Targeted proteomics using parallel reaction monitoring confirms salivary proteins indicative of metastatic triple-negative breast cancer

Giri, Kuldeep; Maity, Sudipa; Ambatipudi, Kiran

doi:10.1016/j.jprot.2022.104701

Cited by 8 publications

(4 citation statements)

References 41 publications

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“…As it preserves good-quality genomic DNA [ 81 ], saliva was recommended as a potential alternative for detecting hereditary BC mutations using Next Generation Sequencing (NGS) [ 82 ]. Targeted proteomics-based analyses have highlighted the peptide-based specific signatures in saliva as putative predictors to distinguish between TNBC and healthy subjects [ 83 ]. Untargeted metabolomics-based approaches and bioinformatics have unveiled the salivary metabolite profiles in women with BC, highlighting the up- or downregulated metabolites associated with BC and putative useful biomarkers for BC [ 84 ].…”

Section: Breast Cancer Investigation In the Multi-omics Eramentioning

confidence: 99%

“…To reveal the full mRNA transcriptome and develop a test based on the detection of cell-free RNA from saliva, Bentata et al showed an enrichment of genes with a functional annotation in alternative splicing that can serve as an indicator for BC [ 85 ]. Hence, integrative salivaomics targets the discovery of noninvasive biomarkers and includes salivary genomics [ 82 ], epigenomics, transcriptomics [ 85 ], proteomics [ 83 ], metabolomics [ 84 , 86 ], immunomics, and microbiomics approaches [ 87 ]. Also, salivaomics is useful for a determination of the metabolic characteristics of saliva, depending on the molecular biological subtype of BC in correlation with the expression levels of HER2, estrogen receptors (ER), and progesterone receptors (PR) [ 28 ].…”

Section: Breast Cancer Investigation In the Multi-omics Eramentioning

confidence: 99%

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Omics-Based Investigations of Breast Cancer

Neagu,

Whitham,

Bruno

et al. 2023

Molecules

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Breast cancer (BC) is characterized by an extensive genotypic and phenotypic heterogeneity. In-depth investigations into the molecular bases of BC phenotypes, carcinogenesis, progression, and metastasis are necessary for accurate diagnoses, prognoses, and therapy assessments in predictive, precision, and personalized oncology. This review discusses both classic as well as several novel omics fields that are involved or should be used in modern BC investigations, which may be integrated as a holistic term, onco-breastomics. Rapid and recent advances in molecular profiling strategies and analytical techniques based on high-throughput sequencing and mass spectrometry (MS) development have generated large-scale multi-omics datasets, mainly emerging from the three ”big omics”, based on the central dogma of molecular biology: genomics, transcriptomics, and proteomics. Metabolomics-based approaches also reflect the dynamic response of BC cells to genetic modifications. Interactomics promotes a holistic view in BC research by constructing and characterizing protein–protein interaction (PPI) networks that provide a novel hypothesis for the pathophysiological processes involved in BC progression and subtyping. The emergence of new omics- and epiomics-based multidimensional approaches provide opportunities to gain insights into BC heterogeneity and its underlying mechanisms. The three main epiomics fields (epigenomics, epitranscriptomics, and epiproteomics) are focused on the epigenetic DNA changes, RNAs modifications, and posttranslational modifications (PTMs) affecting protein functions for an in-depth understanding of cancer cell proliferation, migration, and invasion. Novel omics fields, such as epichaperomics or epimetabolomics, could investigate the modifications in the interactome induced by stressors and provide PPI changes, as well as in metabolites, as drivers of BC-causing phenotypes. Over the last years, several proteomics-derived omics, such as matrisomics, exosomics, secretomics, kinomics, phosphoproteomics, or immunomics, provided valuable data for a deep understanding of dysregulated pathways in BC cells and their tumor microenvironment (TME) or tumor immune microenvironment (TIMW). Most of these omics datasets are still assessed individually using distinct approches and do not generate the desired and expected global-integrative knowledge with applications in clinical diagnostics. However, several hyphenated omics approaches, such as proteo-genomics, proteo-transcriptomics, and phosphoproteomics-exosomics are useful for the identification of putative BC biomarkers and therapeutic targets. To develop non-invasive diagnostic tests and to discover new biomarkers for BC, classic and novel omics-based strategies allow for significant advances in blood/plasma-based omics. Salivaomics, urinomics, and milkomics appear as integrative omics that may develop a high potential for early and non-invasive diagnoses in BC. Thus, the analysis of the tumor circulome is considered a novel frontier in liquid biopsy. Omics-based investigations have applications in BC modeling, as well as accurate BC classification and subtype characterization. The future in omics-based investigations of BC may be also focused on multi-omics single-cell analyses.

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Section: Breast Cancer Investigation In the Multi-omics Eramentioning

confidence: 99%

Section: Breast Cancer Investigation In the Multi-omics Eramentioning

confidence: 99%

Omics-Based Investigations of Breast Cancer

Neagu,

Whitham,

Bruno

et al. 2023

Molecules

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“…Because of the high throughput nature and the rapid development of MS technologies are fostering Point Of Care (POC) devices in clinical settings to directly analyze biological materials like blood, tissue, sweat, urine, saliva, etc. [ 22 , 23 ]. Similarly, the targeted proteomics approaches like the Multiple (or selected) reaction monitoring-mass spectrometry (MRM/SRM) have been employed to validate proteomic biomarkers.…”

Section: Introductionmentioning

confidence: 99%

A large-scale targeted proteomics of serum and tissue shows the utility of classifying high grade and low grade meningioma tumors

Halder,

Biswas,

Chauhan

et al. 2023

Clin Proteom

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Background Meningiomas are the most prevalent primary brain tumors. Due to their increasing burden on healthcare, meningiomas have become a pivot of translational research globally. Despite many studies in the field of discovery proteomics, the identification of grade-specific markers for meningioma is still a paradox and requires thorough investigation. The potential of the reported markers in different studies needs further verification in large and independent sample cohorts to identify the best set of markers with a better clinical perspective. Methods A total of 53 fresh frozen tumor tissue and 51 serum samples were acquired from meningioma patients respectively along with healthy controls, to validate the prospect of reported differentially expressed proteins and claimed markers of Meningioma mined from numerous manuscripts and knowledgebases. A small subset of Glioma/Glioblastoma samples were also included to investigate inter-tumor segregation. Furthermore, a simple Machine Learning (ML) based analysis was performed to evaluate the classification accuracy of the list of proteins. Results A list of 15 proteins from tissue and 12 proteins from serum were found to be the best segregator using a feature selection-based machine learning strategy with an accuracy of around 80% in predicting low grade (WHO grade I) and high grade (WHO grade II and WHO grade III) meningiomas. In addition, the discriminant analysis could also unveil the complexity of meningioma grading from a segregation pattern, which leads to the understanding of transition phases between the grades. Conclusions The identified list of validated markers could play an instrumental role in the classification of meningioma as well as provide novel clinical perspectives in regard to prognosis and therapeutic targets.

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“…In contrast, PRM was developed with an orbitrap mass analyzer to elucidate ion signals with high tolerance and ion trapping capability, enhancing the S/N ratio[121]. Using PRM, individual salivary peptide markers from Lipocalin-1, Plastin-2, and SMR−3B were quantified to detect aggressiveness in TNBC patients[122,123]. Additionally, the potential of PRM can be expanded through the modified development of an internal standard triggeredparallel reaction monitoring (IS-PRM), which improves the quality of spectra and provides more relevant information about the peptide of interest.…”

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confidence: 99%

Realm of proteomics in breast cancer management and drug repurposing to alleviate intricacies of treatment

Behera,

Bisht,

Giri

et al. 2023

Proteomics Clinical Apps

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Breast cancer, a multi‐networking heterogeneous disease, has emerged as a serious impediment to progress in clinical oncology. Although technological advancements and emerging cancer research studies have mitigated breast cancer lethality, a precision cancer‐oriented solution has not been achieved. Thus, this review will persuade the acquiescence of proteomics‐based diagnostic and therapeutic options in breast cancer management. Recently, the evidence of breast cancer health surveillance through imaging proteomics, single‐cell proteomics, interactomics, and post‐translational modification (PTM) tracking, to construct proteome maps and proteotyping for stage‐specific and sample‐specific cancer subtyping have outperformed conventional ways of dealing with breast cancer by increasing diagnostic efficiency, prognostic value, and predictive response. Additionally, the paradigm shift in applied proteomics for designing a chemotherapy regimen to identify novel drug targets with minor adverse effects has been elaborated. Finally, the potential of proteomics in alleviating the occurrence of chemoresistance and enhancing reprofiled drugs' effectiveness to combat therapeutic obstacles has been discussed. Owing to the enormous potential of proteomics techniques, the clinical recognition of proteomics in breast cancer management can be achievable and therapeutic intricacies can be surmountable.

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Targeted proteomics using parallel reaction monitoring confirms salivary proteins indicative of metastatic triple-negative breast cancer

Cited by 8 publications

References 41 publications

Omics-Based Investigations of Breast Cancer

Omics-Based Investigations of Breast Cancer

A large-scale targeted proteomics of serum and tissue shows the utility of classifying high grade and low grade meningioma tumors

Realm of proteomics in breast cancer management and drug repurposing to alleviate intricacies of treatment

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