Special Issues

Multi-Omics Approaches for Precision Medicine

Submission Deadline: 31 December 2024 View: 14 Submit to Special Issue

Guest Editors

Hao Zhang, Department of Neurosurgery, The Second Affiliated Hospital, Chongqing Medical University, China. E-mail: zhsw@hospital.cqmu.edu.cn

Nan Zhang, Biology Key Laboratory of Molecular Biophysics of the Ministry of Education College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China. E-mail: awekevin@onethird-lab.com

Kui Zhang, The Pritzker School of Molecular Engineering, The University of Chicago, United State. E-mail:Zhangk87@gmail.com; kuizhang@uchicago.edu

Summary

In this era of precision medicine and exciting advances, drug resistance remains an essential obstacle to cancer treatment. The development of targeted therapy based on increasingly revealed pathogenic mechanisms of cancer has contributed to overcoming drug resistance. The use of model organisms in target discovery and validation of small molecule drugs is becoming commonplace. A critical objective of this topic is the target discovery and validation of small-molecule drugs. Another important aspect of this topic is describing and elucidating novel molecular targets and pathways and insights into precision medicine.

 

Multi-omics approaches have emerged as powerful tools to investigate the complex nature of cancer and its response to therapy. These approaches integrate data from various sources, such as genomics, transcriptomics, proteomics, and metabolomics, to provide a comprehensive view of the molecular landscape of tumors. Using multi-omics approaches, researchers can identify new biomarkers, pathways, and targets that can guide the development of personalized cancer therapy.

 

This topic does not accept simple bioinformatics analysis studies that are not accompanied by in vitro or in vivo experiments for validation.

Potential topics include but are not limited to the following:

1. Bioinformatics research with validation to identify novel biomarkers and models based on cancer immunotherapy patients;

2. Pathogenic mechanisms of cancer in drug resistance;

3. Novel targeted therapy of cancer based on newly defined molecular mechanisms;

4. Biomarkers for cancer development;

5. The target discovery and validation of small-molecule drugs.


Keywords

Multi-omics; Drug Resistance; Biomarker; Molecular Target.

Published Papers


  • Open Access

    ARTICLE

    Using Multi-Omics Analysis to Explore Diagnostic Tool and Optimize Drug Therapy Selection for Patients with Glioma Based on Cross-Talk Gene Signature

    YUSHI YANG, CHUJIAO HU, SHAN LEI, XIN BAO, ZHIRUI ZENG, WENPENG CAO
    Oncology Research, DOI:10.32604/or.2024.046191
    (This article belongs to the Special Issue: Multi-Omics Approaches for Precision Medicine)
    Abstract Background: The heterogeneity of prognosis and treatment benefits among patients with gliomas is due to tumor microenvironment characteristics. However, biomarkers that reflect microenvironmental characteristics and predict the prognosis of gliomas are limited. Therefore, we aimed to develop a model that can effectively predict prognosis, differentiate microenvironment signatures, and optimize drug selection for patients with glioma. Materials and Methods: The CIBERSORT algorithm, bulk sequencing analysis, and single-cell RNA (scRNA) analysis were employed to identify significant cross-talk genes between M2 macrophages and cancer cells in glioma tissues. A predictive model was constructed based on cross-talk gene expression, and… More >

  • Open Access

    ARTICLE

    Multi-cohort comprehensive analysis unveiling the clinical value and therapeutic effect of GNAL in glioma

    ZHEN LIU, LIANGWANG YANG, ZHENGXING XIE, HUI YU, TIANYI GU, DAOMING SHI, NING CAI, SHENGHUA ZHUO
    Oncology Research, Vol.32, No.5, pp. 965-981, 2024, DOI:10.32604/or.2024.045769
    (This article belongs to the Special Issue: Multi-Omics Approaches for Precision Medicine)
    Abstract Clinical data indicates that glioma patients have poor treatment outcomes and clinical prognosis. The role of olfactory signaling pathway-related genes (OSPRGs) in glioma has not been fully elucidated. In this study, we aimed to investigate the role and relationship between OSPRGs and glioma. Univariate and multivariate Cox regression analyses were performed to assess the relationship between OSPRGs and the overall survival of glioma based on public cohorts, and the target gene (G Protein Subunit Alpha L, GNAL) was screened. The association of GNAL expression with clinicopathological characteristics, gene mutation landscape, tumor immune microenvironment (TIME), deoxyribonucleic acid… More >

  • Open Access

    ARTICLE

    Developing risk models and subtypes of autophagy-associated LncRNAs for enhanced prognostic prediction and precision in therapeutic approaches for liver cancer patients

    LU ZHANG, JINGUO CHU, YUSHAN YU
    Oncology Research, Vol.32, No.4, pp. 703-716, 2024, DOI:10.32604/or.2023.030988
    (This article belongs to the Special Issue: Multi-Omics Approaches for Precision Medicine)
    Abstract Background: Limited research has been conducted on the influence of autophagy-associated long non-coding RNAs (ARLncRNAs) on the prognosis of hepatocellular carcinoma (HCC). Methods: We analyzed 371 HCC samples from TCGA, identifying expression networks of ARLncRNAs using autophagy-related genes. Screening for prognostically relevant ARLncRNAs involved univariate Cox regression, Lasso regression, and multivariate Cox regression. A Nomogram was further employed to assess the reliability of Riskscore, calculated from the signatures of screened ARLncRNAs, in predicting outcomes. Additionally, we compared drug sensitivities in patient groups with differing risk levels and investigated potential biological pathways through enrichment analysis, using… More >

  • Open Access

    ARTICLE

    Investigation of the feasibility of NRAV as a biomarker for hepatocellular carcinoma

    JUN LIU, WENLI LI, RUYUE LU, JIAQING XU, CHUNHUI JIANG, JUNLIN DUAN, LINGZHI ZHANG, GUANFU WANG, JIAXI CHEN
    Oncology Research, Vol.32, No.4, pp. 717-726, 2024, DOI:10.32604/or.2023.043575
    (This article belongs to the Special Issue: Multi-Omics Approaches for Precision Medicine)
    Abstract The long non-coding RNA, Negative Regulator of Antiviral Response (NRAV) has been identified as a participant in both respiratory virus replication and immune checkpoints, however, its involvement in pan-cancer immune regulation and prognosis, particularly those of hepatocellular carcinoma (HCC), remains unclear. To address this knowledge gap, we analyzed expression profiles obtained from The Cancer Genome Atlas (TCGA) database, comparing normal and malignant tumor tissues. We found that NRAV expression is significantly upregulated in tumor tissues compared to adjacent nontumor tissues. Kaplan-Meier (K-M) analysis revealed the prognostic power of NRAV, wherein overexpression was significantly linked to… More >

  • Open Access

    ARTICLE

    CRABP2 regulates infiltration of cancer-associated fibroblasts and immune response in melanoma

    SHUANGSHUANG ZENG, XI CHEN, QIAOLI YI, ABHIMANYU THAKUR, HUI YANG, YUANLIANG YAN, SHAO LIU
    Oncology Research, Vol.32, No.2, pp. 261-272, 2024, DOI:10.32604/or.2023.042345
    (This article belongs to the Special Issue: Multi-Omics Approaches for Precision Medicine)
    Abstract Finding biomarkers for immunotherapy is an urgent issue in cancer treatment. Cellular retinoic acid-binding protein 2 (CRABP2) is a controversial factor in the occurrence and development of human tumors. However, there is limited research on the relationship between CRABP2 and immunotherapy response. This study found that negative correlations of CRABP2 and immune checkpoint markers (PD-1, PD-L1, and CTLA-4) were observed in breast invasive carcinoma (BRCA), skin cutaneous melanoma (SKCM), stomach adenocarcinoma (STAD) and testicular germ cell tumors (TGCT). In particular, in SKCM patients who were treated with PD-1 inhibitors, high levels of CRABP2 predicted poor… More >

  • Open Access

    ARTICLE

    Leveraging diverse cell-death patterns to predict the clinical outcome of immune checkpoint therapy in lung adenocarcinoma: Based on muti-omics analysis and vitro assay

    HONGYUAN LIANG, YANQIU LI, YONGGANG QU, LINGYUN ZHANG
    Oncology Research, Vol.32, No.2, pp. 393-407, 2024, DOI:10.32604/or.2023.031134
    (This article belongs to the Special Issue: Multi-Omics Approaches for Precision Medicine)
    Abstract Advanced LUAD shows limited response to treatment including immune therapy. With the development of sequencing omics, it is urgent to combine high-throughput multi-omics data to identify new immune checkpoint therapeutic response markers. Using GSE72094 (n = 386) and GSE31210 (n = 226) gene expression profile data in the GEO database, we identified genes associated with lung adenocarcinoma (LUAD) death using tools such as “edgeR” and “maftools” and visualized the characteristics of these genes using the “circlize” R package. We constructed a prognostic model based on death-related genes and optimized the model using LASSO-Cox regression methods.… More >

  • Open Access

    ARTICLE

    Extensive prediction of drug response in mutation-subtype-specific LUAD with machine learning approach

    KEGANG JIA, YAWEI WANG, QI CAO, YOUYU WANG
    Oncology Research, Vol.32, No.2, pp. 409-419, 2024, DOI:10.32604/or.2023.042863
    (This article belongs to the Special Issue: Multi-Omics Approaches for Precision Medicine)
    Abstract Background: Lung cancer is the most prevalent cancer diagnosis and the leading cause of cancer death worldwide. Therapeutic failure in lung cancer (LUAD) is heavily influenced by drug resistance. This challenge stems from the diverse cell populations within the tumor, each having unique genetic, epigenetic, and phenotypic profiles. Such variations lead to varied therapeutic responses, thereby contributing to tumor relapse and disease progression. Methods: The Genomics of Drug Sensitivity in Cancer (GDSC) database was used in this investigation to obtain the mRNA expression dataset, genomic mutation profile, and drug sensitivity information of NSCLS. Machine Learning… More >

  • Open Access

    ARTICLE

    Polo-like kinase 1 suppresses lung adenocarcinoma immunity through necroptosis

    PENGCHENG ZHANG, XINGLONG ZHANG, YONGFU ZHU, YIYI CUI, JING XU, WEIPING ZHANG
    Oncology Research, Vol.31, No.6, pp. 937-953, 2023, DOI:10.32604/or.2023.030933
    (This article belongs to the Special Issue: Multi-Omics Approaches for Precision Medicine)
    Abstract Polo-like kinase 1 (PLK1) plays a crucial role in cell mitosis and has been associated with necroptosis. However, the role of PLK1 and necroptosis in lung adenocarcinoma (LA) remains unclear. In this study, we analyzed The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression databases to evaluate the prognostic value and mechanistic role of PLK1 in LA. PLK1 was found to be highly expressed in LA and was positively associated with advanced disease staging and poor survival outcomes. Functional enrichment analysis showed that PLK1 was involved in cell mitosis, neurotransmitter transmission, and drug metabolism. Further analysis… More >

    Graphic Abstract

    Polo-like kinase 1 suppresses lung adenocarcinoma immunity through necroptosis

  • Open Access

    ARTICLE

    Identification of lncRNAs associated with T cells as potential biomarkers and therapeutic targets in lung adenocarcinoma

    LU SUN, HUAICHENG TAN, TING YU, RUICHAO LIANG
    Oncology Research, Vol.31, No.6, pp. 967-988, 2023, DOI:10.32604/or.2023.042309
    (This article belongs to the Special Issue: Multi-Omics Approaches for Precision Medicine)
    Abstract Lung adenocarcinoma (LUAD) is the most common and deadliest subtype of lung cancer. To select more targeted and effective treatments for individuals, further advances in classifying LUAD are urgently needed. The number, type, and function of T cells in the tumor microenvironment (TME) determine the progression and treatment response of LUAD. Long noncoding RNAs (lncRNAs), may regulate T cell differentiation, development, and activation. Thus, our aim was to identify T cell-related lncRNAs (T cell-Lncs) in LUAD and to investigate whether T cell-Lncs could serve as potential stratifiers and therapeutic targets. Seven T cell-Lncs were identified… More >

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