Proteomics-Based Identification of Dysregulated Proteins and Biomarker Discovery in Invasive Ductal Carcinoma, the Most Common Breast Cancer Subtype

Dynamic contrast-enhanced magnetic resonance imaging parameters combined with diffusion-weighted imaging for discriminating malignant lesions, molecular subtypes, and pathological grades in invasive ductal carcinoma patients

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters or diffusion-weighted imaging (DWI) findings provide prognostic information on breast cancer. However, the accuracy of a single MRI technique is unsatisfactory. This study intended to explore the combination of DWI and DCE-MRI parameters in discriminating molecular subtypes in invasive ductal carcinoma (IDC) patients. Eighty-two IDC patients who underwent breast DWI and DCE-MRI examinations were retrospectively analyzed. Eighty-six patients with benign masses were retrieved as benign controls. The combination of ADC value, Ktrans, Kep, Ve, and iAUC had a good ability to discriminate IDC patients (vs. benign controls) with an area under the curve (AUC) [95% confidence interval (CI)] of 0.961 (0.935-0.987). A nomogram-based prediction model with the above combination showed a good predictive value for IDC probability. The combination of ADC value, Ktrans, Kep, and iAUC also had a certain ability to discriminate pathological grade III (vs. I or II) [AUC (95% CI): 0.698 (0.572-0.825)] in IDC patients. Notably, ADC value (P=0.010) and Kep (P=0.043) differed in IDC patients with different molecular subtypes. Besides, ADC value was increased (P<0.001), but Ktrans (P=0.037) and Kep (P=0.004) were decreased in IDC patients with Lumina A (vs. other molecular subtypes). The combination of ADC value, Ktrans, Kep, had an acceptable ability to discriminate Luminal A (vs. other molecular subtypes) [AUC (95% CI): 0.845 (0.748-0.941)] in IDC patients. DWI combined with DCE-MRI parameters discriminates IDC from benign masses; it also identifies Luminal A and pathological grade III in IDC patients.

Salivary Extracellular Vesicles in Detection of Cancers Other than Head and Neck: A Systematic Review

Cancer is one of the leading causes of death worldwide. Evidence indicates that extracellular vesicles are involved in cancer development and may be used as promising biomarkers in cancer detection. Concomitantly, saliva constitutes a non-invasive and inexpensive source of biomarkers. This systematic review investigates the use of salivary extracellular vesicles in detecting cancers located outside of the head and neck. PubMed, Web of Science, Scopus, and Embase were thoroughly searched from database inception to 16 July 2024. Data from sixteen eligible studies were analyzed, including glioblastoma, lung, esophageal, gastric, prostate, hepatocellular, breast, and pancreatobiliary tract cancers. The findings highlight strong diagnostic potential for lung and esophageal cancers, where specific exosomal RNAs and proteins demonstrated high accuracy in distinguishing cancer patients from healthy individuals. Additionally, biomarkers in glioblastoma showed prognostic value, while those in hepatocellular and pancreatobiliary cancers exhibited potential for early detection. However, gastric and prostate cancer biomarkers showed limited reliability, and breast cancer biomarkers require further validation. In conclusion, salivary extracellular vesicles present potential in non-invasive detection across multiple cancer types; however, their diagnostic power needs further research, including standardization and large-scale validation.

Integrative metabolomic-proteomic analysis uncovers a new therapeutic approach in targeting rheumatoid arthritis

OBJECTIVE

Rheumatoid arthritis (RA) is a chronic inflammatory condition that, despite available approaches to manage the disease, lacks an efficient treatment and timely diagnosis. Using the most advanced omics technique, metabolomics and proteomics approach, we explored varied metabolites and proteins to identify unique metabolite-protein signatures involved in the disease pathogenesis of RA.

METHODS

Untargeted metabolomics (n = 20) and proteomics (n = 60) of RA patients' plasma were carried out by HPLC/LC-MS/MS and SWATH, respectively and analyzed by Metaboanalyst. The targets of metabolite retrieved by PharmMapper were matched with SWATH data, and joint pathway analysis was carried out. An in-vitro study of metabolites in TNF-α induced SW982 cells was conducted by Western, RT-PCR, scratch, and ROS scavenging assay. The effect of GUDCA was also evaluated in the CIA rat model.

RESULTS

A Total of 82 metabolites and 231 differential proteins were revealed. Porphyrin and chlorophyll pathway and its metabolite Glycoursodeoxycholic acid (GUDCA) was found to be significantly altered. In vitro analysis has shown that GUDCA reduces inflammation thus offering protection against ROS production and cell proliferation. PharmMapper analysis revealed that GUDCA was significantly linked with identified SWATH proteins insulin like growth factor-1(IGF1), and Transthyretin (TTR) and it upregulates the expression of IGF1 and downregulates the expression of TTR in both in vitro and in vivo models.

CONCLUSION

GUDCA was found to possess antioxidative, antiproliferative properties and an effective anti-inflammatory property at a low dosage. It may be considered as a potential therapeutic option for reducing the inflammatory parameters associated with RA.

Advancing precision and personalized breast cancer treatment through multi-omics technologies

Breast cancer is the most common malignant tumour in women, with more than 685,000 women dying of breast cancer each year. The heterogeneity of breast cancer complicates both treatment and diagnosis. Traditional methods based on histopathology and hormone receptor status are now no longer sufficient. Recently, advances in multi-omics techniques, including genomic, proteomic, and transcriptomic analyses, have deepened our understanding of breast cancer. Combining these approaches allows for precise molecular subtyping, which is essential for the detection of key mutations, protein interactions and gene expression patterns that are highly relevant to different therapeutic strategies. Genomic analyses have been effectively identifying key mutations in cancer. Meanwhile, proteomics and transcriptomics complement by identifying new therapeutic targets and elucidating gene expression dynamics. Integrating multi-omics and conventional diagnostics improves tumour characterisation and enables prognostic accuracy comparable to established standards and treatment response. Existing and emerging technologies enable real-time enhanced tumour follow-up and data analysis through liquid biopsy and artificial intelligence, respectively. Despite these clinical implementation challenges, multi-omics including clinical phenotyping offers significant potential for precision breast cancer treatment. This article describes recent advances in molecular subtyping and multi-omics technologies that are driving key innovations to optimise patient outcomes and further develop personalised medicine in the context of breast cancer care.

The human volatilome meets cancer diagnostics: past, present, and future of noninvasive applications

BACKGROUND

Cancer is a significant public health problem, causing dozens of millions of deaths annually. New cancer screening programs are urgently needed for early cancer detection, as this approach can improve treatment outcomes and increase patient survival. The search for affordable, noninvasive, and highly accurate cancer detection methods revealed a valuable source of tumor-derived metabolites in the human metabolome through the exploration of volatile organic compounds (VOCs) in noninvasive biofluids.

AIM OF REVIEW

This review discusses volatilomics-based approaches for cancer detection using noninvasive biomatrices (breath, saliva, skin secretions, urine, feces, and earwax). We presented the historical background, the latest approaches, and the required stages for clinical validation of volatilomics-based methods, which are still lacking in terms of making noninvasive methods available and widespread to the population. Furthermore, insights into the usefulness and challenges of volatilomics in clinical implementation steps for each biofluid are highlighted.

KEY SCIENTIFIC CONCEPTS OF REVIEW

We outline the methodologies for using noninvasive biomatrices with up-and-coming clinical applications in cancer diagnostics. Several challenges and advantages associated with the use of each biomatrix are discussed, aiming at encouraging the scientific community to strengthen efforts toward the necessary steps to speed up the clinical translation of volatile-based cancer detection methods, as well as discussing in favor of (i) hybrid applications (i.e., using more than one biomatrix) to describe metabolite modulations that can be "cancer volatile fingerprints" and (ii) in multi-omics approaches integrating genomics, transcriptomics, and proteomics into the volatilomic data, which might be a breakthrough for diagnostic purposes, onco-pathway assessment, and biomarker validations.

In Situ Immunofluorescence Imaging of Vital Human Pancreatic Tissue Using Fiber-Optic Microscopy

Purpose

Surgical resection is the only curative option for pancreatic carcinoma, but disease-free and overall survival times after surgery are limited due to early tumor recurrence, most often originating from local microscopic tumor residues (R1 resection). The intraoperative identification of microscopic tumor residues within the resection margin in situ could improve surgical performance. The aim of this study was to evaluate the effectiveness of fiber-optic microscopy for detecting microscopic residues in vital pancreatic cancer tissues. Experimental Design. Fresh whole-mount human pancreatic tissues, histological tissue slides, cell culture, and chorioallantoic membrane xenografts were analyzed. Specimens were stained with selected fluorophore-conjugated antibodies and studied using conventional wide-field and self-designed multicolor fiber-optic fluorescence microscopy instruments.

Results

Whole-mount vital human tissues and xenografts were stained and imaged using an in situ immunofluorescence protocol. Fiber-optic microscopy enabled the detection of epitope-based fluorescence in vital whole-mount tissue using fluorophore-conjugated antibodies and enabled visualization of microvascular, epithelial, and malignant tumor cells. Among the selected antigen-antibody pairs, antibody clones WM59, AY13, and 9C4 were the most promising for fiber-optic imaging in human tissue samples and for endothelial, tumor and epithelial cell detection.

Conclusions

Fresh dissected whole-mount tissue can be stained using direct exposure to selected antibody clones. Several antibody clones were identified that provided excellent immunofluorescence imaging of labeled structures, such as endothelial, epithelial, or EGFR-expressing cells. The combination of in situ immunofluorescence staining and fiber-optic microscopy visualizes structures in vital tissues and could be proposed as an useful tool for the in situ identification of residual tumor mass in patients with a high operative risk for incomplete resection.

Are Meteorin-Like Peptide and Asprosin Important in the Diagnosis of Breast Tumors?

INTRODUCTION

Breast cancer (BC) is one of the most common and leading causes of death in women. Therefore, early and accurate diagnosis is vital. In this study, meteorin-like (METRNL) peptide and asprosin levels were examined in breast tissue in invasive ductal carcinoma (IDC) of the breast, and the roles of these molecules in the diagnosis of BC were investigated.

METHODS

In this retrospective study, tissues from patients with BC in the Pathology Department Laboratory of Fırat University Faculty of Medicine, Elazığ, Turkey, were used. Samples from 30 patients were used. The control group consisted of healthy breast tissues from the same patients. The pathology group consisted of breast tissues with IDC from the same patients. Breast tissue samples from both groups were evaluated immunohistochemically for METRNL and asprosin.

RESULTS

Statistically significant differences were observed between both groups in terms of METRNL and asprosin. It was observed that METRNL and asprosin immunoreactivities were higher in breast tissues with IDC than in healthy breast tissues (p<0.001).

CONCLUSION

When the study results were evaluated, it was seen that there was a significant relationship between healthy breast tissues and the ones with IDC in terms of METRNL and asprosin. It is thought that both METRNL and asprosin may be really important in the future for the early diagnosis and treatment of BC.

Unlocking Overexpressed Membrane Proteins to Guide Breast Cancer Precision Medicine

Breast cancer (BC) is a prevalent form of cancer affecting women worldwide. However, the effectiveness of current BC drugs is limited by issues such as systemic toxicity, drug resistance, and severe side effects. Consequently, there is an urgent need for new therapeutic targets and improved tumor tracking methods. This study aims to address these challenges by proposing a strategy for identifying membrane proteins in tumors that can be targeted for specific BC therapy and diagnosis. The strategy involves the analyses of gene expressions in breast tumor and non-tumor tissues and other healthy tissues by using comprehensive bioinformatics analysis from The Cancer Genome Atlas (TCGA), UALCAN, TNM Plot, and LinkedOmics. By employing this strategy, we identified four transcripts (LRRC15, EFNA3, TSPAN13, and CA12) that encoded membrane proteins with an increased expression in BC tissue compared to healthy tissue. These four transcripts also demonstrated high accuracy, specificity, and accuracy in identifying tumor samples, as confirmed by the ROC curve. Additionally, tissue microarray (TMA) analysis revealed increased expressions of the four proteins in tumor tissues across all molecular subtypes compared to the adjacent breast tissue. Moreover, the analysis of human interactome data demonstrated the important roles of these proteins in various cancer-related pathways. Taken together, these findings suggest that LRRC15, EFNA3, TSPAN13, and CA12 can serve as potential biomarkers for improving cancer diagnosis screening and as suitable targets for therapy with reduced side effects and enhanced efficacy.

Recent Contributions of Mass Spectrometry-Based "Omics" in the Studies of Breast Cancer

Breast cancer (BC) is one of the most heterogeneous groups of cancer. As every biotype of BC is unique and presents a particular "omic" signature, they are increasingly characterized nowadays with novel mass spectrometry (MS) strategies. BC therapeutic approaches are primarily based on the two features of human epidermal growth factor receptor 2 (HER2) and estrogen receptor (ER) positivity. Various strategic MS implementations are reported in studies of BC also involving data independent acquisitions (DIAs) of MS which report novel differential proteomic, lipidomic, proteogenomic, phosphoproteomic, and metabolomic characterizations associated with the disease and its therapeutics. Recently many "omic" studies have aimed to identify distinct subsidiary biotypes for diagnosis, prognosis, and targets of treatment. Along with these, drug-induced-resistance phenotypes are characterized by "omic" changes. These identifying aspects of the disease may influence treatment outcomes in the near future. Drug quantifications and characterizations are also done regularly and have implications in therapeutic monitoring and in drug efficacy assessments. We report these studies, mentioning their implications toward the understanding of BC. We briefly provide the MS instrumentation principles that are adopted in such studies as an overview with a brief outlook on DIA-MS strategies. In all of these, we have chosen a model cancer for its revelations through MS-based "omics".

BREAST CANCER SCREENING IN ROMANIA: CHALLENGES AND OPPORTUNITIES FOR EARLY DETECTION

Breast cancer has surpassed lung cancer as the most common type of cancer globally, representing approximately 25% of all cancer cases and leading in cancer-related mortality among women. In Romania, breast cancer accounts for 26.9% of all female cancer diagnoses, with an increasing incidence and significant mortality rate despite one of the lowest incidence rates in Europe. The study highlights the disparities in breast cancer outcomes across Europe, with Romania showing lower survival rates compared to Western European countries. This disparity is partly attributed to the low participation in breast cancer screening programs, where only 9% of eligible Romanian women underwent mammography in 2020, far below the European average of 60%. The World Health Organization (WHO) and European Commission emphasize the importance of organized population-based screening for women aged 50-69, yet many barriers, including low health literacy, lack of awareness, and socio-economic challenges, hinder effective participation, especially among vulnerable populations. This study, conducted over three years at the "Alessandrescu Rusescu " National Institute for Mother and Child Health, involved 1,705 patients and aims to provide insights into improving breast cancer screening participation and outcomes in Romania.

Omics Technologies Improving Breast Cancer Research and Diagnostics

Breast cancer (BC) has yielded approximately 2.26 million new cases and has caused nearly 685,000 deaths worldwide in the last two years, making it the most common diagnosed cancer type in the world. BC is an intricate ecosystem formed by both the tumor microenvironment and malignant cells, and its heterogeneity impacts the response to treatment. Biomedical research has entered the era of massive omics data thanks to the high-throughput sequencing revolution, quick progress and widespread adoption. These technologies-liquid biopsy, transcriptomics, epigenomics, proteomics, metabolomics, pharmaco-omics and artificial intelligence imaging-could help researchers and clinicians to better understand the formation and evolution of BC. This review focuses on the findings of recent multi-omics-based research that has been applied to BC research, with an introduction to every omics technique and their applications for the different BC phenotypes, biomarkers, target therapies, diagnosis, treatment and prognosis, to provide a comprehensive overview of the possibilities of BC research.

Omics-Based Investigations of Breast Cancer

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.