Expression analysis and clinical utility of L-Dopa decarboxylase (DDC) in prostate cancer

RNA modification regulator DDC in endometrial cancer affects the tumor microenvironment and patient prognosis

Uterine corpus endometrial carcinoma (UCEC) is infiltrated by immune cells, which are involved in the growth and proliferation of malignant tumors and resistance to immunotherapy. This study suggested that RNA modification regulators played an important role in the development and prognosis of UCEC. Many studies confirmed that RNA modification played an essential role in tumor immune regulation, and abnormal RNA modification contributed to tumorigenesis and cancer progression. Based on the RNA modification regulatory factors, the UCEC samples from TCGA (The Cancer Genome Atlas) were classified into two clusters, namely Cluster A and Cluster B, using unsupervised consensus clustering. We obtained DEG (differentially expressed genes) between the two clusters, and constructed a risk model of RNA modification-related genes using DEGs. Cluster A had lower RNA modification regulatory factors, richer immune cell infiltration, and better prognosis. The differentially expressed genes between the two clusters were obtained, and these genes were used for modeling. This model divided patients with UCEC into two groups. The low-risk group had better immune infiltration, and the ROC (receiver operating characteristic) curve showed that this model had good predictive efficacy. The low-risk group had a better response to immunotherapy by immune checkpoint prediction. We obtained the key gene L-dopa decarboxylase (DDC) through the intersection of LASSO model genes and GEO dataset GSE17025. We evaluated the potential biological functions of DDC. The differences in the expression of DDC were verified by immunohistochemistry. We evaluated the relationship between DDC and immune cell infiltration and verified this difference using immunofluorescence. Cluster A with low expression of RNA modification regulators has better prognosis and richer immune cell infiltration, therefore, we believed that RNA modification regulators in UCEC were closely related to the tumor microenvironment. Also, the risk score could well predict the prognosis of patients and guide immunotherapy, which might benefit patients with UCEC.

Multi-omics profiles refine L-dopa decarboxylase (DDC) as a reliable biomarker for prognosis and immune microenvironment of clear cell renal cell carcinoma

Background

Increasing evidence indicates that L-dopa decarboxylase (DDC), which mediates aberrant amino acid metabolism, is significantly associated with tumor progression. However, the impacts of DDC are not elucidated clearly in clear cell renal cell carcinoma (ccRCC). This study aimed to evaluate DDC prognostic value and potential mechanisms for ccRCC patients.

Methods

Transcriptomic and proteomic expressions of and clinical data including 532 patients with ccRCC (The Cancer Genome Atlas RNA-seq data), 226 ccRCC samples (Gene Expression Omnibus), 101 ccRCC patients from the E-MTAB-1980 cohort, and 232 patients with ccRCC with proteogenomic data (Fudan University Shanghai Cancer Center) were downloaded and analyzed to investigate the prognostic implications of DDC expression. Cox regression analyses were implemented to explore the effect of DDC expression on the prognosis of pan-cancer. The "limma" package identified the differentially expressed genes (DEGs) between high DDC subgroups and low DDC groups. Functional enrichments were performed based DEGs between DDC subgroups. The differences of immune cell infiltrations and immune checkpoint genes between DDC subgroups were analyzed to identify potential influence on immune microenvironment.

Results

We found significantly decreased DDC expression in ccRCC tissues compared with normal tissues from multiple independent cohorts based on multi-omics data. We also found that DDC expression was correlated with tumor grades and stages.The following findings revealed that lower DDC expression levels significantly correlated with shorter overall survival (P <0.001) of patients with ccRCC. Moreover, we found that DDC expression significantly correlated with an immunosuppressive tumor microenvironment, higher intra-tumoral heterogeneity, elevated expression of immune checkpoint CD274, and possibly mediated malignant behaviors of ccRCC cells via the PI3k/Akt signaling pathway.

Conclusion

The present study is the first to our knowledge to indicate that decreased DDC expression is significantly associated with poor survival and an immune-suppressive tumor microenvironment in ccRCC. These findings suggest that DDC could serve as a biomarker for guiding molecular diagnosis and facilitating the development of novel individual therapeutic strategies for patients with advanced ccRCC.

Gene Expression Analysis Reveals Prognostic Biomarkers of the Tyrosine Metabolism Reprogramming Pathway for Prostate Cancer

Background

Tyrosine metabolism pathway-related genes were related to prostate cancer progression, which may be used as potential prognostic markers.

Aims

To dissect the dysregulation of tyrosine metabolism in prostate cancer and build a prognostic signature based on tyrosine metabolism-related genes for prostate cancer. Materials and Method. Cross-platform gene expression data of prostate cancer cohorts were collected from both The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Based on the expression of tyrosine metabolism-related enzymes (TMREs), an unsupervised consensus clustering method was used to classify prostate cancer patients into different molecular subtypes. We employed the least absolute shrinkage and selection operator (LASSO) Cox regression analysis to evaluate prognostic characteristics based on TMREs to obtain a prognostic effect. The nomogram model was established and used to synthesize molecular subtypes, prognostic characteristics, and clinicopathological features. Kaplan–Meier plots and logrank analysis were used to clarify survival differences between subtypes.

Results

Based on the hierarchical clustering method and the expression profiles of TMREs, prostate cancer samples were assigned into two subgroups (S1, subgroup 1; S2, subgroup 2), and the Kaplan–Meier plot and logrank analysis showed distinct survival outcomes between S1 and S2 subgroups. We further established a four-gene-based prognostic signature, and both in-group testing dataset and out-group testing dataset indicated the robustness of this model. By combining the four gene-based signatures and clinicopathological features, the nomogram model achieved better survival outcomes than any single classifier. Interestingly, we found that immune-related pathways were significantly concentrated on S1-upregulated genes, and the abundance of memory B cells, CD4+ resting memory T cells, M0 macrophages, resting dendritic cells, and resting mast cells were significantly different between S1 and S2 subgroups.

Conclusions

Our results indicate the prognostic value of genes related to tyrosine metabolism in prostate cancer and provide inspiration for treatment and prevention strategies.

Identification of Potential Predictor of Biochemical Recurrence in Prostate Cancer

Background

Prostate cancer is a common malignancy in men. Radical prostatectomy is one of the primary treatment modalities for patients with prostate cancer. However, early identification of biochemical recurrence is a major challenge for post-radical prostatectomy surveillance. There is a lack of reliable predictors of biochemical recurrence. The purpose of this study was to explore potential biochemical recurrence indicators for prostate cancer.

Materials and Methods

We analyzed transcriptomic data of cases with biochemical recurrence in The Cancer Genome Atlas (TCGA). Then, we performed integrative bioinformatics analyses to establish a biochemical recurrence predictor model of prostate cancer.

Results

There were 146 differentially expressed genes (DEGs) between prostate cancer and normal prostate, including 12 upregulated and 134 downregulated genes. Comprehensive pathway enrichment analyses revealed that these DEGs were associated with multiple cellular metabolic pathways. Subsequently, according to the random assignment principle, 208 patients were assigned to the training cohort and 205 patients to the validation cohort. Univariate Cox regression analysis showed that 7 genes were significantly associated with the biochemical recurrence of prostate cancer. A model consisting of 5 genes was constructed using LASSO regression and multivariate Cox regression to predict biochemical recurrence of prostate cancer. Expression of PAH and AOC1 decreased with an increasing incidence of prostate cancer, whereas expression of DDC, LINC01436 and ORM1 increased with increasing incidence of prostate cancer. Kaplan–Meier curves and receiver operator characteristic (ROC) curves indicated that the 5-gene model had reliable utility in identifying the risk of biochemical recurrence of prostate cancer.

Conclusion

This study provides a model for predicting prostate cancer recurrence after surgery, which may be an optional indicator for postoperative follow-up.

Revised Exon Structure of l-DOPA Decarboxylase (DDC) Reveals Novel Splice Variants Associated with Colorectal Cancer Progression

Colorectal cancer (CRC) is a highly heterogenous malignancy with an increased mortality rate. Aberrant splicing is a typical characteristic of CRC, and several studies support the prognostic value of particular transcripts in this malignancy. l-DOPA decarboxylase (DDC) and its derivative neurotransmitters play a multifaceted role in physiological and pathological states. Our recent data support the existence of 6 DDC novel exons. In this study, we investigated the existence of additional DDC novel exons and transcripts, and their potential value as biomarkers in CRC. Next-generation sequencing (NGS) in 55 human cell lines coupled with Sanger sequencing uncovered 3 additional DDC novel exons and 20 splice variants, 7 of which likely encode new protein isoforms. Eight of these transcripts were detected in CRC. An in-house qPCR assay was developed and performed in TNM II and III CRC samples for the quantification of transcripts bearing novel exons. Extensive biostatistical analysis uncovered the prognostic value of specific DDC novel exons for patients’ disease-free and overall survival. The revised DDC exon structure, the putative protein isoforms with distinct functions, and the prognostic value of novel exons highlight the pivotal role of DDC in CRC progression, indicating its potential utility as a molecular biomarker in CRC.

Polymorphism in ASCL1 target gene DDC is associated with clinical outcomes of small cell lung cancer patients

BACKGROUND

Achaete-scute homolog 1 (ASCL1) is a basic helix-loop-helix transcription factor and is essential in the differentiation of neuroendocrine cells and neural tissues. ASCL1 is frequently overexpressed in small cell lung cancer (SCLC) and plays a crucial role in the pathogenesis of SCLC.

METHODS

This study was conducted to identify the association between single nucleotide polymorphisms (SNPs) in ASCL1 target genes and clinical outcomes of patients with SCLC after chemotherapy. A total of 261 patients diagnosed with SCLC were enrolled in this study. The association between 103 SNPs in 58 ASCL1 target genes and the response to chemotherapy and survival of patients with SCLC were analyzed.

RESULTS

Among the 103 SNPs, 10 SNPs were significantly associated with the response to chemotherapy, and 19 SNPs were associated with OS in multivariate analyses. Among these, Dopa Decarboxylase (DDC) rs12666409A>T was significantly associated with both a worse response to chemotherapy and worse OS (adjusted odds ratio [aOR] = 0.40, 95% CI = 0.18-0.90, P = 0.03; adjusted hazard ratio [aHR] = 1.52, 95% CI = 1.10-2.10, P = 0.01, respectively, under a dominant model). In a stage-stratified analysis, the association was significant only in the extensive disease subgroup (aOR = 0.19, 95% CI = 0.06-0.60, P = 0.01; aHR = 1.73, 95% CI = 1.16-2.56, P = 0.01, respectively, under a dominant model), but not in the limited disease subgroup.

CONCLUSION

The results of our study suggest that DDC rs12666409A>T may be useful markers for predicting the clinical outcomes of patients with SCLC undergoing chemotherapy.

A Study for Therapeutic Treatment against Parkinson's Disease via Chou's 5-steps Rule

The enzyme L-DOPA decarboxylase (DDC), also called aromatic-L-amino-acid decarboxylase, catalyzes the biosynthesis of dopamine, serotonin, and trace amines. Its deficiency or perturbations in expression result in severe motor dysfunction or a range of neurodegenerative and psychiatric disorders. A DDC substrate, L-DOPA, combined with an inhibitor of the enzyme is still the most effective treatment for symptoms of Parkinson's disease. In this review, we provide an update regarding the structures, functions, and inhibitors of DDC, particularly with regards to the treatment of Parkinson's disease. This information will provide insight into the pharmacological treatment of Parkinson's disease.

Identification of novel alternative splice variants of the human L-DOPA decarboxylase (DDC) gene in human cancer cells, using high-throughput sequencing approaches

The human L-DOPA decarboxylase (DDC) is a gene that has been in the center of research attention in many laboratories the last decades, due to its major implication in various disorders, including many types of cancer. In the current work, we used in-house developed RACE and high-throughput sequencing approaches, in order to detect and identify novel DDC transcripts. Bioinformatic analysis revealed new alternative splicing events that support the existence of novel DDC transcripts. As a result, a total of 14 DDC splice variants were identified and their expression profile was investigated in a wide panel of human cancer cell lines. From all 14 novel DDC transcripts that were identified, 9 transcripts are predicted to encode new protein isoforms, while the remaining 5 are nonsense-mediated mRNA decay (NMD) candidates. Our results demonstrate that the human DDC gene undergoes complex processing leading to the figuration of multiple mRNA isoforms in cancer cells.

Exposure to an environmentally relevant phthalate mixture during prostate development induces microRNA upregulation and transcriptome modulation in rats

Environmental exposure to phthalates during intrauterine development might increase susceptibility to neoplasms in reproductive organs such as the prostate. Although studies have suggested an increase in prostatic lesions in adult animals submitted to perinatal exposure to phthalates, the molecular pathways underlying these alterations remain unclear. Genome-wide levels of mRNAs and miRNAs were monitored with RNA-seq to determine if perinatal exposure to a phthalate mixture in pregnant rats is capable of modifying gene expression expression during prostate development of the filial generation. The mixture contains diethyl-phthalate, di-(2-ethylhexyl)-phthalate, dibutyl-phthalate, di-isononyl-phthalate, di-isobutyl-phthalate, and benzylbutyl-phthalate. Pregnant females were divided into 4 groups and orally dosed daily from GD10 to PND21 with corn oil (Control:C) or the phthalate mixture at three doses (20 μg/kg/d:T1; 200 μg/kg/d:T2; 200 mg/kg/d:T3). The phthalate mixture decreased anogenital distance, prostate weight and decreased testosterone level at the lowest exposure dose at PND22. The mixture also increased inflammatory foci and focal hyperplasia incidence at PND120. miR-184 was upregulated in all treated groups in relation to control and miR-141-3p was only upregulated at the lowest dose. In addition, 120 genes were deregulated at the lowest dose with several of these genes related to developmental, differentiation and oncogenesis. The data indicate that phthalate exposure at lower doses can cause greater gene expression modulation as well as other downstream phenotypes than exposure at higher doses. A significant fraction of the downregulated genes were predicted to be targets of miR-141-3p and miR-184, both of which were induced at the lower exposure doses.

Transcriptomics Signature from Next-Generation Sequencing Data Reveals New Transcriptomic Biomarkers Related to Prostate Cancer

Prostate cancer is one of the most common types of cancer among Canadian men. Next-generation sequencing using RNA-Seq provides large amounts of data that may reveal novel and informative biomarkers. We introduce a method that uses machine learning techniques to identify transcripts that correlate with prostate cancer development and progression. We have isolated transcripts that have the potential to serve as prognostic indicators and may have tremendous value in guiding treatment decisions. Analysis of normal versus malignant prostate cancer data sets indicates differential expression of the genes HEATR5B, DDC, and GABPB1-AS1 as potential prostate cancer biomarkers. Our study also supports PTGFR, NREP, SCARNA22, DOCK9, FLVCR2, IK2F3, USP13, and CLASP1 as potential biomarkers to predict prostate cancer progression, especially between stage II and subsequent stages of the disease.

L-Dopa decarboxylase interaction with the major signaling regulator ΡΙ3Κ in tissues and cells of neural and peripheral origin

L-Dopa decarboxylase (DDC) catalyzes the decarboxylation of L-Dopa to dopamine and 5-hydroxytryptophan (5-HTP) to serotonin. Although DDC has been purified from a variety of peripheral organs, including the liver, kidney and pancreas, the physiological significance of the peripherally expressed enzyme is not yet fully understood. DDC has been considered as a potential novel biomarker for various types of cancer, however, the role of DDC in the development of hepatocellular carcinoma (HCC) remains to be evaluated. Phosphatidylinositol 3-kinase (PI3K), on the other hand, has been shown to play a key role in the tumorigenesis, proliferation, metastasis, apoptosis, and angiogenesis of HCC by regulating gene expression. We initially identified the interaction of DDC with PI3K by means of the phage display methodology. This association was further confirmed in human hepatocellular carcinoma cell lines, human embryonic kidney cells, human neuroblastoma cells, as well as mouse brain, by the use of specific antibodies raised against DDC and PI3K. Functional aspects of the above interaction were studied upon treatment with the DDC inhibitor carbidopa and the PI3K inhibitor LY294002. Interestingly, our data demonstrate the expression of the neuronal type DDC mRNA in HCC cells. The present investigation provides new evidence on the possible link of DDC with the PI3K pathway, underlining the biological significance of this complex enzyme.

Non-coding RNAs: the riddle of the transcriptome and their perspectives in cancer

Non-coding RNAs (ncRNAs) constitute a heterogeneous group of RNA molecules in terms of biogenesis, biological function as well as length and structure. These biological molecules have gained attention recently as a potentially crucial layer of tumor cell progression or regulation. ncRNAs are expressed in a broad spectrum of tumors, and they play an important role not only in maintaining but also in promoting cancer development and progression. Recent discoveries have revealed that ncRNAs may act as key signal transduction mediators in tumor signaling pathways by interacting with RNA or proteins. These results reinforce the hypothesis, that ncRNAs constitute therapeutic targets, and point out their clinical potential as stratification markers. The major purpose of this review is to mention the emergence of the importance of ncRNAs, as molecules which are correlated with cancer, and to discuss their clinical implicit as prognostic diagnostic indicators, biomarkers, and therapeutic targets.

Restoration of hydroxyindole O-methyltransferase levels in human cancer cells induces a tryptophan-metabolic switch and attenuates cancer progression

5-Methoxytryptophan (5-MTP) is a tryptophan metabolite with recently discovered anti-inflammatory and tumor-suppressing activities. Its synthesis is catalyzed by a hydroxyindole O-methyltransferase (HIOMT)-like enzyme. However, the exact identity of this HIOMT in human cells remains unclear. Human HIOMT exists in several alternatively spliced isoforms, and we hypothesized that 5-MTP-producing HIOMT is a distinct isoform. Here, we show that human fibroblasts and cancer cells express the HIOMT298 isoform as contrasted with the expression of the HIOMT345 isoform in pineal cells. Sequencing analysis of the cloned isoforms revealed that HIOMT298 is identical to the sequence of a previously reported truncated HIOMT isoform. Of note, HIOMT298 expression was reduced in cancer cells and tissues. Stable transfection of A549 cancer cells with HIOMT298 restored HIOMT expression to normal levels, accompanied by 5-MTP production. Furthermore, HIOMT298 transfection caused a tryptophan-metabolic switch from serotonin to 5-MTP production. To determine the in vivo relevance of this alteration, we compared growth and lung metastasis of HIOMT298-transfected A549 cells with those of vector- or untransfected A549 cells as controls in a murine xenograft model. Of note, the HIOMT298-transfected A549 cells exhibited slower growth and lower metastasis than the controls. Our findings provide insight into the crucial role of HIOMT298 in 5-MTP production in cells and in inhibiting cancer progression and highlight the potential therapeutic value of 5-MTP for managing cancer.

Flux balance analysis predicts Warburg-like effects of mouse hepatocyte deficient in miR-122a

The liver is a vital organ involving in various major metabolic functions in human body. MicroRNA-122 (miR-122) plays an important role in the regulation of liver metabolism, but its intrinsic physiological functions require further clarification. This study integrated the genome-scale metabolic model of hepatocytes and mouse experimental data with germline deletion of Mir122a (Mir122a^–/–) to infer Warburg-like effects. Elevated expression of MiR-122a target genes in Mir122a^–/–mice, especially those encoding for metabolic enzymes, was applied to analyze the flux distributions of the genome-scale metabolic model in normal and deficient states. By definition of the similarity ratio, we compared the flux fold change of the genome-scale metabolic model computational results and metabolomic profiling data measured through a liquid-chromatography with mass spectrometer, respectively, for hepatocytes of 2-month-old mice in normal and deficient states. The Ddc gene demonstrated the highest similarity ratio of 95% to the biological hypothesis of the Warburg effect, and similarity of 75% to the experimental observation. We also used 2, 6, and 11 months of mir-122 knockout mice liver cell to examined the expression pattern of DDC in the knockout mice livers to show upregulated profiles of DDC from the data. Furthermore, through a bioinformatics (LINCS program) prediction, BTK inhibitors and withaferin A could downregulate DDC expression, suggesting that such drugs could potentially alter the early events of metabolomics of liver cancer cells.

For almost a century, researchers have known that cancer cells have an abnormal metabolism and utilize glucose differently than normal cells do. Aerobic glycolysis or the Warburg effect in cancer cells involves elevated glucose uptake with lactic acid production in the presence of oxygen. MicroRNAs have recently been discovered to be key metabolic regulators that mediate the fine tuning of genes that are involved directly or indirectly in cancer metabolism. MicroRNA-122 (miR-122) plays an important role in the regulation of liver metabolism, but its intrinsic physiological functions require further clarification. This study integrated the genome-scale metabolic modeling (GSMM) of hepatocytes and mouse experimental data with germline deletion of Mir122a (Mir122a^–/–) to infer Warburg-like effects. In silico and in vivo observations indicated that DDC overexpression induced Warburg effect in hepatocyte. Furthermore, through a bioinformatics prediction, BTK inhibitors and withaferin A could downregulate DDC expression, suggesting that such drugs could potentially alter the early events of metabolomics of liver cancer cells.

Genome-wide copy number analysis reveals candidate gene loci that confer susceptibility to high-grade prostate cancer

BACKGROUND

Two key issues in prostate cancer (PCa) that demand attention currently are the need for a more precise and minimally invasive screening test owing to the inaccuracy of prostate-specific antigen and differential diagnosis to distinguish advanced vs. indolent cancers. This continues to pose a tremendous challenge in diagnosis and prognosis of PCa and could potentially lead to overdiagnosis and overtreatment complications. Copy number variations (CNVs) in the human genome have been linked to various carcinomas including PCa. Detection of these variants may improve clinical treatment as well as an understanding of the pathobiology underlying this complex disease.

METHODS

To this end, we undertook a pilot genome-wide CNV analysis approach in 36 subjects (18 patients with high-grade PCa and 18 controls that were matched by age and ethnicity) in search of more accurate biomarkers that could potentially explain susceptibility toward high-grade PCa. We conducted this study using the array comparative genomic hybridization technique. Array results were validated in 92 independent samples (46 high-grade PCa, 23 benign prostatic hyperplasia, and 23 healthy controls) using polymerase chain reaction-based copy number counting method.

RESULTS

A total of 314 CNV regions were found to be unique to PCa subjects in this cohort (P<0.05). A log₂ ratio-based copy number analysis revealed 5 putative rare or novel CNV loci or both associated with susceptibility to PCa. The CNV gain regions were 1q21.3, 15q15, 7p12.1, and a novel CNV in PCa 12q23.1, harboring ARNT, THBS1, SLC5A8, and DDC genes that are crucial in the p53 and cancer pathways. A CNV loss and deletion event was observed at 8p11.21, which contains the SFRP1 gene from the Wnt signaling pathway. Cross-comparison analysis with genes associated to PCa revealed significant CNVs involved in biological processes that elicit cancer pathogenesis via cytokine production and endothelial cell proliferation.

CONCLUSION

In conclusion, we postulated that the CNVs identified in this study could provide an insight into the development of advanced PCa.

L-DOPA decarboxylase mRNA levels provide high diagnostic accuracy and discrimination between clear cell and non-clear cell subtypes in renal cell carcinoma

OBJECTIVES

Renal cell carcinoma (RCC) is the most frequent type of kidney cancer. RCC patients frequently present with arterial hypertension due to various causes, including intrarenal dopamine deficiency. L-DOPA decarboxylase (DDC) is the gene encoding the enzyme that catalyzes the biosynthesis of dopamine in humans. Several studies have shown that the expression levels of DDC are significantly deregulated in cancer. Thus, we herein sought to analyze the mRNA levels of DDC and evaluate their clinical significance in RCC.

DESIGN AND METHODS

DDC levels were analyzed in 58 surgically resected RCC tumors and 44 adjacent non-cancerous renal tissue specimens via real-time PCR. Relative levels of DDC were estimated by applying the 2(-ΔΔC)T method, while their diagnostic accuracy and correlation with the clinicopathological features of RCC tumors were assessed by comprehensive statistical analysis.

RESULTS

DDC mRNA levels were found to be dramatically downregulated (p<0.001) in RCC tumors, exhibiting remarkable diagnostic accuracy as assessed by ROC curve analysis (AUC: 0.910; p<0.001) and logistic regression (OR: 0.678; p=0.001). Likewise, DDC was found to be differentially expressed between clear cell RCC and the group of non-clear cell subtypes (p=0.001) consisted of papillary and chromophobe RCC specimens. Furthermore, a statistically significant inverse correlation was also observed when the mRNA levels of DDC were analyzed in relation to tumor grade (p=0.049).

CONCLUSIONS

Our data showed that DDC constitutes a highly promising molecular marker for RCC, exhibiting remarkable diagnostic accuracy and potential to discriminate between clear cell and non-clear cell histological subtypes of RCC.

Quantification and study of the L-DOPA decarboxylase expression in gastric adenocarcinoma cells treated with chemotherapeutic substances

3,4-Dihydroxy-L-phenylalanine decarboxylase (DDC) is an enzyme implicated in the biosynthetic pathways of the neurotransmitters dopamine and probably serotonin. DDC gene expression has been studied in numerous malignancies and the corresponding data have shown remarkable alterations in the mRNA and/or protein levels encoded by the gene. The aim of this study was to examine any modulations in the DDC mRNA levels in gastric cancer cells after their treatment with the chemotherapeutic agents 5-fluorouracil, leucovorin, irinotecan, etoposide, cisplatin, and taxol. The sensitivity of the AGS gastric adenocarcinoma cells to the antineoplastic drugs was evaluated using the MTT assay. Total RNA was extracted and reverse transcribed into cDNA. A highly sensitive quantitative real-time PCR methodology was developed for the quantification of DDC mRNA. GAPDH was used as a housekeeping gene. Relative quantification analysis was carried out using the comparative C T method ((Equation is included in full-text article.)). The treatment of AGS cells with several concentrations of various broadly used anticancer drugs resulted in significant modulations of the DDC mRNA levels compared with those in the untreated cells in a time-specific and drug-specific manner. Generally, DDC expression levels appeared to decrease after three time periods of exposure to the selected chemotherapeutic agents, suggesting a characteristic DDC mRNA expression profile that is possibly related to the mechanism of each drug. Our experimental data show that the DDC gene might serve as a new potential molecular biomarker predicting treatment response in gastric cancer cells.

The loss of the tumour-suppressor miR-145 results in the shorter disease-free survival of prostate cancer patients

BACKGROUND

Prostate cancer (PCa) is characterised by great heterogeneity of the disease progression rate. Tumours range from insignificant and not life threatening to high risk for relapse ones. Consequently, a large number of patients undergo unnecessary treatment. miR-145 is a well-documented tumour suppressor and its expression, which is regulated by the p53 pathway, has been found to be decreased in the majority of human malignancies. The aim of our study was to evaluate the clinical utility of miR-145 for the prognostication of PCa.

METHODS

Total RNA was isolated from 137 prostate tissue specimens obtained from 73 radical prostatectomy-treated PCa patients and 64 transurethral- or open prostatectomy-treated benign prostate hyperplasia (BPH) patients. Following polyadenylation and reverse transcription, miR-145 levels were determined by quantitative real-time PCR assay, using SNORD48 (RNU48) for normalisation purposes.

RESULTS

Downregulated miR-145 expression was found in PCa compared with BPH patients. The reduction of miR-145 expression in PCa was correlated with higher Gleason score, advanced clinical stage, larger tumour diameter and higher prostate-specific antigen (PSA) and follow-up PSA levels. In addition, higher risk for biochemical recurrence and significantly shorter disease-free survival (DFS) was found for the PCa patients expressing lower miR-145. Focusing on 'low- and intermediate-recurrence risk' PCa patients, miR-145 loss was revealed to be a reliable predictor of biochemical relapse and poor DFS independent from Gleason score, clinical stage, PSA and patients' age.

CONCLUSION

The loss of the tumour-suppressor miR-145 increases the risk for disease progression and predicts the poor survival of PCa patients.

L-DOPA decarboxylase mRNA expression is associated with tumor stage and size in head and neck squamous cell carcinoma: a retrospective cohort study

Background

Head and neck squamous cell carcinoma (HNSCC) represents one of the most commonly diagnosed malignancies worldwide. The DDC gene encodes L-DOPA decarboxylase, an enzyme catalyzing the decarboxylation of L-DOPA to dopamine. We have recently shown that DDC mRNA is a significant predictor of patients’ prognosis in colorectal adenocarcinoma and prostate cancer. The aim of the current study was to analyze the DDC mRNA expression in HNSCC patients.

Methods

53 malignant tumors were resected from the larynx, pharynx, tongue, buccal mucosa, parotid glands, and nasal cavity, as well as from 34 adjacent non-cancerous tissues of HNSCC patients, and were homogenized. Total RNA was isolated and converted into first-strand cDNA. An ultrasensitive real-time PCR method based on the SYBR Green chemistry was used for DDC mRNA quantification in head and neck tissue specimens. Relative quantification was performed using the comparative Ct (2^-ddCt) method.

Results

DDC mRNA levels were lower in squamous cell carcinomas (SCCs) of the larynx and tongue than in adjacent non-cancerous tissue specimens. Furthermore, low DDC mRNA expression was noticed in laryngeal and tongue tumors of advanced TNM stage or bigger size, compared to early-stage or smaller tumors, respectively. No statistically significant differences were observed between SCCs resected from pharynx, buccal mucosa, or nasal cavity, and their normal counterparts.

Conclusion

This is the first study examining the DDC mRNA expression in HNSCC. According to our results, DDC mRNA expression may constitute a potential prognostic biomarker in tongue and/or larynx SCCs, which principally represent the overwhelming majority of HNSCC cases.

l-DOPA Decarboxylase (DDC) Expression Status as a Novel Molecular Tumor Marker for Diagnostic and Prognostic Purposes in Laryngeal Cancer

l-DOPA decarboxylase (DDC) plays an essential role in the enzymatic synthesis of dopamine and alterations in its gene expression have been reported in several malignancies. Our objective was to analyze DDC messenger RNA (mRNA) and protein expression in laryngeal tissues and to evaluate the clinical implication of this molecule in laryngeal cancer. In this study, total RNA was isolated from 157 tissue samples surgically removed from 100 laryngeal cancer patients. A highly sensitive real-time polymerase chain reaction methodology based on SYBR Green I fluorescent dye was developed for the quantification of DDC mRNA levels. In addition, Western blot analysis was performed for the detection of DDC protein. DDC mRNA expression was revealed to be significantly downregulated in primary laryngeal cancer samples compared with their nonmalignant counterparts (P = .001). A significant negative association was also disclosed between DDC mRNA levels and TNM staging (P = .034). Univariate analysis showed that patients bearing DDC-positive tumors had a significantly decreased risk of death (hazard ratio = 0.23, P = .012) and local recurrence (hazard ratio = 0.32, P =.006), whereas DDC expression retained its favorable prognostic significance in the multivariate analysis. Kaplan-Meier curves further demonstrated that DDC-positive patients experienced longer overall and disease-free survival periods (P = .006 and P = .004, respectively). Moreover, DDC protein was detected in both neoplastic and noncancerous tissues. Therefore, our results suggest that DDC expression status could qualify as a promising biomarker for the future clinical management of laryngeal cancer patients.

Carbidopa enhances antitumoral activity of bicalutamide on the androgen receptor-axis in castration-resistant prostate tumors

BACKGROUND

Response to bicalutamide after castration failure is not durable and treatment options at this stage are limited. Carbidopa, an L-dopa decarboxylase (AR-coactivator) inhibitor, has been shown to retard prostate tumor growth/PSA production in xenografts. Here, we hypothesize that pharmacological targeting of the AR-axis by combination treatment with bicalutamide plus carbidopa significantly enhances antitumoral activity in vitro and in vivo compared to monotherapy with either drug.

METHODS

Carbidopa was tested for its ability to enhance the effects of bicalutamide on cell viability, apoptosis and PSA transactivation in LNCaP and C4-2 cells. The castration-resistant prostate cancer (CRPC) LNCaP xenograft tumor model was used in vivo. After CRPC progression, mice were treated with carbidopa (50 mg/kg) and bicalutamide (50 mg/kg) as monotherapy or in combination. Tumor volume and serum PSA were evaluated weekly.

RESULTS

Combination treatment of carbidopa plus bicalutamide significantly inhibited cell viability in both cell lines and induced apoptosis. The combination treatment also decreased androgen-induced PSA transactivation by 62.6% in LNCaP cells and by 55.6% in C4-2 cells compared to control, while bicalutamide monotherapy reduced PSA levels by 27.5% and 29.1% in LNCaP and C4-2 cells. In vivo, bicalutamide monotherapy delayed LNCaP CRPC tumor growth rate by 72.2%, while combination treatment reduced tumor growth by 84.4% compared to control. Serum PSA was also reduced 70.6% with bicalutamide monotherapy, while combination therapy reduced PSA levels by 76.7% compared to control.

CONCLUSIONS

This study demonstrates preclinical proof-of-principle that pharmacological targeting of prostate tumors by combination treatment of bicalutamide plus carbidopa significantly reduces AR activity, and thereby delays CRPC tumor progression in vivo.

L-dopa decarboxylase (DDC) gene expression is related to outcome in patients with prostate cancer

What's known on the subject? and What does the study add? L-dopa decarboxylase (DDC) has been documented as a novel co-activator of androgen receptor transcriptional activity. Recently, it was shown that DDC gene expression is significantly higher in patients with PCa than in those with BPH. In the present study, there was a significant association between the DDC gene expression levels and the pathological stage and Gleason score of patients with prostate cancer (PCa). Moreover, DDC expression was shown to be an unfavourable prognostic marker of biochemical recurrence and disease-free survival in patients with PCa treated by radical prostatectomy.

OBJECTIVE

To determine whether L-dopa decarboxylase gene (DDC) expression levels in patients with prostate cancer (PCa) correlate to biochemical recurrence and disease prognosis after radical prostatectomy (RP).

PATIENTS AND METHODS

The present study consisted of 56 samples with confirmed malignancy from patients with PCa who had undergone RP at a single tertiary academic centre. Total RNA was isolated from tissue specimens and a SYBR Green fluorescence-based quantitative real-time polymerase chain reaction methodology was developed for the determination of DDC mRNA expression levels of the tested tissues. Follow-up time ranged between 1.0 and 62.0 months (mean ± SE, 28.6 ± 2.1 month; median, 31.5 months). Time to biochemical recurrence was defined as the interval between the surgery and the measurement of two consecutive values of prostate-specific antigen (PSA) ≥0.2 ng/mL.

RESULTS

DDC expression levels were found to be positively correlated with the tumour-node-metastasis stage (P = 0.021) and Gleason score (P = 0.036) of the patients with PCa. Patients with PCa with raised DDC expression levels run a significantly higher risk of biochemical recurrence after RP, as indicated by Cox proportional regression analysis (P = 0.021). Multivariate Cox proportional regression models revealed the preoperative PSA-, age- and digital rectal examination-independent prognostic value of DDC expression for the prediction of disease-free survival (DFS) among patients with PCa (P = 0.036). Kaplan-Meier survival analysis confirms the significantly shorter DFS after RP of PCa with higher DDC expression levels (P = 0.015).

CONCLUSIONS

This is the first study indicating the potential of DDC expression as a novel prognostic biomarker in patients with PCa who have undergone RP. For further evaluation and clinical application of the findings of the present study, a direct analysis of mRNA and/or its protein expression level in preoperative biopsy, blood serum and urine should be conducted.

Carbidopa abrogates L-dopa decarboxylase coactivation of the androgen receptor and delays prostate tumor progression

The androgen receptor (AR) plays a central role in prostate cancer progression to the castration-resistant (CR) lethal state. L-Dopa decarboxylase (DDC) is an AR coactivator that increases in expression with disease progression and is coexpressed with the receptor in prostate adenocarcinoma cells, where it may enhance AR activity. Here, we hypothesize that the DDC enzymatic inhibitor, carbidopa, can suppress DDC-coactivation of AR and retard prostate tumor growth. Treating LNCaP prostate cancer cells with carbidopa in transcriptional assays suppressed the enhanced AR transactivation seen with DDC overexpression and decreased prostate-specific antigen (PSA) mRNA levels. Carbidopa dose-dependently inhibited cell growth and decreased survival in LNCaP cell proliferation and apoptosis assays. The inhibitory effect of carbidopa on DDC-coactivation of AR and cell growth/survival was also observed in PC3 prostate cancer cells (stably expressing AR). In vivo studies demonstrated that serum PSA velocity and tumor growth rates elevated ∼2-fold in LNCaP xenografts, inducibly overexpressing DDC, were reverted to control levels with carbidopa administration. In castrated mice, treating LNCaP tumors, expressing endogenous DDC, with carbidopa delayed progression to the CR state from 6 to 10 weeks, while serum PSA and tumor growth decreased 4.3-fold and 5.4-fold, respectively. Our study is a first time demonstration that carbidopa can abrogate DDC-coactivation of AR in prostate cancer cells and tumors, decrease serum PSA, reduce tumor growth and delay CR progression. Since carbidopa is clinically approved, it may be readily used as a novel therapeutic strategy to suppress aberrant AR activity and delay prostate cancer progression.

Quantitative expression analysis and prognostic significance of L-DOPA decarboxylase in colorectal adenocarcinoma

BACKGROUND

L-DOPA decarboxylase (DDC) is an enzyme that catalyses, mainly, the decarboxylation of L-DOPA to dopamine and was found to be involved in many malignancies. The aim of this study was to investigate the mRNA expression levels of the DDC gene and to evaluate its clinical utility in tissues with colorectal adenocarcinoma.

METHODS

Total RNA was isolated from colorectal adenocarcinoma tissues of 95 patients. After having tested RNA quality, we prepared cDNA by reverse transcription. Highly sensitive quantitative real-time PCR method for DDC mRNA quantification was developed using the SYBR Green chemistry. GAPDH served as a housekeeping gene. Relative quantification analysis was performed using the comparative C(T) method (2(-DeltaDeltaC(T))).

RESULTS

DDC mRNA expression varied remarkably among colorectal tumours examined in this study. High DDC mRNA expression levels were found in well-differentiated and Dukes' stage A and B tumours. Kaplan-Meier survival curves showed that patients with DDC-positive tumours have significantly longer disease-free survival (P=0.009) and overall survival (P=0.027). In Cox regression analysis of the entire cohort of patients, negative DDC proved to be a significant predictor of reduced disease-free (P=0.021) and overall survival (P=0.047).

CONCLUSIONS

The results of the study suggest that DDC mRNA expression may be regarded as a novel potential tissue biomarker in colorectal adenocarcinoma.