High-throughput proteomics of breast cancer interstitial fluid: identification of tumor subtype-specific serologically relevant biomarkers

Coordinated inflammation and immune response transcriptional regulation in breast cancer molecular subtypes

Breast cancer, characterized by its complexity and diversity, presents significant challenges in understanding its underlying biology. In this study, we employed gene co-expression network analysis to investigate the gene composition and functional patterns in breast cancer subtypes and normal breast tissue. Our objective was to elucidate the detailed immunological features distinguishing these tumors at the transcriptional level and to explore their implications for diagnosis and treatment. The analysis identified nine distinct gene module clusters, each representing unique transcriptional signatures within breast cancer subtypes and normal tissue. Interestingly, while some clusters exhibited high similarity in gene composition between normal tissue and certain subtypes, others showed lower similarity and shared traits. These clusters provided insights into the immune responses within breast cancer subtypes, revealing diverse immunological functions, including innate and adaptive immune responses. Our findings contribute to a deeper understanding of the molecular mechanisms underlying breast cancer subtypes and highlight their unique characteristics. The immunological signatures identified in this study hold potential implications for diagnostic and therapeutic strategies. Additionally, the network-based approach introduced herein presents a valuable framework for understanding the complexities of other diseases and elucidating their underlying biology.

Differential expression of NAT1 pharmacogene in hormone receptor positive vs. negative female breast tumors may affect drug treatment

Studies have reported overexpression of NAT1 gene for xenobiotic metabolizing arylamine N-acetyltransferase type 1 in estrogen receptor positive breast tumors, and this association has been linked to patient chemoresistance and response to tamoxifen. We probed the expression of NAT1, using quantitative reverse transcription PCR to screen clinically characterized breast cancer tissue cDNA arrays. Primers detecting all NAT1 alternative transcripts were used, and the protocol and results are reported according to consensus guidelines. The clinical information about 166 tumor samples screened is provided, including tumor stage, estrogen and progesterone receptor status and HER2 expression. NAT1 was found to be significantly (P < 0.001) upregulated in hormone receptor positive vs. negative tumors. No correlation was apparent between NAT1 and tumor stage or HER2 expression. Our findings demonstrate a strong correlation between the expression of NAT1 and steroid hormone receptors in breast tumors, supporting its possible utility as a pharmacogenetic biomarker or drug target. Of the two polymorphic NAT genes, NAT1 is the one primarily expressed in breast tissue, and is subjected to regulation by two differential promoters and more than one polyadenylation signal. Hormonal factors may enhance NAT1 gene expression at the transcriptional or epigenetic level, and tamoxifen has additionally been shown to inhibit NAT1 enzymatic activity. The outcome of tamoxifen treatment is also more favorable in patients with NAT1 overexpressing tumors. The study adds to the growing body of evidence implicating NAT1 in breast cancer and its pharmacological treatment.

Ultrasensitive Optical Detection and Elimination of Residual Microtumors with a Postoperative Implantable Hydrogel Sensor for Preventing Cancer Recurrence

In vivo optical imaging of trace biomarkers in residual microtumors holds significant promise for cancer prognosis but poses a formidable challenge. Here, a novel hydrogel sensor is designed for ultrasensitive and specific imaging of the elusive biomarker. This hydrogel sensor seamlessly integrates a molecular beacon nanoprobe with fibroblasts, offering both high tissue retention capability and an impressive signal-to-noise ratio for imaging. Signal amplification is accomplished through exonuclease I-mediated biomarker recycling. The resulting hydrogel sensor sensitively detects the biomarker carcinoembryonic antigen with a detection limit of 1.8 pg mL-1 in test tubes. Moreover, it successfully identifies residual cancer nodules with a median diameter of less than 2 mm in mice bearing partially removed primary triple-negative breast carcinomas (4T1). Notably, this hydrogel sensor is proven effective for the sensitive diagnosis of invasive tumors in post-surgical mice with infiltrating 4T1 cells, leveraging the role of fibroblasts in locally enriching tumor cells. Furthermore, the residual microtumor is rapidly photothermal ablation by polydopamine-based nanoprobe under the guidance of visualization, achieving ≈100% suppression of tumor recurrence and lung metastasis. This work offers a promising alternative strategy for visually detecting residual microtumors, potentially enhancing the prognosis of cancer patients following surgical interventions.

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".

Exploring Biomarkers in Breast Cancer: Hallmarks of Diagnosis, Treatment, and Follow-Up in Clinical Practice

Breast cancer is a prevalent malignancy in the present day, particularly affecting women as one of the most common forms of cancer. A significant portion of patients initially present with localized disease, for which curative treatments are pursued. Conversely, another substantial segment is diagnosed with metastatic disease, which has a worse prognosis. Recent years have witnessed a profound transformation in the prognosis for this latter group, primarily due to the discovery of various biomarkers and the emergence of targeted therapies. These biomarkers, encompassing serological, histological, and genetic indicators, have demonstrated their value across multiple aspects of breast cancer management. They play crucial roles in initial diagnosis, aiding in the detection of relapses during follow-up, guiding the application of targeted treatments, and offering valuable insights for prognostic stratification, especially for highly aggressive tumor types. Molecular markers have now become the keystone of metastatic breast cancer diagnosis, given the diverse array of chemotherapy options and treatment modalities available. These markers signify a transformative shift in the arsenal of therapeutic options against breast cancer. Their diagnostic precision enables the categorization of tumors with elevated risks of recurrence, increased aggressiveness, and heightened mortality. Furthermore, the existence of therapies tailored to target specific molecular anomalies triggers a cascade of changes in tumor behavior. Therefore, the primary objective of this article is to offer a comprehensive review of the clinical, diagnostic, prognostic, and therapeutic utility of the principal biomarkers currently in use, as well as of their clinical impact on metastatic breast cancer. In doing so, our goal is to contribute to a more profound comprehension of this complex disease and, ultimately, to enhance patient outcomes through more precise and effective treatment strategies.

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.

Microneedle Patch for Painless Intradermal Collection of Interstitial Fluid Enabling Multianalyte Measurement of Small Molecules, SARS-CoV-2 Antibodies, and Protein Profiling

Blood sampling is a common practice to monitor health, but it entails a series of drawbacks for patients including pain and discomfort. Thus, there is a demand for more convenient ways to obtain samples. Modern analytical techniques enable monitoring of multiple bioanalytes in smaller samples, opening possibilities for new matrices, and microsampling technologies to be adopted. Interstitial fluid (ISF) is an attractive alternative matrix that shows good correlation with plasma concentration dynamics for several analytes and can be sampled in a minimally invasive and painless manner from the skin at the point-of-care. However, there is currently a lack of sampling devices compatible with clinical translation. Here, to tackle state-of-the-art limitations, a cost-effective and compact single-microneedle-based device designed to painlessly collect precisely 1.1 µL of dermal ISF within minutes is presented. The fluid is volume-metered, dried, and stably stored into analytical-grade paper within the microfluidic device. The obtained sample can be mailed to a laboratory, quantitatively analyzed, and provide molecular insights comparable to blood testing. In a human study, the possibility to monitor various classes of molecular analytes is demonstrated in ISF microsamples, including caffeine, hundreds of proteins, and SARS-CoV-2 antibodies, some being detected in ISF for the first time.

PIP kinases: A versatile family that demands further therapeutic attention

Phosphoinositides are membrane-localized phospholipids that regulate a plethora of essential cellular processes. These lipid signaling molecules are critical for cell homeostasis and therefore their levels are strictly regulated by the coordinated action of several families of lipid kinases and phosphatases. In this review, we provide a focused perspective on the phosphatidylinositol phosphate kinase (PIPK) family and the three subfamilies that compose it: Type I PIPKs or phosphatidylinositol-4-phosphate 5-kinases (PI4P5Ks), Type II PIPKs or phosphatidylinositol-5-phosphate 4-kinases (PI5P4Ks), and Type III PIPKs or phosphatidylinositol-3-phosphate 5-kinases (PIKfyve). Each subfamily is responsible for catalyzing a hydroxyl phosphorylation on specific phosphoinositide species to generate a double phosphorylated lipid, therefore regulating the levels of both substrate and product. Here, we summarize our current knowledge about the functions and regulation of each PIPK subfamily. Further, we highlight the roles of these kinases in various in vivo genetic models and give an overview of their involvement in multiple pathological conditions. The phosphoinositide field has been long focused on targeting PI3K signaling, but growing evidence suggests that it is time to draw attention to the other phosphoinositide kinases. The discovery of the involvement of PIPKs in the pathogenesis of multiple diseases has prompted substantial efforts to turn these enzymes into pharmacological targets. An increasingly refined knowledge of the biology of PIPKs in a variety of in vitro and in vivo models will facilitate the development of effective approaches for therapeutic intervention with the potential to translate into meaningful clinical benefits for patients suffering from cancer, immunological and infectious diseases, and neurodegenerative disorders.

Proteomics-Based Identification of Dysregulated Proteins in Breast Cancer

Immunohistochemistry (IHC) is still widely used as a morphology-based assay for in situ analysis of target proteins as specific tumor antigens. However, as a very heterogeneous collection of neoplastic diseases, breast cancer (BC) requires an accurate identification and characterization of larger panels of candidate biomarkers, beyond ER, PR, and HER2 proteins, for diagnosis and personalized treatment, without the limited availability of antibodies that are required to identify specific proteins. Top-down, middle-down, and bottom-up mass spectrometry (MS)-based proteomics approaches complement traditional histopathological tissue analysis to examine expression, modification, and interaction of hundreds to thousands of proteins simultaneously. In this review, we discuss the proteomics-based identification of dysregulated proteins in BC that are essential for the following issues: discovery and validation of new biomarkers by analysis of solid and liquid/non-invasive biopsies, cell lines, organoids and xenograft models; identification of panels of biomarkers for early detection and accurate discrimination between cancer, benign and normal tissues; identification of subtype-specific and stage-specific protein expression profiles in BC grading and measurement of disease progression; characterization of new subtypes of BC; characterization and quantitation of post-translational modifications (PTMs) and aberrant protein-protein interactions (PPI) involved in tumor development; characterization of the global remodeling of BC tissue homeostasis, diagnosis and prognostic information; and deciphering of molecular functions, biological processes and mechanisms through which the dysregulated proteins cause tumor initiation, invasion, and treatment resistance.

Comprehensive proteomic signature and identification of CDKN2A as a promising prognostic biomarker and therapeutic target of colorectal cancer

BACKGROUND

The carcinogenesis of colorectal cancer (CRC) involves many different molecules and multiple pathways, and the specific mechanism has not been elucidated until now. Existing studies on the proteomic signature profiles of CRC are relatively limited. Therefore, we herein aimed to provide a more comprehensive proteomic signature profile and discover new prognostic markers and therapeutic targets by performing proteomic analysis of CRC and paired normal tissues.

AIM

To investigate the proteomic signature and identify novel protein prognostic biomarkers of CRC.

METHODS

Cancer tissues and paired normal tissues were collected from 48 patients who underwent surgical removal at the China-Japan Friendship Hospital from January 2020 to June 2021. Data independent acquisition (DIA) quantitative proteomic analysis was performed using high-performance liquid chromatography–mass spectrometry/mass spectrometry (nano-UHPLC–MS/MS) to identify differentially expressed proteins, among which those with a P adj value (t test, BH correction) < 0.05 and an absolute fold change (|log₂FC|) > 2 were identified as potential markers. Differentially expressed proteins were selected by bioinformatics analysis and validated by immunohistochemical tissue microarrays, and their association with prognosis was further analyzed with the Gene Expression Profiling Interactive Analysis database to identify prognostic protein biomarkers of CRC.

RESULTS

Significantly differential protein expression was observed between cancer tissues and normal tissues. Compared with normal tissues, 1115 proteins were upregulated and 705 proteins were downregulated in CRC based on P adj < 0.05 and |log₂FC| > 2, and bioinformatics analysis revealed that the differentially expressed proteins were involved in multiple biological processes associated with tumorigenesis, including ribosome biogenesis in eukaryotes, focal adhesion, extracellular matrix-receptor interactions and other tumor metabolism processes. Moreover, cyclin-dependent kinase inhibitor 2A (CDKN2A) expression was markedly upregulated in CRC, as validated by immunohistochemistry (0.228 vs 0.364, P = 0.0044), and was significantly enriched in tumor proliferation and signal transduction pathways such as the cell cycle and p53 signaling pathways. High CDKN2A expression was significantly correlated with poor prognosis (P = 0.021). These results demonstrated that CDKN2A functions as a driver of CRC.

CONCLUSION

Our study provides a comprehensive proteomic signature of CRC and highlights CDKN2A as a potential powerful prognostic marker and precision therapeutic target.

Application of Proteomics in Pancreatic Ductal Adenocarcinoma Biomarker Investigations: A Review

Pancreatic ductal adenocarcinoma (PDAC), a highly aggressive malignancy with a poor prognosis is usually detected at the advanced stage of the disease. The only US Food and Drug Administration-approved biomarker that is available for PDAC, CA 19-9, is most useful in monitoring treatment response among PDAC patients rather than for early detection. Moreover, when CA 19-9 is solely used for diagnostic purposes, it has only a recorded sensitivity of 79% and specificity of 82% in symptomatic individuals. Therefore, there is an urgent need to identify reliable biomarkers for diagnosis (specifically for the early diagnosis), ascertain prognosis as well as to monitor treatment response and tumour recurrence of PDAC. In recent years, proteomic technologies are growing exponentially at an accelerated rate for a wide range of applications in cancer research. In this review, we discussed the current status of biomarker research for PDAC using various proteomic technologies. This review will explore the potential perspective for understanding and identifying the unique alterations in protein expressions that could prove beneficial in discovering new robust biomarkers to detect PDAC at an early stage, ascertain prognosis of patients with the disease in addition to monitoring treatment response and tumour recurrence of patients.

Single-Nucleotide Polymorphisms Promote Dysregulation Activation by Essential Gene Mediated Bio-Molecular Interaction in Breast Cancer

Background

Breast cancer (BRCA) is a malignant tumor with a high mortality rate and poor prognosis in patients. However, understanding the molecular mechanism of breast cancer is still a challenge.

Materials and Methods

In this study, we constructed co-expression networks by weighted gene co-expression network analysis (WGCNA). Gene-expression profiles and clinical data were integrated to detect breast cancer survival modules and the leading genes related to prognostic risk. Finally, we introduced machine learning algorithms to build a predictive model aiming to discover potential key biomarkers.

Results

A total of 42 prognostic modules for breast cancer were identified. The nomogram analysis showed that 42 modules had good risk assessment performance. Compared to clinical characteristics, the risk values carried by genes in these modules could be used to classify the high-risk and low-risk groups of patients. Further, we found that 16 genes with significant differential expressions and obvious bridging effects might be considered biological markers related to breast cancer. Single-nucleotide polymorphisms on the CYP24A1 transcript induced RNA structural heterogeneity, which affects the molecular regulation of BRCA. In addition, we found for the first time that ABHD11-AS1 was significantly highly expressed in breast cancer.

Conclusion

We integrated clinical prognosis information, RNA sequencing data, and drug targets to construct a breast cancer–related risk module. Through bridging effect measurement and machine learning modeling, we evaluated the risk values of the genes in the modules and identified potential biomarkers for breast cancer. The protocol provides new insight into deciphering the molecular mechanism and theoretical basis of BRCA.

Expanding role of PI5P4Ks in cancer: A promising druggable target

Cancer cells are challenged by a myriad of microenvironmental stresses, and it is their ability to efficiently adapt to the constantly changing nutrient, energy, oxidative, and/or immune landscape that allows them to survive and proliferate. Such adaptations, however, result in distinct vulnerabilities that are attractive therapeutic targets. Phosphatidylinositol 5-phosphate 4-kinases (PI5P4Ks) are a family of druggable stress-regulated phosphoinositide kinases that become conditionally essential as a metabolic adaptation, paving the way to targeting cancer cell dependencies. Further, PI5P4Ks have a synthetic lethal interaction with the tumor suppressor p53, the loss of which is one of the most prevalent genetic drivers of malignant transformation. PI5P4K's emergence as a crucial axis in the expanding landscape of phosphoinositide signaling in cancer has already stimulated the development of specific inhibitors. Thus, a better understanding of the biology of the PI5P4Ks will allow for targeted and effective therapeutic interventions. Here, we attempt to summarize the mounting roles of the PI5P4Ks in cancer, including evidence that targeting them is a therapeutic vulnerability and promising next-in-line treatment for multiple cancer subtypes.

Update on Thiamine Triphosphorylated Derivatives and Metabolizing Enzymatic Complexes

While the cellular functions of the coenzyme thiamine (vitamin B1) diphosphate (ThDP) are well characterized, the triphosphorylated thiamine derivatives, thiamine triphosphate (ThTP) and adenosine thiamine triphosphate (AThTP), still represent an intriguing mystery. They are present, generally in small amounts, in nearly all organisms, bacteria, fungi, plants, and animals. The synthesis of ThTP seems to require ATP synthase by a mechanism similar to ATP synthesis. In E. coli, ThTP is synthesized during amino acid starvation, while in plants, its synthesis is dependent on photosynthetic processes. In E. coli, ThTP synthesis probably requires oxidation of pyruvate and may play a role at the interface between energy and amino acid metabolism. In animal cells, no mechanism of regulation is known. Cytosolic ThTP levels are controlled by a highly specific cytosolic thiamine triphosphatase (ThTPase), coded by thtpa, and belonging to the ubiquitous family of the triphosphate tunnel metalloenzymes (TTMs). While members of this protein family are found in nearly all living organisms, where they bind organic and inorganic triphosphates, ThTPase activity seems to be restricted to animals. In mammals, THTPA is ubiquitously expressed with probable post-transcriptional regulation. Much less is known about the recently discovered AThTP. In E. coli, AThTP is synthesized by a high molecular weight protein complex from ThDP and ATP or ADP in response to energy stress. A better understanding of these two thiamine derivatives will require the use of transgenic models.

Transdermal sensing: in-situ non-invasive techniques for monitoring of human biochemical status

Improving life expectancy necessitates prevention and early diagnosis of any disease state based on active self-monitoring of symptoms and longitudinal biochemical profiling. Non-invasive and continuous measurement of molecular biomarkers that reflect metabolism and health must however be established to realize this plan. Human samples non-invasively obtained via the skin are suitable in this context for in-situ biochemical monitoring. We present a brief classification of transdermal sampling in aqueous and gaseous phases and then introduce a new generation of transdermal monitoring devices for rapid and accurate assessment of important parameters. Finally, we have summarized the diversity of body-wide skin characteristics that have possible effects for transdermal sampling. Because of its passive nature, in-situ biochemical monitoring via transdermal sampling will potentially lead to a greater understanding of important biochemical markers and their temporal variation.