Challenges in cancer research and multifaceted approaches for cancer biomarker quest

AbstractRecent advances in cancer biology have subsequently led to the development of new molecularly targeted anti-cancer agents that can effectively hit cancer-related proteins and pathways. Despite better insight into genomic aberrations and diversity of cancer phenotypes, it is apparent that proteomics too deserves attention in cancer research. Currently, a wide range of proteomic technologies are being used in quest for new cancer biomarkers with effective use. These, together with newer technologies such as multiplex assays could significantly contribute to the discovery and development of selective and specific cancer biomarkers with diagnostic or prognostic values for monitoring the disease state. This review attempts to illustrate recent advances in the field of cancer biomarkers and multifaceted approaches undertaken in combating cancer

In Search of System-Wide Productivity Gains - The Role of Global Collaborations in Preclinical Translation

Non peer reviewe

European Health Data Space – an opportunity now to grasp the future of data-driven healthcare

Peer reviewedPostprin

YAP regulates cell mechanics by controlling focal adhesion assembly

Hippo effectors YAP/TAZ act as on-off mechanosensing switches by sensing modifications in extracellular matrix (ECM) composition and mechanics. The regulation of their activity has been described by a hierarchical model in which elements of Hippo pathway are under the control of focal adhesions (FAs). Here we unveil the molecular mechanism by which cell spreading and RhoA GTPase activity control FA formation through YAP to stabilize the anchorage of the actin cytoskeleton to the cell membrane. This mechanism requires YAP co-transcriptional function and involves the activation of genes encoding for integrins and FA docking proteins. Tuning YAP transcriptional activity leads to the modification of cell mechanics, force development and adhesion strength, and determines cell shape, migration and differentiation. These results provide new insights into the mechanism of YAP mechanosensing activity and qualify this Hippo effector as the key determinant of cell mechanics in response to ECM cues.Peer reviewe

Early and Non-invasive Diagnosis of Aspergillosis Revealed by Infection Kinetics Monitored in a Rat Model

Background:Aspergillus fumigatus is a ubiquitous saprophytic airborne fungus responsible for more than one million deaths every year. The siderophores of A. fumigatus represent important virulence factors that contribute to the microbiome-metabolome dialog in a host. From a diagnostic point of view, the monitoring of Aspergillus secondary metabolites in urine of a host is promising due to the non-invasiveness, rapidity, sensitivity, and potential for standardization.Methods: Using a model of experimental aspergillosis in immunocompromised Lewis rats, the fungal siderophores ferricrocin (FC) and triacetylfusarinine C (TAFC) were monitored in rat urine before and after lung inoculation with A. fumigatus conidia. Molecular biomarkers in high-dose (HD) and low-dose (LD) infection models were separated using high performance liquid chromatography (HPLC) and were detected by mass spectrometry (MS). In the current work, we corroborated the in vivo MS infection kinetics data with micro-positron emission tomography/computed tomography (μPET/CT) kinetics utilizing 68Ga-labeled TAFC.Results: In the HD model, the initial FC signal reflecting aspergillosis appeared as early as 4 h post-infection. The results from seven biological replicates showed exponentially increasing metabolite profiles over time. In A. fumigatus, TAFC was found to be a less produced biomarker that exhibited a kinetic profile identical to that of FC. The amount of siderophores contributed by the inoculating conidia was negligible and undetectable in the HD and LD models, respectively. In the μPET/CT scans, the first detectable signal in HD model was recorded 48 h post-infection. Regarding the MS assay, among nine biological replicates in the LD model, three animals did not develop any infection, while one animal experienced an exponential increase of metabolites and died on day 6 post-infection. All remaining animals had constant or random FC levels and exhibited few or no symptoms to the experiment termination. In the LD model, the TAFC concentration was not statistically significant, while the μPET/CT scan was positive as early as 6 days post-infection.Conclusion: Siderophore detection in rat urine by MS represents an early and non-invasive tool for diagnosing aspergillosis caused by A. fumigatus. μPET/CT imaging further determines the infection location in vivo and allows the visualization of the infection progression over time

MLPA is a practical and complementary alternative to CMA for diagnostic testing in patients with autism spectrum disorders and identifying new candidate CNVs associated with autism

Background Autism spectrum disorder (ASD) is a complex heterogeneous developmental disease with a significant genetic background that is frequently caused by rare copy number variants (CNVs). Microarray-based whole-genome approaches for CNV detection are widely accepted. However, the clinical significance of most CNV is poorly understood, so results obtained using such methods are sometimes ambiguous. We therefore evaluated a targeted approach based on multiplex ligation-dependent probe amplification (MLPA) using selected probemixes to detect clinically relevant variants for diagnostic testing of ASD patients. We compare the reliability and efficiency of this test to those of chromosomal microarray analysis (CMA) and other tests available to our laboratory. In addition, we identify new candidate genes for ASD identified in a cohort of ASD-diagnosed patients. Method We describe the use of MLPA, CMA, and karyotyping to detect CNV in 92 ASD patients and evaluate their clinical significance. Result Pathogenic and likely pathogenic mutations were identified by CMA in eight (8.07% of the studied cohort) and 12 (13.04%) ASD patients, respectively, and in eight (8.07%) and four (4.35%) patients, respectively, by MLPA. The detected mutations include the 22q13.3 deletion, which was attributed to ring chromosome 22 formation based on karyotyping. CMA revealed a total of 91 rare CNV in 55 patients: eight pathogenic, 15 designated variants of unknown significance (VOUS)—likely pathogenic, 10 VOUS—uncertain, and 58 VOUS—likely benign or benign. MLPA revealed 18 CNV in 18 individuals: eight pathogenic, four designated as VOUS—likely pathogenic, and six designated as VOUS—likely benign/benign. Rare CNVs were detected in 17 (58.62%) out of 29 females and 38 (60.32%) out of 63 males in the cohort. Two genes, DOCK8 and PARK2, were found to be overlapped by CNV designated pathogenic, VOUS—likely pathogenic, or VOUS—uncertain in multiple patients. Moreover, the studied ASD cohort exhibited significant (p < 0.05) enrichment of duplications encompassing DOCK8. Conclusion Multiplex ligation-dependent probe amplification and CMA yielded concordant results for 12 patients bearing CNV designated pathogenic or VOUS—likely pathogenic. Unambiguous diagnoses were achieved for eight patients (corresponding to 8.7% of the total studied population) by both MLPA and CMA, for one (1.09%) patient by karyotyping, and for one (1.09%) patient by FRAXA testing. MLPA and CMA thus achieved identical reliability with respect to clinically relevant findings. As such, MLPA could be useful as a fast and inexpensive test in patients with syndromic autism. The detection rate of potentially pathogenic variants (VOUS—likely pathogenic) achieved by CMA was higher than that for MLPA (13.04% vs. 4.35%). However, there was no corresponding difference in the rate of unambiguous diagnoses of ASD patients. In addition, the results obtained suggest that DOCK8 may play a role in the etiology of ASD

Minimal information for chemosensitivity assays (MICHA): a next-generation pipeline to enable the FAIRification of drug screening experiments

Chemosensitivity assays are commonly used for preclinical drug discovery and clinical trial optimization. However, data from independent assays are often discordant, largely attributed to uncharacterized variation in the experimental materials and protocols. We report here the launching of Minimal Information for Chemosensitivity Assays (MICHA), accessed via https://micha-protocol.org. Distinguished from existing efforts that are often lacking support from data integration tools, MICHA can automatically extract publicly available information to facilitate the assay annotation including: 1) compounds, 2) samples, 3) reagents and 4) data processing methods. For example, MICHA provides an integrative web server and database to obtain compound annotation including chemical structures, targets and disease indications. In addition, the annotation of cell line samples, assay protocols and literature references can be greatly eased by retrieving manually curated catalogues. Once the annotation is complete, MICHA can export a report that conforms to the FAIR principle (Findable, Accessible, Interoperable and Reusable) of drug screening studies. To consolidate the utility of MICHA, we provide FAIRified protocols from five major cancer drug screening studies as well as six recently conducted COVID-19 studies. With the MICHA web server and database, we envisage a wider adoption of a community-driven effort to improve the open access of drug sensitivity assays.Peer reviewe

Tackling the translational challenges of multi-omics research in the realm of European personalised medicine : A workshop report

Personalised medicine (PM) presents a great opportunity to improve the future of individualised healthcare. Recent advances in -omics technologies have led to unprecedented efforts characterising the biology and molecular mechanisms that underlie the development and progression of a wide array of complex human diseases, supporting further development of PM. This article reflects the outcome of the 2021 EATRIS-Plus Multi-omics Stakeholder Group workshop organised to 1) outline a global overview of common promises and challenges that key European stakeholders are facing in the field of multi-omics research, 2) assess the potential of new technologies, such as artificial intelligence (AI), and 3) establish an initial dialogue between key initiatives in this space. Our focus is on the alignment of agendas of European initiatives in multi-omics research and the centrality of patients in designing solutions that have the potential to advance PM in long-term healthcare strategies.Peer reviewe

Generalization of DNA microarray dispersion properties: microarray equivalent of t-distribution

BACKGROUND: DNA microarrays are a powerful technology that can provide a wealth of gene expression data for disease studies, drug development, and a wide scope of other investigations. Because of the large volume and inherent variability of DNA microarray data, many new statistical methods have been developed for evaluating the significance of the observed differences in gene expression. However, until now little attention has been given to the characterization of dispersion of DNA microarray data. RESULTS: Here we examine the expression data obtained from 682 Affymetrix GeneChips(® )with 22 different types and we demonstrate that the Gaussian (normal) frequency distribution is characteristic for the variability of gene expression values. However, typically 5 to 15% of the samples deviate from normality. Furthermore, it is shown that the frequency distributions of the difference of expression in subsets of ordered, consecutive pairs of genes (consecutive samples) in pair-wise comparisons of replicate experiments are also normal. We describe a consecutive sampling method, which is employed to calculate the characteristic function approximating standard deviation and show that the standard deviation derived from the consecutive samples is equivalent to the standard deviation obtained from individual genes. Finally, we determine the boundaries of probability intervals and demonstrate that the coefficients defining the intervals are independent of sample characteristics, variability of data, laboratory conditions and type of chips. These coefficients are very closely correlated with Student's t-distribution. CONCLUSION: In this study we ascertained that the non-systematic variations possess Gaussian distribution, determined the probability intervals and demonstrated that the K(α )coefficients defining these intervals are invariant; these coefficients offer a convenient universal measure of dispersion of data. The fact that the K(α )distributions are so close to t-distribution and independent of conditions and type of arrays suggests that the quantitative data provided by Affymetrix technology give "true" representation of physical processes, involved in measurement of RNA abundance. REVIEWERS: This article was reviewed by Yoav Gilad (nominated by Doron Lancet), Sach Mukherjee (nominated by Sandrine Dudoit) and Amir Niknejad and Shmuel Friedland (nominated by Neil Smalheiser)