Omics A Journal of Integrative Biology最新文献

This analysis and commentary discuss Romania's landmark law, the first globally, acknowledging the right of citizens and patients to personalized medicine. Initiated following the EU Council's 2015 policy on personalized medicine, the law is a result of intersectoral collaborative efforts led by the Centre for Innovation in Medicine in Romania using a quadruple (later evolved to penta) helix model involving academia, public, private, and civil society sectors. Promulgated on May 24, 2023, the law legally entitles patients to personalized health care and in ways informed by individual genetic and phenotypic consideration. The law mandates informed consent for medical interventions and ensures data protection in accordance with the General Data Protection Regulation. We suggest that this pioneering legislation paves the way for integrating personalized medicine into Romania's health care system, shaping clinical practice, research, and health policy. In all, it marks a significant step in redefining health care delivery, emphasizing individualized treatment and the political determinants of personalized medicine, and setting a precedent for future health care innovations worldwide.

Prostate cancer is a major planetary health challenge wherein new ways of thinking drug discovery and therapeutics innovation are much needed. Numerous studies have shown that autophagy inhibition holds a significant role as an adjunctive intervention in prostate cancer. Hydroxychloroquine (HCQ) has gained considerable attention due to its established role as an autophagy inhibitor across diverse cancer types, but its proteomics landscape and systems biology in prostate cancer are currently lacking in the literature. This study reports the proteomic responses to HCQ in prostate cancer cells, namely, androgen-dependent LNCaP and androgen-independent PC3 cells. Differentially expressed proteins and proteome in HCQ-treated cells were determined by label-free quantification with nano-high-performance liquid chromatography and tandem mass spectrometry (nHPLC-MS/MS), and harnessing bioinformatics tools. In PC3 cells, there was a marked shift toward metabolic reprogramming, highlighted by an upregulation of mitochondrial proteins in oxidative phosphorylation and tricarboxylic acid cycle, suggesting an adaptive mechanism to maintain energy production under therapeutic stress. In contrast, LNCaP cells prioritized proteostasis and cell cycle regulation, indicating a more conservative adaptation strategy. To the best of our knowledge, this study is the first to demonstrate the differential responses of prostate cancer cells to autophagy inhibition by HCQ, suggesting that a combination therapy approach, targeting distinct pathways in androgen-independent and androgen-dependent cells, could represent a promising treatment strategy. Moreover, the varied proteomic responses observed between these cell lines underscore the importance of personalized medicine in cancer therapy. Future translational and clinical research on HCQ and prostate cancer are called for.

Tumor mutation burden (TMB) has profound implications for personalized cancer therapy, particularly immunotherapy. However, the size of the panel and the cutoff values for an accurate determination of TMB are still controversial. In this study, a pan-cancer analysis was performed on 22 cancer types from The Cancer Genome Atlas. The efficiency of gene panels of different sizes and the effect of cutoff values in accurate TMB determination was assessed on a large cohort using Whole Exome Sequencing data (n = 9929 patients) as the gold standard. Gene panels of four different sizes (i.e., 0.44-2.54 Mb) were selected for comparative analyses. The heterogeneity of TMB within and between cancer types is observed to be very high, and it becomes possible to obtain the exact TMB value as the size of the panel increases. In panels with limited size, it is particularly difficult to recognize patients with low TMB. In addition, the use of a general TMB cutoff can be quite misleading. The optimal cutoff value varies between 5 and 20, depending on the TMB distribution of the different tumor types. The use of comprehensive gene panels and the optimization of TMB cutoff values for different cancer types can make TMB a robust biomarker in precision oncology. Moreover, optimization of TMB can help accelerate translational medicine research, and by extension, delivery of personalized cancer care in the future.

Over a decade ago, longitudinal multiomics analysis was pioneered for early disease detection and individually tailored precision health interventions. However, high sample processing costs, expansive multiomics measurements along with complex data analysis have made this approach to precision/personalized medicine impractical. Here we describe in a case report, a more practical approach that uses fewer measurements, annual sampling, and faster decision making. We also show how this approach offers promise to detect an exceedingly rare and potentially fatal condition before it fully manifests. Specifically, we describe in the present case report how longitudinal multiomics monitoring (LMOM) helped detect a precancerous pancreatic tumor and led to a successful surgical intervention. The patient, enrolled in an annual blood-based LMOM since 2018, had dramatic changes in the June 2021 and 2022 annual metabolomics and proteomics results that prompted further clinical diagnostic testing for pancreatic cancer. Using abdominal magnetic resonance imaging, a 2.6 cm lesion in the tail of the patient's pancreas was detected. The tumor fluid from an aspiration biopsy had 10,000 times that of normal carcinoembryonic antigen levels. After the tumor was surgically resected, histopathological findings confirmed it was a precancerous pancreatic tumor. Postoperative omics testing indicated that most metabolite and protein levels returned to patient's 2018 levels. This case report illustrates the potentials of blood LMOM for precision/personalized medicine, and new ways of thinking medical innovation for a potentially life-saving early diagnosis of pancreatic cancer. Blood LMOM warrants future programmatic translational research with the goals of precision medicine, and individually tailored cancer diagnoses and treatments.

With their unusually large genome and particle sizes, giant viruses (GVs) defy the conventional definition of viruses. Although most GVs isolated infect unicellular protozoans, such as amoeba, studies in the last decade have established their much wider prevalence infecting most eukaryotic supergroups and some giant viral families with the potential to be human pathogens. Their complexity, almost autonomous life cycle, and enigmatic evolution necessitate the study of GVs. The accurate assessment of GV proteome is a veritable challenge. We have compared the coverage of global protein identification using different methods for GVs isolated in Mumbai, Mimivirus Bombay (MVB), Powai Lake Megavirus (PLMV), and Kurlavirus (KV), along with two previously studied GVs, Acanthamoeba polyphaga Mimivirus (APMV) and Marseillevirus (MV). Our study shows that the simultaneous use of in-gel and in-solution digestion methods can significantly increase the coverage of protein identification in the global proteome analysis of purified GV particles. Combining the two methods of analyses, we identified an additional 72 proteins in APMV and 114 in MV compared with what have been previously reported. Similarly, proteomes of MVB, PLMV, and KV were analyzed, and a total of 242 proteins in MVB, 287 proteins in PLMV, and 174 proteins in KV were identified. Our results suggest that a combined methodology of in-gel and in-solution methods is more efficient and opens up new avenues for innovation in global proteome analysis of GVs. Future planetary health research on GVs can benefit from consideration of a broader range of proteomics methodologies as illustrated by the present study.

This concise review and analysis offers an initial unpacking of a previously under-recognized issue within the microRNA research and communications field regarding the inadvertent use of "has" instead of "hsa" in article titles in the microRNA nomenclature. This subtle change, often the result of grammar auto correction tools, introduces considerable ambiguity and confusion among readers and researchers in reporting of microRNA-related discoveries. The impact of this issue cannot be underestimated, as precise and consistent nomenclature is vital for science communication and computational retrieval of relevant scientific literature and to advance science and innovation. We suggest that the recognition and correction of these often inadvertent "hsa" to "has" substitution errors are timely and important so as to ensure a higher level of accuracy throughout the writing and publication process in the microRNA field in particular. Doing so will also contribute to clarity and consistency in the field of microRNA research, ultimately improving scientific veracity, communication, and progress.

Nematode infections are common in both humans and livestock, with major adverse planetary health and economic impacts. Wuchereria bancrofti is a parasitic nematode that causes lymphatic filariasis, a neglected tropical disease that can lead to severe disability and deformity worldwide. For the long-term survival of the bancroftian parasites in the host, a complex immune invasion strategy is involved through immunomodulation. Therefore, immunomodulation can serve as a site of research and innovation for molecular targets. Macrophage migration inhibitory factor (MIF) is a pleiotropic cytokine crucial to the host antimicrobial alarm system and stress response. Interestingly, the nematode parasite W. bancrofti also produces two homologs of MIF (Wba-MIF1 and 2). Using a mass spectrometry-based phosphoproteomics approach, we report new findings on the immunomodulatory effect and signaling mechanism of Wba-MIF2 in macrophage cells. Accordingly, we observed 1201 phosphorylated sites on 467 proteins. Out of the 1201 phosphorylated sites, 1075, 117, and 9 were found on serine (S), threonine (T), and tyrosine (Y) residues, respectively. Our bioinformatics analysis led to identification of major pathways, including spliceosomes, T cell receptor signaling pathway, Th17 differentiation pathway, interleukin-17 signaling pathway, and insulin signaling pathway upon Wba-MIF2 treatment. Wba-MIF2 treatment also enriched CDK4, CDK1, and DNAPK kinases. The comparison of the signaling pathway of Wba-MIF2 with that of human-MIF suggests both share similar signaling pathways. These findings collectively offer new insights into the role and mechanism of Wba-MIF2 as an immunomodulator and inform future diagnostics and drug discovery research for W. bancrofti.

Breast cancer is the lead cause of cancer-related deaths among women globally. Breast cancer metastasis is a complex and still inadequately understood process and a key dimension of mortality attendant to breast cancer. This study reports dysregulated genes across metastatic stages and tissues, shedding light on their molecular interplay in disease pathogenesis and new possibilities for drug discovery. Comprehensive analyses of gene expression data from primary breast tumor, circulating tumor cells, and distant metastatic sites in the brain, lung, liver, and bone were conducted. Genes dysregulated across multiple stages and tissues were identified as metastatic cascade genes, and are further classified based on functional associations with metastasis-related mechanisms. Their interactions with HUB genes in interactome networks were scrutinized, followed by pathway enrichment analysis. Validation for their potential as targets included assessments for survival, druggability, prognostic marker status, secretome annotation, protein expression, and cell type marker association. Results displayed critical genes in the metastatic cascade and those specific to metastatic sites, revealing the involvement of the collagen degradation and assembly of collagen fibrils and other multimeric structure pathways in driving metastasis. Notably, pivotal cascade genes FABP4, CXCL12, APOD, and IGF1 emerged with high metastatic potential, linked to significant druggability and survival scores, establishing them as potential molecular targets. The significance of this research lies in its potential to uncover novel biomarkers for early detection, therapeutic targets, and a deeper understanding of the molecular mechanisms underpinning the metastatic cascade in breast cancer, and with an eye to precision/personalized medicine.