Head and neck cancers become a severe threat to human’s health nowadays and represent the sixth most common cancer worldwide. Surgery remains the first-line choice for head and neck cancer patients. Limited resectable tissue mass and complicated anatomy structures in the head and neck region put the surgeons in a dilemma between the extensive resection and a better quality of life for the patients. Early diagnosis and treatment of the pre-malignancies, as well as real-time in vivo detection of surgical margins during en bloc resection, could be leveraged to minimize the resection of normal tissues. With the understanding of the head and neck oncology, recent advances in optical hardware and reagents have provided unique opportunities for real-time pre-malignancies and cancer imaging in the clinic or operating room. Optical imaging in the head and neck has been reported using autofluorescence imaging, targeted fluorescence imaging, high-resolution microendoscopy, narrow band imaging and the Raman spectroscopy. In this study, we reviewed the basic theories and clinical applications of optical imaging for the diagnosis and treatment in the field of head and neck oncology with the goal of identifying limitations and facilitating future advancements in the field.

Oral squamous cell carcinoma (OSCC) is becoming more common across the globe. The prognosis of OSCC is largely dependent on the early detection. But the routine oral cavity examination may delay the diagnosis because the early oral malignant lesions may be clinically indistinguishable from benign or inflammatory diseases. In this study, the new diagnostic method is developed by using the surface enhanced Raman spectroscopy (SERS) to detect the serum samples from the cancer patients. The blood serum samples were collected from the OSCC patients, MEC patients and the volunteers without OSCC or MEC. Gold nanoparticles(NPs) were then mixed in the serum samples to obtain the high quality SERS spectra. There were totally 135 spectra of OSCC, 90 spectra of mucoepidermoid carcinoma (MEC) and 145 spectra of normal control group, which were captured by SERS successfully. Compared with the normal control group, the Raman spectral differences exhibited in the spectra of OSCC and MEC groups, which were assigned to the nucleic acids, proteins and lipids. Based on these spectral differences and features, the algorithms of principal component analysis(PCA) and linear discriminant analysis (LDA) were employed to analyze and classify the Raman spectra of different groups. Compared with the normal groups, the major increased peaks in the OSCC and MEC groups were assigned to the molecular structures of the nucleic acids and proteins. And these different major peaks between the OSCC and MEC groups were assigned to the special molecular structures of the carotenoids and lipids. The PCA-LDA results demonstrated that OSCC could be discriminated successfully from the normal control groups with a sensitivity of 80.7% and a specificity of 84.1%. The process of the cross validation proved the results analyzed by PCA-LDA were reliable. The gold NPs were appropriate substances to capture the high-quality SERS spectra of the OSCC, MEC and normal serum samples. The results of this study confirm that SERS combined PCA-LDA had a giant capability to detect and diagnosis OSCC through the serum sample successfully.

Toll‐like receptors (TLRs) are inflammatory triggers and belong to a family of pattern recognition receptors (PRRs) that are central to the regulation of host protective adaptive immune responses. Activation of TLRs in innate immune myeloid cells directs lymphocytes to produce the most appropriate effector responses to eliminate infection and maintain homeostasis of the body's internal environment. Inappropriate TLR stimulation can lead to the development of general autoimmune diseases as well as chronic and acute inflammation, and even cancer. Therefore, TLRs are expected to be targets for therapeutic treatment of inflammation‐related diseases, autoimmune diseases, microbial infections, and human cancers. This review summarizes the recent discoveries in the molecular and structural biology of TLRs. The role of different TLR signaling pathways in inflammatory diseases, autoimmune diseases such as diabetes, cardiovascular diseases, respiratory diseases, digestive diseases, and even cancers (oral, gastric, breast, colorectal) is highlighted and summarizes new drugs and related clinical treatments in clinical trials, providing an overview of the potential and prospects of TLRs for the treatment of TLR‐related diseases.

Objectives: To date, radiomics has been applied in oncology for over a decade and has shown great progress. We used a bibliometric analysis to analyze the publications of radiomics in oncology to clearly illustrate the current situation and future trends and encourage more researchers to participate in radiomics research in oncology.Methods: Publications for radiomics in oncology were downloaded from the Web of Science Core Collection (WoSCC). WoSCC data were collected, and CiteSpace was used for a bibliometric analysis of countries, institutions, journals, authors, keywords, and references pertaining to this field. The state of research and areas of focus were analyzed through burst detection.Results: A total of 7,199 pieces of literature concerning radiomics in oncology were analyzed on CiteSpace. The number of publications has undergone rapid growth and continues to increase. The USA and Chinese Academy of Sciences are found to be the most prolific country and institution, respectively. In terms of journals and co-cited journals, Scientific Reports is ranked highest with respect to the number of publications, and Radiology is ranked highest among co-cited journals. Moreover, Jie Tian has published the most publications, and Phillipe Lambin is the most cited author. A paper published by Gillies et al. presents the highest citation counts. Artificial intelligence (AI), segmentation methods, and the use of radiomics for classification and diagnosis in oncology are major areas of focus in this field. Test-retest statistics, including reproducibility and statistical methods of radiomics research, the relation between genomics and radiomics, and applications of radiomics to sarcoma and intensity-modulated radiotherapy, are frontier areas of this field.Conclusion: To our knowledge, this is the first study to provide an overview of the literature related to radiomics in oncology and may inspire researchers from multiple disciplines to engage in radiomics-related research.

As the first compartment of the protein secretory pathway, the endoplasmic reticulum (ER) acts as a protein synthesis factory, maintaining proteostasis and ER homeostasis. However, a variety of intrinsic and extrinsic perturbations, such as cancer, can disrupt the homeostasis and result in a large accumulation of misfolded/unfolded proteins in the ER lumen, thereby provoking a specific cellular state addressed as “ER stress”. Then the unfolded protein response (UPR), an adaptive signaling pathway, is triggered to address the stress and restore the homeostasis. A novel aspect of ER stress is that it can be transmitted from cancer cells to tumor-infiltrating myeloid cells through certain cancer cell-released soluble factors, which is termed as transmissible ER stress (TERS) or ER stress resonance (ERSR). In this review, we provide a comprehensive overview of the link between cancer and ER stress as well as the possible soluble factors mediating TERS. We further elaborate on the cell-extrinsic effects of TERS on tumor immunity, and how it indirectly modulates cancer development and progression, which is expected to add a new dimension to anticancer therapy.