Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused the COVID-19 health emergency, affecting and killing millions of people worldwide. Following SARS-CoV-2 infection, COVID-19 patients show a spectrum of symptoms ranging from asymptomatic to very severe manifestations. In particular, bronchial and pulmonary cells, involved at the initial stage, trigger a hyper-inflammation phase, damaging a wide range of organs, including the heart, brain, liver, intestine and kidney. Due to the urgent need for solutions to limit the virus' spread, most efforts were initially devoted to mapping outbreak trajectories and variant emergence, as well as to the rapid search for effective therapeutic strategies. Samples collected from hospitalized or dead COVID-19 patients from the early stages of pandemic have been analyzed over time, and to date they still represent an invaluable source of information to shed light on the molecular mechanisms underlying the organ/tissue damage, the knowledge of which could offer new opportunities for diagnostics and therapeutic designs. For these purposes, in combination with clinical data, omics profiles and network models play a key role providing a holistic view of the pathways, processes and functions most affected by viral infection. In fact, in addition to epidemiological purposes, networks are being increasingly adopted for the integration of multiomics data, and recently their use has expanded to the identification of drug targets or the repositioning of existing drugs. These topics will be covered here by exploring the landscape of SARS-CoV-2 survey-based studies using systems biology approaches derived from omics data, paying particular attention to those that have considered samples of human origin.
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http://dx.doi.org/10.3390/biology12091196 | DOI Listing |
Mol Med Rep
March 2025
The First Central Clinical School, Tianjin Medical University, Tianjin 300000, P.R. China.
Hepatocellular carcinoma (HCC) is a common cause of cancer‑related mortality and morbidity worldwide. While iodine‑125 (I) particle brachytherapy has been extensively used in the clinical treatment of various types of cancer, the precise mechanism underlying its effectiveness in treating HCC remains unclear. In the present study, MHCC‑97H cells were treated with I, after which, cell viability and proliferation were assessed using Cell Counting Kit‑8, 5‑ethynyl‑2'‑deoxyuridine and colony formation assays, cell invasion and migration were evaluated using wound healing and Transwell assays, and cell apoptosis was determined using flow cytometry.
View Article and Find Full Text PDFiScience
January 2025
Department of Biology, University of Copenhagen, 2100 Copenhagen, Denmark.
Chromothripsis, a hallmark of cancer, is characterized by extensive and localized DNA rearrangements involving one or a few chromosomes. However, its genome-wide frequency and characteristics in urothelial carcinoma (UC) remain largely unknown. Here, by analyzing single-regional and multi-regional whole-genome sequencing (WGS), we present the chromothripsis blueprint in 488 UC patients.
View Article and Find Full Text PDFProteomics
January 2025
School of Public Health, University of Haifa, Haifa, Israel.
Chronic kidney disease (CKD) poses a significant and growing global health challenge, making early detection and slowing disease progression essential for improving patient outcomes. Traditional diagnostic methods such as glomerular filtration rate and proteinuria are insufficient to capture the complexity of CKD. In contrast, omics technologies have shed light on the molecular mechanisms of CKD, helping to identify biomarkers for disease assessment and management.
View Article and Find Full Text PDFNat Biomed Eng
January 2025
Xinjiang Technical Institutes of Physics and Chemistry, Chinese Academy of Sciences, Urumqi, China.
Graph representation learning has been leveraged to identify cancer genes from biological networks. However, its applicability is limited by insufficient interpretability and generalizability under integrative network analysis. Here we report the development of an interpretable and generalizable transformer-based model that accurately predicts cancer genes by leveraging graph representation learning and the integration of multi-omics data with the topologies of homogeneous and heterogeneous networks of biological interactions.
View Article and Find Full Text PDFCell Death Dis
January 2025
The First Affiliated Hospital, Cancer Research Institute, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, PR China.
This research demonstrates that DCC-2036 (Rebastinib), a potent third-generation tyrosine kinase inhibitor (TKI), effectively suppresses tumor growth in colorectal cancer (CRC) models with functional immune systems. The findings underscore the capacity of DCC-2036 to enhance both the activation and cytotoxic functionality of CD8 T cells, which are crucial for facilitating anti-tumor immune responses. Through comprehensive multi-omics investigations, significant shifts in both gene and protein expression profiles were detected, notably a marked decrease in DKK1 levels.
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