Exploratory study on application of MALDI‑TOF‑MS to detect serum and urine peptides related to small cell lung carcinoma

Targeted O-glycoproteomics for the development of diagnostic markers for advanced colorectal cancer

Aberrant glycosylation is a prominent feature of cancer, that can be used as targets to improve the existing cancer biomarkers, and help to assess metastasis risks, and therapeutic effects. We developed a targeted O-glycoproteomics method using serum specimens, and evaluated its utility in identifying advanced colorectal cancer (CRC) markers. To this end, we combined consecutive lectin affinity purification using Maclura pomifera lectin (MPL), jacalin, and Sambucus nigra lectin, which have affinities for the following O-glycans, that have received attention as cancer-related antigens, Tn (GalNAc-Ser/Thr), Sialyl Tn (Siaα2-6GalNAc-Ser/Thr), T (Galβ1-3GalNAc-Ser/Thr), Sialyl T (Siaα2-3Galβ1-GalNAc-Ser/Thr), and di-Sialyl T (Siaα2-3Galβ1-3[Siaα2-6] GalNAc-Ser/Thr), with a unique O-glycoproteomics approach. A total of 2,068 O-glycoforms derived from 265 proteins were identified in healthy individuals and patients with advanced CRC, of which 44 CRC-specific O-glycoforms were extracted. Particularly, five glycoproteins with T, Sialyl T, and di-Sialyl T antigens in specific peptide regions were evaluated quantitatively and statistically. We found that fibulin-2 (FBLN2) (aa330-349)/T antigen (area under the curve [AUC] = 0.92); macrophage colony-stimulating factor 1 (CSF1) (aa370-395)/(T + di-Sialyl T) (AUC = 0.94); macrophage mannose receptor 1 (MRC1) (aa1083-1101 and aa1215-1229)/T (AUC = 0.96 and 0.99); fibrinogen alpha chain (FGA) (aa354-367, aa511-527 and aa559-573)/Sialyl T (AUC = 0.98, 0.90 and 0.94); and complement component C7 (C7) (aa692-701)/di-Sialyl T (AUC = 1.00), can have high diagnostic efficacy to strategically predict advanced CRC groups. Hence, they could be promising markers for detection of advanced CRC, and provide new clinical test indicators along with lectins, such as MPL and jacalin. Our O-glycoproteomics platform provides a novel tool and resource, for researchers and clinicians seeking to better understand and treat advanced CRC.

MALDI-TOF/MS Analysis of Non-Invasive Human Urine and Saliva Samples for the Identification of New Cancer Biomarkers

Cancer represents a group of heterogeneous diseases that are a leading global cause of death. Even though mortality has decreased in the past thirty years for different reasons, most patients are still diagnosed at the advanced stage, with limited therapeutic choices and poor outcomes. Moreover, the majority of cancers are detected using invasive painful methods, such as endoscopic biopsy, making the development of non-invasive or minimally invasive methods for the discovery and fast detection of specific biomarkers a crucial need. Among body fluids, a valuable non-invasive alternative to tissue biopsy, the most accessible and least invasive are undoubtedly urine and saliva. They are easily retrievable complex fluids containing a large variety of endogenous compounds that may provide information on the physiological condition of the body. The combined analysis of these fluids with matrix-assisted laser desorption ionization–time-of-flight mass spectrometry (MALDI-TOF/MS), a reliable and easy-to-use instrumentation that provides information with relatively simple sample pretreatments, could represent the ideal option to rapidly achieve fast early stage diagnosis of tumors and their real-time monitoring. On this basis, the present review summarizes the recently reported applications relevant to the MALDI analysis of human urine and saliva samples.

Exploratory study on application of MALDI‑TOF‑MS to detect serum and urine peptides related to small cell lung carcinoma

Matrix‑assisted laser desorption/ionization time‑of‑flight mass spectrometry (MALDI‑TOF‑MS) was employed to analyze differential serum and urine peptides in patients with small cell lung cancer (SCLC) and healthy individuals, and SCLC diagnostic classification models were constructed. Serum and urine samples from 72 patients with SCLC, age‑ and gender‑matched with 72 healthy individuals, were divided into training and testing sets in a 3:1 ratio. Serum and urine peptides were extracted using copper ion‑chelating nanomagnetic beads, and mass spectra were obtained using MALDI‑TOF‑MS. Peptide spectra for the training set were analyzed, and the classification model was constructed using ClinProTools (CPT). The testing set was used for blinded model validation. For training‑set sera, 122 differential peptide signal peaks with a mass of 0.8‑10 kDa were observed, and 19 peptides showed significantly different expression [P<0.0005; area under curve (AUC) ≥0.80]. CPT screened 5 peptide peaks (0.8114, 0.83425, 1.86655, 4.11133 and 5.81192 kDa) to construct the classification model. The testing set was used for the blinded validation, which had 95.0% sensitivity and 90.0% specificity. For the training‑set urine, 132 differential peptide signal peaks with m/z ratios of 0.8‑10 kDa were observed, and 8 peptides had significantly different expression (P<0.0005; AUC ≥0.80). Then, 5 peaks (1.0724, 2.37692, 2.7554, 4.75475 and 4.7949 kDa) were used for classification model construction. The testing set was used for 36 blinded validation, which had 85.0% sensitivity and 80.0% specificity. Among the differential peptides, 3 had the same significant peaks at 2.3764, 0.8778 and 0.8616 kDa, identified as fibrinogen α, glucose‑6‑phosphate isomerase and cyclin‑dependent kinase‑1, respectively. The present study highlighted the differences that exist in serum and urine peptides between patients with SCLC and healthy individuals. Serum and urine peptide diagnostic classification models could be constructed using MALDI‑TOF‑MS, and showed high sensitivity and specificity.