Genetic requirements for cell division in a genomically minimal cell.

Genomically minimal cells, such as JCVI-syn3.0, offer a platform to clarify genes underlying core physiological processes. Although this minimal cell includes genes essential for population growth, the physiology of its single cells remained uncharacterized. To investigate striking morphological variation in JCVI-syn3.0 cells, we present an approach to characterize cell propagation and determine genes affecting cell morphology. Microfluidic chemostats allowed observation of intrinsic cell dynamics that result in irregular morphologies. A genome with 19 genes not retained in JCVI-syn3.0 generated JCVI-syn3A, which presents morphology similar to that of JCVI-syn1.0. We further identified seven of these 19 genes, including two known cell division genes, ftsZ and sepF, a hydrolase of unknown substrate, and four genes that encode membrane-associated proteins of unknown function, which are required together to restore a phenotype similar to that of JCVI-syn1.0. This result emphasizes the polygenic nature of cell division and morphology in a genomically minimal cell.

Extracellular Vesicle and Particle Biomarkers Define Multiple Human Cancers.

There is an unmet clinical need for improved tissue and liquid biopsy tools for cancer detection. We investigated the proteomic profile of extracellular vesicles and particles (EVPs) in 426 human samples from tissue explants (TEs), plasma, and other bodily fluids. Among traditional exosome markers, CD9, HSPA8, ALIX, and HSP90AB1 represent pan-EVP markers, while ACTB, MSN, and RAP1B are novel pan-EVP markers. To confirm that EVPs are ideal diagnostic tools, we analyzed proteomes of TE- (n = 151) and plasma-derived (n = 120) EVPs. Comparison of TE EVPs identified proteins (e.g., VCAN, TNC, and THBS2) that distinguish tumors from normal tissues with 90% sensitivity/94% specificity. Machine-learning classification of plasma-derived EVP cargo, including immunoglobulins, revealed 95% sensitivity/90% specificity in detecting cancer. Finally, we defined a panel of tumor-type-specific EVP proteins in TEs and plasma, which can classify tumors of unknown primary origin. Thus, EVP proteins can serve as reliable biomarkers for cancer detection and determining cancer type.

High-Throughput Discovery and Characterization of Human Transcriptional Effectors.

Thousands of proteins localize to the nucleus; however, it remains unclear which contain transcriptional effectors. Here, we develop HT-recruit, a pooled assay where protein libraries are recruited to a reporter, and their transcriptional effects are measured by sequencing. Using this approach, we measure gene silencing and activation for thousands of domains. We find a relationship between repressor function and evolutionary age for the KRAB domains, discover that Homeodomain repressor strength is collinear with Hox genetic organization, and identify activities for several domains of unknown function. Deep mutational scanning of the CRISPRi KRAB maps the co-repressor binding surface and identifies substitutions that improve stability/silencing. By tiling 238 proteins, we find repressors as short as ten amino acids. Finally, we report new activator domains, including a divergent KRAB. These results provide a resource of 600 human proteins containing effectors and demonstrate a scalable strategy for assigning functions to protein domains.

Functional Metabolomics Describes the Yeast Biosynthetic Regulome.

Genome-metabolism interactions enable cell growth. To probe the extent of these interactions and delineate their functional contributions, we quantified the Saccharomyces amino acid metabolome and its response to systematic gene deletion. Over one-third of coding genes, in particular those important for chromatin dynamics, translation, and transport, contribute to biosynthetic metabolism. Specific amino acid signatures characterize genes of similar function. This enabled us to exploit functional metabolomics to connect metabolic regulators to their effectors, as exemplified by TORC1, whose inhibition in exponentially growing cells is shown to match an interruption in endomembrane transport. Providing orthogonal information compared to physical and genetic interaction networks, metabolomic signatures cluster more than half of the so far uncharacterized yeast genes and provide functional annotation for them. A major part of coding genes is therefore participating in gene-metabolism interactions that expose the metabolism regulatory network and enable access to an underexplored space in gene function.

Frequent nonhomologous replacement of replicative helicase loaders by viruses in Vibrionaceae.

Several microbial genomes lack textbook-defined essential genes. If an essential gene is absent from a genome, then an evolutionarily independent gene of unknown function complements its function. Here, we identified frequent nonhomologous replacement of an essential component of DNA replication initiation, a replicative helicase loader gene, in Vibrionaceae. Our analysis of Vibrionaceae genomes revealed two genes with unknown function, named vdhL1 and vdhL2, that were substantially enriched in genomes without the known helicase-loader genes. These genes showed no sequence similarities to genes with known function but encoded proteins structurally similar with a viral helicase loader. Analyses of genomic syntenies and coevolution with helicase genes suggested that vdhL1/2 encodes a helicase loader. The in vitro assay showed that Vibrio harveyi VdhL1 and Vibrio ezurae VdhL2 promote the helicase activity of DnaB. Furthermore, molecular phylogenetics suggested that vdhL1/2 were derived from phages and replaced an intrinsic helicase loader gene of Vibrionaceae over 20 times. This high replacement frequency implies the host's advantage in acquiring a viral helicase loader gene.

Activity-based annotation: the emergence of systems biochemistry.

Current tools to annotate protein function have failed to keep pace with the speed of DNA sequencing and exponentially growing number of proteins of unknown function (PUFs). A major contributing factor to this mismatch is the historical lack of high-throughput methods to experimentally determine biochemical activity. Activity-based methods, such as activity-based metabolite and protein profiling, are emerging as new approaches for unbiased, global, biochemical annotation of protein function. In this review, we highlight recent experimental, activity-based approaches that offer new opportunities to determine protein function in a biologically agnostic and systems-level manner.

Functional analysis of germline VANGL2 variants using rescue assays of vangl2 knockout zebrafish.

Developmental studies have shown that the evolutionarily conserved Wnt Planar Cell Polarity (PCP) pathway is essential for the development of a diverse range of tissues and organs including the brain, spinal cord, heart and sensory organs, as well as establishment of the left-right body axis. Germline mutations in the highly conserved PCP gene VANGL2 in humans have only been associated with central nervous system malformations, and functional testing to understand variant impact has not been performed. Here we report three new families with missense variants in VANGL2 associated with heterotaxy and congenital heart disease p.(Arg169His), non-syndromic hearing loss p.(Glu465Ala) and congenital heart disease with brain defects p.(Arg135Trp). To test the in vivo impact of these and previously described variants, we have established clinically-relevant assays using mRNA rescue of the vangl2 mutant zebrafish. We show that all variants disrupt Vangl2 function, although to different extents and depending on the developmental process. We also begin to identify that different VANGL2 missense variants may be haploinsufficient and discuss evidence in support of pathogenicity. Together, this study demonstrates that zebrafish present a suitable pipeline to investigate variants of unknown significance and suggests new avenues for investigation of the different developmental contexts of VANGL2 function that are clinically meaningful.

PathMethy: an interpretable AI framework for cancer origin tracing based on DNA methylation.

Despite advanced diagnostics, 3%-5% of cases remain classified as cancer of unknown primary (CUP). DNA methylation, an important epigenetic feature, is essential for determining the origin of metastatic tumors. We presented PathMethy, a novel Transformer model integrated with functional categories and crosstalk of pathways, to accurately trace the origin of tumors in CUP samples based on DNA methylation. PathMethy outperformed seven competing methods in F1-score across nine cancer datasets and predicted accurately the molecular subtypes within nine primary tumor types. It not only excelled at tracing the origins of both primary and metastatic tumors but also demonstrated a high degree of agreement with previously diagnosed sites in cases of CUP. PathMethy provided biological insights by highlighting key pathways, functional categories, and their interactions. Using functional categories of pathways, we gained a global understanding of biological processes. For broader access, a user-friendly web server for researchers and clinicians is available at https://cup.pathmethy.com.

New techniques to identify the tissue of origin for cancer of unknown primary in the era of precision medicine: progress and challenges.

Despite a standardized diagnostic examination, cancer of unknown primary (CUP) is a rare metastatic malignancy with an unidentified tissue of origin (TOO). Patients diagnosed with CUP are typically treated with empiric chemotherapy, although their prognosis is worse than those with metastatic cancer of a known origin. TOO identification of CUP has been employed in precision medicine, and subsequent site-specific therapy is clinically helpful. For example, molecular profiling, including genomic profiling, gene expression profiling, epigenetics and proteins, has facilitated TOO identification. Moreover, machine learning has improved identification accuracy, and non-invasive methods, such as liquid biopsy and image omics, are gaining momentum. However, the heterogeneity in prediction accuracy, sample requirements and technical fundamentals among the various techniques is noteworthy. Accordingly, we systematically reviewed the development and limitations of novel TOO identification methods, compared their pros and cons and assessed their potential clinical usefulness. Our study may help patients shift from empirical to customized care and improve their prognoses.

Evolutionary history of MEK1 illuminates the nature of deleterious mutations.

Mutations in signal transduction pathways lead to various diseases including cancers. MEK1 kinase, encoded by the human MAP2K1 gene, is one of the central components of the MAPK pathway and more than a hundred somatic mutations in the MAP2K1 gene were identified in various tumors. Germline mutations deregulating MEK1 also lead to congenital abnormalities, such as the cardiofaciocutaneous syndrome and arteriovenous malformation. Evaluating variants associated with a disease is a challenge, and computational genomic approaches aid in this process. Establishing evolutionary history of a gene improves computational prediction of disease-causing mutations; however, the evolutionary history of MEK1 is not well understood. Here, by revealing a precise evolutionary history of MEK1, we construct a well-defined dataset of MEK1 metazoan orthologs, which provides sufficient depth to distinguish between conserved and variable amino acid positions. We matched known and predicted disease-causing and benign mutations to evolutionary changes observed in corresponding amino acid positions and found that all known and many suspected disease-causing mutations are evolutionarily intolerable. We selected several variants that cannot be unambiguously assessed by automated prediction tools but that are confidently identified as "damaging" by our approach, for experimental validation in Drosophila. In all cases, evolutionary intolerant variants caused increased mortality and severe defects in fruit fly embryos confirming their damaging nature. We anticipate that our analysis will serve as a blueprint to help evaluate known and novel missense variants in MEK1 and that our approach will contribute to improving automated tools for disease-associated variant interpretation.

CHIQUITA1 maintains the temporal transition between proliferation and differentiation in Arabidopsis thaliana.

Body size varies widely among species, populations and individuals, depending on the environment. Transitioning between proliferation and differentiation is a crucial determinant of final organ size, but how the timing of this transition is established and maintained remains unknown. Using cell proliferation markers and genetic analysis, we show that CHIQUITA1 (CHIQ1) is required to maintain the timing of the transition from proliferation to differentiation in Arabidopsis thaliana. Combining kinematic and cell lineage-tracking studies, we found that the number of actively dividing cells in chiquita1-1 plants decreases prematurely compared with wild-type plants, suggesting CHIQ1 maintains the proliferative capacity in dividing cells and ensures that cells divide a specific number of times. CHIQ1 belongs to a plant-specific gene family of unknown molecular function and genetically interacts with three close members of its family to control the timing of proliferation exit. Our work reveals the interdependency between cellular and organ-level processes underlying final organ size determination.

Synergic activity of FGFR2 and MEK inhibitors in the treatment of FGFR2-amplified cancers of unknown primary.

Patients with cancer of unknown primary (CUP) carry the double burden of an aggressive disease and reduced access to therapies. Experimental models are pivotal for CUP biology investigation and drug testing. We derived two CUP cell lines (CUP#55 and #96) and corresponding patient-derived xenografts (PDXs), from ascites tumor cells. CUP cell lines and PDXs underwent histological, immune-phenotypical, molecular, and genomic characterization confirming the features of the original tumor. The tissue-of-origin prediction was obtained from the tumor microRNA expression profile and confirmed by single-cell transcriptomics. Genomic testing and fluorescence in situ hybridization analysis identified FGFR2 gene amplification in both models, in the form of homogeneously staining region (HSR) in CUP#55 and double minutes in CUP#96. FGFR2 was recognized as the main oncogenic driver and therapeutic target. FGFR2-targeting drug BGJ398 (infigratinib) in combination with the MEK inhibitor trametinib proved to be synergic and exceptionally active, both in vitro and in vivo. The effects of the combined treatment by single-cell gene expression analysis revealed a remarkable plasticity of tumor cells and the greater sensitivity of cells with epithelial phenotype. This study brings personalized therapy closer to CUP patients and provides the rationale for FGFR2 and MEK targeting in metastatic tumors with FGFR2 pathway activation.

Homologous recombination-deficient mutation cluster in tumor suppressor RAD51C identified by comprehensive analysis of cancer variants.

Mutations in homologous recombination (HR) genes, including BRCA1, BRCA2, and the RAD51 paralog RAD51C, predispose to tumorigenesis and sensitize cancers to DNA-damaging agents and poly(ADP ribose) polymerase inhibitors. However, ∼800 missense variants of unknown significance have been identified for RAD51C alone, impairing cancer risk assessment and therapeutic strategies. Here, we interrogated >50 RAD51C missense variants, finding that mutations in residues conserved with RAD51 strongly predicted HR deficiency and disrupted interactions with other RAD51 paralogs. A cluster of mutations was identified in and around the Walker A box that led to impairments in HR, interactions with three other RAD51 paralogs, binding to single-stranded DNA, and ATP hydrolysis. We generated structural models of the two RAD51 paralog complexes containing RAD51C, RAD51B-RAD51C-RAD51D-XRCC2 and RAD51C-XRCC3. Together with our functional and biochemical analyses, the structural models predict ATP binding at the interface of RAD51C interactions with other RAD51 paralogs, similar to interactions between monomers in RAD51 filaments, and explain the failure of RAD51C variants in binding multiple paralogs. Ovarian cancer patients with variants in this cluster showed exceptionally long survival, which may be relevant to the reversion potential of the variants. This comprehensive analysis provides a framework for RAD51C variant classification. Importantly, it also provides insight into the functioning of the RAD51 paralog complexes.

AnnoDUF: A Web-Based Tool for Annotating Functions of Proteins Having Domains of Unknown Function.

The rapid expansion of biological sequence databases due to high-throughput genomic and proteomic sequencing methods has left a considerable number of identified protein sequences with unclear or incomplete functional annotations. Domains of unknown function (DUFs) are protein domains that lack functional annotations but are present in numerous proteins. To address the challenge of finding functional annotations for DUFs, we have developed a computational method that efficiently identifies and annotates these enigmatic protein domains by utilizing the position-specific iterative basic local alignment search tool (PSI-BLAST) and data mining techniques. Our pipeline identifies putative potential functionalities of DUFs, thereby decreasing the gap between known sequences and functions. The tool can also take user input sequences to annotate. We executed our pipeline on 5111 unique DUF sequences obtained from Pfam, resulting in putative annotations for 2007 of these. These annotations were subsequently incorporated into a comprehensive database and interfaced with a web-based server named "AnnoDUF". AnnoDUF is freely accessible to both academic and industrial users, via the World Wide Web at the link http://bts.ibab.ac.in/annoduf.php. All scripts used in this study are uploaded to the GitHub repository, and these can be accessed from https://github.com/BioToolSuite/AnnoDUF.

Structural implications of amyloidogenic rare variants Ser282Leu and Gln356Arg identified in h-BRCA1.

Preliminary studies have shown BRCA1 (170-1600) residues to be intrinsically disordered with unknown structural details. However, thousands of clinically reported variants have been identified in this central region of BRCA1. Therefore, we aimed to characterize h-BRCA1(260-553) to assess the structural basis for pathogenicity of two rare missense variants Ser282Leu, Gln356Arg identified from the Indian and Russian populations respectively. Small-angle X-ray scattering analysis revealed WT scores Rg -32 Å, Dmax -93 Å, and Rflex-51% which are partially disordered, whereas Ser282Leu variant displayed a higher degree of disorderedness and Gln356Arg was observed to be aggregated. WT protein also possesses an inherent propensity to undergo a disorder-to-order transition in the presence of cruciform DNA and 2,2,2-Trifluoroethanol (TFE). An increased alpha-helical pattern was observed with increasing concentration of TFE for the Gln356Arg mutant whereas Ser282Leu mutant showed significant differences only at the highest TFE concentration. Furthermore, higher thermal shift was observed for WT-DNA complex compared to the Gln356Arg and Ser282Leu protein-DNA complex. Moreover, mature amyloid-like fibrils were observed with 30 µM thioflavin T (ThT) at 37°C for Ser282Leu and Gln356Arg proteins while the WT protein exists in a protofibril state as observed by TEM. Gln356Arg formed higher-order aggregates with amyloidogenesis over time as monitored by ThT fluorescence. In addition, computational analyses confirmed larger conformational fluctuations for Ser282Leu and Gln356Arg mutants than for the WT. The global structural alterations caused by these variants provide a mechanistic approach for further classification of the variants of uncertain clinical significance in BRCA1 into amyloidogenic variants which may have a significant role in disease pathogenesis.

Nuclear Medicine Imaging Tools in Fever of Unknown Origin: Time for a Revisit and Appropriate Use Criteria.

Fever of unknown origin (FUO) is a clinical conundrum for patients and clinicians alike, and imaging studies are often performed as part of the diagnostic workup of these patients. Recently, the Society of Nuclear Medicine and Molecular Imaging convened and approved a guideline on the use of nuclear medicine tools for FUO. The guidelines support the use of 2-18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) in adults and children with FUO. 18F-FDG PET/CT allows detection and localization of foci of hypermetabolic lesions with high sensitivity because of the 18F-FDG uptake in glycolytically active cells that may represent inflammation, infection, or neoplasia. Clinicians should consider and insurers should cover 18F-FDG PET/CT when evaluating patients with FUO, particularly when other clinical clues and preliminary studies are unrevealing.

Thrombolysis for Wake-Up Stroke Versus Non-Wake-Up Unwitnessed Stroke: EOS Individual Patient Data Meta-Analysis.

BACKGROUND: Stroke with unknown time of onset can be categorized into 2 groups; wake-up stroke (WUS) and unwitnessed stroke with an onset time unavailable for reasons other than wake-up (non-wake-up unwitnessed stroke, non-WUS). We aimed to assess potential differences in the efficacy and safety of intravenous thrombolysis (IVT) between these subgroups. METHODS: Patients with an unknown-onset stroke were evaluated using individual patient-level data of 2 randomized controlled trials (WAKE-UP [Efficacy and Safety of MRI-Based Thrombolysis in Wake-Up Stroke], THAWS [Thrombolysis for Acute Wake-Up and Unclear-Onset Strokes With Alteplase at 0.6 mg/kg]) comparing IVT with placebo or standard treatment from the EOS (Evaluation of Unknown-Onset Stroke Thrombolysis trial) data set. A favorable outcome was prespecified as a modified Rankin Scale score of 0 to 1 at 90 days. Safety outcomes included symptomatic intracranial hemorrhage at 22 to 36 hours and 90-day mortality. The IVT effect was compared between the treatment groups in the WUS and non-WUS with multivariable logistic regression analysis. RESULTS: Six hundred thirty-four patients from 2 trials were analyzed; 542 had WUS (191 women, 272 receiving alteplase), and 92 had non-WUS (42 women, 43 receiving alteplase). Overall, no significant interaction was noted between the mode of onset and treatment effect (P value for interaction=0.796). In patients with WUS, the frequencies of favorable outcomes were 54.8% and 45.5% in the IVT and control groups, respectively (adjusted odds ratio, 1.47 [95% CI, 1.01-2.16]). Death occurred in 4.0% and 1.9%, respectively (P=0.162), and symptomatic intracranial hemorrhage in 1.8% and 0.3%, respectively (P=0.194). In patients with non-WUS, no significant difference was observed in favorable outcomes relative to the control (37.2% versus 29.2%; adjusted odds ratio, 1.76 [0.58-5.37]). One death and one symptomatic intracranial hemorrhage were reported in the IVT group, but none in the control. CONCLUSIONS: There was no difference in the effect of IVT between patients with WUS and non-WUS. IVT showed a significant benefit in patients with WUS, while there was insufficient statistical power to detect a substantial benefit in the non-WUS subgroup. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: CRD42020166903.

Multi-Omics integration can be used to rescue metabolic information for some of the dark region of the Pseudomonas putida proteome.

In every omics experiment, genes or their products are identified for which even state of the art tools are unable to assign a function. In the biotechnology chassis organism Pseudomonas putida, these proteins of unknown function make up 14% of the proteome. This missing information can bias analyses since these proteins can carry out functions which impact the engineering of organisms. As a consequence of predicting protein function across all organisms, function prediction tools generally fail to use all of the types of data available for any specific organism, including protein and transcript expression information. Additionally, the release of Alphafold predictions for all Uniprot proteins provides a novel opportunity for leveraging structural information. We constructed a bespoke machine learning model to predict the function of recalcitrant proteins of unknown function in Pseudomonas putida based on these sources of data, which annotated 1079 terms to 213 proteins. Among the predicted functions supplied by the model, we found evidence for a significant overrepresentation of nitrogen metabolism and macromolecule processing proteins. These findings were corroborated by manual analyses of selected proteins which identified, among others, a functionally unannotated operon that likely encodes a branch of the shikimate pathway.

A Fast, Affordable, and Minimally Invasive Diagnostic Test for Cancer of Unknown Primary Using DNA Methylation Profiling.

Currently, we cannot provide a conclusive diagnosis for 3% to 5% of people who are confronted with cancer. These patients have cancer of unknown primary (CUP), ie, a metastasized cancer for which the tissue of origin cannot be determined. Studies have shown that the DNA methylation profile is a unique "fingerprint" that can be used to classify tumors. Here we used cell-free reduced representation bisulfite sequencing (cfRRBS), a technique that allows us to identify the methylation profile starting from minimal amounts of highly fragmented DNA, for CUP diagnosis on formalin-fixed paraffin-embedded (FFPE) tissue and liquid biopsies. We collected 80 primary tumor FFPE samples covering 16 tumor entities together with 15 healthy plasma samples to use as a custom cfRRBS reference data set. Entity-specific methylation regions are defined for each entity to build a classifier based on nonnegative least squares deconvolution. This classification framework was tested on 30 FFPE, 19 plasma, and 40 pleural and peritoneal effusion samples of both known metastatic tumors and clinical CUPs for which pathological investigation finally resulted in a cancer diagnosis. Using this framework, 27 of 30 FFPE (all CUPs) and 16 of 19 plasma samples (10/13 CUPs) obtained an accurate diagnosis, with a minimal DNA input of 400 pg. Diagnosis of the 40 pleural and peritoneal effusion samples is possible in 9 of 27 samples with negative/inconclusive cytology (6/13 CUPs), showing that cell-free DNA (cfDNA) methylation profiling could complement routine cytologic analysis. However, a low "cfDNA - high-molecular weight DNA ratio" has a considerable impact on the prediction accuracy. Moreover, the accuracy improves significantly if the predicted tumor percentage is >7%. This proof-of-concept study shows the feasibility of using DNA methylation profiling on FFPE and liquid biopsy samples such as blood, ascites, and pleural effusions in a fast and affordable way. Our novel RRBS-based technique requires minimal DNA input, can be performed in <1 week, and is highly adaptable to specific diagnostic problems as we only use 5 FFPE references per tumor entity. We believe that cfRRBS methylation profiling could be a valuable addition to the pathologist's toolbox in the diagnosis of CUPs.

N-cadherin: A diagnostic marker to help discriminate primary liver carcinomas from extrahepatic carcinomas.

Distinguishing primary liver cancer (PLC), namely hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA), from liver metastases is of crucial clinical importance. Histopathology remains the gold standard, but differential diagnosis may be challenging. While absent in most epithelial, the expression of the adherens junction glycoprotein N-cadherin is commonly restricted to neural and mesenchymal cells, or carcinoma cells that undergo the phenomenon of epithelial-to-mesenchymal transition (EMT). However, we recently established N- and E-cadherin expression as hallmarks of normal hepatocytes and cholangiocytes, which are also preserved in HCC and iCCA. Therefore, we hypothesized that E- and/or N-cadherin may distinguish between carcinoma derived from the liver vs carcinoma of other origins. We comprehensively evaluated E- and N-cadherin in 3359 different tumors in a multicenter study using immunohistochemistry and compared our results with previously published 882 cases of PLC, including 570 HCC and 312 iCCA. Most carcinomas showed strong positivity for E-cadherin. Strong N-cadherin positivity was present in HCC and iCCA. However, except for clear cell renal cell carcinoma (23.6% of cases) and thyroid cancer (29.2%), N-cadherin was only in some instances faintly expressed in adenocarcinomas of the gastrointestinal tract (0%-0.5%), lung (7.1%), pancreas (3.9%), gynecological organs (0%-7.4%), breast (2.2%) as well as in urothelial (9.4%) and squamous cell carcinoma (0%-5.6%). As expected, N-cadherin was detected in neuroendocrine tumors (25%-75%), malignant melanoma (46.2%) and malignant mesothelioma (41%). In conclusion, N-cadherin is a useful marker for the distinction of PLC vs liver metastases of extrahepatic carcinomas (P < .01).