Tracing the voyage of SELDI-TOF MS in cancer biomarker discovery and its current depreciation trend – need for resurrection?

Proteomics-Driven Biomarkers in Pancreatic Cancer

Pancreatic cancer is a devastating disease that has a grim prognosis, highlighting the need for improved screening, diagnosis, and treatment strategies. Currently, the sole biomarker for pancreatic ductal adenocarcinoma (PDAC) authorized by the U.S. Food and Drug Administration is CA 19-9, which proves to be the most beneficial in tracking treatment response rather than in early detection. In recent years, proteomics has emerged as a powerful tool for advancing our understanding of pancreatic cancer biology and identifying potential biomarkers and therapeutic targets. This review aims to offer a comprehensive survey of proteomics' current status in pancreatic cancer research, specifically accentuating its applications and its potential to drastically enhance screening, diagnosis, and treatment response. With respect to screening and diagnostic precision, proteomics carries the capacity to augment the sensitivity and specificity of extant screening and diagnostic methodologies. Nonetheless, more research is imperative for validating potential biomarkers and establishing standard procedures for sample preparation and data analysis. Furthermore, proteomics presents opportunities for unveiling new biomarkers and therapeutic targets, as well as fostering the development of personalized treatment strategies based on protein expression patterns associated with treatment response. In conclusion, proteomics holds great promise for advancing our understanding of pancreatic cancer biology and improving patient outcomes. It is essential to maintain momentum in investment and innovation in this arena to unearth more groundbreaking discoveries and transmute them into practical diagnostic and therapeutic strategies in the clinical context.

Determination of Pathogens by Electrophoretic and Spectrometric Techniques

In modern medical diagnostics, where analytical chemistry plays a key role, fast and accurate identification of pathogens is becoming increasingly important. Infectious diseases pose a growing threat to public health due to population growth, international air travel, bacterial resistance to antibiotics, and other factors. For instance, the detection of SARS-CoV-2 in patient samples is a key tool to monitor the spread of the disease. While there are several techniques for identifying pathogens by their genetic code, most of these methods are too expensive or slow to effectively analyze clinical and environmental samples that may contain hundreds or even thousands of different microbes. Standard approaches (e.g., culture media and biochemical assays) are known to be very time- and labor-intensive. The purpose of this review paper is to highlight the problems associated with the analysis and identification of pathogens that cause many serious infections. Special attention was paid to the description of mechanisms and the explanation of the phenomena and processes occurring on the surface of pathogens as biocolloids (charge distribution). This review also highlights the importance of electromigration techniques and demonstrates their potential for pathogen pre-separation and fractionation and demonstrates the use of spectrometric methods, such as MALDI-TOF MS, for their detection and identification.

Biomarker Reproducibility Challenge: A Review of Non-Nucleotide Biomarker Discovery Protocols from Body Fluids in Breast Cancer Diagnosis

Breast cancer has now become the most commonly diagnosed cancer, accounting for one in eight cancer diagnoses worldwide. Non-invasive diagnostic biomarkers and associated tests are superlative candidates to complement or improve current approaches for screening, early diagnosis, or prognosis of breast cancer. Biomarkers detected from body fluids such as blood (serum/plasma), urine, saliva, nipple aspiration fluid, and tears can detect breast cancer at its early stages in a minimally invasive way. The advancements in high-throughput molecular profiling (omics) technologies have opened an unprecedented opportunity for unbiased biomarker detection. However, the irreproducibility of biomarkers and discrepancies of reported markers have remained a major roadblock to clinical implementation, demanding the investigation of contributing factors and the development of standardised biomarker discovery pipelines. A typical biomarker discovery workflow includes pre-analytical, analytical, and post-analytical phases, from sample collection to model development. Variations introduced during these steps impact the data quality and the reproducibility of the findings. Here, we present a comprehensive review of methodological variations in biomarker discovery studies in breast cancer, with a focus on non-nucleotide biomarkers (i.e., proteins, lipids, and metabolites), highlighting the pre-analytical to post-analytical variables, which may affect the accurate identification of biomarkers from body fluids.

Advances of proteomics technologies for multidrug-resistant mechanisms

Multidrug resistance (MDR) is a vital issue in cancer treatment. Drug resistance can be developed through a variety of mechanisms, including increased drug efflux, activation of detoxifying systems and DNA repair mechanisms, and escape of drug-induced apoptosis. Identifying the exact mechanism related in a particular case is a difficult task. Proteomics is the large-scale study of proteins, particularly their expression, structures and functions. In recent years, comparative proteomic methods have been performed to analyze MDR mechanisms in drug-selected model cancer cell lines. In this paper, we review the recent developments and progresses by comparative proteomic approaches to identify potential MDR mechanisms in drug-selected model cancer cell lines, which may help understand and design chemical sensitizers.

Proteomic investigations into resistance in colorectal cancer

Introduction: Despite advances in screening and treatment options, colorectal cancer (CRC) remains one of the most prevalent and lethal cancer subtypes. Resistance to cytotoxic or targeted therapy has remained a constant challenge to the treatment and long-term management of patients, attracting intense worldwide investigation since the 1950s. Through extensive investigations into the proteomic mechanisms and functions that convey resistance to therapy/s, researchers have become able to implicate alterations in several signaling pathways that provide and sustain resistance to treatment.Areas covered: In this review, we summarize how protein alterations are associated with resistance to therapy, with particular emphasis on CRC. An overview of the mechanisms of therapeutic resistance is described, highlighting recent studies which endeavor to elucidate the proteomic changes that are associated with the acquisition and promulgation of therapeutic resistance.Expert opinion: While cancers such as CRC have been intensively studied for decades, unresponsiveness and the resistance to therapy remain critical obstacles in the treatment of patients. Due to the inherent biological and clinical heterogeneity of individual CRCs, proteomic methods stand to become powerful tools to provide biological insights that may guide therapeutic strategies with the ultimate goal of refining emergent immunotherapeutic treatments.

SELDI-TOF MS Analysis of Hepatocellular Carcinoma in an Australian Cohort

BACKGROUND

Hepatocellular carcinoma (HCC) is a common cause of cancer death worldwide. Resection offers the best chance of long-term survival, but a consistent adverse prognostic factor is the presence of microvascular invasion (MVI). In this study, surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS), a high throughput method of analyzing complex samples, was used to explore differentially expressed proteins between HCC and adjacent nontumour liver tissue (ANLT). These findings were correlated with clinical outcomes.

MATERIALS AND METHODS

From 2002 to 2011, tumor and ANLT were collected from patients who underwent liver resection and these samples were later prepared for SELDI-TOF MS. Output data were then used to identify proteins capable of discriminating HCC from ANLT. Proteins from the multivariate analysis were then analyzed to determine prognostic factors and the m/z ratios of these proteins were entered into the ExPASy database to infer potential candidates.

RESULTS

During the study period, 30 patients had SELDI-TOF MS performed on their HCC and ANLT samples. On multivariate analysis, a panel of four proteins-m/z 5840, m/z 8921, m/z 9961, and m/z 25,872-discriminated HCC from ANLT with an area under the ROC curve of 0.954 (P < 0.001). On prognostic factor assessment, decreased m/z 9961 was significantly associated with the presence of MVI (P = 0.025) and shorter disease-free survival (P = 0.045) in our patients. A potential candidate for this protein was coxsackievirus and adenovirus receptor, isoform 3 (CAR 3/7), which helps maintain tight junction integrity.

CONCLUSIONS

Using SELDI TOF-MS, we identified a panel of four proteins with excellent discriminative capacity between HCC and ANLT. Of these, m/z 9961 was the only protein significantly associated with a known poor prognostic factor (presence of MVI) and survival (shorter disease-free survival). While loss of CAR 3/7 could lead to MVI, further research is warranted to validate the identity of protein m/z 9961.

An efficient biomarker panel for diagnosis of breast cancer using surface-enhanced laser desorption ionization time-of-flight mass spectrometry

Breast cancer (BC) is the most frequently diagnosed cancer that affects women worldwide. Early detection of BC is important to improve survival rates and decrease mortality. The aim of the present study was to investigate serum biomarkers using surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF-MS) to distinguish patients with BC from the healthy population and patients with benign breast diseases (BBDs). A total of 62 patients with invasive ductal carcinoma, as confirmed by histopathology, and 47 non-cancerous individuals (NCIs) [16 healthy controls (HCs) and 31 patients with BBD] were enrolled in the present study. Serum protein profiles were determined by SELDI-TOF-MS using an immobilized metal affinity capture array. Serum from patients with BC were compared with that from the HC group using univariate and multivariate statistical analyses. A total of 118 clusters were generated from the individual serum. Univariate analysis revealed that 5 peaks were significantly downregulated (m/z 1,452, 2,670, 3,972, 5,354 and 5,523; P<0.001) and 4 were upregulated (m/z 6,850, 7,926, 8,115 and 8,143; P<0.001) in patients with BC compared with the HC group. A comparison of patients with BC and patients with BBD revealed an additional 9 protein peaks. Among these, 3 peaks (m/z 3,972, 5,336 and 11,185) were significantly downregulated and 6 peaks (m/z 4,062, 4,071, 4,609, 6,850, 8,115 and 8,133) were significantly upregulated. A total of 3 peaks [mass-to-change ratio (m/z) 3,972, 6,850 and 8,115 (BC2)] were common in both sets. The results of the present study suggest that a 4 protein peak set [m/z 3,972, 6,850 and 8,115 (BC2) and 8,949 (BC3)] could be used to distinguish patients with BC from NCI.

Proteomic studies in the discovery of cerebrospinal fluid biomarkers for amyotrophic lateral sclerosis

INTRODUCTION

Amyotrophic lateral sclerosis (ALS) is a progressive degenerative motor neuron disease, which usually leads to death within a few years. The diagnosis is mainly based on clinical symptoms and there is a need for ALS-specific biomarkers to make an early and precise diagnosis, for development of disease-modifying drugs and to gain new insights into pathophysiology. Areas covered: In the present review, we summarize studies using mass spectrometric (MS) approaches to identify protein alterations in the cerebrospinal fluid (CSF) of ALS patients. In total, we identified 11 studies fulfilling our criteria by searching in the PubMed database using the keywords 'ALS' and 'CSF' combined with 'proteome', 'proteomic', 'mass spectrometry' or 'protein biomarker'. Ten proteins were differently regulated in ALS CSF compared to controls in at least 2 studies. We will discuss the relevance of the identified proteins regarding the frequency of identification, extent of alteration and brain-specificity. Expert commentary: Most of the identified CSF biomarker candidates are irreproducible or mainly blood-derived. We assign the missing success of CSF proteomic studies in biomarker discovery to a lack of sensitivity, unsuitable normalization, low quality assurance and variations originating from sample preparation. These issues must be improved in future proteomic studies in CSF.

Mass spectrometry for the discovery of biomarkers of sepsis

Sepsis is a serious medical condition that occurs in 30% of patients in intensive care units (ICUs). Early detection of sepsis is key to prevent its progression to severe sepsis and septic shock, which can cause organ failure and death. Diagnostic criteria for sepsis are nonspecific and hinder a timely diagnosis in patients. Therefore, there is currently a large effort to detect biomarkers that can aid physicians in the diagnosis and prognosis of sepsis. Mass spectrometry is often the method of choice to detect metabolomic and proteomic changes that occur during sepsis progression. These "omics" strategies allow for untargeted profiling of thousands of metabolites and proteins from human biological samples obtained from septic patients. Differential expression of or modifications to these metabolites and proteins can provide a more reliable source of diagnostic biomarkers for sepsis. Here, we focus on the current knowledge of biomarkers of sepsis and discuss the various mass spectrometric technologies used in their detection. We consider studies of the metabolome and proteome and summarize information regarding potential biomarkers in both general and neonatal sepsis.

Simplifying the Preparation of Pollen Grains for MALDI-TOF MS Classification

Matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS) is a well-implemented analytical technique for the investigation of complex biological samples. In MS, the sample preparation strategy is decisive for the success of the measurements. Here, sample preparation processes and target materials for the investigation of different pollen grains are compared. A reduced and optimized sample preparation process prior to MALDI-TOF measurement is presented using conductive carbon tape as target. The application of conductive tape yields in enhanced absolute signal intensities and mass spectral pattern information, which leads to a clear separation in subsequent pattern analysis. The results will be used to improve the taxonomic differentiation and identification, and might be useful for the development of a simple routine method to identify pollen based on mass spectrometry.