In most lymphomas, p53 signaling pathway is inactivated by various mechanisms independent to p53 gene mutations or deletions. In many cases, p53 function is largely regulated by alterations in the protein abundance levels by the action of E3 ubiquitin-protein ligase MDM2, targeting p53 to proteasome-mediated degradation. In the present study, an integrating transcriptomics and proteomics analysis was employed to investigate the effect of p53 activation by a small-molecule MDM2-antagonist, nutlin-3a, on three lymphoma cell models following p53 activation. Our analysis revealed a system-wide nutlin-3a-associated effect in all examined lymphoma types, identifying in total of 4037 differentially affected proteins involved in a plethora of pathways, with significant heterogeneity among lymphomas. Our findings include known p53-targets and novel p53 activation effects, involving transcription, translation, or degradation of protein components of pathways, such as a decrease in key members of PI3K/mTOR pathway, heat-shock response, and glycolysis, and an increase in key members of oxidative phoshosphorylation, autophagy and mitochondrial translation. Combined inhibition of HSP90 or PI3K/mTOR pathway with nutlin-3a-mediated p53-activation enhanced the apoptotic effects suggesting a promising strategy against human lymphomas. Integrated omic profiling after p53 activation offered novel insights on the regulatory role specific proteins and pathways may have in lymphomagenesis.

Metabolomics and pharmacometabolomics are at the forefront of precision medicine, serving as powerful tools in drug discovery and development. These approaches help address critical challenges in the field, including high clinical trial failure rates, adverse drug reactions, and interindividual variability in drug response. Comprehensive metabolome profiling enables the elucidation of disease mechanisms, identification of drug targets, optimization of therapeutic strategies, and assessment of drug safety and efficacy. It also supports more informed clinical trial design. This review highlights the pivotal role of metabolomics in advancing precision medicine and aims to broaden the perspectives of emerging scientists entering this complex field. Key analytical techniques–namely mass spectrometry and nuclear magnetic resonance spectroscopy–are discussed for their respective strengths and limitations in metabolite identification, quantitation, and structural elucidation. Additionally, analytical separation technologies such as liquid and gas chromatography, ion mobility spectrometry, capillary electrophoresis, and supercritical fluid chromatography are explored for their potential to enhance metabolome coverage, improve analytical efficiency, and reduce costs. Ongoing advancements in instrumentation and computational tools are helping to overcome major challenges in metabolomics, including metabolome complexity, data analysis and integration, and biomarker validation. These developments continue to expand the applications of metabolomics and pharmacometabolomics in both preclinical and clinical research. Ultimately, this review underscores their translational potential in facilitating drug discovery, mitigating risks in clinical trials, and shaping the future of precision medicine.

CLL is a hematological malignancy considered as the most frequent lymphoproliferative disease in the western world. It is characterized by high molecular heterogeneity and despite the available therapeutic options, there are many patient subgroups showing the insufficient effectiveness of disease treatment. The challenge is to investigate the individual molecular characteristics and heterogeneity of these patients. Proteomics analysis is a powerful approach that monitors the constant state of flux operators of genetic information and can unravel the proteome heterogeneity and rewiring into protein pathways in CLL patients. This review essences all the available proteomics studies in CLL and suggests the way these studies can be exploited to find effective therapeutic options combined with drug repurposing approaches. Drug repurposing utilizes all the existing knowledge of the safety and efficacy of FDA-approved or investigational drugs and anticipates drug alignment to crucial CLL therapeutic targets, leading to a better disease outcome. The drug repurposing studies in CLL are also discussed in this review. The next goal involves the integration of proteomics-based drug repurposing in precision medicine, as well as the application of this procedure into clinical practice to predict the most appropriate drugs combination that could ensure therapy and the long-term survival of each CLL patient.

Myelodysplastic syndromes (MDS) belong to a category of malignant stem-cell and myeloid disorders that deteriorate the function of the hematopoietic system exacerbated by the omnipresent anemia that characterizes myelodysplasia. The pathogenesis of MDS is driven by cytogenetic abnormalities along with the excessive production of pro-inflammatory cytokines and disruptions in inflammatory signaling pathway, particularly through the influence of carbonylated proteins, which are linked to MDS progression. An additional and major contributor to the pathogenesis of MDS is oxidative stress marked by uncontrolled levels of reactive oxygen species (ROS), which have been suggested as potential biomarkers for assessing disease severity and stratifying MDS cases throughout a variety of methods. Excessive and non-accumulative levels of free iron can also lead to iron overload (IOL)—related promotion of a high oxidative state, whether we refer to treatment-related IOL or natural IOL mechanisms. Proteomic analysis has emerged as a powerful tool for profiling protein samples, and, consequently, understanding the molecular changes underlying MDS. In this review, we evaluated studies and their methodologies aiming in investigating distinctive proteomics signatures associated with MDS pathogenesis, focusing on the role of oxidative stress at the protein level.

Chronic Lymphocytic Leukemia (CLL) is the most common B-cell malignancy in the Western world, characterized by frequent relapses despite temporary remissions. Our study integrated publicly available proteomic, transcriptomic, and patient survival datasets to identify key differences between healthy and CLL samples. We exposed approximately 1000 proteins that differentiate healthy from cancerous cells, with 608 upregulated and 415 downregulated in CLL cases. Notable upregulated proteins include YEATS2 (an epigenetic regulator), PIGR (Polymeric immunoglobulin receptor), and SNRPA (a splicing factor), which may serve as prognostic biomarkers for this disease. Key pathways implicated in CLL progression involve RNA processing, stress resistance, and immune response deficits. Furthermore, we identified three existing drugs—Bosutinib, Vorinostat, and Panobinostat—for potential further investigation in drug repurposing in CLL. We also found limited correlation between transcriptomic and proteomic data, emphasizing the importance of proteomics in understanding gene expression regulation mechanisms. This generally known disparity highlights once again that mRNA levels do not accurately predict protein abundance due to many regulatory factors, such as protein degradation, post-transcriptional modifications, and differing rates of translation. These results demonstrate the value of integrating omics data to uncover deregulated proteins and pathways in cancer and suggest new therapeutic avenues for CLL.

Mantle cell lymphoma (MCL) is a rare, incurable, and aggressive B-cell non-Hodgkin lymphoma (NHL). Early MCL diagnosis and treatment is critical and puzzling due to inter/intra-tumoral heterogeneity and limited understanding of the underlying molecular mechanisms. We developed and applied a multifaceted analysis of selected publicly available transcriptomic data of well-defined MCL stages, integrating network-based methods for pathway enrichment analysis, co-expression module alignment, drug repurposing, and prediction of effective drug combinations. We demonstrate the “butterfly effect” emerging from a small set of initially differentially expressed genes, rapidly expanding into numerous deregulated cellular processes, signaling pathways, and core machineries as MCL becomes aggressive. We explore pathogenicity-related signaling circuits by detecting common co-expression modules in MCL stages, pointing out, among others, the role of VEGFA and SPARC proteins in MCL progression and recommend further study of precise drug combinations. Our findings highlight the benefit that can be leveraged by such an approach for better understanding pathobiology and identifying high-priority novel diagnostic and prognostic biomarkers, drug targets, and efficacious combination therapies against MCL that should be further validated for their clinical impact.