Our purpose was to elucidate the genotype and ophthalmological and audiological phenotype in TUBB4B-associated inherited retinal dystrophy (IRD) and sensorineural hearing loss (SNHL), and to model the effects of all possible amino acid substitutions at the hotspot codons Arg390 and Arg391. Six patients from five families with heterozygous missense variants in TUBB4B were included in this observational study. Ophthalmological testing included best-corrected visual acuity, fundus examination, optical coherence tomography, fundus autofluorescence imaging, and full-field electroretinography (ERG). Audiological examination included pure-tone and speech audiometry in adult patients and auditory brainstem response testing in a child. Genetic testing was performed by disease gene panel analysis based on genome sequencing. The molecular consequences of the substitutions of residues 390 and 391 on TUBB4B and its interaction with α-tubulin were predicted in silico on its three-dimensional structure obtained by homology modelling. Two independent patients had amino acid exchanges at position 391 (p.(Arg391His) or p.(Arg391Cys)) of the TUBB4B protein. Both had a distinct IRD phenotype with peripheral round yellowish lesions with pigmented spots and mild or moderate SNHL, respectively. Yet the phenotype was milder with a sectorial pattern of bone spicules in one patient, likely due to a genetically confirmed mosaicism for p.(Arg391His). Three patients were heterozygous for an amino acid exchange at position 390 (p.(Arg390Gln) or p.(Arg390Trp)) and presented with another distinct retinal phenotype with well demarcated pericentral retinitis pigmentosa. All showed SNHL ranging from mild to severe. One additional patient showed a variant distinct from codon 390 or 391 (p.(Tyr310His)), and presented with congenital profound hearing loss and reduced responses in ERG. Variants at codon positions 390 and 391 were predicted to decrease the structural stability of TUBB4B and its complex with α-tubulin, as well as the complex affinity. In conclusion, the twofold larger reduction in heterodimer affinity exhibited by Arg391 substitutions suggested an association with the more severe retinal phenotype, compared to the substitution at Arg390.

Alternative splicing (AS) alters messenger RNA (mRNA) coding capacity, localization, stability, and translation. Here we use comparative transcriptomics to identify cis-acting elements coupling AS to translational control (AS-TC). We sequenced total cytosolic and polyribosome-associated mRNA from human, chimpanzee, and orangutan induced pluripotent stem cells (iPSCs), revealing thousands of transcripts with splicing differences between subcellular fractions. We found both conserved and species-specific polyribosome association patterns for orthologous splicing events. Intriguingly, alternative exons with similar polyribosome profiles between species have stronger sequence conservation than exons with lineage-specific ribosome association. These data suggest that sequence variation underlies differences in the polyribosome association. Accordingly, single nucleotide substitutions in luciferase reporters designed to model exons with divergent polyribosome profiles are sufficient to regulate translational efficiency. We used position specific weight matrixes to interpret exons with species-specific polyribosome association profiles, finding that polymorphic sites frequently alter recognition motifs for trans-acting RNA binding proteins. Together, our results show that AS can regulate translation by remodeling the cis-regulatory landscape of mRNA isoforms.

In this paper, I study the role of gender-typical parental occupation for young adults’ gender-typical university major choice using data on a recent cohort of university students in Germany. Results show significant intergenerational associations between the gender typicality in parental occupation and young adults’ majors. As to why these effects occur, findings suggest that the transfer of occupation-specific resources from parents to their children plays an important role and that a transmission of gender roles explains at least some of the father-son associations. The paper contributes to existing literature by introducing a novel measure that operationalises the extent to which majors and occupations are ‘typically female’ or ‘typically male’ and by studying different transmission channels.

Einleitung Bei erwachsenen Cochlea-Implantat (CI)-Patienten erfolgt die Anpassung durch verbales Feedback, um die Hörschwelle und den angenehmsten Lautstärkepegel (MCL) zu bestimmen. Dieser Ansatz ist für kleine Kinder und Patienten, die nicht mit den Audiologen interagieren können, nicht geeignet. Bei CI-Patienten kann die elektrisch evozierte Stapediusreflexschwelle (ESRT) als Reaktion auf eine elektrische Stimulation mit dem Implantat bestimmt werden. Die ESRT-Messung erfordert keine aktive Mitarbeit der Patienten und kann mit einem Standardtympanometer durchgeführt werden. Diese Art der Messung ist jedoch oft unzuverlässig. Wir haben einen Messaufbau entwickelt, der keinen Druckaufbau im Gehörgang erfordert. Diesen haben wir im Hinblick auf Genauigkeit und Stabilität der Sonde getestet.

Introduction In adult cochlear implant (CI) patients fitting is facilitated by verbal feedback to determine the threshold and most comfortable loudness level (MCL). This approach is not suitable for young children and patients unable to interact with the audiologist. In CI patients, an Electrically Evoked Stapedius Reflex Threshold (ESRT) can be determined in response to electrical stimulation through the implant. ESRT measurement does not require active feedback by the patient and can be obtained through a standard tympanometer. Still, nowadays this type of measurement is often unreliable because of technical shortcomings, which we aim to overcome. We implemented a setting that does not require pressurization of the ear canal and tested it in terms of accuracy and probe stability.

Head and neck squamous cell carcinomas (HNSCC) are the sixth most common malignancies worldwide. 45% of patients are diagnosed at a late tumor stage associated with poor survival. For metastatic, unresectable or recurrent (m/uR) HNSCC, immune checkpoint inhibition (ICI) was recently approved as a novel therapeutic option showing significant survival benefits compared to standard chemotherapy-based treatment. However, response to ICI is still limited to a small number of patients calling for further improvement of T cell-based immunotherapies. Peptide-based approaches, which rely on the specific immune recognition of tumor-associated human leukocyte antigen (HLA) presented peptides, represent promising and low side effect treatment options. Peptide vaccination has been shown to enhance and induce long-term anti-tumoral immune responses and even clinical responses in HNSCC patients. However, current vaccines are either monovalent, based on patient-individual tumor-specific mutations or restricted to a single HLA allotype and therefore neither widely applicable nor suitable for reliable studies and large-scale production. In this study, using mass spectrometry (MS) -based immunopeptidome analysis of a large cohort of HNSCC patient (n = 30) tumor and adjacent benign samples, we established a tumor-associated off-the-shelf peptide warehouse for broadly applicable personalized therapies. The malignant dataset, comprising 91651 HLA ligands, was compared to adjacent benign and various benign tissues (www.hla-ligand-atlas.org) to identify tumor-exclusive antigens. Further antigen selection was based on allotype-specific high frequent presentation. In total, 23 frequently presented and tumor-exclusive HNSCC-associated peptides were selected for six of the most common HLA class I allotypes (A*01, A*02, A*24, B*15, B*35, B*40) covering >75% of the world population, as well as five HLA class II presented peptides binding various different HLA class II allotypes. Immunogenicity was validated by IFN-γ ELISPOT screening for spontaneous preexisting T cell responses targeting the respective peptides as well as by in vitro priming experiments of naïve T cells in HNSCC patients and healthy volunteers. Furthermore, immunopeptidome analyses identified these antigens in patient plasma samples providing first evidence for “liquid biopsy” immunopeptidome analysis without the need of primary tumor tissue. A phase I study evaluating safety, immunogenicity as well as first efficacy of this warehouse-based vaccine in combination with ICI in HNSCC patients is currently being set up, with personalized peptide selection based on individual HLA-allotype and MS analysis of patient tumor/plasma sample. In conclusion, we here designed a peptide warehouse that enables a polyvalent and widely applicable but still personalized peptide vaccination in HNSCC patients. Citation Format: Sarah Schroeder, Thorben Gross, Annika Nelde, Marcel Wacker, Jens Bauer, Jonas Rieth, Marissa Dubbelaar, Lena Muehlenbruch, Yacine Maringer, Paul-Stefan Mauz, Martin Sailer, Julia Philipp, Sven Becker, Thomas Breuer, Helmut R. Salih, Hans-Georg Rammensee, Hubert Löwenheim, Juliane S. Walz. Immunopeptidomics-guided tumor antigen warehouse design for peptide-based immunotherapy in head and neck squamous cell carcinomas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3555.

Background Reprocessing of complex instruments like flexible ENT-endoscopes with and without working channel are challanging for clinics and private practices. Aim of the study was to analyse the costs of an examination with a reusable endoscope-system and to compare it with two single-use endoscope-systems.Material and Methods A cost minimization analysis was performed at the Department of Otorhinolaryngology, Head and Neck Surgery of the University Medical Center in Mainz, Germany. The local reusable endoscopy-system was compared with two single-use endoscopy-systems of Ambu and Karl Storz.Results Overall costs per examination with a reusable-scope were 23.03 (sic) (11.60 (sic) investment costs + 5.09 (sic) repair costs + 6.34 (sic) reprocessing costs). The single-use Endoscopy-system of Ambu resulted in 120.43 (sic) per examination (120.00 (sic) acquisition costs + 0.43 (sic) storage costs). Overall costs for the singleuse endoscopy-system of Karl Storz were 223.44 (sic) per examination (investment costs for monitors 3.01 (sic) + 220.00 (sic) acquisition costs + 0.43 (sic) storage costs).Discussion Flexible single-use ENT-endoscopy-systems generate higher costs in comparison to conventional reusable ones. But there are also advantages from the medical and economical side.Conclusion A smart mix of reusable and single-use endoscopy systems seems therefore usefull.

High expression of LIN28B is associated with aggressive malignancy and poor survival. Here, probing MYCN-amplified neuroblastoma as a model system, we showed that LIN28B expression was associated with enhanced cell migration in vitro and invasive and metastatic behavior in murine xenografts. Sequence analysis of the polyribosome fraction of LIN28B-expressing neuroblastoma cells revealed let-7-independent enrichment of transcripts encoding components of the translational and ribosomal apparatus and depletion of transcripts of neuronal developmental programs. We further observed that LIN28B utilizes both its cold shock and zinc finger RNA binding domains to preferentially interact with MYCN-induced transcripts of the ribosomal complex, enhancing their translation. These data demonstrated that LIN28B couples the MYCN-driven transcriptional program to enhanced ribosomal translation, thereby implicating LIN28B as a posttranscriptional driver of the metastatic phenotype.

Despite recent advances in therapeutic approaches, patients with MLL-rearranged leukemia still have poor outcomes. Here, we find that the RNA-binding protein IGF2BP3, which is overexpressed in MLL-translocated leukemia, strongly amplifies MLL-Af4-mediated leukemogenesis. Deletion of Igf2bp3 significantly increases the survival of mice with MLL-Af4-driven leukemia and greatly attenuates disease, with a minimal impact on baseline hematopoiesis. At the cellular level, MLL-Af4 leukemia-initiating cells require Igf2bp3 for their function in leukemogenesis. At the molecular level, IGF2BP3 regulates a complex posttranscriptional operon governing leukemia cell survival and proliferation. IGF2BP3-targeted mRNA transcripts include important MLL-Af4-induced genes, such as those in the Hoxa locus, and the Ras signaling pathway. Targeting of transcripts by IGF2BP3 regulates both steady-state mRNA levels and, unexpectedly, pre-mRNA splicing. Together, our findings show that IGF2BP3 represents an attractive therapeutic target in this disease, providing important insights into mechanisms of posttranscriptional regulation in leukemia.

Could robotization make the gender pay gap worse? We provide the first large-scale evidence on the impact of industrial robots on the gender pay gap using data from 20 European countries. We show that robot adoption increases both male and female earnings but also increases the gender pay gap. Using an instrumental variable strategy, we find that a ten percent increase in robotization leads to a 1.8 percent increase in the gender pay gap. These results are mainly driven by countries with high levels of gender inequality and outsourcing destination countries. We then explore the mechanisms behind this effect and find that our results can be explained by the fact that men at medium- and high-skill occupations disproportionately benefit from robotization (through a productivity effect). We rule out the possibility that our results are driven by mechanical changes in the gender composition of the workforce nor by inflows or outflows from the manufacturing sector.

Pancreatic ductal adenocarcinoma (PDAC) lethality is due to metastatic dissemination. Characterization of rare, heterogeneous circulating tumor cells (CTCs) can provide insight into metastasis and guide development of novel therapies. Using the CTC-iChip to purify CTCs from PDAC patients for RNA-seq characterization, we identify three major correlated gene sets, with stemness genes LIN28B/KLF4 , WNT5A , and LGALS3 enriched in each correlated gene set; only LIN28B CTC expression was prognostic. CRISPR knockout of LIN28B —an oncofetal RNA-binding protein exerting diverse effects via negative regulation of let-7 miRNAs and other RNA targets—in cell and animal models confers a less aggressive/metastatic phenotype. This correlates with de-repression of let-7 miRNAs and is mimicked by silencing of downstream let-7 target HMGA2 or chemical inhibition of LIN28B/let-7 binding. Molecular characterization of CTCs provides a unique opportunity to correlated gene set metastatic profiles, identify drivers of dissemination, and develop therapies targeting the “seeds” of metastasis.

Chromosomal rearrangements of the mixed-lineage leukemia (MLL) gene are observed in acute lymphoblastic leukemias (ALL), acute myeloid leukemias (AML), and in rare mixed-lineage leukemia. Despite recent progress in therapeutic approaches, patients with MLL-rearranged (MLLr) leukemias still have very poor outcomes and a high risk of relapse. Of more than 90 fusion partner genes, MLL-AF4 is the most common MLL fusion protein in patients. Previously, we found that the RNA binding protein IGF2BP3 was specifically overexpressed in MLL-rearranged B-ALL, and enforced expression in vivo led to a pathologic expansion of hematopoietic stem and progenitor cells resulting in B and myeloid cell leukocytosis in the periphery. However, the requirement of IGF2BP3 in MLL-AF4 mediated leukemogenesis remains to be determined. Utilizing our previously generated list of differentially regulated targets with IGF2BP3 knockdown and a published dataset of MLL-Af4 targets, we determined that transcripts modulated by IGF2BP3 showed significant enrichment for MLL-Af4-bound genes. Furthermore, we observed that MLL-AF4 directly binds to and transcriptionally induces IGF2BP3. We performed ChIP-PCR assays on RS4;11 and SEM cell lines, human B-ALL cell lines that carry the MLL-AF4 translocation, and determined that the region in the first intron of IGF2BP3 is strongly bound by MLL-AF4. Furthermore, we observed a dose-dependent increase in luciferase reporter activity when we co-transfected a dual-luciferase reporter vector containing the promoter region of IGF2BP3 with increasing levels of MLL-AF4 expressing retroviral vector. To determine the role of Igf2bp3 in MLL-Af4 driven leukemogenesis, we generated the first Igf2bp3 KO murine model. Surprisingly, Igf2bp3 KO mice maintain normal, steady-state hematopoiesis. However, in striking contrast, deletion of Igf2bp3 in the MLL-Af4 leukemia model, significantly increases the survival of MLL-Af4 transplanted mice and greatly attenuates the disease. Furthermore, Igf2bp3 deficiency significantly reduced the tumor burden and disease severity. We observed significant decreases in WBC counts, spleen weights, and infiltrating leukemic cells visualized in histopathological analysis of hematopoietic tissues and quantified by FACS analysis. Moreover, deletion of Igf2bp3 led to a leukemia-initiating cell (LIC) disadvantage in vivo, demonstrated by significantly reduced engraftment in primary transplanted mice and reconstitution of secondary serially transplanted mice. To identify the transcripts directly regulated by Igf2bp3 in the context of MLL-Af4 driven leukemia, we carried out enhanced crosslinking and immunoprecipitation (eCLIP) transcriptome analysis of MLL-Af4 transformed early stem and progenitor cells and primary cells purified from splenic tumors of MLL-Af4 leukemic mice. We discovered an IGF2BP3-regulated post-transcriptional operon governing leukemic cell survival and proliferation, in which mRNA targets include the Hoxa locus and numerous genes within the Ras signaling pathway. In our study, we provide evidence that Igf2bp3 is required for the initiation of MLL-Af4 driven leukemia. We determined that Igf2bp3 is necessary for the development of and function of MLL-Af4 LICs. Mechanistically, we show that Igf2bp3 binds to and modulates the expression of hundreds of critical target transcripts. In summary, we demonstrate that Igf2bp3 is a positive regulator of MLLr leukemogenesis by targeting Hoxa transcripts such as Hoxa9 and numerous Ras signaling pathway transcripts, thereby controlling multiple downstream effector pathways required for disease initiation and aggressiveness. Together, our findings identify IGF2BP3 as an important, potential therapeutic target in this disease. No relevant conflicts of interest to declare.

The serine and arginine-rich splicing factor SRSF1 is an evolutionarily conserved, essential pre-mRNA splicing factor. Through a global protein-RNA interaction survey we discovered SRSF1 binding sites 25-50nt upstream from hundreds of pre-miRNAs. Using primary miRNA-10b as a model we demonstrate that SRSF1 directly regulates microRNA biogenesis both in vitro and in vivo. Selective 2’ hydroxyl acylation analyzed by primer extension (SHAPE) defined a structured RNA element located upstream of the precursor miRNA-10b stem loop. Our data support a model where SRSF1 promotes initial steps of microRNA biogenesis by relieving the repressive effects of cis-regulatory elements within the leader sequence.

Despite recent advances in therapeutic approaches, patients with MLL-rearranged leukemia still have poor outcomes and a high risk of relapse. Here, we found that MLL-AF4, the most common MLL fusion protein in patients, transcriptionally induces IGF2BP3 and that IGF2BP3 strongly amplifies MLL-Af4 mediated leukemogenesis. Deletion of Igf2bp3 significantly increases the survival of mice with MLL-Af4 driven leukemia and greatly attenuates disease, with a minimal impact on baseline hematopoiesis. At the cellular level, MLL-Af4 leukemia-initiating cells require Igf2bp3 for their function in leukemogenesis. eCLIP and transcriptome analysis of MLL-Af4 transformed stem and progenitor cells and MLL-Af4 bulk leukemia cells reveals a complex IGF2BP3-regulated post-transcriptional operon governing leukemia cell survival and proliferation. Regulated mRNA targets include important leukemogenic genes such as those in the Hoxa locus and numerous genes within the Ras signaling pathway. Together, our findings show that IGF2BP3 is an essential positive regulator of MLL-AF4 mediated leukemogenesis and represents an attractive therapeutic target in this disease.

Im Rahmen dieser Arbeit sollte die molekulare Basis des erstaunlich benignen Verhaltens der SPN angesichts des aktivierten Wnt-Signalweges und der Cyclin D1-Uberexpression, welche normalerweise beide mit aggressiven Tumoren assoziiert sind, beleuchtet werden. Hierzu wurde die RNA-Expression der Gene FLI1 sowie DKK1 und INPP5D (SHIP1) als durch FLI1 regulierte Gene und BCL9 als Bestandteil des Wnt/β-Catenin Signalweges untersucht. Neben der SPN wurde zusatzlich eine mogliche Bedeutung dieser Gene im aggressiven PDAC sowie dessen Vorlauferlasion der IPMN gepruft. Die anfangs aufgestellte Hypothese einer Beteiligung der Gene DKK1 und BCL9 sowohl an der SPN- als auch an der PDAC- und IPMN-Tumorgenese musste aufgrund der erhobenen Daten jedoch vorerst verworfen werden. Jedoch scheint FLI1 eine entscheidende Rolle in der SPN-Tumorgenese zu spielen. Zudem sind sowohl FLI1 als auch INPP5D in der IPMN signifikant uberexprimiert, allerdings unabhangig voneinander. Die Frage, uber welchen intrazellularen Signalweg FLI1 und INPP5D diese Rolle ausuben, konnte noch nicht geklart werden. Auch der molekulargenetische Grund fur das niedrig maligne Verhalten der SPN bzw. intermediar-maligne Verhalten der IPMN bleibt weiterhin ein nur zum Teil gelostes Ratsel und wirft noch immer eine Vielzahl von Fragen auf.

Liquid biopsy refers to sampling cellular material that originated from a solid organ and then entered the bloodstream. Circulating epithelial cells (CECs) can be detected by liquid biopsy in the setting of localized cancer1Stott S.L. Richard J.L. Nagrath S. et al.Isolation and characterization of circulating tumor cells from patients with localized and metastatic prostate cancer.Sci Transl Med. 2010; 2: 25ra23Crossref PubMed Scopus (353) Google Scholar, 2Lucci A. Hall C.S. Lodhi A.K. et al.Circulating tumour cells in non-metastatic breast cancer: a prospective study.Lancet Oncol. 2012; 13: 688-695Abstract Full Text Full Text PDF PubMed Scopus (413) Google Scholar and even preneoplastic pancreatic lesions,3Rhim A.D. Thege F.I. Santana S.M. et al.Detection of circulating pancreas epithelial cells in patients with pancreatic cystic lesions.Gastroenterology. 2014; 146: 647-651Abstract Full Text Full Text PDF PubMed Scopus (164) Google Scholar, 4Franses J.W. Basar O. Kadayifci A. et al.Improved detection of circulating epithelial cells in patients with intraductal papillary mucinous neoplasms.Oncologist. 2018; 23: 121-127Crossref PubMed Scopus (15) Google Scholar suggesting their presence is not exclusive to carcinogenesis. Hepatic CECs or “circulating hepatocytes,” which have yet to be described in the absence of malignancy, could serve as a powerful biomarker in the diagnosis and monitoring of chronic liver disease (CLD) and hepatocellular carcinoma (HCC). Isolating CECs is a technologic challenge because of their rarity in the bloodstream and the variable expression of antigens used for cell capture. For example, the Veridex platform (Veridex LLC, Raritan, NJ), which depends on epithelial cell adhesion molecules, yielded HCC CEC detection rates of only 35% and 41% in 2 independent studies.5Kelley R.K. Magbanua M.J. Butler T.M. et al.Circulating tumor cells in hepatocellular carcinoma: a pilot study of detection, enumeration, and next-generation sequencing in cases and controls.BMC Cancer. 2015; 15: 206Crossref PubMed Scopus (82) Google Scholar, 6Sun Y.F. Xu Y. Yang X.R. et al.Circulating stem cell-like epithelial cell adhesion molecule-positive tumor cells indicate poor prognosis of hepatocellular carcinoma after curative resection.Hepatology. 2013; 57: 1458-1468Crossref PubMed Scopus (275) Google Scholar To overcome this limitation, we developed an antigen-agnostic cell sorting device called the iChip, which isolates CECs while preserving cell viability and high-quality RNA content. We previously combined the iChip with an RNA signature based on established liver-specific markers to create an assay for the enrichment and detection of CECs in HCC.7Kalinich M. Bhan I. Kwan T.T. et al.An RNA-based signature enables high specificity detection of circulating tumor cells in hepatocellular carcinoma.Proc Natl Acad Sci U S A. 2017; 114: 1123-1128Crossref PubMed Scopus (107) Google Scholar In the present work, we used the iChip platform to detect CECs in patients with CLD but without HCC and to phenotypically discriminate between CECs in patients with and without HCC. First, we aimed to detect CECs by immunofluorescence. Blood samples were obtained from 10 healthy blood donors, 39 patients with CLD undergoing routine clinical surveillance for but with no evidence of HCC, 54 patients with HCC, and 10 HCC patients who underwent curative treatment and had no clinical evidence of disease (Supplementary Table 1, Supplementary Table 2, Supplementary Table 3, Supplementary Table 4). The iChip performed size-based exclusion of red blood cells, platelets, and plasma, followed by magnetophoresis of labeled white blood cells (WBCs; Supplementary Figure 1A).8Ozkumur E. Shah A.M. Ciciliano J.C. et al.Inertial focusing for tumor antigen-dependent and -independent sorting of rare circulating tumor cells.Sci Transl Med. 2013; 5: 179ra47Crossref PubMed Scopus (772) Google Scholar Second, CECs were enumerated by immunofluorescence staining for glypican-3, an oncofetal protein expressed in HCC but also in CLD liver tissue,9Wang H.L. Anatelli F. Zhai Q.J. et al.Glypican-3 as a useful diagnostic marker that distinguishes hepatocellular carcinoma from benign hepatocellular mass lesions.Arch Pathol Lab Med. 2008; 132: 1723-1728PubMed Google Scholar or cytokeratin, an epithelial marker (Supplementary Figure 1B). Using a threshold of 5 cells per 10 mL of whole blood, we identified CECs in a similar proportion of patients with CLD (79%), HCC (81%), and treated HCC with no evidence of disease (90%), but in only 5% of healthy donors (Supplementary Figure 1C and Supplementary Figure 2A and B; P < .01, each group vs healthy donors). iChip purification combined with immunofluorescent quantification demonstrated a high sensitivity for CEC detection with similar concentrations in patients with HCC and those with CLD. Of patients with CLD, those with advanced fibrosis (METAVIR F3 or F4) had a higher concentration of CECs (median 5.1 cells/mL) than those without advanced fibrosis (0.7 cells/mL; P < .01; Supplementary Figure 1D). Because the CLD study population consisted only of patients with sufficiently high risk of HCC to undergo surveillance, the etiology of CLD for each patient in the subgroup without advanced fibrosis was hepatitis B infection. The difference in CEC concentration associated with fibrosis stage did not appear to be related to CLD etiology, because the trend persisted when the analysis was restricted to only those with CLD induced by hepatitis B virus (median 5.0 cells/mL with advanced fibrosis, 0.7 cells/mL without advanced fibrosis; P = .06; Supplementary Figure 2C). Otherwise, there was no difference in CEC concentration by CLD etiology (Supplementary Figure 2D). As an orthogonal approach to detecting CECs, we used RNA-sequencing (RNA-seq). To determine the sensitivity of this approach, 0, 1, 3, 5, 10, or 50 HepG2 HCC cells were spiked into healthy donor blood 4 mL and processed through the iChip for RNA-seq. HepG2-specific gene expression was detectable in whole blood from a single cell (Figure 1A). Then, we turned to identifying CECs in clinical blood samples from 64 patients with CLD and 52 with HCC. We created a 17 liver-specific gene signature based on Genotype Tissue Expression (GTEx; https://gtexportal.org/home/) expression data. Liver-specific gene expression was identified in samples from the 2 patient groups but were absent in WBC subtypes flow sorted from iChip-processed blood (Figure 1B). Therefore, our data suggested that the liver-specific signature identified rare CECs rather than the aberrant expression of these genes in contaminating WBCs. As a proof of concept that CECs might phenotypically differ depending on the underlying disease state, we pursued gene expression profiling to identify qualitative rather than quantitative differences between CECs in the setting of CLD vs HCC. Our approach is outlined in Figure 1C. Using The Cancer Genome Atlas database, we identified 248 genes overexpressed in HCC compared with liver tissue excluding genes expressed in WBCs. Then, we used a random forest machine-learning approach to generate a classifier based on these genes to distinguish CLD from HCC CECs. In this approach, each decision tree in the random forest casts a “vote” classifying a sample as CLD or HCC. The final classifier used 25 genes (Supplementary Table 5). Notably, 3 of the most informative genes in the classifier (TESC,10Kang J. Kang Y.H. Oh B.M. et al.Tescalcin expression contributes to invasive and metastatic activity in colorectal cancer.Tumour Biol. 2016; 37: 13843-13853Crossref PubMed Scopus (12) Google Scholar SLC6A8,11Loo J.M. Scherl A. Nguyen A. et al.Extracellular metabolic energetics can promote cancer progression.Cell. 2015; 160: 393-406Abstract Full Text Full Text PDF PubMed Scopus (234) Google Scholar SPP112Sangaletti S. Tripodo C. Sandri S. et al.Osteopontin shapes immunosuppression in the metastatic niche.Cancer Res. 2014; 74: 4706-4719Crossref PubMed Scopus (90) Google Scholar) have been implicated in cancer metastasis and another (E2F1) is an established cell proliferation marker. The cross-validated classifier provided excellent separation between CLD and HCC samples, with a preliminary sensitivity of 85% at a specificity of 95% and with identification of early- and late-stage HCC (by Milan criteria; Figure 1D and Supplementary Figure 3). In comparison, recent work combining cell-free DNA and protein blood-based biomarkers had an accuracy of only 44% for predicting HCC, likely because of the lack of common recurrent mutations and specific protein markers inherent to HCC.13Cohen J.D. Li L. Wang Y. et al.Detection and localization of surgically resectable cancers with a multi-analyte blood test.Science. 2018; 359: 926-930Crossref PubMed Scopus (1333) Google Scholar Given these limitations, our CEC RNA approach would be complementary in the study of HCC. In this article, we report on the novel detection of cells from diseased livers circulating in the bloodstream by immunofluorescence and RNA-seq and the potential to use these cells as biomarkers. Important applications of this liquid biopsy might include CLD etiology determination, fibrosis staging, and HCC surveillance. Further study of CECs could open a new field of biomarker development leading to a spectrum of noninvasive diagnosis and monitoring techniques for patients with liver disease. All clinical studies were approved by the Dana-Farber Harvard Cancer Center (protocol 05-300) or Massachusetts General Hospital (2010P000220) institutional review board. Patients were consented and enrolled before blood draws. At enrollment, study investigators collected medical data from the patient’s electronic medical record with the patient’s permission. A maximum of 20 mL of blood was obtained from each patient at any given blood draw in 2 10-mL EDTA tubes, and approximately 8–15 mL of blood was processed per patient. Biotinylated primary antibodies against anti-human CD45 antibody (clone 2D1, BAM1430; R&D Systems, Minneapolis, MN) and anti-human CD66b antibody (80H3; Abd Serotec, Oxford, UK) were spiked into whole blood (5–10 mL total volume) at 100 and 37.5 fg/WBC, respectively, and incubated with rocking at room temperature for 20 minutes. Then, Dynabeads MyOne Strepavidin T1 (65602; Life Technologies, Carlsbad, CA) magnetic beads were added and incubated with rocking at room temperature for an additional 20 minutes. The total blood volume (5–10 mL) was run on the CTC-iChip as previously described.8Ozkumur E. Shah A.M. Ciciliano J.C. et al.Inertial focusing for tumor antigen-dependent and -independent sorting of rare circulating tumor cells.Sci Transl Med. 2013; 5: 179ra47Crossref PubMed Scopus (772) Google Scholar Cells in an aliquot of the iChip output were fixed with 2% paraformaldehyde for 10 minutes and then applied to glass slides by cytospin using a Shandon EZ Megafunnel (A78710001; ThermoFisher, Waltham, MA) at 2000 rpm for 5 minutes. Slides were washed with phosphate buffered saline (PBS) and blocked with 5% donkey serum plus 0.3% Triton-X in PBS for 1 hour at room temperature. Primary antibodies (each at 1:50 dilution in PBS, 0.1% bovine serum albumin, and 0.3% Triton-X) against wide-spectrum cytokeratin (ab9377; Abcam, Cambridge, MA), glypican-3 (ab81263; Abcam), and CD45 (555480; Becton Dickenson, Franklin, NJ) were added and incubated for 1 hour at room temperature. Secondary antibodies (each at 1:200 dilution in PBS, 0.1% bovine serum albumin, and 0.3% Triton-X) directed against each of the primary antibodies were used for fluorescent labeling and incubated for 1 hour at room temperature protected from light: cytokeratin and donkey anti-rabbit Alexa-647 (711-605-152; Jackson ImmunoResearch, West Grove, PA); glypican-3 and donkey anti-sheep Cy3 (713-165-003; Jackson ImmunoResearch); and CD45 and donkey anti-mouse Alexa-488 (715-545-150; Jackson ImmunoResearch). Cell nuclei were counterstained with 4′,6-diamidino-2-phenylindole (5 μg/mL in PBS; Life Technologies). Slides were mounted using ProLong Gold Antifade Reagent (Life Technologies). Stained cells were imaged by fluorescence microscopy (TiE or Eclipse 90i; Nikon, Tokyo, Japan) using the appropriate filter cubes for image acquisition and the BioView platform (BioView, Billerica, MA) for automated image analysis. All candidate CECs detected were reviewed and scored based on intact morphology, localization of CEC markers (wide-spectrum cytokeratin Alexa-647 and/or glypican-3 cyanine 3) with 4′,6-diamidino-2-phenylindole nuclear counterstain, and absence of leukocyte markers (CD45 Alexa-488). HepG2 cells were cultured according to culturing conditions recommended by the American Type Culture Collection (Manassas, VA). Individual cells were obtained by micropipette using a TransferMan NK2 micromanipulator (Eppendorf, Hamburg, Germany) and introduced into 4 mL of blood from healthy donors before processing through the iChip. An iChip product aliquot was pelleted and flash frozen in RNAlater (ThermoFisher Scientific) at −80°C. RNA was extracted (RNEasy Micro; Qiagen, Venlo, Netherlands) and processed as follows for RNA-seq. Amplified cDNA was generated from RNA from each sample using the SMARTer Ultra Low Input RNA Kit (version 3 or 4) for sequencing (Clontech Laboratories, Mountain View, CA) according to the manufacturer’s protocol. Briefly, 1 μL of a 1:50,000 dilution of ERCC RNA Spike-In Mix (Life Technologies) was added to each sample. First-strand synthesis of RNA molecules was performed using the poly-dT-based 3′-SMART CDS primer II A followed by extension and template switching by reverse transcriptase. The second-strand synthesis and amplification polymerase chain reaction (PCR) were run for 18 cycles, and the amplified cDNA was purified with a 1× Agencourt AMPure XP bead cleanup (Beckman Coulter, Brea, CA). The Nextera XT DNA Library Preparation kit (Illumina, San Diego, CA) was used for sample barcoding and fragmentation according to the manufacturer’s protocol. One nanogram of amplified cDNA was used for the enzymatic tagmentation followed by 12 cycles of amplification and unique dual-index barcoding of individual libraries. The PCR product was purified with a 1.8× Agencourt AMPure XP bead cleanup. The eluted cDNA libraries did not undergo the bead-based library normalization step in the Nextera XT protocol (Illumina). Library validation and quantification were performed by quantitative PCR using the KAPA SYBR FAST Universal qPCR Kit (Kapa Biosystems, Wilmington, MA). The individual libraries were pooled at equal concentrations, and the pool concentration was determined using the KAPA SYBR FAST Universal qPCR Kit. The pool of libraries was subsequently sequenced in 3 replicates on a HiSeq 2500 (Illumina) in Rapid Run Mode using a 2 × 100 base-pair kit and a dual-flow cell. The paired-end reads from the 3 sequencing runs were combined and aligned to the hg38 genome from http://genome.ucsc.edu using the STAR 2.4.0h (https://github.com/alexdobin/STAR/releases) aligner with default settings. Reads that did not map or mapped to multiple locations were discarded. Duplicate reads were marked using the MarkDuplicates tool in picard-tools-1.8.4 (https://github.com/Homebrew/homebrew-science/pull/870) and removed. The uniquely aligned reads were counted using htseq-count in the intersection-strict mode against the Homo_sapiens.GRCh38.79.gtf annotation table from http://www.ensembl.org. Then, the data were imported into the R statistical programming language (R Foundation, Vienna, Austria) for analysis. All RNA-seq raw data have been submitted to the National Center for Biotechnology Information Gene Expression Omnibus (accession GSE117623). For a subset of patients with HCC, the iChip product was divided into 2 equal aliquots: 1 aliquot was pelleted and flash frozen as described earlier and 1 was flow sorted to isolate subtypes of contaminating WBCs (monocytes, granulocytes, natural killer cells, cytotoxic T cells, helper T cells, and B cells). Cells were fixed with Cytofix (554655; BD Biosciences, San Jose, CA). The following antibodies were used: CD45 (IM0782U; Beckman Coulter), CD56 (IM2073U; Beckman Coulter), CD16 (360712; BioLegend, San Diego, CA), CD14 (301808; BioLegend), CD3 (317330; BioLegend), CD19 (302216; BioLegend), CD4 (300556; BioLegend), CD8 (301016; BioLegend), and CD66b (305112; BioLegend). As described earlier, flow-sorted cells were pelleted, flash frozen in RNAlater, and subjected to RNA-seq. The RNA-seq raw data consisted of read counts for 59,074 transcripts on 64 CLD and 52 HCC samples. Of those, only samples with more than 250,000 total reads were kept, leaving 44 CLD and 39 HCC samples. To narrow the list of features in our dataset to those with higher likelihood of relevance for predicting HCC status, RNA-seq expression data were obtained from The Cancer Genome Atlas Liver Cancer Project, which contains expression counts for normal liver and HCC tissue. A differential expression analysis was performed on this dataset to identify transcripts overexpressed in HCC vs normal liver tissue using DESeq2 1.16.1 (https://bioconductor.org/packages/release/bioc/html/DESeq2.html) with Benjamini-Hochberg correction for multiple hypothesis testing in R. Using this analysis combined with RNA-seq data of bulk WBCs, a list of transcripts with adjusted P value less than .05, log2-fold change greater than 2, less than 50 rpm in WBCs, and a mean expression in healthy liver tissue greater than 0.5 rpm was constructed. This list was used to narrow the 59,074 features in the raw dataset to a set of 248 transcripts more likely to be predictive of HCC. The final dataset used in all analyses consisted of log2(1 + RPM) for the 248 transcripts and 83 samples identified as described earlier. Ten iterations of 10-fold cross-validation were implemented to evaluate the performance of the classification algorithm, which is described step by step below:1.Feature selection. A 1-sided t-test with alternative hypothesis HA: μCLD < μHCC was conducted on the training set for each of the 248 transcripts identified by the The Cancer Genome Atlas differential expression analysis using R stats 3.4.2. Only those with P values less than .05 were retained.2.Random forest classifier. All transcripts kept from the feature selection step were used to train the random forest, which was built using randomForest 4.6-12 in R. The parameter mtry was left at its default value of sqrt(p), where p is the number of features in the dataset, and ntree = 500 trees were constructed. Sampling was stratified according to disease status. As a comparator classifier, a multivariable logistic regression model was created using the 10 most significant genes by P value from the feature selection step.3.Prediction. The proportion of trees in the random forest that voted for a classification of cancer for each sample in the test set was obtained from the random forest output and used to construct receiver operating characteristics curves with pROC 1.10.0 (R Foundation).Supplementary Figure 2Immunofluorescence of CECs in iChip-processed blood samples from healthy donors or patients with CLD, HCC, or treated HCC with no evidence of malignant disease. (A) Enumeration of cells positive for GPC3. (B) Enumeration of cells positive for wide-spectrum CK. (C) CEC concentration (CK or GPC3 positive) in patients with HBV-induced CLD (without HCC) stratified by fibrosis stage (with early stage defined as F1 or F2 and advanced fibrosis defined as F3 or F4). (D) CEC concentration in patients with CLD stratified by etiology of liver disease. P values were analyzed by Mann-Whitney test and were significant at a Bonferroni-adjusted significance level of .05 except 1c. AIH, autoimmune hepatitis; CK, cytokeratin; GPC3, glypican-3; HBV, hepatitis B virus; HCV, hepatitis C virus; HD, health donor; NASH, nonalcoholic steatohepatitis; NED, no evidence of disease; PSC, primary sclerosing cholangitis.View Large Image Figure ViewerDownload Hi-res image Download (PPT)Supplementary Figure 3(A) HCC score (vote fraction from RF classifier) in patients with CLD, patients with HCC who received treatment but still had active disease at time of blood draw, and patients with active HCC who were treatment naïve. P values were analyzed by Mann-Whitney test and were significant at a Bonferroni-adjusted significance level of .05. (B) Receiver operating characteristic curve for the HCC classifier created by multivariable logistic regression modeling. (C) Receiver operating characteristic curve for the HCC RF classifier. AUC, area under the receiver operating curve; No Tx, active disease and treatment-naïve; On Tx, received treatment but still had active disease at time of blood draw; RF, random forest.View Large Image Figure ViewerDownload Hi-res image Download (PPT)Supplementary Table 1Demographics and Results for Patients With Chronic Liver Disease Undergoing Surveillance for Hepatocellular CarcinomaSampleAgeSexDiagnosisAdvanced FibrosisAFP (ng/mL)CK+ (cells/mL)GPC3+ (cells/mL)CECaCECs are defined as cells expressing CK or GPC3 by immunofluorescence. (cells/mL)HCC ScorebHCC score is the vote fraction from the random forest classifier.CLD.00161FHCVyes2.70.010.110.10.39CLD.00264MHBVno—0.04.84.80.08CLD.00331FHBVno3.30.014.514.50.21CLD.00463Malcoholyes6.60.03.43.40.38CLD.00581FHBVyes1.90.05.05.00.40CLD.00653MHBVyes2.90.05.15.10.19CLD.00736FHBVno20.95.35.3—CLD.00864MHBVno1.90.90.90.90.37CLD.00959FHBVno30.83.23.2—CLD.01046Falcoholyes1.75.36.26.20.32CLD.01177MHBVno1.70.00.00.0—CLD.01285Falcoholyes1.40.08.98.9—CLD.01387FHCVyes8.10.92.62.60.14CLD.015_259MHBVno2.2———0.11CLD.01766MHCVyes4.40.01.61.6—CLD.01967Malcoholyes1.95.85.85.8—CLD.02040MHBVno2.50.50.50.5—CLD.02242MPSCyes3.35.30.05.30.27CLD.02372MHCVyes1.70.81.61.6—CLD.02477MHBVyes2.10.012.312.30.46CLD.02554Malcohol/NASHyes10.410.715.415.40.54CLD.02655Falcoholyes40.05.35.3—CLD.02750MHBVno4.60.03.73.7—CLD.02870MHBVno3.20.00.00.0—CLD.02938MPSCyes1.25.16.36.3—CLD.03059Fcryptogenicyes5.50.916.016.0—CLD.03128MHBVno2.30.00.00.0—CLD.03270MHCVyes3.20.00.60.60.33CLD.03354MHCVyes2.8———0.26CLD.03473FHBVyes2.81.83.63.60.46CLD.03760FHBVno3.30.00.00.0—CLD.03860FHBVno2.13.73.16.2—CLD.03954FHBVno3.50.00.00.00.80CLD.04039MHBVno40.00.00.00.22CLD.04151MHBVno4.80.00.00.0—CLD.04254MHBVno3.21.62.42.4—CLD.04365FNASHyes3.10.80.80.8—CLD.04457MNASHyes40.65.55.5—CLD.04568MHCV/NASHyes12.20.04.94.9—CLD.046_260MHBVyes3.2———0.35CLD.04866FHCVyes3.12.35.15.1—CLD.05050FAIHyes51.24.14.1—CLD.05537FHBVno1.4———0.30CLD.05647MHBVno4.4———0.25CLD.05744FHBVno1.6———0.09CLD.05831MHBVno1.7———0.18CLD.06061FAIHyes10.5———0.08CLD.06169FHCVyes3.2———0.04CLD.06242FHBVno4.8———0.05CLD.06554MHCVyes2.4———0.07CLD.07045FHBVno4.8———0.25CLD.07166MHBVno4.8———0.32CLD.07248FHBVno1.3———0.18CLD.07369FHCVyes4.6———0.20CLD.07744MHBVyes5.1———0.10CLD.07840MHCVno1.3———0.16CLD.07954MHBVno1.6———0.28CLD.08174MHBVno2———0.29CLD.08274MNASHyes1.9———0.47CLD.08360FHBVno4.4———0.25CLD.08469MHBVyes3.2———0.11CLD.08564MHBVyes2.6———0.20CLD.08764MHBVyes2.6———0.08CLD.08869MHCVyes4.4———0.09CLD.08943MHBVno6.6———0.13CLD.09069MHCVyes4.4———0.20CLD.09143MHBVno6.6———0.03AFP, α-fetoprotein; AIH, autoimmune hepatitis; CK, cytokeratin; F, female; GPC3, glypican-3; HBV, hepatitis B virus; HCV, hepatitis C virus; M, male; NASH, nonalcoholic steatohepatitis; PSC, primary sclerosing cholangitis.a CECs are defined as cells expressing CK or GPC3 by immunofluorescence.b HCC score is the vote fraction from the random forest classifier. Open table in a new tab Supplementary Table 2Demographics and Results for Patients With HCC and Active Disease (With or Without Treatment Before Blood Draw)SampleAgeSexRisk FactorCirrhosisAFP (ng/mL)TreatmentMilan CriteriaCK+ (cells/mL)GPC3+ (cells/mL)CECaCECs are defined as cells expressing CK or GPC3 by immunofluorescence. (cells/mL)HCC ScorebHCC Score is the vote fraction from the random forest classifier.HCC.00843Mhemochromatosisno9534RT, sorafenib, chemotherapy, checkpoint inhibitor, resectionno57103.5103.5—HCC.01174MNAno939.2ablation, resectionno2.418.418.40.47HCC.013_063FBudd-Chiari syndromeyes6.1noneyes31.190.490.4—HCC.01363FBudd-Chiari syndromeyes3.4ablation, RTyes———0.88HCC.01469FNASHyes218TACEyes0.70.70.70.13HCC.01570FPSCyes3.8noneyes3030.60HCC.01670MHBVno101.5thymalfasinyes000—HCC.01882MNASHno132367noneyes40.661.861.80.84HCC.01964Malcoholyes10.4noneno4445.155.4—HCC.019_264Malcoholyes21RT, sorafenibno———0.65HCC.02168MNASH, alcoholyes4891ablationno04.24.2—HCC.02568Malcoholyes4.3noneyes0.91.72.6—HCC.02685Mcryptogenicyes1.3noneyes015.415.4—HCC.02755MHBVno731.8noneno5.46.611.40.91HCC.02970MNASHyes4800ablationno15.223.634.20.83HCC.030_078MHBVyes151.6noneno399—HCC.03078MHBVyes26.9TACEyes———0.34HCC.031_063MHCVyes64.9ablation, TACE, transplantationNED1534.535.3—HCC.03471FNAno3.8noneno0.63.63.6—HCC.03582FNAno2043.5SIRT, RT, sorafenibno1.19.19.1—HCC.03754Malcoholyes5947ablation, SIRT, sorafenibno03.33.3—HCC.040_070MNAno2.2resectionno1.314.515.8—HCC.04070MNAno5.6RT, checkpoint inhibitor, resectionnoNANANA0.79HCC.04172Malcoholyes338RTno01.21.2—HCC.041_372Malcoholyes1092RT, sorafenibno———0.56HCC.04258MHCV, alcoholyes5.4noneno0.50.50.50.40HCC.04479FNAno19598noneno0.500.5—HCC.04666MHBVyes5.5ablationyes1.410.310.30.19HCC.04762Malcoholyes12.7ablationyes000—HCC.05076Malcoholyes5.4ablation, TACE, RTyes02.32.3—HCC.05223Mbiliary atresiayes1.5RTno02.52.5—HCC.05966MHCV, alcoholyes4847ablationno43.648.749.50.89HCC.06063FNASHyes13629noneno03.23.20.88HCC.06167FNAno60.6resectionno01.31.3—HCC.06263MNASHyes185.2TACEyes03.73.70.49HCC.06453MHCVyes1.6noneyes00.80.80.73HCC.06559MHBVno63.3noneyes0000.74HCC.06774FNAno2.5sorafenibno0.71.31.30.93HCC.06883MHBVyes4.7RTnoNANANA0.76HCC.06962MNASHyes20.8TACEyesNANANA0.69HCC.074_064MNASH, alcoholyes167580noneno000—HCC.07581MHBVyes7.7ablation, sorafenib, chemotherapy, checkpoint inhibitor, resectionno0110.74HCC.07679MHBVyes13322noneno01.51.5—HCC.07860MHBVno4.7ablation, resectionno2.22.22.20.77HCC.07971MNAno5.2noneno———0.78HCC.08262MHCV, alcoholyes5.9noneyes6.77.37.30.83HCC.08359MHCV, alcoholyes8.5TACE, SIRT, RT, sorafenibno2.12.12.10.85HCC.08481MNAno16.8sorafenibno000—HCC.08757Malcoholyes16.7ablation, TACEyes01.21.20.80HCC.09069Malcoholyes19960noneno4.75.35.30.97HCC.09172MHBVno3.2noneyes0000.90HCC.09377MNAno3.2RT, resectionno0000.85HCC.09470MNAno156.4SIRT, RTno466—HCC.09564MHCV, alcoholyes7.6TACEyes1.32.72.70.75HCC.09752FNAno1.3ablation, chemotherapy, transplantation, resection, everolimus/leuprolide, sitravatinibno06.46.40.67HCC.09866Malcoholyes356noneno0000.75HCC.09958Malcoholyes254.9TACEyes1.51.51.50.56HCC.10178MNASHyesNAnoneyes1.22.52.50.54HCC.10261Malcohol, hemochromatosisyes9.6noneyes05.65.60.88HCC.10368MA1ATyes286.8ablationyes02.72.70.64HCC.10474MNAno15.4noneno3.26.46.40.30HCC.10556MHCVyes3.7noneno1.61.61.60.79AFP, α-fetoprotein; A1AT, α1-antitrypsin deficiency; CK, cytokeratin; F, female; GPC3, glypican-3; HBV, hepatitis B virus; HCV, hepatitis C virus; M, male; NA, not available; NASH, nonalcoholic steatohepatitis; NED, no evidence of disease; PSC, primary sclerosing cholangitis; RT, radiotherapy (external); SIRT, selective internal radiation therapy; TACE, transarterial chemoembolization.a CECs are defined as cells expressing CK or GPC3 by immunofluorescence.b HCC Score is the vote fraction from the random forest classifier. Open table in a new tab Supplementary Table 3Demographics and Results for Patients With HCC and No Evidence of Disease After TreatmentSampleAgeSexRisk FactorCirrhosisAFP (ng/mL)TreatmentCK+ (cells/mL)GPC3+ (cells/mL)CECaCECs are defined as cells expressing CK or GPC3 by immunofluorescence. (cells/mL)HCC.033_085Mhemochromatosisno1.3TACE2.03.33.3HCC.05168MNASHyes2.5ablation, TACE, transplantation0.910.410.4HCC.05363MHCV, alcoholyes2.3resection0.06.46.4HCC.05551Malcoholyes2.6ablation, transplantation2.45.68.0HCC.058_254MHBVyes3.6resection0.00.00.0HCC.06368MHBVyes22.3TACE8.09.89.8HCC.07777MBudd-Chiari syndromeno16.7ablation8.09.89.8HCC.08571MNASHyes7.4TACE1.24.94.9HCC.08675MHBVyes2.9ablation0.51.11.1HCC.08881MHCVno1.6ablation1.55.15.1AFP, α-fetoprotein; CK, cytokeratin; F, female; GPC3, glypican-3; HBV, hepatitis B virus; HCV, hepatitis C virus; M, male; NASH, nonalcoholic steatohepatitis; TACE, transarterial chemoembolization.a CECs are defined as cells expressing CK or GPC3 by immunofluorescence. Open table in a new tab Supplementary Table 4Healthy Blood Donor DemographicsSampleSexAgeCK+ (cells/mL)GPC3+ (cells/mL)CEC (cells/mL)HD.01F2800.40.4HD.02M3400.40.4HD.03M4000.40.4HD.04M2902.42.4HD.05M23000HD.06M38000HD.07F2400.40.4HD.08F2600.40.4HD.09F351.201.2HD.10F27000CK, cytokeratin; F, female; GPC3, glypican-3; M, male. Open table in a new tab Supplementary Table 5Gene Signature for Blood-Based Biomarker to Diagnose HCCGeneWeightaGene weight is the mean decrease in Gini index, as a metric for the contribution of the gene to the classifier.Gene FunctionInvolvement in CancerPublicationTESC5.170functions as an integral cofactor in cell pH regulation by controlling plasma membrane-type Na+/H+ exchange activitymetastasis in colorectal cancerKang et al. Tumour Biol 2016;37:13843–13853OSBP24.203lipid binding proteincarcinogenesis by ERK pathwayDu et al. Semin Cell Dev Biol 81:149–153SLC6A83.937required for uptake of creatine in muscles and brainincreases survival of metastasesLoo et al. Cell 2015;160:393–406SEPT52.504cytokinesis and vesicle traffickingcarcinogenesisRussell and Hall. Br J Cancer 2005;93:499–503F2RL31.502protease-activated receptor involved in transmembrane signalingmethylation status associated with lung cancer risk and moralityZhang et al. Int J Cancer 2015;137:1739–1748E2F11.378cell cycle controlproliferationZhan et al. Cell Signal 2014;26:1075–1081EZH21.079regulates transcriptional repressionaltered transcriptional programmingKim and Roberts. Nat Med 2016;22:128–134CDC200.924cell cycle controlproliferationKidokoro et al. Oncogene 2008;27:1562–1571CCNA20.894cell cycle controlproliferationGao et al. PLoS One 2014;9:e91771CCNB10.876cell cycle controlproliferation, hepatocarcinogenesisPatil et al. Cancer Res 2009;69:253–261PLXNB30.766cell migrationunclearCDC60.754cell cycle controlcarcinogenesisYao and Mishra. Cancer Biol Ther 2009;8:1691–1698MYBL20.689cell cycle controlproliferation, survivalMusa et al. Cell Death Dis 2017;8:e2895APOBEC3B0.653cytidine deaminasemutagenesisKuong and Loeb. Nat Genet 2013;45:964–965SPP10.648ECM protein important for tissue remodeling; also acts as cytokineinvolved with metastasisSangaletti et al. Cancer Res 2014;74:4706–4719AKR1B100.639aldo-keto reductasemediates liver cancer cell proliferationJin et al. Sci Rep 2016;6:22746TOP2A0.606topoisomerasecarcinogenesisWong et al. Int J Cancer 2009;124:644–652ASPM0.600mitotic spindle regulationmarker of invasiveness in HCCLin et al. Clin Cancer Res 2008;14:4814–4820SLC6A90.579sodium-dependent reuptake of glycineunclearRECQL40.554human DNA helicases involved in genomic instabilityup-regulation, poor prognosis in HCCLi et al. Oncol Lett 2017;14:4751–4757NUSAP10.554spindle microtubule organizationinvolved with invasion and metastasisGordon C, et al. Oncotarget 2017;8:29935–29950PLVAP0.540involved in the formation of stomatal and fenestrel diaphragms of caveolaeinduced in endothelium of cancers with enhanced metastasis and angiogenesisCarson-Walter et al. Clin Cancer Res 2005;11:7643–7650FMO10.523oxidative metabolism of xenobioticsunclearPDZK1IP10.520intracellular protein traffickingregulation of immune microenvironmentGarcia-Heredia and Carnero. Oncotarget 2017;8:98580–98597FBXO320.510substrate recognition for ubiquitinationunclearECM, extracellular matrix; ERK, extracellular signal–regulated kinasea Gene weight is the mean decrease in Gini index, as a metric for the contribution of the gene to the classifier. Open table in a new tab AFP, α-fetoprotein; AIH, autoimmune hepatitis; CK, cytokeratin; F, female; GPC3, glypican-3; HBV, hepatitis B virus; HCV, hepatitis C virus; M, male; NASH, nonalcoholic steatohepatitis; PSC, primary sclerosing cholangitis. AFP, α-fetoprotein; A1AT, α1-antitrypsin deficiency; CK, cytokeratin; F, female; GPC3, glypican-3; HBV, hepatitis B virus; HCV, hepatitis C virus; M, male; NA, not available; NASH, nonalcoholic steatohepatitis; NED, no evidence of disease; PSC, primary sclerosing cholangitis; RT, radiotherapy (external); SIRT, selective internal radiation therapy; TACE, transarterial chemoembolization. AFP, α-fetoprotein; CK, cytokeratin; F, female; GPC3, glypican-3; HBV, hepatitis B virus; HCV, hepatitis C virus; M, male; NASH, nonalcoholic steatohepatitis; TACE, transarterial chemoembolization. CK, cytokeratin; F, female; GPC3, glypican-3; M, male. ECM, extracellular matrix; ERK, extracellular signal–regulated kinase Circulating Epithelial Cells in Patients With Liver DiseaseGastroenterologyVol. 156Issue 6PreviewWe read with great interest the article by Bhan et al,1 who reported a new liquid biopsy method to monitor chronic liver disease (CLD) and hepatocellular carcinoma (HCC). In their study, circulating epithelial cells (CECs) were detected by a cell sorting device called iChip, then enumerated by the immunofluorescent staining, and finally determined by RNA sequencing. This platform provided a high sensitivity and specificity in detecting CECs in patients with CLD or HCC and could discriminate HCC from CLD. Full-Text PDF Reply to “Detection and Analysis of Circulating Epithelial Cells in Liquid Biopsies from Patients with Liver Disease”: Implications for Transplant ChimerismGastroenterologyVol. 156Issue 6PreviewWe read the article by Bhan et al1 with great interest. To our best knowledge, the authors provide the first direct proof of circulating epithelial cells (CEC) with a hepatocellular-like genotype and phenotype other than cells from circulating tumor (stem) cells.2 More interestingly, they show that the levels of these liver-derived CECs correlated with the extent of liver fibrosis, in as many as 80% of the cases in severely injured livers, while almost no CECs were detected in healthy controls (only 5%). Full-Text PDF

n amendment to this paper has been published and can be accessed via a link at the top of the paper.

BMP4/7-dependent expression of inhibitor of differentiation/DNA binding (Id) proteins 1 and 3 has been implicated in tumor progression and poor prognosis of malignant melanoma patients. Hyaluronic acid (HA), a pericellular matrix component, supports BMP7 signalling in murine chondrocytes through its receptor CD44. However, its role in regulating BMP signalling in melanoma is not clear. In this study we found that depletion of endogenously-produced HA by hyaluronidase treatment or by inhibition of HA synthesis by 4-methylumbelliferone (4-MU) resulted in reduced BMP4/7-dependent Id1/3 protein expression in mouse melanoma B16-F10 and Ret cells. Conversely, exogenous HA treatment increased BMP4/7-dependent Id1/3 protein expression. Knockdown of CD44 reduced BMP4/7-dependent Id1/3 protein expression, and attenuated the ability of exogenous HA to stimulate Id1 and Id3 expression in response to BMP. Co-IP experiments demonstrated that CD44 can physically associate with the BMP type II receptor (BMPR) ACVR2B. Importantly, we found that coordinate expression of Id1 or Id3 with HA synthases HAS2, HAS3, and CD44 is associated with reduced overall survival of cutaneous melanoma patients. Our results suggest that HA-CD44 interactions with BMPR promote BMP4/7-dependent Id1/3 protein expression in melanoma, contributing to reduced survival in melanoma patients.

Understanding the malleability of gender norms is crucial to address gender inequalities. We study the effect of parenting daughters on a gender role attitude relating to the traditional male breadwinner model: whether the husband should earn and the wife stay at home. We control for other covariates that capture alternative explanations for gender role perceptions. Our results suggest evidence of a positive effect of parenting daughters on acceptance of less traditional gender roles. The effect is only robust among fathers and driven by parenting school age rather than younger daughters, which is consistent with a social identity explanation. Results suggest that parenting daughters of school age (as opposed to parenting only sons) increases the probability to disagree with the statement that 'husband should earn and wife stay at home' by over 5 percentage points. We conclude that gender role attitudes can be shaped by events that occur later in life.

Single-cell technologies have described heterogeneity across tissues, but the spatial distribution and forces that drive single-cell phenotypes have not been well defined. Combining single-cell RNA and protein analytics in studying the role of stromal cancer-associated fibroblasts (CAFs) in modulating heterogeneity in pancreatic cancer (pancreatic ductal adenocarcinoma [PDAC]) model systems, we have identified significant single-cell population shifts toward invasive epithelial-to-mesenchymal transition (EMT) and proliferative (PRO) phenotypes linked with mitogen-activated protein kinase (MAPK) and signal transducer and activator of transcription 3 (STAT3) signaling. Using high-content digital imaging of RNA in situ hybridization in 195 PDAC tumors, we quantified these EMT and PRO subpopulations in 319,626 individual cancer cells that can be classified within the context of distinct tumor gland "units." Tumor gland typing provided an additional layer of intratumoral heterogeneity that was associated with differences in stromal abundance and clinical outcomes. This demonstrates the impact of the stroma in shaping tumor architecture by altering inherent patterns of tumor glands in human PDAC.