Altered expression of cytochrome P450 enzymes involved in metabolism of androgens and vitamin D in the prostate as a risk factor for prostate cancer

Construction and Validation of a Prognostic Model Based on Mitochondrial Genes in Prostate Cancer

This study attempted to build a prostate cancer (PC) prognostic risk model with mitochondrial feature genes. PC-related MTGs were screened for Cox regression analyses, followed by establishing a prognostic model. Model validity was analyzed via survival analysis and receiver operating characteristic (ROC) curves, and model accuracy was validated in the GEO dataset. Combining risk score with clinical factors, the independence of the risk score was verified by using Cox analysis, followed by generating a nomogram. The Gleason score, microsatellite instability (MSI), immune microenvironment, and tumor mutation burden were analyzed in two risk groups. Finally, the prognostic feature genes were verified through a q-PCR test. Ten PC-associated MTGs were screened, and a prognostic model was built. Survival analysis and ROC curves illustrated that the model was a good predictor for the risk of PC. Cox regression analysis revealed that risk score acted as an independent prognostic factor. The Gleason score and MSI in the high-risk group were substantially higher than in the low-risk group. Levels of ESTIMATE Score, Immune Score, Stromal Score, immune cells, immune function, immune checkpoint, and immunopheno score of partial immune checkpoints in the high-risk group were significantly lower than in the low-risk group. Genes with the highest mutation frequencies in the two groups were SPOP, TTN, and TP53. The q-PCR results of the feature genes were consistent with the gene expression results in the database. The 10-gene model based on MTGs could accurately predict the prognosis of PC patients and their responses to immunotherapy.

Nitrophenols disrupt the expression and activity of biotransformation enzymes (CYP3A and COMT) in chicken ovarian follicles in vivo and in vitro

Nitrophenols are environmental pollutants and xenobiotics, the main sources of which are diesel exhaust fumes and pesticides. The biotransformation processes that take place in the liver are defence mechanisms against xenobiotics, such as nitrophenols. Our previous study showed that the chicken ovary is an additional xenobiotic detoxification place and that nitrophenols disrupt steroidogenesis in chicken ovarian follicles. Therefore, the present study aimed to determine the in vivo and in vitro effects of 4-nitrophenol (PNP) and 3-methyl-4-nitrophenol (PNMC) on the expression and activity of phase I (CYP3A) and phase II (COMT) biotransformation enzymes in chicken ovary. In an in vivo study, hens were treated with a vehicle or 10 mg PNP or PNMC/kg b.wt. per day for 6 days. In an in vitro study, prehierarchical white and yellowish follicles, as well as the granulosa and theca layers of the three largest preovulatory follicles (F3, F2 and F1), were isolated and then incubated in a control medium or medium supplemented with PNP (10-6 M) or PNMC (10-6 M) for 24 or 48 h. Both in vivo and in vitro studies showed that nitrophenols exert tissue- and compound-dependent (PNP or PNMC) effects on CYP3A and COMT gene (real-time PCR) protein (Western blot) expression and their activity (colorimetric methods). The inhibitory effect of nitrophenols in vivo on the activity of biotransformation enzymes suggest that the ovary has the capacity to metabolise PNP and PNMC.

Pleiotropy of Progesterone Receptor Membrane Component 1 in Modulation of Cytochrome P450 Activity

Progesterone receptor membrane component 1 (PGRMC1) is one of few proteins that have been recently described as direct modulators of the activity of human cytochrome P450 enzymes (CYP)s. These enzymes form a superfamily of membrane-bound hemoproteins that metabolize a wide variety of physiological, dietary, environmental, and pharmacological compounds. Modulation of CYP activity impacts the detoxification of xenobiotics as well as endogenous pathways such as steroid and fatty acid metabolism, thus playing a central role in homeostasis. This review is focused on nine main topics that include the most relevant aspects of past and current PGRMC1 research, focusing on its role in CYP-mediated drug metabolism. Firstly, a general overview of the main aspects of xenobiotic metabolism is presented (I), followed by an overview of the role of the CYP enzymatic complex (IIa), a section on human disorders associated with defects in CYP enzyme complex activity (IIb), and a brief account of cytochrome b5 (cyt b5)'s effect on CYP activity (IIc). Subsequently, we present a background overview of the history of the molecular characterization of PGRMC1 (III), regarding its structure, expression, and intracellular location (IIIa), and its heme-binding capability and dimerization (IIIb). The next section reflects the different effects PGRMC1 may have on CYP activity (IV), presenting a description of studies on the direct effects on CYP activity (IVa), and a summary of pathways in which PGRMC1's involvement may indirectly affect CYP activity (IVb). The last section of the review is focused on the current challenges of research on the effect of PGRMC1 on CYP activity (V), presenting some future perspectives of research in the field (VI).

CYP7B1 as a Biomarker for Prostate Cancer Risk and Progression: Metabolic and Oncogenic Signatures (Diagnostic Immunohistochemistry Analysis by Tissue Microarray in Prostate Cancer Patients-Diamond Study)

We aimed to analyze the association between CYP7B1 and prostate cancer, along with its association with proteins involved in cancer and metabolic processes. A retrospective analysis was performed on 390 patients with prostate cancer (PC) or benign prostatic hyperplasia (BPH). We investigated the interactions between CYP7B1 expression and proteins associated with PC and metabolic processes, followed by an analysis of the risk of biochemical recurrence based on CYP7B1 expression. Of the 139 patients with elevated CYP7B1 expression, 92.8% had prostate cancer. Overall, no increased risk of biochemical recurrence was associated with CYP7B1 expression. However, in a non-diabetic subgroup analysis, higher CYP7B1 expression indicated a higher risk of biochemical recurrence, with an HR of 1.78 (CI: 1.0-3.2, p = 0.05). PC is associated with elevated CYP7B1 expression. In a subgroup analysis of non-diabetic patients, elevated CYP7B1 expression was associated with an increased risk of biochemical recurrence, suggesting increased cancer aggressiveness.

Cytochrome P450 genes expression in human prostate cancer

CYP-dependent metabolites play a critical role in regulating the cell cycle, as well as the proliferative, invasive, and migratory activity of cancer cells. We conducted a study to analyze the relative gene expression of various CYPs (CYP7B1, CYP27A1, CYP39A1, CYP51, CYP1B1, CYP3A5, CYP4F8, CYP5A1, CYP4F2, CYP2J2, CYP2E1, CYP2R1, CYP27B1, CYP24A1) in 41 pairs of prostate samples (tumor and conventional normal tissues) using qPCR. Our analysis determined significant individual variability in the expression levels of all studied CYPs, both in the tumor and in conventionally normal groups. However, when we performed a paired test between the tumor and normal groups, we found no significant difference in the expression of the studied genes. We did observe a tendency to increase the level of CYP1B1 expression in the tumor group. We also did not find any significant difference between the levels of the studied CYPs in the tumor and conventional normal groups at different stages of prostate cancer and pathomorphological indicators. Correlation analysis revealed the presence of a positive relationship between the expressions of some cholesterol-metabolizing CYP genes, as well as between genes responsible for vitamin D biosynthesis and cholesterol biosynthesis. We observed significant correlative relationships between the expression of CYPs and some prostate cancer-related genes (CDH2, MMP9, SCHLAP1, GCR, CYP17A1, ACTA2, CXCL14, FAP, CCL17, MSMB, IRF1, VDR). Therefore, the expression of CYPs is not directly associated with prostate cancer but is largely determined by genetic, epigenetic factors, as well as endogenous substrates and xenobiotics. The significant correlative relationship between CYPs and genes associated with cancer may indicate common regulatory pathways that may have a synergistic effect on the tumor, ensuring the survival of cancer cells.

Revisiting the significance of nano-vitamin D for food fortification and therapeutic application

OBJECTIVE

Vitamin D (a prohormone) is an important micronutrient required by the body for skeletal homeostasis and a range of non-skeletal actions. Calcitriol, the active form of vitamin D, regulates a variety of cellular and metabolic processes through both genomic and nongenomic pathways. Often prescribed for treating rickets and osteoporosis, vitamin D deficiency can exacerbate various other medical conditions.

SIGNIFICANCE, METHODS, AND RESULTS

Despite its multifunctional uses, the sensitivity of vitamin D makes formulating an efficient drug delivery system a challenging task, which is further complicated by its poor aqueous solubility. Enhancing the oral absorption of vitamin D is vital in utilizing its full efficacy. Recent developments in encapsulation and nanotechnology have shown promising results in overcoming these constraints.

CONCLUSION

This review thus offers an insight to adequately comprehend the mechanistic pharmacology of vitamin D, its pathophysiological role, and justification of its medical indications, along with the benefits of utilizing nanotechnology for vitamin D delivery.

Association between oxidative balance score and prostate specific antigen among older US adults

Objective

Oxidative Balance Score (OBS) is an index affecting the oxidative stress of dietary and lifestyle factors. We aimed to explore the association of OBS with prostate specific antigen (PSA) among older males.

Methods

A total of 5,136 samples were collected in this study to investigate the relationship between OBS and PSA from the National Health and Nutrition Examination Survey. Logistic regression models and restricted cubic spline were used to assess the associations between OBS and PSA.

Results

Compared with the Q1 group, the odds ratios for the association between OBS and PSA were 1.005 (1.003, 1.009), 1.003 (1.001, 1.006), and 1.001 (0.978, 1.022) for Q2, Q3, and Q4, respectively. In the age-specific analyses, the association was significant among individuals aged 65 years old and over: the odds ratios for the association between OBS and PSA were 1.019 (1.005, 1.028), 1.028 (1.018, 1.039), and 1.038 (1.022, 1.049) for Q2, Q3, and Q4, respectively. But it was not significant among individuals aged less than 65 years old: the odds ratios for the association between OBS and PSA were 1.016 (0.995, 1.026), 1.015 (0.985, 1.022), and 0.988 (0.978, 1.016) for Q2, Q3, and Q4, respectively. The restricted cubic splines also indicated a nonlinear relationship between OBS and PSA among individuals aged 65 years old and over (Poverall = 0.006, Pnonlinear = 0.021).

Conclusion

Our findings provide evidence that OBS is positively associated with higher levels of PSA among older adults. Further large-scale prospective cohort studies are needed to verify our findings.

From resistance to resilience: Uncovering chemotherapeutic resistance mechanisms; insights from established models

Despite the tremendous advances in cancer treatment, resistance to chemotherapeutic agents impedes higher success rates and accounts for major relapses in cancer therapy. Moreover, the resistance of cancer cells to chemotherapy is linked to low efficacy and high recurrence of cancer. To stand up against chemotherapy resistance, different models of chemotherapy resistance have been established to study various molecular mechanisms of chemotherapy resistance. Consequently, this review is going to discuss different models of induction of chemotherapy resistance, highlighting the most common mechanisms of cancer resistance against different chemotherapeutic agents, including overexpression of efflux pumps, drug inactivation, epigenetic modulation, and epithelial-mesenchymal transition. This review aims to open a new avenue for researchers to lower the resistance to the existing chemotherapeutic agents, develop new therapeutic agents with low resistance potential, and establish possible prognostic markers for chemotherapy resistance.

Transcriptomic analysis identifies CYP27A1 as a diagnostic marker for the prognosis and immunity in lung adenocarcinoma

BACKGROUND

The association between lipid metabolism disorder and carcinogenesis is well-established, but there is limited research on the connection between lipid metabolism-related genes (LRGs) and lung adenocarcinoma (LUAD). The objective of our research was to identify LRGs as the potential biomarkers for prognosis and assess their impact on immune cell infiltration in LUAD.

METHODS

We identified novel prognostic LRGs for LUAD patients via the bioinformatics analysis. CYP27A1 expression level was systematically evaluated via various databases, such as TCGA, UALCAN, and TIMER. Subsequently, LinkedOmics was utilized to perform the CYP27A1 co-expression network and GSEA. ssGSEA was conducted to assess the association between infiltration of immune cells and CYP27A1 expression. CYP27A1's expression level was validated by qRT-PCR analysis.

RESULTS

CYP27A1 expression was decreased in LUAD. Reduced CYP27A1 expression was linked to unfavorable prognosis in LUAD. Univariate and multivariate analyses indicated that CYP27A1 was an independent prognostic biomarker for LUAD patients. GSEA results revealed a positive correlation between CYP27A1 expression and immune-related pathways. Furthermore, CYP27A1 expression was positively correlated with the infiltration levels of most immune cells.

CONCLUSION

CYP27A1 is a potential biomarker for LUAD patients, and our findings provided a novel perspective to develop the prognostic marker for LUAD patients.

Electrochemical transformations catalyzed by cytochrome P450s and peroxidases

Cytochrome P450s (Cyt P450s) and peroxidases are enzymes featuring iron heme cofactors that have wide applicability as biocatalysts in chemical syntheses. Cyt P450s are a family of monooxygenases that oxidize fatty acids, steroids, and xenobiotics, synthesize hormones, and convert drugs and other chemicals to metabolites. Peroxidases are involved in breaking down hydrogen peroxide and can oxidize organic compounds during this process. Both heme-containing enzymes utilize active Fe^IVO intermediates to oxidize reactants. By incorporating these enzymes in stable thin films on electrodes, Cyt P450s and peroxidases can accept electrons from an electrode, albeit by different mechanisms, and catalyze organic transformations in a feasible and cost-effective way. This is an advantageous approach, often called bioelectrocatalysis, compared to their biological pathways in solution that require expensive biochemical reductants such as NADPH or additional enzymes to recycle NADPH for Cyt P450s. Bioelectrocatalysis also serves as an ex situ platform to investigate metabolism of drugs and bio-relevant chemicals. In this paper we review biocatalytic electrochemical reactions using Cyt P450s including C-H activation, S-oxidation, epoxidation, N-hydroxylation, and oxidative N-, and O-dealkylation; as well as reactions catalyzed by peroxidases including synthetically important oxidations of organic compounds. Design aspects of these bioelectrocatalytic reactions are presented and discussed, including enzyme film formation on electrodes, temperature, pH, solvents, and activation of the enzymes. Finally, we discuss challenges and future perspective of these two important bioelectrocatalytic systems.

Underlying Features of Prostate Cancer-Statistics, Risk Factors, and Emerging Methods for Its Diagnosis

Prostate cancer (PCa) is the most frequently occurring type of malignant tumor and a leading cause of oncological death in men. PCa is very heterogeneous in terms of grade, phenotypes, and genetics, displaying complex features. This tumor often has indolent growth, not compromising the patient's quality of life, while its more aggressive forms can manifest rapid growth with progression to adjacent organs and spread to lymph nodes and bones. Nevertheless, the overtreatment of PCa patients leads to important physical, mental, and economic burdens, which can be avoided with careful monitoring. Early detection, even in the cases of locally advanced and metastatic tumors, provides a higher chance of cure, and patients can thus go through less aggressive treatments with fewer side effects. Furthermore, it is important to offer knowledge about how modifiable risk factors can be an effective method for reducing cancer risk. Innovations in PCa diagnostics and therapy are still required to overcome some of the limitations of the current screening techniques, in terms of specificity and sensitivity. In this context, this review provides a brief overview of PCa statistics, reporting its incidence and mortality rates worldwide, risk factors, and emerging screening strategies.

Construction of a lipid metabolism-related risk model for hepatocellular carcinoma by single cell and machine learning analysis

One of the most common cancers is hepatocellular carcinoma (HCC). Numerous studies have shown the relationship between abnormal lipid metabolism-related genes (LMRGs) and malignancies. In most studies, the single LMRG was studied and has limited clinical application value. This study aims to develop a novel LMRG prognostic model for HCC patients and to study its utility for predictive, preventive, and personalized medicine. We used the single-cell RNA sequencing (scRNA-seq) dataset and TCGA dataset of HCC samples and discovered differentially expressed LMRGs between primary and metastatic HCC patients. By using the least absolute selection and shrinkage operator (LASSO) regression machine learning algorithm, we constructed a risk prognosis model with six LMRGs (AKR1C1, CYP27A1, CYP2C9, GLB1, HMGCS2, and PLPP1). The risk prognosis model was further validated in an external cohort of ICGC. We also constructed a nomogram that could accurately predict overall survival in HCC patients based on cancer status and LMRGs. Further investigation of the association between the LMRG model and somatic tumor mutational burden (TMB), tumor immune infiltration, and biological function was performed. We found that the most frequent somatic mutations in the LMRG high-risk group were CTNNB1, TTN, TP53, ALB, MUC16, and PCLO. Moreover, naïve CD8+ T cells, common myeloid progenitors, endothelial cells, granulocyte-monocyte progenitors, hematopoietic stem cells, M2 macrophages, and plasmacytoid dendritic cells were significantly correlated with the LMRG high-risk group. Finally, gene set enrichment analysis showed that RNA degradation, spliceosome, and lysosome pathways were associated with the LMRG high-risk group. For the first time, we used scRNA-seq and bulk RNA-seq to construct an LMRG-related risk score model, which may provide insights into more effective treatment strategies for predictive, preventive, and personalized medicine of HCC patients.

Human orphan cytochromes P450: An update

Orphan cytochromes P450 (CYP) are enzymes whose biological functions and substrates are unknown. However, the use of new experimental strategies has allowed obtaining more information about their relevance in the metabolism of endogenous and exogenous compounds. Likewise, the modulation of their expression and activity has been associated with pathogenesis and prognosis in different diseases. In this work, we review the regulatory pathways and the possible role of orphan CYP to provide evidence that allow us to stop considering some of them as orphan enzymes and to propose them as possible therapeutic targets in the design of new strategies for the treatment of diseases associated with CYP-mediated metabolism.

Volatilomics: An Emerging and Promising Avenue for the Detection of Potential Prostate Cancer Biomarkers

Simple Summary

The lack of highly specific and sensitive biomarkers for the early detection of prostate cancer (PCa) is a major barrier to its management. Volatilomics emerged as a non-invasive, simple, inexpensive, and easy-to-use approach for cancer screening, characterization of disease progression, and follow-up of the treatment’s success. We provide a brief overview of the potential of volatile organic metabolites (VOMs) for the establishment of PCa biomarkers from non-invasive matrices. Endogenous VOMs have been investigated as potential biomarkers since changes in these VOMs can be characteristic of specific disease processes. Recent studies have shown that the conjugation of the prostate-specific antigen (PSA) screening with other methodologies, such as risk calculators, biomarkers, and imaging tests, can attenuate overdiagnosis and under-detection issues. This means that the combination of volatilomics with other methodologies could be extremely valuable for the differentiation of clinical phenotypes in a group of patients, providing more personalized treatments.

Abstract

Despite the spectacular advances in molecular medicine, including genomics, proteomics, transcriptomics, lipidomics, and personalized medicine, supported by the discovery of the human genome, prostate cancer (PCa) remains the most frequent malignant tumor and a leading cause of oncological death in men. New methods for prognostic, diagnostic, and therapy evaluation are mainly based on the combination of imaging techniques with other methodologies, such as gene or protein profiling, aimed at improving PCa management and surveillance. However, the lack of highly specific and sensitive biomarkers for its early detection is a major hurdle to this goal. Apart from classical biomarkers, the study of endogenous volatile organic metabolites (VOMs) biosynthesized by different metabolic pathways and found in several biofluids is emerging as an innovative, efficient, accessible, and non-invasive approach to establish the volatilomic biosignature of PCa patients, unravelling potential biomarkers. This review provides a brief overview of the challenges of PCa screening methods and emergent biomarkers. We also focus on the potential of volatilomics for the establishment of PCa biomarkers from non-invasive matrices.

Molecular and pathological subtypes related to prostate cancer disparities and disease outcomes in African American and European American patients

Prostate cancer (PCa) disproportionately affects African American (AA) men, yet present biomarkers do not address the observed racial disparity. The objective of this study was to identify biomarkers with potential benefits to AA PCa patients. Differentially expressed genes (DEG) analysis coupled with gene set enrichment analysis (GSEA) and leading-edge genes analysis showed that the keratin family of genes, including KRT8, KRT15, KRT19, KRT34, and KRT80, constituted the single most prominent family of genes enriched in AA compared to European American (EA) PCa cell lines. In PCa patients (TCGA and MSKCC patient cohorts), KRT8, KRT15, and KRT19 expression were relatively higher in AA than in EA patients. The differences in the expression of KRT15 and KRT19, but not KRT8, were enhanced by Gleason score and ERG fusion status; in low Gleason (Gleason ≤ 6 [TCGA cohort] and Gleason ≤ 7 [MSKCC cohort]), the expression of KRT15 and KRT19 was significantly (p ≤ 0.05) higher in AA than in EA patients. Survival analysis revealed that high expression of KRT15 and KRT19 was associated with increased risk of biochemical recurrence in low Gleason category patients in the TCGA patient cohort. Interestingly, KRT15 and KRT19 expression were also associated with an increased risk of death in the metastatic prostate adenocarcinoma cohort, suggesting the potential to predict the risks of disease recurrence and death in the low Gleason category and advanced disease conditions respectively. Gene set enrichment analysis revealed known oncogenic gene signatures, including KRAS and ERBB2, to be enriched in patients expressing high KRT15 and KRT19. Furthermore, high KRT15 and KRT19 were linked to the basal and LumA PCa subtypes, which are associated with poor postoperative androgen deprivation therapy (ADT) response compared to the LumB subtype. Taken together, the present study identifies genes with high expression in AA than in EA PCa. The identified genes are linked to oncogenic gene signatures, including KRAS and ERBB2, and to basal and LumA PCa subtypes that are associated with poor postoperative ADT response. This study, therefore, reveals biomarkers with the potential to address biomarker bias in PCa risk stratification and/or prognosis.

The Role of Cytochrome P450 Enzymes in COVID-19 Pathogenesis and Therapy

Coronavirus disease 2019 (COVID-19) has become a new public health crisis threatening the world. Dysregulated immune responses are the most striking pathophysiological features of patients with severe COVID-19, which can result in multiple-organ failure and death. The cytochrome P450 (CYP) system is the most important drug metabolizing enzyme family, which plays a significant role in the metabolism of endogenous or exogenous substances. Endogenous CYPs participate in the biosynthesis or catabolism of endogenous substances, including steroids, vitamins, eicosanoids, and fatty acids, whilst xenobiotic CYPs are associated with the metabolism of environmental toxins, drugs, and carcinogens. CYP expression and activity are greatly affected by immune response. However, changes in CYP expression and/or function in COVID-19 and their impact on COVID-19 pathophysiology and the metabolism of therapeutic agents in COVID-19, remain unclear. In this analysis, we review current evidence predominantly in the following areas: firstly, the possible changes in CYP expression and/or function in COVID-19; secondly, the effects of CYPs on the metabolism of arachidonic acid, vitamins, and steroid hormones in COVID-19; and thirdly, the effects of CYPs on the metabolism of therapeutic COVID-19 drugs.

Systematic Elucidation of the Aneuploidy Landscape and Identification of Aneuploidy Driver Genes in Prostate Cancer

Aneuploidy is widely identified as a remarkable feature of malignancy genomes. Increasing evidences suggested aneuploidy was involved in the progression and metastasis of prostate cancer (PCa). Nevertheless, no comprehensive analysis was conducted in PCa about the effects of aneuploidy on different omics and, especially, about the driver genes of aneuploidy. Here, we validated the association of aneuploidy with the progression and prognosis of PCa and performed a systematic analysis in mutation profile, methylation profile, and gene expression profile, which detailed the molecular process aneuploidy implicated. By multi-omics analysis, we managed to identify 11 potential aneuploidy driver genes (GSTM2, HAAO, C2orf88, CYP27A1, FAXDC2, HFE, C8orf88, GSTP1, EFS, HIF3A, and WFDC2), all of which were related to the development and metastasis of PCa. Meanwhile, we also found aneuploidy and its driver genes were correlated with the immune microenvironment of PCa. Our findings could shed light on the tumorigenesis of PCa and provide a better understanding of the development and metastasis of PCa; additionally, the driver genes could be promising and actionable therapeutic targets pointing to aneuploidy.

Identification of Novel Diagnostic Biomarkers in Prostate Adenocarcinoma Based on the Stromal-Immune Score and Analysis of the WGCNA and ceRNA Network

Prostate cancer is still a significant global health burden in the coming decade. Novel biomarkers for detection and prognosis are needed to improve the survival of distant and advanced stage prostate cancer patients. The tumor microenvironment is an important driving factor for tumor biological functions. To investigate RNA prognostic biomarkers for prostate cancer in the tumor microenvironment, we obtained relevant data from The Cancer Genome Atlas (TCGA) database. We used the bioinformatics tools Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) algorithm and weighted coexpression network analysis (WGCNA) to construct tumor microenvironment stromal-immune score-based competitive endogenous RNA (ceRNA) networks. Then, the Cox regression model was performed to screen RNAs associated with prostate cancer survival. The differentially expressed gene profile in tumor stroma was significantly enriched in microenvironment functions, like immune response, cancer-related pathways, and cell adhesion-related pathways. Based on these differentially expressed genes, we constructed three ceRNA networks with 152 RNAs associated with the prostate cancer tumor microenvironment. Cox regression analysis screened 31 RNAs as the potential prognostic biomarkers for prostate cancer. The most interesting 8 prognostic biomarkers for prostate cancer included lncRNA LINC01082, miRNA hsa-miR-133a-3p, and genes TTLL12, PTGDS, GAS6, CYP27A1, PKP3, and ZG16B. In this systematic study for ceRNA networks in the tumor environment, we screened out potential biomarkers to predict prognosis for prostate cancer. Our findings might apply a valuable tool to improve prostate cancer clinical management and the new target for mechanism study and therapy.

Ronald C.D. Breslow (1931-2017): A career in review

Reviewed herein are key research accomplishments of Professor Ronald Charles D. Breslow (1931-2017) throughout his more than 60 year research career. These accomplishments span a wide range of topics, most notably physical organic chemistry, medicinal chemistry, and bioorganic chemistry. These topics are reviewed, as are topics of molecular electronics and origin of chirality, which combine to make up the bulk of this review. Also reviewed briefly are Breslow's contributions to the broader chemistry profession, including his work for the American Chemical Society and his work promoting gender equity. Throughout the article, efforts are made to put Breslow's accomplishments in the context of other work being done at the time, as well as to include subsequent iterations and elaborations of the research.

Associations Between Cytochrome P450 (CYP) Gene Single-Nucleotide Polymorphisms and Second-to-Fourth Digit Ratio in Chinese University Students

BACKGROUND Cytochrome P450 (CYP) genes are necessary for the production or metabolism of fetal sex hormones during pregnancy. The second-to-fourth digit ratio (2D: 4D) is formed in the early stage of human fetal development and considered an indicator reflecting prenatal sex steroids levels. We explored the association between 2D: 4D and single-nucleotide polymorphisms (SNPs) of CYP. MATERIAL AND METHODS Correlation analysis between 2D: 4D and 8 SNPs, rs2687133 (CPY3A7), rs7173655 (CYP11A1), rs1004467, rs17115149, and rs2486758 (CYP17A1), and rs4646, rs2255192, rs4275794 (CYP19A1), was performed using data from 426 female and 412 male Chinese university students. SNP genotyping was conducted using PCR. Digit lengths were photographed and measured by image processing software. RESULTS rs2486758 (CYP17A1) correlated with left hand 2D: 4D in men (P=0.026), and rs1004467 (CYP17A1) correlated with right hand 2D: 4D in men (P=0.008) and the whole population (P=0.032). In men, allele G rs1004467 decreased right hand 2D: 4D, while allele C of rs2486758 increased left hand 2D: 4D. In women, left hand 2D: 4D was higher in genotypes with allele A of SNP rs4646 (CYP19A1) under the dominant genetic model; female DR-L was higher in genotypes with allele T of rs17115149 (CYP11A1). SNPs rs2687133 (CYP3A7) and rs1004467 (CYP17A1) were significantly correlated with right hand 2D: 4D (P=0.0107). CONCLUSIONS SNPs rs1004467 and rs2486758 of CYP17A1 are significant in the relationship between 2D: 4D and CYP gene polymorphisms under different conditions. SNP interactions between CYP genes probably impact 2D: 4D. The correlation between 2D: 4D and some sex hormone-related diseases may be due to the effect of CYP variants on the 2 phenotypes.