The International Classification of Diseases (ICD) hierarchical taxonomy is used for so-called clinical coding of medical reports, typically presented in unstructured text. In the Czech Republic, it is currently carried out manually by a so-called clinical coder. However, due to the human factor, this process is error-prone and expensive. The coder needs to be properly trained and spends significant effort on each report, leading to occasional mistakes. The main goal of this paper is to propose and implement a system that serves as an assistant to the coder and automatically predicts diagnosis codes. These predictions are then presented to the coder for approval or correction, aiming to enhance efficiency and accuracy. We consider two classification tasks: main (principal) diagnosis; and all diagnoses. Crucial requirements for the implementation include minimal memory consumption, generality, ease of portability, and sustainability. The main contribution lies in the proposal and evaluation of ICD classification models for the Czech language with relatively few training parameters, allowing swift utilisation on the prevalent computer systems within Czech hospitals and enabling easy retraining or fine-tuning with newly available data. First, we introduce a small transformer-based model for each task followed by the design of a transformer-based "Four-headed" model incorporating four distinct classification heads. This model achieves comparable, sometimes even better results, against four individual models. Moreover this novel model significantly economises memory usage and learning time. We also show that our models achieve comparable results against state-of-the-art English models on the Mimic IV dataset even though our models are significantly smaller.

• Keywords
• Coding, Diagnosis coding, ICD, Medical, Text classification,
• MeSH
• Electronic Health Records MeSH
• Clinical Coding * MeSH
• Humans MeSH
• International Classification of Diseases * MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Geographicals
• Czech Republic MeSH

PURPOSE: Renal cell carcinoma belongs among the deadliest malignancies despite great progress in therapy and accessibility of primary care. One of the main unmet medical needs remains the possibility of early diagnosis before the tumor dissemination and prediction of early relapse and disease progression after a successful nephrectomy. In our study, we aimed to identify novel diagnostic and prognostic biomarkers using next-generation sequencing on a novel cohort of RCC patients. METHODS: Global expression profiles have been obtained using next-generation sequencing of paired tumor and non-tumor tissue of 48 RCC patients. Twenty candidate lncRNA have been selected for further validation on an independent cohort of paired tumor and non-tumor tissue of 198 RCC patients. RESULTS: Sequencing data analysis showed significant dysregulation of more than 2800 lncRNAs. Out of 20 candidate lncRNAs selected for validation, we confirmed that 14 of them are statistically significantly dysregulated. In order to yield better discriminatory results, we combined several best performing lncRNAs into diagnostic and prognostic models. A diagnostic model consisting of AZGP1P1, CDKN2B-AS1, COL18A1, and RMST achieved AUC 0.9808, sensitivity 95.96%, and specificity 90.4%. The model for prediction of early relapse after nephrectomy consists of COLCA1, RMST, SNHG3, and ZNF667-AS1 and achieved AUC 0.9241 with sensitivity 93.75% and specificity 71.07%. Notably, no combination has outperformed COLCA1 alone. Lastly, a model for stage consists of ZNF667-AS1, PVT1, RMST, LINC00955, and TCL6 and achieves AUC 0.812, sensitivity 85.71%, and specificity 69.41%. CONCLUSION: In our work, we identified several lncRNAs as potential biomarkers and developed models for diagnosis and prognostication in relation to stage and early relapse after nephrectomy.

• Keywords
• Biomarker, Diagnosis, Early relapse, Long non-coding RNA, Next-generation sequencing, Prognosis,
• MeSH
• Carcinoma, Renal Cell * diagnosis   genetics   surgery   MeSH
• Humans MeSH
• Neoplasm Recurrence, Local diagnosis   genetics   surgery   MeSH
• Biomarkers, Tumor genetics   MeSH
• Kidney Neoplasms * diagnosis   genetics   surgery   MeSH
• Nephrectomy MeSH
• Gene Expression Regulation, Neoplastic MeSH
• RNA, Long Noncoding * genetics   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• Biomarkers, Tumor MeSH
• RNA, Long Noncoding * MeSH

BACKGROUND: To provide an overview of the importance of long non-coding RNAs (lncRNAs) in the pathogenesis of renal cell carcinoma and their utility as bio-markers for dia-gnosis, prognosis and prediction of treatment response. MATERIALS AND METHODS: A literature search in the Pubmed and Web of Science databases using the keywords variations of “long non-coding RNA” (“lncRNA”, “long noncoding RNA”, “long non-coding RNA”) and “renal cell carcinoma” (“renal cancer”, “renal cell carcinoma”, “kidney cancer”) was performed. The results related to the pathogenesis, dia-gnosis, prognosis and use as therapeutic targets were separated. RESULTS: Long non-coding RNAs regulate gene expression at different levels. They act both as oncogenes and tumor suppressors. The mechanism of their action has not been fully elucidated, but they are actively involved in the regulation of hypoxia inducible factors pathway, epithelial-mesenchymal transition, cell proliferation, cell cycle regulation, apoptosis, local invasion and development of metastases. Aberrant expression in tumor tissue compared to healthy parenchyma and the correlation of expression levels with clinical-pathological features allow the potential use of many lncRNAs as bio-markers for early detection and prognosis of the disease, including the response to targeted therapy. In vitro assays indicate the potential use of lncRNAs as therapeutic targets. CONCLUSION: Our knowledge of long non-coding RNAs in relation to renal cell carcinoma is increasing rapidly. At present, some of them can be considered as promising bio-markers. Further research is needed before they can be introduced into routine clinical practice.

• Keywords
• bio­marker, dia­gnosis, long non-coding RNA, prognosis, renal cell carcinoma,
• MeSH
• Cell Cycle genetics   MeSH
• Epithelial-Mesenchymal Transition genetics   MeSH
• Carcinoma, Renal Cell diagnosis   genetics   mortality   therapy   MeSH
• Humans MeSH
• Biomarkers, Tumor genetics   MeSH
• Kidney Neoplasms diagnosis   genetics   mortality   therapy   MeSH
• Prognosis MeSH
• Cell Proliferation genetics   MeSH
• Gene Expression Regulation, Neoplastic MeSH
• RNA, Long Noncoding genetics   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Review MeSH
• Names of Substances
• Biomarkers, Tumor MeSH
• RNA, Long Noncoding MeSH

Early detection of colorectal cancer (CRC) is the key for prevention and the ability to impact long-term survival of CRC patients. Current CRC screening modalities are inadequate for global application because of low sensitivity and specificity in case of conventional stool-based screening tests, and high costs and a low participation compliance in colonoscopy. An accurate stool- or blood-based screening test with use of innovative biomarkers is an appealing alternative as it is non-invasive and poses minimal risk to patients. It is easy to perform, can be repeated at shorter intervals, and therefore would likely lead to a much higher compliance rates. Non-coding RNAs (ncRNAs) have recently gained attention because of their involvement in different biological processes, such as proliferation, differentiation, migration, angiogenesis and apoptosis. An increasing number of studies have demonstrated that mutations or abnormal expression of ncRNAs are closely associated with various cancers, including CRC. The discovery that ncRNAs (mainly microRNAs) are stable in stool and in blood plasma and serum presents the opportunity to develop novel strategies taking advantage of circulating ncRNAs as early diagnostic biomarkers of CRC. This chapter is a comprehensive examination of aberrant ncRNAs expression levels in tumor tissue, stool and blood of CRC patients and a summary of the current findings on ncRNAs, including microRNAs, small nucleolar RNAs, small nuclear RNAs, Piwi-interacting RNAs, circular RNAs and long ncRNAs in regards to their potential usage for screening or early detection of CRC.

• Keywords
• Colorectal cancer, Early diagnosis, Non-coding RNA, Screening, lncRNA, microRNA, piRNAs, snRNAs, snoRNAs,
• MeSH
• Adenocarcinoma chemistry   diagnosis   genetics   MeSH
• Adenoma chemistry   diagnosis   genetics   MeSH
• Early Detection of Cancer methods   MeSH
• Feces chemistry   MeSH
• Colorectal Neoplasms chemistry   diagnosis   genetics   MeSH
• Plasma MeSH
• Humans MeSH
• Biomarkers, Tumor analysis   blood   MeSH
• RNA, Untranslated analysis   blood   MeSH
• Patient Acceptance of Health Care MeSH
• Colonic Polyps chemistry   diagnosis   genetics   MeSH
• Gene Expression Regulation, Neoplastic MeSH
• Sensitivity and Specificity MeSH
• Serum MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Review MeSH
• Names of Substances
• Biomarkers, Tumor MeSH
• RNA, Untranslated MeSH

Gliomas are the most common malignancies of the central nervous system. Because of tumor localization and the biological behavior of tumor cells, gliomas are characterized by very poor prognosis. Despite significant efforts that have gone into glioma research in recent years, the therapeutic efficacy of available treatment options is still limited, and only a few clinically usable diagnostic biomarkers are available. More and more studies suggest non-coding RNAs to be promising diagnostic biomarkers and therapeutic targets in many cancers, including gliomas. One of the largest groups of these molecules is long non-coding RNAs (lncRNAs). LncRNAs show promising potential because of their unique tissue expression patterns and regulatory functions in cancer cells. Understanding the role of lncRNAs in gliomas may lead to discovery of the novel molecular mechanisms behind glioma biological features. It may also enable development of new solutions to overcome the greatest obstacles in therapy of glioma patients. In this review, we summarize the current knowledge about lncRNAs and their involvement in the molecular pathology of gliomas. A conclusion follows that these RNAs show great potential to serve as powerful diagnostic, prognostic, and predictive biomarkers as well as therapeutic targets.

• Keywords
• biomarker, diagnosis, glioblastoma, glioma, long non-coding RNA, molecular pathology, prognosis,
• MeSH
• Glioma genetics   pathology   MeSH
• Humans MeSH
• Pathology, Molecular MeSH
• Biomarkers, Tumor genetics   MeSH
• Prognosis MeSH
• RNA, Long Noncoding genetics   MeSH
• Animals MeSH
• Check Tag
• Humans MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Review MeSH
• Names of Substances
• Biomarkers, Tumor MeSH
• RNA, Long Noncoding MeSH

Liquid biopsy-the determination of circulating cells, proteins, DNA or RNA from biofluids through a "less invasive" approach-has emerged as a novel approach in all cancer entities. Circulating non-(protein) coding RNAs including microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and YRNAs can be passively released by tissue or cell damage or actively secreted as cell-free circulating RNAs, bound to lipoproteins or carried by exosomes. In renal cell carcinoma (RCC), a growing body of evidence suggests circulating non-coding RNAs (ncRNAs) such as miRNAs, lncRNAs, and YRNAs as promising and easily accessible blood-based biomarkers for the early diagnosis of RCC as well as for the prediction of prognosis and treatment response. In addition, circulating ncRNAs could also play a role in RCC pathogenesis and progression. This review gives an overview over the current study landscape of circulating ncRNAs and their involvement in RCC pathogenesis as well as their potential utility as future biomarkers in RCC diagnosis and treatment.

• Keywords
• biomarker, diagnosis, liquid biopsy, long non-coding RNA, microRNA, prognosis, renal cell carcinoma,
• Publication type
• Journal Article MeSH
• Review MeSH

BACKGROUND: Long non-coding RNAs (lncRNA) are more than 200-nucleotide-long RNA molecules that affect multiple physiologic phenomena and have important regulatory functions in cells. Their levels are often altered in various malignancies, thus they represent a potential biomarker for the diagnostics, prognosis or recurrence of cancer. Their importance has recently led to an enormous increase in a number of publications on the subject. The most frequently studied lncRNAs are HOTAIR, MALAT1 and PCA3. AIM: Numerous methods are currently being developed for the analysis or detection of lncRNA. They are mostly based on optical methods used for the detection of messenger RNAs, including polymerase chain reaction with reverse transcription, fluorescence in situ hybridisation or next-generation sequencing, but caution must be taken due to their structural differences. Here, we describe not only standard but also novel techniques for lncRNA detection, including chemiluminescent and electrochemical techniques. CONCLUSION: Despite the great progress and plethora of papers on this topic, there is only one single approved lncRNA-based diagnostic test, a PCA3 test for the diagnosis of prostate cancer from the patients urine. All other tests are only in their research phase and need to be validated. Nevertheless, lncRNA diagnostics offer enormous potential and thus it is highly probable that other diagnostic tests on different lncRNA types will soon appear.

• Keywords
• biosensing techniques, carcinogenesis, long non-coding RNA, tumor biomarkers,
• MeSH
• Humans MeSH
• Biomarkers, Tumor genetics   MeSH
• Prostatic Neoplasms diagnosis   genetics   MeSH
• Prognosis MeSH
• RNA, Long Noncoding genetics   MeSH
• Check Tag
• Humans MeSH
• Male MeSH
• Publication type
• Journal Article MeSH
• Review MeSH
• Names of Substances
• Biomarkers, Tumor MeSH
• RNA, Long Noncoding MeSH

OBJECTIVES: Long non-coding RNAs (lncRNAs) are RNA transcripts longer than 200 nucleotides that are not translated into proteins. They are involved in pathogenesis of many diseases including cancer and have a potential to serve as diagnostic and prognostic markers. We aimed to investigate lncRNA expression profiles in bone marrow plasma cells (BMPCs) of newly diagnosed multiple myeloma (MM) patients in comparison to normal BMPCs of healthy donors (HD) in a three-phase biomarker study. METHODS: Expression profile of 83 lncRNA was performed by RT2 lncRNA PCR Array (Qiagen), followed by quantitative real-time PCR using specific TaqMan non-coding RNA assays analyzing 84 newly diagnosed MM patients and 25 HD. RESULTS: Our analysis revealed dysregulation of two lncRNAs; NEAT1 (sensitivity of 55.0% and specificity of 79.0%) and UCA1 (sensitivity of 85.0% and specificity of 94.7%). UCA1 levels correlated with albumin and monoclonal immunoglobulin serum levels, cytogenetic aberrations, and survival of MM patients. CONCLUSION: Our study suggests a possible prognostic impact of UCA1 expression levels on MM patients.

• Keywords
• biomarker, long non-coding RNA, multiple myeloma, plasma cells, prognosis, quantitative real-time PCR,
• MeSH
• Biomarkers MeSH
• Chromosome Aberrations MeSH
• Diagnosis, Differential MeSH
• In Situ Hybridization, Fluorescence MeSH
• Kaplan-Meier Estimate MeSH
• Real-Time Polymerase Chain Reaction MeSH
• Middle Aged MeSH
• Humans MeSH
• Multiple Myeloma diagnosis   genetics   mortality   therapy   MeSH
• Biomarkers, Tumor * MeSH
• Prognosis MeSH
• Gene Expression Regulation, Neoplastic * MeSH
• RNA, Long Noncoding genetics   MeSH
• ROC Curve MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Neoplasm Staging MeSH
• Gene Expression Profiling MeSH
• Check Tag
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• Biomarkers MeSH
• Biomarkers, Tumor * MeSH
• NEAT1 long non-coding RNA, human MeSH Browser
• RNA, Long Noncoding MeSH
• UCA1 RNA, human MeSH Browser

Long non-coding RNA molecules (lncRNA) are defined as molecules over 200 nucleotides long that are localized in the nucleus and cytoplasm of cells. Although function of most lnRNA is not known, it is obvious that they are involved in various biological processes. LncRNA play a key role in transcriptional as well as posttranscriptional regulatory pathways and are involved in important cell processes, such as proliferation, differentiation, apoptosis but also pathogenesis of various diseases. Their dysregulation is important in steps of tumor transformation. In this review, we will describe the nature, function and molecular basis of these molecules as well as their diagnostic potential. The main focus of this review is the usage of these molecules in the most often diagnosed tumors in the Czech population--colorectal carcinoma, breast and prostate carcinomas.

• MeSH
• Humans MeSH
• Neoplasms diagnosis   MeSH
• Gene Expression Regulation, Neoplastic MeSH
• RNA, Long Noncoding physiology   MeSH
• Check Tag
• Humans MeSH
• Publication type
• English Abstract MeSH
• Journal Article MeSH
• Review MeSH
• Names of Substances
• RNA, Long Noncoding MeSH

This narrative review summarizes and discusses the implications of the Diagnostic and Statistical Manual of Mental Disorders (DSM)-5 and the upcoming International Classification of Diseases (ICD)-11 classification systems on the prevalence of bipolar disorder and on the validity of the DSM-5 diagnosis of bipolar disorder according to the Robin and Guze criteria of diagnostic validity. Here we review and discuss current data on the prevalence of bipolar disorder diagnosed according to DSM-5 versus DSM-IV, and data on characteristics of bipolar disorder in the two diagnostic systems in relation to extended Robin and Guze criteria: 1) clinical presentation, 2) associations with para-clinical data such as brain imaging and blood-based biomarkers, 3) delimitation from other disorders, 4) associations with family history / genetics, 5) prognosis and long-term follow-up, and 6) treatment effects. The review highlights that few studies have investigated consequences for the prevalence of the diagnosis of bipolar disorder and for the validity of the diagnosis. Findings from these studies suggest a substantial decrease in the point prevalence of a diagnosis of bipolar with DSM-5 compared with DSM-IV, ranging from 30-50%, but a smaller decrease in the prevalence during lifetime, corresponding to a 6% reduction. It is concluded that it is likely that the use of DSM-5 and ICD-11 will result in diagnostic delay and delayed early intervention in bipolar disorder. Finally, we recommend areas for future research.

• Keywords
• Bipolar disorder;DSM-5;ICD-11;Validity of diagnosis;Diagnostic delay;Delayed early intervention,
• MeSH
• Bipolar Disorder * diagnosis   epidemiology   MeSH
• Diagnostic and Statistical Manual of Mental Disorders MeSH
• Humans MeSH
• International Classification of Diseases MeSH
• Delayed Diagnosis MeSH
• Prevalence MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Review MeSH