The dynamic role of immune checkpoint molecules in diagnosis, prognosis, and treatment of head and neck cancers.

Head and neck cancer (HNC) is the sixth most common cancer type, accounting for approximately 277,597 deaths worldwide. Recently, the Food and Drug Administration (FDA) has approved immune checkpoint blockade (ICB) agents targeting programmed death-1 (PD-1) and programmed death-ligand 1 (PD-L1) as a treatment regimen for head and neck squamous cell carcinomas (HNSCC). Studies have reported the role of immune checkpoint inhibitors as targeted therapeutic regimens that unleash the immune response against HNSCC tumors. However, the overall response rates to immunotherapy vary between 14-32% in recurrent or metastatic HNSCC, with clinical response and treatment success being unpredictable. Keeping this perspective in mind, it is imperative to understand the role of T cells, natural killer cells, and antigen-presenting cells in modulating the immune response to immunotherapy. In lieu of this, these immune molecules could serve as prognostic and predictive biomarkers to facilitate longitudinal monitoring and understanding of treatment dynamics. These immune biomarkers could pave the path for personalized monitoring and management of HNSCC. In this review, we aim to provide updated immunological insight on the mechanism of action, expression, and the clinical application of immune cells' stimulatory and inhibitory molecules as prognostic and predictive biomarkers in HNC. The review is focused mainly on CD27 and CD137 (members of the TNF-receptor superfamily), natural killer group 2 member D (NKG2D), tumor necrosis factor receptor superfamily member 4 (TNFRSF4 or OX40), S100 proteins, PD-1, PD-L1, PD-L2, T cell immunoglobulin and mucin domain 3 (TIM-3), cytotoxic T lymphocyte-associated antigen 4 (CTLA-4), lymphocyte-activation gene 3 (LAG-3), indoleamine-pyrrole 2,3-dioxygenase (IDO), B and T lymphocyte attenuator (BTLA). It also highlights the importance of T, natural killer, and antigen-presenting cells as robust biomarker tools for understanding immune checkpoint inhibitor-based treatment dynamics. Though a comprehensive review, all aspects of the immune molecules could not be covered as they were beyond the scope of the review; Further review articles can cover other aspects to bridge the knowledge gap.

Dynamic liquid biopsy components as predictive and prognostic biomarkers in colorectal cancer.

Colorectal cancer (CRC) is one of the most common cancers worldwide. The diagnosis, prognosis and therapeutic monitoring of CRC depends largely on tissue biopsy. However, due to tumor heterogeneity and limitations such as invasiveness, high cost and limited applicability in longitudinal monitoring, liquid biopsy has gathered immense attention in CRC. Liquid biopsy has several advantages over tissue biopsy including ease of sampling, effective monitoring, and longitudinal assessment of treatment dynamics. Furthermore, the importance of liquid biopsy is signified by approval of several liquid biopsy assays by regulatory bodies indicating the powerful approach of liquid biopsy for comprehensive CRC screening, diagnostic and prognostics. Several liquid biopsy biomarkers such as novel components of the microbiome, non-coding RNAs, extracellular vesicles and circulating tumor DNA are extensively being researched for their role in CRC management. Majority of these components have shown promising results on their clinical application in CRC including early detection, observe tumor heterogeneity for treatment and response, prediction of metastases and relapse and detection of minimal residual disease. Therefore, in this review, we aim to provide updated information on various novel liquid biopsy markers such as a) oral microbiota related bacterial network b) gut microbiome-associated serum metabolites c) PIWI-interacting RNAs (piRNAs), microRNA(miRNAs), Long non-coding RNAs (lncRNAs), circular RNAs (circRNAs) and d) circulating tumor DNAs (ctDNA) and circulating tumor cells (CTC) for their role in disease diagnosis, prognosis, treatment monitoring and their applicability for personalized management of CRC.