Melanoma 2.0. Skin cancer as a paradigm for emerging diagnostic technologies, computational modelling and artificial intelligence.

We live in an unprecedented time in oncology. We have accumulated samples and cases in cohorts larger and more complex than ever before. New technologies are available for quantifying solid or liquid samples at the molecular level. At the same time, we are now equipped with the computational power necessary to handle this enormous amount of quantitative data. Computational models are widely used helping us to substantiate and interpret data. Under the label of systems and precision medicine, we are putting all these developments together to improve and personalize the therapy of cancer. In this review, we use melanoma as a paradigm to present the successful application of these technologies but also to discuss possible future developments in patient care linked to them. Melanoma is a paradigmatic case for disruptive improvements in therapies, with a considerable number of metastatic melanoma patients benefiting from novel therapies. Nevertheless, a large proportion of patients does not respond to therapy or suffers from adverse events. Melanoma is an ideal case study to deploy advanced technologies not only due to the medical need but also to some intrinsic features of melanoma as a disease and the skin as an organ. From the perspective of data acquisition, the skin is the ideal organ due to its accessibility and suitability for many kinds of advanced imaging techniques. We put special emphasis on the necessity of computational strategies to integrate multiple sources of quantitative data describing the tumour at different scales and levels.

A proteomic profile of the healthy human placenta.

BACKGROUND: The placenta remains one of the least studied organs within the human body. Yet, placental dysfunction has been associated with various pregnancy complications leading to both maternal and fetal death and long-term health consequences. The aim of this study was to characterise the protein networks of healthy term placental sub-anatomical regions using label free quantification mass spectrometry. METHODS: Three healthy placentae were sampled at five sample sites and each biopsy was dissected into maternal-, middle-, and fetal- sub-anatomical regions. Quadrupole-orbitrap mass spectrometer was used in data dependant analysis mode to identify 1859 unique proteins before detailed differential expression between regions. RESULTS: Protein profiling identified 1081, 1086, and 1101 proteins in maternal, middle, and fetal sub-anatomical regions respectively. Differentially expressed proteins were identified considering the effect between sample site location and sub-anatomical region on protein expression. Of these, 374 differentially expressed proteins (Two-way ANOVA adjusted p-value < 0.05, HSD Tukey adjusted p-value 0.05) were identified between sample site locations and sub-anatomical regions. The placenta specific disease map NaviCenta ( https://www.sbi.uni-rostock.de/minerva/index.xhtml?id=NaviCenta ) was used to focus functional analysis results to the placenta specific context. Subsequently, functional analysis with a focus on senescence, and mitochondrial function were performed. Significant differences were observed between sub-anatomical regions in protein intensity and composition. A decrease in anti-senescent proteins within the maternal sub-anatomical region, and an increase in proteins associated with a switch from ATP to fatty acid consumption as a source of energy between middle and fetal sub-anatomical regions were observed. CONCLUSION: These results suggest that normal proteomic variations exist within the anatomical structure of the placenta, thus recommending serial sectioning methodology for consistent placental research.

Cell-Type-Specific Gene Regulatory Networks of Pro-Inflammatory and Pro-Resolving Lipid Mediator Biosynthesis in the Immune System.

Lipid mediators are important regulators in inflammatory responses, and their biosynthetic pathways are targeted by commonly used anti-inflammatory drugs. Switching from pro-inflammatory lipid mediators (PIMs) to specialized pro-resolving (SPMs) is a critical step toward acute inflammation resolution and preventing chronic inflammation. Although the biosynthetic pathways and enzymes for PIMs and SPMs have now been largely identified, the actual transcriptional profiles underlying the immune cell type-specific transcriptional profiles of these mediators are still unknown. Using the Atlas of Inflammation Resolution, we created a large network of gene regulatory interactions linked to the biosynthesis of SPMs and PIMs. By mapping single-cell sequencing data, we identified cell type-specific gene regulatory networks of the lipid mediator biosynthesis. Using machine learning approaches combined with network features, we identified cell clusters of similar transcriptional regulation and demonstrated how specific immune cell activation affects PIM and SPM profiles. We found substantial differences in regulatory networks in related cells, accounting for network-based preprocessing in functional single-cell analyses. Our results not only provide further insight into the gene regulation of lipid mediators in the immune response but also shed light on the contribution of selected cell types in their biosynthesis.

Exploring Thiazolopyridine AV25R: Unraveling of Biological Activities, Selective Anti-Cancer Properties and In Silico Target and Binding Prediction in Hematological Neoplasms.

Thiazolopyridines are a highly relevant class of small molecules, which have previously shown a wide range of biological activities. Besides their anti-tubercular, anti-microbial and anti-viral activities, they also show anti-cancerogenic properties, and play a role as inhibitors of cancer-related proteins. Herein, the biological effects of the thiazolopyridine AV25R, a novel small molecule with unknown biological effects, were characterized. Screening of a set of lymphoma (SUP-T1, SU-DHL-4) and B- acute leukemia cell lines (RS4;11, SEM) revealed highly selective effects of AV25R. The selective anti-proliferative and metabolism-modulating effects were observed in vitro for the B-ALL cell line RS4;11. Further, we were able to detect severe morphological changes and the induction of apoptosis. Gene expression analysis identified a large number of differentially expressed genes after AV25R exposure and significant differentially regulated cancer-related signaling pathways, such as VEGFA-VEGFR2 signaling and the EGF/EGFR pathway. Structure-based pharmacophore screening approaches using in silico modeling identified potential biological AV25R targets. Our results indicate that AV25R binds with several proteins known to regulate cell proliferation and tumor progression, such as FECH, MAP11, EGFR, TGFBR1 and MDM2. The molecular docking analyses indicates that AV25R has a higher binding affinity compared to many of the experimentally validated small molecule inhibitors of these targets. Thus, here we present in vitro and in silico analyses which characterize, for the first time, the molecular acting mechanism of AV25R, including cellular and molecular biologic effects. Additionally, this predicted the target binding of the molecule, revealing a high affinity to cancer-related proteins and, thus, classified AVR25 for targeted intervention approaches.

COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms.

We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.

Can urodynamic diagnosis of dysfunctional voiding/external sphincter nonrelaxation be made on two-channel pressure-flow study without video-urodynamics, electromyography, or urethral pressure profilometry? Plateau detrusor pattern in perspective.

AIMS: urodynamic diagnosis of dysfunctional voiding/external-sphincter nonrelaxation (DV/EUSD) needs assistance of specialized testing namely urethral pressure profilometry (UPP), electromyography (EMG), and/or videofluoroscopy (VUDS). We aimed to find a predictive model based on standard pressure-flow study without need for specialized testing. MATERIAL AND METHODS: In this retrospective study (2017-2021), clinical and urodynamic data of adult men and women presenting with voiding dysfunction was collected. Mandatory inclusion criteria were availability of all-(1) findings of clinical examination and neurological status, (2) a valid filling cystometry and pressure-flow study (with active detrusor contraction), (3) a final clinic-urodynamic diagnosis. Voiding cystourethrography (VCUG) was performed to confirm the location of obstruction. RESULTS: Data of 218 participants (178♂, 40♀) was eligible. Plateau detrusor contraction pattern was observed in 89.0% of men and 86% of women with DV/EUSD; whereas only 7.5% men and no women with other obstructions demonstrated this pattern. Forward likelihood Logistic regression analysis revealed presence of plateau pattern, lower bladder outlet obstruction index (BOOI), and smaller difference between Pdetmax and PdetQmax highly predictive of presence of DV/EUSD in men as per the following equation-Y = -9.900 + (0.085 × BOOI) + (0.123 × pdetmax - pdetQmax) + (4.061 × detrusor pattern). A kattan-type nomogram was constructed based on the above equation. In women, presence of plateau pattern alone was highly predictive of DV/EUSD. CONCLUSION: Diagnosis of DV/EUSD can be accurately predicted using parameters of three-channel urodynamics (plateau pattern, BOOI, Pdetmax-pdetQmax) minimizing need for specialized testing.

Structure-function relationships explain CTCF zinc finger mutation phenotypes in cancer.

CCCTC-binding factor (CTCF) plays fundamental roles in transcriptional regulation and chromatin architecture maintenance. CTCF is also a tumour suppressor frequently mutated in cancer, however, the structural and functional impact of mutations have not been examined. We performed molecular and structural characterisation of five cancer-specific CTCF missense zinc finger (ZF) mutations occurring within key intra- and inter-ZF residues. Functional characterisation of CTCF ZF mutations revealed a complete (L309P, R339W, R377H) or intermediate (R339Q) abrogation as well as an enhancement (G420D) of the anti-proliferative effects of CTCF. DNA binding at select sites was disrupted and transcriptional regulatory activities abrogated. Molecular docking and molecular dynamics confirmed that mutations in residues specifically contacting DNA bases or backbone exhibited loss of DNA binding. However, R339Q and G420D were stabilised by the formation of new primary DNA bonds, contributing to gain-of-function. Our data confirm that a spectrum of loss-, change- and gain-of-function impacts on CTCF zinc fingers are observed in cell growth regulation and gene regulatory activities. Hence, diverse cellular phenotypes of mutant CTCF are clearly explained by examining structure-function relationships.

3D Modeling of Non-coding RNA Interactions.

Non-coding RNAs (ncRNAs) are a growing class of transcripts, with lengths ranging from tens to several thousand of bases, involved in the regulation of a large number of biological processes and diseases. Many of these ncRNAs have emerged as the molecules of interest for prognostic, diagnostic, and therapeutic purposes in many diseases including cancer. Although ncRNAs do not encode proteins, they fold into complex structures to interact with target proteins, DNA, or other RNAs. In contrast to microRNAs (miRNAs) where researchers mainly focused on the nucleotide sequence for target prediction in the past, folding and structural conservation seems to be important to encode functions and interactions of long non-coding RNA (lncRNA). In this chapter, we discuss methods and tools available for the structural modeling of ncRNAs together with various examples from the literature where structural modeling helped decipher the function of ncRNAs. We also provide a step-by-step procedure to design 3D structures of ncRNAs combining state-of-the-art tools available toward the design of novel RNA therapeutics.

Placental mitochondrial function as a driver of angiogenesis and placental dysfunction.

The placenta is a highly vascularized and complex foetal organ that performs various tasks, crucial to a healthy pregnancy. Its dysfunction leads to complications such as stillbirth, preeclampsia, and intrauterine growth restriction. The specific cause of placental dysfunction remains unknown. Recently, the role of mitochondrial function and mitochondrial adaptations in the context of angiogenesis and placental dysfunction is getting more attention. The required energy for placental remodelling, nutrient transport, hormone synthesis, and the reactive oxygen species leads to oxidative stress, stemming from mitochondria. Mitochondria adapt to environmental changes and have been shown to adjust their oxygen and nutrient use to best support placental angiogenesis and foetal development. Angiogenesis is the process by which blood vessels form and is essential for the delivery of nutrients to the body. This process is regulated by different factors, pro-angiogenic factors and anti-angiogenic factors, such as sFlt-1. Increased circulating sFlt-1 levels have been linked to different preeclamptic phenotypes. One of many effects of increased sFlt-1 levels, is the dysregulation of mitochondrial function. This review covers mitochondrial adaptations during placentation, the importance of the anti-angiogenic factor sFlt-1in placental dysfunction and its role in the dysregulation of mitochondrial function.

Overexpression of microRNAs miR-25-3p, miR-185-5p and miR-132-3p in Late Onset Fetal Growth Restriction, Validation of Results and Study of the Biochemical Pathways Involved.

In a prospective study, 48 fetuses were evaluated with Doppler ultrasound after 34 weeks and classified, according to the cerebroplacental ratio (CPR) and estimated fetal weight (EFW), into fetuses with normal growth and fetuses with late-onset fetal growth restriction (LO-FGR). Overexpression of miRNAs from neonatal cord blood belonging to LO-FGR fetuses, was validated by real-time PCR. In addition, functional characterization of overexpressed miRNAs was performed by analyzing overrepresented pathways, gene ontologies, and prioritization of synergistically working miRNAs. Three miRNAs: miR-25-3p, miR-185-5p and miR-132-3p, were significantly overexpressed in cord blood of LO-FGR fetuses. Pathway and gene ontology analysis revealed over-representation of certain molecular pathways associated with cardiac development and neuron death. In addition, prioritization of synergistically working miRNAs highlighted the importance of miR-185-5p and miR-25-3p in cholesterol efflux and starvation responses associated with LO-FGR phenotypes. Evaluation of miR-25-3p; miR-132-3p and miR-185-5p might serve as molecular biomarkers for the diagnosis and management of LO-FGR; improving the understanding of its influence on adult disease.

An integrative network-driven pipeline for systematic identification of lncRNA-associated regulatory network motifs in metastatic melanoma.

BACKGROUND: Melanoma phenotype and the dynamics underlying its progression are determined by a complex interplay between different types of regulatory molecules. In particular, transcription factors (TFs), microRNAs (miRNAs), and long non-coding RNAs (lncRNAs) interact in layers that coalesce into large molecular interaction networks. Our goal here is to study molecules associated with the cross-talk between various network layers, and their impact on tumor progression. RESULTS: To elucidate their contribution to disease, we developed an integrative computational pipeline to construct and analyze a melanoma network focusing on lncRNAs, their miRNA and protein targets, miRNA target genes, and TFs regulating miRNAs. In the network, we identified three-node regulatory loops each composed of lncRNA, miRNA, and TF. To prioritize these motifs for their role in melanoma progression, we integrated patient-derived RNAseq dataset from TCGA (SKCM) melanoma cohort, using a weighted multi-objective function. We investigated the expression profile of the top-ranked motifs and used them to classify patients into metastatic and non-metastatic phenotypes. CONCLUSIONS: The results of this study showed that network motif UCA1/AKT1/hsa-miR-125b-1 has the highest prediction accuracy (ACC = 0.88) for discriminating metastatic and non-metastatic melanoma phenotypes. The observation is also confirmed by the progression-free survival analysis where the patient group characterized by the metastatic-type expression profile of the motif suffers a significant reduction in survival. The finding suggests a prognostic value of network motifs for the classification and treatment of melanoma.

Comparison of STONE score, Guy's stone score and Clinical Research Office of the Endourological Society (CROES) score as predictive tools for percutaneous nephrolithotomy outcome: a prospective study.

OBJECTIVE: To evaluate which among the three scoring systems used to predict stone-free status (SFS) after percutaneous nephrolithotomy (PCNL), namely Guy's stone score (GSS), STONE nephrolithometry score and Clinical Research Office of the Endourological Society (CROES) nephrolithometry nomogram, is the most accurate predictor of SFS. METHOD AND MATERIALS: We prospectively included all patients who underwent PCNL (tract size >24 F) at our hospital between July 2017 and January 2019. All demographic and peri-operative data were tabulated including calculation of GSS, STONE score and CROES nomogram score using preoperative computed tomography. Comparison of the 'stone-free' group and 'residual-stone' group was carried out using standard statistical methods. RESULTS: A total of 252 patients were enrolled. The mean GSS, STONE score and CROES score in the stone-free group was 1.60, 6.98 and 212.27, respectively, and in the residual stone group group it was 2.93, 8.98 and 129.89, respectively (P < 0.001 in each). Receiver-operating characteristic (ROC) curves showed that all three scoring systems had similar predictive accuracy for post-PCNL SFS, with STONE score having the highest area under the ROC curve value (0.852). GSS was significantly associated with operating time, estimated blood loss (EBL) and length of hospital stay (LOS; P < 0.001 in each). STONE score and CROES score were both significantly associated with EBL (P = 0.029 and 0.001, respectively). CONCLUSION: All three scoring systems are equally predictive of post-PCNL SFS. EBL is significantly associated with all three scoring systems, while GSS is also associated with operating time and LOS.

Recent advancement in the early detection of melanoma using computerized tools: An image analysis perspective.

BACKGROUND: The paper reviews the advancement of tools and current technologies for the detection of melanoma. We discussed several computational strategies from pre- to postprocessing image operations, descriptors, and popular classifiers to diagnose a suspected skin lesion based on its virtual similarity to the malignant lesion with known histopathology. We reviewed the current state of smart phone-based apps as diagnostic tools for screening. METHODS: A literature survey was conducted using a combination of keywords in the bibliographic databases: PubMed, AJCC, PH2, EDRA, and ISIC melanoma project. A number of melanoma detection apps were downloaded for two major mobile operating systems, iOS and Android; their important uses, key challenges, and various expert opinions were evaluated and also discussed. RESULTS: We have provided an overview of research on the computer-aided diagnosis methods to estimate melanoma risk and early screening. Dermoscopic images are the most viable option for the advent of new image processing technologies based on which many of the skin cancer detection apps are being developed recently. We have categorized and explored their potential uses, evaluation criteria, limitations, and other details. CONCLUSION: Such advancements are helpful in the sense they are raising awareness. Diagnostic accuracy is the major issue of smart phone-based apps and it cannot replace an adequate clinical experience and biopsy procedures.

A web platform for the network analysis of high-throughput data in melanoma and its use to investigate mechanisms of resistance to anti-PD1 immunotherapy.

Cellular phenotypes are established and controlled by complex and precisely orchestrated molecular networks. In cancer, mutations and dysregulations of multiple molecular factors perturb the regulation of these networks and lead to malignant transformation. High-throughput technologies are a valuable source of information to establish the complex molecular relationships behind the emergence of malignancy, but full exploitation of this massive amount of data requires bioinformatics tools that rely on network-based analyses. In this report we present the Virtual Melanoma Cell, an online tool developed to facilitate the mining and interpretation of high-throughput data on melanoma by biomedical researches. The platform is based on a comprehensive, manually generated and expert-validated regulatory map composed of signaling pathways important in malignant melanoma. The Virtual Melanoma Cell is a tool designed to accept, visualize and analyze user-generated datasets. It is available at: https://www.vcells.net/melanoma. To illustrate the utilization of the web platform and the regulatory map, we have analyzed a large publicly available dataset accounting for anti-PD1 immunotherapy treatment of malignant melanoma patients.

The RNA world in the 21st century-a systems approach to finding non-coding keys to clinical questions.

There was evidence that RNAs are a functionally rich class of molecules not only since the arrival of the next-generation sequencing technology. Non-coding RNAs (ncRNA) could be the key to accelerated diagnosis and enhanced prediction of disease and therapy outcomes as well as the design of advanced therapeutic strategies to overcome yet unsatisfactory approaches.In this review, we discuss the state of the art in RNA systems biology with focus on the application in the systems biomedicine field. We propose guidelines for analysing the role of microRNAs and long non-coding RNAs in human pathologies. We introduce RNA expression profiling and network approaches for the identification of stable and effective RNomics-based biomarkers, providing insights into the role of ncRNAs in disease regulation. Towards this, we discuss ways to model the dynamics of gene regulatory networks and signalling pathways that involve ncRNAs. We also describe data resources and computational methods for finding putative mechanisms of action of ncRNAs. Finally, we discuss avenues for the computer-aided design of novel RNA-based therapeutics.

Personalized cancer immunotherapy using Systems Medicine approaches.

The immune system is by definition multi-scale because it involves biochemical networks that regulate cell fates across cell boundaries, but also because immune cells communicate with each other by direct contact or through the secretion of local or systemic signals. Furthermore, tumor and immune cells communicate, and this interaction is affected by the tumor microenvironment. Altogether, the tumor-immunity interaction is a complex multi-scale biological system whose analysis requires a systemic view to succeed in developing efficient immunotherapies for cancer and immune-related diseases. In this review we discuss the necessity and the structure of a systems medicine approach for the design of anticancer immunotherapies. We support the idea that the approach must be a combination of algorithms and methods from bioinformatics and patient-data-driven mathematical models conceived to investigate the role of clinical interventions in the tumor-immunity interaction. For each step of the integrative approach proposed, we review the advancement with respect to the computational tools and methods available, but also successful case studies. We particularized our idea for the case of identifying novel tumor-associated antigens and therapeutic targets by integration of patient's immune and tumor profiling in case of aggressive melanoma.

Impact of graphene-based nanomaterials (GBNMs) on the structural and functional conformations of hepcidin peptide.

Graphene-based nanomaterials (GBNMs) are widely used in various industrial and biomedical applications. GBNMs of different compositions, size and shapes are being introduced without thorough toxicity evaluation due to the unavailability of regulatory guidelines. Computational toxicity prediction methods are used by regulatory bodies to quickly assess health hazards caused by newer materials. Due to increasing demand of GBNMs in various size and functional groups in industrial and consumer based applications, rapid and reliable computational toxicity assessment methods are urgently needed. In the present work, we investigate the impact of graphene and graphene oxide nanomaterials on the structural conformations of small hepcidin peptide and compare the materials for their structural and conformational changes. Our molecular dynamics simulation studies revealed conformational changes in hepcidin due to its interaction with GBMNs, which results in a loss of its functional properties. Our results indicate that hepcidin peptide undergo severe structural deformations when superimposed on the graphene sheet in comparison to graphene oxide sheet. These observations suggest that graphene is more toxic than a graphene oxide nanosheet of similar area. Overall, this study indicates that computational methods based on structural deformation, using molecular dynamics (MD) simulations, can be used for the early evaluation of toxicity potential of novel nanomaterials.

Epigenetic factor EPC1 is a master regulator of DNA damage response by interacting with E2F1 to silence death and activate metastasis-related gene signatures.

Transcription factor E2F1 is a key regulator of cell proliferation and apoptosis. Recently, it has been shown that aberrant E2F1 expression often detectable in advanced cancers contributes essentially to cancer cell propagation and characterizes the aggressive potential of a tumor. Conceptually, this requires a subset of malignant cells capable of evading apoptotic death through anticancer drugs. The molecular mechanism by which the pro-apoptotic activity of E2F1 is antagonized is widely unclear. Here we report a novel function for EPC1 (enhancer of polycomb homolog 1) in DNA damage protection. Depletion of EPC1 potentiates E2F1-mediated apoptosis in response to genotoxic treatment and abolishes tumor cell motility. We found that E2F1 directly binds to the EPC1 promoter and EPC1 vice versa physically interacts with bifunctional E2F1 to modulate its transcriptional activity in a target gene-specific manner. Remarkably, nuclear-colocalized EPC1 activates E2F1 to upregulate the expression of anti-apoptotic survival genes such as BCL-2 or Survivin/BIRC5 and inhibits death-inducing targets. The uncovered cooperativity between EPC1 and E2F1 triggers a metastasis-related gene signature in advanced cancers that predicts poor patient survival. These findings unveil a novel oncogenic function of EPC1 for inducing the switch into tumor progression-relevant gene expression that may help to set novel therapies.

Aryl Hydrocarbon Receptor Activation Contributes to Benzanthrone-Induced Hyperpigmentation via Modulation of Melanogenic Signaling Pathways.

Benzanthrone (BA), an oxidized polycyclic aromatic hydrocarbon (PAH), has been found to be a potential health threat to occupational workers involved in dye manufacturing factories. It has been observed that occupational workers become exposed to BA either during manufacturing, pulverization, or storage and developed various kinds of skin diseases like contact dermatitis, itching, erythema, roughness, and foremost, hyperpigmentation. It has been shown that some environmental organic pollutants (POPs) like dioxins, furans, and polychlorinated biphenyls (PCBs) may act as ligands for the aryl hydrocarbon receptor (AhR) and regulate hyperpigmentation. Here, we hypothesized that BA may also act as a ligand for AhR and possibly regulate the melanogenic pathway to induced hyperpigmentation. Our computation results indicate that BA has a high binding affinity toward AhR for the initiation of melanogenic signaling. Following the in silico predictions, we used primary mouse melanocytes (PMMs) and confirmed that exposure to BA (5, 10, and 25 µM) resulted in an increase in AhR expression, tyrosinase activity, and melanin synthesis. Moreover, to study the physiological relevance of these findings, C57BL/6 mice were topically exposed to BA, and enhanced pigmentation and melanin synthesis were observed. Furthermore, the study was extended to assess the mechanistic aspects involved in BA-induced hyperpigmentation in PMMs as well as in mouse skin. Our results suggest that BA exposure initiates AhR signaling and increases tyrosinase enzyme activity and melanin synthesis. Moreover, the genes that regulate the melanin synthesis, such as TRP-1, TRP-2 and the transcription factor MITF, were also found to be increased. Thus, altogether, we suggest that BA-AhR interactions are critical for BA-induced hyperpigmentation.