Comparative sera proteomics analysis of differentially expressed proteins in oral squamous cell carcinoma

Integrating Artificial Intelligence for Advancing Multiple-Cancer Early Detection via Serum Biomarkers: A Narrative Review

The concept and policies of multicancer early detection (MCED) have gained significant attention from governments worldwide in recent years. In the era of burgeoning artificial intelligence (AI) technology, the integration of MCED with AI has become a prevailing trend, giving rise to a plethora of MCED AI products. However, due to the heterogeneity of both the detection targets and the AI technologies, the overall diversity of MCED AI products remains considerable. The types of detection targets encompass protein biomarkers, cell-free DNA, or combinations of these biomarkers. In the development of AI models, different model training approaches are employed, including datasets of case-control studies or real-world cancer screening datasets. Various validation techniques, such as cross-validation, location-wise validation, and time-wise validation, are used. All of the factors show significant impacts on the predictive efficacy of MCED AIs. After the completion of AI model development, deploying the MCED AIs in clinical practice presents numerous challenges, including presenting the predictive reports, identifying the potential locations and types of tumors, and addressing cancer-related information, such as clinical follow-up and treatment. This study reviews several mature MCED AI products currently available in the market, detecting their composing factors from serum biomarker detection, MCED AI training/validation, and the clinical application. This review illuminates the challenges encountered by existing MCED AI products across these stages, offering insights into the continued development and obstacles within the field of MCED AI.

Risk of head and neck cancer in relation to blood inflammatory biomarkers in the Swedish AMORIS cohort

Background

Inflammation is critically involved in the development of human cancer, and blood inflammatory biomarkers have been proposed to indicate the risk of different cancer types.

Methods

Using the Swedish Apolipoprotein-Related Mortality Risk (AMORIS) Cohort (N=812,073), we first performed a time-to-event analysis to evaluate the association of the baseline level of 12 blood inflammatory biomarkers measured during 1985-1996 with the subsequent risk of head and neck cancer (HNC) identified through the nationwide Swedish Cancer Register until end of 2020. A nested case-control study was further conducted to demonstrate the longitudinal trends of the studied biomarkers during the 30-year period prior to diagnosis of HNC.

Results

In the time-to-event analysis, we identified a total of 2,510 newly diagnosed HNC cases. There was an increased risk of HNC per standard deviation (SD) increase of haptoglobin (hazard ratio [HR]: 1.25; 95% confidence interval [CI]: 1.21-1.30), leukocytes (HR: 1.22; 95%CI: 1.17-1.28), sedimentation rate (HR: 1.17; 95%CI: 1.07-1.29), and monocytes (HR: 1.34; 95%CI: 1.07-1.68) at baseline, after adjustment for age, sex, fasting status, occupational status, and country of birth. In contrast, there was a decreased risk of HNC per SD increase of lymphocytes in % (HR: 0.85; 95%CI: 0.73-0.99) and lymphocyte-to-monocyte ratio (LMR) (HR: 0.81; 95%CI: 0.69-0.95) at baseline. In the nested case-control study using repeatedly measured biomarker levels, we found that individuals with HNC had consistently higher levels of haptoglobin, leukocytes, sedimentation rate, and monocytes, as well as consistently lower levels of lymphocytes in % and LMR, during the 30-year period prior to diagnosis, compared to controls.

Conclusion

Based on a cohort of more than half a million participants with up to 35 years of follow-up, our findings provide solid evidence supporting the presence of alterations in blood inflammatory biomarkers during the decades before diagnosis of HNC.

Spatial transcriptomics reveals distinct and conserved tumor core and edge architectures that predict survival and targeted therapy response

The spatial organization of the tumor microenvironment has a profound impact on biology and therapy response. Here, we perform an integrative single-cell and spatial transcriptomic analysis on HPV-negative oral squamous cell carcinoma (OSCC) to comprehensively characterize malignant cells in tumor core (TC) and leading edge (LE) transcriptional architectures. We show that the TC and LE are characterized by unique transcriptional profiles, neighboring cellular compositions, and ligand-receptor interactions. We demonstrate that the gene expression profile associated with the LE is conserved across different cancers while the TC is tissue specific, highlighting common mechanisms underlying tumor progression and invasion. Additionally, we find our LE gene signature is associated with worse clinical outcomes while TC gene signature is associated with improved prognosis across multiple cancer types. Finally, using an in silico modeling approach, we describe spatially-regulated patterns of cell development in OSCC that are predictably associated with drug response. Our work provides pan-cancer insights into TC and LE biology and interactive spatial atlases ( http://www.pboselab.ca/spatial_OSCC/ ; http://www.pboselab.ca/dynamo_OSCC/ ) that can be foundational for developing novel targeted therapies.

Clusterin and Its Isoforms in Oral Squamous Cell Carcinoma and Their Potential as Biomarkers: A Comprehensive Review

Oral squamous cell carcinoma (OSCC) is a prevalent type of head and neck cancer, ranked as the sixth most common cancer worldwide, accounting for approximately 300,000 new cases and 145,000 deaths annually. Early detection using biomarkers significantly increases the 5-year survival rate of OSCC by up to 80-90%. Clusterin (CLU), also known as apolipoprotein J, is a sulfated chaperonic glycoprotein expressed in all tissues and human fluids and has been reported to be a potential biomarker of OSCC. CLU has been implicated as playing a vital role in many biological processes such as apoptosis, cell cycle, etc. Abnormal CLU expression has been linked with the development and progression of cancers. Despite the fact that there are many studies that have reported the involvement of CLU and its isoforms in OSCC, the exact roles of CLU and its isoforms in OSCC carcinogenesis have not been fully explored. This article aims to provide a comprehensive review of the current understanding of CLU structure and genetics and its correlation with OSCC tumorigenesis to better understand potential diagnostic and prognostic biomarker development. The relationship between CLU and chemotherapy resistance in cancer will also be discussed to explore the therapeutic application of CLU and its isoforms in OSCC.

Endocytosis of LXRs: Signaling in liver and disease

Nuclear receptors are among one of the major transcriptional factors that induces gene regulation in the nucleus. Liver X receptor (LXR) is a transcription factor which regulates essential lipid homeostasis in the body including fatty acid, cholesterol and phospholipid synthesis. Liver X receptor-retinoid X receptor (LXR-RXR) heterodimer is activated by either of the ligand binding on LXR or RXR. The promoter region of the gene which is targeted by LXR is bound to the response element of LXR. The activators bind to the heterodimer once the corepressor is dissociated. The cellular process such as endocytosis aids in intracellular trafficking and endosomal formation in transportation of molecules for essential signaling within the cell. LXR isotypes play a crucial role in maintaining lipid homeostasis by regulating the level of cholesterol. In the liver, the deficiency of LXRα can alter the normal physiological conditions depicting the symptoms of various cardiovascular and liver diseases. LXR can degrade low density lipoprotein receptors (LDLR) by the signaling of LXR-IDOL through endocytic trafficking in lipoprotein uptake. Various gene expressions associated with cholesterol level and lipid synthesis are regulated by LXR transcription factor. With its known diversified ligand binding, LXR is capable of regulating expression of various specific genes responsible for the progression of autoimmune diseases. The agonists and antagonists of LXR stand to be an important factor in transcription of the ABC family, essential for high density lipoprotein (HDL) formation. Endocytosis and signaling mechanism of the LXR family is broad and complex despite their involvement in cellular growth and proliferation. Here in this chapter, we aimed to emphasize the master regulation of LXR activation, regulators, and their implications in various metabolic activities especially in lipid homeostasis. Furthermore, we also briefed the significant role of LXR endocytosis in T cell immune regulation and a variety of human diseases including cardiovascular and neuroadaptive.

Circ_0004491 stimulates guanine nucleotide-binding protein alpha subunit to inhibit the malignant progression of oral squamous cell carcinoma by sponging miR-2278

Background/purpose

Circular RNA origin recognition complex subunit 4 (circORC4; ID: hsa_circ_0004491) have been confirmed to be a novel potential biomarker of oral squamous cell carcinoma (OSCC). This study aimed to explore the molecular mechanism of circ_0004491 in OSCC progression.

Materials and methods

Levels of circ_0004491, microRNA (miR)-2278, guanine nucleotide-binding protein alpha subunit (GNAS), Bax, Bcl-2, E-cadherin and ki-67 were detected by quantitative real-time PCR, western blotting and immunohistochemistry. The proliferation of OSCC cells was measured using colony formation assay and EdU staining. Cell apoptosis and motility were detected by flow cytometry and transwell assays respectively. Interaction between miR-2278 and circ_0004491 or GNAS was predicted by bioinformatics analysis and confirmed via luciferase reporter assay and RNA immunoprecipitation assay. Xenograft tumor model was used to analyze the role of circ_0004491 in tumor growth in vivo.

Results

Circ_0004491 was downregulated in OSCC tissues and cell lines. Circ_0004491 overexpression suppressed the proliferation, migration and invasion whereas facilitated the apoptosis of OSCC cells. Circ_0004491 acted as a molecular sponge for miR-2278, and circ_0004491 overexpression-mediated effect was partly reversed by miR-2278 mimic in OSCC cells. MiR-2278 interacted with the 3'UTR of GNAS. Circ_0004491 contributed to GNAS level by sponging miR-2278 in OSCC cells. GNAS knockdown restored miR-2278 inhibitor-mediated effect in OSCC cells. Circ_0004491 overexpression repressed xenograft tumor growth in vivo.

Conclusion

Circ_0004491 can repress OSCC progression by regulation of miR-2278/GNAS axis, providing a possible circRNA-targeted therapy for OSCC.

A systematic review of proteomic biomarkers in oral squamous cell cancer

BACKGROUND

Head and neck squamous cell cancer (HNSCC) is the most common cancer associated with chewing tobacco, in the world. As this is divided in to sites and subsites, it does not make it to top 10 cancers. The most common subsite is the oral cancer. At the time of diagnosis, more than 50% of patients with oral squamous cell cancers (OSCC) had advanced disease, indicating the lack of availability of early detection and risk assessment biomarkers. The new protein biomarker development and discovery will aid in early diagnosis and treatment which lead to targeted treatment and ultimately a good prognosis.

METHODS

This systematic review was performed as per PRISMA guidelines. All relevant studies assessing characteristics of oral cancer and proteomics were considered for analysis. Only human studies published in English were included, and abstracts, incomplete articles, and cell line or animal studies were excluded.

RESULTS

A total of 308 articles were found, of which 112 were found to be relevant after exclusion. The present review focuses on techniques of cancer proteomics and discovery of biomarkers using these techniques. The signature of protein expression may be used to predict drug response and clinical course of disease and could be used to individualize therapy with such knowledge.

CONCLUSIONS

Prospective use of these markers in the clinical setting will enable early detection, prediction of response to treatment, improvement in treatment selection, and early detection of tumor recurrence for disease monitoring. However, most of these markers for OSCC are yet to be validated.