxicity. We, therefore, established and validated a mass spectrometry method for intracellular quantification of idarubicin and idarubicinol and investigated idarubicinol formation in different cell lines and its inhibition by known inhibitors of the aldo-keto reductases AKR1A1, AKR1B1, and AKR1C3 and the carbonyl reductases CBR1/3. The enzyme expression pattern differed among the cell lines with dominant expression of CBR1/3 in HEK293 and MCF-7 and very high expression of AKR1C3 in HepG2 cells. In HEK293 and MCF-7 cells, menadione was the most potent inhibitor (IC50 = 1.6 and 9.8 µM), while in HepG2 cells, ranirestat was most potent (IC50 = 0.4 µM), suggesting that ranirestat is not a selective AKR1B1 inhibitor, but also an AKR1C3 inhibitor. Over-expression of AKR1C3 verified the importance of AKR1C3 for idarubicinol formation and showed that ranirestat is also a potent inhibitor of this enzyme. Taken together, our study underlines the importance of AKR1C3 and CBR1 for the reduction of idarubicin and identifies potent inhibitors of metabolic formation of the cardiotoxic idarubicinol, which should now be tested in vivo to evaluate whether such combinations can increase the cardiac safety of idarubicin therapies while preserving its efficacy.

Exploring the Molecular Mechanisms of Huaier on Modulating Metabolic Reprogramming of Hepatocellular Carcinoma: A Study based on Network Pharmacology, Molecular Docking and Bioinformatics

BACKGROUND

Huaier (Trametes robiniophila Murr), a traditional Chinese medicine, is widely used in China as a complementary and alternative therapy to treat hepatocellular carcinoma (HCC). Past studies have shown that Huaier can arrest the cell cycle, promote apoptosis and inhibit the proliferation of cancer cells. However, how it regulates the metabolism of HCC is still unclear.

OBJECTIVE

This study explores the metabolic-related function of Huaier in treating HCC with an in-silico approach.

METHODS

A network pharmacology and bioinformatics-based approach was employed to investigate the molecular pathogenesis of metabolic reprogramming in HCC with Huaier. The compounds of Huaier were obtained from public databases. Oral bioavailability and drug likeness were screened using the TCMSP platform. The differential gene expressions between HCC and non-tumor tissue were calculated and used to find the overlap from the targets of Huaier. The enrichment analysis of the overlapped targets by Metascape helped filter out the metabolism-related targets of Huaier in treating HCC. Protein-protein interaction (PPI) network construction and topological screening revealed the hub nodes. The prognosis and clinical correlation of these targets were validated from the cancer genome atlas (TCGA) database, and the interactions between the hub nodes and active ingredients were validated by molecular docking.

RESULTS

The results showed that Peroxyergosterol, Daucosterol, and Kaempferol were the primary active compounds of Huaier involved in the metabolic reprogramming of HCC. The top 6 metabolic targets included AKR1C3, CYP1A1, CYP3A4, CYP1A2, CYP17A1, and HSD11B1. The decreased expression of CYP3A4 and increased expression of AKR1C3 were related to the poor overall survival of HCC patients. The molecular docking validated that Peroxyergosterol and Kaempferol exhibited the potential to modulate CYP3A4 and AKR1C3 from a computational perspective.

CONCLUSION

This study provided a workflow for understanding the mechanism of Huaier in regulating the metabolic reprogramming of HCC.

Genetically predicted serum testosterone and risk of gynecological disorders: a Mendelian randomization study

Background

Testosterone plays a key role in women, but the associations of serum testosterone level with gynecological disorders risk are inconclusive in observational studies.

Methods

We leveraged public genome-wide association studies to analyze the effects of four testosterone related exposure factors on nine gynecological diseases. Causal estimates were calculated by inverse variance-weighted (IVW), MR-Egger and weighted median methods. The heterogeneity test was performed on the obtained data through Cochrane's Q value, and the horizontal pleiotropy test was performed on the data through MR-Egger intercept and MR-PRESSO methods. "mRnd" online analysis tool was used to evaluate the statistical power of MR estimates.

Results

The results showed that total testosterone and bioavailable testosterone were protective factors for ovarian cancer (odds ratio (OR) = 0.885, P = 0.012; OR = 0.871, P = 0.005) and endometriosis (OR = 0.805, P = 0.020; OR = 0.842, P = 0.028) but were risk factors for endometrial cancer (OR = 1.549, P < 0.001; OR = 1.499, P < 0.001) and polycystic ovary syndrome (PCOS) (OR = 1.606, P = 0.019; OR = 1.637, P = 0.017). dehydroepiandrosterone sulfate (DHEAS) is a protective factor against endometriosis (OR = 0.840, P = 0.016) and premature ovarian failure (POF) (OR = 0.461, P = 0.046) and a risk factor for endometrial cancer (OR= 1.788, P < 0.001) and PCOS (OR= 1.970, P = 0.014). sex hormone-binding globulin (SHBG) is a protective factor against endometrial cancer (OR = 0.823, P < 0.001) and PCOS (OR = 0.715, P = 0.031).

Conclusion

Our analysis suggested causal associations between serum testosterone level and ovarian cancer, endometrial cancer, endometriosis, PCOS, POF.

A novel AKR1C3 specific prodrug AST-3424 and its combination therapy in hepatocellular carcinoma

OBJECTIVE

AST-3424 is a novel specific aldo-keto reductase 1C3 (AKR1C3) prodrug that releases a DNA alkylating reagent upon reduction by AKR1C3. This study aimed to evaluate the efficacy and safety of AST-3424 in patient-derived tumor xenograft (PDTX) model and orthotopic model against hepatocellular carcinoma (HCC).

MATERIALS AND METHOD

PDTX models derived from three HCC patients and orthotopic mice models using HepG2 cells were developed. The mice were treated with AST-3424 alone or combined with other drugs (oxaliplatin, apatinib, sorafenib and elemene in PDTX models, oxaliplatin and 5- fluorouracil in orthotopic models). The tumor volume and weight, as well as the mice weight were assessed. The liver tumor and transplanted tumor were removed for histological, immunohistochemical and Western blot detection in orthotopic model experiments.

RESULTS

AST-3424 could inhibit tumor growth in HCC PDTX models and orthotopic models, with no difference in safety compared with other marketed drugs, and the drug combination did not increase toxicity. The inhibitory effect of combination treatment was more obvious than which used alone. The reduction of AKR1C3 expression was negatively correlated with AST-3424 dose.

CONCLUSION

AST-3424 had a promising effect against HCC in PDTX model and orthotopic model with good safety. It could promote the sensitivity of other drugs without increasing toxicity. Clinical trials are warranted to further certify its antitumor effect and safety.

Detection of key mRNAs in liver tissue of hepatocellular carcinoma patients based on machine learning and bioinformatics analysis

One methodology extensively used to develop biomarkers is the precise detection of highly responsive genes that can distinguish cancer samples from healthy samples. The purpose of this study was to screen for potential hepatocellular carcinoma (HCC) biomarkers based on non-fusion integrative multi-platform meta-analysis method. The gene expression profiles of liver tissue samples from two microarray platforms were initially analyzed using a meta-analysis based on an empirical Bayesian method to robust discover differentially expressed genes in HCC and non-tumor tissues. Then, using the bioinformatics technique of weighted correlation network analysis, the highly associated prioritized Differentially Expressed Genes (DEGs) were clustered. Co-expression network and topological analysis were utilized to identify sub-clusters and confirm candidate genes. Next, a diagnostic model was developed and validated using a machine learning algorithm. To construct a prognostic model, the Cox proportional hazard regression analysis was applied and validated. We identified three genes as specific biomarkers for the diagnosis of HCC based on accuracy and feasibility. The diagnostic model's area under the curve was 0.931 with confidence interval of 0.923-0.952.•Non-fusion integrative multi-platform meta-analysis method.•Classification methods and biomarkers recognition via machine learning method.•Biomarker validation models.

A bile acid-related prognostic signature in hepatocellular carcinoma

Due to the high mortality of hepatocellular carcinoma (HCC), its prognostic models are urgently needed. Bile acid (BA) metabolic disturbance participates in hepatocarcinogenesis. We aim to develop a BA-related gene signature for HCC patients. Research data of HCC were obtained from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) online databases. After least absolute shrinkage and selection operator (LASSO) regression analysis, we developed a BA-related prognostic signature in TCGA cohort based on differentially expressed prognostic BA-related genes. Then, the predictive performance of the signature was evaluated and verified in TCGA and ICGC cohort respectively. We obtained the risk score of each HCC patient according to the model. The differences of immune status and drug sensitivity were compared in patients that were stratified based on risk score. The protein and mRNA levels of the modeling genes were validated in the Human Protein Atlas database and our cell lines, respectively. In TCGA cohort, we selected 4 BA-related genes to construct the first BA-related prognostic signature. The risk signature exhibited good discrimination and predictive ability, which was verified in ICGC cohort. Patients were classified into high- and low-risk groups according to their median scores. The occurrence of death increased with increasing risk score. Low-risk patients owned favorable overall survival. High-risk patients possessed high immune checkpoint expression and low IC50 values for sorafenib, cisplatin and doxorubicin. Real-time quantitative PCR and immunohistochemical results validate expression of modeling genes in the signature. We constructed the first BA-related gene signature, which might help to identify HCC patients with poor prognosis and guide individualized treatment.

Bruton’s Tyrosine Kinase Inhibitor Zanubrutinib Effectively Modulates Cancer Resistance by Inhibiting Anthracycline Metabolism and Efflux

Zanubrutinib (ZAN) is a Bruton’s tyrosine kinase inhibitor recently approved for the treatment of some non-Hodgkin lymphomas. In clinical trials, ZAN is often combined with standard anthracycline (ANT) chemotherapy. Although ANTs are generally effective, drug resistance is a crucial obstacle that leads to treatment discontinuation. This study showed that ZAN counteracts ANT resistance by targeting aldo-keto reductase 1C3 (AKR1C3) and ATP-binding cassette (ABC) transporters. AKR1C3 catalyses the transformation of ANTs to less potent hydroxy-metabolites, whereas transporters decrease the ANT-effective concentrations by pumping them out of the cancer cells. In our experiments, ZAN inhibited the AKR1C3-mediated inactivation of daunorubicin (DAUN) at both the recombinant and cellular levels. In the drug combination experiments, ZAN synergistically sensitised AKR1C3-expressing HCT116 and A549 cells to DAUN treatment. Gene induction studies further confirmed that ZAN did not increase the intracellular level of AKR1C3 mRNA; thus, the drug combination effect is not abolished by enzyme induction. Finally, in accumulation assays, ZAN was found to interfere with the DAUN efflux mediated by the ABCB1, ABCG2, and ABCC1 transporters, which might further contribute to the reversal of ANT resistance. In summary, our data provide the rationale for ZAN inclusion in ANT-based therapy and suggest its potential for the treatment of tumours expressing AKR1C3 and/or the above-mentioned ABC transporters.

SMOX expression predicts the prognosis of non-small cell lung cancer

Background

The development of non-small cell lung cancer (NSCLC) is very rapid, and the effect of its treatment is often closely related to the diagnosis time of the disease. Therefore, simple and convenient tumor biomarkers are helpful for the timely diagnosis and prevention of NSCLC.

Methods

Through univariate and multivariate Cox regression analyses, SMOX was determined as an independent prognostic factor of GSE42127, GSE41271, GSE68465, and TCGA datasets. Furthermore, western blot, reverse transcription-polymerase chain reaction (RT-PCR), and immunohistochemical analysis were performed to confirm the predictive efficiency of SMOX expression in NSCLC.

Results

Patients were divided into high and low expression groups according to the median value of SMOX expression, and Kaplan-Meier curves of multiple datasets indicated that patients with low SMOX expression had a better survival rate. According to the analysis of immune infiltration, the immune microenvironment, and immune checkpoints, SMOX expression of the high and low groups showed differences in immunity in NSCLC. By comparing cancer and adjacent tissues using western blot analysis, RT-PCR and immunohistochemical analysis, we found that SMOX was highly expressed in tumor tissues and had low expression in adjacent tissues. Simultaneously, the Kaplan-Meier curve suggested that among the 155 NSCLC patients, those with low SMOX expression had better survival.

Conclusions

SMOX can be used as an effective predictive target for NSCLC.

Interpreting the Molecular Mechanisms of Yinchenhao Decoction on Hepatocellular Carcinoma through Absorbed Components Based on Network Pharmacology

To investigate the mechanisms through which Yinchenhao decoction (YCHD) inhibits hepatocellular carcinoma (HCC), we analyzed YCHD ingredients absorbed into the bloodstream by using network pharmacology. We conducted a weighted gene coexpression network analysis on gene expression data collected from the Gene Expression Omnibus and The Cancer Genome Atlas databases to derive an HCC gene set; moreover, we used four online prediction system databases to predict the potential targets of YCHD ingredients absorbed into the bloodstream. We discovered that YCHD directly interfered with 17 HCC-related disease targets. Subsequent gene ontology enrichment analyses of these 17 disease targets revealed that YCHD exhibited effects through 17 biological processes, 7 molecular functions, and 9 cellular components. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses indicated 14 pathways through which YCHD inhibits HCC. We observed similar trends in how the 17 small molecules interfered with the key target set. We surmised that YCHD inhibits HCC by regulating inflammatory and metabolic pathways. Network pharmacological analysis of YCHD ingredients absorbed into the bloodstream may provide new insights and serve as a new method for discovering the molecular mechanisms through which YCHD inhibits HCC.