Circulating and non-circulating proteins and nucleic acids as biomarkers and therapeutic molecules in ovarian cancer

Utkarsh, Kumar; Abhishek, Kumar; Aditi, Aditi; Khan, Azhar U.; Nayyar, Ashima; Haque, Shabirul; Iqbal, Shams

doi:10.1016/j.gendis.2022.07.004

Cited by 4 publications

(6 citation statements)

References 133 publications

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“…An oncogenic biomarker is a biomolecule that may be found in the body's tissues and fluids and can be used to recognize the presence of cancer cells. Cancer cells secrete proteins, carbohydrates [93], or nucleic acids as biomarkers during carcinogenesis [94]. The evaluation of the biomarker level aids in the early detection of cancer and its possibility of relapse, which in turn improves related monitoring and therapeutic efficacy.…”

Section: Identification Of Biomarkers For Detection Of Cancermentioning

confidence: 99%

Recent Advances in Nanomaterials-Based Targeted Drug Delivery for Preclinical Cancer Diagnosis and Therapeutics

et al. 2023

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Nano-oncology is a branch of biomedical research and engineering that focuses on using nanotechnology in cancer diagnosis and treatment. Nanomaterials are extensively employed in the field of oncology because of their minute size and ultra-specificity. A wide range of nanocarriers, such as dendrimers, micelles, PEGylated liposomes, and polymeric nanoparticles are used to facilitate the efficient transport of anti-cancer drugs at the target tumor site. Real-time labeling and monitoring of cancer cells using quantum dots is essential for determining the level of therapy needed for treatment. The drug is targeted to the tumor site either by passive or active means. Passive targeting makes use of the tumor microenvironment and enhanced permeability and retention effect, while active targeting involves the use of ligand-coated nanoparticles. Nanotechnology is being used to diagnose the early stage of cancer by detecting cancer-specific biomarkers using tumor imaging. The implication of nanotechnology in cancer therapy employs photoinduced nanosensitizers, reverse multidrug resistance, and enabling efficient delivery of CRISPR/Cas9 and RNA molecules for therapeutic applications. However, despite recent advancements in nano-oncology, there is a need to delve deeper into the domain of designing and applying nanoparticles for improved cancer diagnostics.

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Section: Identification Of Biomarkers For Detection Of Cancermentioning

confidence: 99%

Recent Advances in Nanomaterials-Based Targeted Drug Delivery for Preclinical Cancer Diagnosis and Therapeutics

et al. 2023

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“…CCNE1 amplification, occurring in 15-20% of HGSC cases (Bell et al, 2011; Jamalzadeh et al, 2022; Marone et al, 1998), has been linked to HGSC patient survival (Chan et al, 2020; Jamalzadeh et al, 2022; Stronach et al, 2018). WFDC2 is a well-established ovarian cancer biomarker (AlSomairi et al, 2024; Braicu et al, 2022; Utkarsh et al, 2023) and is also associated with HGSC patient survival (James et al, 2022). PPIB was selected as a control gene, and it is already used in several ovarian cancer studies by RNAscope assay and RT-PCR analysis (Desbois et al, 2020; Pan & Ma, 2020).…”

Section: Introductionmentioning

confidence: 99%

Comparative Analysis of Gene Expression Analysis Methods for RNA In Situ Hybridization Images

Ariotta,

Azzalini,

Canzonieri

et al. 2024

Preprint

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Gene expression analysis is pivotal in cancer research and clinical practice. While traditional methods lack spatial context, RNA in situ hybridization (RNA-ISH) is a powerful technique that retains spatial tissue information. Here, we investigated RNAscope score, RT-droplet digital PCR (RT-ddPCR), and automated QuantISH and QuPath in quantifying RNA-ISH expression values from formalin-fixed paraffin-embedded samples. We compared the methods using high-grade serous ovarian carcinoma samples, focusing on CCNE1, WFDC2, and PPIB genes. Our findings demonstrate good concordance between automated methods and RNAscope, with RT-ddPCR showing less concordance. We conclude that QuantISH exhibits robust performance, even for low-expressed genes like CCNE1, showcasing its modular design and enhancing accessibility as a viable alternative for gene expression analysis.

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“…Collectively, these elements contribute to the intricate and dynamic protein composition found in serum. 14 Serum proteomics, as a subset of proteomics, offers a potent and all-encompassing method for investigating the complete protein landscape present in blood samples. 13 , 15 The fundamental approach involves systematically analyzing alterations in the blood proteome throughout the progression of the disease to identify biomarkers specific to that particular condition.…”

Section: Introductionmentioning

confidence: 99%

Serum Proteomic Analysis Revealed Biomarkers for Eosinophilic Chronic Rhinosinusitis with Nasal Polyps Pathophysiology

Chen,

Gao,

Liu

et al. 2024

JIR

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Background Individuals with eosinophilic chronic rhinosinusitis with nasal polyps(eCRSwNP) exhibited worse outcomes and higher postoperative recurrence rates. This study aimed to identify biomarkers that can aid in the early differentiation of eCRSwNP and enhance our comprehension of its pathophysiology. Methods We recruited two independent cohorts. In the discovery cohort, CRSwNP was categorized into eCRSwNP and non-eosinophilic CRSwNP(neCRSwNP), and serum proteomics was performed to identify differentially expressed proteins between the two groups. These candidate proteins were chosen and confirmed in the validation cohort using an enzyme-linked immunosorbent assay (ELISA), Western blot (WB), quantitative real time-polymerase chain reaction (qRT-PCR), immunofluorescence (IF), and their predictive values and associations with tissue eosinophilic pathophysiology were evaluated. Results We identified a total of 39 differential proteins between the two groups, including 20 proteins upregulated and 19 downregulated in the eCRSwNP group. Further validation was conducted on the top 5 proteins that were up or down-regulated. Results from the ELISA showed that levels of serum MRC1, CDH13, and MMP2 were significantly higher, TRIM28 was lower in the eCRSwNP group compared to the neCRSwNP group (all P<0.05), and serum MRC1 (AUC=0.742, P<0.001) and MMP2 (AUC=0.766, P<0.001) levels exhibited promising predicting values for eCRSwNP. Moreover, qRT-PCR and WB analysis found that MMP2 and MRC1 expressions were enhanced in the eCRSwNP group compared to the neCRSwNP group (all P<0.01), and their levels were positively correlated with the number and percentages of tissue eosinophils (all P<0.01). The IF suggested that MMP2 and MRC1 were overexpressed in the nasal polyps tissues of eCRSwNP patients, and MMP2 was mainly located on eosinophils. Conclusion Circulating proteins identified by proteomics could serve as potential preoperative biomarkers for distinguishing eCRSwNP. Among them, MMP2 was enhanced in eCRSwNP and correlated with tissue eosinophilia, which provided valuable insights into the pathophysiology of eCRSwNP.

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Circulating and non-circulating proteins and nucleic acids as biomarkers and therapeutic molecules in ovarian cancer

Cited by 4 publications

References 133 publications

Recent Advances in Nanomaterials-Based Targeted Drug Delivery for Preclinical Cancer Diagnosis and Therapeutics

Recent Advances in Nanomaterials-Based Targeted Drug Delivery for Preclinical Cancer Diagnosis and Therapeutics

Comparative Analysis of Gene Expression Analysis Methods for RNA In Situ Hybridization Images

Serum Proteomic Analysis Revealed Biomarkers for Eosinophilic Chronic Rhinosinusitis with Nasal Polyps Pathophysiology

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