Peptidomics-Driven Strategy Reveals Peptides and Predicted Proteases Associated With Oral Cancer Prognosis

Targeting bacterial metabolites in tumor for cancer therapy: An alternative approach for targeting tumor-associated bacteria

Emerging evidence reveal that tumor-associated bacteria (TAB) can facilitate the initiation and progression of multiple types of cancer. Recent work has emphasized the significant role of intestinal microbiota, particularly bacteria, plays in affecting responses to chemo- and immuno-therapies. Hence, it seems feasible to improve cancer treatment outcomes by targeting intestinal bacteria. While considering variable richness of the intestinal microbiota and diverse components among individuals, direct manipulating the gut microbiota is complicated in clinic. Tumor initiation and progression requires the gut microbiota-derived metabolites to contact and reprogram neoplastic cells. Hence, directly targeting tumor-associated bacteria metabolites may have the potential to provide alternative and innovative strategies to bypass the gut microbiota for cancer therapy. As such, there are great opportunities to explore holistic approaches that incorporates TAB-derived metabolites and related metabolic signals modulation for cancer therapy. In this review, we will focus on key opportunistic areas by targeting TAB-derived metabolites and related metabolic signals, but not bacteria itself, for cancer treatment, and elucidate future challenges that need to be addressed in this emerging field.

Mapping Conformational Changes in the Saliva Proteome Potentially Associated with Oral Cancer Aggressiveness

Diverse proteomics-based strategies have been applied to saliva to quantitatively identify diagnostic and prognostic targets for oral cancer. Considering that these targets may be regulated by events that do not imply variation in protein abundance levels, we hypothesized that changes in protein conformation can be associated with diagnosis and prognosis, revealing biological processes and novel targets of clinical relevance. For this, we employed limited proteolysis-mass spectrometry in saliva samples to explore structural alterations, comparing the proteome of healthy control and oral squamous cell carcinoma (OSCC) patients with and without lymph node metastasis. Thirty-six proteins with potential structural rearrangements were associated with clinical patient features including transketolase and its interacting partners. Moreover, N-glycosylated peptides contribute to structural rearrangements of potential diagnostic and prognostic markers. Altogether, this approach utilizes saliva proteins to search for targets for diagnosing and prognosing oral cancer and can guide the discovery of potential regulated sites beyond protein-level abundance.

Stable isotope labeling-based two-step derivatization strategy for analysis of Phosphopeptides

Investigating site-specific protein phosphorylation remains a challenging task. The present study introduces a two-step chemical derivatization method for accurate identification of phosphopeptides. Methylamine neutralizes carboxyl groups, thus reducing the adsorption of non-phosphorylated peptides during enrichment, while dimethylamine offers a cost-effective reagent for stable isotope labeling of phosphorylation sites. The derivatization improves the mass spectra obtained through liquid chromatography-tandem mass spectrometry. The product ions at m/z 58.07 and 64.10 Da, resulting from dimethylamine-d0 and dimethylamine-d6 labeled phosphorylation sites respectively, can serve as report ions. Derivatized phosphopeptides from casein demonstrate enhanced ionization and formation of product ions, yielding a significant increase in the number of identifiable peptides. When using the parallel reaction monitoring technique, it is possible to distinguish isomeric phosphopeptides with the same amino acid sequence but different phosphorylation sites. By employing a proteomic software and screening the report ions, we identified 29 endogenous phosphopeptides in 10 μL of human saliva with high reliability. These findings indicate that the two-step derivatization strategy has great potential in site-specific phosphorylation and large-scale phosphoproteomics research. SIGNIFICANCE: There is a significant need to improve the accuracy of identifying phosphoproteins and phosphopeptides and analyzing them quantitatively. Several chemical derivatization techniques have been developed to label phosphorylation sites, thus enabling the identification and relative quantification of phosphopeptides. Nevertheless, these methods have limitations, such as incomplete conversion or the need for costly isotopic reagents. Building upon previous contributions, our study moves the field forward due to high efficiency in site-specific labeling, cost-effectiveness, improved sensitivity, and comprehensive product ion coverage. Using the two-step derivatization approach, we successfully identified 29 endogenous phosphopeptides in 10 μL of human saliva with high reliability. The outcomes underscore the possibility of the method for site-specific phosphorylation and large-scale phosphoproteomics investigations.

Peptidomics Strategies to Evaluate Cancer Diagnosis, Prognosis, and Treatment

Peptides have potential bioactive functions, and the peptidomics landscape has been broadly investigated for various diseases, including cancer. In this chapter, we reviewed the past four years of literature available and selected 16 peer-reviewed publications exploring peptidomics in diagnosis, prognosis, and treatment in cancer research. We highlighted their main aims, mass spectrometry-based peptidomics, multi-omics, data-driven and in silico strategies, functional assays, and clinical applications. Moreover, we underscored several levels of difficulties in translating the peptidomics findings to clinical practice, aiming to learn with the accumulated knowledge and guide upcoming studies. Finally, this review reinforces the peptidomics robustness in discovering potential candidates for monitoring the several stages of cancer disease and therapeutic treatment, leveraging the management of cancer patients in the future.

Comprehensive glycoprofiling of oral tumours associates N-glycosylation with lymph node metastasis and patient survival

While altered protein glycosylation is regarded a trait of oral squamous cell carcinoma (OSCC), the heterogeneous and dynamic glycoproteome of tumour tissues from OSCC patients remain unmapped. To this end, we here employ an integrated multi-omics approach comprising unbiased and quantitative glycomics and glycoproteomics applied to a cohort of resected primary tumour tissues from OSCC patients with (n = 19) and without (n = 12) lymph node metastasis. While all tumour tissues displayed relatively uniform N-glycome profiles suggesting overall stable global N-glycosylation during disease progression, altered expression of six sialylated N-glycans was found to correlate with lymph node metastasis. Notably, glycoproteomics and advanced statistical analyses uncovered altered site-specific N-glycosylation revealing previously unknown associations with several clinicopathological features. Importantly, the glycomics and glycoproteomics data unveiled that comparatively high abundance of two core-fucosylated and sialylated N-glycans (Glycan 40a and Glycan 46a) and one N-glycopeptide from fibronectin were associated with low patient survival, while a relatively low abundance of N-glycopeptides from both afamin and CD59 were also associated with poor survival. This study provides novel insight into the complex OSCC tissue N-glycoproteome forming an important resource to further explore the underpinning disease mechanisms and uncover new prognostic glyco-markers for OSCC.

A meta-analysis reveals the protein profile associated with malignant transformation of oral leukoplakia

The search for biomarkers associated with oral leukoplakia malignant transformation is critical for early diagnosis and improved prognosis of oral cancer patients. This systematic review and meta-analysis aimed to assess protein-based markers potentially associated with malignant transformation of oral leukoplakia. Five database and the grey literature were searched. In total, 142 studies were included for qualitative synthesis, where 173 proteins were investigated due to their potential role in malignant progression from oral leukoplakia (OL) to oral squamous cell carcinoma (OSCC). The abundance of these proteins was analyzed in fixed tissues and/or biofluid samples, mainly by immunohistochemistry and ELISA, and 12 were shared by both samples. Enrichment analysis revealed that the differential abundant proteins are mostly involved with regulation of cell death, regulation of cell proliferation, and regulation of apoptotic process. Also, these proteins are mainly expressed in the extracellular region (55.5%), cell surface (24.8%), and vesicles (49.1%). The meta-analysis revealed that the proteins related to tumor progression, PD-L1, Mdm2, and Mucin-4 were significantly associated with greater abundance in OSCC patients, with an Odds Ratio (OR) of 0.12 (95% CI: 0.04-0.40), 0.44 (95% CI: 0.24-0.81), and 0.18 (95% CI: 0.04-0.86), respectively, with a moderate certainty of evidence. The results indicate a set of proteins that have been investigated across OSCC initiation and progression, and whose transcriptional expression is associated with clinical characteristics relevant to the prognosis and aggressiveness. Further verification and validation of this biomarkers set are strongly recommended for future clinical application.

Connecting multiple microenvironment proteomes uncovers the biology in head and neck cancer

The poor prognosis of head and neck cancer (HNC) is associated with metastasis within the lymph nodes (LNs). Herein, the proteome of 140 multisite samples from a 59-HNC patient cohort, including primary and matched LN-negative or -positive tissues, saliva, and blood cells, reveals insights into the biology and potential metastasis biomarkers that may assist in clinical decision-making. Protein profiles are strictly associated with immune modulation across datasets, and this provides the basis for investigating immune markers associated with metastasis. The proteome of LN metastatic cells recapitulates the proteome of the primary tumor sites. Conversely, the LN microenvironment proteome highlights the candidate prognostic markers. By integrating prioritized peptide, protein, and transcript levels with machine learning models, we identify nodal metastasis signatures in blood and saliva. We present a proteomic characterization wiring multiple sites in HNC, thus providing a promising basis for understanding tumoral biology and identifying metastasis-associated signatures.

Microbiome and cancer

The human microbiome constitutes a complex multikingdom community that symbiotically interacts with the host across multiple body sites. Host-microbiome interactions impact multiple physiological processes and a variety of multifactorial disease conditions. In the past decade, microbiome communities have been suggested to influence the development, progression, metastasis formation, and treatment response of multiple cancer types. While causal evidence of microbial impacts on cancer biology is only beginning to be unraveled, enhanced molecular understanding of such cancer-modulating interactions and impacts on cancer treatment are considered of major scientific importance and clinical relevance. In this review, we describe the molecular pathogenic mechanisms shared throughout microbial niches that contribute to the initiation and progression of cancer. We highlight advances, limitations, challenges, and prospects in understanding how the microbiome may causally impact cancer and its treatment responsiveness, and how microorganisms or their secreted bioactive metabolites may be potentially harnessed and targeted as precision cancer therapeutics.

Proteomic approaches to assist in diagnosis and prognosis of oral cancer

Introduction: Oral squamous cell carcinoma (OSCC) ranks among the top 10 leading causes of cancer worldwide, with 5-year survival rate of about 50%, high lymph node metastasis, and relapse rates. The OSCC diagnosis, prognosis, and treatment are mostly based on the clinical TNM classification. There is an urgent need for the discovery of biomarkers and therapeutic targets to assist in the clinical decision-making process.Areas covered: We summarize proteomic studies of the OSCC tumor, immune microenvironment, potential liquid biopsy sites, and post-translational modifications trying to retrieve information in the discovery and verification or (pre)validation phases. The search strategy was based on the combination of MeSH terms and expert refinement.Expert opinion: Untargeted combined with targeted proteomics are strategies that provide reliable and reproducible quantitation of proteins and are the methods of choice of many groups worldwide. Undoubtedly, proteomics has been contributing to the understanding of OSCC progression and uncovers potential candidates as biomarker or therapeutic targets. Nevertheless, none of these targets are available in the clinical practice yet. The scientific community needs to overcome the limitations by investing in robust experimental designs to strengthen the value of the findings, leveraging the translation of knowledge, and further supporting clinical decisions.