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.