OBJECTIVE: Constitutional indocyanine green (ICG) excretory defects must be distinguished when assessing liver function. The absence of OATP1B3 expression due to homogenous alterations in the SLCO1B3 gene has been recently reported to induce ICG excretory defects; however, its association with the clinical examinations and the clinical implications of heterogeneous SLCO1B3 gene alteration remain unclear.
METHODS: OATP1B3 expression was evaluated in 49 patients who underwent hepatectomy after evaluation of the ICG retention rate at 15 min (ICGR15) and technetium-99 m-galactosyl serum albumin (99mTc-GSA) hepatic scintigraphy. Additionally, alterations in SLCO1B3 were analyzed in patients without OATP1B3 expression. Subsequently, 59 patients who underwent hepatectomy for colorectal liver metastasis (CRLM) were analyzed.
RESULTS: Of 49 patients, 6 (12%) had absent OATP1B3 expression. They had significantly higher ICGR15 value (74.7% vs. 23.5%; p < 0.0001), better modified albumin-bilirubin (ALBI) grade (≤grade 2A, 100% vs. 42%; p = 0.010), more normal 99mTc-GSA hepatic scintigraphy (100% vs. 28%; p = 0.0003), and better pathological liver fibrosis (F0-1, 100% vs. 49%; p = 0.027) compared to those with OATP1B3 expression. Three available frozen blocks of cases without OATP1B3 expression showed homozygous alterations in SLCO1B3. Of 59 patients with CRLM in normal liver background, five (8.5%) had heterozygous insertion in SLCO1B3, however they had no difference in ICGR15 values or other clinical findings compared to the other patients.
CONCLUSIONS: Constitutional ICG excretory defects may be defined by the complete absence of OATP1B3 expression. The modified ALBI grade and 99mTc-GSA hepatic scintigraphy were useful for detecting constitutional ICG excretory defects.

The movement of organic anionic drugs across cell membranes is partly governed by interactions with SLC and ABC transporters in the intestine, liver, kidney, blood-brain barrier, placenta, breast, and other tissues. Major transporters involved include organic anion transporters (OATs, SLC22 family), organic anion transporting polypeptides (OATPs, SLCO family), and multidrug resistance proteins (MRPs, ABCC family). However, the sets of molecular properties of drugs that are necessary for interactions with OATs (OAT1, OAT3) vs. OATPs (OATP1B1, OATP1B3) vs. MRPs (MRP2, MRP4) are not well-understood. Defining these molecular properties is necessary for a better understanding of drug and metabolite handling across the gut-liver-kidney axis, gut-brain axis, and other multi-organ axes. It is also useful for tissue targeting of small molecule drugs and predicting drug-drug interactions and drug-metabolite interactions. Here, we curated a database of drugs shown to interact with these transporters in vitro and used chemoinformatic approaches to describe their molecular properties. We then sought to define sets of molecular properties that distinguish drugs interacting with OATs, OATPs, and MRPs in binary classifications using machine learning and artificial intelligence approaches. We identified sets of key molecular properties (e.g., rotatable bond count, lipophilicity, number of ringed structures) for classifying OATs vs. MRPs and OATs vs. OATPs. However, sets of molecular properties differentiating OATP vs. MRP substrates were less evident, as drugs interacting with MRP2 and MRP4 do not form a tight group owing to differing hydrophobicity and molecular complexity for interactions with the two transporters. If the results also hold for endogenous metabolites, they may deepen our knowledge of organ crosstalk, as described in the Remote Sensing and Signaling Theory. The results also provide a molecular basis for understanding how small organic molecules differentially interact with OATs, OATPs, and MRPs.

The determination of the appropriate initial dose for tacrolimus is crucial in achieving the target concentration promptly and avoiding adverse effects and poor prognosis. However, the trial-and-error approach is still common practice. This study aimed to establish a prediction model for an initial dosing algorithm of tacrolimus in patients receiving a lung transplant. A total of 210 lung transplant recipients were enrolled, and 26 single nucleotide polymorphisms (SNP) from 18 genes that could potentially affect tacrolimus pharmacokinetics were genotyped. Associations between SNPs and tacrolimus concentration/dose ratio were analyzed. SNPs that remained significant in pharmacogenomic analysis were further combined with clinical factors to construct a prediction model for tacrolimus initial dose. The dose needed to reach steady state tacrolimus concentrations and achieve the target range was used to validate model prediction efficiency. Our final model consisted of 7 predictors-CYP3A5 rs776746, SLCO1B3 rs4149117, SLC2A2 rs1499821, NFATc4 rs1955915, alanine aminotransferase, direct bilirubin, and hematocrit-and explained 41.4% variance in the tacrolimus concentration/dose ratio. It achieved an area under the receiver operating characteristic curve of 0.804 (95% confidence interval, 0.746-0.861). The Hosmer-Lemeshow test yielded a nonsignificant P value of .790, suggesting good fit of the model. The predicted dose exhibited good correlation with the observed dose in the early postoperative period (r = 0.748, P less than .001). Our study provided a genotype-guided prediction model for tacrolimus initial dose, which may help to guide individualized dosing of tacrolimus in the lung transplant population in clinical practice.

BACKGROUND: Severe neonatal hyperbilirubinemia could lead to kernicterus and neonatal death. This study aimed to analyze the association between single nucleotide polymorphisms in genes involved in bilirubin metabolism and the incidence of severe hyperbilirubinemia.
METHODS: A total of 144 neonates with severe hyperbilirubinemia and 50 neonates without or mild hyperbilirubinemia were enrolled in 3 institutions between 2019 and 2020. Twelve polymorphisms of 5 genes (UGT1A1, SLCO1B1, SLCO1B3, BLVRA, and HMOX1) were analyzed by PCR amplification of genomic DNA. Genotyping was performed using an improved multiplex ligation detection reaction technique based on ligase detection reaction.
RESULTS: The frequencies of the A allele in UGT1A1-rs4148323 and the C allele in SLCO1B3-rs2417940 in the severe hyperbilirubinemia group (30.2% and 90.6%, respectively) were significantly higher than those in the controls (30.2% vs.13.0%, 90.6% vs. 78.0%, respectively, both p < 0.05). Haplotype analysis showed the ACG haplotype of UGT1A1 were associated with an increased hyperbilirubinemia risk (OR 3.122, p = 0.001), whereas the GCG haplotype was related to a reduced risk (OR 0.523, p = 0.018).
CONCLUSIONS: The frequencies of the A allele in rs4148323 and the C allele in rs2417940 are highly associated with the incidence of severe hyperbilirubinemia in Chinese Han neonates.
BACKGROUND: Trial registration number:ChiCTR1800020424; Date of registration:2018-12-29.

Extracellular vesicles (EVs) provide a minimally invasive liquid biopsy source of tumor-specific markers for patients who have already undergone prostatectomies. Our laboratory has previously demonstrated enrichment of the cancer-type solute carrier organic anion transporter family 1B3 (ct-SLCO1B3) and the ATP Binding Cassette Subfamily Member C (ABCC3) in castration-resistant cell lines (CRPC). However, their expression in EVs has yet to be explored. Our study demonstrated that ct-SLCO1B3 and ABCC3 are highly detectable in CRPC cell line-derived EVs. We also showed that ct-SLCO1B3 and ABCC3 were detectable in a CRPC xenograft mouse model, both intratumorally and in plasma-derived EVs. Our results provide evidence for EV-contained ct-SLCO1B3 and ABCC3 as novel, EV-based tumor markers for prostate cancer progression.

Table eggs with color-uniformity shell are visually attractive for consumers. Lueyang black-boned chicken (LBC) lays colorful eggs, which is undesirable for sale of table eggs, but provides a segregating population for mapping functional variants affecting eggshell color. SLCO1B3 was identified as the causative gene for blue eggs in the Dongxiang and Araucana chickens. The aim of this study is to map functional variants associated with chicken eggshell color in the SLCO1B3. Eggshell color of LBC (n = 383) was measured using the L*a*b color space. SLCO1B3 was resequencing using a subset (n = 30) of 383 samples. Linkage disequilibrium among 139 SNP was analyzed. Association of 16 SNP in the SLCO1B3 and 8 in CPOX, ALAS1, and ABCG2 genes with L*a*b were tested by a polygenic model (LMM) and a polygenic/oligogenic mixed model (BSLMM). Chromatin state annotations were retrieved from the UCSC database. Effect of SLCO1B3 variants distributed in mapping and upstream 1.6-kb regions on promoter activities were analyzed using dual-luciferase reporter assay. One hundred and thirty-nine variants maintained low linkage disequilibrium with 80% of r2 less than 0.226. Fifteen SLCO1B3 variants were significantly associated with a*, of which 1B3_SNP108 was showed the strongest association and the largest effect on a*. In the BSLMM, 1B3_SNP108 alone appeared in the Markov chain Monte Carlo as major variants in 100% of posterior inclusion probability. None of variants in CPOX, ALAS1, and ABCG2 were significantly associated with color indexes except that 2 ALAS1 variants were associated with L*. 1B3_SNP108 distributes in the Intron4 where 6 active enhancers and 1 ATAC island were enriched. However, 1B3_SNP108-containing constructs showed negligible activities in the reporter assay. No significant differences of activities between haplotypes were found for five 5\'-deleted promoter constructs. The data recognizes 1B3_SNP108 as a valuable marker for breeding of eggshell color. Functional variants are localized in the region adjacent to the 1B3_SNP108 due to low linkage disequilibrium in the LBC. Our findings extend the role of SLCO1B3 from a causative gene for blue eggs to a major regulator driving continuous variation of LBC eggshell color.

The liver serves as the central organ for lipid metabolism, making it a crucial component of chicken physiology. However, the intricate regulation of lipid absorption, synthesis, decomposition, and transport within the liver is influenced by various factors, such as environmental conditions, diet, and genetics. Recent research has suggested that numerous functional genes and transcription factors play a pivotal role in liver metabolism via different molecular mechanisms. In this study, we examined the transcriptomes of both healthy and fatty chicken livers to better understand the role of functional genes in chicken liver fat metabolism. Our bioinformatics analysis of RNA-seq data revealed differential expression of SLCO1B3 in healthy liver and fatty liver, with lower ex-pression levels observed in fatty liver. To further investigate the potential role of SLCO1B3 in liver metabolism, we conducted in vitro experiments to knock down its expression in primary hepatocytes. Our results indicated that SLCO1B3 could suppress lipogenesis, hepatocyte apoptosis, and inflammation. These findings provide insight into the molecular mechanism of SLCO1B3 as a functional gene capable of regulating fat metabolism in chicken liver, and may contribute to ad-dressing the issue of fatty liver in chicken.

Chicken blue-greenish coloration (BGC) was known as a classic Mendel trait caused by a retrovirus (EAV-HP) insertion in the SLCO1B3 gene. Lueyang black-boned chicken (LBC) BGC is light and varies continuously, implying that LBC BGC may be controlled by a new molecular mechanism. The aim of this study was to provide an insight into the molecular basis of LBC BGC. The EAV-HP was detected in the BGC (n = 105) and non-BGC LBC (n = 474) using a PCR-based method. The association of SLCO1B3 expression in shell glands and sequence variants in a 1.6-kb region upstream from the transcription start site of SLCO1B3 with eggshell color and biliverdin (pigment for BGC) concentration was studied. Promoter activities of haplotypes in the 1.6-kb region were analyzed by luciferase reporter assay. This study did not found the EAV-HP in BGC and Non-BGC LBC, but detected a strong positive correlation between levels of SLCO1B3 expression in shell glands and biliverdin concentrations. A total of 31 SNP were found in the 1.6-kb region. Twenty-two of 31 SNP formed 42 types of haplotypes in the re-sequenced samples (n = 94). Haplotype 4 was present in higher frequency in the BGC (52%) than Non-BGC (3%). Haplotype 13 was significantly associated with Non-BGC (Non-BGC vs. BGC = 26% vs. 6%). In line with the above associations, Haplotype 4 showed higher (P < 0.05) levels of SLCO1B3 expression in shell glands, biliverdin concentration, and promoter activity than Haplotype 13. This study confirms that LBC BGC is not caused by the EAV-HP, but remains to be associated with the change of SLCO1B3 expression. Haplotype 4 accounts to some extents for the molecular basis of LBC BGC. The new molecular mechanism supports LBC BGC independently evolved.

Background: Hepatocellular carcinoma (HCC) is one of the most common cancers with high mortality in the world. HCC screening and diagnostic models are becoming effective strategies to reduce mortality and improve the overall survival (OS) of patients. Here, we expected to establish an effective novel diagnostic model based on new genes and explore potential drugs for HCC therapy. Methods: The gene expression data of HCC and normal samples (GSE14811, GSE60502, GSE84402, GSE101685, GSE102079, GSE113996, and GSE45436) were downloaded from the Gene Expression Omnibus (GEO) dataset. Bioinformatics analysis was performed to distinguish two differentially expressed genes (DEGs), diagnostic candidate genes, and functional enrichment pathways. QRT-PCR was used to validate the expression of diagnostic candidate genes. A diagnostic model based on candidate genes was established by an artificial neural network (ANN). Drug sensitivity analysis was used to explore potential drugs for HCC. CCK-8 assay was used to detect the viability of HepG2 under various presentative chemotherapy drugs. Results: There were 82 DEGs in cancer tissues compared to normal tissue. Protein-protein interaction (PPI), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses and infiltrating immune cell analysis were administered and analyzed. Diagnostic-related genes of MT1M, SPINK1, AKR1B10, and SLCO1B3 were selected from DEGs and used to construct a diagnostic model. The receiver operating characteristic (ROC) curves were 0.910 and 0.953 in the training and testing cohorts, respectively. Potential drugs, including vemurafenib, LOXO-101, dabrafenib, selumetinib, Arry-162, and NMS-E628, were found as well. Vemurafenib, dabrafenib, and selumetinib were observed to significantly affect HepG2 cell viability. Conclusion: The diagnostic model based on the four diagnostic-related genes by the ANN could provide predictive significance for diagnosis of HCC patients, which would be worthy of clinical application. Also, potential chemotherapy drugs might be effective for HCC therapy.

The coordinated movement of organic anions (e.g., drugs, metabolites, signaling molecules, nutrients, antioxidants, gut microbiome products) between tissues and body fluids depends, in large part, on organic anion transporters (OATs) [solute carrier 22 (SLC22)], organic anion transporting polypeptides (OATPs) [solute carrier organic (SLCO)], and multidrug resistance proteins (MRPs) [ATP-binding cassette, subfamily C (ABCC)]. Depending on the range of substrates, transporters in these families can be considered multispecific, oligospecific, or (relatively) monospecific. Systems biology analyses of these transporters in the context of expression patterns reveal they are hubs in networks involved in interorgan and interorganismal communication. The remote sensing and signaling theory explains how the coordinated functions of drug transporters, drug-metabolizing enzymes, and regulatory proteins play a role in optimizing systemic and local levels of important endogenous small molecules. We focus on the role of OATs, OATPs, and MRPs in endogenous metabolism and how their substrates (e.g., bile acids, short chain fatty acids, urate, uremic toxins) mediate interorgan and interorganismal communication and help maintain and restore homeostasis in healthy and disease states.