Pathologist workload, burnout, and wellness: connecting the dots.

No standard tool to measure pathologist workload currently exists. An accurate measure of workload is needed for determining the number of pathologists to be hired, distributing the workload fairly among pathologists, and assessing the overall cost of pathology consults. Initially, simple tools such as counting cases or slides were used to give an estimate of the workload. More recently, multiple workload models, including relative value units (RVUs), the Royal College of Pathologists (RCP) point system, Level 4 Equivalent (L4E), Work2Quality (W2Q), and the University of Washington, Seattle (UW) slide count method, have been developed. There is no "ideal" model that is universally accepted. The main differences among the models come from the weights assigned to different specimen types, differential calculations for organs, and the capture of additional tasks needed for safe and timely patient care. Academic centers tend to see more complex cases that require extensive sampling and additional testing, while community-based and private laboratories deal more with biopsies. Additionally, some systems do not account for teaching, participation in multidisciplinary rounds, quality assurance activities, and medical oversight. A successful workload model needs to be continually updated to reflect the current state of practice.Awareness about physician burnout has gained attention in recent years and has been added to the World Health Organization's International Classification of Diseases (World Health Organization, WHO) as an occupational phenomenon. However, the extent to which this affects pathologists is not well understood. According to the WHO, burnout syndrome is diagnosed by the presence of three components: emotional exhaustion, depersonalization from one's work (cynicism related to one's job), and a low sense of personal achievement or accomplishment. Three drivers of burnout are the demand for productivity, lack of recognition, and electronic health records. Prominent consequences of physician burnout are economic and personal costs to the public and to the providers.Wellness is physical and mental well-being that allows individuals to manage stress effectively and to thrive in both their professional and personal lives. To achieve wellness, it is necessary to understand the root causes of burnout, including over-work and working under stressful conditions. Wellness is more than the absence of stress or burnout, and the responsibility of wellness should be shared by pathologists themselves, their healthcare organization, and governing bodies. Each pathologist needs to take their own path to achieve wellness.

Glial fibrillary acidic protein, neurofilament light, matrix metalloprotease 3 and fatty acid binding protein 4 as non-invasive brain tumor biomarkers.

BACKGROUND: Gliomas are aggressive malignant tumors, with poor prognosis. There is an unmet need for the discovery of new, non-invasive biomarkers for differential diagnosis, prognosis, and management of brain tumors. Our objective is to validate four plasma biomarkers - glial fibrillary acidic protein (GFAP), neurofilament light (NEFL), matrix metalloprotease 3 (MMP3) and fatty acid binding protein 4 (FABP4) - and compare them with established brain tumor molecular markers and survival. METHODS: Our cohort consisted of patients with benign and malignant brain tumors (GBM = 77, Astrocytomas = 26, Oligodendrogliomas = 23, Secondary tumors = 35, Meningiomas = 70, Schwannomas = 15, Pituitary adenomas = 15, Normal individuals = 30). For measurements, we used ultrasensitive electrochemiluminescence multiplexed immunoassays. RESULTS: High plasma GFAP concentration was associated with GBM, low GFAP and high FABP4 were associated with meningiomas, and low GFAP and low FABP4 were associated with astrocytomas and oligodendrogliomas. NEFL was associated with progression of disease. Several prognostic genetic alterations were significantly associated with all plasma biomarker levels. We found no independent associations between plasma GFAP, NEFL, FABP4 and MMP3, and overall survival. The candidate biomarkers could not reliably discriminate GBM from primary or secondary CNS lymphomas. CONCLUSIONS: GFAP, NEFL, FABP4 and MMP3 are useful for differential diagnosis and prognosis, and are associated with molecular changes in gliomas.

Transforming diagnostics: The implementation of digital pathology in clinical laboratories.

Digital pathology (DP) has emerged as a cutting-edge technology that promises to revolutionise diagnostics in clinical laboratories. This perspective article explores the implementation planning and considerations of DP in a single multicentre institution in Canada, the University Health Network, discussing benefits, challenges, potential implications and considerations for future adopters. We examine the transition from traditional microscopy to digital slide scanning and its impact on pathology practice, patient care and medical research. Furthermore, we address the regulatory, infrastructure and change management considerations for successful integration into clinical laboratories. By highlighting the advantages and addressing concerns, we aim to shed light on the transformative potential of DP and its role in shaping the future of diagnostics.

Computational pathology: an evolving concept.

The initial enthusiasm about computational pathology (CP) and artificial intelligence (AI) was that they will replace pathologists entirely on the way to fully automated diagnostics. It is becoming clear that currently this is not the immediate model to pursue. On top of the legal and regulatory complexities surrounding its implementation, the majority of tested machine learning (ML)-based predictive algorithms do not display the exquisite performance needed to render them unequivocal, standalone decision makers for matters with direct implications to human health. We are thus moving into a different model of "computer-assisted diagnostics", where AI is there to provide support, rather than replacing, the pathologist. Herein we focus on the practical aspects of CP, from a pathologist perspective. There is a wide range of potential applications where CP can enhance precision of pathology diagnosis, tailor prognostic and predictive information, as well as save time. There are, however, a number of potential limitations for CP that currently hinder their wider adoption in the clinical setting. We address the key necessary steps towards clinical implementation of computational pathology, discuss the significant obstacles that hinders its adoption in the clinical context and summarize some proposed solutions. We conclude that the advancement of CP in the clinic is a promising resource-intensive endeavour that requires broad and inclusive collaborations between academia, industry, and regulatory bodies.

ABCC2 brush-border expression predicts outcome in papillary renal cell carcinoma: a multi-institutional study of 254 cases.

AIMS: Papillary renal cell carcinoma (PRCC) histologic subtyping is no longer recommended in the 2022 WHO classification. Currently, WHO/ISUP nucleolar grade is the only accepted prognostic histologic parameter for PRCC. ABCC2, a renal drug transporter, has been shown to significantly predict outcomes in PRCC. In this study we evaluated the prognostic significance of ABCC2 IHC staining patterns in a large, multi-institutional PRCC cohort and assessed the association of these patterns with ABCC2 mRNA expression. METHODS AND RESULTS: We assessed 254 PRCCs for ABCC2 IHC reactivity patterns that were stratified into negative, cytoplasmic, brush-border <50%, and brush-border ≥50%. RNA in situ hybridization (ISH) was used to determine the transcript level of each group. Survival analysis was performed with SPSS and GraphPad software. RNA-ISH showed that the ABCC2 group with any brush-border staining was associated with a significant increase in the transcript level, when compared to the negative/cytoplasmic group (P = 0.034). Both ABCC2 groups with brush-border <50% (P = 0.024) and brush-border ≥50% (P < 0.001) were also associated with worse disease-free survival (DFS) in univariate analysis. Multivariate analysis showed that only ABCC2 IHC brush-border (<50% and ≥50%) reactivity groups (P = 0.037 and P = 0.003, respectively), and high-stage disease (P < 0.001) had a DFS of prognostic significance. In addition, ABCC2 brush-border showed significantly worse DFS in pT1a (P = 0.014), pT1 (P = 0.013), ≤4 cm tumour (P = 0.041) and high stage (P = 0.014) groups, while a similar analysis with high WHO/ISUP grade in these groups was not significant. CONCLUSION: ABCC2 IHC brush-border expression in PRCC correlates with significantly higher gene expression and also independently predicts survival outcomes.

Disruptive innovations in the clinical laboratory: catching the wave of precision diagnostics.

Disruptive innovation is an invention that disrupts an existing market and creates a new one by providing a different set of values, which ultimately overtakes the existing market. Typically, when disruptive innovations are introduced, their performance is initially less than existing standard technologies, but because of their ability to bring the cost down, and with gradual improvement, they end up replacing established service standards.Disruptive technologies have their fingerprints in health care. Pathology and laboratory medicine are fertile soils for disruptive innovations because they are heavily reliant on technology. Disruptive innovations have resulted in a revolution of our diagnostic ability and will take laboratory medicine to the next level of patient care. There are several examples of disruptive innovations in the clinical laboratory. Digitizing pathology practice is an example of disruptive technology, with many advantages and an extended scope of applications. Next-generation sequencing can be disruptive in two ways. The first is by replacing an array of laboratory tests, which each requires expensive and specialized instruments and expertise, with a single cost-effective technology. The second is by disrupting the current paradigm of the clinical laboratory as a diagnostic service by taking it into a new era of preventive or primary care pathology. Other disruptive innovations include the use of dry chemistry reagents in chemistry analyzers and also point of care testing. The use of artificial intelligence is another promising disruptive innovation that can transform the future of pathology and laboratory medicine. Another emerging disruptive concept is the integration of two fields of medicine to create an interrelated discipline such as "histogenomics and radiohistomics." Another recent disruptive innovation in laboratory medicine is the use of social media in clinical practice, education, and publication.There are multiple reasons to encourage disruptive innovations in the clinical laboratory, including the escalating cost of health care, the need for better accessibility of diagnostic care, and the increased demand on the laboratory in the era of precision diagnostics. There are, however, a number of challenges that need to be overcome such as the significant resistance to disruptive innovations by current technology providers and governmental regulatory bodies. The hesitance from health care providers and insurance companies must also be addressed.Adoption of disruptive innovations requires a multifaceted approach that involves orchestrated solutions to key aspects of the process, including creating successful business models, multidisciplinary collaborations, and innovative accreditation and regulatory oversight. It also must be coupled with successful commercialization plans and modernization of health care structure. Fostering a culture of disruptive innovation requires establishing unique collaborative models between academia and industry. It also requires uncovering new sources of unconventional funding that are open to high-risk high-reward projects. It should also be matched with innovative thinking, including new approaches for delivery of care and identifying novel cohorts of patients who can benefit from disruptive technology.

Percutaneous deep vein arterialization: An emerging technique for no-option chronic limb-threatening ischemia patients.

Chronic limb-threatening ischemia (CLTI), with characteristic ischemic rest pain, non-healing ulcers, or gangrene attributable to arterial occlusive disease, requires successful revascularization to minimize tissue loss. End-stage CLTI in particular, with occlusion of the pedal arteries, results in a lack of suitable targets for bypass and can result in failure of endovascular revascularization procedures, leaving no option for treatment other than amputation. With limb salvage as the primary goal, nontraditional revascularization techniques such as percutaneous deep vein arterialization (pDVA) may help minimize incidence of amputation. We present a case of a patient with no-option CLTI, at high risk of amputation who failed conventional endovascular revascularization attempts facing imminent major amputation. The limb was salvaged with a successful pDVA procedure.

Searching for prognostic biomarkers for small renal masses in the urinary proteome.

Renal cell carcinoma (RCC) is frequently diagnosed incidentally as an early-stage small renal mass (SRM; pT1a, ≤4 cm). Overtreatment of patients with benign or clinically indolent SRMs is increasingly common and has resulted in a recent shift in treatment recommendations. There are currently no available biomarkers that can accurately predict clinical behavior. Therefore, we set out to identify early biomarkers of RCC progression. We employed a quantitative label-free liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) proteomics approach and targeted parallel-reaction monitoring to identify and validate early, noninvasive urinary biomarkers for RCC-SRMs. In total, we evaluated 115 urine samples, including 33 renal oncocytoma (≤4 cm) cases, 30 progressive and 26 nonprogressive clear cell RCC (ccRCC)-SRM cases, in addition to 26 healthy controls. We identified six proteins, which displayed significantly elevated expression in clear cell RCC-SRMs (ccRCC-SRMs) relative to healthy controls. Proteins C12ORF49 and EHD4 showed significantly elevated expression in ccRCC-SRMs compared to renal oncocytoma (≤4 cm). Additionally, proteins EPS8L2, CHMP2A, PDCD6IP, CNDP2 and CEACAM1 displayed significantly elevated expression in progressive relative to nonprogressive ccRCC-SRMs. A two-protein signature (EPS8L2 and CCT6A) showed significant discriminatory ability (areas under the curve: 0.81, 95% CI: 0.70-0.93) in distinguishing progressive from nonprogressive ccRCC-SRMs. Patients (Stage I-IV) with EPS8L2 and CCT6A mRNA alterations showed significantly shorter overall survival (p = 1.407 × 10-6 ) compared to patients with no alterations. Our in-depth proteomic analysis identified novel biomarkers for early-stage RCC-SRMs. Pretreatment characterization of urinary proteins may provide insight into early RCC progression and could potentially help assign patients to appropriate management strategies.

Necessity and Challenges of Sample Preconcentration in Analysis of Multiple MicroRNAs by Capillary Electrophoresis.

Thousands of putative microRNA (miRNA)-based cancer biomarkers have been reported, but none has been validated for approval by the Food and Drug Administration. One of the reasons for this alarming discrepancy is the lack of a method that is sufficiently robust for carrying out validation studies, which may require analysis of samples from hundreds of patients across multiple institutions and pooling the results together. The capillary electrophoresis (CE)-based hybridization assay proved to be more robust than reversed transcription polymerase chain reaction (the current standard), but its limit of quantification (LOQ) exceeds 10 pM while miRNA concentrations in cell lysates are below 1 pM. Thus, CE-based separation must be preceded by on-column sample preconcentration. Here, we explain the challenges of sample preconcentration for CE-based miRNA analyses and introduce a preconcentration method that can suit CE-based miRNA analysis utilizing peptide nucleic acid (PNA) hybridization probes. The method combines field-amplified sample stacking (FASS) with isotachophoresis (ITP). We proved that FASS-ITP could retain and concentrate both near-neutral PNA with highly negatively charged PNA-miRNA hybrids. We demonstrated that preconcentration by FASS-ITP could be combined with the CE-based separation of the unreacted PNA probes from the PNA-miRNA hybrids and facilitate improvement in LOQ by a factor of 140, down to 0.1 pM. Finally, we applied FASS-ITP-CE for the simultaneous detection of two miRNAs in crude cell lysates and proved that the method was robust when used in complex biological matrices. The 140-fold improvement in LOQ and the robustness to biological matrices will significantly expand the applicability of CE-based miRNA analysis, bringing it closer to becoming a practical tool for validation of miRNA biomarkers.

Identification of Prognostic Biomarkers in the Urinary Peptidome of the Small Renal Mass.

Renal cell carcinoma (RCC) is often diagnosed incidentally as a small renal mass (SRM; pT1a, ≤4 cm). Increasing concerns surrounding the overtreatment of patients with benign or clinically silent SRMs has resulted in a recent shift in treatment recommendations, especially in elderly and infirm patients. There are currently no biomarkers that can predict progression. We used a quantitative label-free liquid chromatography-tandem mass spectrometry peptidomics approach and targeted parallel-reaction monitoring to identify early, noninvasive diagnostic and prognostic biomarkers for early-stage RCC-SRMs. In total, 115 urine samples, including 33 renal oncocytoma (≤4 cm) cases, 30 progressive and 26 nonprogressive clear cell RCC-SRM cases, and 26 healthy controls were evaluated. Nine endogenous peptides that displayed significantly elevated expression in clear cell RCC-SRMs relative to healthy controls were identified. Peptides NVINGGSHAGNKLAMQEF, VNVDEVGGEALGRL, and VVAGVANALAHKYH showed significantly elevated expression in clear cell RCC-SRMs relative to renal oncocytoma. Additionally, peptides SHTSDSDVPSGVTEVVVKL and IVDNNILFLGKVNRP displayed significantly elevated expression in progressive relative to nonprogressive clear cell RCC-SRMs. Peptide SHTSDSDVPSGVTEVVVKL showed the most significant discriminatory utility (area under the curve, 0.76; 95% CI, 0.62-0.90; P = 0.0027). Patients with elevated SHTSDSDVPSGVTEVVVKL expression had significantly shorter overall survival (hazard ratio, 4.13; 95% CI, 1.09-15.65; P = 0.024) compared to patients with low expression. Pretreatment characterization of urinary peptides can provide insight into early RCC progression and may aid clinical decision-making and improve disease management.

Integrated Molecular Analysis of Papillary Renal Cell Carcinoma and Precursor Lesions Unfolds Evolutionary Process from Kidney Progenitor-Like Cells.

Papillary renal cell carcinoma (PRCC) is the most common type of RCC in end-stage kidney disease (ESKD). Papillary adenoma (PA) is a small benign lesion morphologically similar to PRCC and is suggested to be its precursor. PA is also prevalent in ESKD. The evolution of PAs to PRCCs and their relationship to ESKD are poorly understood. A total of 140 PAs, normal kidneys, ESKDs, and PRCCs were analyzed. Previously described markers of renal tubular progenitor cells were analyzed using immunohistochemistry and quantified with digital analysis. Progenitor cells were significantly increased in ESKD (P < 0.0001) and PAs (P = 0.02) in comparison with the normal kidney. Pathway analysis using global miRNA and chromosomal copy number variations revealed a common developmental theme between PA and the PRCCs. Whole exome sequencing showed a KMT2C-specific pathogenic mutation among all PAs and PRCCs. KMT2C is a chromosome 7 epigenetic regulator implicated in development and oncogenesis. Collectively, results show possible connection of PRCCs to PA and the progenitor-like cell population, which are increased in response to renal tubular injury. In addition, each PRCC histologic subtype had its own set of mutational changes, indicating divergence from a common precursor. The study reports previously unknown biological aspects of PRCC development and could influence current surveillance criteria and early detection strategies of PRCC tumors.

Cancer and platelet crosstalk: opportunities and challenges for aspirin and other antiplatelet agents.

Platelets have long been recognized as key players in hemostasis and thrombosis; however, growing evidence suggests that they are also significantly involved in cancer, the second leading cause of mortality worldwide. Preclinical and clinical studies showed that tumorigenesis and metastasis can be promoted by platelets through a wide variety of crosstalk between platelets and cancer cells. For example, cancer changes platelet behavior by directly inducing tumor-platelet aggregates, triggering platelet granule and extracellular vesicle release, altering platelet phenotype and platelet RNA profiles, and enhancing thrombopoiesis. Reciprocally, platelets reinforce tumor growth with proliferation signals, antiapoptotic effect, and angiogenic factors. Platelets also activate tumor invasion and sustain metastasis via inducing an invasive epithelial-mesenchymal transition phenotype of tumor cells, promoting tumor survival in circulation, tumor arrest at the endothelium, and extravasation. Furthermore, platelets assist tumors in evading immune destruction. Hence, cancer cells and platelets maintain a complex, bidirectional communication. Recently, aspirin (acetylsalicylic acid) has been recognized as a promising cancer-preventive agent. It is recommended at daily low dose by the US Preventive Services Task Force for primary prevention of colorectal cancer. The exact mechanisms of action of aspirin in chemoprevention are not very clear, but evidence has emerged that suggests a platelet-mediated effect. In this article, we will introduce how cancer changes platelets to be more cancer-friendly and highlight advances in the modes of action for aspirin in cancer prevention. We also discuss the opportunities, challenges, and opposing viewpoints on applying aspirin and other antiplatelet agents for cancer prevention and treatment.

Sunitinib induces early histomolecular changes in a subset of renal cancer cells that contribute to resistance.

Sunitinib is the standard-of-care, first-line treatment for advanced renal cell carcinoma (RCC). Characteristics of treatment-resistant RCC have been described; however, complex tumor adaptation mechanisms obstruct the identification of significant operators in resistance. We hypothesized that resistance is a late manifestation of early, treatment-induced histomolecular alterations; therefore, studying early drug response may identify drivers of resistance. We describe an epithelioid RCC growth pattern in RCC xenografts, which emerges in sunitinib-sensitive tumors and is augmented during resistance. This growth modality is molecularly and morphologically related to the RCC spheroids that advance during in vitro treatment. Based on time-lapse microscopy, mRNA and microRNA screening, and tumor behavior-related characteristics, we propose that the spheroid and adherent RCC growth patterns differentially respond to sunitinib. Gene expression analysis indicated that sunitinib promoted spheroid formation, which provided a selective survival advantage under treatment. Functional studies confirm that E-cadherin is a key contributor to the survival of RCC cells under sunitinib treatment. In summary, we suggest that sunitinib-resistant RCC cells exist in treatment-sensitive tumors and are histologically identifiable.-Lichner, Z., Saleeb, R., Butz, H., Ding, Q., Nofech-Mozes, R., Riad, S., Farag, M., Varkouhi, A. K., dos Santos, C. C., Kapus, A., Yousef, G. M. Sunitinib induces early histomolecular changes in a subset of renal cancer cells that contribute to resistance.

miR-146a-5p mediates epithelial-mesenchymal transition of oesophageal squamous cell carcinoma via targeting Notch2.

This corrects the article DOI: 10.1038/bjc.2016.367.

Direct Quantitative Analysis of Multiple microRNAs (DQAMmiR) with Peptide Nucleic Acid Hybridization Probes.

Direct quantitative analysis of multiple miRNAs (DQAMmiR) is a hybridization-based assay, in which the excess of the DNA hybridization probes is separated from the miRNA-probe hybrids, and the hybrids are separated from each other in gel-free capillary electrophoresis (CE) using two types of mobility shifters: single-strand DNA binding protein (SSB) added to the CE running buffer and peptide drag tags conjugated with the probes. Here we introduce the second-generation DQAMmiR, which utilizes peptide nucleic acid (PNA) rather than DNA hybridization probes and requires no SSB in the CE running buffer. PNA probes are electrically neutral, while PNA-miRNA hybrids are negatively charged, and this difference in charge can be a basis for separation of the hybrids from the probes. In this proof-of-principle work, we first experimentally confirmed that the PNA-RNA hybrid was separable from the excess of the PNA probe without SSB in the running buffer, resulting in a near 10 min time window, which would allow, theoretically, separation of up to 30 hybrids. Then, we adapted to PNA-RNA hybrids our previously developed theoretical model for predicting hybrid mobilities. The calculation performed with the modified theoretical model indicated that PNA-RNA hybrids of slightly different lengths could be separated from each other without drag tags. Accordingly, we designed a simple experimental model capable of confirming: (i) separation of tag-free hybrids of different lengths and (ii) separation of same-length hybrids due to a drag tag on the PNA probe. The experimental model included three miRNAs: 20-nt miR-147a, 20-nt miR-378g, and 22-nt miR-21. The three complementary PNA probes had lengths matching those of the corresponding target miRNAs. The probe for miR-147a had a short five-amino-acid drag tag; the other two had no drag tags. We were able to achieve baseline separation of the three hybrids from each other. The LOQ of 14 pM along with the high accuracy (recovery >90%) and precision (RSD ≈ 10%) of the assay at picomolar target concentrations suggest that PNA-facilitated DQAMmiR could potentially support practical miRNA analysis of clinical samples.

The miRNA-kallikrein interaction: a mosaic of epigenetic regulation in cancer.

The kallikrein-related peptidases (KLKs) constitute a family of 15 highly conserved serine proteases with trypsin- and chymotrypsin-like activities. Dysregulated expression and/or aberrant activation of KLKs has been linked to various pathophysiological processes, including cancer. Many KLKs have been identified as potential cancer biomarkers. microRNAs (miRNAs) are a class of small non-coding RNAs that regulate gene expression by pairing to the 3' untranslated region (UTR) of complimentary mRNA targets. miRNAs are dysregulated in many cancers, including prostate, kidney and ovarian cancers. Several studies have shown that miRNAs are involved in the post-transcriptional regulation of KLKs. However, recent evidence suggests that miRNAs can also act as downstream effectors of KLKs. In this review, we provide an update on the epigenetic regulation of KLKs by miRNAs. We also present recent experimental evidence that supports the regulatory role of KLKs on miRNA networks. The potential diagnostic and therapeutic applications of miRNA-kallikrein interactions are also discussed.

Liquid biopsy: a step forward towards precision medicine in urologic malignancies.

There is a growing trend towards exploring the use of a minimally invasive "liquid biopsy" to identify biomarkers in a number of cancers, including urologic malignancies. Multiple aspects can be assessed in circulating cell-free DNA, including cell-free DNA levels, integrity, methylation and mutations. Other prospective liquid biopsy markers include circulating tumor cells, circulating RNAs (miRNA, lncRNAs and mRNAs), cell-free proteins, peptides and exosomes have also emerged as non-invasive cancer biomarkers. These circulating molecules can be detected in various biological fluids, including blood, urine, saliva and seminal plasma. Liquid biopsies hold great promise for personalized medicine due to their ability to provide multiple non-invasive global snapshots of the primary and metastatic tumors. Molecular profiling of circulating molecules has been a stepping-stone to the successful introduction of several non-invasive multi-marker tests into the clinic. In this review, we provide an overview of the current state of cell-free DNA-based kidney, prostate and bladder cancer biomarker research and discuss the potential utility other circulating molecules. We will also discuss the challenges and limitations facing non-invasive cancer biomarker discovery and the benefits of this growing area of translational research.

Accurate MicroRNA Analysis in Crude Cell Lysate by Capillary Electrophoresis-Based Hybridization Assay in Comparison with Quantitative Reverse Transcription-Polymerase Chain Reaction.

Accurate quantitation of microRNA (miRNA) in tissue samples is required for validation and clinical use of miRNA-based disease biomarkers. Since sample processing, such as RNA extraction, introduces undesirable biases, it is advantageous to measure miRNA in a crude cell lysate. Here, we report on accurate miRNA quantitation in crude cell lysate by a CE-based hybridization assay termed direct quantitative analysis of multiple miRNAs (DQAMmiR). Accuracy and precision of miRNA quantitation were determined for miRNA samples in a crude cell lysate, RNA extract from the lysate, and a pure buffer. The results showed that the measurements were matrix-independent with inaccuracies of below 13% from true values and relative standard deviations of below 11% from the mean values in a miRNA concentration range of 2 orders of magnitude. We compared DQAMmiR-derived results with those obtained by a benchmark miRNA-quantitation method-quantitative reverse transcription-polymerase chain reaction (qRT-PCR). qRT-PCR-based measurements revealed multifold inaccuracies and relative standard deviations of up to 70% in crude cell lysate. Robustness of DQAMmiR to changes in sample matrix makes it a perfect candidate for validation and clinical use of miRNA-based disease biomarkers.

An integrated proteomic and peptidomic assessment of the normal human urinome.

BACKGROUND: Urine represents an ideal source of clinically relevant biomarkers as it contains a large number of proteins and low molecular weight peptides. The comprehensive characterization of the normal urinary proteome and peptidome can serve as a reference for future biomarker discovery. Proteomic and peptidomic analysis of urine can also provide insight into normal physiology and disease pathology, especially for urogenital diseases. METHODS: We developed an integrated proteomic and peptidomic analytical protocol in normal urine. We employed ultrafiltration to separate protein and peptide fractions, which were analyzed separately using liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) on the Q-Exactive mass spectrometer. RESULTS: By analyzing six urines from healthy individuals with advanced age, we identified 1754 proteins by proteomic analysis and 4543 endogenous peptides, arising from 566 proteins by peptidomic analysis. Overall, we identified 2091 non-redundant proteins by this integrated approach. In silico protease activity analysis indicated that metalloproteases are predominantly involved in the generation of the endogenous peptide signature. In addition, a number of proteins that were detected in normal urine have previously been implicated in various urological malignancies, including bladder cancer and renal cell carcinoma (RCC). CONCLUSIONS: We utilized a highly sensitive proteomics approach that enabled us to identify one of the largest sets of protein identifications documented in normal human urine. The raw proteomics and peptidomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD003595.

miR-146a-5p mediates epithelial-mesenchymal transition of oesophageal squamous cell carcinoma via targeting Notch2.

BACKGROUND: Our previous study found that dysregulated microRNA-146a-5p (miR-146a-5p) is involved in oesophageal squamous cell cancer (ESCC) proliferation. This article aimed to evaluate its detailed mechanisms in ESCC epithelial-mesenchymal transition (EMT) progression. METHODS: Invasion assay, qRT-PCR and western blotting were used to validate the roles of miR-146a-5p and Notch2 in EMT progression. miRNA target gene prediction databases and dual-luciferase reporter assay were used to validate the target gene. RESULTS: miR-146a-5p inhibitor led to increase of invaded ESCC cells, while miR-146a-5p mimics inhibited invasion ability of ESCC cells. Protein level of E-cadherin decreased, whereas those of Snail and Vimentin increased in the anti-miR-146a-5p group, which demonstrated that miR-146a-5p inhibits EMT progression of ESCC cells. miRNA target gene prediction databases indicated the potential of Notch2 as a direct target gene of miR-146a-5p and dual-luciferase reporter assay validated it. Importantly, shRNA-Notch2 restrained EMT and partially abrogated the inhibiting effects of miR-146a-5p on EMT progression of ESCC cells. CONCLUSIONS: miR-146a-5p functions as a tumour-suppressive miRNA targeting Notch2 and inhibits the EMT progression of ESCC.