Multi-Omics Model Applied to Cancer Genetics

Pettini, Francesco; Visibelli, Anna; Cicaloni, Vittoria; Iovinelli, Daniele; Spiga, Ottavia

doi:10.3390/ijms22115751

Cited by 26 publications

(17 citation statements)

References 132 publications

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“…To date, the rapid growth of microarray and high-throughput sequencing techniques has generated enormous amounts of data available in either web-based platforms or comprehensive tools that allow us to properly monitor tumor progression at various levels, including genomics, epigenomics, transcriptomics, proteomics, and metabolomics 54 , 55 . The underlying pathogenesis of tumors in general and lung cancer, in particular, has thus been reported to be dominated by specific somatic genomic alterations.…”

Section: Discussionmentioning

confidence: 99%

Prognostic and Immune Infiltration Value of Proteasome Assembly Chaperone (PSMG) Family Genes in Lung Adenocarcinoma

Xuan¹,

Yeh²,

Su³

et al. 2023

Int. J. Med. Sci.

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The complexity of lung adenocarcinoma (LUAD) including many interacting biological processes makes it difficult to find therapeutic biomarkers for treatment. Previous studies demonstrated that PSMG (proteasome assembly chaperone) family members regulate the degradation of abnormal proteins. However, transcript expressions of this gene family in LUAD still need to be more fully investigated. Therefore, we used a holistic bioinformatics approach to explore PSMG genes involved in LUAD patients by integrating several high-throughput databases and tools including The Cancer Genome Atlas (TCGA), and Kaplan-Meier plotter database. These data demonstrated that PSMG3 and PSMG4 were expressed at significantly higher levels in neoplastic cells than in normal lung tissues. Notably, increased expressions of these proteins were correlated with poor prognoses of lung cancer patients, which probably confirmed their fundamental roles in the staging of LUAD tumors. Meanwhile, it was also indicated that there were positive correlations between PSMG family genes and the immune response, metabolism of ubiquinone, cell cycle regulatory pathways, and heat shock protein 90 (HSP90)/phosphatidylinositol 3-kinase (PI3K)/Wnt signaling. Experimental data also confirmed that the knockdown of PSMG4 in LUAD cell lines decreased cell proliferation and influenced expressions of downstream molecules. Collectively, this study revealed that PSMG family members are novel prognostic biomarkers for LUAD progression, which also provide new therapeutic targets of LUAD patients.

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Section: Discussionmentioning

confidence: 99%

Prognostic and Immune Infiltration Value of Proteasome Assembly Chaperone (PSMG) Family Genes in Lung Adenocarcinoma

Xuan¹,

Yeh²,

Su³

et al. 2023

Int. J. Med. Sci.

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“…Owing to impressive advances in high-throughput technologies, multi-omics approaches are now being intensively pursued for in-depth studies of individual cancer types and their response to therapeutic regimens [ 248 , 249 , 250 , 251 ]. Multiple levels of cellular perturbations can be investigated in detail in different tissues, tumor samples and in single cells.…”

Section: Discussionmentioning

confidence: 99%

From Omics to Multi-Omics Approaches for In-Depth Analysis of the Molecular Mechanisms of Prostate Cancer

Nevedomskaya

Haendler

2022

IJMS

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Cancer arises following alterations at different cellular levels, including genetic and epigenetic modifications, transcription and translation dysregulation, as well as metabolic variations. High-throughput omics technologies that allow one to identify and quantify processes involved in these changes are now available and have been instrumental in generating a wealth of steadily increasing data from patient tumors, liquid biopsies, and from tumor models. Extensive investigation and integration of these data have led to new biological insights into the origin and development of multiple cancer types and helped to unravel the molecular networks underlying this complex pathology. The comprehensive and quantitative analysis of a molecule class in a biological sample is named omics and large-scale omics studies addressing different prostate cancer stages have been performed in recent years. Prostate tumors represent the second leading cancer type and a prevalent cause of cancer death in men worldwide. It is a very heterogenous disease so that evaluating inter- and intra-tumor differences will be essential for a precise insight into disease development and plasticity, but also for the development of personalized therapies. There is ample evidence for the key role of the androgen receptor, a steroid hormone-activated transcription factor, in driving early and late stages of the disease, and this led to the development and approval of drugs addressing diverse targets along this pathway. Early genomic and transcriptomic studies have allowed one to determine the genes involved in prostate cancer and regulated by androgen signaling or other tumor-relevant signaling pathways. More recently, they have been supplemented by epigenomic, cistromic, proteomic and metabolomic analyses, thus, increasing our knowledge on the intricate mechanisms involved, the various levels of regulation and their interplay. The comprehensive investigation of these omics approaches and their integration into multi-omics analyses have led to a much deeper understanding of the molecular pathways involved in prostate cancer progression, and in response and resistance to therapies. This brings the hope that novel vulnerabilities will be identified, that existing therapies will be more beneficial by targeting the patient population likely to respond best, and that bespoke treatments with increased efficacy will be available soon.

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“…The integration of different types of omics data, combined with prior knowledge of regulation pathways, shows us a much more precise vision of activities inside sarcoma cells and may discover novel regulatory mechanisms as well. Unsupervised integrations identify every correlation among omics data, extracting biological process behind cancer progression, whereas supervised methods based on known phenotype knowledge improve the accuracy for cancer detection (52). These advanced research methods allow us to further study the complete picture of sarcoma as well as other malignancies, with accuracy, reliability, and comprehensiveness.…”

Section: Advantages and Drawbacks Of Applying Multi-omics Approachmentioning

confidence: 99%

Application of Multi-Omics Approach in Sarcomas: A Tool for Studying Mechanism, Biomarkers, and Therapeutic Targets

Zou

Sun

et al. 2022

Front. Oncol.

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Sarcomas are rare, heterogeneous mesenchymal neoplasms with various subtypes, each exhibiting unique genetic characteristics. Although studies have been conducted to improve the treatment for sarcomas, the specific development from normal somatic cells to sarcoma cells is still unclear and needs further research. The diagnosis of sarcomas depends heavily on the pathological examination, which is yet a difficult work and requires expert analysis. Advanced treatment like precise medicine optimizes the efficacy of treatment and the prognosis of sarcoma patients, yet, in sarcomas, more studies should be done to put such methods in clinical practice. The revolution of advanced technology has pushed the multi-omics approach to the front, and more could be learnt in sarcomas with such methods. Multi-omics combines the character of each omics techniques, analyzes the mechanism of tumor cells from different levels, which makes up for the shortage of single-omics, and gives us an integrated picture of bioactivities inside tumor cells. Multi-omics research of sarcomas has reached appreciable progress in recent years, leading to a better understanding of the mutation, proliferation, and metastasis of sarcomas. With the help of multi-omics approach, novel biomarkers were found, with promising effects in improving the process of diagnosis, prognosis anticipation, and treatment decision. By analyzing large amounts of biological features, subtype clustering could be done in a better precision, which may be useful in the clinical procedure. In this review, we summarized recent discoveries using multi-omics approach in sarcomas, discussed their merits and challenges, and concluded with future perspectives of the sarcoma research.

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Multi-Omics Model Applied to Cancer Genetics

Cited by 26 publications

References 132 publications

Prognostic and Immune Infiltration Value of Proteasome Assembly Chaperone (PSMG) Family Genes in Lung Adenocarcinoma

Prognostic and Immune Infiltration Value of Proteasome Assembly Chaperone (PSMG) Family Genes in Lung Adenocarcinoma

From Omics to Multi-Omics Approaches for In-Depth Analysis of the Molecular Mechanisms of Prostate Cancer

Application of Multi-Omics Approach in Sarcomas: A Tool for Studying Mechanism, Biomarkers, and Therapeutic Targets

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