Salivary biomarker development using genomic, proteomic and metabolomic approaches.

The use of saliva as a diagnostic sample provides a non-invasive, cost-efficient method of sample collection for disease screening without the need for highly trained professionals. Saliva collection is far more practical and safe compared with invasive methods of sample collection, because of the infection risk from contaminated needles during, for example, blood sampling. Furthermore, the use of saliva could increase the availability of accurate diagnostics for remote and impoverished regions. However, the development of salivary diagnostics has required technical innovation to allow stabilization and detection of analytes in the complex molecular mixture that is saliva. The recent development of cost-effective room temperature analyte stabilization methods, nucleic acid pre-amplification techniques and direct saliva transcriptomic analysis have allowed accurate detection and quantification of transcripts found in saliva. Novel protein stabilization methods have also facilitated improved proteomic analyses. Although candidate biomarkers have been discovered using epigenetic, transcriptomic, proteomic and metabolomic approaches, transcriptomic analyses have so far achieved the most progress in terms of sensitivity and specificity, and progress towards clinical implementation. Here, we review recent developments in salivary diagnostics that have been accomplished using genomic, transcriptomic, proteomic and metabolomic approaches

Early detection and personalized treatment in oral cancer: the impact of omics approaches

BACKGROUND: Oral cancer is one of the most common malignant lesions of the head and neck. This cancer is an aggressive and lethal disease with no significant improvements in the overall survival in the last decades. Moreover, the incidence of oral HPV-positive tumors is rising, especially in young people. This oral neoplasm develops through numerous molecular imbalances that affect key genes and signaling pathways; however, the molecular mechanisms involved in the pathogenesis and progression of oral tumors are still to be fully determined. In order to improve the quality of life and long-term survival rate of these patients, it is vital to establish accurate biomarkers that help in the early diagnosis, prognosis and development of target treatments. Such biomarkers may possibly allow for selection of patients that will benefit from each therapy modality, helping in the optimization of intensity and sequence of the treatments in order to decrease side effects and improve survival. CONCLUSION: In this review we discuss the current knowledge of oral cancer and the potential role of omics approaches to identify molecular biomarkers in the improvement of early diagnosis, treatment and prognosis. The pursuit to improve the quality of life and decrease mortality rates of the oral patients needs to be centralized on the identification of critical genes in oral carcinogenesis. Understanding the molecular biology of oral cancer is vital for search new therapies, being the molecular-targeted therapies the most promising treatment for these patients.info:eu-repo/semantics/publishedVersio

Clinical relevance of breast cancer-related genes as potential biomarkers for oral squamous cell carcinoma

Background: Squamous cell carcinoma of the oral cavity (OSCC) is a common cancer form with relatively low 5-year survival rates, due partially to late detection and lack of complementary molecular markers as targets for treatment. Molecular profiling of head and neck cancer has revealed biological similarities with basal-like breast and lung carcinoma. Recently, we showed that 16 genes were consistently altered in invasive breast tumors displaying varying degrees of aggressiveness. Methods: To extend our findings from breast cancer to another cancer type with similar characteristics, we performed an integrative analysis of transcriptomic and proteomic data to evaluate the prognostic significance of the 16 putative breast cancer-related biomarkers in OSCC using independent microarray datasets and immunohistochemistry. Predictive models for disease-specific (DSS) and/or overall survival (OS) were calculated for each marker using Cox proportional hazards models. Results: We found that CBX2, SCUBE2, and STK32B protein expression were associated with important clinicopathological features for OSCC (peritumoral inflammatory infiltration, metastatic spread to the cervical lymph nodes, and tumor size). Consequently, SCUBE2 and STK32B are involved in the hedgehog signaling pathway which plays a pivotal role in metastasis and angiogenesis in cancer. In addition, CNTNAP2 and S100A8 protein expression were correlated with DSS and OS, respectively. Conclusions: Taken together, these candidates and the hedgehog signaling pathway may be putative targets for drug development and clinical management of OSCC patients

Cancer proteogenomics : connecting genotype to molecular phenotype

The central dogma of molecular biology describes the one-way road from DNA to RNA and finally to protein. Yet, how this flow of information encoded in DNA as genes (genotype) is regulated in order to produce the observable traits of an individual (phenotype) remains unanswered. Recent advances in high-throughput data, i.e., ‘omics’, have allowed the quantification of DNA, RNA and protein levels leading to integrative analyses that essentially probe the central dogma along all of its constituent molecules. Evidence from these analyses suggest that mRNA abundances are at best a moderate proxy for proteins which are the main functional units of cells and thus closer to the phenotype. Cancer proteogenomic studies consider the ensemble of proteins, the so-called proteome, as the readout of the functional molecular phenotype to investigate its influence by upstream events, for example DNA copy number alterations. In typical proteogenomic studies, however, the identified proteome is a simplification of its actual composition, as they methodologically disregard events such as splicing, proteolytic cleavage and post-translational modifications that generate unique protein species – proteoforms. The scope of this thesis is to study the proteome diversity in terms of: a) the complex genetic background of three tumor types, i.e. breast cancer, childhood acute lymphoblastic leukemia and lung cancer, and b) the proteoform composition, describing a computational method for detecting protein species based on their distinct quantitative profiles. In Paper I, we present a proteogenomic landscape of 45 breast cancer samples representative of the five PAM50 intrinsic subtypes. We studied the effect of copy number alterations (CNA) on mRNA and protein levels, overlaying a public dataset of drug- perturbed protein degradation. In Paper II, we describe a proteogenomic analysis of 27 B-cell precursor acute lymphoblastic leukemia clinical samples that compares high hyperdiploid versus ETV6/RUNX1-positive cases. We examined the impact of the amplified chromosomes on mRNA and protein abundance, specifically the linear trend between the amplification level and the dosage effect. Moreover, we investigated mRNA-protein quantitative discrepancies with regard to post-transcriptional and post-translational effects such as mRNA/protein stability and miRNA targeting. In Paper III, we describe a proteogenomic cohort of 141 non-small cell lung cancer clinical samples. We used clustering methods to identify six distinct proteome-based subtypes. We integrated the protein abundances in pathways using protein-protein correlation networks, bioinformatically deconvoluted the immune composition and characterized the neoantigen burden. In Paper IV, we developed a pipeline for proteoform detection from bottom-up mass- spectrometry-based proteomics. Using an in-depth proteomics dataset of 18 cancer cell lines, we identified proteoforms related to splice variant peptides supported by RNA-seq data. This thesis adds on the previous literature of proteogenomic studies by analyzing the tumor proteome and its regulation along the flow of the central dogma of molecular biology. It is anticipated that some of these findings would lead to novel insights about tumor biology and set the stage for clinical applications to improve the current cancer patient care

Lack of predictive tools for conventional and targeted cancer therapy:barriers to biomarker development and clinical translation

Predictive tools, utilising biomarkers, aim to objectively assess the potential response to a particular clinical intervention in order to direct treatment. Conventional cancer therapy remains poorly served by predictive biomarkers, despite being the mainstay of treatment for most patients. In contrast, targeted therapy benefits from a clearly defined protein target for potential biomarker assessment. We discuss potential data sources of predictive biomarkers for conventional and targeted therapy, including patient clinical data and multi-omic biomarkers (genomic, transcriptomic and protein expression). Key examples, either clinically adopted or demonstrating promise for clinical translation, are highlighted. Following this, we provide an outline of potential barriers to predictive biomarker development; broadly discussing themes of approaches to translational research and study/trial design, and the impact of cellular and molecular tumor heterogeneity. Future avenues of research are also highlighted

SITC cancer immunotherapy resource document: a compass in the land of biomarker discovery.

Since the publication of the Society for Immunotherapy of Cancer\u27s (SITC) original cancer immunotherapy biomarkers resource document, there have been remarkable breakthroughs in cancer immunotherapy, in particular the development and approval of immune checkpoint inhibitors, engineered cellular therapies, and tumor vaccines to unleash antitumor immune activity. The most notable feature of these breakthroughs is the achievement of durable clinical responses in some patients, enabling long-term survival. These durable responses have been noted in tumor types that were not previously considered immunotherapy-sensitive, suggesting that all patients with cancer may have the potential to benefit from immunotherapy. However, a persistent challenge in the field is the fact that only a minority of patients respond to immunotherapy, especially those therapies that rely on endogenous immune activation such as checkpoint inhibitors and vaccination due to the complex and heterogeneous immune escape mechanisms which can develop in each patient. Therefore, the development of robust biomarkers for each immunotherapy strategy, enabling rational patient selection and the design of precise combination therapies, is key for the continued success and improvement of immunotherapy. In this document, we summarize and update established biomarkers, guidelines, and regulatory considerations for clinical immune biomarker development, discuss well-known and novel technologies for biomarker discovery and validation, and provide tools and resources that can be used by the biomarker research community to facilitate the continued development of immuno-oncology and aid in the goal of durable responses in all patients

Immune cell phenotypes of head and neck lesions associated with viral infections

Tonsillar cancer (TC) and nasopharyngeal cancer (NPC) are associated with high-risk humanpapillomavirus (HPV) and Epstein-Barr virus (EBV), respectively. Similarly, benign lesions, knownas laryngeal papilloma (LP), are associated with low-risk HPV. Recent advances have includedimmunotherapy as a part of the treatment regimen for recurrent and metastatic HNC and LP,although with limited response rates.An in-depth understanding of the genetics of the lesions and molecular underpinnings hasidentified molecular changes that may guide patient care. In papers I-III, key immune players,including CD8+ T cells and antigen-presenting cells (APCs), were studied in NPC and TC. Usingquantitative density of CD8+ T cells in NPC, three phenotypes were defined: "inflamed", "immune-excluded", and "desert". Based on CD8+ T cells infiltratrion, the inflamed phenotype wasassociated with higher survival rates than the "immune-excluded".In paper II, digital spatial technology was used to further investigate the defined phenotypes.Higher median expression of protein markers such as CD11c and IDO1 and lower medianexpression of fibronectin in NPC stromal regions were associated with improved survival. In paperIII, we demonstrated a correlation between the levels of APCs and CD8+ T cells in HPV+ TC, andshowed that patients with high levels of CD8 transcripts had improved survivalIn papers IV-V, we investigated LP using gene expression and flow cytometry and observed aninverse relationship between CD8+ T cells and neutrophils. In addition, a streptococcus subspecieswas associated with severe clinical symptoms and high neutrophil counts in chronic LP (paper V:a case report). These findings provide a basis for further investigations of neutrophil and bacterialassociations in HPV-associated lesions.In conclusion, the cell types and biomarkers investigated in this thesis highlight the immuneheterogeneity of NPC, TC, and LP. Validations in larger patient cohorts are needed to developclinically applicable biomarkers for prognostics and patient stratification

Chromosomal Alterations and Gene Expression Changes Associated with the Progression of Leukoplakia to Advanced Gingivobuccal Cancer

We present an integrative genome-wide analysis that can be used to predict the risk of progression from leukoplakia to oral squamous cell carcinoma (OSCC) arising in the gingivobuccal complex (GBC). We find that the genomic and transcriptomic profiles of leukoplakia resemble those observed in later stages of OSCC and that several changes are associated with this progression, including amplification of 8q24.3, deletion of 8p23.2, and dysregulation of DERL3, EIF5A2, ECT2, HOXC9, HOXC13, MAL, MFAP5 and NELL2. Comparing copy number profiles of primary tumors with and without lymph-node metastasis, we identify alterations associated with metastasis, including amplifications of 3p26.3, 8q24.21, 11q22.1, 11q22.3 and deletion of 8p23.2. Integrative analysis reveals several biomarkers that have never or rarely been reported in previous OSCC studies, including amplifications of 1p36.33 (attributable to MXRA8), 3q26.31 (EIF5A2), 9p24.1 (CD274), and 12q13.2 (HOXC9 and HOXC13). Additionally, we find that amplifications of 1p36.33 and 11q22.1 are strongly correlated with poor clinical outcome. Overall, our findings delineate genomic changes that can be used in treatment management for patients with potentially malignant leukoplakia and OSCC patients with higher risk of lymph-node metastasis

Proteomic Analysis of the Unfolded Protein Response in Melanoma

Despite enormous advancements made in the last decade in the treatment of metastatic melanoma, due to drug resistance and drug toxicities, new therapies and treatment strategies are needed. Additionally, there are no prognostic biomarkers for metastatic disease able to predict outcome. Thirty-two potential biomarkers were analysed by selected reaction monitoring (SRM) in 30 stage III melanoma patients. A 14-protein panel was discovered, able to predict patients likely to have poor outcome and therefore potentially benefit from aggressive therapeutic strategies. From the above study, the Unfolded Protein Response (UPR) was revealed to be a major cellular pathway up-regulated in patients with poor outcome. The UPR is a cellular stress response, which is initiated by a build-up of unfolded protein in the endoplasmic reticulum (ER). Increased activation of the UPR is associated with several cancers however, the mechanisms used to promote tumour progression and metastases are not well understood. To characterise this stress response, the UPR was activated in melanoma cell line models. Using quantitative mass spectrometry 64 proteins were identified as differentially abundant with increased UPR activation. Among them, eight UPR-associated proteins were validated by SRM, identifying these proteins as core modulators of the UPR. An in silico analysis of the eight UPR-associated proteins in pan-cancer patient data across 16 solid tumour types revealed the eight UPR-associated proteins were markers of poor survival across cancer types. The combined data demonstrates the UPR is a major contributor to cancer progression. The study contributes to our knowledge of melanoma biology by elucidating the broad impact of the UPR on several cellular pathways and mechanisms that would promote tumour growth and increase the metastatic potential of melanoma. Furthermore, novel UPR drug targets were identified, including cooperative pathways that could be targeted in combinatorial therapie

Challenges in cancer research and multifaceted approaches for cancer biomarker quest

AbstractRecent advances in cancer biology have subsequently led to the development of new molecularly targeted anti-cancer agents that can effectively hit cancer-related proteins and pathways. Despite better insight into genomic aberrations and diversity of cancer phenotypes, it is apparent that proteomics too deserves attention in cancer research. Currently, a wide range of proteomic technologies are being used in quest for new cancer biomarkers with effective use. These, together with newer technologies such as multiplex assays could significantly contribute to the discovery and development of selective and specific cancer biomarkers with diagnostic or prognostic values for monitoring the disease state. This review attempts to illustrate recent advances in the field of cancer biomarkers and multifaceted approaches undertaken in combating cancer