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Predictive Diagnostics and Personalized Treatment
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Predictive Diagnostics and Personalized Treatment

A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Pharmacology".

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 18879

Special Issue Editor

Prof. Dr. Olga Golubnitschaja

E-Mail Website
Guest Editor
Predictive, Preventive Personalised (3P) Medicine, Department of Radiation Oncology, University Hospital Bonn, Rheinische Friedrich-Wilhelms-Universität Bonn, 53127 Bonn, Germany
Interests: predictive preventive personalised medicine (PPPM/3PM); suboptimal health; vasospasm; cancer and metastatic disease; stroke; diabetes; cardiovascular disease; noncommunicable disorder; COVID-19; phenotyping; genotyping; molecular diagnostics; biomarker panels; patient stratification; individualized profiling; liquid biopsy; articifial intelligence; disease modeling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The paradigm change from reactive medicine to a cost-effective predictive approach and personalization of medical services is non-incremental in biomedical sciences and healthcare. A predictive and personalized approach ranges from identifying individuals in a suboptimal health condition followed by cost-effective targeted prevention, to palliative care evolving from “just end of life” care to treatment algorithms tailored to the person with optimized individual outcomes. Multiprofessional expertise is essential. Methodology and tools include phenotyping and genotyping, condition-specific biomarker panels, patient stratification, individualized profiling, liquid biopsy, application of articifial intelligence, and disease modeling. Medical ethics and the healthcare economy have to be considered for any innovation proposed. 

Prof. Dr. Olga Golubnitschaja
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Clinical Medicine is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • predictive diagnosis
  • personalized medicine
  • suboptimal health
  • COVID-19
  • noncommunicable disease
  • collateral pathologies
  • multilevel diagnostics
  • biomarker panels
  • patient stratification
  • individualised profiling
  • treatment algorhithms
  • bioinformatics
  • disease modeling
  • healthcare economy and ethics

Published Papers (7 papers)

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Research

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11 pages, 2192 KiB  
Article
Upregulation of miRNA-200c during Disease Progression in COVID-19 Patients
by Lukas van de Sand, Peer Braß, Jonas Gregorius, Kevin Pattberg, Andrea Engler, Ulf Dittmer, Christian Taube, Stephan Brock, Marc Moritz Berger, Thorsten Brenner, Oliver Witzke and Adalbert Krawczyk
J. Clin. Med. 2023, 12(1), 283; https://doi.org/10.3390/jcm12010283 - 29 Dec 2022
Cited by 3 | Viewed by 1398
Abstract
The COVID-19 pandemic has caused more than 6 million deaths worldwide since its first outbreak in December 2019 and continues to be a major health problem. Several studies have established that the infection by SARS-CoV-2 can be categorized in a viremic, acute and [...] Read more.
The COVID-19 pandemic has caused more than 6 million deaths worldwide since its first outbreak in December 2019 and continues to be a major health problem. Several studies have established that the infection by SARS-CoV-2 can be categorized in a viremic, acute and recovery or severe phase. Hyperinflammation during the acute pneumonia phase is a major cause of severe disease progression and death. Treatment of COVID-19 with directly acting antivirals is limited within a narrow window of time between first clinical symptoms and the hyperinflammatory response. Therefore, early initiation of treatment is crucial to assure optimal health care for patients. Molecular diagnostic biomarkers represent a potent tool to predict the course of disease and thus to assess the optimal treatment regimen and time point. Here, we investigated miRNA-200c as a potential marker for the prediction of the severity of COVID-19 to preventively initiate and personalize therapeutic interventions in the future. We found that miRNA-200c correlates with the severity of disease. With retrospective analysis, however, there is no correlation with prognosis at the time of hospitalization. Our study provides the basis for further evaluation of miRNA-200c as a predictive biomarker for the progress of COVID-19. Full article
(This article belongs to the Special Issue Predictive Diagnostics and Personalized Treatment)
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16 pages, 1063 KiB  
Article
A Machine Learning Model for Predicting Hospitalization in Patients with Respiratory Symptoms during the COVID-19 Pandemic
by Victor Muniz De Freitas, Daniela Mendes Chiloff, Giulia Gabriella Bosso, Janaina Oliveira Pires Teixeira, Isabele Cristina de Godói Hernandes, Maira do Patrocínio Padilha, Giovanna Corrêa Moura, Luis Gustavo Modelli De Andrade, Frederico Mancuso, Francisco Estivallet Finamor, Aluísio Marçal de Barros Serodio, Jaquelina Sonoe Ota Arakaki, Marair Gracio Ferreira Sartori, Paulo Roberto Abrão Ferreira and Érika Bevilaqua Rangel
J. Clin. Med. 2022, 11(15), 4574; https://doi.org/10.3390/jcm11154574 - 05 Aug 2022
Cited by 5 | Viewed by 2170
Abstract
A machine learning approach is a useful tool for risk-stratifying patients with respiratory symptoms during the COVID-19 pandemic, as it is still evolving. We aimed to verify the predictive capacity of a gradient boosting decision trees (XGboost) algorithm to select the most important [...] Read more.
A machine learning approach is a useful tool for risk-stratifying patients with respiratory symptoms during the COVID-19 pandemic, as it is still evolving. We aimed to verify the predictive capacity of a gradient boosting decision trees (XGboost) algorithm to select the most important predictors including clinical and demographic parameters in patients who sought medical support due to respiratory signs and symptoms (RAPID RISK COVID-19). A total of 7336 patients were enrolled in the study, including 6596 patients that did not require hospitalization and 740 that required hospitalization. We identified that patients with respiratory signs and symptoms, in particular, lower oxyhemoglobin saturation by pulse oximetry (SpO2) and higher respiratory rate, fever, higher heart rate, and lower levels of blood pressure, associated with age, male sex, and the underlying conditions of diabetes mellitus and hypertension, required hospitalization more often. The predictive model yielded a ROC curve with an area under the curve (AUC) of 0.9181 (95% CI, 0.9001 to 0.9361). In conclusion, our model had a high discriminatory value which enabled the identification of a clinical and demographic profile predictive, preventive, and personalized of COVID-19 severity symptoms. Full article
(This article belongs to the Special Issue Predictive Diagnostics and Personalized Treatment)
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11 pages, 851 KiB  
Article
Combined First Month Body Weight Loss and Development of Tolerance as Predictors of 6-Month Efficacy of Mazindol in Mild and Moderate Obese Subjects
by Juan Carlos Huerta-Cruz, Héctor Isaac Rocha-González, Ashuin Kammar-García, Samuel Canizales-Quinteros, Lina Marcela Barranco-Garduño and Juan Gerardo Reyes-García
J. Clin. Med. 2022, 11(11), 3211; https://doi.org/10.3390/jcm11113211 - 04 Jun 2022
Cited by 1 | Viewed by 1985
Abstract
The weight loss response to anti-obesity drugs is highly variable and poorly understood, which does not allow us to know, in advance, in which subjects the drug will be effective and in which it will not. The objective of this study was to [...] Read more.
The weight loss response to anti-obesity drugs is highly variable and poorly understood, which does not allow us to know, in advance, in which subjects the drug will be effective and in which it will not. The objective of this study was to explore the body weight reduction in kilograms in the first month (1mo-BWRkg) and the development of tolerance as predictors of 6-month efficacy for treatment with 1 mg mazindol twice a day. One hundred ninety-six obese subjects were individually or jointly analyzed. Approximately 60% of subjects developed tolerance to mazindol and achieved increasing proportional levels of 6-month efficacy according to 1mo-BWRkg intervals (<1 kg, 1 to <2 kg, 2 to <4 kg and ≥4 kg). Both moT and 1mo-BWRkg were significantly correlated with the mean percentage body weight reduction (BWR%) after 6-months of treatment. The qualitative analysis of both predictors on the progressive efficacy of mazindol was used to classify patients according to expected efficacy (inefficient, slightly effective, partially effective, or fully effective), based on the mean percentage efficacy and the number of subjects reaching a BWR% of <5%, 5 to <10%, 10 to <15% or ≥15%. In conclusion, combined 1mo-BWRkg and moT were early predictors for the progressive efficacy of 6-month mazindol anti-obesity therapy. This finding represents progress in predictive, preventive, and personalized medicine which could serve for estimating the expectations of individual efficacy with the use of the drug. and highlights the basic principle of personalized medicine, “one size does not fit all”. Full article
(This article belongs to the Special Issue Predictive Diagnostics and Personalized Treatment)
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12 pages, 1730 KiB  
Article
Differential Expression of the Sphingolipid Pathway Is Associated with Sensitivity to the PP2A Activator FTY720 in Colorectal Cancer Cell Lines
by Peter Sciberras, Laura Grech and Godfrey Grech
J. Clin. Med. 2021, 10(21), 4999; https://doi.org/10.3390/jcm10214999 - 27 Oct 2021
Cited by 1 | Viewed by 2265
Abstract
Protein phosphatase 2A (PP2A) is a ubiquitously expressed intracellular serine/threonine phosphatase. Deregulation of PP2A is a common event associated with adenocarcinomas of the colon and rectum. We have previously shown that breast cancer cell lines are sensitive to the PP2A activator FTY720, and [...] Read more.
Protein phosphatase 2A (PP2A) is a ubiquitously expressed intracellular serine/threonine phosphatase. Deregulation of PP2A is a common event associated with adenocarcinomas of the colon and rectum. We have previously shown that breast cancer cell lines are sensitive to the PP2A activator FTY720, and that sensitivity is predicted by high Aurora kinase A (AURKA) mRNA expression. In this study, we hypothesized that high relative AURKA expression could predict sensitivity to FTY720-induced apoptosis in colorectal cancer (CRC). The CRC cell lines NCI H716, COLO320DM, DLD-1, SW480, and HT-29 show a high relative AURKA expression as compared to LS411N, T84, HCT116, SW48, and LOVO. Following viability assays, LS411N, T84, HCT116, and SW480 were shown to be sensitive to FTY720, whereas DLD-1 and HT-29 were non-sensitive. Hence, AURKA mRNA expression does not predict sensitivity to FTY720 in CRC cell lines. Differentially expressed genes (DEGs) were obtained by comparing the sensitive CRC cell lines (LS411N and HCT116) against the non-sensitive (HT-29 and DLD-1). We found that 253 genes were significantly altered in expression, and upregulation of CERS4, PPP2R2C, GNAZ, PRKCG, BCL2, MAPK12, and MAPK11 suggests the involvement of the sphingolipid signaling pathway, known to be activated by phosphorylated-FTY720. In conclusion, although AURKA expression did not predict sensitivity to FTY720, it is evident that specific CRC cell lines are sensitive to 5 µM FTY720, potentially because of the differential expression of genes involved in the sphingolipid pathway. Full article
(This article belongs to the Special Issue Predictive Diagnostics and Personalized Treatment)
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12 pages, 614 KiB  
Article
Combined Impact of Inflammation and Pharmacogenomic Variants on Voriconazole Trough Concentrations: A Meta-Analysis of Individual Data
by Léa Bolcato, Charles Khouri, Anette Veringa, Jan Willem C. Alffenaar, Takahiro Yamada, Takafumi Naito, Fabien Lamoureux, Xavier Fonrose, Françoise Stanke-Labesque and Elodie Gautier-Veyret
J. Clin. Med. 2021, 10(10), 2089; https://doi.org/10.3390/jcm10102089 - 13 May 2021
Cited by 14 | Viewed by 2227
Abstract
Few studies have simultaneously investigated the impact of inflammation and genetic polymorphisms of cytochromes P450 2C19 and 3A4 on voriconazole trough concentrations. We aimed to define the respective impact of inflammation and genetic polymorphisms on voriconazole exposure by performing individual data meta-analyses. A [...] Read more.
Few studies have simultaneously investigated the impact of inflammation and genetic polymorphisms of cytochromes P450 2C19 and 3A4 on voriconazole trough concentrations. We aimed to define the respective impact of inflammation and genetic polymorphisms on voriconazole exposure by performing individual data meta-analyses. A systematic literature review was conducted using PubMed to identify studies focusing on voriconazole therapeutic drug monitoring with data of both inflammation (assessed by C-reactive protein level) and the pharmacogenomics of cytochromes P450. Individual patient data were collected and analyzed in a mixed-effect model. In total, 203 patients and 754 voriconazole trough concentrations from six studies were included. Voriconazole trough concentrations were independently influenced by age, dose, C-reactive protein level, and both cytochrome P450 2C19 and 3A4 genotype, considered individually or through a combined genetic score. An increase in the C-reactive protein of 10, 50, or 100 mg/L was associated with an increased voriconazole trough concentration of 6, 35, or 82%, respectively. The inhibitory effect of inflammation appeared to be less important for patients with loss-of-function polymorphisms for cytochrome P450 2C19. Voriconazole exposure is influenced by age, inflammatory status, and the genotypes of both cytochromes P450 2C19 and 3A4, suggesting that all these determinants need to be considered in approaches of personalization of voriconazole treatment. Full article
(This article belongs to the Special Issue Predictive Diagnostics and Personalized Treatment)
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17 pages, 959 KiB  
Article
ABG Assistant—Towards an Understanding of Complex Acid-Base Disorders
by Łukasz Gutowski, Kaja Gutowska, Alicja Brożek, Marcin Nowicki and Dorota Formanowicz
J. Clin. Med. 2021, 10(7), 1516; https://doi.org/10.3390/jcm10071516 - 05 Apr 2021
Cited by 1 | Viewed by 3712
Abstract
The ability to diagnose acid-base imbalances correctly is essential for physicians and other healthcare workers. Despite its importance, it is often considered too complex and confusing. Although most people dealing with arterial blood gases (ABGs) do not usually have problems with acid-base disorder [...] Read more.
The ability to diagnose acid-base imbalances correctly is essential for physicians and other healthcare workers. Despite its importance, it is often considered too complex and confusing. Although most people dealing with arterial blood gases (ABGs) do not usually have problems with acid-base disorder assessment, such an analysis is also carried out by other healthcare workers for whom this can be a challenging task. Many aspects may be problematic, partly due to multiple data analysis methods and no definitive statement on which one is better. According to our survey, the correctness of arterial blood gas analysis is unsatisfactory, especially in mixed disorders, which do not always manifest an obvious set of symptoms. Therefore, ABG parameters can be used as an established biomarker panel, which is considered to be a powerful tool for personalized medicine. Moreover, using different approaches to analyze acid-base disorders can lead to varying diagnoses in some cases. Because of these problems, we developed a mobile application that can spot diagnostic differences by taking into account physiological and chemical approaches, including their variants, with a corrected anion gap. The proposed application is characterized by a high percentage of correct analyses and can be an essential aid for diagnosing acid-base disturbances. Full article
(This article belongs to the Special Issue Predictive Diagnostics and Personalized Treatment)
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Review

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50 pages, 595 KiB  
Review
Abscopal Effects in Metastatic Cancer: Is a Predictive Approach Possible to Improve Individual Outcomes?
by Barbara Link, Adriana Torres Crigna, Michael Hölzel, Frank A. Giordano and Olga Golubnitschaja
J. Clin. Med. 2021, 10(21), 5124; https://doi.org/10.3390/jcm10215124 - 31 Oct 2021
Cited by 10 | Viewed by 3909
Abstract
Patients with metastatic cancers often require radiotherapy (RT) as a palliative therapy for cancer pain. RT can, however, also induce systemic antitumor effects outside of the irradiated field (abscopal effects) in various cancer entities. The occurrence of the abscopal effect is associated with [...] Read more.
Patients with metastatic cancers often require radiotherapy (RT) as a palliative therapy for cancer pain. RT can, however, also induce systemic antitumor effects outside of the irradiated field (abscopal effects) in various cancer entities. The occurrence of the abscopal effect is associated with a specific immunological activation in response to RT-induced cell death, which is mainly seen under concomitant immune checkpoint blockade. Even if the number of reported apscopal effects has increased since the introduction of immune checkpoint inhibition, its occurrence is still considered rare and unpredictable. The cases reported so far may nevertheless allow for identifying first biomarkers and clinical patterns. We here review biomarkers that may be helpful to predict the occurrence of abscopal effects and hence to optimize therapy for patients with metastatic cancers. Full article
(This article belongs to the Special Issue Predictive Diagnostics and Personalized Treatment)
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