Oral squamous cell carcinoma (OSCC) is a highly aggressive cancer and the fourth leading malignancy among males in Taiwan. Some pathogenic bacteria are associated with periodontitis and oral cancer. However, the comprehensive profile of the oral microbiome during the cancer's progression from the early stage to the late stage is still unclear. We profiled the oral microbiota and identified bacteria biomarkers associated with OSCC. The microbiota of an oral rinse from 51 healthy individuals and 197 OSCC patients at different stages were investigated using 16S rRNA V3V4 amplicon sequencing, followed by bioinformatics and statistical analyses. The oral microbiota communities from stage 4 patients showed significantly higher complexity than those from healthy controls. The populations also dynamically changed with the cancer's progression from stage 1 to stage 4. The predominant phyla in the oral samples showed variation in the relative abundance of Fusobacteria, Bacteroidetes, and Actinobacteria. The abundance of Fusobacteria increased significantly with the progression of oral cancer from the healthy controls (2.98%) to OSCC stage 1 (4.35%) through stage 4 (7.92%). At the genus level, the abundance of Fusobacterium increased, while the number of Streptococcus, Haemophilus, Porphyromonas, and Actinomyces decreased with cancer progression. Fusobacterium periodonticum, Parvimonas micra, Streptococcus constellatus, Haemophilus influenza, and Filifactor alocis were associated with OSCC, and they progressively increased in abundance from stage 1 to stage 4. The abundances of Streptococcus mitis, Haemophilus parainfluenzae, and Porphyromonas pasteri were inversely associated with OSCC progression. We selected a bacterial marker panel of three bacteria (upregulated F. periodonticum, down-regulated S. mitis, and P. pasteri), which had an AUC of 0.956 (95% CI = 0.925–0.986) in discriminating OSCC stage 4 from the healthy controls. Furthermore, the functional prediction of oral bacterial communities showed that genes involved in carbohydrate-related metabolism, such as methane metabolism, and energy-metabolism-related parameters, such as oxidative phosphorylation and carbon fixation in photosynthetic organisms, were enriched in late-stage OSCC, while those responsible for amino acid metabolism, such as folate biosynthesis and valine, leucine, and isoleucine biosynthesis, were significantly associated with the healthy controls. In conclusion, our results provided evidence of oral bacteria community changes during oral cancer progression and suggested the possibility of using bacteria as OSCC diagnostic markers.

Although cancer cell secretome profiling is a promising strategy used to identify potential body fluid-accessible cancer biomarkers, questions remain regarding the depth to which the cancer cell secretome can be mined and the efficiency with which researchers can select useful candidates from the growing list of identified proteins. Therefore, we analyzed the secretomes of 23 human cancer cell lines derived from 11 cancer types using one-dimensional SDS-PAGE and nano-LC-MS/MS performed on an LTQ-Orbitrap mass spectrometer to generate a more comprehensive cancer cell secretome. A total of 31,180 proteins was detected, accounting for 4,584 non-redundant proteins, with an average of 1,300 proteins identified per cell line. Using protein secretionpredictive algorithms, 55.8% of the proteins appeared to be released or shed from cells. The identified proteins were selected as potential marker candidates according to three strategies: (i) proteins apparently secreted by one cancer type but not by others (cancer type-specific marker candidates), (ii) proteins released by most cancer cell lines (pan-cancer marker candidates), and (iii) proteins putatively linked to cancer-relevant pathways. We then examined protein expression profiles in the Human Protein Atlas to identify biomarker candidates that were simultaneously detected in the secretomes and highly expressed in cancer tissues. This analysis yielded 6 -137 marker candidates selective for each tumor type and 94 potential pan-cancer markers. Among these, we selectively validated monocyte differentiation antigen CD14 (for liver cancer), stromal cell-derived factor 1 (for lung cancer), and cathepsin L1 and interferon-induced 17-kDa protein (for nasopharyngeal carcinoma) as potential serological cancer markers. In summary, the proteins identified from the secretomes of 23 cancer cell lines and the Hu-

Bladder cancer is a common urologic cancer whose incidence continues to rise annually. Urinary microparticles are an attractive material for noninvasive bladder cancer biomarker discovery. In this study, we applied isotopic dimethylation labeling coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS) to discover bladder cancer biomarkers in urinary microparticles isolated from hernia (control) and bladder cancer patients. This approach identified 2964 proteins based on more than two distinct peptides, of which 2058 had not previously been reported as constituents of human urine exosomes/microparticles. A total of 107 differentially expressed proteins were identified as candidate biomarkers. Differences in the concentrations of 29 proteins (41 signature peptides) were precisely quantified by LC-MRM/MS in 48 urine samples of bladder cancer, hernia, and urinary tract infection/hematuria. Concentrations of 24 proteins changed significantly (p<0.05) between bladder cancer (n=28) and hernia (n=12), with area-under-the-curve values ranging from 0.702 to 0.896. Finally, we quantified tumor-associated calcium-signal transducer 2 (TACSTD2) in raw urine specimens (n=221) using a commercial ELISA and confirmed its potential value for diagnosis of bladder cancer. Our study reveals a strong association of TACSTD2 with bladder cancer and highlights the potential of human urinary microparticles in the noninvasive diagnosis of bladder cancer.

A urine sample preparation workflow for the iTRAQ (isobaric tag for relative and absolute quantitation) technique was established. The reproducibility of this platform was evaluated and applied to discover proteins with differential levels between pooled urine samples from nontumor controls and three bladder cancer patient subgroups with different grades/stages (a total of 14 controls and 23 cancer cases in two multiplex iTRAQ runs). Combining the results of two independent clinical sample sets, a total of 638 urine proteins were identified. Among them, 55 proteins consistently showed >2-fold differences in both sample sets. Western blot analyses of individual urine samples confirmed that the levels of apolipoprotein A-I (APOA1), apolipoprotein A-II, heparin cofactor 2 precursor and peroxiredoxin-2 were significantly elevated in bladder cancer urine specimens (n = 25-74). Finally, we quantified APOA1 in a number of urine samples using a commercial ELISA and confirmed again its potential value for diagnosis (n = 126, 94.6% sensitivity and 92.0% specificity at a cutoff value of 11.16 ng/mL) and early detection (n = 71, 83.8% sensitivity and 94.0% specificity). Collectively, our results provide the first iTRAQ-based quantitative profile of bladder cancer urine proteins and represent a valuable resource for the discovery of bladder cancer markers.

Oral cavity squamous cell carcinoma (OSCC), which is frequently associated with poor prognosis and mortality, is a leading cause of cancer-related death worldwide. Discovery of body fluid accessible biomarkers is needed to improve OSCC screening. To this end, we profiled proteomes of saliva from the healthy volunteers, the individuals with oral potentially malignant disorders (OPMD), and the OSCC patients by means of SDS-PAGE coupled with LC-MS/MS. In the control, the OPMD, and the OSCC groups, 958, 845, and 1030 salivary proteins were detected, respectively. With spectral counting-based label-free quantification, 22 overexpressed salivary proteins were identified in the OSCC group compared with the healthy controls and the OPMD individuals. Among them, resistin (RETN) was subjected to further validation with an independent cohort using ELISA. The data confirmed that the salivary RETN levels in the OSCC patients were significantly higher than that in the healthy or in the OPMD group. Moreover, the elevated levels of salivary RETN were highly correlated with late-stage primary tumors, advanced overall stage, and lymph-node metastasis. Our results not only reveal that profiling of saliva proteome is feasible for discovery of OSCC biomarkers, but also identify RETN as a potential salivary biomarker for OSCC detection.

Oral cavity squamous cell carcinoma (OSCC) is a devastating disease that accounts for 3% of all cancer cases diagnosed annually. OSCC is usually diagnosed at advanced clinical stages, resulting in poor outcomes. To identify effective biomarkers for improved OSCC diagnosis and/or management, we simultaneously analyzed the OSCC cell secretome and tissue transcriptome. Among the 19 candidates isolated, guanylate-binding protein 1 (GBP1) was selected for further validation using serum samples from OSCC patients and healthy controls. Notably, the serum level of GBP1 was higher in OSCC patients, compared to that in healthy controls. Immunohistochemical analysis further revealed GBP1 overexpression in OSCC tissues, compared with adjacent noncancerous epithelia. Importantly, the higher GBP1 level in OSCC tissue was associated with higher overall pathological stage, positive perineural invasion, and poorer prognosis. Moreover, GBP1 modulated the migration and invasion of OSCC cells in vitro. Our results collectively indicate that integrated analysis of the cancer secretome and transcriptome is a feasible strategy for the efficient identification of novel OSCC markers.

Lung cancer is the leading cause of cancer-related death worldwide. Both diagnostic and prognostic biomarkers are urgently needed to increase patient survival. In this study, we identified/quantified 1763 proteins from paired adenocarcinoma (ADC) tissues with different extents of lymph node (LN) involvement using an iTRAQ-based quantitative proteomic analysis. Based on a bioinformatics analysis and literature search, we selected six candidates (ERO1L, PABPC4, RCC1, RPS25, NARS, and TARS) from a set of 133 proteins that presented a 1.5-fold increase in expression in ADC tumors without LN metastasis compared with adjacent normal tissues. These six proteins were further verified using immunohistochemical staining and Western blot analyses. The protein levels of these six candidates were higher in tumor tissues compared with adjacent normal tissues. The ERO1L and NARS levels were positively associated with LN metastasis. Importantly, ERO1L overexpression in patients with early-stage ADC was positively correlated with poor survival, suggesting that ERO1L overexpression in primary sites of early-stage cancer tissues indicates a high risk for cancer micrometastasis. Moreover, we found that knockdown of either ERO1L or NARS reduced the viability and migration ability of ADC cells. Our results collectively provide a potential biomarker data set for ADC diagnosis/prognosis and reveal novel roles of ERO1L and NARS in ADC progression. Molecular & Cellular Proteomics 15:

Oral cancer is one of the most common cancers worldwide. To identify biomarkers for oral cancer diagnosis, salivary proteins differentially expressed in oral cancer patients have been identified with iTRAQ-based MS analyses. The candidates were further selected using MRM-MS and validated with the immunoassays. The results suggest that three proteins (CFH, FGA, and SERPINA1) have the potential as diagnosis and prognosis biomarkers of oral cancer, and analysis of salivary proteome is a feasible strategy for biomarker discovery.